“人工智能、机器学习、虚拟现实和放射组学”在经皮肾镜取石术中的作用：过去30年的发表趋势综述

The role of 'artificial intelligence, machine learning, virtual reality, and radiomics' in PCNL: a review of publication trends over the last 30 years.

作者信息

Nedbal Carlotta, Cerrato Clara, Jahrreiss Victoria, Castellani Daniele, Pietropaolo Amelia, Galosi Andrea Benedetto, Somani Bhaskar Kumar

机构信息

Urology Unit, Azienda Ospedaliero-Universitaria delle Marche, Polytechnic University of Marche, Ancona, Italy.

Department of Urology, University Hospitals Southampton, NHS Trust, Southampton, UK.

出版信息

Ther Adv Urol. 2023 Sep 8;15:17562872231196676. doi: 10.1177/17562872231196676. eCollection 2023 Jan-Dec.

DOI:10.1177/17562872231196676

PMID:37693931

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10492475/

Abstract

INTRODUCTION

We wanted to analyze the trend of publications in a period of 30 years from 1994 to 2023, on the application of 'artificial intelligence (AI), machine learning (ML), virtual reality (VR), and radiomics in percutaneous nephrolithotomy (PCNL)'. We conducted this study by looking at published papers associated with AI and PCNL procedures, including simulation training, with preoperative and intraoperative applications.

MATERIALS AND METHODS

Although MeSH terms research on the PubMed database, we performed a comprehensive review of the literature from 1994 to 2023 for all published papers on 'AI, ML, VR, and radiomics' in 'PCNL', with papers in all languages included. Papers were divided into three 10-year periods: Period 1 (1994-2003), Period 2 (2004-2013), and Period 3 (2014-2023).

RESULTS

Over a 30-year timeframe, 143 papers have been published on the subject with 116 (81%) published in the last decade, with a relative increase from Period 2 to Period 3 of +427% ( = 0.0027). There was a gradual increase in areas such as automated diagnosis of larger stones, automated intraoperative needle targeting, and VR simulators in surgical planning and training. This increase was most marked in Period 3 with automated targeting with 52 papers (45%), followed by the application of AI, ML, and radiomics in predicting operative outcomes (22%, = 26) and VR for simulation (18%, = 21). Papers on technological innovations in PCNL ( = 9), intelligent construction of personalized protocols ( = 6), and automated diagnosis ( = 2) accounted for 15% of publications. A rise in automated targeting for PCNL and PCNL training between Period 2 and Period 3 was +247% ( = 0.0055) and +200% ( = 0.0161), respectively.

CONCLUSION

An interest in the application of AI in PCNL procedures has increased in the last 30 years, and a steep rise has been witnessed in the last 10 years. As new technologies are developed, their application in devices for training and automated systems for precise renal puncture and outcome prediction seems to play a leading role in modern-day AI-based publication trends on PCNL.

摘要

引言

我们希望分析1994年至2023年这30年间关于“人工智能（AI）、机器学习（ML）、虚拟现实（VR）和放射组学在经皮肾镜取石术（PCNL）中的应用”的出版物趋势。我们通过查阅与AI和PCNL手术相关的已发表论文来开展这项研究，包括模拟训练以及术前和术中应用。

材料与方法

通过在PubMed数据库中检索医学主题词（MeSH），我们对1994年至2023年期间所有关于“PCNL中的AI、ML、VR和放射组学”的已发表论文进行了全面的文献综述，纳入了所有语言的论文。论文分为三个10年时间段：第1阶段（1994 - 2003年）、第2阶段（2004 - 2013年）和第3阶段（2014 - 2023年）。

结果

在30年的时间范围内，关于该主题已发表了143篇论文，其中116篇（81%）发表于过去十年，从第2阶段到第3阶段相对增长了427%（P = 0.0027）。在诸如较大结石的自动诊断、术中自动针定位以及手术规划和训练中的VR模拟器等领域有逐渐增加的趋势。这种增长在第3阶段最为明显，自动定位方面有52篇论文（45%），其次是AI、ML和放射组学在预测手术结果中的应用（22%，n = 26）以及VR用于模拟（18%，n = 21）。关于PCNL技术创新（n = 9）、个性化方案的智能构建（n = 6）和自动诊断（n = 2）的论文占出版物的15%。第2阶段到第3阶段PCNL自动定位和PCNL训练的增长分别为247%（P = 0.0055）和200%（P = 0.0161）。