External-beam radiotherapy is widely recognized as a best-practice treatment for various cancers. However, the current models used in clinical settings to optimize treatment plan dosimetry based on expected tumour response and radiation-induced toxicity lack patient-specific insights. Instead, they depend on radiobiological parameters primarily derived from in-vitro experiments, failing to capture the complexity of in-vivo pathology.

The MINIONS (Patient-specific Microstructural and radIobiological model for persoNalised external beam radiatIONn therapy in localised tumourS) project is an advanced research initiative aimed at integrating patient-specific microstructural and radiobiological models into personalized radiotherapy treatment planning and adaptation. This approach focuses on a detailed characterization of each patient’s tumour, enabling significantly improved tumour control probabilities.

The primary objective of MINIONS is to develop the first-ever real-time patient-specific model that accurately represents the microscopic features of tumours and their interactions with radiation. To achieve this, the program encompasses several scientific activities: 

1. Monte Carlo (MC) simulations of Diffusion-Weighted Magnetic Resonance (DW-MR) signals and radiation-tissue interactions using a library of in-silico cellular substrates to create an integrated simulation platform. 
2. Artificial Intelligence-based techniques to accelerate MC simulations, ensuring they are compatible with the demands of rapid treatment planning and adaptation. 
3. Advanced DW-MR imaging methods to non-invasively gather the necessary data to inform the simulation platform, enabling the development of patient-specific microstructural and radiobiological models. 

To validate the performance of these models, both in-vivo and ex-vivo testing will be conducted. The collaboration between researchers, engineers, and clinicians will ensure that this innovative strategy can be effectively implemented in clinical practice, ultimately improving survival rates and quality of life for a broad range of cancer patients.