Mapping Cortical Morphology in Youth With Velocardiofacial (22q11.2 Deletion) Syndrome

Objective: Velo-cardio-facial syndrome (VCFS; 22q11.2 deletion syndrome) represents one of the highest known risk factors for schizophrenia. Insofar as up to thirty percent of individuals with this genetic disorder develop schizophrenia, VCFS constitutes a unique, etiologically homogeneous model for understanding the pathogenesis of schizophrenia. Method: Using a longitudinal, case-control design, we acquired anatomic magnetic resonance images to investigate both cross-sectional and longitudinal alterations in surface cortical morphology in a cohort of adolescents with VCFS and age-matched typical controls. All participants were scanned at two time points. Results: Relative to controls, youth with VCFS exhibited alterations in inferior frontal, dorsal frontal, occipital, and cerebellar brain regions at both time points. We observed little change over time in surface morphology of either study group. However, within the VCFS group only, worsening psychosocial functioning over time was associated with Time 2 surface contractions in left middle and inferior temporal gyri. Further, prodromal symptoms at Time 2 were associated with surface contractions in left and right orbitofrontal, temporal and cerebellar regions, as well as surface protrusions of supramarginal gyrus. Conclusions: These findings advance our understanding of cortical disturbances in VCFS that produce vulnerability for psychosis in this high risk population

Morphological Abnormalities of the Thalamus in Youths With Attention Deficit Hyperactivity Disorder

The role of the thalamus in the genesis of attention deficit hyperactivity disorder (ADHD) remains poorly understood. The authors used anatomical MRI to examine the morphology of the thalamus in youths with ADHD and healthy comparison youths

In Vivo Human Right Ventricle Shape and Kinematic Analysis with and without Pulmonary Hypertension

Pulmonary hypertension (PH) is a severe cardio-pulmonary illness which has been commonly observed to induce substantial and ultimately deleterious changes to the human right ventricle (RV) shape and function. As such, the functional state of the RV is thought to be a major determinant of symptoms and survival rates for PH. However, there has been little success to-date to identify clinically obtainable metrics of RV shape and deformation as a means to detect the onset and progression of PH. This difficulty is largely the result of the absence of a proven approach that is generally applicable for consistent and reliable quantitative analysis of anatomical shapes, particularly the RV, between patients and over time. Therefore, a computational framework which can quantitatively analyze RV shape and deformation could be a key to assist in clinically detecting the onset and progression of PH. Statistical shape analysis techniques were developed, implemented, and assessed to analyze variations in human RV endocardial surface (RVES) shapes and kinematics from noninvasive clinical medical imaging data with respect to a spectrum of hemodynamic states. A computational framework for the quantitative analysis and statistical decomposition of sets of 3D genus-0 shapes that combines a modified harmonic mapping approach directly with proper orthogonal decomposition (DM-POD) is presented. The DM-POD approach is shown to be a robust technique for recovering inherent shape-related features through the analysis of sets of artificially generated shapes. The DM-POD approach is then applied to obtain kinematic features of the human RV based on the relative change in shape of the endocardial surface using cardiac computed tomography images. In addition, the kinematic features of the RVES obtained by the DM-POD approach are shown to be consistent and associated with intrinsically physiological components of the heart, and thus may potentially provide a more accurate means for classifying the progressive change in RV function caused by PH, in comparison to traditional clinical hemodynamic and volume-based metrics. Statistical shape analysis for the human RV is further evaluated through analysis of alternate components of the DM-POD approach, as well as through comparison of the DM-POD workflow with an alternate spherical harmonic function-based workflow (SPHARM), with respect to the aspects of surface representation, alignment, and decomposition. Additionally, different ways of utilizing the available imaging data with respect to the classification potential are investigated by considering analysis results when applying both the various DM-POD and SPHARM approaches with several different combinations of the phases captured throughout a single cardiac cycle for the patient set. Lastly, a novel statistical decomposition technique known as independent component analysis (ICA) was incorporated into the statistical shape analysis framework (i.e., DM-POD) to produce an alternative workflow (DM-ICA). Both the DM-POD and DM-ICA approaches are applied to analyze sets of artificially generated data and the human RVES datasets, and the respective results are compared. The DM-POD and DM-ICA workflows are shown to produce consistent, but substantially different results due to the various principles and views of each of the two statistical decomposition algorithms (i.e., POD and ICA). Most importantly, the results from the DM-POD and DM-ICA workflows appear to relate to RV function in unique ways, with respect to both traditional clinical metrics and each other, and have the potential to provide new metrics for better understanding of the human RV and its relationship to PH

The role of subchondral bone in osteoarthritis

Osteoarthritis (OA) is the most common form of arthritis. Affected individuals commonly suffer with chronic pain, joint dysfunction, and reduced quality of life. OA also confers an immense burden on health services and economies. Current OA therapies are symptomatic and there are no therapies that modify structural progression. The lack of validated, responsive and reliable biomarkers represents a major barrier to the development of structure-modifying therapies. MRI provides tremendous insight into OA structural disease and has highlighted the importance of subchondral bone in OA. The hypothesis underlying this thesis is that novel quantitative imaging biomarkers of subchondral bone will provide valid measures for OA clinical trials. The Osteoarthritis Initiative (OAI) provided a large natural history database of knee OA to enable testing of the validity of these novel biomarkers. A systematic literature review identified independent associations between subchondral bone features with structural progression, pain and total knee replacement in peripheral joint OA. However very few papers examined the association of 3D bone shape with these patient-centred outcomes. A cross-sectional analysis of the OAI established a significant association between 3D bone area and conventional radiographic OA severity scores, establishing construct validity of 3D bone shape. A nested case-control analysis within the OAI determined that 3D bone shape was associated with the outcome of future total knee replacement, establishing predictive validity for 3D bone shape. A regression analysis within the OAI identified that 3D bone shape was associated with current knee symptoms but not incident symptoms, establishing evidence of concurrent but not predictive validity for new symptoms. In summary, 3D bone shape is an important biomarker of OA which has construct and predictive validity in knee OA. This thesis, along with parallel work on reliability and responsiveness provides evidence supporting its suitability for use in clinical trials