RadioVal will implement a comprehensive clinical evaluation of radiomics-driven estimation of NAC response, involving a diverse sample of EU training cases and multi-continent testing cases through the AI4HI Network. Three key innovations will drive this initiative. Firstly, a novel radiomics evaluation framework will be established, incorporating specific criteria, metrics, and methods like the Radiomics Usability Scale and specialised cost-effectiveness analysis. Moreover, transfer learning and domain adaptation will be employed to evaluate the applicability of radiomics solutions across Europe and beyond. Secondly, a radiomics traceability tool will be developed, including a radiomics passport for model monitoring, along with functions for quality control, failure detection, periodic evaluation, and continuous learning. Finally, a comprehensive multi-stakeholder radiomics information and communication package will enhance awareness and inclusion in radiomics-driven prediction of NAC response in breast cancer. Moreover, RadioVal will establish a legal governance framework to enable data sharing while upholding compliance with data privacy regulations and safeguarding citizen rights. Additionally, the project will devise standards and best practices to ensure future AI solutions are technically robust, clinically safe, and devoid of bias. The multi-stakeholder approach will foster shared decision-making and dialogue between clinicians and patients/caregivers, improving tool effectiveness and patient engagement. Social innovation will guide innovations and evaluations, considering diverse needs and contexts, while systematically analysing clinical, ethical, and regulatory implications. To ensure further uptake and success, the project has identified crucial requirements including follow-up research, end user testing, real-world demonstrations, and legal counsel support.
