尿液细胞学:报告系统、辅助研究和人工智能的更新与挑战

Juan Xing , Jordan P. Reynolds , Xiaoying Liu , Liron Pantanowitz
{"title":"尿液细胞学:报告系统、辅助研究和人工智能的更新与挑战","authors":"Juan Xing ,&nbsp;Jordan P. Reynolds ,&nbsp;Xiaoying Liu ,&nbsp;Liron Pantanowitz","doi":"10.1016/j.hpr.2024.300733","DOIUrl":null,"url":null,"abstract":"<div><p>Several urine cytology classifications have been published in the literature. However, global acceptance in the field of urine cytology was only gained in 2016 after The Paris System for reporting urinary cytology was published. Despite this Paris System and its shifted focus toward the detection of high-grade urothelial carcinoma, the perceived weakness of low sensitivity and indeterminate diagnoses when screening with urine cytology remains unresolved. To overcome these shortcomings, investigators have studied a variety of emerging ancillary tests to augment urine cytology (UroVysion, ImmunoCyt/uCyte+, BTA-stat/TRAK, NMP22, SCD-A7, URO17, CellDetect, UroMark, UroSEEK). Furthermore, with the advent of digital cytology, the creation of artificial intelligence tools has created innovative opportunities to aid with urine cytology. This review article discusses the lessons learned in the evolution of reporting systems, explores the merit and challenges of ancillary tests, and calls attention to potential utility of applying artificial intelligence in urine cytology.</p></div>","PeriodicalId":100612,"journal":{"name":"Human Pathology Reports","volume":"35 ","pages":"Article 300733"},"PeriodicalIF":0.0000,"publicationDate":"2024-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772736X24000057/pdfft?md5=47d0e37442379d106c973709c84ef298&pid=1-s2.0-S2772736X24000057-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Urine cytology: Updates and challenges in reporting systems, ancillary studies, and artificial intelligence\",\"authors\":\"Juan Xing ,&nbsp;Jordan P. Reynolds ,&nbsp;Xiaoying Liu ,&nbsp;Liron Pantanowitz\",\"doi\":\"10.1016/j.hpr.2024.300733\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Several urine cytology classifications have been published in the literature. However, global acceptance in the field of urine cytology was only gained in 2016 after The Paris System for reporting urinary cytology was published. Despite this Paris System and its shifted focus toward the detection of high-grade urothelial carcinoma, the perceived weakness of low sensitivity and indeterminate diagnoses when screening with urine cytology remains unresolved. To overcome these shortcomings, investigators have studied a variety of emerging ancillary tests to augment urine cytology (UroVysion, ImmunoCyt/uCyte+, BTA-stat/TRAK, NMP22, SCD-A7, URO17, CellDetect, UroMark, UroSEEK). Furthermore, with the advent of digital cytology, the creation of artificial intelligence tools has created innovative opportunities to aid with urine cytology. This review article discusses the lessons learned in the evolution of reporting systems, explores the merit and challenges of ancillary tests, and calls attention to potential utility of applying artificial intelligence in urine cytology.</p></div>\",\"PeriodicalId\":100612,\"journal\":{\"name\":\"Human Pathology Reports\",\"volume\":\"35 \",\"pages\":\"Article 300733\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-02-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2772736X24000057/pdfft?md5=47d0e37442379d106c973709c84ef298&pid=1-s2.0-S2772736X24000057-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Human Pathology Reports\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2772736X24000057\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Human Pathology Reports","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772736X24000057","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

文献中已发表了多种尿液细胞学分类方法。然而,直到 2016 年尿液细胞学报告巴黎体系(The Paris System for reporting urinary cytology)发布后,尿液细胞学领域才获得全球认可。尽管有了巴黎系统,并且其重点转向检测高级别尿路上皮癌,但尿液细胞学筛查中灵敏度低和诊断不确定的弱点仍未得到解决。为了克服这些缺点,研究人员研究了各种新出现的辅助检测方法来增强尿液细胞学检查(UroVysion、ImmunoCyt/uCyte+、BTA-stat/TRAK、NMP22、SCD-A7、URO17、CellDetect、UroMark、UroSEEK)。此外,随着数字细胞学技术的出现,人工智能工具的创造也为尿液细胞学检查带来了创新机会。这篇综述文章讨论了报告系统发展过程中的经验教训,探讨了辅助检验的优点和挑战,并呼吁人们关注人工智能在尿液细胞学中应用的潜在效用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Urine cytology: Updates and challenges in reporting systems, ancillary studies, and artificial intelligence

Several urine cytology classifications have been published in the literature. However, global acceptance in the field of urine cytology was only gained in 2016 after The Paris System for reporting urinary cytology was published. Despite this Paris System and its shifted focus toward the detection of high-grade urothelial carcinoma, the perceived weakness of low sensitivity and indeterminate diagnoses when screening with urine cytology remains unresolved. To overcome these shortcomings, investigators have studied a variety of emerging ancillary tests to augment urine cytology (UroVysion, ImmunoCyt/uCyte+, BTA-stat/TRAK, NMP22, SCD-A7, URO17, CellDetect, UroMark, UroSEEK). Furthermore, with the advent of digital cytology, the creation of artificial intelligence tools has created innovative opportunities to aid with urine cytology. This review article discusses the lessons learned in the evolution of reporting systems, explores the merit and challenges of ancillary tests, and calls attention to potential utility of applying artificial intelligence in urine cytology.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
0.60
自引率
0.00%
发文量
0
期刊最新文献
Pineal gland invasion and leptomeningeal dissemination of pancreatic mucinous adenocarcinoma Pleura-Based Lipomatous Neoplasm with RUNX1T1::PLAG1 Rearrangement and RB1 Gene Deletion Occult pleomorphic lobular breast carcinoma presenting exclusively as microangiopathic hemolytic anemia and circulating tumor cells: An autopsy case report Case of obesity-related glomerulopathy treated by pronounced weight loss by diet and exercise Superficial CD34-positive fibroblastic tumour with MED12 :: chr4 intergenic :: PRDM10 fusion: A case report
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1