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All Hands Meeting 2004, Boston http://www.nbirn.net Informatics Workshop
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Introduction Thanks to Jonathan Sacks for organization of this session! Special Introductions: Computational ‘Virtual’ Core MGH – Shawn Murphy; MIT – David Karger New Site; WashU – Randy Buckner / Dan Marcus General Introductions: Who are you, and what are the areas you’re particularly interested in?
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Introduction Today’s Goals: foreach p (Informatics Project Areas) Review where we are Discuss where we need to go Finalize ‘staged’ milestones for next year Get everyone up to speed on current status Align workplan with new (m & FIRST) awards
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Introduction Things to keep in mind for all projects: In addition to synergy, the individual testbeds may have some unique requirements Timeline mBIRN 3 year timeframe: 1 year to do something, 1 year to publish it, 1 year to get renewal funded Who is the User? Morphometric Expert, Clinical Expert, Randumb User, etc… Classes of Data Prospective, Retrospective Modes of Data Access Self, Group of Selected Collaborators, World, etc… Clinical Applications must drive developments
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mBIRN Renewal: Informatics Aim 1: Where’s the Data? Local/Global Upload Raw/Derived Aim 2: More types of Data Diffusion, Genetics Aim 3: Uses of Data Quality assurance (acquisition, processing) Querying Statistics Services Knowledge Management
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Informatics Project Areas SRB (BVDG?) HID XNAT LONI DB Workflow Control Haystack Query Interface Statistics Interface RPDR Ontology Provenance Quality Assurance Mediation Upload Query Atlas BIRN Services Others…
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Clinical Measures Genotype Local Storage BIRN Rack SRB MCAT HID DUP Calibration & Analysis Tools GRID Portal Mediator Institution A BIRN Rack SRB MCAT Institution B HID … Workflow Control: - Queries (identify subject populations, extract data, etc.) - Statistical Analysis - Download Data for: > Visualization > More Statistics > More Processing - Interoperable Queries (literature, homology, other databases, etc.) Human Data Protection Standardized Acquisition Protocol Institution C Informatics Architecture Local DB
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Clinician’s Requirements for HID Query and Statistics Interface
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Do structural differences contribute to specific symptoms such as memory dysfunction or depression independent of diagnosis? 1. Determine whether hippocampal atrophy contributes to memory dysfunction and dementia risk in unipolar depression, mild cognitive impairment (MCI), and mild Alzheimer’s disease (AD). Hypothesis 1a. Decreased hippocampal volume will predict increased risk of dementia independent of diagnosis (unipolar depression, MCI and mild AD). Hypothesis 1b. Decreased hippocampal volume will predict memory impairment independent of diagnosis.
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2. Determine whether amygdala atrophy and thinning of the dorsolateral prefrontal cortex (DLPFC) contributes to depression or apathy in unipolar depression, MCI, and mild AD. Hypothesis 2a. Decreased amygdala volume and thinning of the DLPFC will predict the severity of depression within each diagnostic category (unipolar depression, MCI and mild AD). Hypothesis 2b. Decreased amygdala volume and thinning of the DLPFC will predict the apathy within each diagnostic category.
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Do specific structural differences distinguish specific diagnostic categories? 3. Determine whether atrophy in temporal lobe and cingulate gyrus contribute to memory dysfunction and dementia risk associated with Alzheimer’s disease (AD). Hypothesis 3a. Patients with mild AD will have smaller entorhinal cortical volumes than patients with MCI and controls. Hypothesis 3b. Patients with mild AD will have smaller banks of the superior temporal sulcus than patients with MCI and controls. Hypothesis 3c. Patients with mild AD will have smaller caudal portions of the anterior cingulate gyrus than patients with MCI and controls. Hypothesis 3d. Patients with mild AD will have thinner cortex in the regions of the inferior parietal lobule, entorhinal area, banks of the superior temporal sulcus and posterior portion of the anterior cingulate gyrus than patients with MCI and controls.
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4. Determine whether atrophy in frontal lobe and specific subcortical areas characterizes unipolar depression. Hypothesis 4a. Patients with depression will have smaller volumes of orbital cortex and DLPFC than age-and gender- matched controls. Hypothesis 4b. Patients with unipolar depression will have thinner cortical surface in the orbital and dorsolateral prefrontal regions than age- and gender-matched controls. Hypothesis 4c. The cortical volumes in the orbital frontal and dorsolateral prefrontal regions will correlate with the thickness of the cortical surface in these regions. Hypothesis 4d. Patients with unipolar depression will have smaller caudate and amygdala volumes than age-and sex- matched controls.
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5. Determine whether atrophy in the temporal and parietal lobes and cingulate identify the risk of developing dementia. Hypothesis 5a. Patients with MCI will have thinner cortex of the inferior parietal lobule, entorhinal area, banks of the superior temporal sulcus and posterior portion of the anterior cingulate gyrus region than age- and sex-matched controls. Hypothesis 5b. Non-demented ApoE 4 homozygotes will have greater asymmetries of hippocampal volume and of the cortical ribbon in the inferior parietal lobe than age- and sex-matched controls.
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Statistics Interface Statistical Analysis of Morphometry Across Sites
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Enhancements to Statistical Interface Enable ‘By’ Functionality Hierarchical ANOVA / MANOVA Total Brain Cerebrum, Cerebellum, Brainstem, Ventricular System Cerebral Cortex, White Matter, Thalamus, Caudate, Accumbens, Putamen, Pallidum, Hippocampus, Amygdala Frontal, Occipital, Parietal, Temporal Lobes Gyral Regions within Lobe Enable laterality functions (L+R, L-R, average, symmetry index, etc.)
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Enhancements to Query Interface Access to ‘Studies’ (See Brad Dickerson Demo for examples) Example Multisite questions Retrospective
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Human Imaging Database Goal: develop the image repository and relational database for clinical and derived morphometric data Cortical Summary Data by Region Subcortical Summary Data by Region BWH (SPL): J. Sacks Duke University: S. Gadde, S. Anastasiadis UCI: D. Wei JHU: A. Kolasny, R. Yashinski MGH (NMR): K. Song UCSD (fMRI): B. Ozyurt UCLA (LONI): K. Crawford BIRN CC: J. Grethe
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