SP 8.07 Use of Artificial Intelligence in Pre-Operative Planning for Oncoplastic Breast Surgery: A Systematic Review
Chien Lin Soh, Omar Haidar, Meera JoshiAbstract
Background
Artificial intelligence (AI) is a rapidly emerging field of computer science that has wide reaching potential for clinical application in breast cancer surgery. This systematic review explores the current use of AI in pre-operative oncoplastic surgery planning, aiming to optimize patient outcomes through data-driven, personalized decision-making by leveraging big data.
Methods
A systematic review was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). A Pubmed search was conducted between inception to 27th November 2025. Studies which investigated the performance of AI models in the field of oncoplastic breast surgery were included. Title/abstract and full-text screening were performed by two independent reviewers. A qualitative synthesis was performed.
Results
Twenty-two studies, involving a total of 42,424 patients, met the inclusion criteria. These studies were categorized into prognostication and prediction of complications (n=12), decision-making (n=7), and axillary de-escalation (n=3). AI was found to be effective in predicting cancer recurrence, disease-free survival, complications related to reconstruction (e.g. nipple-areolar complex necrosis, implant issues), and axillary node metastasis. The studies reporting AUC outcomes showed a range of 0.65 to 0.99. Models such as XGBoost and deep survival regression with mixture effects demonstrated non-inferior performance compared to traditional statistical methods. Additionally, AI tools were able to replicate multidisciplinary team discussions and provide patient counselling.
Conclusion
AI is a rapidly advancing field with great potential to enhance pre-operative decision-making in oncoplastic breast surgery. AI is poised to become a valuable tool in clinical settings, improving both clinical outcomes and patient care.