This R01 application is for five years of funding to develop, evaluate and apply novel computational tools for the purpose of understanding morphometric changes in neuroanatomical structures related to schizophrenia. Shape measures are of interest in schizophrenia because this disorder is viewed by some as a neurodevelopmental in origin and because there is evidence to suggest that during morphogenesis of the brain, abnormal pressures and/or tissue formations likely change the shape of brain structures, particularly those in the midline of the brain, as well as influencing folding patterns of the neocortex. We believe that computational morphometry tools are critical to characterize and to quantify shape changes accurately. In fact, neuroscience research as a whole has shown a growing interest in computer assisted shape studies for numerous conditions including, but not limited to, normal neurodevelopment, Alzheimer's disease, schizophrenia and schizotypal personality disorder (SPD), bipolar disorder, psychotic affective disorder, and fetal alcohol exposure. Our primary objective is thus to develop further new image analysis techniques to enable the detection and localization of shape differences between populations. We will apply this new technology to selected brain structures in first episode schizophrenic subjects compared to first episode affective subjects (mainly manic), and normal controls. Our secondary objective is to quantitatively evaluate and compare current state-of-the-art shape analysis tools, including ours, as few algorithms have been validated. Accordingly, a synthetic data set with known shape modifications will be created to use in a control experiment. In addition, we will evaluate all shape techniques on real data with previously observed shape changes (i.e., caudate nucleus in SPDs and amygdala-hippocampus in patients with schizophrenia). Finally, in an effort to promote open science, we will make all results, data, parameters and algorithms publicly available to the scientific community. By characterizing and delineating shape abnormalities in schizophrenia, we will understand further the role of brain morphometry abnormalities in schizophrenia, a disorder that is a major public health problem, affecting close to 1% of the general population.

Public Health Relevance

A well accepted hypothesis is that some brain disorders are neurodevelopmental in origin and that during morphogenesis of the brain, abnormal pressures or tissue formations likely impact the proper development of neuroanatomical structures. The goal of this project is to design computational tools to analyze the morphometry of brain structures in the context of schizophrenia and related disorders. We believe that our proposed study, to design and to evaluate computational morphometric tools, will provide us with invaluable information about normal and abnormal neurodevelopment and its correlation with mental illnesses.

National Institute of Health (NIH)
National Institute of Mental Health (NIMH)
Research Project (R01)
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Study Section
Neural Basis of Psychopathology, Addictions and Sleep Disorders Study Section (NPAS)
Program Officer
Meinecke, Douglas L
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Brigham and Women's Hospital
United States
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Hong, Yi; Gao, Yi; Niethammer, Marc et al. (2014) Depth-based shape-analysis. Med Image Comput Comput Assist Interv 17:17-24
Savadjiev, Peter; Rathi, Yogesh; Bouix, Sylvain et al. (2014) Fusion of white and gray matter geometry: a framework for investigating brain development. Med Image Anal 18:1349-60
Gao, Yi; Riklin-Raviv, Tammy; Bouix, Sylvain (2014) Shape analysis, a field in need of careful validation. Hum Brain Mapp 35:4965-78
Nummenmaa, Aapo; McNab, Jennifer A; Savadjiev, Peter et al. (2014) Targeting of white matter tracts with transcranial magnetic stimulation. Brain Stimul 7:80-4
Lou, Yifei; Irimia, Andrei; Vela, Patricio A et al. (2013) Multimodal deformable registration of traumatic brain injury MR volumes via the Bhattacharyya distance. IEEE Trans Biomed Eng 60:2511-20
Gao, Yi; Bouix, Sylvain; Shenton, Martha et al. (2013) Sparse texture active contour. IEEE Trans Image Process 22:3866-78
Clemm von Hohenberg, Christian; Wigand, Marlene C; Kubicki, Marek et al. (2013) CNTNAP2 polymorphisms and structural brain connectivity: a diffusion-tensor imaging study. J Psychiatr Res 47:1349-56
Bouix, Sylvain; Pasternak, Ofer; Rathi, Yogesh et al. (2013) Increased gray matter diffusion anisotropy in patients with persistent post-concussive symptoms following mild traumatic brain injury. PLoS One 8:e66205
Kikinis, Zora; Makris, Nikos; Finn, Christine T et al. (2013) Genetic contributions to changes of fiber tracts of ventral visual stream in 22q11.2 deletion syndrome. Brain Imaging Behav 7:316-25
Shenton, M E; Hamoda, H M; Schneiderman, J S et al. (2012) A review of magnetic resonance imaging and diffusion tensor imaging findings in mild traumatic brain injury. Brain Imaging Behav 6:137-92

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