Translating Imaging Science to the Emerging Grid Infrastructure

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Translating Imaging Science to the Emerging Grid
Infrastructure

• Jeffrey S. Grethe - BIRN
• University of California, San Diego

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We speak piously of taking measurements and
making small studies that will add another brick
to the temple of science. Most such bricks just
lie around the brickyard. Platt, J.R. (1964)
Strong Inference. Science. 146 347-353.
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Objectives

• Establish a stable, high performance network
  linking key Biotechnology Centers and General
  Clinical Research Centers
• Establish distributed and linked data collections
  with partnering groups - create a Data GRID for
  the BIRN
• Facilitate the use of "grid-based" computational
  infrastructure and integrate BIRN with other GRID
  middleware projects
• Enable data mining from multiple data collections
  or databases on neuroimaging and bioinformatics
• Build a stable software and hardware
  infrastructure that will allow centers to
  coordinate efforts to accumulate larger studies
  than can be carried out at one site.

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Challenges
Neuroscience
High Speed Network
Computation
Mouse BIRN
User Access
FIRST BIRN
Distributed Data
Data Integration
Morphometry BIRN
Informatics
Community
Policies
Best Practices
IRB
HIPAA
Governance
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Challenges
Neuroscience
High Speed Network
Computation
Mouse BIRN
User Access
FIRST BIRN
Distributed Data
Data Integration
Morphometry BIRN
Informatics
Community
Policies
Best Practices
IRB
HIPAA
Governance
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CREATING BIRN TEST-BED PARTNERSHIPS

• Three Research Project Application Test Beds
  have been Assembled to Shape BIRN and Guide
  Infrastructure Development
• Multi-scale Mouse BIRN - Animal Models of disease
  / Multi Scale/Multi Method - Examples MS Mouse,
  DAT KOM (a schizophrenic and otherwise
  interesting mouse animal model) and a Parkinsons
  Disease Mouse
• Brain Morphometrics (Human Structure BIRN) -
  Targets neuroanatomical correlates of
  neuropsychiatric illness (Unipolar Depression,
  mild Alzheimer's Disease (AD), mild cognitive
  impairment (MCI)
• Functional Imaging BIRN Development of a common
  functional magnetic resonance imaging (fMRI)
  protocol and to study regional brain dysfunction
  related to the progression and treatment of
  schizophrenia - attack on underlying cause of
  disease

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A National Collaboratory
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Science Drives The Infrastructure

• USE APPLICATION SCIENCE PULL TO GUIDE
  DEVELOPMENT OF THE NEXT GENERATION
  CYBERINFRASTRUCTURE
• Craft a plan to achieve an important scientific
  goal requiring development and implementation of
  innovative computational infrastructure.
• Articulate a Grand Challenge and define work to
  achieve this goal with increasing levels of
  specificity.
• Bring application scientists and computer
  scientists together in projects at each level to
  build elements of the new infrastructure.

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Challenges
Neuroscience
High Speed Network
Computation
Mouse BIRN
User Access
FIRST BIRN
Distributed Data
Data Integration
Morphometry BIRN
Informatics
Community
Policies
Best Practices
IRB
HIPAA
Governance
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User Access to Grid Resources

• Application environment being developed to
  provide centralized access to BIRN tools,
  applications, resources with a Single Login from
  any Internet capable location
• Provides simple, intuitive access to Grid
  resources for data storage, distributed
  computation, and visualization

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Interfacing the Desktop with the Grid

• Developed a Java Grid Interface (JGI) that
  provides wrapper for applications on a users
  desktop.
• Brokers communications and information/data
  transfer between the application and BIRN
  resources (e.g. SRB)
• LONI Pipeline, 3D Slicer, FreeSurfer, and ImageJ
• Continue to extend and develop the JGI
• OGSA compliance

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Distribution of a Bioinformatics Toolbox

• Package and deploy test bedspecific software
  through the distribution of the BIRN
  bioinformatics toolbox
• Use ROCKS (http//www.rocksclusters.org) as the
  distribution mechanism

• Bioinformatics toolbox can be made available to
  any researcher interested in a robust package of
  neuroimaging applications.
• First release to occur this fall using the new
  ROCKS distribution model.

BIRN Roll
FreeSurfer
AIR
AFNI

FSL
Grid Wrappers
Grid Role
BIRN ROCKS Distribution
Grid Roll
ROCKS Core
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Scientific Workflow

• Sequence of steps (utilities, applications,
  pipelines) required to acquire, process,
  visualize, and extract useful information from a
  scientific data.
• Advantages of workflow managed within the Portal
• Progress through the workflow can be organized
  and tracked
• Automated and transparent mechanisms for the flow
  of data from one step to the next using SRB
• Tools are centralized and presented with uniform
  GUIs to improve usability
• Administration burden of each step (groups of
  steps) is eliminated
• Flexibility to enhance each process through
  direct, transparent access to the grid

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Interactive Scientific Workflows
Provide researchers with transparent access to a
computing environment that supports their natural
working paradigm while taking advantage of the
evolving grid infrastructure
Data curation requires determination of data
quality and validity
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Workflow Considerations

• Provide full provenance for data within the BIRN
  environment
• Morphometry BIRN is modifying tools to provide
  proper provenance information
• Data provenance is being taken into account in
  the human imaging database
• Workflow Optimization
• Take advantage of resource discovery services
  being deployed
• Use of data provenance information
• Global versus run time optimizations

• Incorporation of legacy applications
• LONI Pipeline (UCLA)
• Standard install
• Incorporation into Portal
• Advisement on future Grid enhancements to Pipeline

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Challenges
Neuroscience
High Speed Network
Computation
Mouse BIRN
User Access
FIRST BIRN
Distributed Data
Data Integration
Morphometry BIRN
Informatics
Community
Policies
Best Practices
IRB
HIPAA
Governance
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Governance

• Incorporating processes for Multi-sites studies
  and sharing of human data
• HIPPA Compliance
• Patient confidentiality
• Institutional Review Board (IRB) approvals
• Developing guidelines - for sharing data
  authorship
• Breaking down the barriers
• Mistrust
• Open sharing of information
• Who gets credit
• Commercial products
• Governance
• Integrating new participants

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IRB Working Group

• One member from each BIRN site required to
  participate
• Each member is required to review BIRN consents,
  waivers and procedures with local IRBs
• Regular video conferences among members to
  coordinate information and activities
• Produce BIRN template language for subject
  consent, IRB waiver for data upload and IRB
  waiver for data download
• Interact with Data Sharing Task Force

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What Regulations Apply?
Institutional Policy
It Depends!
Local Policy
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Data Sharing Task Force

• Produce guidelines and procedures for data
  sharing across institutions taking into account
  Common Rule, HIPAA and state regulations
• Develop procedures to allow for longitudinal
  studies within BIRN
• Examine policies that are relevant to BIRN (e.g.
  revised policies being drafted for tissue banks
  and data banks)
• Interact with Architecture working groups to help
  define security and subject confidentiality
  infrastructure and policy
• Data Replication
• Certificate Policies
• Registration Authority Policies
• Local access control
• Auditing activity logs

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EU Privacy Directives

• EU directive 95/46/EC article 8
• Member states shall prohibit the processing of
  personal data concerning health or sex life.
• Recommendation nr R (97) 5 Exceptions
• Diagnostic and therapeutic reasons
• Public health reasons, public interest
• Criminal offenses
• Specific contractual obligations fulfilment
• Legal claims
• Consent for specific purposes

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Data Classifications
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Anonymization vs. De-Identification

• Both require deletion of direct identifiers
• Anonymization cannot have a link field
  (De-Identified data can).
• Anonymization makes protocol eligible for
  exemption from IRB review.
• De-Identification makes data exempt from HIPAA
  regulations.
• De-Identification with link field does NOT exempt
  data from IRB review.

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EU Data Definitions

• Recommendation R (97)5 on the protection of
  medical data
• Personal data covers any information relating to
  an identified or identifiable individual.
• An individual shall not be regarded as
  identifiable if identification requires an
  unreasonable amount of time and manpower.
• In cases where the individual is not
  identifiable, the data are referred to as
  anonymous

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Identifiable Health Information

• High-resolution structural images can be used as
  an identifier.
• Reconstruction of face from raw anatomical data
  might be able to be used to identify subject
• Some members of scientific community
  require/desire unaltered raw data
• Are allowed to provide both raw and skull
  stripped data
• Need to get approval from local IRB to allow for
  the sharing of raw anatomical data
• Users wishing to access data also require IRB
  approval

Is there a scalable and distributed solution for
researchers to access identifiable health
information?
Raw
Skull Stripped
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Data Sharing Infrastructure

• Security related metadata
• All data uploaded within BIRN must have
  associated metadata
• Data classification
• IRB agreements
• Subject consent
• Longitudinal data
• Data sharing permissions are dependent on
  metadata
• For example, de-identified data can not be shared
  with all users
• Secure environment required for the storage of
  protected information
• Linkage of BIRN ID with original subject ID
• Protected data
• Auditing of data access and movement required
• HIPAA
• Internal Security
• Data Usage Statistics

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