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.

Grant Number: 3R37CA275824-03S1
NIH Institute/Center: NIH
Principal Investigator: Partha Basu