Lydia MAIGNE, PhD Laboratoire de Physique Corpusculaire [email protected]
description
Transcript of Lydia MAIGNE, PhD Laboratoire de Physique Corpusculaire [email protected]
INFSO-RI-508833
Enabling Grids for E-sciencE
Grid based telemedicine application for GATE Monte Carlo dosimetric studies using HOPE (Hospital Platform for E-health)
Lydia MAIGNE, PhDLaboratoire de Physique [email protected]: M.Diarena, S.Nowak, C. Thiam, D.Donnarieix and V.Breton
Lydia Maigne EGEE User Forum – Clermont-Ferrand - 11-14 February 2008 2
Enabling Grids for E-sciencE
Better treatment requires better planning
• Today: analytic calculation to compute dose distributions in the tumor or to model scans
– For new Intensity Modulated Radiotherapy treatments, analytic calculations off by 10 to 20% near heterogeneities
– Quantification of the radioactivity inside an organ or a tumor after an internal dosimetry treatment very difficult to perform
• Better alternative: Monte Carlo (MC) simulations
unacceptable time consuming• The GRID impact: reduce MC computing time to a level acceptable
by the physician
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GATE: Geant4 Application for Tomographic Emission
noyauGEANT4
Développementsdédiés
SPECT/TEP
GATE
Goal: Develop a platform dedicated to PET and SPECT applications
Ensure a long terme development
• Based on Geant4
• Dedicated tools for imaging
• Easy to use
• Shared developement• OpenGATE collaboration
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Enabling Grids for E-sciencE
Medical physics Application
Some examples of medical physics applications:
PET camera
Ocular brachytherapy treatment
Radiotherapy
OpenGATE collaboration
http://www.opengatecollaboration.org
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Pseudorandom number sequences
Random numbers consumption depends of: interactions, number of particles générated, etc…Linear RN consumption in function of the number of particles generated
x15x14x13x12x11x10x9x8x7x6x5x4x3x2x1
status000.rndm status001.rndm status002.rndm
Status 1 Status 2 Status 3
1000 status of the Random Number Generator with a length of 3.1010 numbers.
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Enabling Grids for E-sciencE
6°) Split the simulations:
• A GATE simulation generating a lot of particles in matter could take a very long time to run on a single processor
– So, the big simulation generating 10M of particles is divided into little ones, for example 10 simulations generating 1M of particles 20 simulations generating 500000 particles 50 simulations generating 200000 particles ……
– All the other files needed to launch Monte Carlo simulations are automatically created with the program.
jdl filesjobXXX.jdl
Script filesscriptXXX.csh
Required filesMacro files
macroXXX.macStatus files
statusXXX.rndm
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Enabling Grids for E-sciencE
An ocular brachytherapy treatment
2°) Treatment planning
Calculation ofdeposit dose on the tumor
(~1mn):A treatment plan is
developed using the images
1°) Obtain scanner slices images
The head is imaged using a MRI and/or CT scanner
3°) Ocular brachytherapy treatment
Irradiation of the ocular tumor using an ophthalmic
applicator
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Enabling Grids for E-sciencE
HOPE portal
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How it works on the grid
DICOM
DICOM
ConfidentialMetadata
ConfidentialMetadata
DICOM
DICOM
ConfidentialMetadata
ConfidentialMetadata
AMGAAMGA
UI
PACSPACS
I mages DI COM
Cryptage HTTPS
GridFTP
Medical images access on the gridFTP like transfers: GridFTP secured protocol
Metadata access:Proxy authentication and VOMS authorizationSecured connections using SSL (Secure Socket Layer):
cryptographic systems to transfer documentsAuthorizationb using ACLs (Access Control List)
Medical images management on the grid (AMGA server):Langages based on SQLHierarchical organizationof metadata (tree)Dynamic schemas: add,delete, modif y fieldsReplication of metadata on other AMGA servers
AMGAAMGA
UI
PACSPACS
I mages DI COM
Cryptage HTTPS
GridFTP
Medical images access on the gridFTP like transfers: GridFTP secured protocol
Metadata access:Proxy authentication and VOMS authorizationSecured connections using SSL (Secure Socket Layer):
cryptographic systems to transfer documentsAuthorizationb using ACLs (Access Control List)
Medical images management on the grid (AMGA server):Langages based on SQLHierarchical organizationof metadata (tree)Dynamic schemas: add,delete, modif y fieldsReplication of metadata on other AMGA servers
•The telemedicine infrastructure allows users to exchange medical data from different hospitals. •The information exchange takes place between web services deployed in different locations and is completely transparent to end users. •Information are transferred between different locations only on request using SOAP messages over an SSL secured channel.
Security:
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Enabling Grids for E-sciencE
1°) The connexion: to a smart adaptive identifier
• Patient smart card– The card will host an identifier based on hash value of
name, birth and family components– Each medical act is stored as a small string in the card
• Encryption– Between the PACS server and the web portal, patient
ID and medical act will be a part of a key used to encrypt images to secure transactions
• Data retrieval system– A secure authentication for patients to retrieve their
personal data
• Physician authentication– Healthcare professional smart card + Password
Look at the poster of Paul de Vlieger:Smart adaptive identifier for a medical data retrievement system
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1°) Enter a new patient: patient sheet
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2°) Obtain the medical images of the tumor from the PACS system
Scanner slices:DICOM
or DICOMRT format
• Scanner slices of the patient brain in DICOM or DICOMRT format
Size of the scan slices: 512 X 512 X 1 pixels
Size of a voxel in the image: 0,625 X 0,625 X 1,25 mm
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2°) Obtain the medical images of the tumor from the PACS system
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3°) Register and replicate the binary image on SEs:
StorageStorageElementElementComputiComputi
ngngElementElement
StorageStorageElementElementComputiComputi
ngngElementElement
StorageStorageElementElementComputiComputi
ngngElementElement
StorageStorageElementElementComputiComputi
ngngElementElement
Image:text file
Binary file:Image.rawSize 19M
Scanner slices:DICOM format
An
on
ym
isatio
n
Concatenation
DICOM Viewer
Site 1
Site 2
Site 3
Site 4
User interfaceUser interface
Copy image.raw
on a SE
Replicate image on the
other SEs
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4°) Register the confidential data:
Image:text file
Binary file:Image.rawSize 19M
Scanner slices:DICOM format
AMGADatabase
An
on
ym
isatio
n
Concatenation
StorageStorageElementElementComputiComputi
ngngElementElement
StorageStorageElementElementComputiComputi
ngngElementElement
StorageStorageElementElementComputiComputi
ngngElementElement
StorageStorageElementElementComputiComputi
ngngElementElement
Site1
Site2
Site3
Site4
Register lfn in the
database
Query a lfn to the
database
User interfaceUser interface
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5°) Submission on the Grid:
StorageStorageElementElementComputiComputi
ngngElementElement
StorageStorageElementElementComputiComputi
ngngElementElement
StorageStorageElementElementComputiComputi
ngngElementElement
StorageStorageElementElementComputiComputi
ngngElementElement
GATE
GATE
GATE
GATE
Image:text file
Binary file:Image.rawSize 19M
Scanner slices:DICOM format
AMGADatabase
User interfaceUser interface
Site1
Site2
Site3
Site4
An
on
ym
isatio
n
Concatenation
Submission of jdls to the
CEs
Copy the medical image from the SE to
the CE
Retrieving of root output
files from CEs
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5°) Submission on the Grid:
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6°) Results: Treatment plans
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Computing time tests
Local computing:260 hours on a 3GHz processorGrid computing: 10 hours for 50 divisions
Gain in computing:
26
Radiotherapy
Local computing:907 days on a 3GHz processorGrid computing:3 days for 1813 jobs, 24h/ job
Gain in computing
800
SPECT
Local computing:260 hours on a 3GHz processorGrid computing: 10 hours for 50 divisions
Gain in computing:
26
Radiotherapy
Local computing:907 days on a 3GHz processorGrid computing:3 days for 1813 jobs, 24h/ job
Gain in computing
800
SPECT
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Conclusion and perspectives
• New convivial web platforms for different biomedical applications
• Tools begin to be used by medical staff
• Grid stability, EGEEIII infrastructure• Develop convivial end users tools to be used in
hospital• Federate the communities (the HealthGrid association)• Confidential data, legal issues• Think about the electronic medical patient file and how
the grid could deal with in a near future.
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References
• EGEEII biomedical applications:– http://egee-na4.ct.infn.it/biomed/egee2-applications.html
• WISDOM: – www.wisdom.healthgrid.org
• LifeGrid project:– www.lifegrid.org
• GATE Monte Carlo platform:– www.opengatecollaboration.org
• HealthGrid initiative:– www.healthgrid.org
• Contacts:– PCSV team web site: http://clrwww.in2p3.fr/PCSV– Lydia Maigne: [email protected]