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