ERCIM NEWS 69 April 2007 22 Special Theme: The Digital Patient based among other things on actual imaging data. Processed molecular data is used in order to perturb the radiobio- logical or pharmacodynamic cell-kill parameters about their population- based mean values. At the heart of the proposed simulation approach lies a prototype system of quantizing cell clusters included within each geometri- cal cell of a discretizing mesh, which covers the anatomic area of interest. Cell-cycle phase durations and imag- ing-based metabolism distribution define the quantization equivalence classes considered. Several algorithms have been developed so as to simulate various macroscopic mechanisms such as tumour expansion or shrinkage and mechanical boundary conditions, as well as the effects of particular drugs (eg temozolomide) and radiation on the tumorous and normal tissue under con- sideration. A number of the models developed, which mainly refer to imageable glioblastomas, have already been clini- cally validated to a substantial degree by exploiting the outcomes of pertinent clinical trials. Long-term clinical testing and adaptation procedures are in progress. The response of treatment- affected normal tissues in radiothera- peutic schemes has also been addressed for certain cases. Currently, a substantial extension of the simulation models to cases of nephroblastoma (Wilm's tumour) and breast cancer is being per- formed within the frame of the EC- funded project ACGT (Advancing Clin- ico-Genomic Trials on cancer), in col- laboration with several European insti- tutions including the Foundation for Research and Technology Hellas, Her- aklion, in Greece. Of particular clinical importance is the tight collaboration with the Paediatric Haematology and Oncology Clinic of the University of Saarland in Germany, and Belgium’s Institut Jules Bordet, located in Brus- sels. The whole effort is also supported by the NIH-NCI-funded Center for the Development of a Virtual Tumor (CviT), based in Massachusetts, USA. It is worth noting the remarkably collabo- rative character of this and other com- plementary research efforts on a global scale. It is expected that the type of model described here will provide clinicians and researchers with the option of run- ning virtual experiments to optimize cancer treatment strategies based on the specific molecular, histopathologic, imaging and historical data of individual patients. A deeper understanding of the cancer disease at a molecular level and at the same time of the related macro- scopic phenomena is a further interme- diate goal of considerable importance. Links: In Silico Ontology group, NTUA: http://www.in-silico-oncology.iccs.ntua.gr ACGT project: http://www.eu-acgt.org/ Center for the Development of a Virtual Tumor: https://www.cvit.org/ Please contact: Georgios Stamatakos National Technical University of Athens, Greece Tel: + 30 210 772 2288 E-mail: gestam@central.ntua.gr Interactive Simulation and Visualization for Cancer Treatment Planning with Grid-Based Technology by Robert G. Belleman, Michael Scarpa and Bram Stolk Can virtual reality help to understand tumour growth? Researchers at the Section Computational Science of the University of Amsterdam (UvA), SARA Computing and Networking Services (SARA) in the Netherlands and the In-Silico Oncology Group of the National Technical University of Athens (NTUA) have combined interactive Virtual Reality visualization with in-silico tumour simulation models to better comprehend tumour growth and optimize the planning of treatment schemes. Visualization is often used in situations where data analysis algorithms for the detection of features in scientific data are too limited or do not even exist. It exploits the researcher's visual acuity, cognitive abilities, expertise and experi- ence in recognizing patterns. One of its application areas is computer simula- tion. Simulation results are often repre- sented by abstract mathematical struc- tures, and visualization is used to con- vert these into pictures. At the core of every simulation is a mathematical model that is evaluated by a computer. Invariably, a computer sim- ulation model is defined by a number of parameters that control the behaviour of the simulation, and which are therefore of crucial importance to the model developer and the end-user of the model. Awareness of a model’s behaviour is greatly enhanced when a researcher is given the ability to control a simulation by interactively manipulating the model’s parameters. Such an interactive system aids in exploring the behaviour of a simulation because parameter changes are immediately visible. This provides a feedback-response mecha- nism allowing a researcher to use the visualization to plan a response. Tumour Growth Simulation In the EU-funded project ‘Advancing Clinico-Genomic Trials (ACGT) on Cancer’, researchers collaborate to combine interactive visualization, vir- tual reality technology and in-silico tumour growth simulations into an interactive environment. This can be used to explore simulated predictions of tumour growth and treatment response. The architecture constructed in ACGT consists of a Grid-based distributed computing and software framework. It