Application possibilities of artificial intelligence in facial vascularized composite allotransplantation—a narrative review

Frontiers in Surgery

Surgery

Ali-Farid Safi¹  Maximilian Miragall²  Katya Remy²  Leonard Knoedler³  Michael Alfertshofer⁴  Samuel Knoedler⁵  Omar Allam⁵  Martin Kauke-Navarro⁵  Bohdan Pomahac⁵ 

[1] Craniologicum, Center for Cranio-Maxillo-Facial Surgery, Bern, Switzerland;Faculty of Medicine, University of Bern, Bern, Switzerland;Department of Oral and Maxillofacial Surgery, University Hospital Regensburg, Regensburg, Germany;Department of Plastic, Hand- and Reconstructive Surgery, University Hospital Regensburg, Regensburg, Germany;Division of Plastic Surgery, Department of Surgery, Yale New Haven Hospital, Yale School of Medicine, New Haven, CT, United States;Division of Hand, Plastic and Aesthetic Surgery, Ludwig-Maximilians University Munich, Munich, Germany;Division of Plastic Surgery, Department of Surgery, Yale New Haven Hospital, Yale School of Medicine, New Haven, CT, United States;

关键词: vascularized composite allotransplantation;    VCA;    facial VCA;    face transplant;    artificial intelligence;    AI;    machine learning;    deep learning;   

DOI  :  10.3389/fsurg.2023.1266399

 received in 2023-07-24, accepted in 2023-09-26,  发布年份 2023

来源: Frontiers

【 摘 要 】

Facial vascularized composite allotransplantation (FVCA) is an emerging field of reconstructive surgery that represents a dogmatic shift in the surgical treatment of patients with severe facial disfigurements. While conventional reconstructive strategies were previously considered the goldstandard for patients with devastating facial trauma, FVCA has demonstrated promising short- and long-term outcomes. Yet, there remain several obstacles that complicate the integration of FVCA procedures into the standard workflow for facial trauma patients. Artificial intelligence (AI) has been shown to provide targeted and resource-effective solutions for persisting clinical challenges in various specialties. However, there is a paucity of studies elucidating the combination of FVCA and AI to overcome such hurdles. Here, we delineate the application possibilities of AI in the field of FVCA and discuss the use of AI technology for FVCA outcome simulation, diagnosis and prediction of rejection episodes, and malignancy screening. This line of research may serve as a fundament for future studies linking these two revolutionary biotechnologies.

【 授权许可】

Unknown   
© 2023 Knoedler, Knoedler, Allam, Remy, Miragall, Safi, Alfertshofer, Pomahac and Kauke-Navarro.