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基于模拟的微创手术治疗培训(MIST):人工智能整合的当前证据和未来方向——欧洲泌尿外科学会腔内泌尿外科的系统评价

Simulation-based training in minimally invasive surgical therapies (MIST): current evidence and future directions for artificial intelligence integration-a systematic review by EAU endourology.

作者信息

Nedbal Carlotta, Gauhar Vineet, Herrmann Thomas, Singh Abhishek, Talyshinskii Ali, Al Jaafari Feras, Somani Bhaskar Kumar

机构信息

Polytechnic University Le Marche, Ancona, Italy.

Urology, ASST Fatebenefratelli Sacco, Milan, Italy.

出版信息

World J Urol. 2025 Jul 18;43(1):448. doi: 10.1007/s00345-025-05834-8.

Abstract

INTRODUCTION

Benign prostatic hyperplasia (BPH) affects a growing proportion of the aging male population. Minimally invasive surgical therapies (MISTs) such as Rezum and UroLift offer effective alternatives to traditional approaches like transurethral resection of the prostate (TURP). However, training in these procedures is challenged by limited case exposure and variability across residency programs. Simulation-based training has emerged as a valuable tool to enhance surgical education. This study aims to assess the current evidence on simulation-based training for Rezum and UroLift, evaluating its validity, effectiveness, and potential integration with artificial intelligence (AI) in urology education.

MATERIALS AND METHODS

A systematic literature review was conducted on March 11, 2025, across PubMed, Scopus, Cochrane, and Google Scholar following PRISMA guidelines. Search terms included combinations of MIST techniques (Rezum, UroLift, iTIND) and training modalities (simulation, virtual reality, artificial intelligence). Studies were selected using PICOS criteria, focusing on urology trainees undergoing simulation-based training. Preclinical, review, and non-English studies were excluded.

RESULTS

only 3 studies met the inclusion criteria: one focused on Ron between junior and senior residents, especially in implant placement and procedural technique. Simulation was highly rated by trainees in workshop settings, though predictive validity remains unproven.

CONCLUSION

Simulation-based training for Rezum and UroLift is a promising method to enhance resident competency in MIST procedures. Current evidence supports its face, content, and construct validity, though further studies are needed to confirm predictive validity and optimize training protocols. Integration of AI and telementoring may further improve training effectiveness and accessibility across institutions.

摘要

引言

良性前列腺增生(BPH)影响着日益增多的老年男性人群。诸如Rezum和UroLift等微创外科治疗方法(MIST)为经尿道前列腺切除术(TURP)等传统方法提供了有效的替代方案。然而,这些手术的培训面临着病例接触有限和各住院医师培训项目之间存在差异的挑战。基于模拟的培训已成为增强外科教育的一种有价值的工具。本研究旨在评估目前关于Rezum和UroLift基于模拟培训的证据,评估其有效性、效能以及在泌尿外科教育中与人工智能(AI)潜在整合的情况。

材料与方法

2025年3月11日,按照PRISMA指南,在PubMed、Scopus、Cochrane和谷歌学术上进行了系统的文献综述。检索词包括MIST技术(Rezum、UroLift、iTIND)和培训方式(模拟、虚拟现实、人工智能)的组合。使用PICOS标准选择研究,重点关注接受基于模拟培训的泌尿外科住院医师。排除临床前研究、综述和非英文研究。

结果

仅3项研究符合纳入标准:一项关注初级和高级住院医师之间的Rezum培训,特别是在植入物放置和手术技术方面。在工作坊环境中,模拟受到学员的高度评价,不过预测有效性仍未得到证实。

结论

Rezum和UroLift基于模拟的培训是提高住院医师在MIST手术中能力的一种有前景的方法。目前的证据支持其表面效度、内容效度和结构效度,不过需要进一步研究来证实预测效度并优化培训方案。人工智能和远程指导的整合可能会进一步提高培训效果和各机构之间的可及性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2086/12274230/5069a975a6e8/345_2025_5834_Fig1_HTML.jpg

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