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Velo-Cardio-Facial Syndrome PRINCIPAL INVESTIGATOR: Marek Kubicki, MD, PhD INVESTIGATORS: Zora Kikinis, PhD Sylvain Bouix, PhD Marc Niethammer, PhD Martha Shenton, PhD Christine Finn, MD Raju Kucherlapati, MD RESEARCH ASSISTANT: Kate Smith, BA National Alliance for Medical Image Computing http://na-mic.org May, 2007 Velo-Cardio-Facial Syndrome (VCFS) • Deletion of the fragment of short arm of the 22nd chromosome (single copies of 30 to 45 genes missing) • Prevalence 1 in every 4000 newborns • Clinical symptoms: – "velum" latin meaning soft palate – “kardia" greek meaning heart – "facial" latin having to do with the face • Cognitive symptoms: – Psychomotor deficits – Learning and memory disabilities – Emotional abnormalities (flat affect and poor social interaction). – High incidence for schizophrenia and/or bipolar disorder in adult (30% VCFS patients develop schizophrenia), and 4-5 genes have been suggested to be related to schizophrenia (COMT- attention, memory, prefrontal function; RTN4R- axonal regeneration and plasticity) National Alliance for Medical Image Computing http://na-mic.org May, 2007 Aims • Etiology of schizophrenia and related diseases • Prognosis of mental health diseases in VCFS • Early intervention National Alliance for Medical Image Computing http://na-mic.org May, 2007 Project • Subject recruitment • Psychological interview • DNA analysis, genotyping of the 22q11.2 region • Brain imaging (MRI, DTI and fMRI) • Analysis of imaging data, and genetic correlations National Alliance for Medical Image Computing http://na-mic.org May, 2007 Imaging Data Available Two stages: • Available now: 7 VCFS and 7 matched control cases scanned on 1.5 T magnet (DTI and structural scans) 15 schizophrenics and 15 control cases scanned on 3T magnet (DTI and fMRI) plus 1.5T chronic schizophrenia data (DTI and structural scans) • Available by the end of the year: 15 VCFS and 15 matched control cases scanned on 3T magnet (DTI, structural scans and fMRI) National Alliance for Medical Image Computing http://na-mic.org May, 2007 Hypotheses Regions that we want to study with MRI - DLPC (executive function, memory) - Orbital Frontal Gyrus (emotion) - Cingulate Gyrus (attention, emotion) - Hippocampus (memory, learning) Tracts that we want to study with DTI (frontal-temporal connections): - Fornix (memory) - Arcuate Fasciculus (language) - Cingulum Bundle (attention) - Uncinate Fasciculus (emotion, affective flattening) Networks that want to study with fMRI : - Memory, attention, emotion, language (semantic processing) National Alliance for Medical Image Computing http://na-mic.org May, 2007 Specific Requirements - Automatic DLPC segmentation. - Automatic segmentation of other structures (orbital frontal cortex, cingulate gyrus, hippocampus). - Tools for measuring anatomical connectivity between these regions (optimal path analysis, stochastic tractography). - “Default network” and “rest” fMRI analysis. - Anatomical (DTI), and functional (fMRI) connectivity analysis. National Alliance for Medical Image Computing http://na-mic.org May, 2007 Progress So Far - Automatic DLPC segmentation. - John and Brad finished the slicer2 module, its being tested and used for first episode schizophrenia study now. - Automatic segmentation of other structures (orbital frontal cortex, cingulate gyrus, hippocampus). - We have limited experience with freesurfer and cingulate, have not tried Killian’s segmentation for anything other than STG. - Tools for measuring anatomical connectivity between these regions (optimal path analysis, stochastic tractography). - Optimal Path Analysis- we used it, but its not yet in the slicer, there might be some problems with it. Same with Stochastic tractography. - “Default network” fMRI analysis, functional connectivity analysis. - Polina and Sandy might have some tools, but we have not tried them yet. National Alliance for Medical Image Computing http://na-mic.org May, 2007 Potential Challenges for Segmentation/Registration • Different brain shape • Thicker skull • Brain atrophy • Congenital abnormalities • Brain asymmetry • White matter lesions National Alliance for Medical Image Computing http://na-mic.org May, 2007 Segmentation/Registration Beneficial algorithms/software: • Automatic segmentation procedures tailored for VCFS (atlas?). • Automatic parameterization of segmentation algorithm (e.g., optimal parameter selection for EM segmenter based on training data). • Robust and easy to use registration. Capabilities for batch processing. National Alliance for Medical Image Computing http://na-mic.org May, 2007 VCFS Schizophrenia Candidate Genes • COMT (controls dopamine degradation in prefrontal cortex, related to attention and memory) • RTN4R (also known as Nogo 66, related to axonal regeneration and plasticity) • PRODH • ZDH8 • SNAP29 • TBX1 National Alliance for Medical Image Computing http://na-mic.org May, 2007