AI to predict Cancer metastasis using Ultra-Echo-Sono imaging
Cancer metastasis is the leading cause of death within tumor disease and is currently an unmet clinical need. This dramatic clinical evidence requires immediate action in terms of early diagnosis and then pre-emptive therapies, no...
Cancer metastasis is the leading cause of death within tumor disease and is currently an unmet clinical need. This dramatic clinical evidence requires immediate action in terms of early diagnosis and then pre-emptive therapies, not only for the primary tumor, but especially at the first stages of metastasis formation. Metastasis is the result of a complex mechanism, still under study, which involves the trafficking of biological materials, in particular extracellular vesicles (EVs), from the primary tumor site towards other tissues.
The project AI CUrES aims to propose novel methodologies for early diagnosis of metastasis, by gaining new knowledge at the early stage of their formation with a real-time and predictive approach. This work has the future vision of predicting possible patient’s outcomes and helping to set timely pre-emptive therapies. I believe that this is possible by exploiting the EVs specifically produced by the primary tumor, here by colorectal cancer (CRC). In AI CUrES, such EVs will be tagged by specific nanosized-contrast agents and their trafficking in biological media reported by an innovative multi-modal bioimaging technology having high resolution, deep tissue penetration, real-time and molecular characteristics. The collected images of EVs trafficking towards recipient cells or tissues will be refined and further elaborated by artificial intelligence algorithms, with the aim to predict the possible metastasis development from a starting CRC tumor mass.
AI CuRES will prove the efficacy of this approach by enabling, as expected outcomes, deep scientific knowledge on metastasis formation mechanisms and demonstrating a breakthrough innovation in bioimaging technologies and digital tools for health monitoring and diagnosis of oncological patients. The results can be also useful in other tumors leading to metastasis and to empower Europe towards digital tools for predictive diagnosis.ver más
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