Riemannian Statistical Analysis of Cortical Geometry with Robustness to Partial Homology and Misalignment

Typical studies of the geometry of the cerebral cortical structure focus on either cortical folding or thickness. They rely on spatial normalization, but use cortical descriptors that are sensitive to misregistration arising from the well-known problems of partial homologies between subject brains and local optima in nonlinear registration. In contrast to these approaches, we propose a novel framework for studying the geometry of the entire cortical sheet, subsuming its folding and thickness characteristics. We propose a novel descriptor of local cortical geometry to increase robustness to partial homology and misregistration. The proposed descriptor lies on a Riemannian manifold, and we describe a method for hypothesis testing on manifolds for cross-sectional studies. Results on simulated and clinical data show the benefits of the proposed approach for detecting between-group differences with greater accuracy and consistency.

Placental ABC Transporters: Biological Impact and Pharmaceutical Significance

The human placenta fulfills a variety of essential functions during prenatal life. Several ABC transporters are expressed in the human placenta, where they play a role in the transport of endogenous compounds and may protect the fetus from exogenous compounds such as therapeutic agents, drugs of abuse, and other xenobiotics. To date, considerable progress has been made toward understanding ABC transporters in the placenta. Recent studies on the expression and functional activities are discussed. This review discusses the placental expression and functional roles of several members of ABC transporter subfamilies B, C, and G including MDR1/P-glycoprotein, the MRPs, and BCRP, respectively. Since placental ABC transporters modulate fetal exposure to various compounds, an understanding of their functional and regulatory mechanisms will lead to more optimal medication use when necessary in pregnancy.

Automated MRI Volumetric Analysis in Patients with Rasmussen Syndrome

BACKGROUND AND PURPOSE

Rasmussen syndrome, also known as Rasmussen encephalitis, is typically associated with volume loss of the affected hemisphere of the brain. Our aim was to apply automated quantitative volumetric MR imaging analyses to patients diagnosed with Rasmussen encephalitis, to determine the predictive value of lobar volumetric measures and to assess regional atrophy differences as well as monitor disease progression by using these measures.

MATERIALS AND METHODS

Nineteen patients (42 scans) with diagnosed Rasmussen encephalitis were studied. We used 2 control groups: one with 42 age- and sex-matched healthy subjects and the other with 42 epileptic patients without Rasmussen encephalitis with the same disease duration as patients with Rasmussen encephalitis. Volumetric analysis was performed on T1-weighted images by using BrainSuite. Ratios of volumes from the affected hemisphere divided by those from the unaffected hemisphere were used as input to a logistic regression classifier, which was trained to discriminate patients from controls. Using the classifier, we compared the predictive accuracy of all the volumetric measures. These ratios were used to further assess regional atrophy differences and correlate with epilepsy duration.

RESULTS

Interhemispheric and frontal lobe ratios had the best prediction accuracy for separating patients with Rasmussen encephalitis from healthy controls and patient controls without Rasmussen encephalitis. The insula showed significantly more atrophy compared with all the other cortical regions. Patients with longitudinal scans showed progressive volume loss in the affected hemisphere. Atrophy of the frontal lobe and insula correlated significantly with epilepsy duration.

CONCLUSIONS

Automated quantitative volumetric analysis provides accurate separation of patients with Rasmussen encephalitis from healthy controls and epileptic patients without Rasmussen encephalitis, and thus may assist the diagnosis of Rasmussen encephalitis. Volumetric analysis could also be included as part of follow-up for patients with Rasmussen encephalitis to assess disease progression.

Interactive effects of BDNF Val66Met genotype and trauma on limbic brain anatomy in childhood

Childhood trauma is a major precipitating factor in psychiatric disease. Emerging data suggest that stress susceptibility is genetically determined, and that risk is mediated by changes in limbic brain circuitry. There is a need to identify markers of disease vulnerability, and it is critical that these markers be investigated in childhood and adolescence, a time when neural networks are particularly malleable and when psychiatric disorders frequently emerge. In this preliminary study, we evaluated whether a common variant in the brain-derived neurotrophic factor (BDNF) gene (Val66Met; rs6265) interacts with childhood trauma to predict limbic gray matter volume in a sample of 55 youth high in sociodemographic risk. We found trauma-by-BDNF interactions in the right subcallosal area and right hippocampus, wherein BDNF-related gray matter changes were evident in youth without histories of trauma. In youth without trauma exposure, lower hippocampal volume was related to higher symptoms of anxiety. These data provide preliminary evidence for a contribution of a common BDNF gene variant to the neural correlates of childhood trauma among high-risk urban youth. Altered limbic structure in early life may lay the foundation for longer term patterns of neural dysfunction, and hold implications for understanding the psychiatric and psychobiological consequences of traumatic stress on the developing brain.

Impact of Early and Late Visual Deprivation on the Structure of the Corpus Callosum: A Study Combining Thickness Profile with Surface Tensor-Based Morphometry

Blindness represents a unique model to study how visual experience may shape the development of brain organization. Exploring how the structure of the corpus callosum (CC) reorganizes ensuing visual deprivation is of particular interest due to its important functional implication in vision (e.g., via the splenium of the CC). Moreover, comparing early versus late visually deprived individuals has the potential to unravel the existence of a sensitive period for reshaping the CC structure. Here, we develop a novel framework to capture a complete set of shape differences in the CC between congenitally blind (CB), late blind (LB) and sighted control (SC) groups. The CCs were manually segmented from T1-weighted brain MRI and modeled by 3D tetrahedral meshes. We statistically compared the combination of local area and thickness at each point between subject groups. Differences in area are found using surface tensor-based morphometry; thickness is estimated by tracing the streamlines in the volumetric harmonic field. Group differences were assessed on this combined measure using Hotelling's T(2) test. Interestingly, we observed that the total callosal volume did not differ between the groups. However, our fine-grained analysis reveals significant differences mostly localized around the splenium areas between both blind groups and the sighted group (general effects of blindness) and, importantly, specific dissimilarities between the LB and CB groups, illustrating the existence of a sensitive period for reorganization. The new multivariate statistics also gave better effect sizes for detecting morphometric differences, relative to other statistics. They may boost statistical power for CC morphometric analyses.

21: DETERMINANTS OF VASCULAR INFLAMMATION BY 18-FLUORODEOXYGLUCOSE PET/MRI: FINDINGS FROM THE PSORIASIS, ATHEROSCLEROSIS AND CARDIOMETABOLIC DISEASE INITIATIVE

Purpose of Study

Psoriasis (PSO), a chronic inflammatory disease associated with increased CV risk, provides a clinical human model to study inflammatory atherogenesis. We aimed to assess the major determinants of vascular inflammation (VI) measured by 18FDG PET-MRI in a well-phenotyped PSO cohort.

Methods Used

124 consecutive patients with PSO underwent 18FDG PET-MRI scans. We used target-to-background ratio to quantify VI 120 minutes post FDG injection. Homeostatic model assessment of insulin resistance (HOMA-IR) was measured, along with cholesterol efflux capacity (CEC) and HDL particle concentration by NMR (Liposcience) fasting.

Summary of Results

Our cohort was middle aged (mean 49±13.3 years) with mild to moderate PSO, and low CV risk (median Framingham Risk Score (FRS) 2, IQR 2–6). PSO was associated with increased VI (β=0.27, p<0.005), compared to healthy controls. VI was associated with HOMA-IR (β=0.26, p<0.001), CEC (β=−0.12, p=0.04) and HDL particle concentration (β=−0.19, p=0.003) beyond traditional CV risk factors (age, gender, FRS and BMI). Among these, HOMA-IR provided maximum incremental value in predicting VI beyond traditional risk factors (χ2=39.36, p<0.001).

Conclusions

VI by FDG PET MRI is associated with traditional CV risk factors and cardiometabolic parameters. Insulin resistance and CEC were most strongly associated with VI by 18FDG PET-MRI beyond traditional CV risk factors and BMI in PSO suggesting that cardiometabolic disease increases CV risk in PSO.

Abstract 21 Figure 1

18: IMPROVEMENT IN PSORIASIS SKIN DISEASE SEVERITY IS ASSOCIATED WITH REDUCTION OF CORONARY PLAQUE BURDEN

Purpose of Study

Psoriasis (PSO), a chronic inflammatory disease associated with increased cardiovascular (CV) risk, provides a clinical human model to study inflammatory atherogenesis. While PSO severity is associated with both in vivo vascular disease and future CV risk, the longitudinal impact of PSO severity on coronary disease progression is unknown. We hypothesized that an improvement in PSO severity may lead to a reduction in coronary plaque burden by coronary CT angiography (CCTA).

Methods Used

Consecutively recruited PSO patients (N=50) underwent CCTA (320 detector row, Toshiba) and cardiometabolic profiling at baseline and 1-year follow-up. Total (TB) and non-calcified (NCB) coronary plaque burden were quantified using QAngio (Medis, Netherlands). PSO severity was measured as the psoriasis area severity index (PASI). The longitudinal change in coronary plaque burden was analyzed with unadjusted and adjusted regression.

Summary of Results

The cohort had a low Framingham Risk Score and mild to moderate PSO. Patients whose PSO severity improved (ΔPASI −27%; p<0.001) (N=33) had significant improvement in TB (β=0.40, p=0.003) and NCB (β=0.49, p<0.001) (table 1), beyond adjustment for traditional CV risk factors, BMI, statin use, & systemic/biologic PSO therapy.

Conclusions

Improvement in PSO severity was associated with improvement in coronary plaque burden by CCTA. Our study suggests that a reduction in skin inflammation may reduce the progression of early, non-calcified coronary plaque. Larger studies are needed to confirm these findings.

Abstract 18 Figure 1

*P-value is calculated by comparing baseline and 1-year follow-up values for variables using paired t-test for continuous variables, and Pearson's chi-squared test for categorical variables. All values are expressed as Mean±SD, unless specified otherwise. PASI: Psoriasis Area Severity Index.

Registration-Based Morphometry for Shape Analysis of the Bones of the Human Wrist

We present a method that quantifies point-wise changes in surface morphology of the bones of the human wrist. The proposed method, referred to as Registration-based Bone Morphometry (RBM), consists of two steps: an atlas selection step and an atlas warping step. The atlas for individual wrist bones was selected based on the shortest ℓ2 distance to the ensemble of wrist bones from a database of a healthy population of subjects. The selected atlas was then warped to the corresponding bones of individuals in the population using a non-linear registration method based on regularized ℓ2 distance minimization. The displacement field thus calculated showed local differences in bone shape that then were used for the analysis of group differences. Our results indicate that RBM has potential to provide a standardized approach to shape analysis of bones of the human wrist. We demonstrate the performance of RBM for examining group differences in wrist bone shapes based on sex and between those of the right and left wrists in healthy individuals. We also present data to show the application of RBM for tracking bone erosion status in rheumatoid arthritis.

Structure-Activity Relationships of the Peptide Kappa Opioid Receptor Antagonist Zyklophin

The dynorphin (Dyn) A analogue zyklophin ([N-benzyl-Tyr(1)-cyclo(d-Asp(5),Dap(8))]dynorphin A(1-11)NH2) is a kappa opioid receptor (KOR)-selective antagonist in vitro, is active in vivo, and antagonizes KOR in the CNS after systemic administration. Hence, we synthesized zyklophin analogues to explore the structure-activity relationships of this peptide. The synthesis of selected analogues required modification to introduce the N-terminal amino acid due to poor solubility and/or to avoid epimerization of this residue. Among the N-terminal modifications, the N-phenethyl and N-cyclopropylmethyl substitutions resulted in analogues with the highest KOR affinities. Pharmacological results for the alanine-substituted analogues indicated that Phe(4) and Arg(6), but interestingly not the Tyr(1) phenol, are important for zyklophin's KOR affinity and that Arg(7) was important for KOR antagonist activity. In the GTPγS assay, while all of the cyclic analogues exhibited negligible KOR efficacy, the N-cyclopropylmethyl-Tyr(1) and N-benzyl-Phe(1) analogues were 28- and 11-fold more potent KOR antagonists, respectively, than zyklophin.

How age of acquisition influences brain architecture in bilinguals

In the present study, we explored how Age of Acquisition (AoA) of L2 affected brain structures in bilingual individuals. Thirty-six native English speakers who were bilingual were scanned with high resolution MRI. After MRI signal intensity inhomogeneity correction, we applied both voxel-based morphometry (VBM) and surface-based morphometry (SBM) approaches to the data. VBM analysis was performed using FSL's standard VBM processing pipeline. For the SBM analysis, we utilized a semi-automated sulci delineation procedure, registered the brains to an atlas, and extracted measures of twenty four pre-selected regions of interest. We addressed three questions: (1) Which areas are more susceptible to differences in AoA? (2) How do AoA, proficiency and current level of exposure work together in predicting structural differences in the brain? And (3) What is the direction of the effect of AoA on regional volumetric and surface measures? Both VBM and SBM results suggested that earlier second language exposure was associated with larger volumes in the right parietal cortex. Consistently, SBM showed that the cortical area of the right superior parietal lobule increased as AoA decreased. In contrast, in the right pars orbitalis of the inferior frontal gyrus, AoA, proficiency, and current level of exposure are equally important in accounting for the structural differences. We interpret our results in terms of current theory and research on the effects of L2 learning on brain structures and functions.

Reproducibility of brain-cognition relationships using three cortical surface-based protocols: An exhaustive analysis based on cortical thickness

People differ in their cognitive functioning. This variability has been exhaustively examined at the behavioral, neural and genetic level to uncover the mechanisms by which some individuals are more cognitively efficient than others. Studies investigating the neural underpinnings of interindividual differences in cognition aim to establish a reliable nexus between functional/structural properties of a given brain network and higher order cognitive performance. However, these studies have produced inconsistent results, which might be partly attributed to methodological variations. In the current study, 82 healthy young participants underwent MRI scanning and completed a comprehensive cognitive battery including measurements of fluid, crystallized, and spatial intelligence, along with working memory capacity/executive updating, controlled attention, and processing speed. The cognitive scores were obtained by confirmatory factor analyses. T1 -weighted images were processed using three different surface-based morphometry (SBM) pipelines, varying in their degree of user intervention, for obtaining measures of cortical thickness (CT) across the brain surface. Distribution and variability of CT and CT-cognition relationships were systematically compared across pipelines and between two cognitively/demographically matched samples to overcome potential sources of variability affecting the reproducibility of findings. We demonstrated that estimation of CT was not consistent across methods. In addition, among SBM methods, there was considerable variation in the spatial pattern of CT-cognition relationships. Finally, within each SBM method, results did not replicate in matched subsamples.

An equal start: absence of group differences in cognitive, social, and neural measures prior to music or sports training in children

Several studies comparing adult musicians and non-musicians have provided compelling evidence for functional and anatomical differences in the brain systems engaged by musical training. It is not known, however, whether those differences result from long-term musical training or from pre-existing traits favoring musicality. In an attempt to begin addressing this question, we have launched a longitudinal investigation of the effects of childhood music training on cognitive, social and neural development. We compared a group of 6- to 7-year old children at the start of intense after-school musical training, with two groups of children: one involved in high intensity sports training but not musical training, another not involved in any systematic training. All children were tested with a comprehensive battery of cognitive, motor, musical, emotional, and social assessments and underwent magnetic resonance imaging and electroencephalography. Our first objective was to determine whether children who participate in musical training were different, prior to training, from children in the control groups in terms of cognitive, motor, musical, emotional, and social behavior measures as well as in structural and functional brain measures. Our second objective was to determine whether musical skills, as measured by a music perception assessment prior to training, correlates with emotional and social outcome measures that have been shown to be associated with musical training. We found no neural, cognitive, motor, emotional, or social differences among the three groups. In addition, there was no correlation between music perception skills and any of the social or emotional measures. These results provide a baseline for an ongoing longitudinal investigation of the effects of music training.

Skull-stripping with machine learning deformable organisms

BACKGROUND

Segmentation methods for medical images may not generalize well to new data sets or new tasks, hampering their utility. We attempt to remedy these issues using deformable organisms to create an easily customizable segmentation plan. We validate our framework by creating a plan to locate the brain in 3D magnetic resonance images of the head (skull-stripping).

NEW METHOD

Our method borrows ideas from artificial life to govern a set of deformable models. We use control processes such as sensing, proactive planning, reactive behavior, and knowledge representation to segment an image. The image may have landmarks and features specific to that dataset; these may be easily incorporated into the plan. In addition, we use a machine learning method to make our segmentation more accurate.

RESULTS

Our method had the least Hausdorff distance error, but included slightly less brain voxels (false negatives). It also had the lowest false positive error and performed on par to skull-stripping specific method on other metrics.

COMPARISON WITH EXISTING METHOD(S)

We tested our method on 838 T1-weighted images, evaluating results using distance and overlap error metrics based on expert gold standard segmentations. We evaluated the results before and after the learning step to quantify its benefit; we also compare our results to three other widely used methods: BSE, BET, and the Hybrid Watershed algorithm.

CONCLUSIONS

Our framework captures diverse categories of information needed for brain segmentation and will provide a foundation for tackling a wealth of segmentation problems.

Non-rigid registration of serial dedicated breast CT, longitudinal dedicated breast CT and PET/CT images using the diffeomorphic demons method

RATIONALE AND OBJECTIVES

Dedicated breast CT and PET/CT scanners provide detailed 3D anatomical and functional imaging data sets and are currently being investigated for applications in breast cancer management such as diagnosis, monitoring response to therapy and radiation therapy planning. Our objective was to evaluate the performance of the diffeomorphic demons (DD) non-rigid image registration method to spatially align 3D serial (pre- and post-contrast) dedicated breast computed tomography (CT), and longitudinally-acquired dedicated 3D breast CT and positron emission tomography (PET)/CT images.

METHODS

The algorithmic parameters of the DD method were optimized for the alignment of dedicated breast CT images using training data and fixed. The performance of the method for image alignment was quantitatively evaluated using three separate data sets; (1) serial breast CT pre- and post-contrast images of 20 women, (2) breast CT images of 20 women acquired before and after repositioning the subject on the scanner, and (3) dedicated breast PET/CT images of 7 women undergoing neo-adjuvant chemotherapy acquired pre-treatment and after 1 cycle of therapy.

RESULTS

The DD registration method outperformed no registration (p < 0.001) and conventional affine registration (p ≤ 0.002) for serial and longitudinal breast CT and PET/CT image alignment. In spite of the large size of the imaging data, the computational cost of the DD method was found to be reasonable (3-5 min).

CONCLUSIONS

Co-registration of dedicated breast CT and PET/CT images can be performed rapidly and reliably using the DD method. This is the first study evaluating the DD registration method for the alignment of dedicated breast CT and PET/CT images.

Global point signature for shape analysis of carpal bones

We present a method based on spectral theory for the shape analysis of carpal bones of the human wrist. We represent the cortical surface of the carpal bone in a coordinate system based on the eigensystem of the two-dimensional Helmholtz equation. We employ a metric--global point signature (GPS)--that exploits the scale and isometric invariance of eigenfunctions to quantify overall bone shape. We use a fast finite-element-method to compute the GPS metric. We capitalize upon the properties of GPS representation--such as stability, a standard Euclidean (ℓ(2)) metric definition, and invariance to scaling, translation and rotation--to perform shape analysis of the carpal bones of ten women and ten men from a publicly-available database. We demonstrate the utility of the proposed GPS representation to provide a means for comparing shapes of the carpal bones across populations.

Improved B0 -distortion correction in diffusion MRI using interlaced q-space sampling and constrained reconstruction

PURPOSE

To enable high-quality correction of susceptibility-induced geometric distortion artifacts in diffusion magnetic resonance imaging (MRI) images without increasing scan time.

THEORY AND METHODS

A new method for distortion correction is proposed based on subsampling a generalized version of the state-of-the-art reversed-gradient distortion correction method. Rather than acquire each q-space sample multiple times with different distortions (as in the conventional reversed-gradient method), we sample each q-space point once with an interlaced sampling scheme that measures different distortions at different q-space locations. Distortion correction is achieved using a novel constrained reconstruction formulation that leverages the smoothness of diffusion data in q-space.

RESULTS

The effectiveness of the proposed method is demonstrated with simulated and in vivo diffusion MRI data. The proposed method is substantially faster than the reversed-gradient method, and can also provide smaller intensity errors in the corrected images and smaller errors in derived quantitative diffusion parameters.

CONCLUSION

The proposed method enables state-of-the-art distortion correction performance without increasing data acquisition time.

Canonical Granger causality between regions of interest

Estimating and modeling functional connectivity in the brain is a challenging problem with potential applications in the understanding of brain organization and various neurological and neuropsychological conditions. An important objective in connectivity analysis is to determine the connections between regions of interest in the brain. However, traditional functional connectivity analyses have frequently focused on modeling interactions between time series recordings at individual sensors, voxels, or vertices despite the fact that a single region of interest will often include multiple such recordings. In this paper, we present a novel measure of interaction between regions of interest rather than individual signals. The proposed measure, termed canonical Granger causality, combines ideas from canonical correlation and Granger causality analysis to yield a measure that reflects directed causality between two regions of interest. In particular, canonical Granger causality uses optimized linear combinations of signals from each region of interest to enable accurate causality measurements from substantially less data compared to alternative multivariate methods that have previously been proposed for this scenario. The optimized linear combinations are obtained using a variation of a technique developed for optimization on the Stiefel manifold. We demonstrate the advantages of canonical Granger causality in comparison to alternative causality measures for a range of different simulated datasets. We also apply the proposed measure to local field potential data recorded in a macaque brain during a visuomotor task. Results demonstrate that canonical Granger causality can be used to identify causal relationships between striate and prestriate cortexes in cases where standard Granger causality is unable to identify statistically significant interactions.

MORPHOMETRY FOR EARLY MONITORING OF TREATMENT RESPONSE IN RHEUMATOID ARTHRITIS

New aggressive therapeutic options have recently become available to treat inflammatory arthritis (IA) and rheumatoid arthritis in particular. These treatments not only control joint destruction, they may also aid in new bone formation at sites of eroded bone. Separation of non-responders from responders to these treatments, is critical, and is known to lead to reduced disease burden, toxicity, side-effects and overall cost. The bones of the wrist are early targets of IA and are known to show response to therapy early. In this paper, we develop a method to quantify point-wise erosive changes of wrist bones in IA patients undergoing treatment. The method employs 3D registration-based morphometric analysis. Our results indicate that the proposed method has potential to improve sensitivity to small, early changes in bone erosion status. This study has potential to provide new imaging biomarkers to be used in clinical trials evaluating the efficacy of new arthritis drugs.

Correcting Susceptibility-Induced Distortion in Diffusion-Weighted MRI using Constrained Nonrigid Registration

Echo Planar Imaging (EPI) is the standard pulse sequence used in fast diffusion-weighted magnetic resonance imaging (MRI), but is sensitive to susceptibility-induced inhomogeneities in the main B₀ magnetic field. In diffusion MRI of the human head, this leads to geometric distortion of the brain in reconstructed diffusion images, and a lack of correspondence with undistorted high-resolution MRI scans that are used to define the subject anatomy. In this study, we have tested an approach to estimate and correct this distortion of using a non-linear registration framework based on mutual-information. We use the commonly acquired anatomical image as the registration-template and constrain the registration using spatial regularization and physics-based information about the characteristics of the distortion, but without requiring any additional data collection. Results are shown for simulated and experimental data.

Endoscopic excision of Juvenile nasopharyngeal angiofibroma - A comprehensive approach

OBJECTIVE

Endoscopie excision of Juvenile Nasopharyngeal Angiofibroma (JNA) was carried out with (he objective of minimizing blood loss and attempting a complete excision of the tumor under direct vision with the help of Hopkins telescopes.

STUDY DESIGN

A prospective 4 year study of 23 cases of JNA treated by endoscopie excision is presented. Of these, 18 were treated by endoscopie excision alone. The remaining 5 were treated with a two staged approach either by mid-facial degloving followed by endoscopy or by 2 endoscopie procedures.

RESULTS

The tumor was excised completely in 17 out of the total 18 cases that were treated exclusively by endoscopy. One case has shown a recurrence. The 5 cases treated by the staged approach represented very large tumours or tumours with intra-cranial extensions. In I of these cases, inoperable tumor remnant engulfing the internal carotid artery was treated by radiotherapy post-operatively.

CONCLUSION

With successful excision of JNA in all but one case, we could reasonably conclude, that endoscopie excision of JNA could become a safer and a more precise alternative to open surgery provided it is practiced judiciously by surgeons who have considerable experience in endoscopie surgery and the necessary backup to convert to open surgery should the need arise.

Frontal information flow and connectivity in psychopathy

Despite accumulating evidence of structural deficits in individuals with psychopathy, especially in frontal regions, our understanding of systems-level disturbances in cortical networks remains limited. We applied novel graph theory-based methods to assess information flow and connectivity based on cortical thickness measures in 55 individuals with psychopathy and 47 normal controls. Compared with controls, the psychopathy group showed significantly altered interregional connectivity patterns. Furthermore, bilateral superior frontal cortices in the frontal network were identified as information flow control hubs in the psychopathy group in contrast to bilateral inferior frontal and medial orbitofrontal cortices as network hubs of the controls. Frontal information flow and connectivity may have a significant role in the neuropathology of psychopathy.

Automatic intra-subject registration-based segmentation of abdominal fat from water-fat MRI

PURPOSE

To develop an automatic registration-based segmentation algorithm for measuring abdominal adipose tissue depot volumes and organ fat fraction content from three-dimensional (3D) water-fat MRI data, and to evaluate its performance against manual segmentation.

MATERIALS AND METHODS

Data were obtained from 11 subjects at two time points with intermediate repositioning, and from four subjects before and after a meal with repositioning. Imaging was performed on a 3 Tesla MRI, using the IDEAL chemical-shift water-fat pulse sequence. Adipose tissue (subcutaneous--SAT, visceral--VAT) and organs (liver, pancreas) were manually segmented twice for each scan by a single trained observer. Automated segmentations of each subject's second scan were generated using a nonrigid volume registration algorithm for water-fat MRI images that used a b-spline basis for deformation and minimized image dissimilarity after the deformation. Manual and automated segmentations were compared using Dice coefficients and linear regression of SAT and VAT volumes, organ volumes, and hepatic and pancreatic fat fractions (HFF, PFF).

RESULTS

Manual segmentations from the 11 repositioned subjects exhibited strong repeatability and set performance benchmarks. The average Dice coefficients were 0.9747 (SAT), 0.9424 (VAT), 0.9404 (liver), and 0.8205 (pancreas); the linear correlation coefficients were 0.9994 (SAT volume), 0.9974 (VAT volume), 0.9885 (liver volume), 0.9782 (pancreas volume), 0.9996 (HFF), and 0.9660 (PFF). When comparing manual and automated segmentations, the average Dice coefficients were 0.9043 (SAT volume), 0.8235 (VAT), 0.8942 (liver), and 0.7168 (pancreas); the linear correlation coefficients were 0.9493 (SAT volume), 0.9982 (VAT volume), 0.9326 (liver volume), 0.8876 (pancreas volume), 0.9972 (HFF), and 0.8617 (PFF). In the four pre- and post-prandial subjects, the Dice coefficients were 0.9024 (SAT), 0.7781 (VAT), 0.8799 (liver), and 0.5179 (pancreas); the linear correlation coefficients were 0.9889, 0.9902 (SAT, and VAT volume), 0.9523 (liver volume), 0.8760 (pancreas volume), 0.9991 (HFF), and 0.6338 (PFF).

CONCLUSION

Automated intra-subject registration-based segmentation is potentially suitable for the quantification of abdominal and organ fat and achieves comparable quantitative endpoints with respect to manual segmentation.

A Method for Automated Cortical Surface Registration and Labeling

Registration and delineation of anatomical features in MRI of the human brain play an important role in the investigation of brain development and disease. Accurate, automatic and computationally efficient cortical surface registration and delineation of surface-based landmarks, including regions of interest (ROIs) and sulcal curves (sulci), remain challenging problems due to substantial variation in the shapes of these features across populations. We present a method that performs a fast and accurate registration, labeling and sulcal delineation of brain images. The new method presented in this paper uses a multiresolution, curvature based approach to perform a registration of a subject brain surface model to a delineated atlas surface model; the atlas ROIs and sulcal curves are then mapped to the subject brain surface. A geodesic curvature flow on the cortical surface is then used to refine the locations of the sulcal curves sulci and label boundaries further, such that they follow the true sulcal fundi more closely. The flow is formulated using a level set based method on the cortical surface, which represents the curves as zero level sets. We also incorporate a curvature based weighting that drives the curves to the bottoms of the sulcal valleys in the cortical folds. Finally, we validate our new approach by comparing sets of automatically delineated sulcal curves it produced to corresponding sets of manually delineated sulcal curves. Our results indicate that the proposed method is able to find these landmarks accurately.

Diffeomorphic sulcal shape analysis on the cortex

We present a diffeomorphic approach for constructing intrinsic shape atlases of sulci on the human cortex. Sulci are represented as square-root velocity functions of continuous open curves in R³, and their shapes are studied as functional representations of an infinite-dimensional sphere. This spherical manifold has some advantageous properties--it is equipped with a Riemannian L² metric on the tangent space and facilitates computational analyses and correspondences between sulcal shapes. Sulcal shape mapping is achieved by computing geodesics in the quotient space of shapes modulo scales, translations, rigid rotations, and reparameterizations. The resulting sulcal shape atlas preserves important local geometry inherently present in the sample population. The sulcal shape atlas is integrated in a cortical registration framework and exhibits better geometric matching compared to the conventional euclidean method. We demonstrate experimental results for sulcal shape mapping, cortical surface registration, and sulcal classification for two different surface extraction protocols for separate subject populations.