Simple Summary Computer vision (CV) is a field of artificial intelligence (AI) that deals with the automatic analysis of videos and images. Recent advances in AI and CV methods coupled with the growing availability of surgical videos of minimally invasive procedures have led to the development of AI-based algorithms to improve surgical care. Initial proofs of concept have focused on fairly standardized procedures such as laparoscopic cholecystectomy. However, the real value of CV in surgery resides in analyzing and providing assistance in more complex and variable procedures such as colorectal resections. This manuscript provides a brief introduction to AI for surgeons and a comprehensive overview of CV solutions for colorectal cancer surgery. Artificial intelligence (AI) and computer vision (CV) are beginning to impact medicine. While evidence on the clinical value of AI-based solutions for the screening and staging of colorectal cancer (CRC) is mounting, CV and AI applications to enhance the surgical treatment of CRC are still in their early stage. This manuscript introduces key AI concepts to a surgical audience, illustrates fundamental steps to develop CV for surgical applications, and provides a comprehensive overview on the state-of-the-art of AI applications for the treatment of CRC. Notably, studies show that AI can be trained to automatically recognize surgical phases and actions with high accuracy even in complex colorectal procedures such as transanal total mesorectal excision (TaTME). In addition, AI models were trained to interpret fluorescent signals and recognize correct dissection planes during total mesorectal excision (TME), suggesting CV as a potentially valuable tool for intraoperative decision-making and guidance. Finally, AI could have a role in surgical training, providing automatic surgical skills assessment in the operating room. While promising, these proofs of concept require further development, validation in multi-institutional data, and clinical studies to confirm AI as a valuable tool to enhance CRC treatment.

Quero, G., Mascagni, P., Kolbinger, F. R., Fiorillo, C., De Sio, D., Longo, F., Schena, C. A., Laterza, V., Rosa, F., Menghi, R., Papa, V., Tondolo, V., Cina, C., Distler, M., Weitz, J., Speidel, S., Padoy, N., Alfieri, S., Artificial Intelligence in Colorectal Cancer Surgery: Present and Future Perspectives, <<CANCERS>>, 2022; 14 (15): N/A-N/A. [doi:10.3390/cancers14153803] [https://hdl.handle.net/10807/230891]

Artificial Intelligence in Colorectal Cancer Surgery: Present and Future Perspectives

Quero, Giuseppe;Mascagni, Pietro;Fiorillo, Claudio;De Sio, Davide;Longo, Fabio;Schena, Carlo Alberto;Laterza, Vito;Rosa, Fausto;Menghi, Roberta;Papa, Valerio;Tondolo, Vincenzo;Alfieri, Sergio
2022

Abstract

Simple Summary Computer vision (CV) is a field of artificial intelligence (AI) that deals with the automatic analysis of videos and images. Recent advances in AI and CV methods coupled with the growing availability of surgical videos of minimally invasive procedures have led to the development of AI-based algorithms to improve surgical care. Initial proofs of concept have focused on fairly standardized procedures such as laparoscopic cholecystectomy. However, the real value of CV in surgery resides in analyzing and providing assistance in more complex and variable procedures such as colorectal resections. This manuscript provides a brief introduction to AI for surgeons and a comprehensive overview of CV solutions for colorectal cancer surgery. Artificial intelligence (AI) and computer vision (CV) are beginning to impact medicine. While evidence on the clinical value of AI-based solutions for the screening and staging of colorectal cancer (CRC) is mounting, CV and AI applications to enhance the surgical treatment of CRC are still in their early stage. This manuscript introduces key AI concepts to a surgical audience, illustrates fundamental steps to develop CV for surgical applications, and provides a comprehensive overview on the state-of-the-art of AI applications for the treatment of CRC. Notably, studies show that AI can be trained to automatically recognize surgical phases and actions with high accuracy even in complex colorectal procedures such as transanal total mesorectal excision (TaTME). In addition, AI models were trained to interpret fluorescent signals and recognize correct dissection planes during total mesorectal excision (TME), suggesting CV as a potentially valuable tool for intraoperative decision-making and guidance. Finally, AI could have a role in surgical training, providing automatic surgical skills assessment in the operating room. While promising, these proofs of concept require further development, validation in multi-institutional data, and clinical studies to confirm AI as a valuable tool to enhance CRC treatment.
2022
Inglese
Quero, G., Mascagni, P., Kolbinger, F. R., Fiorillo, C., De Sio, D., Longo, F., Schena, C. A., Laterza, V., Rosa, F., Menghi, R., Papa, V., Tondolo, V., Cina, C., Distler, M., Weitz, J., Speidel, S., Padoy, N., Alfieri, S., Artificial Intelligence in Colorectal Cancer Surgery: Present and Future Perspectives, <<CANCERS>>, 2022; 14 (15): N/A-N/A. [doi:10.3390/cancers14153803] [https://hdl.handle.net/10807/230891]
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