Artificial Intelligence in Microsurgical Planning: A Five-Year Leap in Clinical Translation.

Journal of clinical medicine 2025 Vol.14(13)

Shadid O, Seth I, Cuomo R, Rozen WM, Marcaccini G

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Abstract

Microsurgery is a highly complex and technically demanding field within reconstructive surgery, with outcomes heavily dependent on meticulous planning, precision, and postoperative monitoring. Over the last five years, artificial intelligence (AI) has emerged as a transformative tool across all phases of microsurgical care, offering new capabilities in imaging analysis, intraoperative decision support, and outcome prediction. A comprehensive narrative review was conducted to evaluate the peer-reviewed literature published between 2020 and May 2025. Multiple databases, including PubMed, Embase, Cochrane, Scopus, and Web of Science, were searched using combinations of controlled vocabulary and free-text terms relating to AI and microsurgery. Studies were included if they described AI applications during the preoperative, intraoperative, or postoperative phases of microsurgical care in human subjects. Using predictive models, AI demonstrated significant utility in preoperative planning through automated perforator mapping, flap design, and individualised risk stratification. AI-enhanced augmented reality and perfusion analysis tools improved precision intraoperatively, while innovative robotic platforms and intraoperative advisors showed early promise. Postoperatively, mobile-based deep learning applications enabled continuous flap monitoring with sensitivities exceeding 90%, and AI models accurately predicted surgical site infections, transfusion needs, and long-term outcomes. Despite these advances, most studies relied on retrospective single-centre data, and large-scale, prospective validation remains limited. AI is poised to enhance microsurgical precision, safety, and efficiency. However, its integration is challenged by data heterogeneity, generalisability concerns, and the need for human oversight in nuanced clinical scenarios. Standardised data collection and multicentre collaboration are vital for robust, equitable AI deployment. With careful validation and implementation, AI holds the potential to redefine microsurgical workflows and improve patient outcomes across diverse clinical settings.

추출된 의학 개체 (NER)

유형영어 표현한국어 / 풀이UMLS CUI출처등장
시술 microsurgery 미세수술 dict 2
시술 flap 피판재건술 dict 2
합병증 perforator scispacy 1
질환 infections C0851162
Infections of musculoskeletal system
scispacy 1
기타 human scispacy 1
기타 patient scispacy 1

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