Xenios Papademetris’ Bibliography (May 2012) (1-105)

 

1.            Papademetris X and Belhumeur PN. Estimation of motion boundary location and optical flow using dynamic programming. Image Processing, 1996 Proceedings, International Conference on. 1996;1:509-12 vol.1.

Abstract: We present a new method for the estimation of optical flow which uses a dynamic programming based algorithm to simultaneously detect the presence of motion boundaries and to estimate optical flow. This allows for a more accurate estimation of the motion field near discontinuities. The results compare favorably with those produced by other methods

doi:10.1109/icip.1996.559545 (http://dx.crossref.org/10.1109/icip.1996.559545)

 

2.            Papademetris X, Shi P, Dione D, Sinusas A, Constable RT and Duncan J. Recovery of Soft Tissue Object Deformation from 3D Image Sequences Using Biomechanical Models. Information Processing in Medical Imaging. 1999;1613:352-7.

Abstract: The estimation of soft tissue deformation from 3D image sequences is an important problem in a number of fields such as diagnosis of heart disease and image guided surgery. In this paper we describe a methodology for using biomechanical material models, within a Bayesian framework which allows for proper modeling of image noise, in order to estimate these deformations. The resulting partial differential equations are discretized and solved using the finite element method. We demonstrate the application of this method to estimating strains from sequences of in-vivo left ventricular MR images, where we incorporate information about the fibrous structure of the ventricle. The deformation estimates obtained exhibit similar patterns with measurements obtained from more invasive techniques, used as a gold standard.

doi:10.1007/3-540-48714-x_28 (http://dx.crossref.org/10.1007/3-540-48714-x_28)

 

3.            Papademetris X, Sinusas A, Dione D and Duncan J. 3D Cardiac Deformation from Ultrasound Images. Medical Image Computing and Computer-Assisted Intervention – MICCAI’99. 1999;1679:420-9.

Abstract: The quantitative estimation of regional cardiac deformation from 3D image sequences has important clinical implications for the assessment of viability in the heart wall. Such estimates have so far been obtained almost exclusively from Magnetic Resonance (MR) images, specifically MR tagging. In this paper we describe a methodology for estimating cardiac deformations from 3D ultrasound images. The images are segmented interactively and then initial correspondence is established using a shape-tracking approach. A dense motion field is then estimated using an anisotropic linear elastic model, which accounts for the fiber directions in the left-ventricle. The dense motion field is in turn used to calculate the deformation of the heart wall in terms of strain in cardiac specific directions. The strains obtained using this approach in open-chest dogs before and after coronary occlusion related to changes in blood flow, show good agreement with previously published results in the literature. This proposed method provides quantitative regional 3D estimates of heart deformation from ultrasound images.

doi:10.1007/10704282_46 (http://dx.crossref.org/10.1007/10704282_46)

 

4.            Papademetris X, Sinusas A, Dione D, Constable RT and Duncan J. Estimating 3D Strain from 4D Cine-MRI and Echocardiography: In-Vivo Validation. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2000. 2000;1935:CH394-CH.

Abstract: The quantitative estimation of regional cardiac deformation from 3D image sequences has important clinical implications for the assessment of myocardial viability. The validation of such image-derived estimates, however, is a non-trivial problem as it is very difficult to obtain ground truth. In this work we present an approach to validating strain estimates derived from 3D cine-Magnetic Resonance (MR) and 3D Echocardiography (3DE) images using our previously-developed shape-based tracking algorithm. The images are segmented interactively and then initial correspondence is established using a shape-tracking approach. A dense motion field is then estimated using a transversely linear elastic model, which accounts for the fiber directions in the left ventricle. The dense motion field is in turn used to calculate the deformation of the heart wall in terms of strains. The strains obtained using our algorithm are compared to strains estimated using implanted markers and sonomicrometers, which are used as the gold standards. These preliminary studies show encouraging results.

doi:10.1007/978-3-540-40899-4_70 (http://dx.crossref.org/10.1007/978-3-540-40899-4_70)

 

5.            Papademetris X, Constable R, Onat E, Duncan J, Sinusas A and Dione D. The Active Elastic Model. Information Processing in Medical Imaging. 2001;2082:36-49.

Abstract: Continuum mechanical models have been used to regularize ill-posed problems in many applications in medical imaging analysis such as image registration and left ventricular motion estimation. In this work, we present a significant extension to the common elastic model which we call the active elastic model . The active elastic model is designed to reduce bias in deformation estimation and to allow the imposition of proper priors on deformation estimation problems that contain information regarding both the expected magnitude and the expected variability of the deformation to be estimated. We test this model on the problem of left ventricular deformation estimation, and present ideas for its application in image registration and brain deformation during neurosurgery.

doi:10.1007/3-540-45729-1_4 (http://dx.crossref.org/10.1007/3-540-45729-1_4)

 

6.            Papademetris X, Sinusas AJ, Dione DP and Duncan JS. Estimation of 3D left ventricular deformation from echocardiography. Med Image Anal. 2001;5(1):17-28. Epub 2001/03/07. PMID: 11231174.

Abstract: The quantitative estimation of regional cardiac deformation from 3D image sequences has important clinical implications for the assessment of viability in the heart wall. Such estimates have so far been obtained almost exclusively from Magnetic Resonance (MR) images, specifically MR tagging. In this paper we describe a methodology for estimating cardiac deformations from 3D echocardiography (3DE). The images are segmented interactively and then initial correspondence is established using a shape-tracking approach. A dense motion field is then estimated using a transversely isotropic linear elastic model, which accounts for the fiber directions in the left ventricle. The dense motion field is in turn used to calculate the deformation of the heart wall in terms of strain in cardiac specific directions. The strains obtained using this approach in open-chest dogs before and after coronary occlusion, show good agreement with previously published results in the literature. They also exhibit a high correlation with strains produced in the same animals using implanted sonomicrometers. This proposed method provides quantitative regional 3D estimates of heart deformation from ultrasound images.

doi:doi:10.1016/S1361-8415(00)00022-0 (http://dx.crossref.org/doi:10.1016/S1361-8415(00)00022-0)

 

7.            Sinusas AJ, Papademetris X, Constable RT, Dione DP, Slade MD, Shi P and Duncan JS. Quantification of 3-D regional myocardial deformation: shape-based analysis of magnetic resonance images. American journal of physiology Heart and circulatory physiology. 2001;281(2):H698-714. Epub 2001/07/17. PMID: 11454574.

Abstract: A comprehensive three-dimensional (3-D) shape-based approach for quantification of regional myocardial deformations was evaluated in a canine model (n = 8 dogs) with the use of cine magnetic resonance imaging. The shape of the endocardial and epicardial surfaces was used to track the 3-D trajectories of a dense field of points over the cardiac cycle. The shape-based surface displacements are integrated with a continuum biomechanics model incorporating myofiber architecture to estimate both cardiac- and fiber-specific endocardial and epicardial strains and shears for 24 left ventricular regions. Whereas radial and circumferential end-systolic strains were fairly uniform, there was a significant apex-to-base gradient in longitudinal strain and radial-longitudinal shear. We also observed transmural epicardial-to-endocardial gradients in both cardiac- and fiber-specific strains. The increase in endocardial strain was accompanied by increases in radial-longitudinal shear and radial-fiber shears in the endocardium, supporting previous theories of regional myocardial deformation that predict considerable sliding between myocardial fibers.

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8.            Papademetris X, Sinusas AJ, Dione DP, Constable RT and Duncan JS. Estimation of 3-D left ventricular deformation from medical images using biomechanical models. IEEE transactions on medical imaging. 2002;21(7):786-800. Epub 2002/10/11. PMID: 12374316.

Abstract: The quantitative estimation of regional cardiac deformation from three-dimensional (3-D) image sequences has important clinical implications for the assessment of viability in the heart wall. We present here a generic methodology for estimating soft tissue deformation which integrates image-derived information with biomechanical models, and apply it to the problem of cardiac deformation estimation. The method is image modality independent. The images are segmented interactively and then initial correspondence is established using a shape-tracking approach. A dense motion field is then estimated using a transversely isotropic, linear-elastic model, which accounts for the muscle fiber directions in the left ventricle. The dense motion field is in turn used to calculate the deformation of the heart wall in terms of strain in cardiac specific directions. The strains obtained using this approach in open-chest dogs before and after coronary occlusion, exhibit a high correlation with strains produced in the same animals using implanted markers. Further, they show good agreement with previously published results in the literature. This proposed method provides quantitative regional 3-D estimates of heart deformation.

doi:10.1109/TMI.2002.801163 (http://dx.crossref.org/10.1109/TMI.2002.801163)

 

9.            Kobashi K, Papademetris X and Duncan J. A New Biomechanical Model Based Approach on Brain Shift Compensation. Medical Image Computing and Computer-Assisted Intervention. 2003;2878:59-66.

Abstract: We propose a new algorithm for biomechanical model-based brain shift compensation in image guided neurosurgery. It can be used to update preoperative images with intraoperatively acquired information. We derive a model equation with regard to external forces acting on the brain surface during neurosurgery which can be consistently integrated with intraopearatively acquired information, assuming that these forces induce a linear biomechanical response. We treat external forces on the brain boundaries as unknown variables and then estimate them within a framework of inverse finite element analysis. By incorporating additional constraints from prior knowledge, we can solve the derived equations to obtain reasonable estimation results on boundary forces and the entire displacement field. This algorithm is especially beneficial in reducing navigation error of deeper brain structures by updating preoperative images using only exposed surface displacement. In this paper, we describe the derivation of the equations and present examples of two dimensional synthetic data, where the estimated displacement errors are reduced by fifty percent, compared to the standard approach.

doi:10.1007/978-3-540-39899-8_8 (http://dx.crossref.org/10.1007/978-3-540-39899-8_8)

 

10.          Lin N, Papademetris X, Sinusas A and Duncan J. Analysis of Left Ventricular Motion Using a General Robust Point Matching Algorithm. Medical Image Computing and Computer-Assisted Intervention - MICCAI 2003. 2003;2878:556-63.

Abstract: In this paper we present a novel and fully automated approach for the estimation of non-rigid cardiac motion and deformation from sequences of three dimensional medical images. Our approach extends the robust point matching (RPM) algorithm to include shape-based information as inspired by our own previous work in this area. The resulting algorithm labeled as generalized robust point matching (G-RPM) is capable of accurately estimating left ventricular motion without the need of a prior, and often time-consuming, segmentation of the myocardium. We evaluate our approach on both synthetic data as well as using sequences of in-vivo cardiac magnetic resonance images. The approach can easily be adjusted for a number of applications to find the optimal non-rigid transformation.

doi:10.1007/978-3-540-39899-8_69 (http://dx.crossref.org/10.1007/978-3-540-39899-8_69)

 

11.          Papademetris X, Jackowski A, Schultz R, Staib L and Duncan J. Computing 3D Non-rigid Brain Registration Using Extended Robust Point Matching for Composite Multisubject fMRI Analysis. Medical Image Computing and Computer-Assisted Intervention - MICCAI 2003. 2003;2879:788-95.

Abstract: In this paper we present extensions to the Robust Point Matching framework to improve its ability to handle larger point sets with greater computational efficiency. While in the past this methodology has only been used to register either two-dimensional or small synthetic three-dimensional data-sets we demonstrate its first successful application on large real 3D data-sets. We apply this methodology to the problem of forming composite activation maps from functional magnetic resonance images. In particular we demonstrate the superior performance of this algorithm to a pure intensity-based registration in the specific area of the fusiform gyrus. We also demonstrate that the robustness of this method can be useful in the case where part of the brain is missing as a result of incorrect image slice specification.

doi:10.1007/978-3-540-39903-2_96 (http://dx.crossref.org/10.1007/978-3-540-39903-2_96)

 

12.          Duncan JS, Papademetris X, Yang J, Jackowski M, Zeng X and Staib LH. Geometric strategies for neuroanatomic analysis from MRI. NeuroImage. 2004;23 Suppl 1:S34-45. Epub 2004/10/27. PMID: 15501099; PMCID: PMC2832750

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2832750.

Abstract: In this paper, we describe ongoing work in the Image Processing and Analysis Group (IPAG) at Yale University specifically aimed at the analysis of structural information as represented within magnetic resonance images (MRI) of the human brain. Specifically, we will describe our applied mathematical approaches to the segmentation of cortical and subcortical structure, the analysis of white matter fiber tracks using diffusion tensor imaging (DTI), and the intersubject registration of neuroanatomical (aMRI) data sets. Many of our methods rally around the use of geometric constraints, statistical (MAP) estimation, and the use of level set evolution strategies. The analysis of gray matter structure and connecting white matter paths combined with the ability to bring all information into a common space via intersubject registration should provide us with a rich set of data to investigate structure and variation in the human brain in neuropsychiatric disorders, as well as provide a basis for current work in the development of integrated brain function-structure analysis.

doi:10.1016/j.neuroimage.2004.07.027 (http://dx.crossref.org/10.1016/j.neuroimage.2004.07.027)

 

13.          Okuda H, Shkarin P, Behar K, Duncan J and Papademetris X. Construction of a 3D Volumetric Probabilistic Model of the Mouse Kidney from MRI. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2004. 2004;3217:1052-4.

Abstract: We present the results of constructing a probabilistic volumetric model of 3D MR kidney images. The ultimate goal of this work is the mouse kidney segmentation based on a probabilistic volumetric model. The kidneys were aligned into the base shape using an extended robust point matching algorithm. The registration step consists of the global linear transformation and the local B-spline based free form deformation. Shape modeling is performed with globally aligned shape and template volumetric image is generated with locally aligned images. We are currently working on developing a segmentation algorithm using our model.

doi:10.1007/978-3-540-30136-3_134 (http://dx.crossref.org/10.1007/978-3-540-30136-3_134)

 

14.          Papademetris X, Jackowski AP, Schultz RT, Staib LH and Duncan JS. Integrated Intensity and Point-Feature Nonrigid Registration. Medical image computing and computer-assisted intervention : MICCAI  International Conference on Medical Image Computing and Computer-Assisted Intervention. 2004;3216(2004):763-70. Epub 2001/09/02. PMID: 20473359; PMCID: PMC2869095

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2869095.

Abstract: In this work, we present a method for the integration of feature and intensity information for non rigid registration. Our method is based on a free-form deformation model, and uses a normalized mutual information intensity similarity metric to match intensities and the robust point matching framework to estimate feature (point) correspondences. The intensity and feature components of the registration are posed in a single energy functional with associated weights. We compare our method to both point-based and intensity-based registrations. In particular, we evaluate registration accuracy as measured by point landmark distances and image intensity similarity on a set of seventeen normal subjects. These results suggest that the integration of intensity and point-based registration is highly effective in yielding more accurate registrations.

doi: 10.1007/978-3-540-30135-6_93 (http://dx.crossref.org/ 10.1007/978-3-540-30135-6_93)

 

15.          Yang J, Papademetris X, Staib LH, Schultz RT and Duncan JS. Functional Brain Image Analysis Using Joint Function-Structure Priors. Medical image computing and computer-assisted intervention : MICCAI  International Conference on Medical Image Computing and Computer-Assisted Intervention. 2004;3217:736-44. Epub 2004/01/01. PMID: 20543899; PMCID: PMC2883266

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2883266.

Abstract: We propose a new method for context-driven analysis of functional magnetic resonance images (fMRI) that incorporates spatial relationships between functional parameter clusters and anatomical structure directly for the first time. We design a parametric scheme that relates functional and structural spatially-compact regions in a single unified manner. Our method is motivated by the fact that the fMRI and anatomical MRI (aMRI) have consistent relations that provide configurations and context that aid in fMRI analysis. We develop a statistical decision-making strategy to estimate new fMRI parameter images (based on a General Linear Model-GLM) and spatially-clustered zones within these images. The analysis is based on the time-series data and contextual information related to appropriate spatial grouping of parameters in the functional data and the relationship of this grouping to relevant gray matter structure from the anatomical data. We introduce a representation for the joint prior of the functional and structural information, and define a joint probability distribution over the variations of functional clusters and the related structure contained in a set of training images. We estimate the Maximum A Posteriori (MAP) functional parameters, formulating the function-structure model in terms of level set functions. Results from 3D fMRI and aMRI show that this context-driven analysis potentially extracts more meaningful information than the standard GLM approach.

doi:10.1007/978-3-540-30136-3_90 (http://dx.crossref.org/10.1007/978-3-540-30136-3_90)

 

16.          Blumberg HP, Fredericks C, Wang F, Kalmar JH, Spencer L, Papademetris X, Pittman B, Martin A, Peterson BS, Fulbright RK and Krystal JH. Preliminary evidence for persistent abnormalities in amygdala volumes in adolescents and young adults with bipolar disorder. Bipolar disorders. 2005;7(6):570-6. Epub 2006/01/13. PMID: 16403182; PMCID: PMC2291299

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2291299.

Abstract: OBJECTIVES: Abnormalities in volumes of the amygdala have been reported previously in adolescents and adults with bipolar disorder (BD). Several studies have reported reduced volumes in adolescents with BD; however, both decreases and increases in volumes have been reported in adults with BD. Understanding of potential developmental contributions to these disturbances in morphology of the amygdala has been limited by the absence of longitudinal data in persons with BD. Here we use a within-subject longitudinal design to investigate whether amygdala volume abnormalities persist in adolescents and young adults with BD over a time interval of approximately 2 years. METHODS: Participants included 18 adolescents and young adults: 10 participants with BD I and 8 healthy comparison participants. Amygdala volumes were measured on high-resolution magnetic resonance imaging scans acquired twice for each subject over intervals of approximately 2 years. Amygdala volumes were the dependent measures in a mixed-model statistical analysis to compare amygdala volumes between groups over time while covarying for total brain volume. RESULTS: Amygdala volumes were significantly smaller in adolescents and young adults with BD compared with healthy participants (p = 0.018). The effect of time was not significant. CONCLUSIONS: Although the sample size is modest, this study provides preliminary evidence to support the presence of decreased amygdala volumes in adolescents and young adults with BD that persist during this developmental epoch.

doi:10.1111/j.1399-5618.2005.00264.x (http://dx.crossref.org/10.1111/j.1399-5618.2005.00264.x)

 

17.          Jackowski M, Papademetris X, Dobrucki LW, Sinusas AJ and Staib LH. Characterizing vascular connectivity from microCT images. Medical image computing and computer-assisted intervention : MICCAI  International Conference on Medical Image Computing and Computer-Assisted Intervention. 2005;8(Pt 2):701-8. Epub 2006/05/12. PMID: 16686021.

Abstract: X-ray microCT (computed tomography) has become a valuable tool in the analysis of vascular architecture in small animals. Because of its high resolution, a detailed assessment of blood vessel physiology and pathology is possible. Vascular measurement from noninvasive imaging is important for the study and quantification of vessel disease and can aid in diagnosis, as well as measure disease progression and response to therapy. The analysis of tracked vessel trajectories enables the derivation of vessel connectivity information, lengths between vessel junctions as well as level of ramification, contributing to a quantitative analysis of vessel architecture. In this paper, we introduce a new vessel tracking methodology based on wave propagation in oriented domains. Vessel orientation and vessel likelihood are estimated based on an eigenanalysis of gray-level Hessian matrices computed at multiple scales. An anisotropic wavefront then propagates through this vector field with a speed modulated by the maximum vesselness response at each location. Putative vessel trajectories can be found by tracing the characteristics of the propagation solution between different points. We present preliminary results from both synthetic and mouse microCT image data.

doi:10.1007/11566489_86 (http://dx.crossref.org/10.1007/11566489_86)

 

18.          Papademetris X, Dione DP, Dobrucki LW, Staib LH and Sinusas AJ. Articulated rigid registration for serial lower-limb mouse imaging. Medical image computing and computer-assisted intervention : MICCAI  International Conference on Medical Image Computing and Computer-Assisted Intervention. 2005;8(Pt 2):919-26. Epub 2006/05/12. PMID: 16686048.

Abstract: This paper describes a new piecewise rotational transformation model for capturing the articulation of joints such as the hip and the knee. While a simple piecewise rigid model can be applied, such models suffer from discontinuities at the motion boundary leading to both folding and stretching. Our model avoids both of these problems by constructing a provably continuous transformation along the motion interface. We embed this transformation model within the robust point matching framework and demonstrate its successful application to both synthetic data, and to serial x-ray CT mouse images. In the later case, our model captures the articulation of six joints, namely the left/right hip, the left/right knee and the left/right ankle. In the future such a model could be used to initialize non-rigid registrations of images from different subjects, as well as, be embedded in intensity-based and integrated registration algorithms. It could also be applied to human data in cases where articulated motion is an issue (e.g. image guided prostate radiotherapy, lower extremity CT angiography).

doi:10.1007/11566489_11 (http://dx.crossref.org/10.1007/11566489_11)

 

19.          Papademetris X, Shkarin P, Staib LH and Behar KL. Regional whole body fat quantification in mice. Information processing in medical imaging : proceedings of the  conference. 2005;19:369-80. Epub 2007/03/16. PMID: 17354710.

Abstract: Obesity has risen to epidemic levels in the United States and around the world. Global indices of obesity such as the body mass index (BMI) have been known to be inaccurate predictors of risk of diabetes, and it is commonly recognized that the distribution of fat in the body is a key measure. In this work, we describe the early development of image analysis methods to quantify regional body fat distribution in groups of both male and female wildtype mice using magnetic resonance images. In particular, we present a new formulation which extends the expectation-maximization formalism commonly applied in brain segmentation to multi-exponential data and applies it to the problem of regional whole body fat quantification. Previous segmentation approaches for multispectral data typically perform the classification on fitted parameters, such as the density and the relaxation times. In contrast, our method directly computes a likelihood term from the raw data and hence explicitly accounts for errors in the fitting process, while still using the fitted parameters to model the variation in the appearance of each tissue class. Early validation results, using magnetic resonance spectroscopic imaging as a gold standard, are encouraging. We also present results demonstrating differences in fat distribution between male and female mice.

doi:10.1007/11505730_31 (http://dx.crossref.org/10.1007/11505730_31)

 

20.          Wang J, Qiu M, Papademetris X and Constable RT. Brain tissue segmentation based on corrected gray-scale analysis. Conference proceedings :  Annual International Conference of the IEEE Engineering in Medicine and Biology Society IEEE Engineering in Medicine and Biology Society Conference. 2005;3:3027-30. Epub 2007/02/07. PMID: 17282881.

Abstract: Image signal-to-noise ratio (SNR) and signal intensity (SI) inhomogeneities are factors that strongly affect the accuracy and precision of brain tissue segmentations in magnetic resonance image (MRI). In this work, SNR and contrast of brain images are optimized by TR and inversion recovery time TI in multi-spectrum MRI data sets. SI inhomogeneities are measured in vivo using a recently developed method allowing improved correction. The three-Gaussain distribution model is used to fit histograms of the images to find the initialization parameters for an Expectation-Maximization (EM) segmentation algorithm. Compared with other methods, the field map method provides better correction of SI inhomogeneities and excellent segmentation results.

doi:10.1109/IEMBS.2005.1617112 (http://dx.crossref.org/10.1109/IEMBS.2005.1617112)

 

21.          Weiss R, Taksali SE, Dufour S, Yeckel CW, Papademetris X, Cline G, Tamborlane WV, Dziura J, Shulman GI and Caprio S. The "obese insulin-sensitive" adolescent: importance of adiponectin and lipid partitioning. The Journal of clinical endocrinology and metabolism. 2005;90(6):3731-7. Epub 2005/03/31. PMID: 15797955.

Abstract: There is a wide interindividual variation in peripheral insulin sensitivity at any given body mass index or percent body fat among obese adolescents with normal glucose tolerance. The goals of this study were to determine whether variability in insulin sensitivity is associated with differences in patterns of lipid partitioning or substrate use under fasting and hyperinsulinemic conditions. We compared 14 obese insulin-resistant adolescents with 14 obese insulin-sensitive controls, pair matched for age, gender, pubertal stage and body composition. Insulin sensitivity was assessed by the hyperinsulinemic-euglycemic clamp, intramyocellular lipid content by (1)H-nuclear magnetic resonance and visceral fat by magnetic resonance imaging. Obese insulin-sensitive subjects had lower intramyocellular (1.64 +/- 0.68 vs.2.26 +/- 0.62% of water peak, P = 0.017) and visceral lipid deposition (45 +/- 23 vs. 77 +/- 52 cm(2), P = 0.04) and a higher level of adiponectin, compared with their obese-resistant counterparts (8.8 +/- 3.6 vs. 6.5 +/- 1.8 mug/dl, P = 0.015). Glycerol fluxes were similar between the two obese groups yet occurred in the face of different concentrations of insulin. Intramyocellular lipid and visceral fat were negatively related to insulin sensitivity. Obese insulin-sensitive adolescents are characterized by lower lipid deposition in the intramyocellular and visceral compartments and greater levels of adiponectin, despite similar degree of adiposity.

doi:10.1210/jc.2004-2305 (http://dx.crossref.org/10.1210/jc.2004-2305)

 

22.          Burgert TS, Taksali SE, Dziura J, Goodman TR, Yeckel CW, Papademetris X, Constable RT, Weiss R, Tamborlane WV, Savoye M, Seyal AA and Caprio S. Alanine aminotransferase levels and fatty liver in childhood obesity: associations with insulin resistance, adiponectin, and visceral fat. The Journal of clinical endocrinology and metabolism. 2006;91(11):4287-94. Epub 2006/08/17. PMID: 16912127.

Abstract: BACKGROUND: Concurrent with the rise in obesity, nonalcoholic fatty liver disease is recognized as the leading cause of serum aminotransferase elevations in obese youth. Nevertheless, the complete metabolic phenotype associated with abnormalities in biomarkers of liver injury and intrahepatic fat accumulation remains to be established. METHODS: In a multiethnic cohort of 392 obese adolescents, alanine aminotransferase (ALT) levels were related with parameters of insulin sensitivity, glucose, and lipid metabolism as well as adipocytokines and biomarkers of inflammation. A subset of 72 adolescents had determination of abdominal fat partitioning and intrahepatic fat accumulation using magnetic resonance imaging. FINDINGS: Elevated ALT (> 35 U/liter) was found in 14% of adolescents, with a predominance of male gender and white/Hispanic race/ethnicity. After adjusting for potential confounders, rising ALT was associated with reduced insulin sensitivity and glucose tolerance as well as rising free fatty acids and triglycerides. Worsening of glucose and lipid metabolism was already evident as ALT levels rose into the upper half of the normal range (18-35 U/liter). When hepatic fat fraction was assessed using fast magnetic resonance imaging, 32% of subjects had an increased hepatic fat fraction, which was associated with decreased insulin sensitivity and adiponectin, and increased triglycerides, visceral fat, and deep to superficial sc fat ratio. The prevalence of the metabolic syndrome was significantly greater in those with fatty liver. INTERPRETATION: Deterioration in glucose and lipid metabolism is associated even with modest ALT elevations. Hepatic fat accumulation in childhood obesity is strongly associated with the triad of insulin resistance, increased visceral fat, and hypoadiponectinemia. Hence, hepatic steatosis may be a core feature of the metabolic syndrome.

doi:10.1210/jc.2006-1010 (http://dx.crossref.org/10.1210/jc.2006-1010)

 

23.          DeLorenzo C, Papademetris X, Vives KP, Spencer D and Duncan JS. Combined feature/intensity-based brain shift compensation using stereo guidance. Biomedical Imaging: Nano to Macro, 2006 3rd IEEE International Symposium on. 2006:335-8.

Abstract: During neurosurgery, soft tissue deformation produces non-rigid brain motion. Biomechanical models are often used in conjunction with image-derived information to infer volumetric brain displacements and compensate for this deformation. Proper use of these compensation systems depends on incorporating appropriate model parameters, balancing the model/data tradeoff and, importantly, on the accuracy of the image-derived information used with the model. The goal of this work is to improve cortical surface tracking accuracy using intraoperative stereo camera images. We use image-derived cortical surface displacement to drive our model. This method takes advantage of both stereo image intensities and segmented cortical features to detect surface motion within a Bayesian framework. To quantify accuracy, the algorithm is tested on both simulated and real surfaces

doi:10.1109/isbi.2006.1624921 (http://dx.crossref.org/10.1109/isbi.2006.1624921)

 

24.          DeLorenzo C, Papademetris X, Wu K, Vives KP, Spencer D and Duncan JS. Nonrigid 3D brain registration using intensity/feature information. Medical image computing and computer-assisted intervention : MICCAI  International Conference on Medical Image Computing and Computer-Assisted Intervention. 2006;9(Pt 1):932-9. Epub 2007/03/16. PMID: 17354980; PMCID: PMC2864121

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2864121.

Abstract: The brain deforms non-rigidly during neurosurgery, preventing preoperatively acquired images from accurately depicting the intraoperative brain. If the deformed brain surface can be detected, biomechanical models can be applied to calculate the resulting volumetric deformation. The reliability of this volumetric calculation is dependent on the accuracy of the surface detection. This work presents a surface tracking algorithm which relies on Bayesian analysis to track cortical surface movement. The inputs to the model are 3D preoperative brain images and intraoperative stereo camera images. The addition of a camera calibration optimization term creates a more robust model, capable of tracking the cortical surface in the presence of camera calibration error.

doi:10.1007/11866565_114 (http://dx.crossref.org/10.1007/11866565_114)

 

25.          Koch KM, Papademetris X, Rothman DL and de Graaf RA. Rapid calculations of susceptibility-induced magnetostatic field perturbations for in vivo magnetic resonance. Physics in medicine and biology. 2006;51(24):6381-402. Epub 2006/12/07. PMID: 17148824.

Abstract: Static magnetic field perturbations generated by variations of magnetic susceptibility within samples reduce the quality and integrity of magnetic resonance measurements. These perturbations are difficult to predict in vivo where wide variations of internal magnetic susceptibility distributions are common. Recent developments have provided rapid computational means of estimating static field inhomogeneity within the small susceptibility limits of materials typically studied using magnetic resonance. Such a predictive mechanism could be a valuable tool for sequence simulation, field shimming and post-acquisition image correction. Here, we explore this calculation protocol and demonstrate its predictive power in estimating in vivo inhomogeneity within the human brain. Furthermore, we quantitatively explore the predictive limits of the computation. For in vivo comparison, a method of magnetic susceptibility registration using MRI and CT data is presented and utilized to carry out subject-specific inhomogeneity estimation. Using this algorithm, direct comparisons in human brain and phantoms are made between field map acquisitions and calculated inhomogeneity. Distortion correction in echo-planar images due to static field inhomogeneity is also demonstrated using the computed field maps.

doi:10.1088/0031-9155/51/24/007 (http://dx.crossref.org/10.1088/0031-9155/51/24/007)

 

26.          Papademetris X, Vives KP, DiStasio M, Staib LH, Neff M, Flossman S, Frielinghaus N, Zaveri H, Novotny EJ, Blumenfeld H, Constable RT, Hetherington HP, Duckrow RB, Spencer SS, Spencer DD and Duncan JS. Development of a research interface for image guided intervention: initial application to epilepsy neurosurgery. Biomedical Imaging: Nano to Macro, 2006 3rd IEEE International Symposium on. 2006:490-3.

Abstract: This paper describes the development and application of methods to integrate research image analysis methods and software with a commercial image guided surgery navigation system (the BrainLAB VectorVision Cranial System.) The integration was achieved using a custom designed client/server architecture termed VectorVision Link (VV Link) which extends functionality from the Visualization Toolkit. VV Link enables bi-directional data transfer such as image data sets, visualizations and tool positions in real time. The system was tested in both laboratory experiments and in real epilepsy neurosurgeries with highly promising results

doi:10.1109/isbi.2006.1624960 (http://dx.crossref.org/10.1109/isbi.2006.1624960)

 

27.          Scharff E, Papademetris X, Hetherington HP, Pan JW, Zaveri H, Blumenfeld H, Duckrow RB, Spencer SS, Spencer DD, Duncan JS and Novotny EJ. Correlation of magnetic resonance spectroscopic imaging and intracranial EEG localization of seizures. 7. Biomedical Imaging: Nano to Macro, 2006 3rd IEEE International Symposium on. 2006:510-3.

Abstract: Two and a half million people in US have epilepsy 600,000 individuals have medically intractable epilepsy. Epilepsy surgery offers an alternative treatment and a potential cure. In certain patients, particularly subjects with normal anatomical MRI, evaluation often includes intracranial electrode recording. Continuous monitoring of electrical signals directly from the brain for periods of 1 to 14 days are performed to record actual seizures that provide more precise localization of seizures. Magnetic resonance spectroscopic imaging (MRSI) offers the potential to localize such regions non-invasively. In this study we present results from a comparison of such abnormal region identification for ten patients from both intracranial electrodes and MRSI. The analysis employed both rigid and non-rigid registration methods, as well as localization of intracranial electrodes from CT images. We found that IcEEG and MRSI localization methods were concordant in all ten subjects

doi:10.1109/isbi.2006.1624965 (http://dx.crossref.org/10.1109/isbi.2006.1624965)

 

28.          Scouten A, Papademetris X and Constable RT. Spatial resolution, signal-to-noise ratio, and smoothing in multi-subject functional MRI studies. NeuroImage. 2006;30(3):787-93. Epub 2005/12/14. PMID: 16343951.

Abstract: Functional MRI is aimed at localizing cortical activity to understand the role of specific cortical regions, providing insight into the neurophysiological underpinnings of brain function. Scientists developing fMRI methodology seek to improve detection of subtle activations and to spatially localize these activations more precisely. Except for applications in the clinical environment, such as functional mapping in patients prior to neurosurgical intervention, most basic neuroscience studies involve group level random-effects analyses. Prior to grouping data, the data from each individual are typically smoothed. A wide range of motivations for smoothing have been given including to match the spatial scale of hemodynamic responses, to normalize the error distribution (by the Central Limit Theorem) to improve the validity of inferences based on parametric tests, and, in the context of inter-subject averaging smoothing has been shown necessary to project the data down to a scale where homologies in functional anatomy are expressed across subjects. This work demonstrates that, for single-subject studies, if smoothing is to be employed, the data should be acquired at lower resolutions to maximize SNR. The benefits of a low-resolution acquisition are limited by partial volume effects and by the weak impact of resolution-dependent noise on the overall group level statistics. Given that inter-subject noise dominates across a range of tasks, improvements in within-subject noise, through changes in acquisition strategy or even moving to higher field strength, may do little to improve group statistics. Such improvements however may greatly impact single-subject studies such as those used in neurosurgical planning.

doi:10.1016/j.neuroimage.2005.10.022 (http://dx.crossref.org/10.1016/j.neuroimage.2005.10.022)

 

29.          Staib LH, Jackowski M and Papademetris X. Brain shape characterization from deformation. Biomedical Imaging: Nano to Macro, 2006 3rd IEEE International Symposium on. 2006:1140-3.

Abstract: The characterization of shape in the brain is of great importance for understanding differences in structure and the relationship to function. Structural differences have been associated with, for example, age, sex, handedness, cognitive abilities and many neurologic and psychiatric conditions. Nonrigid registration methods enable the characterization of shape differences between images based on the transformation that relates them. Unlike methods which characterize shape in terms of geometric features computed from individual structures, transformation-based deformation description characterizes the entire space and therefore may better reflect the interrelationships between structures, as well as changes within and near structure. The transformation, as characterized by the local Jacobian, can yield an expressive description of local shape differences

doi:10.1109/isbi.2006.1625124 (http://dx.crossref.org/10.1109/isbi.2006.1625124)

 

30.          Bathula DR, Papademetris X and Duncan JS. Level Set Based Clustering for Analysis of Functional Mri Data. Proceedings / IEEE International Symposium on Biomedical Imaging: from nano to macro IEEE International Symposium on Biomedical Imaging. 2007;4(4193311):416-9. Epub 2007/01/01. PMID: 20216927; PMCID: PMC2834251

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2834251.

Abstract: We present a level set based clustering technique to detect activation regions from functional brain images using contextual information. Earlier similar approaches have been primarily concerned with local spatial context. Our approach relies on the idea that voxels within a functional region have similar temporal behavior. Using a level set formulation, a two-dimensional curve is evolved with a speed proportional to a similarity measure between the fMRI signals of voxels lying on the curve and their neighbors in the direction of propagation. The correlation coefficient is used to quantify similarity in time series of adjacent voxels. Simulation results from synthetic images demonstrate that using spatio-temporal contextual information provides better segmentation than a context-free, voxel-wise technique. Results from a real fMRI experiment using auditory stimulation are also presented.

doi:10.1109/ISBI.2007.356877 (http://dx.crossref.org/10.1109/ISBI.2007.356877)

 

31.          DeLorenzo C, Papademetris X, Staib LH, Vives KP, Spencer DD and Duncan JS. Nonrigid Intraoperative Cortical Surface Tracking Using Game Theory. Computer Vision, 2007 ICCV 2007 IEEE 11th International Conference on. 2007:1-8.

Abstract: During neurosurgery, nonrigid brain deformation prevents preoperatively acquired images from accurately depicting the intraoperative brain. Stereo vision systems can be used to track cortical surface deformation and update preoperative brain images in conjunction with a biomechanical model. However, these stereo systems are often plagued with calibration error, which can corrupt the deformation estimation. In order to decouple the effects of camera calibration and surface deformation, a framework is needed which can solve for disparate and often competing variables. Game theory, which was developed specifically to handle decision making in this type of competitive environment, has been applied to various fields from economics to biology. In this paper, we apply game theory to cortical surface tracking and use it to infer information about the physical processes of brain deformation and image acquisition.

doi:10.1109/iccv.2007.4409135 (http://dx.crossref.org/10.1109/iccv.2007.4409135)

 

32.          DeLorenzo C, Papademetris X, Vives KP, Spencer DD and Duncan JS. A comprehensive system for intraoperative 3D brain deformation recovery. Medical image computing and computer-assisted intervention : MICCAI  International Conference on Medical Image Computing and Computer-Assisted Intervention. 2007;10(Pt 2):553-61. Epub 2007/11/30. PMID: 18044612; PMCID: PMC2864112

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2864112.

Abstract: During neurosurgery, brain deformation renders preoperative images unreliable for localizing pathologic structures. In order to visualize the current brain anatomy, it is necessary to nonrigidly warp these preoperative images to reflect the intraoperative brain. This can be accomplished using a biomechanical model driven by sparse intraoperative information. In this paper, a linear elastic model of the brain is developed which can infer volumetric brain deformation given the cortical surface displacement. This model was tested on both a realistic brain phantom and in vivo, proving its ability to account for large brain deformations. Also, an efficient semiautomatic strategy for preoperative cortical feature detection is outlined, since accurate segmentation of cortical features can aid intraoperative cortical surface tracking.

doi:10.1007/978-3-540-75759-7_67 (http://dx.crossref.org/10.1007/978-3-540-75759-7_67)

 

33.          DeLorenzo C, Papademetris X, Vives KP, Spencer DD and Duncan JS. A REALISTIC BRAIN PHANTOM FOR 3D DEFORMATION RECOVERY. Biomedical Imaging: From Nano to Macro, 2007 ISBI 2007 4th IEEE International Symposium on. 2007:9-12.

Abstract: Soft tissue deformation occurs during neurosurgery causing misalignment between preoperatively acquired images and the intraoperative brain. Compensation for this deformation is often accomplished using sparse intraoperative data from the exposed cortical surface combined with a biomechanical model. While simulations provide an important tool for testing these surface tracking algorithms, intraoperative conditions are most closely modeled using physical brain phantoms. We have developed a realistic silicone brain phantom and have used this phantom to test our surface tracking algorithm. The physical properties of this phantom allowed reliable testing of intraoperative surface tracking in a controlled environment

doi:10.1109/isbi.2007.356775 (http://dx.crossref.org/10.1109/isbi.2007.356775)

 

34.          Greene WH, Chelikani S, Papademetris X, Knisely JP and Duncan J. A Constrained Non-Rigid Registration Algorithm for Application in Prostate Radiotherapy. Proceedings / IEEE International Symposium on Biomedical Imaging: from nano to macro IEEE International Symposium on Biomedical Imaging. 2007;4193392:740-3. Epub 2007/01/01. PMID: 20011132; PMCID: PMC2792992

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2792992.

Abstract: This paper presents a novel free-form deformation registration algorithm with non-rigid constraints to capture the transformation between the planning day and treatment day CT images used for external beam radiotherapy for prostate cancer. The algorithm is constrained to the predetermined motion of a segmented organ, which is described by an injective free-form deformation (FFD) based on B-splines. The end goal is for the injective transformation to be used to update the radiotherapy plan to take into account bone and soft tissue deformation. The results of the algorithm have been compared to those achieved using rigid and fully non-rigid registration. The results clearly indicate that the constrained non-rigid registration algorithm presented in this paper performed much better at capturing the motion of the constrained organ, the bladder in this case, than the rigid or fully non-rigid registration algorithms.

doi:10.1109/ISBI.2007.356958 (http://dx.crossref.org/10.1109/ISBI.2007.356958)

 

35.          Mounzer R, Shkarin P, Papademetris X, Constable T, Ruddle NH and Fahmy TM. Dynamic imaging of lymphatic vessels and lymph nodes using a bimodal nanoparticulate contrast agent. Lymphat Res Biol. 2007;5(3):151-8. Epub 2007/11/27. PMID: 18035933.

Abstract: BACKGROUND: Evaluation of lymphedema and lymph node metastasis in humans has relied primarily on invasive or radioactive modalities. While noninvasive technologies such as magnetic resonance imaging (MRI) offer the potential for true three-dimensional imaging of lymphatic structures, invasive modalities, such as optical fluorescence microscopy, provide higher resolution and clearer delineation of both lymph nodes and lymphatic vessels. Thus, contrast agents that image lymphatic vessels and lymph nodes by both fluorescence and MRI may further enhance our understanding of the structure and function of the lymphatic system. Recent applications of bimodal (fluorescence and MR) contrast agents in mice have not achieved clear visualization of lymphatic vessels and nodes. Here the authors describe the development of a nanoparticulate contrast agent that is taken up by lymphatic vessels to draining lymph nodes and detected by both modalities. METHODS: A unique nanoparticulate contrast agent composed of a polyamidoamine dendrimer core conjugated to paramagnetic contrast agents and fluorescent probes was synthesized. Anesthetized mice were injected with the nanoparticulates in the hind footpads and imaged by MR and fluorescence microscopy. High resolution MR and fluorescence images were obtained and compared to traditional techniques for lymphatic visualization using Evans blue dye. RESULTS: Lymph nodes and lymphatic vessels were clearly observed by both MRI and fluorescence microscopy using the bimodal nanoparticulate contrast agent. Characteristic tail-lymphatics were also visualized by both modalities. Contrast imaging yielded a higher resolution than the traditional method employing Evans blue dye. MR data correlated with fluorescence and Evans blue dye imaging. CONCLUSION: A bimodal nanoparticulate contrast agent facilitates the visualization of lymphatic vessels and lymph nodes by both fluorescence microscopy and MRI with strong correlation between the two modalities. This agent may translate to applications such as the assessment of malignancy and lymphedema in humans and the evaluation of lymphatic vessel function and morphology in animal models.

doi:10.1089/lrb.2007.5302 (http://dx.crossref.org/10.1089/lrb.2007.5302)

 

36.          Petersen KF, Dufour S, Savage DB, Bilz S, Solomon G, Yonemitsu S, Cline GW, Befroy D, Zemany L, Kahn BB, Papademetris X, Rothman DL and Shulman GI. The role of skeletal muscle insulin resistance in the pathogenesis of the metabolic syndrome. Proceedings of the National Academy of Sciences of the United States of America. 2007;104(31):12587-94. Epub 2007/07/21. PMID: 17640906; PMCID: PMC1924794

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/1924794.

Abstract: We examined the hypothesis that insulin resistance in skeletal muscle promotes the development of atherogenic dyslipidemia, associated with the metabolic syndrome, by altering the distribution pattern of postprandial energy storage. Following ingestion of two high carbohydrate mixed meals, net muscle glycogen synthesis was reduced by approximately 60% in young, lean, insulin-resistant subjects compared with a similar cohort of age-weight-body mass index-activity-matched, insulin-sensitive, control subjects. In contrast, hepatic de novo lipogenesis and hepatic triglyceride synthesis were both increased by >2-fold in the insulin-resistant subjects. These changes were associated with a 60% increase in plasma triglyceride concentrations and an approximately 20% reduction in plasma high-density lipoprotein concentrations but no differences in plasma concentrations of TNF-alpha, IL-6, adiponectin, resistin, retinol binding protein-4, or intraabdominal fat volume. These data demonstrate that insulin resistance in skeletal muscle, due to decreased muscle glycogen synthesis, can promote atherogenic dyslipidemia by changing the pattern of ingested carbohydrate away from skeletal muscle glycogen synthesis into hepatic de novo lipogenesis, resulting in an increase in plasma triglyceride concentrations and a reduction in plasma high-density lipoprotein concentrations. Furthermore, insulin resistance in these subjects was independent of changes in the plasma concentrations of TNF-alpha, IL-6, high-molecular-weight adiponectin, resistin, retinol binding protein-4, or intraabdominal obesity, suggesting that these factors do not play a primary role in causing insulin resistance in the early stages of the metabolic syndrome.

doi:10.1073/pnas.0705408104 (http://dx.crossref.org/10.1073/pnas.0705408104)

 

37.          Qian X, Brennan M, Dione D, Dobrucki L, Jackowski M, Breuer C, Sinusas A and Papademetris X. Detection of Complex Vascular Structures using Polar Neighborhood Intensity Profile. Computer Vision, 2007 ICCV 2007 (MMBIA) IEEE 11th International Conference on. 2007.

Abstract: Modern medical imaging techniques enable the acquisition of in-vivo high resolution images of the vascular system. Most common methods for the detection of vessels in these images, such as multiscale Hessian-based operators and matched filters, rely on the assumption that, at each voxel there is a single cylinder. Such an assumption is clearly violated at the multitude of branching points that are easily observed in all but the most focused vascular image studies. In this paper, we propose a novel method for detecting vessels in medical images that relaxes this single cylinder constraint. Instead, we extract characteristics of the local intensity profile (in a spherical polar coordinate system) which we term as the polar neighborhood intensity profile enabling us to detect vessels even near branching points. Our method demonstrates improved performance over standard methods on both 2D synthetic images and MRA 3D animal vascular images, particularly close to vessel branching regions. This methodology is also applicable to the detection of other structures such as sheets with the appropriate choice of operators.

 

 

doi:10.1109/ICCV.2007.4409172 (http://dx.crossref.org/10.1109/ICCV.2007.4409172)

 

38.          Yun Z, Papademetris X, Duncan JS and Sinusas A. CARDIAC MR IMAGE SEGMENTATION WITH INCOMPRESSIBILITY CONSTRAINT. Biomedical Imaging: From Nano to Macro, 2007 ISBI 2007 4th IEEE International Symposium on. 2007:185-8.

Abstract: Automatic segmentation of the left ventricle (LV) from cardiac images remains an open problem. While current methods are already sufficient to outline endocardial (ENDO) surface automatically, these methods are problematic for finding reliable epicardial (EPI) surfaces. It is mainly due to the low myocardium/background contrast. In this paper, we propose a new algorithm that is motivated by the approximate incompressibility of myocardium during a cardiac cycle and takes it as an important constraint. We design in a probabilistic framework a deformable model that evolves according to the regional intensity distribution while maintaining the volume of myocardium. Experiments on 225 sets of volumetric cardiac MR images validate the accuracy and robustness of this method

doi:10.1109/isbi.2007.356819 (http://dx.crossref.org/10.1109/isbi.2007.356819)

 

39.          Yun Z, Papademetris X, Sinusas A and Duncan JS. Local Shape Registration Using Boundary-Constrained Match of Skeletons. Computer Vision and Pattern Recognition, 2007 CVPR '07 IEEE Conference on. 2007:1-8.

Abstract: This paper presents a new shape registration algorithm that establishes "meaningful correspondence " between objects, in that it preserves the local shape correspondence between the source and target objects. By observing that an object's skeleton corresponds to its local shape peaks, we use skeleton to characterize the local shape of the source and target objects. Unlike traditional graph-based skeleton matching algorithms that focus on matching skeletons alone and ignore the overall alignment of the boundaries, our algorithm is formulated in a variational framework which aligns local shape by registering two potential fields that are associated with skeletons. Also, we add a boundary constraint term to the energy functional, such that our algorithm can be applied to match bulky objects where skeleton and boundary are far away to each other. To increase the robustness of our algorithm, we incorporate M-estimator and dynamic pruning algorithm to form a feedback system that eliminates local shape outliers caused by nonrigid deformation, occlusion, and missing parts. Experiments on 2D binary shapes and 3D cardiac sequences validate the accuracy and robustness of this algorithm.

doi:10.1109/cvpr.2007.383427 (http://dx.crossref.org/10.1109/cvpr.2007.383427)

 

40.          Zhu Y, Papademetris X, Sinusas A and Duncan JS. Segmentation of myocardial volumes from real-time 3D echocardiography using an incompressibility constraint. Medical image computing and computer-assisted intervention : MICCAI  International Conference on Medical Image Computing and Computer-Assisted Intervention. 2007;10(Pt 1):44-51. Epub 2007/12/07. PMID: 18051042.

Abstract: Real-time three-dimensional (RT3D) echocardiography is a new imaging modality that presents the unique opportunity to visualize the complex three-dimensional (3-D) shape and the motion of left ventricle (LV) in vivo. To take advantage of this opportunity, automatic segmentation of LV myocardium is essential. While there are a variety of efforts on the segmentation of LV endocardial (ENDO) boundaries, the segmentation of epicardial (EPI) boundaries is still problematic. In this paper, we present a new approach of coupled-surfaces propagation to address this problem. Our method is motivated by the idea that the volume of the myocardium is close to being constant during a cardiac cycle and takes this tight coupling as an important constraint. We employ two surfaces, each driven by the image-derived information that takes into account the ultrasound physics by modeling speckle using shifted Rayleigh distribution while maintaining the coupling. By evolving two surfaces simultaneously, the final representation of myocardium is thus achieved. Results from 328 sets of RT3D echocardiographic data are evaluated against the outlines of three observers. We show that the results from automatic segmentation are comparable to those from manual segmentation.

doi:10.1007/978-3-540-75757-3_6 (http://dx.crossref.org/10.1007/978-3-540-75757-3_6)

 

41.          Bathula DR, Tagare HD, Staib LH, Papademetris X, Schultz RT and Duncan JS. Bayesian analysis of fMRI data with ICA based spatial prior. Medical image computing and computer-assisted intervention : MICCAI  International Conference on Medical Image Computing and Computer-Assisted Intervention. 2008;11(Pt 2):246-54. Epub 2008/11/06. PMID: 18982612; PMCID: PMC2864117

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2864117.

Abstract: Spatial modeling is essential for fMRI analysis due to relatively high noise in the data. Earlier approaches have been primarily concerned with the spatial coherence of the BOLD response in local neighborhoods. In addition to a smoothness constraint, we propose to incorporate prior knowledge of brain activation patterns learned from training samples. This spatially informed prior can significantly enhance the estimation process by inducing sensitivity to task related regions of the brain. As fMRI data exhibits intersubject variability in functional anatomy, we design the prior using Independent Component Analysis (ICA). Due to the non-Gaussian assumption, ICA does not regress to the mean activation pattern and thus avoids suppressing intersubject differences. Results from a real fMRI experiment indicate that our approach provides statistically significant improvement in estimating activation compared to the standard general linear model (GLM) based methods.

doi:10.1007/978-3-540-85990-1_30 (http://dx.crossref.org/10.1007/978-3-540-85990-1_30)

 

42.          Brennan MP, Dardik A, Hibino N, Roh JD, Nelson GN, Papademetris X, Shinoka T and Breuer CK. Tissue-engineered vascular grafts demonstrate evidence of growth and development when implanted in a juvenile animal model. Annals of surgery. 2008;248(3):370-7. Epub 2008/09/16. PMID: 18791357; PMCID: PMC2726802

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2726802.

Abstract: INTRODUCTION: The development of a living, autologous vascular graft with the ability to grow holds great promise for advancing the field of pediatric cardiothoracic surgery. OBJECTIVE: To evaluate the growth potential of a tissue-engineered vascular graft (TEVG) in a juvenile animal model. METHODS: Polyglycolic acid nonwoven mesh tubes (3-cm length, 1.3-cm id; Concordia Fibers) coated with a 10% copolymer solution of 50:50 L-lactide and epsilon-caprolactone were statically seeded with 1 x 10 cells/cm autologous bone marrow derived mononuclear cells. Eight TEVGs (7 seeded, 1 unseeded control) were implanted as inferior vena cava (IVC) interposition grafts in juvenile lambs. Subjects underwent bimonthly magnetic resonance angiography (Siemens 1.5 T) with vascular image analysis (www.BioimageSuite.org). One of 7-seeded grafts was explanted after 1 month and all others were explanted 6 months after implantation. Neotissue was characterized using qualitative histologic and immunohistochemical staining and quantitative biochemical analysis. RESULTS: All grafts explanted at 6 months were patent and increased in volume as measured by difference in pixel summation in magnetic resonance angiography at 1 month and 6 months. The volume of seeded TEVGs at explant averaged 126.9% +/- 9.9% of their volume at 1 month. Magnetic resonance imaging demonstrated no evidence of aneurysmal dilation. TEVG resembled the native IVC histologically and had comparable collagen (157.9 +/- 26.4 microg/mg), elastin (186.9 +/- 16.7 microg/mg), and glycosaminoglycan (9.7 +/- 0.8 microg/mg) contents. Immunohistochemical staining and Western blot analysis showed that Ephrin-B4, a determinant of normal venous development, was acquired in the seeded grafts 6 months after implantation. CONCLUSIONS: TEVGs demonstrate evidence of growth and venous development when implanted in the IVC of a juvenile lamb model.

doi:10.1097/SLA.0b013e318184dcbd (http://dx.crossref.org/10.1097/SLA.0b013e318184dcbd)

 

43.          Greene WH, Chelikani S, Papademetris X, Staib LH, Knisely JP and Duncan J. Tracking Organ Overlap for a Constrained Non-Rigid Registration Algorithm. Proceedings / IEEE International Symposium on Biomedical Imaging: from nano to macro IEEE International Symposium on Biomedical Imaging. 2008;4541207:1159. Epub 2008/01/01. PMID: 20126424; PMCID: PMC2814434

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2814434.

Abstract: This paper tracks organ (prostate, rectum, bladder) overlap in a constrained non-rigid registration (NRR) algorithm to register computed tomographic (CT) images used in external beam prostate radiotherapy. The local motion of the organs is described by a hierarchical multi-resolution FFD based on cubic B-splines. Registration is achieved by minimizing a cost function which is a combination of three functions representing the overlap of the critical organs, image similarity and smoothness of the transformation. The constrained NRR algorithm generated better registration results when compared to an unconstrained NRR algorithm.

doi:10.1109/ISBI.2008.4541207 (http://dx.crossref.org/10.1109/ISBI.2008.4541207)

 

44.          Greene WH, Chelikani S, Purushothaman K, Chen Z, Knisely JP, Staib LH, Papademetris X and Duncan J. A constrained non-rigid registration algorithm for use in prostate image-guided radiotherapy. Medical image computing and computer-assisted intervention : MICCAI  International Conference on Medical Image Computing and Computer-Assisted Intervention. 2008;11(Pt 1):780-8. Epub 2008/11/05. PMID: 18979817; PMCID: PMC2790815

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2790815.

Abstract: A constrained non-rigid registration (CNRR) algorithm for use in updating prostate external beam image-guided radiotherapy treatment plans is presented in this paper. The developed algorithm is based on a multi-resolution cubic B-spline FFD transformation and has been tested and verified using 3D CT images from 10 sets of real patient data acquired from 4 different patients on different treatment days. The registration can be constrained to any combination of the prostate, rectum, bladder, pelvis, left femur, and right femur. The CNRR was tested with 5 different combinations of constraints and each test significantly outperformed both rigid and non-rigid registration at aligning constrained bones and critical organs. The CNRR was then used to update the treatment plans to account for articulated, rigid bone motion and non-rigid organ deformation. Each updated treatment plan outperformed the original treatment plan by increasing radiation dosage to the prostate and lowering radiation dosage to the rectum and bladder.

doi:10.1007/978-3-540-85988-8_93 (http://dx.crossref.org/10.1007/978-3-540-85988-8_93)

 

45.          Joshi A, Qian X, Dione DP, Bulsara KR, Breuer CK, Sinusas AJ and Papademetris X. Effective visualization of complex vascular structures using a non-parametric vessel detection method. IEEE Trans Vis Comput Graph. 2008;14(6):1603-10. Epub 2008/11/08. PMID: 18989016; PMCID: PMC2636705

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2636705.

Abstract: The effective visualization of vascular structures is critical for diagnosis, surgical planning as well as treatment evaluation. In recent work, we have developed an algorithm for vessel detection that examines the intensity profile around each voxel in an angiographic image and determines the likelihood that any given voxel belongs to a vessel; we term this the "vesselness coefficient" of the voxel. Our results show that our algorithm works particularly well for visualizing branch points in vessels. Compared to standard Hessian based techniques, which are fine-tuned to identify long cylindrical structures, our technique identifies branches and connections with other vessels. Using our computed vesselness coefficient, we explore a set of techniques for visualizing vasculature. Visualizing vessels is particularly challenging because not only is their position in space important for clinicians but it is also important to be able to resolve their spatial relationship. We applied visualization techniques that provide shape cues as well as depth cues to allow the viewer to differentiate between vessels that are closer from those that are farther. We use our computed vesselness coefficient to effectively visualize vasculature in both clinical neurovascular x-ray computed tomography based angiography images, as well as images from three different animal studies. We conducted a formal user evaluation of our visualization techniques with the help of radiologists, surgeons, and other expert users. Results indicate that experts preferred distance color blending and tone shading for conveying depth over standard visualization techniques.

doi:10.1109/TVCG.2008.123 (http://dx.crossref.org/10.1109/TVCG.2008.123)

 

46.          Joshi A, Scheinost D, Vives KP, Spencer DD, Staib LH and Papademetris X. Novel interaction techniques for neurosurgical planning and stereotactic navigation. IEEE Trans Vis Comput Graph. 2008;14(6):1587-94. Epub 2008/11/08. PMID: 18989014; PMCID: PMC2633029

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2633029.

Abstract: Neurosurgical planning and image guided neurosurgery require the visualization of multimodal data obtained from various functional and structural image modalities, such as Magnetic Resonance Imaging (MRI), Computed Tomography (CT), functional MRI, Single photon emission computed tomography (SPECT) and so on. In the case of epilepsy neurosurgery for example, these images are used to identify brain regions to guide intracranial electrode implantation and resection. Generally, such data is visualized using 2D slices and in some cases using a 3D volume rendering along with the functional imaging results. Visualizing the activation region effectively by still preserving sufficient surrounding brain regions for context is exceedingly important to neurologists and surgeons. We present novel interaction techniques for visualization of multimodal data to facilitate improved exploration and planning for neurosurgery. We extended the line widget from VTK to allow surgeons to control the shape of the region of the brain that they can visually crop away during exploration and surgery. We allow simple spherical, cubical, ellipsoidal and cylindrical (probe aligned cuts) for exploration purposes. In addition we integrate the cropping tool with the image-guided navigation system used for epilepsy neurosurgery. We are currently investigating the use of these new tools in surgical planning and based on further feedback from our neurosurgeons we will integrate them into the setup used for image-guided neurosurgery.

doi:10.1109/TVCG.2008.150 (http://dx.crossref.org/10.1109/TVCG.2008.150)

 

47.          Lacadie CM, Fulbright RK, Rajeevan N, Constable RT and Papademetris X. More accurate Talairach coordinates for neuroimaging using non-linear registration. NeuroImage. 2008;42(2):717-25. Epub 2008/06/24. PMID: 18572418; PMCID: PMC2603575

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2603575.

Abstract: While the Talairach atlas remains the most commonly used system for reporting coordinates in neuroimaging studies, the absence of an actual 3-D image of the original brain used in its construction has severely limited the ability of researchers to automatically map locations from 3-D anatomical MRI images to the atlas. Previous work in this area attempted to circumvent this problem by constructing approximate linear and piecewise-linear mappings between standard brain templates (e.g. the MNI template) and Talairach space. These methods are limited in that they can only account for differences in overall brain size and orientation but cannot correct for the actual shape differences between the MNI template and the Talairach brain. In this paper we describe our work to digitize the Talairach atlas and generate a non-linear mapping between the Talairach atlas and the MNI template that attempts to compensate for the actual differences in shape between the two, resulting in more accurate coordinate transformations. We present examples in this paper and note that the method is available freely online as a Java applet.

doi:10.1016/j.neuroimage.2008.04.240 (http://dx.crossref.org/10.1016/j.neuroimage.2008.04.240)

 

48.          Meltzer JA, Zaveri HP, Goncharova, II, Distasio MM, Papademetris X, Spencer SS, Spencer DD and Constable RT. Effects of working memory load on oscillatory power in human intracranial EEG. Cereb Cortex. 2008;18(8):1843-55. Epub 2007/12/07. PMID: 18056698; PMCID: PMC2474453

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2474453.

Abstract: Studies of working memory load effects on human EEG power have indicated divergent effects in different frequency bands. Although gamma power typically increases with load, the load dependency of the lower frequency theta and alpha bands is uncertain. We obtained intracranial electroencephalography measurements from 1453 electrode sites in 14 epilepsy patients performing a Sternberg task, in order to characterize the anatomical distribution of load-related changes across the frequency spectrum. Gamma power increases occurred throughout the brain, but were most common in the occipital lobe. In the theta and alpha bands, both increases and decreases were observed, but with different anatomical distributions. Increases in theta and alpha power were most prevalent in frontal midline cortex. Decreases were most commonly observed in occipital cortex, colocalized with increases in the gamma range, but were also detected in lateral frontal and parietal regions. Spatial overlap with group functional magnetic resonance imaging results was minimal except in the precentral gyrus. These findings suggest that power in any given frequency band is not a unitary phenomenon; rather, reactivity in the same frequency band varies in different brain regions, and may relate to the engagement or inhibition of a given area in a cognitive task.

doi:10.1093/cercor/bhm213 (http://dx.crossref.org/10.1093/cercor/bhm213)

 

49.          Nelson GN, Roh JD, Mirensky TL, Wang Y, Yi T, Tellides G, Pober JS, Shkarin P, Shapiro EM, Saltzman WM, Papademetris X, Fahmy TM and Breuer CK. Initial evaluation of the use of USPIO cell labeling and noninvasive MR monitoring of human tissue-engineered vascular grafts in vivo. FASEB journal : official publication of the Federation of American Societies for Experimental Biology. 2008;22(11):3888-95. Epub 2008/08/20. PMID: 18711027; PMCID: PMC2574029

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2574029.

Abstract: This pilot study examines noninvasive MR monitoring of tissue-engineered vascular grafts (TEVGs) in vivo using cells labeled with iron oxide nanoparticles. Human aortic smooth muscle cells (hASMCs) were labeled with ultrasmall superparamagnetic iron oxide (USPIO) nanoparticles. The labeled hASMCs, along with human aortic endothelial cells, were incorporated into eight TEVGs and were then surgically implanted as aortic interposition grafts in a C.B-17 SCID/bg mouse host. USPIO-labeled hASMCs persisted in the grafts throughout a 3 wk observation period and allowed noninvasive MR imaging of the human TEVGs for real-time, serial monitoring of hASMC retention. This study demonstrates the feasibility of applying noninvasive imaging techniques for evaluation of in vivo TEVG performance.

doi:10.1096/fj.08-107367 (http://dx.crossref.org/10.1096/fj.08-107367)

 

50.          Taksali SE, Caprio S, Dziura J, Dufour S, Cali AM, Goodman TR, Papademetris X, Burgert TS, Pierpont BM, Savoye M, Shaw M, Seyal AA and Weiss R. High visceral and low abdominal subcutaneous fat stores in the obese adolescent: a determinant of an adverse metabolic phenotype. Diabetes. 2008;57(2):367-71. Epub 2007/11/06. PMID: 17977954.

Abstract: OBJECTIVE: To explore whether an imbalance between the visceral and subcutaneous fat depots and a corresponding dysregulation of the adipokine milieu is associated with excessive accumulation of fat in the liver and muscle and ultimately with insulin resistance and the metabolic syndrome. RESEARCH DESIGN AND METHODS: We stratified our multi-ethnic cohort of 118 obese adolescents into tertiles based on the proportion of abdominal fat in the visceral depot. Abdominal and liver fat were measured by magnetic resonance imaging and muscle lipid (intramyocellular lipid) by proton magnetic resonance spectroscopy. RESULTS: There were no differences in age, BMI Z score, or fat-free mass across tertiles. However, as the proportion of visceral fat increased across tertiles, BMI and percentage of fat and subcutaneous fat decreased, while hepatic fat increased. In addition, there was an increase in 2-h glucose, insulin, c-peptide, triglyceride levels, and insulin resistance. Notably, both leptin and total adiponectin were significantly lower in tertile 3 than 1, while C-reactive protein and interleukin-6 were not different across tertiles. There was a significant increase in the odds ratio for the metabolic syndrome, with subjects in tertile 3 5.2 times more likely to have the metabolic syndrome than those in tertile 1. CONCLUSIONS: Obese adolescents with a high proportion of visceral fat and relatively low abdominal subcutaneous fat have a phenotype reminiscent of partial lipodystrophy. These adolescents are not necessarily the most severely obese, yet they suffer from severe metabolic complications and are at a high risk of having the metabolic syndrome.

doi:10.2337/db07-0932 (http://dx.crossref.org/10.2337/db07-0932)

 

51.          Wang F, Jackowski M, Kalmar JH, Chepenik LG, Tie K, Qiu M, Gong G, Pittman BP, Jones MM, Shah MP, Spencer L, Papademetris X, Constable RT and Blumberg HP. Abnormal anterior cingulum integrity in bipolar disorder determined through diffusion tensor imaging. The British journal of psychiatry : the journal of mental science. 2008;193(2):126-9. Epub 2008/08/02. PMID: 18669996; PMCID: PMC2732002

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2732002.

Abstract: BACKGROUND: Convergent evidence implicates white matter abnormalities in bipolar disorder. The cingulum is an important candidate structure for study in bipolar disorder as it provides substantial white matter connections within the corticolimbic neural system that subserves emotional regulation involved in the disorder. AIMS: To test the hypothesis that bipolar disorder is associated with abnormal white matter integrity in the cingulum. METHOD: Fractional anisotropy in the anterior and posterior cingulum was compared between 42 participants with bipolar disorder and 42 healthy participants using diffusion tensor imaging. RESULTS: Fractional anisotropy was significantly decreased in the anterior cingulum in the bipolar disorder group compared with the healthy group (P=0.003); however, fractional anisotropy in the posterior cingulum did not differ significantly between groups. CONCLUSIONS: Our findings demonstrate abnormalities in the structural integrity of the anterior cingulum in bipolar disorder. They extend evidence that supports involvement of the neural system comprising the anterior cingulate cortex and its corticolimbic gray matter connection sites in bipolar disorder to implicate abnormalities in the white matter connections within the system provided by the cingulum.

doi:10.1192/bjp.bp.107.048793 (http://dx.crossref.org/10.1192/bjp.bp.107.048793)

 

52.          Wang F, Kalmar JH, Edmiston E, Chepenik LG, Bhagwagar Z, Spencer L, Pittman B, Jackowski M, Papademetris X, Constable RT and Blumberg HP. Abnormal corpus callosum integrity in bipolar disorder: a diffusion tensor imaging study. Biological psychiatry. 2008;64(8):730-3. Epub 2008/07/16. PMID: 18620337; PMCID: PMC2586998

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2586998.

Abstract: OBJECTIVE: Abnormalities in the anterior interhemispheric connections provided by the corpus callosum (CC) have long been implicated in bipolar disorder (BD). In this study, we used complementary diffusion tensor imaging methods to study the structural integrity of the CC and localization of potential abnormalities in BD. METHODS: Subjects included 33 participants with BD and 40 healthy comparison participants. Fractional anisotropy (FA) measures were compared between groups with region of interest (ROI) methods to investigate the anterior, middle, and posterior CC and voxel-based methods to further localize abnormalities. RESULTS: In ROI-based analyses, FA was significantly decreased in the anterior and middle CC in the BD group (p < .05). Voxel-based analyses similarly localized group differences to the genu, rostral body, and anterior midbody of CC (p < .05, corrected). CONCLUSION: The findings demonstrate abnormalities in the structural integrity of the anterior CC in BD that might contribute to altered interhemispheric connectivity in this disorder.

doi:10.1016/j.biopsych.2008.06.001 (http://dx.crossref.org/10.1016/j.biopsych.2008.06.001)

 

53.          Yun Z, Papademetris X, Sinusas AJ and Duncan JS. Integrated segmentation and motion analysis of cardiac MR images using a subject-specific dynamical model. Computer Vision and Pattern Recognition Workshops, 2008 CVPRW '08 IEEE Computer Society Conference on. 2008:1-8.

Abstract: In this paper we propose an integrated cardiac segmentation and motion tracking algorithm. First, we present a subject-specific dynamical model (SSDM) that simultaneously handles inter-subject variability and temporal dynamics (intra-subject variability), such that it can progressively identify the subject vector associated with a new cardiac sequence, and use this subject vector to predict the subject-specific segmentation of the future frames based on the shapes observed in earlier frames. Second, we use the segmentation as a guide in selecting feature points with significant shape characteristics, and invoke the generalized robust point matching (G-RPM) strategy with boundary element method (BEM)-based regularization model to estimate physically realistic displacement field in a computationally efficient way. The integrated algorithm is formulated in a recursive Bayesian framework that sequentially segments cardiac images and estimates myocardial displacements. ldquoLeave-one-outrdquo validation on 32 sequences demonstrates that the segmentation results are improved when the SSDM is used, and the tracking results are much more accurate when the segmentation module is added.

doi:10.1109/cvprw.2008.4563007 (http://dx.crossref.org/10.1109/cvprw.2008.4563007)

 

54.          Yun Z, Ping Y, Papademetris X, Sinusas AJ and Duncan JS. Integrated segmentation and deformation analysis of 4-D cardiac MR images. Biomedical Imaging: From Nano to Macro, 2008 ISBI 2008 5th IEEE International Symposium on. 2008:1437-40.

Abstract: Segmentation and motion estimation from cardiac images are usually considered separately, yet they can obviously benefit from each other. In this paper, we propose a joint segmentation and motion estimation algorithm for the purposes of myocardial deformation analysis and strain estimation. We use segmentation as a guide for selecting feature points with significant shape characteristics, and invoke a Generalized Robust Point Matching (GRPM) strategy with Boundary Element Method (BEM)-based regularization model to estimate the dense displacement field and strain map from 3-D cardiac sequences. Quantitative analysis of the results is performed in comparison with the displacements found using implanted markers, taken to be gold standards.

doi:10.1109/isbi.2008.4541277 (http://dx.crossref.org/10.1109/isbi.2008.4541277)

 

55.          Zhu Y, Papademetris X, Sinusas A and Duncan JS. Segmentation of Left Ventricle From 3D Cardiac MR Image Sequences Using A Subject-Specific Dynamical Model. Proceedings / CVPR, IEEE Computer Society Conference on Computer Vision and Pattern Recognition IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2008;2008:1-8. Epub 2008/01/01. PMID: 20052308; PMCID: PMC2801445

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2801445.

Abstract: Statistical model-based segmentation of the left ventricle from cardiac images has received considerable attention in recent years. While a variety of statistical models have been shown to improve segmentation results, most of them are either static models (SM) which neglect the temporal coherence of a cardiac sequence or generic dynamical models (GDM) which neglect the inter-subject variability of cardiac shapes and deformations. In this paper, we use a subject-specific dynamical model (SSDM) that handles inter-subject variability and temporal dynamics (intra-subject variability) simultaneously. It can progressively identify the specific motion patterns of a new cardiac sequence based on the segmentations observed in the past frames. We formulate the integration of the SSDM into the segmentation process in a recursive Bayesian framework in order to segment each frame based on the intensity information from the current frame and the prediction from the past frames. We perform "Leave-one-out" test on 32 sequences to validate our approach. Quantitative analysis of experimental results shows that the segmentation with the SSDM outperforms those with the SM and GDM by having better global and local consistencies with the manual segmentation.

doi:10.1109/CVPR.2008.4587433 (http://dx.crossref.org/10.1109/CVPR.2008.4587433)

 

56.          Zhu Y, Papademetris X, Sinusas AJ and Duncan JS. Bidirectional segmentation of three-dimensional cardiac MR images using a subject-specific dynamical model. Medical image computing and computer-assisted intervention : MICCAI  International Conference on Medical Image Computing and Computer-Assisted Intervention. 2008;11(Pt 2):450-7. Epub 2008/11/06. PMID: 18982636; PMCID: PMC2829658

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2829658.

Abstract: Statistical model-based segmentation of the left ventricles has received considerable attention these years. While many statistical models have been shown to improve segmentation results, most of them either belong to (1) static models (SM) that neglect the temporal coherence of a cardiac sequence, or (2) generic dynamical models (GDM) that neglect the individual differences of cardiac motion. In this paper, we propose a subject-specific dynamical model (SSDM) that can simultaneously handle inter-subject variability and temporal cardiac dynamics (intra-subject variability). We also design a dynamic prediction algorithm that can progressively predict the shape of a new cardiac sequence at a given frame based on the shapes observed in earlier frames. Furthermore, to reduce the accumulation of the segmentation errors throughout the entire sequence, we take into account the periodic nature of cardiac motion and perform bidirectional segmentation from a certain frame in a cardiac sequence. "Leave-one-out" validation on 32 sequences show that our algorithm can capture local shape variations and suppress the propagation of segmentation errors.

doi:10.1007/978-3-540-85990-1_54 (http://dx.crossref.org/10.1007/978-3-540-85990-1_54)

 

57.          Chahboune H, Mishra AM, DeSalvo MN, Staib LH, Purcaro M, Scheinost D, Papademetris X, Fyson SJ, Lorincz ML, Crunelli V, Hyder F and Blumenfeld H. DTI abnormalities in anterior corpus callosum of rats with spike-wave epilepsy. NeuroImage. 2009;47(2):459-66. Epub 2009/04/29. PMID: 19398019; PMCID: PMC2712639

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2712639.

Abstract: OBJECTIVE: Absence epilepsy is a common seizure disorder in children which can produce chronic psychosocial sequelae. Human patients and rat absence models show bilateral spike-wave discharges (SWD) in cortical regions. We employed diffusion tensor imaging (DTI) in rat absence models to detect abnormalities in white matter pathways connecting regions of seizure activity. METHODS: We studied Wistar albino Glaxo rats of Rijswijk (WAG/Rij), genetic absence epilepsy rats of Strasbourg (GAERS), and corresponding nonepileptic control strains. Ex vivo DTI was performed at 9.4 T with diffusion gradients applied in 16 orientations. We compared fractional anisotropy (FA), perpendicular (lambda(perpendicular)) and parallel (lambda(||)) diffusivity between groups using t-maps and region of interest (ROI) measurements. RESULTS: Adult epileptic WAG/Rij rats exhibited a localized decrease in FA in the anterior corpus callosum. This area was confirmed by tractography to interconnect somatosensory cortex regions most intensely involved in seizures. This FA decrease was not present in young WAG/Rij rats before onset of SWD. GAERS, which have more severe SWD than WAG/Rij, exhibited even more pronounced callosal FA decreases. Reduced FA in the epileptic animals originated from an increased lambda(perpendicular) with no significant changes in lambda(||). INTERPRETATION: Reduced FA with increased lambda(perpendicular) suggests that chronic seizures cause reduction in myelin or decreased axon fiber density in white matter pathways connecting regions of seizure activity. These DTI abnormalities may improve the understanding of chronic neurological difficulties in children suffering with absence epilepsy, and may also serve as a noninvasive biomarker for monitoring beneficial effects of treatment.

doi:10.1016/j.neuroimage.2009.04.060 (http://dx.crossref.org/10.1016/j.neuroimage.2009.04.060)

 

58.          Chepenik LG, Fredericks C, Papademetris X, Spencer L, Lacadie C, Wang F, Pittman B, Duncan JS, Staib LH, Duman RS, Gelernter J and Blumberg HP. Effects of the brain-derived neurotrophic growth factor val66met variation on hippocampus morphology in bipolar disorder. Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology. 2009;34(4):944-51. Epub 2008/08/16. PMID: 18704093; PMCID: PMC2837582

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2837582.

Abstract: Histological and behavioral research in bipolar disorder (BD) implicates structural abnormalities in the hippocampus. Brain-derived neurotrophic growth factor (BDNF) protein is associated with hippocampal development and plasticity, and in mood disorder pathophysiology. We tested the hypotheses that both the BDNF val66met polymorphism and BD diagnosis are associated with decreased hippocampus volume, and that individuals with BD who carry the met allele have the smallest hippocampus volumes compared to individuals without BD and val/val homozygotes. We further explored localization of morphological differences within hippocampus in BD associated with the met allele. Twenty individuals with BD and 18 healthy comparison (HC) subjects participated in high-resolution magnetic resonance imaging scans from which hippocampus volumes were defined and measured. We used linear mixed model analysis to study effects of diagnosis and BDNF genotype on hippocampus volumes. We then employed three-dimensional mapping to localize areas of change within the hippocampus associated with the BDNF met allele in BD. We found that hippocampus volumes were significantly smaller in BD compared to HC subjects, and presence of the BDNF met allele was associated with smaller hippocampus volume in both diagnostic groups. The BD subgroup who carried the BDNF met allele had the smallest hippocampus volumes, and three-dimensional mapping identified these decreases as most prominent in left anterior hippocampus. These results support effects of BD diagnosis and BDNF genotype on hippocampus structure and suggest a genetic subgroup within BD who may be most vulnerable to deficits in hippocampus and may most benefit from interventions that influence BDNF-mediated signaling.

doi:10.1038/npp.2008.107 (http://dx.crossref.org/10.1038/npp.2008.107)

 

59.          Criscione JM, Le BL, Stern E, Brennan M, Rahner C, Papademetris X and Fahmy TM. Self-assembly of pH-responsive fluorinated dendrimer-based particulates for drug delivery and noninvasive imaging. Biomaterials. 2009;30(23-24):3946-55. Epub 2009/05/16. PMID: 19443028.

Abstract: Dendrimers are nanoscale macromolecules with well-defined branching chemical structures. Control over the architecture and function of these structures has enabled many advances in materials science and biomedical applications. Though dendrimers are directly synthesized by iteration of simple repetitive steps, generation of the larger, more complex structures required for many biomedical applications by covalent synthetic methods has been challenging. Here we demonstrate a spontaneous self-assembly of poly(amidoamine) dendrimers into complex nanoscopic and microscopic particulates following partial fluorination of the constituent dendrimer subunits. These dense particulates exhibit a stimulus-induced response to low external pH that causes their disassembly over time, enabling controlled release of encapsulated agents. In addition, we show that these assemblies offer a sufficiently high density of fluorine spins to enable detection of their site-specific accumulation in vivo by (19)F magnetic resonance imaging ((19)F MRI). Fluorinated dendrimer-based particulates present new features and capabilities important for a wide variety of emerging biomedical applications.

doi:10.1016/j.biomaterials.2009.04.014 (http://dx.crossref.org/10.1016/j.biomaterials.2009.04.014)

 

60.          Dobrucki LW, Dione DP, Kalinowski L, Dione D, Mendizabal M, Yu J, Papademetris X, Sessa WC and Sinusas AJ. Serial noninvasive targeted imaging of peripheral angiogenesis: validation and application of a semiautomated quantitative approach. Journal of nuclear medicine : official publication, Society of Nuclear Medicine. 2009;50(8):1356-63. Epub 2009/07/21. PMID: 19617325.

Abstract: Previous studies by our group have demonstrated the feasibility of noninvasive imaging of alpha(v) integrin to assess temporal and spatial changes in peripheral and myocardial angiogenesis. In this study, we validate the reproducibility, accuracy, and applicability of a new semiautomated noninvasive approach for serial quantitative evaluation of targeted micro-SPECT/CT images of peripheral angiogenesis in wild-type and endothelial nitric oxide sythase (eNOS)-deficient (eNOS-/-) mice subjected to hindlimb ischemia. METHODS: Mice (n = 15) underwent surgical ligation of the right femoral artery to induce unilateral hindlimb ischemia. One week after ligation, a (99m)Tc-labeled cyclic-Arg-Gly-Asp peptide targeted at alpha(v) integrin (NC100692, n = 10) or a (99m)Tc-labeled negative control (AH-111744, n = 5) was injected, and 60 min later in vivo micro-SPECT/CT images were acquired. Mice were euthanized, tissue from proximal and distal hindlimb was excised for gamma-well counting (GWC) of radiotracer activity, and ischemic-to-nonischemic (I/NI) ratio was calculated. Micro-SPECT/CT images were analyzed using a new semiautomated approach that applies complex volumes of interest (VOIs) derived from segmentation of the micro-CT images onto micro-SPECT images to calculate I/NI activity ratios for the proximal and distal hindlimb. Studies were reprocessed for determination of intra- and interobserver variability. To compare 3-dimensional (3D) VOI analysis with traditional manual 2-dimensional region-of-interest (ROI) analysis of maximum-intensity-projection images, micro-SPECT images were summed onto a single anterior-posterior projection. Rectangular ROIs were manually drawn and I/NI ratio calculated. Our new 3D analysis approach was applied to additional groups of mice (eNOS-/-, n = 5; wild-type, n = 3) imaged before and 1 and 4 wk after femoral artery resection. RESULTS: Our new semiautomated approach for the evaluation of images of alpha(v) integrin targeted with micro-SPECT/CT demonstrated both a high intra- and interobserver variability (R(2) = 0.997) and an accuracy (R(2) = 0.780) for estimation of relative radiotracer activity relative to GWC. Analysis of serial micro-SPECT/CT images demonstrated a significant increase in relative NC100692 retention in the ischemic hindlimb of both wild-type and eNOS-/- mice at 1 wk after surgery. There was a significant (approximately 25%) decrease in radiotracer uptake in eNOS-/- mice relative to wild-type animals, which was not observed at baseline or 4 wk after ligation. CONCLUSION: A new semiautomated analysis of images of alpha(v) integrin targeted with micro-SPECT/CT provides a noninvasive approach for serial quantitative evaluation of peripheral angiogenesis. The reproducibility and accuracy of this approach allows for quantitative analysis of serial targeted molecular images of lower extremities, has applicability to other targeted SPECT or PET radiotracers, and may have implications for clinical imaging in patients with peripheral arterial disease.

doi:10.2967/jnumed.108.060822 (http://dx.crossref.org/10.2967/jnumed.108.060822)

 

61.          Greene WH, Chelikani S, Purushothaman K, Knisely JP, Chen Z, Papademetris X, Staib LH and Duncan JS. Constrained non-rigid registration for use in image-guided adaptive radiotherapy. Med Image Anal. 2009;13(5):809-17. Epub 2009/08/18. PMID: 19682945; PMCID: PMC2771756

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2771756.

Abstract: A constrained non-rigid registration (CNRR) algorithm for use in prostate image-guided adaptive radiotherapy is presented in a coherent mathematical framework. The registration algorithm is based on a global rigid transformation combined with a series of local injective non-rigid multi-resolution cubic B-spline Free Form Deformation (FFD) transformations. The control points of the FFD are used to non-rigidly constrain the transformation to the prostate, rectum, and bladder. As well, the control points are used to rigidly constrain the transformation to the estimated position of the pelvis, left femur, and right femur. The algorithm was tested with both 3D conformal radiotherapy (3DCRT) and intensity-modulated radiotherapy (IMRT) dose plan data sets. The 3DCRT dose plan set consisted of 10 fan-beam CT (FBCT) treatment-day images acquired from four different patients. The IMRT dose plan set consisted of 32 cone-beam CT (CBCT) treatment-day images acquired from 4 different patients. The CNRR was tested with different combinations of anatomical constraints and each test significantly outperformed both rigid and non-rigid registration at aligning constrained bones and critical organs. The CNRR results were used to adapt the dose plans to account for patient positioning errors as well as inter-day bone motion and intrinsic organ deformation. Each adapted dose plan improved performance by lowering radiation distribution to the rectum and bladder while increasing or maintaining radiation distribution to the prostate.

doi:10.1016/j.media.2009.07.004 (http://dx.crossref.org/10.1016/j.media.2009.07.004)

 

62.          Ho HP, Papademetris X, Wang F, Blumberg HP and Staib LH. Volumetric shape model for oriented tubular structure from DTI data. Medical image computing and computer-assisted intervention : MICCAI  International Conference on Medical Image Computing and Computer-Assisted Intervention. 2009;12(Pt 2):18-25. Epub 2009/01/01. PMID: 20426091; PMCID: PMC2863144

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2863144.

Abstract: In this paper, we describe methods for constructing shape priors using orientation information to model white matter tracts from magnetic resonance diffusion tensor images (DTI). Shape Normalization is needed for the construction of a shape prior using statistical methods. Moving beyond shape normalization using boundary-only or orientation-only information, our method combines the idea of sweeping and inverse-skeletonization to parameterize 3D volumetric shape, which provides point correspondence and orientations over the whole volume in a continuous fashion. Tangents from this continuous model can be treated as a de-noised reconstruction of the original structural orientation inside a shape. We demonstrate the accuracy of this technique by reconstructing synthetic data and the 3D cingulum tract from brain DTI data and manually drawn 2D contours for each tract. Our output can also serve as the input for subsequent boundary finding or shape analysis.

doi:10.1007/978-3-642-04271-3_3 (http://dx.crossref.org/10.1007/978-3-642-04271-3_3)

 

63.          Jiang Y, Edmiston E, Wang F, Blumberg HP, Papademetris X and Staib LH. Improving the Reliability of Shape Comparison by Perturbation. Proceedings / IEEE International Symposium on Biomedical Imaging: from nano to macro IEEE International Symposium on Biomedical Imaging. 2009;5193140:686-9. Epub 2009/01/01. PMID: 20333326; PMCID: PMC2843157

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2843157.

Abstract: Shape comparison is a key scenario in morphometric study, where registration is often involved and found to be unreliable: different registrations can lead to different shape differences. This paper proposes a generic scheme applicable to most registration methods, to reduce this unreliability. It perturbs the registration processes by feeding them with resampled shape groups, and then aggregates the results to yield the final result. This scheme can be simplified for pair-wise registration methods to reduce the computation. Experiments are conducted on both synthetic and biomedical shapes using different registration methods, which demonstrate its effectiveness.

doi:10.1109/ISBI.2009.5193140 (http://dx.crossref.org/10.1109/ISBI.2009.5193140)

 

64.          Jiang Y, Edmiston E, Wang F, Blumberg HP, Staib LH and Papademetris X. Shape Comparison Using Perturbing Shape Registration. Proceedings / CVPR, IEEE Computer Society Conference on Computer Vision and Pattern Recognition IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2009;2009:683-90. Epub 2010/04/14. PMID: 20386618; PMCID: PMC2852275

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2852275.

Abstract: Shape registration is often involved in computing statistical differences between groups of shapes, which is a key aspect of morphometric study. The results of shape difference are found to be sensitive to registration, i.e., different registration methods lead to varied results. This raises the question of how to improve the reliability of registration procedures. This paper proposes a perturbation scheme, which perturbs registrations by feeding them with different resampled shape groups, and then aggregates the resulting shape differences. Experiments are conducted using three typical registration algorithms on both synthetic and biomedical shapes, where more reliable inter-group shape differences are found under the proposed scheme.

doi:10.1109/CVPRW.2009.5206598 (http://dx.crossref.org/10.1109/CVPRW.2009.5206598)

 

65.          Kalmar JH, Wang F, Spencer L, Edmiston E, Lacadie CM, Martin A, Constable RT, Duncan JS, Staib LH, Papademetris X and Blumberg HP. Preliminary evidence for progressive prefrontal abnormalities in adolescents and young adults with bipolar disorder. Journal of the International Neuropsychological Society : JINS. 2009;15(3):476-81. Epub 2009/05/01. PMID: 19402934; PMCID: PMC2852397

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2852397.

Abstract: Previous cross-sectional study of ventral prefrontal cortex (VPFC) implicated progressive volume abnormalities during adolescence in bipolar disorder (BD). In the present study, a within-subject, longitudinal design was implemented to examine brain volume changes during adolescence/young adulthood. We hypothesized that VPFC volume decreases over time would be greater in adolescents/young adults with BD than in healthy comparison adolescents/young adults. Eighteen adolescents/young adults (10 with BD I and 8 healthy comparison participants) underwent two high-resolution magnetic resonance imaging scans over approximately 2 years. Regional volume changes over time were measured. Adolescents/young adults with BD displayed significantly greater volume loss over time, compared to healthy comparison participants, in a region encompassing VPFC and rostral PFC and extending to rostral anterior cingulate cortex (p < .05). Additional areas where volume change differed between groups were observed. While data should be interpreted cautiously due to modest sample size, this study provides preliminary evidence to support the presence of accelerated loss in VPFC and rostral PFC volume in adolescents/young adults with BD.

doi:10.1017/S1355617709090584 (http://dx.crossref.org/10.1017/S1355617709090584)

 

66.          Papademetris X, DeLorenzo C, Flossmann S, Neff M, Vives KP, Spencer DD, Staib LH and Duncan JS. From medical image computing to computer-aided intervention: development of a research interface for image-guided navigation. The international journal of medical robotics + computer assisted surgery : MRCAS. 2009;5(2):147-57. Epub 2009/03/21. PMID: 19301361; PMCID: PMC2796181

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2796181.

Abstract: BACKGROUND: This paper describes the development and application of a research interface to integrate research image analysis software with a commercial image-guided surgery navigation system. This interface enables bi-directional transfer of data such as images, visualizations and tool positions in real time. METHODS: We describe both the design and the application programming interface of the research interface, as well as showing the function of an example client program. The resulting interface provides a practical and versatile link for bringing image analysis research techniques into the operating room (OR). RESULTS: We present examples from the successful use of this research interface in both phantom experiments and real neurosurgeries. In particular, we demonstrate that the integrated dual-computer system achieves tool-tracking performance that is comparable to the more typical single-computer scenario. CONCLUSIONS: Network interfaces for this type are viable solutions for the integration of commercial image-guided navigation systems and research software.

doi:10.1002/rcs.241 (http://dx.crossref.org/10.1002/rcs.241)

 

67.          Qian X, Brennan MP, Dione DP, Dobrucki WL, Jackowski MP, Breuer CK, Sinusas AJ and Papademetris X. A non-parametric vessel detection method for complex vascular structures. Med Image Anal. 2009;13(1):49-61. Epub 2008/08/06. PMID: 18678521; PMCID: PMC2614119

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2614119.

Abstract: Modern medical imaging techniques enable the acquisition of in vivo high resolution images of the vascular system. Most common methods for the detection of vessels in these images, such as multiscale Hessian-based operators and matched filters, rely on the assumption that at each voxel there is a single cylinder. Such an assumption is clearly violated at the multitude of branching points that are easily observed in all, but the most focused vascular image studies. In this paper, we propose a novel method for detecting vessels in medical images that relaxes this single cylinder assumption. We directly exploit local neighborhood intensities and extract characteristics of the local intensity profile (in a spherical polar coordinate system) which we term as the polar neighborhood intensity profile. We present a new method to capture the common properties shared by polar neighborhood intensity profiles for all the types of vascular points belonging to the vascular system. The new method enables us to detect vessels even near complex extreme points, including branching points. Our method demonstrates improved performance over standard methods on both 2D synthetic images and 3D animal and clinical vascular images, particularly close to vessel branching regions.

doi:10.1016/j.media.2008.05.005 (http://dx.crossref.org/10.1016/j.media.2008.05.005)

 

68.          Scheinost D, Blumenfeld H and Papademetris X. An Improved Unbiased Method for Diffspect Quantification in Epilepsy. Proceedings / IEEE International Symposium on Biomedical Imaging: from nano to macro IEEE International Symposium on Biomedical Imaging. 2009;2009:927-30. Epub 2009/06/01. PMID: 20706559; PMCID: PMC2920136

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2920136.

Abstract: Determining the region of seizure onset is of critical importance for treating medically intractable epilepsy. Comparisons between an ictal and interictal Single Photon Emission Computed Tomography (SPECT) images have been shown to be successful in localizing focal epilepsy. The Ictal-Interictal Subtraction Analysis by Statistical Parametric Mapping (ISAS) algorithm remains one the more successful algorithms for comparing these images. However ISAS is limited by its statistical design. This design introduces a scan order bias in the estimation of the normal variance of sequential SPECT images. We have corrected this bias by estimating the normal variance with a half-normal distribution. In this paper we present an updated algorithm (ISAS HN) based on the original ISAS algorithm with a corrected estimate of the normal variance and an open-source utility for ISAS HN.

doi:10.1109/ISBI.2009.5193205 (http://dx.crossref.org/10.1109/ISBI.2009.5193205)

 

69.          Suh JW, Scheinost D, Dione DP, Dobrucki LW, Sinusas AJ and Papademetris X. A non-rigid registration method for serial microCT mouse hindlimb images. Medical image computing and computer-assisted intervention : MICCAI  International Conference on Medical Image Computing and Computer-Assisted Intervention. 2009;12(Pt 1):688-95. Epub 2009/01/01. PMID: 20426048; PMCID: PMC2856964

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2856964.

Abstract: We present a new method for the non-rigid registration of serial mouse microCT images which undergo potentially large changes in the positions of the legs due to articulation. While non-rigid registration methods have been extensively used in the evaluation of individual organs, application in whole body imaging has been limited, primarily because the scale of possible displacements and deformations is large resulting in poor convergence of most methods. Our method is based on the extended demons algorithm that uses a level-set representation of the mouse skin and skeleton as an input, and composed of three steps reflecting the natural physical movements of bony structures. We applied our method to the registration of serial microCT mouse images demonstrating encouraging performances as compared to competitive techniques.

doi:10.1007/978-3-642-04268-3_85 (http://dx.crossref.org/10.1007/978-3-642-04268-3_85)

 

70.          Tokuda J, Fischer GS, Papademetris X, Yaniv Z, Ibanez L, Cheng P, Liu H, Blevins J, Arata J, Golby AJ, Kapur T, Pieper S, Burdette EC, Fichtinger G, Tempany CM and Hata N. OpenIGTLink: an open network protocol for image-guided therapy environment. The international journal of medical robotics + computer assisted surgery : MRCAS. 2009;5(4):423-34. Epub 2009/07/22. PMID: 19621334; PMCID: PMC2811069

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2811069.

Abstract: BACKGROUND: With increasing research on system integration for image-guided therapy (IGT), there has been a strong demand for standardized communication among devices and software to share data such as target positions, images and device status. METHOD: We propose a new, open, simple and extensible network communication protocol for IGT, named OpenIGTLink, to transfer transform, image and status messages. We conducted performance tests and use-case evaluations in five clinical and engineering scenarios. RESULTS: The protocol was able to transfer position data with submillisecond latency up to 1024 fps and images with latency of <10 ms at 32 fps. The use-case tests demonstrated that the protocol is feasible for integrating devices and software. CONCLUSION: The protocol proved capable of handling data required in the IGT setting with sufficient time resolution and latency. The protocol not only improves the interoperability of devices and software but also promotes transitions of research prototypes to clinical applications.

doi:10.1002/rcs.274 (http://dx.crossref.org/10.1002/rcs.274)

 

71.          Welborn BL, Papademetris X, Reis DL, Rajeevan N, Bloise SM and Gray JR. Variation in orbitofrontal cortex volume: relation to sex, emotion regulation and affect. Social cognitive and affective neuroscience. 2009;4(4):328-39. Epub 2009/12/19. PMID: 20019072; PMCID: PMC2799952

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2799952.

Abstract: Sex differences in brain structure have been examined extensively but are not completely understood, especially in relation to possible functional correlates. Our two aims in this study were to investigate sex differences in brain structure, and to investigate a possible relation between orbitofrontal cortex subregions and affective individual differences. We used tensor-based morphometry to estimate local brain volume from MPRAGE images in 117 healthy right-handed adults (58 female), age 18-40 years. We entered estimates of local brain volume as the dependent variable in a GLM, controlling for age, intelligence and whole-brain volume. Men had larger left planum temporale. Women had larger ventromedial prefrontal cortex (vmPFC), right lateral orbitofrontal (rlOFC), cerebellum, and bilateral basal ganglia and nearby white matter. vmPFC but not rlOFC volume covaried with self-reported emotion regulation strategies (reappraisal, suppression), expressivity of positive emotions (but not of negative), strength of emotional impulses, and cognitive but not somatic anxiety. vmPFC volume statistically mediated sex differences in emotion suppression. The results confirm prior reports of sex differences in orbitofrontal cortex structure, and are the first to show that normal variation in vmPFC volume is systematically related to emotion regulation and affective individual differences.

doi:10.1093/scan/nsp028 (http://dx.crossref.org/10.1093/scan/nsp028)

 

72.          Womer FY, Wang F, Chepenik LG, Kalmar JH, Spencer L, Edmiston E, Pittman BP, Constable RT, Papademetris X and Blumberg HP. Sexually dimorphic features of vermis morphology in bipolar disorder. Bipolar disorders. 2009;11(7):753-8. Epub 2009/10/21. PMID: 19839998; PMCID: PMC2844245

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2844245.

Abstract: OBJECTIVES: The cerebellar vermis is increasingly implicated in bipolar disorder (BD). In this study, we investigated vermis morphology in BD using a quantitative volumetric analysis. METHODS: Volumes for total vermis and vermis subregions V1 (lobules I-V), V2 (lobules VI-VII), and V3 (lobules VIII-X) were calculated using high-resolution structural magnetic resonance imaging obtained from 44 individuals with BD (25 females and 19 males) and 43 healthy comparison (HC) subjects (26 females and 17 males). Total vermis volumes were compared between the BD and HC groups. Potential effects of vermis subregions and clinical features were explored. RESULTS: Total vermis volumes were significantly larger in the BD group than in the HC group (p = 0.02). There was a significant group-by-sex interaction (p = 0.02). Total vermis volumes were significantly larger in males with BD than HC males (p = 0.004); vermis volumes did not differ significantly between females with and without BD (p = 0.95). Subregion analyses showed a trend-level interaction between diagnosis and subregion (p = 0.07) in which subregion V1 volumes were significantly larger in BD participants (p = 0.001), with differences primarily driven by males (p = 0.001). CONCLUSIONS: Our findings demonstrate increases in cerebellar vermis volumes in males with BD. These findings support the presence of structural alterations in the cerebellar vermis in BD and furthermore the influence of sex on such changes.

doi:10.1111/j.1399-5618.2009.00745.x (http://dx.crossref.org/10.1111/j.1399-5618.2009.00745.x)

 

73.          Zhu Y, Papademetris X, Sinusas AJ and Duncan JS. A Dynamical Shape Prior for LV Segmentation from RT3D Echocardiography. Medical image computing and computer-assisted intervention : MICCAI  International Conference on Medical Image Computing and Computer-Assisted Intervention. 2009;5761:206-13. Epub 2010/01/08. PMID: 20054422; PMCID: PMC2801876

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2801876.

Abstract: Real-time three-dimensional (RT3D) echocardiography is the newest generation of three-dimensional (3-D) echocardiography. Segmentation of RT3D echocardiographic images is essential for determining many important diagnostic parameters. In cardiac imaging, since the heart is a moving organ, prior knowledge regarding its shape and motion patterns becomes an important component for the segmentation task. However, most previous cardiac models are either static models (SM), which neglect the temporal coherence of a cardiac sequence or generic dynamical models (GDM), which neglect the inter-subject variability of cardiac motion. In this paper, we present a subject-specific dynamical model (SSDM) which simultaneously handles inter-subject variability and cardiac dynamics (intra-subject variability). It can progressively predict the shape and motion patterns of a new sequence at the current frame based on the shapes observed in the past frames. The incorporation of this SSDM into the segmentation process is formulated in a recursive Bayesian framework. This results in a segmentation of each frame based on the intensity information of the current frame, as well as on the prediction from the previous frames. Quantitative results on 15 RT3D echocardiographic sequences show that automatic segmentation with SSDM is superior to that of either SM or GDM, and is comparable to manual segmentation.

doi:10.1007/978-3-642-04268-3_26 (http://dx.crossref.org/10.1007/978-3-642-04268-3_26)

 

74.          Delorenzo C, Papademetris X, Staib LH, Vives KP, Spencer DD and Duncan JS. Image-guided intraoperative cortical deformation recovery using game theory: application to neocortical epilepsy surgery. IEEE transactions on medical imaging. 2010;29(2):322-38. Epub 2010/02/05. PMID: 20129844; PMCID: PMC2824434

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2824434.

Abstract: During neurosurgery, nonrigid brain deformation prevents preoperatively-acquired images from accurately depicting the intraoperative brain. Stereo vision systems can be used to track intraoperative cortical surface deformation and update preoperative brain images in conjunction with a biomechanical model. However, these stereo systems are often plagued with calibration error, which can corrupt the deformation estimation. In order to decouple the effects of camera calibration from the surface deformation estimation, a framework that can solve for disparate and often competing variables is needed. Game theory, which was developed to handle decision making in this type of competitive environment, has been applied to various fields from economics to biology. In this paper, game theory is applied to cortical surface tracking during neocortical epilepsy surgery and used to infer information about the physical processes of brain surface deformation and image acquisition. The method is successfully applied to eight in vivo cases, resulting in an 81% decrease in mean surface displacement error. This includes a case in which some of the initial camera calibration parameters had errors of 70%. Additionally, the advantages of using a game theoretic approach in neocortical epilepsy surgery are clearly demonstrated in its robustness to initial conditions.

doi:10.1109/TMI.2009.2027993 (http://dx.crossref.org/10.1109/TMI.2009.2027993)

 

75.          DeYoung CG, Hirsh JB, Shane MS, Papademetris X, Rajeevan N and Gray JR. Testing predictions from personality neuroscience. Brain structure and the big five. Psychological science. 2010;21(6):820-8. Epub 2010/05/04. PMID: 20435951; PMCID: PMC3049165

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/3049165.

Abstract: We used a new theory of the biological basis of the Big Five personality traits to generate hypotheses about the association of each trait with the volume of different brain regions. Controlling for age, sex, and whole-brain volume, results from structural magnetic resonance imaging of 116 healthy adults supported our hypotheses for four of the five traits: Extraversion, Neuroticism, Agreeableness, and Conscientiousness. Extraversion covaried with volume of medial orbitofrontal cortex, a brain region involved in processing reward information. Neuroticism covaried with volume of brain regions associated with threat, punishment, and negative affect. Agreeableness covaried with volume in regions that process information about the intentions and mental states of other individuals. Conscientiousness covaried with volume in lateral prefrontal cortex, a region involved in planning and the voluntary control of behavior. These findings support our biologically based, explanatory model of the Big Five and demonstrate the potential of personality neuroscience (i.e., the systematic study of individual differences in personality using neuroscience methods) as a discipline.

doi:10.1177/0956797610370159 (http://dx.crossref.org/10.1177/0956797610370159)

 

76.          Jiang Y, Zhuang Z, Sinusas AJ and Papademetris X. Vascular Tree Reconstruction by Minimizing A Physiological Functional Cost. Conference on Computer Vision and Pattern Recognition Workshops IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops. 2010:178-85. Epub 2011/07/15. PMID: 21755061; PMCID: PMC3132942

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/3132942.

Abstract: The reconstruction of complete vascular trees from medical images has many important applications. Although vessel detection has been extensively investigated, little work has been done on how connect the results to reconstruct the full trees. In this paper, we propose a novel theoretical framework for automatic vessel connection, where the automation is achieved by leveraging constraints from the physiological properties of the vascular trees. In particular, a physiological functional cost for the whole vascular tree is derived and an efficient algorithm is developed to minimize it. The method is generic and can be applied to different vessel detection/segmentation results, e.g. the classic rigid detection method as adopted in this paper. We demonstrate the effectiveness of this method on both 2D and 3D data.

doi:10.1109/CVPRW.2010.5543593 (http://dx.crossref.org/10.1109/CVPRW.2010.5543593)

 

77.          Joshi A, Papanastassiou A, Vives KP, Spencer DD, Staib LH and Papademetris X. Light-Sensitive Visualization of Multimodal Data for Neurosurgical Applications. Proceedings / IEEE International Symposium on Biomedical Imaging: from nano to macro IEEE International Symposium on Biomedical Imaging. 2010;2010(14-17 April 2010):884-7. Epub 2011/05/10. PMID: 21552380; PMCID: PMC3086020

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/3086020.

Abstract: We present a technique for enhancing multimodal visualizations for image-guided neurosurgery in the presence of adverse lighting conditions. In the surgical environment, images used for real time navigation are displayed in suboptimal conditions due to the varying lighting conditions. Our approach actively monitors the incoming light on the display and appropriately enhances the visualization based on the change in light. Based on the results of a user study to evaluate our approach, we found that our enhanced visualization techniques were mostly preferred over regular visualizations.

doi:10.1109/ISBI.2010.5490128 (http://dx.crossref.org/10.1109/ISBI.2010.5490128)

 

78.          Lu C, Chelikani S, Chen Z, Papademetris X, Staib LH and Duncan JS. Integrated segmentation and nonrigid registration for application in prostate image-guided radiotherapy. Medical image computing and computer-assisted intervention : MICCAI  International Conference on Medical Image Computing and Computer-Assisted Intervention. 2010;13(Pt 1):53-60. Epub 2010/10/01. PMID: 20879214.

Abstract: Many current image-guided radiotherapy (IGRT) systems incorporate an in-room cone-beam CT (CBCT) with a radiotherapy linear accelerator for treatment day imaging. Segmentation of key anatomical structures (prostate and surrounding organs) in 3DCBCT images as well as registration between planning and treatment images are essential for determining many important treatment parameters. Due to the image quality of CBCT, previous work typically uses manual segmentation of the soft tissues and then registers the images based on the manual segmentation. In this paper, an integrated automatic segmentation/constrained nonrigid registration is presented, which can achieve these two aims simultaneously. This method is tested using 24 sets of real patient data. Quantitative results show that the automatic segmentation produces results that have an accuracy comparable to manual segmentation, while the registration part significantly outperforms both rigid and non-rigid registration. Clinical application also shows promising results.

doi:10.1007/978-3-642-15705-9_7 (http://dx.crossref.org/10.1007/978-3-642-15705-9_7)

 

79.          Scheinost D, Teisseyre TZ, Distasio M, DeSalvo MN, Papademetris X and Blumenfeld H. New open-source ictal SPECT analysis method implemented in BioImage Suite. Epilepsia. 2010;51(4):703-7. Epub 2010/01/16. PMID: 20074234; PMCID: PMC2963625

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2963625.

Abstract: Ictal single photon emission computed tomography (SPECT) is a powerful tool for noninvasive seizure localization, but it has been underutilized because of practical challenges, including difficulty in implementing ictal-interictal SPECT difference analysis. We previously validated a freely available utility for this purpose, ictal-interictal subtraction analysis by statistical parametric mapping (SPM) (ISAS). To further simplify and improve the difference imaging technique, we now compare a new algorithm, ISAS BioImage Suite (see http://spect.yale.edu and http://bioimagesuite.org), to the original ISAS method in 13 patients with known seizure localization. We found that ISAS BioImage Suite was in agreement with the original algorithm in all cases for which ISAS correctly identified a single unambiguous region of seizure onset. We also tested for possible effects of scan-order bias in the control group used for the analysis and found no significant effect on the results. These findings establish a simple, validated and objective method for analyzing ictal-interictal SPECT difference images for use in the care of patients with epilepsy.

doi:10.1111/j.1528-1167.2009.02425.x (http://dx.crossref.org/10.1111/j.1528-1167.2009.02425.x)

 

80.          Shen X, Papademetris X and Constable RT. Graph-theory based parcellation of functional subunits in the brain from resting-state fMRI data. NeuroImage. 2010;50(3):1027-35. Epub 2010/01/12. PMID: 20060479; PMCID: PMC3062848

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/3062848.

Abstract: Resting-state fMRI provides a method to examine the functional network of the brain under spontaneous fluctuations. A number of studies have proposed using resting-state BOLD data to parcellate the brain into functional subunits. In this work, we present two state-of-the-art graph-based partitioning approaches, and investigate their application to the problem of brain network segmentation using resting-state fMRI. The two approaches, the normalized cut (Ncut) and the modularity detection algorithm, are also compared to the Gaussian mixture model (GMM) approach. We show that the Ncut approach performs consistently better than the modularity detection approach, and it also outperforms the GMM approach for in vivo fMRI data. Resting-state fMRI data were acquired from 43 healthy subjects, and the Ncut algorithm was used to parcellate several different cortical regions of interest. The group-wise delineation of the functional subunits based on resting-state fMRI was highly consistent with the parcellation results from two task-based fMRI studies (one with 18 subjects and the other with 20 subjects). The findings suggest that whole-brain parcellation of the cortex using resting-state fMRI is feasible, and that the Ncut algorithm provides the appropriate technique for this task.

doi:10.1016/j.neuroimage.2009.12.119 (http://dx.crossref.org/10.1016/j.neuroimage.2009.12.119)

 

81.          Suh JW, Scheinost D, Qian X, Sinusas AJ, Breuer CK and Papademetris X. Serial Nonrigid Vascular Registration Using Weighted Normalized Mutual Information. Proceedings / IEEE International Symposium on Biomedical Imaging: from nano to macro IEEE International Symposium on Biomedical Imaging. 2010;2010:25. Epub 2011/04/12. PMID: 21479163; PMCID: PMC3071602

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/3071602.

Abstract: Vascular registration is a challenging problem with many potential applications. However, registering vessels accurately is difficult as they often occupy a small portion of the image and their relative motion/deformation is swamped by the displacements seen in large organs such as the heart and the liver. Our registration method uses a vessel detection algorithm to generate a vesselness image (probability of having a vessel at any given voxel) which is used to construct a weighting factor that is used to modify the intensity metric to give preference to vascular structures while maintaining the larger context. Therefore, our proposing method uses fully data-driven calculated weights and needs no prior knowledge for the weight calculation. We applied our method to the registration of serial MRI lamb images obtained from studies on tissue engineered vascular grafts and demonstrate encouraging performance as compared to non-weighted registration methods.

doi:10.1109/ISBI.2010.5490422 (http://dx.crossref.org/10.1109/ISBI.2010.5490422)

 

82.          Zhu Y, Papademetris X, Sinusas AJ and Duncan JS. A coupled deformable model for tracking myocardial borders from real-time echocardiography using an incompressibility constraint. Med Image Anal. 2010;14(3):429-48. Epub 2010/03/31. PMID: 20350833.

Abstract: Real-time three-dimensional (RT3D) echocardiography is a new image acquisition technique that allows instantaneous acquisition of volumetric images for quantitative assessment of cardiac morphology and function. To quantify many important diagnostic parameters, such as ventricular volume, ejection fraction, and cardiac output, an automatic algorithm to delineate the left ventricle (LV) from RT3D echocardiographic images is essential. While a number of efforts have been made towards segmentation of the LV endocardial (ENDO) boundaries, the segmentation of epicardial (EPI) boundaries remains problematic. In this paper, we present a coupled deformable model that addresses this problem. The idea behind our method is that the volume of the myocardium is close to being constant during a cardiac cycle and our model uses this coupling as an important constraint. We employ two surfaces, each driven by the image-derived information that takes into account ultrasound physics by modeling the speckle statistics using the Nakagami distribution while maintaining the coupling. By simultaneously evolving two surfaces, the final segmentation of the myocardium is thus achieved. Results from 80 sets of synthetic data and 286 sets of real canine data were evaluated against the ground truth and against outlines from three independent observers, respectively. We show that results obtained with our incompressibility constraint were more accurate than those obtained without constraint or with a wall thickness constraint, and were comparable to those from manual segmentation.

doi:10.1016/j.media.2010.02.005 (http://dx.crossref.org/10.1016/j.media.2010.02.005)

 

83.          Zhu Y, Papademetris X, Sinusas AJ and Duncan JS. Segmentation of the left ventricle from cardiac MR images using a subject-specific dynamical model. IEEE transactions on medical imaging. 2010;29(3):669-87. Epub 2009/10/01. PMID: 19789107; PMCID: PMC2832728

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2832728.

Abstract: Statistical models have shown considerable promise as a basis for segmenting and interpreting cardiac images. While a variety of statistical models have been proposed to improve the segmentation results, most of them are either static models (SMs), which neglect the temporal dynamics of a cardiac sequence, or generic dynamical models (GDMs), which are homogeneous in time and neglect the intersubject variability in cardiac shape and deformation. In this paper, we develop a subject-specific dynamical model (SSDM) that simultaneously handles temporal dynamics (intrasubject variability) and intersubject variability. We also propose a dynamic prediction algorithm that can progressively identify the specific motion patterns of a new cardiac sequence based on the shapes observed in past frames. The incorporation of this SSDM into the segmentation framework is formulated in a recursive Bayesian framework. It starts with a manual segmentation of the first frame, and then segments each frame according to intensity information from the current frame as well as the prediction from past frames. In addition, to reduce error propagation in sequential segmentation, we take into account the periodic nature of cardiac motion and perform segmentation in both forward and backward directions. We perform "leave-one-out" test on 32 canine sequences and 22 human sequences, and compare the experimental results with those from SM, GDM, and active appearance motion model (AAMM). Quantitative analysis of the experimental results shows that SSDM outperforms SM, GDM, and AAMM by having better global and local consistencies with manual segmentation. Moreover, we compare the segmentation results from forward and forward-backward segmentation. Quantitative evaluation shows that forward-backward segmentation suppresses the propagation of segmentation errors.

doi:10.1109/TMI.2009.2031063 (http://dx.crossref.org/10.1109/TMI.2009.2031063)

 

84.          Criscione JM, Dobrucki LW, Zhuang ZW, Papademetris X, Simons M, Sinusas AJ and Fahmy TM. Development and application of a multimodal contrast agent for SPECT/CT hybrid imaging. Bioconjugate chemistry. 2011;22(9):1784-92. Epub 2011/08/20. PMID: 21851119; PMCID: PMC3204385

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/3204385.

Abstract: Hybrid or multimodality imaging is often applied in order to take advantage of the unique and complementary strengths of individual imaging modalities. This hybrid noninvasive imaging approach can provide critical information about anatomical structure in combination with physiological function or targeted molecular signals. While recent advances in software image fusion techniques and hybrid imaging systems have enabled efficient multimodal imaging, accessing the full potential of this technique requires development of a new toolbox of multimodal contrast agents that enhance the imaging process. Toward that goal, we report the development of a hybrid probe for both single photon emission computed tomography (SPECT) and X-ray computed tomography (CT) imaging that facilitates high-sensitivity SPECT and high spatial resolution CT imaging. In this work, we report the synthesis and evaluation of a novel intravascular, multimodal dendrimer-based contrast agent for use in preclinical SPECT/CT hybrid imaging systems. This multimodal agent offers a long intravascular residence time (t(1/2) = 43 min) and sufficient contrast-to-noise for effective serial intravascular and blood pool imaging with both SPECT and CT. The colocalization of the dendritic nuclear and X-ray contrasts offers the potential to facilitate image analysis and quantification by enabling correction for SPECT attenuation and partial volume errors at specified times with the higher resolution anatomic information provided by the circulating CT contrast. This may allow absolute quantification of intramyocardial blood volume and blood flow and may enable the ability to visualize active molecular targeting following clearance from the blood.

doi:10.1021/bc200162r (http://dx.crossref.org/10.1021/bc200162r)

 

85.          Edmiston EE, Wang F, Kalmar JH, Womer FY, Chepenik LG, Pittman B, Gueorguieva R, Hur E, Spencer L, Staib LH, Constable RT, Fulbright RK, Papademetris X and Blumberg HP. Lateral ventricle volume and psychotic features in adolescents and adults with bipolar disorder. Psychiatry research. 2011;194(3):400-2. Epub 2011/11/02. PMID: 22041535; PMCID: PMC3225709

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/3225709.

Abstract: This magnetic resonance imaging study demonstrates increased lateral ventricle volume (LVV) in adolescents and adults with bipolar disorder (BD) with psychotic symptoms, but not without psychosis, compared to healthy adolescents and adults. This suggests LVV is a morphologic feature associated with psychosis in BD, present by adolescence.

doi:10.1016/j.pscychresns.2011.07.005 (http://dx.crossref.org/10.1016/j.pscychresns.2011.07.005)

 

86.          Elhawary H, Liu H, Patel P, Norton I, Rigolo L, Papademetris X, Hata N and Golby AJ. Intraoperative real-time querying of white matter tracts during frameless stereotactic neuronavigation. Neurosurgery. 2011;68(2):506-16; discussion 16. Epub 2010/12/08. PMID: 21135719; PMCID: PMC3121103

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/3121103.

Abstract: BACKGROUND: Brain surgery faces important challenges when trying to achieve maximum tumor resection while avoiding postoperative neurological deficits. OBJECTIVE: For surgeons to have optimal intraoperative information concerning white matter (WM) anatomy, we developed a platform that allows the intraoperative real-time querying of tractography data sets during frameless stereotactic neuronavigation. METHODS: Structural magnetic resonance imaging, functional magnetic resonance imaging, and diffusion tensor imaging were performed on 5 patients before they underwent lesion resection using neuronavigation. During the procedure, the tracked surgical tool tip position was transferred from the navigation system to the 3-dimensional Slicer software package, which used this position to seed the WM tracts around the tool tip location, rendering a geometric visualization of these tracts on the preoperative images previously loaded onto the navigation system. The clinical feasibility of this approach was evaluated in 5 cases of lesion resection. In addition, system performance was evaluated by measuring the latency between surgical tool tracking and visualization of the seeded WM tracts. RESULTS: Lesion resection was performed successfully in all 5 patients. The seeded WM tracts close to the lesion and other critical structures, as defined by the functional and structural images, were interactively visualized during the intervention to determine their spatial relationships relative to the lesion and critical cortical areas. Latency between tracking and visualization of tracts was less than a second for a fiducial radius size of 4 to 5 mm. CONCLUSION: Interactive tractography can provide an intuitive way to inspect critical WM tracts in the vicinity of the surgical region, allowing the surgeon to have increased intraoperative WM information to execute the planned surgical resection.

doi:10.1227/NEU.0b013e3182036282 (http://dx.crossref.org/10.1227/NEU.0b013e3182036282)

 

87.          Granot D, Scheinost D, Markakis EA, Papademetris X and Shapiro EM. Serial monitoring of endogenous neuroblast migration by cellular MRI. NeuroImage. 2011;57(3):817-24. Epub 2011/05/17. PMID: 21571076; PMCID: PMC3129484

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/3129484.

Abstract: Endogenous neural progenitor cell migration in vivo can be monitored using MRI-based cell tracking. The current protocol is that micron sized iron oxide particles (MPIOs) are injected into the lateral ventricle proximal to the neural stem cell niche in the brain. MPIOs are endocytosed and incorporated into the neural progenitor cell population, making them visible by gradient echo MRI. Here this new method is extended to serially quantify cell migration. Initially, in vivo cell labeling methodologies were optimized, as high susceptibility effects from the MPIOs generate substantial signal loss around the injection site, masking early migratory events. Then, using improved labeling conditions, a longitudinal study was conducted over two weeks to quantify the migration of labeled progenitor cells toward the olfactory bulb (OB). By 3 days following injection, we calculated 0.26% of the volume of the OB containing labeled cells. By 8days, this volume nearly doubled to 0.49% and plateaued. These MRI results are in accordance with our data on iron quantification from the OB and with those from purely immunohistochemical studies.

doi:10.1016/j.neuroimage.2011.04.063 (http://dx.crossref.org/10.1016/j.neuroimage.2011.04.063)

 

88.          Hampson M, Scheinost D, Qiu M, Bhawnani J, Lacadie CM, Leckman JF, Constable RT and Papademetris X. Biofeedback of real-time functional magnetic resonance imaging data from the supplementary motor area reduces functional connectivity to subcortical regions. Brain connectivity. 2011;1(1):91-8. Epub 2011/01/01. PMID: 22432958.

Abstract: Recent studies have reported that biofeedback of real-time functional magnetic resonance imaging data can enable people to gain control of activity in specific parts of their brain and can alter functional connectivity between brain areas. Here we describe a study using biofeedback of real-time functional magnetic resonance imaging data to train healthy subjects to control activity in their supplementary motor area (SMA), a region of interest in Tourette syndrome (TS). Although a significant increase in control over the SMA during biofeedback was not found, subjects were able to exert significant control over the SMA in later biofeedback sessions despite not having control in the first biofeedback session. Further, changes were found in their resting state functional connectivity. Specifically, when comparing functional connectivity to the SMA before and after biofeedback, the strength of functional connectivity with subcortical regions was reduced after the biofeedback. This suggests that biofeedback may allow subjects to develop greater conscious control over activity in their SMA by reducing the influence of corticostriatothalamocortical loops on the region. This possibility is promising for TS, where aberrant dynamics in corticostriatothalamocortical loops have long been suspected to give rise to tic symptoms. Further studies in TS patients are needed.

doi:10.1089/brain.2011.0002 (http://dx.crossref.org/10.1089/brain.2011.0002)

 

89.          Harrington JK, Chahboune H, Criscione JM, Li AY, Hibino N, Yi T, Villalona GA, Kobsa S, Meijas D, Duncan DR, Devine L, Papademetris X, Shin'oka T, Fahmy TM and Breuer CK. Determining the fate of seeded cells in venous tissue-engineered vascular grafts using serial MRI. FASEB journal : official publication of the Federation of American Societies for Experimental Biology. 2011;25(12):4150-61. Epub 2011/08/19. PMID: 21846838; PMCID: PMC3236630

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/3236630.

Abstract: A major limitation of tissue engineering research is the lack of noninvasive monitoring techniques for observations of dynamic changes in single tissue-engineered constructs. We use cellular magnetic resonance imaging (MRI) to track the fate of cells seeded onto functional tissue-engineered vascular grafts (TEVGs) through serial imaging. After in vitro optimization, murine macrophages were labeled with ultrasmall superparamagnetic iron oxide (USPIO) nanoparticles and seeded onto scaffolds that were surgically implanted as inferior vena cava interposition grafts in SCID/bg mice. Serial MRI showed the transverse relaxation times (T(2)) were significantly lower immediately following implantation of USPIO-labeled scaffolds (T(2) = 44 +/- 6.8 vs. 71 +/- 10.2 ms) but increased rapidly at 2 h to values identical to control implants seeded with unlabeled macrophages (T(2) = 63 +/- 12 vs. 63 +/- 14 ms). This strongly indicates the rapid loss of seeded cells from the scaffolds, a finding verified using Prussian blue staining for iron containing macrophages on explanted TEVGs. Our results support a novel paradigm where seeded cells are rapidly lost from implanted scaffolds instead of developing into cells of the neovessel, as traditionally thought. Our findings confirm and validate this paradigm shift while demonstrating the first successful application of noninvasive MRI for serial study of cellular-level processes in tissue engineering.

doi:10.1096/fj.11-185140 (http://dx.crossref.org/10.1096/fj.11-185140)

 

90.          Ho HP, Wang F, Papademetris X, Blumberg HP and Staib LH. Integrated parcellation and normalization using DTI fasciculography. Medical image computing and computer-assisted intervention : MICCAI  International Conference on Medical Image Computing and Computer-Assisted Intervention. 2011;14(Pt 2):33-41. Epub 2011/10/15. PMID: 21995010.

Abstract: Existing methods for fiber tracking, interactive bundling and editing from Diffusion Magnetic Resonance Images (DMRI) reconstruct white matter fascicles using groups of virtual pathways. Classical numerical fibers suffer from image noise and cumulative tracking errors. 3D visualization of bundles of fibers reveals structural connectivity of the brain; however, extensive human intervention, tracking variations and errors in fiber sampling make quantitative fascicle comparison difficult. To simplify the process and offer standardized white matter samples for analysis, we propose a new integrated fascicle parcellation and normalization method that combines a generic parametrized volumetric tract model with orientation information from diffusion images. The new technique offers a tract-derived spatial parameter for each voxel within the model. Cross-subject statistics of tract data can be compared easily based on these parameters. Our implementation demonstrated interactive speed and is available to the public in a packaged application.

doi:10.1007/978-3-642-23629-7_5 (http://dx.crossref.org/10.1007/978-3-642-23629-7_5)

 

91.          Jiang Y, Zhuang ZW, Sinusas AJ, Staib LH and Papademetris X. Vessel connectivity using Murray's hypothesis. Medical image computing and computer-assisted intervention : MICCAI  International Conference on Medical Image Computing and Computer-Assisted Intervention. 2011;14(Pt 3):528-36. Epub 2011/10/19. PMID: 22003740.

Abstract: We describe a new method for vascular image analysis that incorporates a generic physiological principle to estimate vessel connectivity, which is a key issue in reconstructing complete vascular trees from image data. We follow Murray's hypothesis of the minimum work principle to formulate the problem as an optimization problem. This principle reflects a global property of any vascular network, in contrast to various local geometric properties adopted as constraints previously. We demonstrate the effectiveness of our method using a set of microCT mouse coronary images. It is shown that the performance of our method has a statistically significant improvement over the widely adopted minimum spanning tree methods that rely on local geometric constraints.

doi:10.1007/978-3-642-23626-6_65 (http://dx.crossref.org/10.1007/978-3-642-23626-6_65)

 

92.          Joshi A, Scheinost D, Globinsky R, Vives KP, Spencer DD, Staib LH and Papademetris X. Augmented inline-based navigation for stereotactic image guided neurosurgery. Biomedical Imaging: From Nano to Macro, 2011 IEEE International Symposium on. 2011:1869-72.

Abstract: Image-guided neurosurgery requires navigation in 3D using a computer-assisted surgery system that tracks surgical tools in realtime and displays their positions with respect to the preoperatively acquired images (e.g. CT, MRI, fMRI etc.) A key problem in image guided procedures is the need to navigate to specific locations highlighted in the images, such as image-derived functional areas, that have no obvious corresponding anatomical landmarks - we refer to such locations as virtual landmarks. To address these issues, we contribute a novel interactive visualization technique to provide improved feedback to surgeons - Augmented inline visualization. Based on the results of an expert evaluation, we found neurosurgeons to be 30% more accurate when using our augmented inline representation.

doi:10.1109/isbi.2011.5872772 (http://dx.crossref.org/10.1109/isbi.2011.5872772)

 

93.          Joshi A, Scheinost D, Okuda H, Belhachemi D, Murphy I, Staib LH and Papademetris X. Unified framework for development, deployment and robust testing of neuroimaging algorithms. Neuroinformatics. 2011;9(1):69-84. Epub 2011/01/21. PMID: 21249532; PMCID: PMC3066099

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/3066099.

Abstract: Developing both graphical and command-line user interfaces for neuroimaging algorithms requires considerable effort. Neuroimaging algorithms can meet their potential only if they can be easily and frequently used by their intended users. Deployment of a large suite of such algorithms on multiple platforms requires consistency of user interface controls, consistent results across various platforms and thorough testing. We present the design and implementation of a novel object-oriented framework that allows for rapid development of complex image analysis algorithms with many reusable components and the ability to easily add graphical user interface controls. Our framework also allows for simplified yet robust nightly testing of the algorithms to ensure stability and cross platform interoperability. All of the functionality is encapsulated into a software object requiring no separate source code for user interfaces, testing or deployment. This formulation makes our framework ideal for developing novel, stable and easy-to-use algorithms for medical image analysis and computer assisted interventions. The framework has been both deployed at Yale and released for public use in the open source multi-platform image analysis software--BioImage Suite (bioimagesuite.org).

doi:10.1007/s12021-010-9092-8 (http://dx.crossref.org/10.1007/s12021-010-9092-8)

 

94.          Jou RJ, Jackowski AP, Papademetris X, Rajeevan N, Staib LH and Volkmar FR. Diffusion tensor imaging in autism spectrum disorders: preliminary evidence of abnormal neural connectivity. The Australian and New Zealand journal of psychiatry. 2011;45(2):153-62. Epub 2010/12/07. PMID: 21128874; PMCID: PMC3123660

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/3123660.

Abstract: OBJECTIVE: This study indirectly tested the hypothesis that individuals with autism spectrum disorders (ASDs) have impaired neural connections between the amygdala, fusiform face area, and superior temporal sulcus, key processing nodes of the 'social brain'. This would be evidenced by abnormalities in the major fibre tracts known to connect these structures, including the inferior longitudinal fasciculus and inferior fronto-occipital fasciculus. METHOD: Magnetic resonance diffusion tensor imaging was performed on 20 right-handed males (ASD = 10, controls = 10) with a mean age 13.5 +/- 4.0 years. Subjects were group-matched according to age, full-scale IQ, handedness, and ethnicity. Fractional anisotropy was used to assess structural integrity of major fibre tracts. Voxel-wise comparison of white matter fractional anisotropy was conducted between groups using ANCOVA adjusting for age, full-scale IQ, and brain volume. Volumes of interest were identified using predetermined probability and cluster thresholds. Follow-up tractography was performed to confirm the anatomic location of all volumes of interest which were observed primarily in peri-callosal regions and the temporal lobes. RESULTS: The regions of lower fractional anisotropy, as confirmed by tractography, involved the inferior longitudinal fasciculus/inferior fronto-occipital fasciculus, superior longitudinal fasciculus, and corpus callosum/cingulum. Notably, some volumes of interest were adjacent to the fusiform face area, bilaterally, corresponding to involvement of the inferior longitudinal fasciculus. The largest effect sizes were noted for volumes of interest in the right anterior radiation of the corpus callosum/cingulum and right fusiform face area (inferior longitudinal fasciculus). CONCLUSIONS: This study provides preliminary evidence of impaired neural connectivity in the corpus callosum/cingulum and temporal lobes involving the inferior longitudinal fasciculus/inferior fronto-occipital fasciculus and superior longitudinal fasciculus in ASDs. These findings provide preliminary support for aberrant neural connectivity between the amygdala, fusiform face area, and superior temporal sulcus-temporal lobe structures critical for normal social perception and cognition.

doi:10.3109/00048674.2010.534069 (http://dx.crossref.org/10.3109/00048674.2010.534069)

 

95.          Laufer I, Negishi M, Lacadie CM, Papademetris X and Constable RT. Dissociation between the activity of the right middle frontal gyrus and the middle temporal gyrus in processing semantic priming. PloS one. 2011;6(8):e22368. Epub 2011/08/11. PMID: 21829619; PMCID: PMC3150328

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/3150328.

Abstract: The aim of this event-related functional magnetic resonance imaging (fMRI) study was to test whether the right middle frontal gyrus (MFG) and middle temporal gyrus (MTG) would show differential sensitivity to the effect of prime-target association strength on repetition priming. In the experimental condition (RP), the target occurred after repetitive presentation of the prime within an oddball design. In the control condition (CTR), the target followed a single presentation of the prime with equal probability of the target as in RP. To manipulate semantic overlap between the prime and the target both conditions (RP and CTR) employed either the onomatopoeia "oink" as the prime and the referent "pig" as the target (OP) or vice-versa (PO) since semantic overlap was previously shown to be greater in OP. The results showed that the left MTG was sensitive to release of adaptation while both the right MTG and MFG were sensitive to sequence regularity extraction and its verification. However, dissociated activity between OP and PO was revealed in RP only in the right MFG. Specifically, target "pig" (OP) and the physically equivalent target in CTR elicited comparable deactivations whereas target "oink" (PO) elicited less inhibited response in RP than in CTR. This interaction in the right MFG was explained by integrating these effects into a competition model between perceptual and conceptual effects in priming processing.

doi:10.1371/journal.pone.0022368 (http://dx.crossref.org/10.1371/journal.pone.0022368)

 

96.          Lu C, Chelikani S, Papademetris X, Knisely JP, Milosevic MF, Chen Z, Jaffray DA, Staib LH and Duncan JS. An integrated approach to segmentation and nonrigid registration for application in image-guided pelvic radiotherapy. Med Image Anal. 2011;15(5):772-85. Epub 2011/06/08. PMID: 21646038; PMCID: PMC3164526

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/3164526.

Abstract: External beam radiotherapy (EBRT) has become the preferred options for nonsurgical treatment of prostate cancer and cervix cancer. In order to deliver higher doses to cancerous regions within these pelvic structures (i.e. prostate or cervix) while maintaining or lowering the doses to surrounding non-cancerous regions, it is critical to account for setup variation, organ motion, anatomical changes due to treatment and intra-fraction motion. In previous work, manual segmentation of the soft tissues is performed and then images are registered based on the manual segmentation. In this paper, we present an integrated automatic approach to multiple organ segmentation and nonrigid constrained registration, which can achieve these two aims simultaneously. The segmentation and registration steps are both formulated using a Bayesian framework, and they constrain each other using an iterative conditional model strategy. We also propose a new strategy to assess cumulative actual dose for this novel integrated algorithm, in order to both determine whether the intended treatment is being delivered and, potentially, whether or not a plan should be adjusted for future treatment fractions. Quantitative results show that the automatic segmentation produced results that have an accuracy comparable to manual segmentation, while the registration part significantly outperforms both rigid and nonrigid registration. Clinical application and evaluation of dose delivery show the superiority of proposed method to the procedure currently used in clinical practice, i.e. manual segmentation followed by rigid registration.

doi:10.1016/j.media.2011.05.010 (http://dx.crossref.org/10.1016/j.media.2011.05.010)

 

97.          Martuzzi R, Ramani R, Qiu M, Shen X, Papademetris X and Constable RT. A whole-brain voxel based measure of intrinsic connectivity contrast reveals local changes in tissue connectivity with anesthetic without a priori assumptions on thresholds or regions of interest. NeuroImage. 2011;58(4):1044-50. Epub 2011/07/19. PMID: 21763437; PMCID: PMC3183817

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/3183817.

Abstract: The analysis of spontaneous fluctuations of functional magnetic resonance imaging (fMRI) signals has recently gained attention as a powerful tool for investigating brain circuits in a non-invasive manner. Correlation-based connectivity analysis investigates the correlations of spontaneous fluctuations of the fMRI signal either between a single seed region of interest (ROI) and the rest of the brain or between multiple ROIs. To do this, a priori knowledge is required for defining the ROI(s) and without such knowledge functional connectivity fMRI cannot be used as an exploratory tool for investigating the functional organization of the brain and its modulation under different conditions. In this work we examine two indices that provide voxel based maps reflecting the intrinsic connectivity contrast (ICC) of individual tissue elements without the need for defining ROIs and hence require no a priori information or assumptions. These voxel based ICC measures can also be used to delineate regions of interest for further functional or network analyses. The indices were applied to the study of sevoflurane anesthesia-induced alterations in intrinsic connectivity. In concordance with previous studies, the results show that sevoflurane affects different brain circuits in a heterogeneous manner. In addition ICC analyses revealed changes in regions not previously identified using conventional ROI connectivity analyses, probably because of an inappropriate choice of the ROI in the earlier studies. This work highlights the importance of such voxel based connectivity methodology.

doi:10.1016/j.neuroimage.2011.06.075 (http://dx.crossref.org/10.1016/j.neuroimage.2011.06.075)

 

98.          Sahul ZH, Mukherjee R, Song J, McAteer J, Stroud RE, Dione DP, Staib L, Papademetris X, Dobrucki LW, Duncan JS, Spinale FG and Sinusas AJ. Targeted imaging of the spatial and temporal variation of matrix metalloproteinase activity in a porcine model of postinfarct remodeling: relationship to myocardial dysfunction. Circulation Cardiovascular imaging. 2011;4(4):381-91. Epub 2011/04/21. PMID: 21505092; PMCID: PMC3140564

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/3140564.

Abstract: BACKGROUND: Matrix metalloproteinases (MMPs) are known to modulate left ventricular (LV) remodeling after a myocardial infarction (MI). However, the temporal and spatial variation of MMP activation and their relationship to mechanical dysfunction after MI remain undefined. METHODS AND RESULTS: MI was surgically induced in pigs (n = 23) and cine magnetic resonance (MR) and dual-isotope hybrid single-photon emission CT (SPECT)/CT imaging obtained using thallium-201 and a technetium-99m-labeled MMP targeted tracer ((99m)Tc-RP805) at 1, 2, and 4 weeks post-MI along with controls (n = 5). Regional myocardial strain was computed from MR images and related to MMP zymography and ex vivo myocardial (99m)Tc-RP805 retention. MMP activation as assessed by in vivo and ex vivo (99m)Tc-RP805 imaging and retention studies was increased nearly 4-fold within the infarct region at 1 week post-MI and remained elevated up to 1 month post-MI. The post-MI change in LV end-diastolic volumes was correlated with MMP activity (y = 31.34e(0.48x), P = 0.04). MMP activity was increased within the border and remote regions early post-MI, but declined over 1 month. There was a high concordance between regional (99m)Tc-RP805 uptake and ex vivo MMP-2 activity. CONCLUSIONS: A novel, multimodality, noninvasive hybrid SPECT/CT imaging approach was validated and applied for in vivo evaluation of MMP activation in combination with cine MR analysis of LV deformation. Increased (99m)Tc-RP805 retention was seen throughout the heart early post-MI and was not purely a reciprocal of thallium-201 perfusion. The (99m)Tc-RP805 SPECT/CT imaging may provide unique information regarding regional myocardial MMP activation and predict late post-MI LV remodeling.

doi:10.1161/CIRCIMAGING.110.961854 (http://dx.crossref.org/10.1161/CIRCIMAGING.110.961854)

 

99.          Suh JW, Kwon OK, Scheinost D, Sinusas AJ, Cline GW and Papademetris X. Whole body nonrigid CT-PET registration using weighted demons. Biomedical Imaging: From Nano to Macro, 2011 IEEE International Symposium on. 2011:1223-6.

Abstract: We present a new registration method for whole-body rat computed tomography (CT) image and positron emission tomography (PET) images using a weighted demons algorithm. The CT and PET images are acquired in separate scanners at different times and the inherent differences in the imaging protocols produced significant nonrigid changes between the two acquisitions in addition to heterogeneous image characteristics. In this situation, we utilized both the transmission-PET and the emission-PET images in the deformable registration process emphasizing particular regions of the moving transmission-PET image using the emission-PET image. We validated our results with nine rat image sets using M-Hausdorff distance similarity measure. We demonstrate improved performance compared to standard methods such as Demons and normalized mutual information-based non-rigid FFD registration.

doi:10.1109/isbi.2011.5872622 (http://dx.crossref.org/10.1109/isbi.2011.5872622)

 

100.        Suh JW, Scheinost D, Dione DP, Dobrucki LW, Sinusas AJ and Papademetris X. A non-rigid registration method for serial lower extremity hybrid SPECT/CT imaging. Med Image Anal. 2011;15(1):96-111. Epub 2010/09/28. PMID: 20869902; PMCID: PMC2988883

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/2988883.

Abstract: Small animal X-ray computed tomographic (microCT) imaging of the lower extremities permits evaluation of arterial growth in models of hindlimb ischemia, and when applied serially can provide quantitative information about disease progression and aid in the evaluation of therapeutic interventions. The quantification of changes in tissue perfusion and concentration of molecular markers concurrently obtained using nuclear imaging requires the ability to non-rigidly register the microCT images over time, a task made more challenging by the potentially large changes in the positions of the legs due to articulation. While non-rigid registration methods have been extensively used in the evaluation of individual organs, application in whole body imaging has been limited, primarily because the scale of possible displacements and deformations is large resulting in poor convergence of most methods. In this paper we present a new method based on the extended demons algorithm that uses a level-set representation of the body contour and skeletal structure as an input. The proposed serial registration method reflects the natural physical moving combination of mouse anatomy in which the movement of bones is the framework for body movements, and the movement of skin constrains the detailed movements of the specific segmented body regions. We applied our method to both the registration of serial microCT mouse images and the quantification of microSPECT component of the serially hybrid microCT-SPECT images demonstrating improved performance as compared to existing registration techniques.

doi:10.1016/j.media.2010.08.002 (http://dx.crossref.org/10.1016/j.media.2010.08.002)

 

101.        Delorenzo C, Papademetris X, Staib L, Vives K, Spencer D and Duncan J. Volumetric Intraoperative Brain Deformation Compensation: Model Development and Phantom Validation. IEEE transactions on medical imaging. 2012. Epub 2012/05/09. PMID: 22562728.

Abstract: During neurosurgery, nonrigid brain deformation may affect the reliability of tissue localization based on preoperative images. To provide accurate surgical guidance in these cases, preoperative images must be updated to reflect the intraoperative brain. This can be accomplished by warping these preoperative images using a biomechanical model. Due to the possible complexity of this deformation, intraoperative information is often required to guide the model solution. In this paper, a linear elastic model of the brain is developed to infer volumetric brain deformation associated with measured intraoperative cortical surface displacement. The developed model relies on known material properties of brain tissue, and does not require further knowledge about intraoperative conditions. To provide an initial estimation of volumetric model accuracy, as well as determine the models sensitivity to the specified material parameters and surface displacements, a realistic brain phantom was developed. Phantom results indicate that the linear elastic model significantly reduced localization error due to brain shift, from >16 mm to under 5 mm, on average. In addition, though in vivo quantitative validation is necessary, preliminary application of this approach to images acquired during neocortical epilepsy cases confirms the feasibility of applying the developed model to in vivo data.

doi:10.1109/TMI.2012.2197407 (http://dx.crossref.org/10.1109/TMI.2012.2197407)

 

102.        Duque A, Coman D, Carlyle BC, Bordner KA, George ED, Papademetris X, Hyder F and Simen AA. Neuroanatomical changes in a mouse model of early life neglect. Brain structure & function. 2012;217(2):459-72. Epub 2011/10/11. PMID: 21984312.

Abstract: Using a novel mouse model of early life neglect and abuse (ENA) based on maternal separation with early weaning, George et al. (BMC Neurosci 11:123, 2010) demonstrated behavioral abnormalities in adult mice, and Bordner et al. (Front Psychiatry 2(18):1-18, 2011) described concomitant changes in mRNA and protein expression. Using the same model, here we report neuroanatomical changes that include smaller brain size and abnormal inter-hemispheric asymmetry, decreases in cortical thickness, abnormalities in subcortical structures, and white matter disorganization and atrophy most severely affecting the left hemisphere. Because of the similarities between the neuroanatomical changes observed in our mouse model and those described in human survivors of ENA, this novel animal model is potentially useful for studies of human ENA too costly or cumbersome to be carried out in primates. Moreover, our current knowledge of the mouse genome makes this model particularly suited for targeted anatomical, molecular, and pharmacological experimentation not yet possible in other species.

doi:10.1007/s00429-011-0350-9 (http://dx.crossref.org/10.1007/s00429-011-0350-9)

 

103.        Hampson M, Stoica T, Saksa J, Scheinost D, Qiu M, Bhawnani J, Pittenger C, Papademetris X and Constable T. Real-time fMRI biofeedback targeting the orbitofrontal cortex for contamination anxiety. Journal of visualized experiments : JoVE. 2012(59). Epub 2012/02/03. PMID: 22297729.

Abstract: We present a method for training subjects to control activity in a region of their orbitofrontal cortex associated with contamination anxiety using biofeedback of real-time functional magnetic resonance imaging (rt-fMRI) data. Increased activity of this region is seen in relationship with contamination anxiety both in control subjects and in individuals with obsessive-compulsive disorder (OCD), a relatively common and often debilitating psychiatric disorder involving contamination anxiety. Although many brain regions have been implicated in OCD, abnormality in the orbitofrontal cortex (OFC) is one of the most consistent findings. Furthermore, hyperactivity in the OFC has been found to correlate with OCD symptom severity and decreases in hyperactivity in this region have been reported to correlate with decreased symptom severity. Therefore, the ability to control this brain area may translate into clinical improvements in obsessive-compulsive symptoms including contamination anxiety. Biofeedback of rt-fMRI data is a new technique in which the temporal pattern of activity in a specific region (or associated with a specific distributed pattern of brain activity) in a subject's brain is provided as a feedback signal to the subject. Recent reports indicate that people are able to develop control over the activity of specific brain areas when provided with rt-fMRI biofeedback. In particular, several studies using this technique to target brain areas involved in emotion processing have reported success in training subjects to control these regions. In several cases, rt-fMRI biofeedback training has been reported to induce cognitive, emotional, or clinical changes in subjects. Here we illustrate this technique as applied to the treatment of contamination anxiety in healthy subjects. This biofeedback intervention will be a valuable basic research tool: it allows researchers to perturb brain function, measure the resulting changes in brain dynamics and relate those to changes in contamination anxiety or other behavioral measures. In addition, the establishment of this method serves as a first step towards the investigation of fMRI-based biofeedback as a therapeutic intervention for OCD. Given that approximately a quarter of patients with OCD receive little benefit from the currently available forms of treatment, and that those who do benefit rarely recover completely, new approaches for treating this population are urgently needed.

doi:10.3791/3535 (http://dx.crossref.org/10.3791/3535)

 

104.        Ho HP, Wang F, Papademetris X, Blumberg HP and Staib LH. Fasciculography: robust prior-free real-time normalized volumetric neural tract parcellation. IEEE transactions on medical imaging. 2012;31(2):217-30. Epub 2011/09/15. PMID: 21914568.

Abstract: Fiber tracking in diffusion tensor magnetic resonance images (DTIs) reveals 3-D structural connectivity of the brain conveniently and thus is a viable tool for investigating neural differences. Unfortunately, local noise, image artifacts and numerical tracking errors during integration-based techniques are cumulative. Prematurely terminated fibers and under-sampled fiber bundles result in incomplete reconstruction of white matter fiber tracts and hence incorrect anatomical measurements. Quantitative cross-subject tract analysis, which is critical for abnormality detection, is complicated by inefficient and inaccurate tract reconstruction and normalization from fiber bundles. Because of the above problems, we propose a parcellation method that aims for lower sensitivity to initialization and local orientation error by directly segmenting full white matter tracts (Fasciculography), rather than reconstructing individual curves, from diffusion tensor fields. A fast, robust volumetric, and intrinsically normalized solution is achieved by noise-filtering using a generic parametrized tract model to prevent premature tract termination. At the same time, orientation information reduces the search space, significantly speeding up the tract parcellation process with less human intervention. Detailed comparisons against streamline tracking, shortest-path tracking, and nonrigid registration using synthetic and real DTIs confirmed the superior properties of Fasciculography. Since a normalized tract can be delineated interactively in a just few seconds using the proposed method, accurate high volume tract comparisons become feasible.

doi:10.1109/TMI.2011.2167629 (http://dx.crossref.org/10.1109/TMI.2011.2167629)

 

105.        Suh JW, Kwon OK, Scheinost D, Sinusas AJ, Cline GW and Papademetris X. CT-PET weighted image fusion for separately scanned whole body rat. Medical physics. 2012;39(1):533-42. Epub 2012/01/10. PMID: 22225323; PMCID: PMC3266828

Pubmed Central Full Text: www.ncbi.nlm.nih.gov/pmc/articles/3266828.

Abstract: PURPOSE: The limited resolution and lack of spatial information in positron emission tomography (PET) images require the complementary anatomic information from the computed tomography (CT) and/or magnetic resonance imaging (MRI). Therefore, multimodality image fusion techniques such as PET/CT are critical in mapping the functional images to structural images and thus facilitate the interpretation of PET studies. In our experimental situation, the CT and PET images are acquired in separate scanners at different times and the inherent differences in the imaging protocols produce significant nonrigid changes between the two acquisitions in addition to dissimilar image characteristics. The registration conditions are also poor because CT images have artifacts due to the limitation of current scanning settings, while PET images are very blurry (in transmission-PET) and have vague anatomical structure boundaries (in emission-PET). METHODS: The authors present a new method for whole body small animal multimodal registration. In particular, the authors register whole body rat CT image and PET images using a weighted demons algorithm. The authors use both the transmission-PET and the emission-PET images in the registration process emphasizing particular regions of the moving transmission-PET image using the emission-PET image. After a rigid transformation and a histogram matching between the CT and the transmission-PET images, the authors deformably register the transmission-PET image to the CT image with weights based on the intensity-normalized emission-PET image. For the deformable registration process, the authors develop a weighted demons registration method that can give preferences to particular regions of the input image using a weight image. RESULTS: The authors validate the results with nine rat image sets using the M-Hausdorff distance (M-HD) similarity measure with different outlier-suppression parameters (OSP). In comparison with standard methods such as the regular demons and the normalized mutual information (NMI)-based nonrigid free-form deformation (FFD) registration, the proposed weighted demons registration method shows average M-HD errors: 3.99 +/- 1.37 (OSP = 10), 5.04 +/- 1.59 (OSP = 20) and 5.92 +/- 1.61 (OSP = infinity) with statistical significance (p < 0.0003) respectively, while NMI-based nonrigid FFD has average M-HD errors: 5.74 +/- 1.73 (OSP = 10), 7.40 +/- 7.84 (OSP = 20) and 9.83 +/- 4.13 (OSP = infinity), and the regular demons has average M-HD errors: 6.79 +/- 0.83 (OSP = 10), 9.19 +/- 2.39 (OSP = 20) and 11.63 +/- 3.99 (OSP = infinity), respectively. In addition to M-HD comparisons, the visual comparisons on the faint-edged region between the CT and the aligned PET images also show the encouraging improvements over the other methods. CONCLUSIONS: In the whole body multimodal registration between CT and PET images, the utilization of both the transmission-PET and the emission-PET images in the registration process by emphasizing particular regions of the transmission-PET image using an emission-PET image is effective. This method holds promise for other image fusion applications where multiple (more than two) input images should be registered into a single informative image.

doi:10.1118/1.3672167 (http://dx.crossref.org/10.1118/1.3672167)