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Novel, One Stop, Affordable, Point of Care and AI Supported System of Screening, Triage and Treatment Selection for Cervical Cancer in LMICs

International Agency for Research on Cancer · 2023
ClinicalTrials.gov · Datasets · License: Public Domain · 2023
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cervical-cancernascreening
Artificial intelligence (AI) is fast gaining reputation as a highly promising solution for cervical cancer screening. AI-based detection of cervical neoplasias is named automated visual exam (AVE) by the National Cancer Institute, USA. The investigators propose to develop and evaluate the performance characteristics of a novel AI system to both screen and triage women as well as help in treatment decision making. AI will analyse infrared spectroscopic signals derived from urine samples of unscreened women for the presence of high-risk human papillomavirus (hr-HPV). Our preliminary study has shown that spectroscopy can detect hr-HPV in urine. For screen-positive women the AI will interpret a set of cervical images captured with a high-quality devoted camera to detect high grade cervical precancers and cancers and to determine the type of transformation zone (TZ) (helps in treatment decision). The prototype device for image capture and the AI algorithms are already developed by us. The technologies will be further improved in part 1 (initial 2 years) and validated in part 2 (subsequent 3 years). During Part 1, the investigators will analyse urine samples collected from 1100 women at multiple screening clinics in Zimbabwe for the presence of hr-HPV using spectroscopy and use the signals generated to improve the AI algorithm. In this part the investigators will also assess the concordance between hr-HPV detection in urine samples using spectroscopy and cervical human papillomavirus (HPV) detection using a validated HPV test. The cervical image recognition device and the AI algorithm will be further improved during part 1 by collecting more images from hr-HPV positive and negative women. AI will also be trained to interpret the cervical images to determine the TZ type. In part 2 total 2100 women will be screened in Zimbabwe with AI-supported spectroscopic analysis of urine to detect hr-HPV and a validated HPV test to evaluate and compare their sensitivity and specificity
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