Intraoperative-technologies advancements in automated cancer detection: a narrative review

The field of intraoperative cancer detection and profiling raises a conspicuous number of challenges, including time constraints and sensitivity requirements. In this review, we analyze the state of the art of imaging and biopsy techniques to address these challenges. Artificial Intelligence (AI) for processing (i) biomechanical parameters such as Young moduli and ultrasound attenuation coefficients and (ii) color, shape and fluorescent properties in imaging approaches, may be the key for overcoming the temporal-sensitivity complexity. Providing surgeons with advanced technologies, in order to objectively standardize the diagnostic phases of cancer surgeries, has paramount importance to foster progresses in the field that can effectively translate in clinical practice. With this review, we provided an overview of the latest intraoperative technologies for tumor localization, focusing on the possible advantages for the healthcare system that can be obtained with the integration of AI techniques.