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Grid Applications in Health. Andres Gómez, PhD CESGA agomez@cesga.es. OBJECTIVES. Provide terminology Show real clinical real applications Some legal issues Future. GRID INFRASTRUCTURE. HEALTH GRID REQUIREMENTS. Data confidentiality Interactivity Work-flow Fast return of short jobs

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Grid Applications in Health

Andres Gómez, PhD

CESGA

agomez@cesga.es


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OBJECTIVES

  • Provide terminology

  • Show real clinical real applications

  • Some legal issues

  • Future


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GRID INFRASTRUCTURE


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HEALTH GRID REQUIREMENTS

  • Data confidentiality

  • Interactivity

  • Work-flow

  • Fast return of short jobs

  • Hide infrastructure details (portals)


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Source: EELA-2

Source:EGEE

Source: Crossgrid project

GRID HEALTH APPLICATIONS

  • Surgical simulation

  • Image processing

  • In silico drug discovery

  • Share patient’s images and data

  • Many more (EELA-2)


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CLINICAL RADIOTHERAPY

  • 60-70% cancer patients

  • Established methods

  • Many protocols


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DATA ACQUISITION

  • DICOM-CT

    • INCLUDES PATIENT’S DATA

    • IMAGES

    • NEEDS ANONIMYZATION/SECURITY

  • ACCESS FROM GRID

    • TRENCADIS

    • MEDICAL DATA MANAGER (EGEE)


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MEDICAL DATA MANAGER. Insert data

J. Montagnat, et.al. ”A Secure Grid Medical Data Manager Interfaced to the gLite Middleware” in Journal of Grid Computing (JGC), 6 (1), pages 45–59, Kluwer, march 2008

Source: EGEE. Johan Montagnat


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MEDICAL DATA MANAGER. Get data

Source: EGEE. Johan Montagnat


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GTV: Gross Target Volume

Extent of Tumour Visible on Scan

CTV: Clinical Target Volume

Extension of GTV to include possible microscopic disease or additional structures (e.g. seminal vesicles in prostate ca)

PTV: Planned Target Volume

Include margins for organ motion, set-up inaccuracies (may be non-uniform i.e. larger margin AP than Inf-Sup)

Ensures CTV will be covered despite variables.

TV: Target or Treatment Volume

Volume Irradiated (if possible PTV=TV)

IV: Irradiated Volume

Volume, which receives a ‘significant’ dose

CTV

GTV

TV

PTV

IV

ANATOMIC MODEL

  • DICOM-STRUCT


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TREATMENT SELECTION

  • CONFORMAL RADIOTHERAPY (CRT)

  • INTENSITY MODULATED RADIOTHERAPY (IMRT)

  • IMAGE GUIDE RADIOTHERAPY (IGRT)

  • BRACHITHERAPY

  • ETC.


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Accelerator

Multileaf Collimator

CONFORMAL RADRIOTHERAPY (CRT)

Tumour is irradiated from

several angles

Collimator takes the shape of the tumour

http://eimrt.cesga.es

TUMOUR

Organ at risk


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INTENSITY MODULATED RADIATION THERAPY (IMRT)

Collimator moves during beam-time, modulating intensity

Also from different angles

TUMOUR

Organ at risk


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DOSE CALCULATION.

  • SOFTWARE: TREATMENT PLANNING SYSTEM

    • USE FAST ALGORITHMS

    • RUN LOCALLY: WORKSTATIONS/CLUSTER

  • OUTPUTS (OPTIONAL)

    • DICOM-RTDOSE. CALCULATED DOSE

      • Dose Matrix,

      • Dose Points (2D & 3D),

      • Isodoses,

      • DVH

    • DICOM-RTPLAN: TREATMENT PLAN

      • Fractionation,

      • Tolerance,

      • Patient Setup,

      • Beams, & Sources


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DOSE CALCULATION


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PLAN VERIFICATION. EIMRT SERVICE

  • BASED ON BEAMnrc and DOSXYZ MONTE CARLO

  • CALCUTES DOSE DISTRIBUTIONS FOR AN EXISTING TREATMENT

  • ADDS TOOLS FOR COMPARING REFERENCE AND CALCULATED DOSES (3D GAMMA MAPS)

J. Pena, et. al. “eIMRT: a web platform for the verification and optimization of radiation treatment plans”, in press in Journal of Applied Clinical Medical Physics


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eIMRT Proposal

Results

Results

  • Commisioning

  • Verification < 5 hours

  • Optimization < minutes

CTs

Treatment

BEFORE

TPS

WITH E-IMRT


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ARCHITECTURE

PERSONAL DATA REMOVED FROM INPUT FILES BEFORE UPLOAD

SERVER

CLIENT

GRID + CLUSTER

Service Oriented Architecture

Based on GRID technologies


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GRIDWAY

ARCHITECTURE

SERVER SIDE

DEMO CLIENT

DRMAA

SLA

SOA Architecture

Based on GRID technologies


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DRMAA

  • Init/exit

  • Job template interfaces

  • Job submit

    • Individual jobs

    • Jobs arrays (bulk)

  • Job monitoring and control

  • Auxiliary or system routines


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DRMAA

Example

import org.ggf.drmaa.*;

public class DrmaaRunJob {

public static void main (String[] args) {

SessionImpl session = new SessionImpl();

JobTemplateImpl jt = new JobTemplateImpl();

session =(SessionImpl) SessionFactory.getFactory().getSession();

try

{

session.init(null);

jt = (JobTemplateImpl) session.createJobTemplate();

jt.setWorkingDirectory("wdir");

//Basic parameters

jt.setJobName("taskname.jt");

jt.setRemoteCommand(“/bin/ls");

jt.setArgs(“-al”);

//Output files, from local to remote (including protocol)

jt.setOutputPath("stdout." + SessionImpl.DRMAA_GW_JOB_ID+".txt");

jt.setErrorPath("stderr." + SessionImpl.DRMAA_GW_JOB_ID+".txt");

//Job submission to GridWay

Stgring id = session.runJob(jt);

session.exit();

} catch (DrmaaException e) {

e.printStackTrace();

}

}

}


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SLA Negotiation overview

GRID

TREATMENT

SERVICES

GRIDWAY

DRMAA

SLA

Negotiator

client

SLA

SLA

Negotiator

server

EXTERNAL

RESOURCES

PROVIDER


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SLA components interaction

SLA

Negotiator

client

Provider

List

Broker GW-SLA

SLA

Negotiator

server

Pre SLA

GW Internal

Struct

SLA Evaluation

Resources

provider

DB Services

Plugin GW-SLA

GRIDWAY


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E-IMRT VERIFICATION

  • Phase 1: Accelerator simulation.

  • Phase 2: Accelerator treatment head simulation (GRID)

  • Phase 3: Patient simulation.

  • Phase 4: Dose delivered to the patient(GRID)

  • Phase 5: Dose collection and end of process.

Radiotherapist manually

compares TPS and e-IMRT Monte Carlo doses

Using different maps


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E-IMRT VERIFICATION (II)


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E-IMRT VERIFICATION (III)


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PLAN OPTIMIZATION. EIMRT SERVICE

  • BASED ON MCDOSE

  • OPTIMIZE FLUENCES

  • RETURNS SEVERAL TREATMENT POSSIBILITIES

  • GENERATE DVH FOR CHECK

J. Pena, et. al. “eIMRT: a web platform for the verification and optimization of radiation treatment plans”, in press in Journal of Applied Clinical Medical Physics


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PLAN OPTIMIZATION. EIMRT SERVICE

J. Pena, et. al. “eIMRT: a web platform for the verification and optimization of radiation treatment plans”, in press in Journal of Applied Clinical Medical Physics


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INPUT/OUTPUT SUMMARY

VERIFICATION

OPTIMIZATION

  • Input:

    • DICOM RTplan

    • DICOM RTstruct

    • DICOM CT

    • DICOM RTdose (from TPS, optional)

  • Output:

    • DICOM RTdose (MCarlo)

  • Input:

    • DICOM RTstruct

    • DICOM CT

  • Other data:

    • Prescriptions

  • Output:

    • DICOM RTplan


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RESEARCH CHALLENGES HEALTHGRID

Source: http://eu-share.org/roadmap/SHARE_roadmap_long.pdf


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RESEARCH CHALLENGES HEALTHGRID


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LEGAL ISSUES

  • 2007/47/EC of 5 September 2007

    • http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2007:247:0021:0055:EN:PDF

    • Medical device: “medical device” means any instrument, apparatus, appliance, software, material or other article, whether used alone or in combination, together with any accessories, including the software intended by its manufacturer to be used specifically for diagnostic and/or therapeutic purposes and necessary for its proper application, intended by the manufacturer to be used for human beings for the purpose of:

      • diagnosis, prevention, monitoring, treatment or alleviation of disease,

      • diagnosis, monitoring, treatment, alleviation of or compensation for an injury or handicap,

      • investigation, replacement or modification of the anatomy or of a physiological process,

      • control of conception

    • For devices which incorporate software or which are medical software in themselves, the software must be validated according to the state of the art taking into account the principles of development lifecycle, risk management, validation and verification


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LEGAL ISSUES

  • Directive 95/46/EC of the European Parliament and of the Council of 24 October 1995 on the protection of individuals with regard to the processing of personal data and on the free movement of such data

    • the processing of data concerning health is prohibited by default

    • Only allowed for clinical usage by health professional with obligation of secrecy

    • Anyother case, patient consent


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Grid Computing vs Cloud Computing

Cloud Computing

Source:Trends.google.com


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Cloud Computing

“Clouds are a large pool of easily usable and accessible virtualized resources (such as hardware, development platforms and/or services). These resources can be dynamically reconfigured to adjust to a variable load (scale), allowing also for an optimum resource utilization. This pool of resources is typically exploited by a pay-per-use model in which guarantees are offered by the Infrastructure Provider by means of customized SLAs.”

Luis M. Vaquero, et.al.: “A Break in the Clouds: Towards a Cloud Definition“


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Cloud Computing


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THANK YOU

Any questions?

Visithttp://eimrt.cesga.es


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