首页|人工智能TPS辅助阅片系统联合荧光原位杂交技术在诊断尿路上皮癌中的应用价值

人工智能TPS辅助阅片系统联合荧光原位杂交技术在诊断尿路上皮癌中的应用价值

扫码查看
目的 探讨人工智能尿液细胞学巴黎报告系统(TPS)辅助阅片系统联合荧光原位杂交技术(FISH)在诊断尿路上皮癌中的应用价值.方法 回顾性选取2021年3月至2024年3月中国医科大学附属第一医院收治的128例疑似尿路上皮癌患者为研究对象,采用人工智能TPS辅助阅片系统对尿液细胞学检查进行结果判读,并进行FISH检查,以组织病理学检查结果为金标准,评估人工智能TPS辅助阅片系统联合FISH检查对尿路上皮癌的诊断效能.结果 组织病理学检查显示,阴性11.72%(15/128),尿路上皮非典型增生7.03%(9/128),低度乳头状尿路上皮肿瘤27.34%(35/128),高级别乳头状尿路上皮癌53.12%(68/128),其他恶性肿瘤转移性癌0.78%(1/128),TPS诊断结果显示,TPS 1级占1.56%(2/128),TPS 2 级占 14.84%(19/128),TPS 3 级占 12.50%(16/128),TPS 4 级占 68.75%(88/128),TPS 5 级占 2.34%(3/128),TPS 6级占2.34%(3/128);FISH诊断结果显示,CEP3异常占61.72%(79/128),CSP7异常62.50%(80/128),CEP17异常34.38%(44/128),GLP-pl6异常19.53%(25/128);TPS、FISH单一及联合诊断尿路上皮癌准确度分别 89.84%、88.28%、96.88%,联合诊断优于单一诊断(c2=4.870,P<0.05).结论 人工智能TPS辅助阅片系统联合FISH检查可以大大提高尿路上皮癌患者诊断准确度,值得临床推广应用.
Application of artificial intelligence TPS assisted film reading system combined with fluo-rescence in situ hybridization in diagnosis of urothelial carcinoma
Objective To investigate the application value of artificial intelligence(AI)urine cy-tology Paris Reporting System(TPS)assisted film reading system combined with fluorescence in situ hybrid-ization(FISH)in the diagnosis of urothelial carcinoma.Methods A total of 128 patients with suspected uro-thelial carcinoma were admitted to The First Hospital of China Medical University from March 2021 to March 2024 were retrospectively selected as the study subjects.The results of the urine cytology examination were in-terpreted using an artificial intelligence TPS assisted film reading system,and FISH examination was per-formed,with histopathological examination results serving as the gold standard.The aim of the study was to evaluate the diagnostic efficacy of the artificial intelligence TPS-assisted film reading system combined with FISH examination in detecting urothelial carcinoma.Results The histopathological examination showed the following results:negative 11.72%(15/128),atypical urothelial hyperplasia 7.03%(9/128),low-grade papil-lary urothelial tumor 27.34%(35/128),high-grade papillary urothelial carcinoma 53.12%(68/128),and meta-static carcinoma 0.78%(1/128).TPS diagnosis results indicated that TPS grade 1 accounted for 1.56%(2/128),TPS grade 2 accounted for 14.84%(19/128),TPS grade 3 accounted for 12.50%(16/128),and TPS grade 4 accounted for 68.75%(88/128),TPS Grade 5 accounted for 2.34%(3/128),TPS grade 6 accounted for 2.34%(3/128).The results of FISH diagnosis showed abnormalities in CEP3 in 61.72%(79/128),CSP7 in 62.50%(80/128),CEP17 34.38%(44/128),and GLP-pl6 in 19.53%(25/128).The accuracy of single and com-bined TPS and FISH in diagnosing urothelial carcinoma was 89.84%,88.28%,and 96.88%,respectively,and the combined diagnosis was superior to the single diagnosis(c2=4.870,P<0.05).Conclusion An artificial intel-ligence TPS-assisted film reading system,combined with FISH examination,can significantly improve the diag-nostic accuracy of patients with urothelial carcinoma.This innovative approach is deserving of clinical application.

Artificial intelligenceTPSFISHUrothelial carcinoma

高昕、周殊伶、戚贺、崔馨月、王明哲、常城玮

展开 >

中国医科大学第一临床学院,辽宁,沈阳 110122

中国医科大学第二临床学院,辽宁,沈阳 110122

人工智能 尿液细胞学巴黎报告系统 荧光原位杂交技术 尿路上皮癌

2024

分子诊断与治疗杂志
中山大学

分子诊断与治疗杂志

CSTPCD
影响因子:0.65
ISSN:1674-6929
年,卷(期):2024.16(12)