Lydia Maigne

Medical Images Simulation, Storage, and Processing on the European DataGrid Testbed

The European 1ST DataGrid project was a pioneer in identifying the medical imaging field as an application domain that can benefit from Grid technologies. This paper describes how and for which purposes medical imaging applications can be Grid-enabled. Applications that have been deployed on the DataGrid testbed and middleware are described. They relate to medical image manipulation, including image production, secured image storage, and image processing. Results show that Grid technologies are still in their youth to address all issues related to complex medical imaging applications. If the benefit of Grid enabling for some medical applications is clear, there remain opened research and technical issues to develop and integrate all necessary services.

Track structure modeling in liquid water: A review of the Geant4-DNA very low energy extension of the Geant4 Monte Carlo simulation toolkit

Understanding the fundamental mechanisms involved in the induction of biological damage by ionizing radiation remains a major challenge of todays radiobiology research. The Monte Carlo simulation of physical, physicochemical and chemical processes involved may provide a powerful tool for the simulation of early damage induction. The Geant4-DNA extension of the general purpose Monte Carlo Geant4 simulation toolkit aims to provide the scientific community with an open source access platform for the mechanistic simulation of such early damage. This paper presents the most recent review of the Geant4-DNA extension, as available to Geant4 users since June 2015 (release 10.2 Beta). In particular, the review includes the description of new physical models for the description of electron elastic and inelastic interactions in liquid water, as well as new examples dedicated to the simulation of physicochemical and chemical stages of water radiolysis. Several implementations of geometrical models of biological targets are presented as well, and the list of Geant4-DNA examples is described.

PARALLELIZATION OF MONTE CARLO SIMULATIONS AND SUBMISSION TO A GRID ENVIRONMENT

Monte Carlo simulations are increasingly used in medical physics. In scintigraphic imaging these simulations are used to model imaging systems and to develop and assess tomographic reconstruction algorithms and correction methods for improved image quantization. In radiotherapy-brachytherapy the goal is to evaluate accurately the dosimetry in complex phantoms and at interfaces of tissue, where analytic calculations have shown some limits. The main drawback of Monte Carlo simulations is their high computing time. The aim of our research is to reduce the computing time by parallelizing a simulation on geographically distributed processors. The method is based on the parallelization of the Random Number Generator (RNG) used in Monte Carlo simulations. The long serial of numbers used by the sequential simulation is split. Once the partitioning is done, a software application allows the user to generate automatically the files describing each simulation part. Finally, another software executes them on the DataGrid testbed using an API. All these steps have been made transparent for the user by providing a web page asking the user for all the parameters necessary to launch the simulation and retrieve results. Different tests have been done in order to show first, the reliability of the physical results obtained by concatenation of parallelized output data and secondly the time gained for jobs execution.

Comparison of GATE/GEANT4 with EGSnrc and MCNP for electron dose calculations at energies between 15 keV and 20 MeV

The GATE Monte Carlo simulation platform based on the GEANT4 toolkit has come into widespread use for simulating positron emission tomography (PET) and single photon emission computed tomography (SPECT) imaging devices. Here, we explore its use for calculating electron dose distributions in water. Mono-energetic electron dose point kernels and pencil beam kernels in water are calculated for different energies between 15 keV and 20 MeV by means of GATE 6.0, which makes use of the GEANT4 version 9.2 Standard Electromagnetic Physics Package. The results are compared to the well-validated codes EGSnrc and MCNP4C. It is shown that recent improvements made to the GEANT4/GATE software result in significantly better agreement with the other codes. We furthermore illustrate several issues of general interest to GATE and GEANT4 users who wish to perform accurate simulations involving electrons. Provided that the electron step size is sufficiently restricted, GATE 6.0 and EGSnrc dose point kernels are shown to agree to within less than 3% of the maximum dose between 50 keV and 4 MeV, while pencil beam kernels are found to agree to within less than 4% of the maximum dose between 15 keV and 20 MeV.

PDB4DNA: Implementation of DNA geometry from the Protein Data Bank (PDB) description for Geant4-DNA Monte-Carlo simulations

This paper describes PDB4DNA, a new Geant4 user application, based on an independent, cross-platform, free and open source C++ library, so-called PDBlib, which enables use of atomic level description of DNA molecule in Geant4 Monte Carlo particle transport simulations. For the evaluation 15 of direct damage induced on the DNA molecule by ionizing particles, the application makes use of an algorithm able to determine the closest atom in the DNA molecule to energy depositions. Both the PDB4DNA application and the PDBlib library are available as free and open source

Simulating the Impact of the Natural Radiation Background on Bacterial Systems: Implications for Very Low Radiation Biological Experiments.

At very low radiation dose rates, the effects of energy depositions in cells by ionizing radiation is best understood stochastically, as ionizing particles deposit energy along tracks separated by distances often much larger than the size of cells. We present a thorough analysis of the stochastic impact of the natural radiative background on cells, focusing our attention on E. coli grown as part of a long term evolution experiment in both underground and surface laboratories. The chance per day that a particle track interacts with a cell in the surface laboratory was found to be 6 × 10−5 day−1, 100 times less than the expected daily mutation rate for E. coli under our experimental conditions. In order for the chance cells are hit to approach the mutation rate, a gamma background dose rate of 20 μGy hr−1 is predicted to be required.

Innovative In Silico Approaches to Address Avian Flu Using Grid Technology

The recent years have seen the emergence of diseases which have spread very quickly all around the world either through human travels like SARS or animal migration like avian flu. Among the biggest challenges raised by infectious emerging diseases, one is related to the constant mutation of the viruses which turns them into continuously moving targets for drug and vaccine discovery. Another challenge is related to the early detection and surveillance of the diseases as new cases can appear just anywhere due to the globalization of exchanges and the circulation of people and animals around the earth, as recently demonstrated by the avian flu epidemics. For 3 years now, a collaboration of teams in Europe and Asia has been exploring some innovative in silico approaches to better tackle avian flu taking advantage of the very large computing resources available on international grid infrastructures. Grids were used to study the impact of mutations on the effectiveness of existing drugs against H5N1 and to find potentially new leads active on mutated strains. Grids allow also the integration of distributed data in a completely secured way. The paper proposes new approaches for the integration of existing data sources towards a global surveillance network for molecular epidemiology and in silico drug discovery.

Tetraspanin 8 (TSPAN 8) as a potential target for radio-immunotherapy of colorectal cancer

Tetraspanin 8 (TSPAN8) overexpression is correlated with poor prognosis in human colorectal cancer (CRC). A murine mAb Ts29.2 specific for human TSPAN8 provided significant efficiency for immunotherapy in CRC pre-clinical models. We therefore evaluate the feasability of targeting TSPAN8 in CRC with radiolabeled Ts29.2. Staining of tissue micro-arrays with Ts29.2 revealed that TSPAN8 espression was restricted to a few human healthy tissues. DOTA-Ts29.2 was radiolabeled with 111In or 177Lu with radiochemical purities >95%, specific activity ranging from 300 to 600 MBq/mg, and radioimmunoreactive fractions >80%. The biodistribution of [111In]DOTA-Ts29.2 in nude mice bearing HT29 or SW480 CRC xenografts showed a high specificity of tumor localization with high tumor/blood ratios (HT29: 4.3; SW480-TSPAN8: 3.9 at 72h and 120h post injection respectively). Tumor-specific absorbed dose calculations for [177Lu]DOTA-Ts29.2 was 1.89 Gy/MBq, establishing the feasibility of using radioimmunotherapy of CRC with this radiolabeled antibody. A significant inhibition of tumor growth in HT29 tumor-bearing mice treated with [177Lu]DOTA-Ts29.2 was observed compared to control groups. Ex vivo experiments revealed specific DNA double strand breaks associated with cell apoptosis in [177Lu]DOTA-Ts29.2 treated tumors compared to controls. Overall, we provide a proof-of-concept for the use of [111In/177Lu]DOTA-Ts29.2 that specifically target in vivo aggressive TSPAN8-positive cells in CRC.

Development of a Metamodel for Medical Database Management on a Grid Network: Application to Health Watch and Epidemiology for Cancer and Perinatal Health

Centralized management of patient data is no more a viable solution. In many countries, patient identification restrictions due to privacy laws implies developing thorough mechanism to avoid duplicates and information loss. In this paper we present a work in progress dealing with a grid distributed medical data base. GPU based identification algorithms for disease surveillance, medical data exchange and epidemiological analyses.

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.