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

Summary

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 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 part (part 2), the investigators will also conduct a cost analysis and compare cost of our approach to current standard Zimbabwean practice. The International Agency for Research on Cancer- World Health Organization WHO (IARC-WHO) 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.

Conditions

• Cervical Cancer
• Screening

Interventions

DIAGNOSTIC_TEST

Screening with HPV test

Women aged 25-49 yrs will be screened with a validated HPV test. They will also provide urine samples for HPV test. Women HPV positive in either sample will be referred to colposcopy for disease ascertainment.

Sponsors & Collaborators

• University of California, San Francisco

  collaborator OTHER

• University of Zimbabwe

  collaborator OTHER

• Lancaster University

  collaborator OTHER

• Neo Sense Vector (NSV)

  collaborator UNKNOWN

• National Cancer Institute (NCI)

  collaborator NIH

• University of Cincinnati

  collaborator OTHER

• International Agency for Research on Cancer

  lead OTHER

Principal Investigators

• Partha Basu, MD · International Agency For Research On Cancer (IARC)

• Bothwell Guzha, MD · University of Zimbabwe

• Mike Chirenje Zvavahera, MD · University of California, San Francisco

• Ihtesham U Rehman, PhD · Lancaster University

• Walter Prendiville, MD · Neo Sense Vector (NSV)

Study Design

Allocation

NA

Purpose

SCREENING

Masking

NONE

Model

SINGLE_GROUP

Eligibility

Min Age

25 Years

Max Age

49 Years

Sex

FEMALE

Healthy Volunteers

No

Timeline & Regulatory

Start

2023-12-09

Primary Completion

2027-12-31

Completion

2027-12-31

Countries

• United States
• Zimbabwe

Study Locations