Carlotta Nedbal, Clara Cerrato, Victoria Jahrreiss, Daniele Castellani, Amelia Pietropaolo, Andrea Benedetto Galosi, Bhaskar Kumar Somani
{"title":"“人工智能、机器学习、虚拟现实和放射组学”在PCNL中的作用:回顾过去30年的出版趋势。","authors":"Carlotta Nedbal, Clara Cerrato, Victoria Jahrreiss, Daniele Castellani, Amelia Pietropaolo, Andrea Benedetto Galosi, Bhaskar Kumar Somani","doi":"10.1177/17562872231196676","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>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.</p><p><strong>Materials and methods: </strong>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).</p><p><strong>Results: </strong>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% (<i>p</i> = 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%, <i>n</i> = 26) and VR for simulation (18%, <i>n</i> = 21). Papers on technological innovations in PCNL (<i>n</i> = 9), intelligent construction of personalized protocols (<i>n</i> = 6), and automated diagnosis (<i>n</i> = 2) accounted for 15% of publications. A rise in automated targeting for PCNL and PCNL training between Period 2 and Period 3 was +247% (<i>p</i> = 0.0055) and +200% (<i>p</i> = 0.0161), respectively.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":23010,"journal":{"name":"Therapeutic Advances in Urology","volume":null,"pages":null},"PeriodicalIF":2.6000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/d7/03/10.1177_17562872231196676.PMC10492475.pdf","citationCount":"0","resultStr":"{\"title\":\"The role of 'artificial intelligence, machine learning, virtual reality, and radiomics' in PCNL: a review of publication trends over the last 30 years.\",\"authors\":\"Carlotta Nedbal, Clara Cerrato, Victoria Jahrreiss, Daniele Castellani, Amelia Pietropaolo, Andrea Benedetto Galosi, Bhaskar Kumar Somani\",\"doi\":\"10.1177/17562872231196676\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>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.</p><p><strong>Materials and methods: </strong>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).</p><p><strong>Results: </strong>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% (<i>p</i> = 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%, <i>n</i> = 26) and VR for simulation (18%, <i>n</i> = 21). Papers on technological innovations in PCNL (<i>n</i> = 9), intelligent construction of personalized protocols (<i>n</i> = 6), and automated diagnosis (<i>n</i> = 2) accounted for 15% of publications. A rise in automated targeting for PCNL and PCNL training between Period 2 and Period 3 was +247% (<i>p</i> = 0.0055) and +200% (<i>p</i> = 0.0161), respectively.</p><p><strong>Conclusion: </strong>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.</p>\",\"PeriodicalId\":23010,\"journal\":{\"name\":\"Therapeutic Advances in Urology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/d7/03/10.1177_17562872231196676.PMC10492475.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Therapeutic Advances in Urology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1177/17562872231196676\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"UROLOGY & NEPHROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Therapeutic Advances in Urology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/17562872231196676","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"UROLOGY & NEPHROLOGY","Score":null,"Total":0}
The role of 'artificial intelligence, machine learning, virtual reality, and radiomics' in PCNL: a review of publication trends over the last 30 years.
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% (p = 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%, n = 26) and VR for simulation (18%, n = 21). Papers on technological innovations in PCNL (n = 9), intelligent construction of personalized protocols (n = 6), and automated diagnosis (n = 2) accounted for 15% of publications. A rise in automated targeting for PCNL and PCNL training between Period 2 and Period 3 was +247% (p = 0.0055) and +200% (p = 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.
期刊介绍：
Therapeutic Advances in Urology delivers the highest quality peer-reviewed articles, reviews, and scholarly comment on pioneering efforts and innovative studies across all areas of urology.
The journal has a strong clinical and pharmacological focus and is aimed at clinicians and researchers in urology, providing a forum in print and online for publishing the highest quality articles in this area. The editors welcome articles of current interest across all areas of urology, including treatment of urological disorders, with a focus on emerging pharmacological therapies.
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