Currently submitted to: Journal of Medical Internet Research
Date Submitted: Aug 22, 2026
Open Peer Review Period: Aug 23, 2026 - Oct 18, 2026
(currently open for review)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Applications, Predictive Models, and Clinical Integration of Artificial Intelligence in Autologous Breast Reconstruction: Scoping Review
ABSTRACT
Background:
Artificial intelligence has undergone rapid development in recent years and is increasingly integrated into various medical specialties, including plastic and reconstructive surgery. However, a comprehensive mapping of AI applications specific to autologous breast reconstruction is required.
Objective:
This scoping review aims to systematically map the current literature regarding artificial intelligence applications in autologous breast reconstruction.
Methods:
A scoping review was conducted using the MEDLINE, Scopus and Embase databases. Full-text original articles investigating the use of AI in autologous breast reconstruction published between January 1, 2020, to June 30, 2026, were included. Abstracts, case reports, animal studies and studies evaluating non-autologous breast reconstruction exclusively were excluded. Thirty studies met the final eligibility criteria.
Results:
Among the 30 included studies, AI was predominantly applied in the preoperative phase, with emerging applications in intraoperative and postoperative care. Preoperatively, AI was utilized for risk and complication prediction, patient-reported outcomes, patient satisfaction modeling, automated imaging analysis, and interactive patient counseling. AI was applied intraoperatively to answer clinical queries and quantify perforators in DIEP flap surgery. Postoperatively, deep learning models were applied to postoperative assessment and patient-centered outcome evaluations.
Conclusions:
AI is currently applied extensively in the preoperative phase of autologous breast reconstruction for predictive modelling, imaging automation and patient counseling. Intraoperative and postoperative applications are equally emerging. Further studies are required to validate these models on larger, diverse datasets to ensure safety and accuracy before routine clinical adoption.
Citation
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Copyright
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