Dschang

Cervical cancer remains a significant health issue in low- and middle-income countries due to financial and logistical challenges. Researchers are evaluating an automated smartphone-based image classification device called AVC, designed to improve the accuracy of cervical cancer screening by analyzing videos of the cervix during visual inspection with acetic acid VIA. This study compares the AVCs performance to current triage tests like VIA and cytology, using histopathological examination as the reference standard, and also examines participant and provider acceptance. The AVC test involves local midwives recording two-minute videos of the cervix immediately after applying acetic acid, using a smartphone fixed on a tripod 15 cm away. The device uses artificial intelligence to classify cervical tissue based on acetowhitening dynamics to distinguish precancerous and cancerous tissue from non-cancerous areas. The study is nested within an existing cervical cancer screening program involving HPV self-sampling for women aged 30 to 49 years, with VIA triage and treatment if needed. Participants will undergo HPV testing followed by VIA and the AVC test if HPV-positive. The study will monitor the accuracy, feasibility, and acceptability of the AVC over two years. Researchers will collect data through video recordings and histopathological exams, focusing on diagnostic accuracy as the primary outcome. The study is categorized as minimal risk and includes follow-up assessments to compare the diagnostic tools and gather feedback on the new technology.