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)
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)
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)
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)
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)
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)
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.
)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)
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)