Personalized medicine allows more efficient navigation of the therapeutic path by integrating the different omics dimensions of the individual patient.

Therefore, the collection of omics data and medical data management platforms are crucial for technological development, although they are burdened by substantial costs of implementation, management, updating, and maintenance, hence the importance of the WG coordinated by Luca Boldrini of the Fondazione IRCCS Policlinico Gemelli in Rome.

Radiomics, as the quantitative interpretation of bio-imaging through special software, is a significant opportunity for data collection to understand better the biological characteristics of the disease and the patient’s clinical history. It can be applied to any biomedical imaging currently used in clinical practice (e.g., computed axial tomography, PET examinations, magnetic resonances, ultrasound or traditional radiology) and represents an innovative and evolving field of research.

Two main types of application are identified in clinical practice: tissue characterization and prediction of outcomes. In the first, radiomics represents a kind of virtual biopsy, “enriching” the traditional radiological diagnostic process and obtaining characterizations of the tissues under examination normally impossible with traditional radiological approaches (e.g., expression of a given gene or cellular grading). The second integrates this quantitative information in the clinical decision-making process for the prediction of specific outcomes, such as the effectiveness of the proposed treatment.