Imaging, Medical Analysis and Grid Environments (IMAGE)

April 21, 2023

Translating Imaging Science to the Emerging Grid Infrastructure

Jeffrey S. Grethe - BIRN

University of California, San Diego

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.

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.

Neuroscience

Challenges

Governance

Informatics

Morphometry BIRN

FIRST BIRN

Mouse BIRN

Distributed Data

Data Integration

IRB

HIPAA

Policies

Best Practices

Community

High Speed Network

Computation

User Access

Neuroscience

Challenges

Governance

Informatics

Morphometry BIRN

FIRST BIRN

Mouse BIRN

Distributed Data

Data Integration

IRB

HIPAA

Policies

Best Practices

Community

High Speed Network

Computation

User Access

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 Parkinson’s 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

A National Collaboratory

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.

Neuroscience

Challenges

Governance

Informatics

Morphometry BIRN

FIRST BIRN

Mouse BIRN

Distributed Data

Data Integration

IRB

HIPAA

Policies

Best Practices

Community

High Speed Network

Computation

User Access

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

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

Grid Role

Distribution of a Bioinformatics Toolbox

• Package and deploy test bed—specific software through the distribution of the BIRN bioinformatics toolbox

• Use ROCKS (http://www.rocksclusters.org) as the distribution mechanism

AIR

FreeSurfer

• • •

AFNI

FSL

BIRN Roll

ROCKS Core

Grid Roll

Grid Wrappers

BIRN ROCKS

Distribution

• 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.

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

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

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

Neuroscience

Challenges

Governance

Informatics

Morphometry BIRN

FIRST BIRN

Mouse BIRN

Distributed Data

Data Integration

IRB

HIPAA

Policies

Best Practices

Community

High Speed Network

Computation

User Access

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

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

What Regulations Apply?

State Law

Common Rule

HIPAA

IRB Interpretation Local Policy

Institutional Policy

It Depends!

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

• 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

EU Privacy Directives

Data ClassificationsCharacteristic Protected Health

InformationResearch Health

InformationLimited

Data SetDe-Identified Data

Individually identifiable ie.,meets HIPAA definition ofindividually identifiable helathinformation

Yes Yes

Varies NoUsed for support clinicaldecision making for anindividual, or for payment oroperations

Yes No Varies Varies

Associated with healthcareservice event

Yes NoVaries Varies

Need-to-know, minimumnecessary access control

Yes YesYes No

Separation of person-identifiable and non-personidentifiable data elementswherever feasible

No YesYes N/A

Individual authorization(consent) for creation and useof data

Varies YesVaries No

Business Partner agreementsfor disclosures

Yes NoNo No

Logs and audit trails of useand disclosure Yes

Current best practice forresearch records

Current bestpractice for

research records

Current bestpractice for

research recordsRight to request amendment ofrecords

Yes At discretion ofinvestigator

At discretion ofinvestigator

At discretion ofinvestigator

Table 1: Data Characteristics (adapted from Masys et al. 2002)

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.

• 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

EU Data Definitions

Identifiable Health Information

Raw Skull Stripped

• 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 approvalIs there a scalable and distributed solution for researchers to access identifiable health information?

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