Vincent Breton

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.

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.

Grid-enabling medical image analysis

Grids have emerged as a promising technology to handle the data and compute intensive requirements of many application areas. Digital medical image processing is a promising application area for grids. Given the volume of data, the sensitivity of medical information, and the joint complexity of medical datasets and computations expected in clinical practice, the challenge is to fill the gap between the grid middleware and the requirements of clinical applications. The research project AGIR (Grid Analysis of Radiological Data) presented in this paper addresses this challenge through a combined approach: on one hand, leveraging the grid middleware through core grid medical services which target the requirements of medical data processing applications; on the other hand, grid-enabling a panel of applications ranging from algorithmic research to clinical applications.

Validation of a dose deposited by low-energy photons using GATE/GEANT4

The GATE Monte Carlo simulation platform based on the Geant4 toolkit has now become a diffused tool for simulating PET and SPECT imaging devices. In this paper, we explore its relevance for dosimetry of low-energy 125I photon brachytherapy sources used to treat prostate cancers. To that end, three 125-iodine sources widely used in prostate cancer brachytherapy treatment have been modelled. GATE simulations reproducing dosimetric reference observables such as radial dose function g(r), anisotropy function F(r, theta) and dose-rate constant (Lambda) were performed in liquid water. The calculations were splitted on the EGEE grid infrastructure to reduce the computing time of the simulations. The results were compared to other relevant Monte Carlo results and to measurements published and fixed as recommended values by the AAPM Task Group 43. GATE results agree with consensus values published by AAPM Task Group 43 with an accuracy better than 2%, demonstrating that GATE is a relevant tool for the study of the dose induced by low-energy photons.

Virtual screening on large scale grids

Large scale grids for in silico drug discovery open opportunities of particular interest to neglected and emerging diseases. In 2005 and 2006, we have been able to deploy large scale virtual docking within the framework of the WISDOM initiative against malaria and avian influenza requiring about 100 years of CPU on the EGEE, Auvergrid and TWGrid infrastructures. These achievements demonstrated the relevance of large scale grids for the virtual screening by molecular docking. This also allowed evaluating the performances of the grid infrastructures and to identify specific issues raised by large scale deployment.

Rigorous Distribution of Stochastic Simulations Using the DistMe Toolkit

Monte Carlo simulations are considered as naturally parallel, because many replications of the same experiment can be distributed on multiple execution units to reduce the global simulation time. However, one needs to take care of the underlying random number streams and ensure that the generated streams do not show intra or inter-correlations. Such errors occur in naive parallelizing approaches, they can lead to erroneous results or to a significant loss in precision. Based on a generic and documented XML format for random number generator statuses and on automatic tools to distribute stochastic simulations, the DistMe software package eases the distribution of stochastic simulations, while keeping the quality of the parallel random number streams as a critical issue. It is written in Java and has been designed to be run on any operating system and hardware with a Java virtual machine available. It has been designed using model engineering to obtain a high quality, modular and very extensible software. This toolkit, freely available on Sourceforge, is designed to speed up Monte Carlo simulations using any parallel machine based on the bag of work paradigm. It provides the user with a set of classes representing a description at a meta level of his simulation environments. Once the developer has described his simulation using DistMe classes, simulation jobs ready for runtime are instantiated. This software is released under GPL licence and the latest development sources are available online (Sourceforge CVS). This paper presents the architecture of DistMe and simulation distribution examples for Geant4 and GATE simulations. The impact of correlations is shown on the GATE application.

Guest Editorial: Special Section on Grid, Web Services, Software Agents, and Ontology Applications for Life Sciences

The ten papers in this special section focus on grid, web services, software agents, and ontology applications for life sciences. While most of the papers focus on Grid and distributed computation, others are concerned with advanced techniques and methodologies, like Web services and agent-based systems.

Mechanistic DNA damage simulations in Geant4-DNA Part 2: Electron and proton damage in a bacterial cell

We extended a generic Geant4 application for mechanistic DNA damage simulations to an Escherichia coli cell geometry, finding electron damage yields and proton damage yields largely in line with experimental results. Depending on the simulation of radical scavenging, electrons double strand breaks (DSBs) yields range from 0.004 to 0.010 DSB Gy-1 Mbp-1, while protons have yields ranging from 0.004 DSB Gy-1 Mbp-1 at low LETs and with strict assumptions concerning scavenging, up to 0.020 DSB Gy-1 Mbp-1 at high LETs and when scavenging is weakest. Mechanistic DNA damage simulations can provide important limits on the extent to which physical processes can impact biology in low background experiments. We demonstrate the utility of these studies for low dose radiation biology calculating that in E. coli, the median rate at which the radiation background induces double strand breaks is 2.8 × 10-8 DSB day-1, significantly less than the mutation rate per generation measured in E. coli, which is on the order of 10-3.

Mechanistic DNA damage simulations in Geant4-DNA part 1: A parameter study in a simplified geometry

Mechanistic modelling of DNA damage in Monte Carlo simulations is highly sensitive to the parameters that define DNA damage. In this work, we use a simple testing geometry to investigate how different choices of physics models and damage model parameters can change the estimation of DNA damage in a mechanistic DNA damage simulation built in Geant4-DNA. The choice of physics model can lead to variations by up to a factor of two in the yield of physically induced strand breaks, and the parameters that determine scavenging, and physical and chemical single strand break induction can have even larger consequences. Using low energy electrons as primary particles, a variety of parameters are tested in this geometry in order to arrive at a parameter set consistent with past simulation studies. We find that the modelling of scavenging can play an important role in determining results, and speculate that high-scavenging regimes, where only chemical radicals within 1 nm of DNA are simulated, could provide a good means of testing mechanistic DNA simulations.

Understanding low radiation background biology through controlled evolution experiments

Biological experiments conducted in underground laboratories over the last decade have shown that life can respond to relatively small changes in the radiation background in unconventional ways. Rapid changes in cell growth, indicative of hormetic behaviour and long‐term inheritable changes in antioxidant regulation have been observed in response to changes in the radiation background that should be almost undetectable to cells. Here, we summarize the recent body of underground experiments conducted to date, and outline potential mechanisms (such as cell signalling, DNA repair and antioxidant regulation) that could mediate the response of cells to low radiation backgrounds. We highlight how multigenerational studies drawing on methods well established in studying evolutionary biology are well suited for elucidating these mechanisms, especially given these changes may be mediated by epigenetic pathways. Controlled evolution experiments with model organisms, conducted in underground laboratories, can highlight the short‐ and long‐term differences in how extremely low‐dose radiation environments affect living systems, shining light on the extent to which epimutations caused by the radiation background propagate through the population. Such studies can provide a baseline for understanding the evolutionary responses of microorganisms to ionizing radiation, and provide clues for understanding the higher radiation environments around uranium mines and nuclear disaster zones, as well as those inside nuclear reactors.