Prostate cancer is the 4th most frequent cancer worldwide, being the most frequent in men and mainly associated with age, although its mortality is not particularly high compared to other neoplasms.

Molecular markers such as prostate specific antigen (PSA) and biopsy for histopathological study and tumor classification on the Gleason or ISUP scales are used for diagnosis and risk stratification. Mortality decreases dramatically when the tumor is detected and treated early. The most recent evidence demonstrates the importance of using biomedical imaging techniques, fundamentally Magnetic Resonance Imaging (MRI) for the diagnosis of prostate cancer, which avoids having to resort to biopsy in many cases and allows the follow-up of cases with negative biopsy to anticipate the diagnosis. In addition, risk stratification carried out during diagnosis is essential to achieve therapeutic success. In this framework, the overall objective of the project is the development of artificial intelligence (AI) algorithms and new MR coils and sequences, to acquire images of higher sensitivity in less than 15 minutes, and after further processing and interpretation, to establish a predictive model of aggressive cancer together with a minimum set of clinical data.

The result of this new scan will effectively implement personalized medicine in oncology clinical practice by enabling early and differential diagnosis, while also improving the monitoring and evaluation of the treatment of these patients. To carry it out, General Electric HealthCare España (GEHC), the Instituto de Investigación Sanitaria La Fe (IIS La Fe) and the Instituto de Instrumentación e Imagen Molecular (I3M) will work together.