TwinCaRT

This project aims to develop a digital twin for patients diagnosed with prostate cancer to predict tumor progression and response to radiotherapy. By integrating multi-omics data (e.g., hypoxia, cell proliferation, gene expression) with mechanistic modeling, the digital twin will enable in-silico simulations for optimizing treatment plans. Based on a biologically-driven mechanistic model of tumor growth and response to irradiation, this patient-specific digital twin will address challenges such as model calibration, partial observability, and the complexity of radiobiological mechanisms across multiple spatio-temporal scales. To increase the predictive capabilities and personalize the radiotherapy, novel data fusion approaches will be combined with new observables from MRI sequences, PSMA PET-CT, histopathology, and transcriptomics.

The project will be carried out by eight teams with multidisciplinary expertise in imaging physicshistopathology, radiobiology, Monte Carlo simulation, mechanistic modeling, medical physics, artificial intelligence, and clinical practice. This collaboration, including an industrial partner for technology transfer, will ensure the successful development and implementation of the digital twin not only for prostate cancer treatment but this methodology could be easily applied to other anatomical localizations.

This project leverages the expertise of the two first French radiotherapy centers to install the MR-Linac Elekta Unity (1.5 T MRI), platforms unique in France that enable the delivery of highly precise treatments. The project will result in advancements in medical physics, imaging, and AI, improving patient outcomes through personalized therapies and reducing healthcare costs via optimized treatment processes. By tailoring therapies with the digital twin, this approach will allow to improve quality of life for prostate cancer patients.