Nowadays, genetic profiling and characterization of lung cancers have a role of paramount importance in order to treat patients with adequate targeted treatments and immunotherapy.

Invasive tissue biopsy is still the most common procedure to obtain tissue samples; however, it has several limitations including complications and costs. Recently, a quantitative assessment of visual features from CT data has shown promising results. In terms of mutational status gene prediction. 

The virtual biopsy project directly addresses the problem of developing a robust methodology for the automated and accurate lesion segmentation and classification as gene-addicted using only TC scan images. It leverages a novel clinical trial conducted at S. Luigi hospital in Turin conducted by a multi-disciplinary team composed of researchers from radiology, oncology, pathology and computer science departments of the University of Turin. For this, the virtual biopsy project innovates methods in life science even beyond primary objectives.

Contats:
Dr. Marco Calandri, Prof. Marco Aldinucci, Prof. Concetto Spampinato