A novel, one stop, affordable, point of care and artificial intelligence supported system of screening, triage and treatment selection for cervical cancer and precancer in the LMICs

EASTER Application identifier 1161104 Summary statement Artificial intelligence (AI) has penetrated many scientific disciplines, including medicine. 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 US NCI. Despite the availability of effective screening, triage and treatment methods for cervical pre-cancer, cervical cancer elimination is still elusive in low and middle income countries (LMICs) where the great majority of disease prevails. We 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 phase 1 (initial 2 years) and validated in phase 2 (subsequent 3 years). During phase 1, we will analyse urine samples collected from 2000 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 phase we will also assess the concordance between hr-HPV detection in urine samples using spectroscopy and cervical HPV detection using a validated HPV test. The cervical image recognition device and the AI algorithm will be further improved during phase 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 phase 2 total 3800 women will be screened in Zimbabwe with AI-supported spectroscopic analysis of urine to detect hrHPV and a validated HPV test to evaluate and compare their sensitivity and specificity to detect histology-proved high grade cervical precancers and cancers. The sensitivity and specificity of AI-supported detection of cervical neoplasias on cervical images will be evaluated to triage the HPV positive women. The accuracy of AI to determine TZ type will be compared with expert opinion. During the field validation phase (phase 2), we will also conduct a cost analysis and compare cost of our approach to current standard Zimbabwean practice. The International Agency for Research on Cancer (WHO cancer research organization) has partnered with The Neo Sense Vector Company (NSV), Delaware, USA (industry), The Engineering Department, Lancaster University, Lancaster, UK and The University of Zimbabwe, College of Health Sciences, Harare, Zimbabwe to implement this study focusing on innovation that will greatly contribute to the global elimination of cervical cancer, a WHO priority.