All Hands Meeting 2004, Boston
http://www.nbirn.net
Informatics Workshop
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?
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
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
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
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…
Clinical Measures
Genotype
Local Storage
BIRN Rack
SRBMCAT
HID
DU
P
Calibration & Analysis
Tools
GRID
PortalMediator
Institution A
BIRN Rack
SRBMCAT
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
StandardizedAcquisition
Protocol
Institution C
Informatics Architecture
Local DB
Clinician’s Requirements for HID Query and Statistics Interface
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.
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.
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.
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.
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.
Statistics Interface
Statistical Analysis of Morphometry Across Sites
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.)
Enhancements to Query Interface• Access to ‘Studies’ (See Brad Dickerson Demo for examples)
Example Multisite questions• Retrospective
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