Applications and challenges of artificial intelligence in plastic surgery imaging: A narrative review

BACKGROUND As artificial intelligence (AI) continues to expand across medical specialties, its application in medical imaging within plastic and reconstructive surgery (PRS) remains limited in the literature. Imaging plays a critical role in surgical planning, intraoperative decision-making, and postoperative monitoring in PRS, presenting an opportunity for AI to enhance clinical outcomes. AIM To evaluate the current applications of AI in medical imaging for plastic surgery, with a focus on its use in preoperative planning, intraoperative guidance, and postoperative monitoring. METHODS A literature search was conducted using MEDLINE, EMBASE, ScienceDirect, and OVID up to February 2025. Studies were included based on relevance to AI use in plastic surgery imaging. Extracted data included AI modality, surgical context, outcomes, and limitations. The search followed PRISMA guidelines and was registered with PROSPERO (CRD420251008741). RESULTS AI tools have improved preoperative planning through three-dimensional vascular mapping, augmented reality, and thermographic imaging. Intraoperatively, AI-enabled navigation and robotic systems have increased surgical precision. Postoperative AI applications, including deep learning algorithms and sensor-based monitoring, support early complication detection and wound healing assessment. However, persistent barriers include data variability, model generalizability, surgeon unfamiliarity, and lack of regulatory standards. CONCLUSION AI-driven imaging technologies show promise in enhancing decision-making and outcomes in PRS. To ensure safe clinical integration, future efforts must focus on structured validation, standardization, and ethical oversight.