Department of Dermatology, Warren Alpert Medical School, Brown University, Providence, Rhode Island.
Warren Alpert Medical School, Brown University, Providence, Rhode Island.
Dermatol Surg. 2024 Sep 1;50(9):799-806. doi: 10.1097/DSS.0000000000004297. Epub 2024 Jul 11.
Over the past decade, several studies have shown that potential of artificial intelligence (AI) in dermatology. However, there has yet to be a systematic review evaluating the usage of AI specifically within the field of Mohs micrographic surgery (MMS).
In this review, we aimed to comprehensively evaluate the current state, efficacy, and future implications of AI when applied to MMS for the treatment of nonmelanoma skin cancers (NMSC).
A systematic review and meta-analysis was conducted following PRISMA guidelines across several databases, including PubMed/MEDLINE, Embase, and Cochrane libraries. A predefined protocol was registered in PROSPERO, with literature search involving specific keywords related to AI and Mohs surgery for NMSC.
From 23 studies evaluated, our results find that AI shows promise as a prediction tool for precisely identifying NMSC in tissue sections during MMS. Furthermore, high AUC and concordance values were also found across the various usages of AI in MMS, including margin control, surgical recommendations, similarity metrics, and in the prediction of stage and construction complexity.
The findings of this review suggest promising potential for AI to enhance the accuracy and efficiency of Mohs surgery, particularly for NMSC.
在过去的十年中，已有多项研究表明人工智能（AI）在皮肤科领域具有潜力。然而，目前还没有系统的综述评估 AI 在 Mohs 显微外科（MMS）领域的具体应用。
在本次综述中，我们旨在全面评估 AI 在治疗非黑素瘤皮肤癌（NMSC）的 MMS 中的应用的当前状态、疗效和未来影响。
根据 PRISMA 指南，我们在多个数据库（包括 PubMed/MEDLINE、Embase 和 Cochrane 图书馆）中进行了系统的回顾和荟萃分析。文献检索涉及与 AI 和 MMS 治疗 NMSC 相关的特定关键词，并在 PROSPERO 中预先注册了方案。
从评估的 23 项研究中，我们的结果发现 AI 作为一种预测工具，在 MMS 中准确识别组织切片中的 NMSC 方面具有广阔的应用前景。此外，在 MMS 中 AI 的各种应用（包括边缘控制、手术建议、相似性度量以及对阶段和构建复杂度的预测）中，也发现了高 AUC 和一致性值。
本综述的研究结果表明，AI 有潜力提高 Mohs 手术的准确性和效率，特别是对于 NMSC。
