GINSENG : une grille dédiée à l'e-santé et l'épidémiologie

Emerging challenge concerning public health statistics is the ability to provide real time information on population health. It is especially relevant in case of emergency scenarios: pollution through toxic gas emission or radioactivity, heat waves, pandemic flu viruses. The daily improvement of care practice can also benefit of any real time information on patients hosted in medical structures. To face this problematic, the french GINSENG project uses the european grid technology to create a sentinel network for e-health and epidemiology. This distributed network architecture offers many advantages: * Medical data banks from each hospital or labs can be interrogated directly without centralizing any information * Such architecture is then really cost effective. * Statistical studies will be soon available in real time through a web interface accessible by the medical staff. While patient data consistency can mainly be achieved by working on medical databases standardization, patient identification and medical data linkage mechanisms are performed dynamically through the grid network. Authentication and data encryption are ensured by healthcare professional smartcards containing an X509 grid-compatible certificate delivered by a trusted certification authority. The GINSENG project focuses on two fields: cancer surveillance and perinatal health

GINSENG (Global Initiative for Sentinel E-health Network on Grid)

The GINSENG (Global Initiative for Sentinel E-health Network on Grid) project aims to implement a grid infrastructure for ehealthand epidemiology in Auvergne. A distributed medical database is created upon a secure network for epidemiologicalstudies. Our goal is to create a decentralized information system using grid technologies. The medical sites involved in theproject are clustered around two themes: cancer monitoring and perinatal care. On each medical site a server whichduplicates the medical database, is deployed with grid services. At the same time, full control of the information is kept by theorganizations storing patients' files. This solution allows for a high level of security, privacy, availability, and fault tolerance.Queries made on the distributed medical databases are made via a secure web portal. Public health authorities use thisinfrastructure for health monitoring, epidemiological studies and evaluation of specific medical practices

New Advanced Technologies to Provide Decentralised and Secure Access to Medical Records: Case Studies in Oncology

The main problem for health professionals and patients in accessing information is that this information is very often distributed over many medical records and locations. This problem is particularly acute in cancerology because patients may be treated for many years and undergo a variety of examinations. Recent advances in technology make it feasible to gain access to medical records anywhere and anytime, allowing the physician or the patient to gather information from an “ephemeral electronic patient record”. However, this easy access to data is accompanied by the requirement for improved security (confidentiality, traceability, integrity, ...) and this issue needs to be addressed. In this paper we propose and discuss a decentralised approach based on recent advances in information sharing and protection: Grid technologies and watermarking methodologies. The potential impact of these technologies for oncology is illustrated by the examples of two experimental cases: a cancer surveillance network and a radiotherapy treatment plan. It is expected that the proposed approach will constitute the basis of a future secure “google-like” access to medical records

Dosimétrie personnalisée par simulation Monte Carlo GATE sur grille de calcul. Application à la curiethérapie oculaire.

N° d'ordre : DU 1607, EDSF 463Although often quite time consuming, Monte Carlo method is the calculation algorithm that most closely models the actual physics of the energy deposition process. The idea is to use Monte Carlo calculations in daily cancer treatment using radiation to compete with treatment planning systems (TPS) in the delivering of absorbed dose to tumour for specific treatments. To achieve this goal, two points have been particularly studied in this thesis: the validation of the GATE platform for dosimetry applications using electrons, with a specific study concerning ocular brachytherapy treatments using 106Ru/106Rh ophthalmic applicators and the deployment of GATE simulations in a grid environment to reduce the very high computation time of those simulations.Monoenergetic and polyenergetic electron dose point kernels have been simulated using the GATE platform and compared with other Monte Carlo codes. Three versions of the GEANT4 physics package have been used for the comparisons (5.2, 6.2 and 7.0). Results show that the Multiple Scattering implementation is responsible for the discrepancies observed between the codes. Simulations of ocular brachytherapy treatments compared with Monte Carlo and measurements show a good agreement. The transcription of Hounsfield units from CT images of patient's anatomy to tissue parameters is the other work presented for a next usage of GATE on voxelized images for personnalized dosimetry. The DataGrid and then the EGEE infrastructures were used to deploy GATE simulations to reduce their computation time in order to use them in clinical practice.The method used to parallelize the GATE simulations is the splitting of the random number generator (RNG) into independent sequences. Computing time tests performed on the grid testbeds show that a significant speed-up is obtained. Functionalities to split, launch and monitor GATE simulations on a grid infrastructure have been implemented on the GENIUS web portal. A first prototype of this portal is accessible from hospital to use the accurate Monte Carlo algorithms in a transparent and secure way for ocular cancer treatments.Bien que souvent assez consommatrice en temps de calcul, la méthode Monte Carlo est l'algorithme de calcul qui modélise au plus près la physique liée aux processus de dépôts d'énergie. L'idée est d'utiliser les calculs Monte Carlo dans le traitement quotidien du cancer par rayonnement pour rivaliser avec les systèmes de planification de traitement (TPS) existants dans le but de délivrer une dose absorbée à la tumeur pour des traitements spécifiques. Pour atteindre cet objectif, deux points ont été particulièrement étudiés au cours de cette thèse : la validation de la plate-forme de simulation GATE pour des applications en dosimétrie utilisant des électrons, une étude particulière est faite concernant les traitements de curiethérapie oculaire utilisant des applicateurs ophtalmiques de 106Ru/106Rh, et le déploiement des simulations GATE dans un environnement de grille pour réduire les temps de calcul très élevés de ces simulations.Des points kernels de dose d'électrons mono-énergétiques et poly-énergétiques ont été simulés en utilisant la plate-forme GATE et comparés à d'autres codes Monte Carlo. Trois versions des packages de librairies ont été utilisées pour les comparaisons (5.2, 6.2 et 7.0). Les résultats montrent que l'implémentation de la diffusion multiple est responsable des différences observées entre les codes. Les simulations de traitements de curiethérapie oculaire comparées avec d'autres Monte Carlo et des mesures montrent un bon accord. La transcription des unités Hounsfield, à partir des données scanner sur l'anatomie du patient, en paramètres tissulaires est l'autre étude présentée pour une utilisation prochaine de GATE sur des images voxélisées pour la dosimétrie personnalisée. Les infrastructures des projets DataGrid puis d'EGEE ont été utilisées pour déployer les simulations GATE afin de réduire leur temps de calcul dans le but de les utiliser en routine clinique.La méthode utilisée pour paralléliser les simulations GATE est la division du générateur de nombres aléatoires (RNG) en séquences indépendantes. Des tests de temps de calcul réalisés sur des bancs tests de grille montrent qu'un gain significatif est obtenu. Les fonctionnalités pour diviser, lancer et contrôler les simulations GATE sur une infrastructure de grille ont été implémentées sur le portail web GENIUS. Un premier prototype de ce portail est accessible à partir d'un centre hospitalier pour l'utilisation de la précision des algorithmes Monte Carlo de manière transparente et sécurisée pour des traitements de cancer de l'œil

La plateforme de simulation Monte Carlo GATe pour l’hadronthérapie

National audienceOn the behalf of the OpenGATE collaboratio

Docimétrie personnalisée par simulation Monte Carlo GATE sur grille de calcul. Application à la curiethérapie oculaire

Le but était d'optimiser la plate-forme de simulation Monte Carlo GATE ( Geant 4 Application for Tomographic Emission) pour fournir des planifications de traitements en dosimétrie précises, personnalisées et rapides. Une application à la curiethérapie oculaire est présentée. Une validation du logiciel GEANT4 est effectuée avec une modélisation de points sources émetteurs d'électrons. L'implémentation du processus de diffusion multiple doit être encore corrigé dans les prochaines versions de GEANT4. La transcription des unités Hounsfield en paramètres tissulaires est présentée pour une utilisation de GATE sur des images voxélisées. Les distributions de dose obtenues avec GATE pour les traitements de curiethérapie oculaire sont comparées et validées. Un déploiement de GATE sur grille de calcul est effectué, le gain en temps de calcul est très significatif. Un portail web d'accès convivial à la grille a été développéCLERMONT FD-BCIU Sci.et Tech. (630142101) / SudocSTRASBOURG-Bib.Central Recherche (674822133) / SudocCLERMONT FD-BUFR Dep. Physique (630142220) / SudocSudocFranceF

Implementation of S-Factor Calculation for Personalized Radionuclide Therapy Dosimetry Into the GATE Platform

International audiencePurpose: Dosimetry is of major value in the preclinical phase of radiopharmaceutical development and its clinical use may be considered an inherent part of therapy to establish the maximum tolerated dose and dose-response relationship. The OpenGATE collaboration is constantly improving the GATE Monte Carlo simulation platform for dosimetry calculations. Our team, as part of the collaboration, has proposed a method implementing S-factor calculation using GATE.Methods: The usual strategy of internal emitter dose estimation using the MIRD formalism establishes that dose can be determined by the product of S-factor times cumulated activity in the source organ.Our procedure is based on the definition of sources and targets volumes from RT-struct DICOM files obtained from patient CT scans. In GATE 8.0 (estimated release by spring 2017) it will be possible to manage DICOM files; we modified in addition the code to have the possibility to manage RT-struct files.Contoured organs from CT scan can be converted into voxelized volumes inside GATE, then simulations can be easily performed choosing a source volume and specifying target volumes. This approach has been validated in different preclinical dosimetry studies.Results: We are now able to perform S-factor calculations in preclinical models with a computing time of around 6 hours on a single CPU (Intel Xeon 3.00GHz) for an initial number of particles (gamma E=140keV) of 10⁷ and with 3 defined materials (soft tissue, lung and bone).Conclusion: We look ahead to create a useful and convenient tool for personalized internal dosimetry in the purpose of speed up S-factor calculation in preclinical and clinical trials. We consider adding S-factor calculation tool to GATE after the next release (by end 2017).Funding Support, Disclosures, and Conflict of Interest: This work was supported by grants from ANR (Agence Nationale pour la Recherche), Programme Recherche translationnelle en sante (DS0411) 2015 under contract ANR-15-CE18-003 and from ITMO "Technologies pour la sante" - AVIESA

CPOP: an open-source C++ cell population modeler combined to Geant4 simulations for radiation biology

International audienceMulticellular tumor spheroids are realistic in-vitro systems in radiation biology research to study the effect of anticancer drugs or to evaluate the resistance of cancer cells within specific conditions. When combining the modeling of spheroids together with the simulation of radiation therapy treatments using Monte Carlo methods, one could estimate cell and DNA damage to be compared with experimental endpoints. We developed a Cell Population (CPOP) modeler combined to Geant4 simulations in order to tackle how energy depositions are allocated to cells, especially when enhancing radiation outcomes using high-Z nanoparticles