Usha Rani Poli, Anirudh G Gudlavalleti, Jaya Bharadwaj Y, Hira B Pant, Varun Agiwal, G V S Murthy
{"title":"醋酸视觉检查的开发和临床验证-使用宫颈图像的人工智能工具在南印度宫颈癌的筛查和治疗视觉筛查:一项试点研究。","authors":"Usha Rani Poli, Anirudh G Gudlavalleti, Jaya Bharadwaj Y, Hira B Pant, Varun Agiwal, G V S Murthy","doi":"10.1200/GO.24.00146","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>The burden of cervical cancer in India is enormous, with more than 60,000 deaths being reported in 2020. The key intervention in the WHO's global strategy for the elimination of cervical cancer is to aim for the treatment and care of 90% of women diagnosed with cervical lesions. The current screen-and-treat approach as an option for resource-limited health care systems where screening of the cervix with visual inspection with acetic acid application (VIA) is followed by immediate ablative treatment by nurses in the case of a positive test. This approach often results in overtreatment, owing to the subjective nature of the test. Unnecessary treatments can be diminished with the use of emerging computer-assisted visual evaluation technology, using artificial intelligence (AI) tool to triage VIA-positive women. The aim of this study was (1) to develop a VIA-AI tool using cervical images to identify and categorize the VIA-screen-positive areas for eligibility and suitability for ablative treatment, and (2) to understand the efficacy of the VIA-AI tool in guiding the nurses to decide on treatment eligibility in the screen-and-treat cervical screening program.</p><p><strong>Methods: </strong>This was an exploratory, interventional study. The VIA-AI tool was developed using deep-learning AI from the image bank collected in our previously conducted screening programs. This VIA-AI tool was then pilot-tested in an ongoing nurse-led VIA screening program.</p><p><strong>Results: </strong>A comparative assessment of the cervical features performed in all women using the VIA-AI tool showed clinical accuracy of 76%. The perceived challenge rate for false positives was 20%.</p><p><strong>Conclusion: </strong>This novel cervical image-based VIA-AI algorithm showed promising results in real-life settings, and could help minimize overtreatment in single-visit VIA screening and treatment programs in resource-constrained situations.</p>","PeriodicalId":14806,"journal":{"name":"JCO Global Oncology","volume":"10 ","pages":"e2400146"},"PeriodicalIF":3.2000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11684514/pdf/","citationCount":"0","resultStr":"{\"title\":\"Development and Clinical Validation of Visual Inspection With Acetic Acid Application-Artificial Intelligence Tool Using Cervical Images in Screen-and-Treat Visual Screening for Cervical Cancer in South India: A Pilot Study.\",\"authors\":\"Usha Rani Poli, Anirudh G Gudlavalleti, Jaya Bharadwaj Y, Hira B Pant, Varun Agiwal, G V S Murthy\",\"doi\":\"10.1200/GO.24.00146\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>The burden of cervical cancer in India is enormous, with more than 60,000 deaths being reported in 2020. The key intervention in the WHO's global strategy for the elimination of cervical cancer is to aim for the treatment and care of 90% of women diagnosed with cervical lesions. The current screen-and-treat approach as an option for resource-limited health care systems where screening of the cervix with visual inspection with acetic acid application (VIA) is followed by immediate ablative treatment by nurses in the case of a positive test. This approach often results in overtreatment, owing to the subjective nature of the test. Unnecessary treatments can be diminished with the use of emerging computer-assisted visual evaluation technology, using artificial intelligence (AI) tool to triage VIA-positive women. The aim of this study was (1) to develop a VIA-AI tool using cervical images to identify and categorize the VIA-screen-positive areas for eligibility and suitability for ablative treatment, and (2) to understand the efficacy of the VIA-AI tool in guiding the nurses to decide on treatment eligibility in the screen-and-treat cervical screening program.</p><p><strong>Methods: </strong>This was an exploratory, interventional study. The VIA-AI tool was developed using deep-learning AI from the image bank collected in our previously conducted screening programs. This VIA-AI tool was then pilot-tested in an ongoing nurse-led VIA screening program.</p><p><strong>Results: </strong>A comparative assessment of the cervical features performed in all women using the VIA-AI tool showed clinical accuracy of 76%. The perceived challenge rate for false positives was 20%.</p><p><strong>Conclusion: </strong>This novel cervical image-based VIA-AI algorithm showed promising results in real-life settings, and could help minimize overtreatment in single-visit VIA screening and treatment programs in resource-constrained situations.</p>\",\"PeriodicalId\":14806,\"journal\":{\"name\":\"JCO Global Oncology\",\"volume\":\"10 \",\"pages\":\"e2400146\"},\"PeriodicalIF\":3.2000,\"publicationDate\":\"2024-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11684514/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"JCO Global Oncology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1200/GO.24.00146\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/12/12 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"JCO Global Oncology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1200/GO.24.00146","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/12/12 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"ONCOLOGY","Score":null,"Total":0}
Development and Clinical Validation of Visual Inspection With Acetic Acid Application-Artificial Intelligence Tool Using Cervical Images in Screen-and-Treat Visual Screening for Cervical Cancer in South India: A Pilot Study.
Purpose: The burden of cervical cancer in India is enormous, with more than 60,000 deaths being reported in 2020. The key intervention in the WHO's global strategy for the elimination of cervical cancer is to aim for the treatment and care of 90% of women diagnosed with cervical lesions. The current screen-and-treat approach as an option for resource-limited health care systems where screening of the cervix with visual inspection with acetic acid application (VIA) is followed by immediate ablative treatment by nurses in the case of a positive test. This approach often results in overtreatment, owing to the subjective nature of the test. Unnecessary treatments can be diminished with the use of emerging computer-assisted visual evaluation technology, using artificial intelligence (AI) tool to triage VIA-positive women. The aim of this study was (1) to develop a VIA-AI tool using cervical images to identify and categorize the VIA-screen-positive areas for eligibility and suitability for ablative treatment, and (2) to understand the efficacy of the VIA-AI tool in guiding the nurses to decide on treatment eligibility in the screen-and-treat cervical screening program.
Methods: This was an exploratory, interventional study. The VIA-AI tool was developed using deep-learning AI from the image bank collected in our previously conducted screening programs. This VIA-AI tool was then pilot-tested in an ongoing nurse-led VIA screening program.
Results: A comparative assessment of the cervical features performed in all women using the VIA-AI tool showed clinical accuracy of 76%. The perceived challenge rate for false positives was 20%.
Conclusion: This novel cervical image-based VIA-AI algorithm showed promising results in real-life settings, and could help minimize overtreatment in single-visit VIA screening and treatment programs in resource-constrained situations.