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NeuroLOG ANR-06-TLOG-024

NeuroLOG

Software technologies for integration of process, data and knowledge in medical imaging

Software technologies for integration of process and data in medical imaging

http:/ / neurolog.polytech.unice.fr

NeuroLOG

The NeuroLOG Platform

Federating multi-centric neuroscience resources

Johan MONTAGNAT Franck MICHEL Vilnius, Apr. 13th 2011

NeuroLOG ANR-06-TLOG-024

NeuroLOG

Software technologies for integration of process, data and knowledge in medical imaging

Neurosciences requirements

• Major challenge for this century
• population aging, brain disorders growth, brain function understanding...
• Large medical image databases
• Statistical studies
• Population-specific atlases of the brain
• Data intensive procedures
• Heterogeneous data sets
• Different acquisition conditions, centers
• Several imaging modalities
• Associated clinical information
• Complex data analysis procedures
• Specific to some modalities, acquisition parameters
• Minutes to hours of computation time each
• Chained into application pipelines (workflows)
• Sensitive data
• Stringent access control requirements

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NeuroLOG ANR-06-TLOG-024

NeuroLOG

Software technologies for integration of process, data and knowledge in medical imaging

Collaborative approach

• Sharing Computing algorithms and resources
• Research (populations studies, models design, validation, statistics)
• Complex analysis algorithms & pipelines (compute intensive image

processing, time constraints...)

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Data Processing tools Procedures Computing power

NeuroLOG ANR-06-TLOG-024

NeuroLOG

Software technologies for integration of process, data and knowledge in medical imaging

Brain atrophy measure workflow

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Detection of the longitudinal brain volume change is an issue of central relevance in neuroimaging.

• Early diagnosis for neurodegenerative

diseases (e.g. Alzheimer's).

• Reduction of costs in clinical trials,

increasing of the power in longitudinal studies.

NeuroLOG ANR-06-TLOG-024

NeuroLOG

Software technologies for integration of process, data and knowledge in medical imaging

Inputs: longitudinal study

Baseline image (T0) Other time point mages (T0 + 6 months, T0 + 12 months...)

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NeuroLOG ANR-06-TLOG-024

NeuroLOG

Software technologies for integration of process, data and knowledge in medical imaging

Image normalization

Space alignment (registration) Intensity alignment

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NeuroLOG ANR-06-TLOG-024

NeuroLOG

Software technologies for integration of process, data and knowledge in medical imaging

Parameters extraction

Mask Brain extraction Deformation field computation Quantitative parameters (atrophy measurement For Alzheimer's disease diagnosis) 1044901 -10294 -0.009 1044901 -10484 -0.010

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NeuroLOG ANR-06-TLOG-024

NeuroLOG

Software technologies for integration of process, data and knowledge in medical imaging

Generic infrastructure limitations

• The grid provides a foundational layer for distributed,

intensive computing

• Distributed files, large number of computing tasks
• Gap between grid infrastructures and medical environment
• Low level foundational middlewares
• Complex requirements from the health community
• Need for neuroradiological data integration
• Domain-specific data representation, mediation for existing databases
• Legacy neuroscience computing environments
• Bridging local and grid resources
• Neurology data analysis pipelines
• Need to integrate neuro-data analysis codes and procedures
• Access control and privacy
• The foundational security layer needs to be refined with adapted

security policies

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NeuroLOG ANR-06-TLOG-024

NeuroLOG

Software technologies for integration of process, data and knowledge in medical imaging

• Enable the sharing of resources:
• Data & knowledge representation
• Ontologies + relational schema
• Neuroradiological data & associated metadata
• Distributed on neuroscience

centers + EGI grid resources

• Integration of heterogeneous data stores
• Image analysis tools
• Bundled, relocatable,

remote invocation

• Application pipelines
• Sites computing resources
• Four pathologies
• Multiple Sclerosis, brain strokes, brain tumors, Alzheimer's disease

NeuroLOG objectives

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NeuroLOG ANR-06-TLOG-024

NeuroLOG

Software technologies for integration of process, data and knowledge in medical imaging

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Middleware design

NeuroLOG ANR-06-TLOG-024

NeuroLOG

Software technologies for integration of process, data and knowledge in medical imaging

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Software architecture

NeuroLOG ANR-06-TLOG-024

NeuroLOG

Software technologies for integration of process, data and knowledge in medical imaging

Platform deployment

• 5 sites connected
• 4 collaborating hosiptals
• Pitié Salpétrière (Paris)
• Michalon (Grenoble)
• CHU Rennes
• Antoine Lacassagne (Nice)
• 7 academic partners
• I3S, IRISA, GIN, MIS, IFR49, INRIA

Sophia, LRI

• 2 companies
• SAP, Visioscopie

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NeuroLOG ANR-06-TLOG-024

NeuroLOG

Software technologies for integration of process, data and knowledge in medical imaging

Data management layer

• Provide a seamless access to heterogeneous distributed data
• Heterogeneous data (modality, clinical context…)
• Heterogeneous legacy database providers & schemas…
• Heterogeneous file systems, resource storage units (local, grid)
• Need to provide:
• Federated view of the metadata
• Common access to physical files
• While enforcing strong constraints:
• Each partner site should keep control of access to their data
• Keep autonomous data management on each site: weak coupling
• Legacy data stores should not be altered
• Ensure secure access to sensitive data and metadata

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NeuroLOG ANR-06-TLOG-024

NeuroLOG

Software technologies for integration of process, data and knowledge in medical imaging

Federated relational schema

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Subject Study Dataset Examination MR Protocols Instrument Variables Scores Assessment

Ontology Common relational schema

NeuroLOG ANR-06-TLOG-024

NeuroLOG

Software technologies for integration of process, data and knowledge in medical imaging

• Approach
• Derived the ontology into relational

Federated Schema

• A dynamic mediation & federation

interface maps local database schemas to the federated schema

• A file transfer interface makes files

available to the end-user or processing tools

 Come up with a global federated view that hides data distribution and heterogeneity from the end-user

Data management layer

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NeuroLOG ANR-06-TLOG-024

NeuroLOG

Software technologies for integration of process, data and knowledge in medical imaging

Sharing image analysis tools

• Generic Application Service Wrapper (GASW)
• Service wrapper to non instrumented code
• Tool packaging in re-locatable self-contained executable units
• Expose tools as web services,

standard invocation interface

• Handle data transfer
• Remote execution capability
• n the EGI grid
• Tools discovery through the

federated view

• Executable remotely

by any authorized user

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NeuroLOG

Software technologies for integration of process, data and knowledge in medical imaging

Enabling processing pipelines

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• MOTEUR workflow engine
• Generic workflow design and

execution

• Support for different interfaces

to processors

• Data and processing

parallelism

• Handles stand-alone (client)

and client-server deployment

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Software technologies for integration of process, data and knowledge in medical imaging

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• Multiple credentials per user
• Grid certificates (delivered by grid authority)
• Middleware certificates (delivered by site authority)
• Databases credential (SQL 92)
• Health professional smartcards
• …
• Single sign-on enforced
• NeuroLOG security policy
• Individuals identification
• Distributed security administration
• No central point of control
• Sites keep access control over all their data
• Adapts to heterogeneous site security policies

Distributed data access control

NeuroLOG ANR-06-TLOG-024

NeuroLOG

Software technologies for integration of process, data and knowledge in medical imaging

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Distributed data access control

• Each site data access policy prevails for the data items

the site owns

rule : { StudyA ; read ; }

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Software technologies for integration of process, data and knowledge in medical imaging

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Results

• NeuroLOG collaborating platform for multi-centric

studies

• Integrate heterogeneous & distributed legacy data sets
• Share image analysis tools, distribute invocation
• Build complex experiment pipelines
• Distributed access control with prevailing local policies
• Advanced functionality
• High level ontology-based data representation
• EGI Grid interface, large-scale distributed processing
• The grid for neuroscientists
• Transparent access to grid resources
• Compliance with legacy environments

NeuroLOG ANR-06-TLOG-024

NeuroLOG

Software technologies for integration of process, data and knowledge in medical imagingLimitations

• Semantic validation not yet integrated
• At processing tool annotation time: check compatibility of

inputs/outputs with DataSet Processing class constraints

• At w/f design time: user-assisted composition checks compatibility
• f inputs/outputs of composed services
• At run time: check validity of actual inputs for each service
• Produced semantic data is still limited
• Developments on-going to provide richer semantic description of

produced datasets using reasoning

• EGI interface still limited
• Integration work on-going to complete remote invocation and

retrieval of results from storage elements

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Software technologies for integration of process, data and knowledge in medical imaging

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Global picture

Workflow Manager

P

S2 S3

Q

S4

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Software technologies for integration of process, data and knowledge in medical imaging

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Thank you