# Innovations in cervical cancer diagnosis for low resource settings using advanced optical imaging and machine learning diagnostic algorithms.

> **NIH NIH R44** · CALLA HEALTH FOUNDATION · 2022 · $998,014

## Abstract

The broad goal of this project is to adapt a portable, low-cost, easy-to-use Pocket-sized Colposcope (developed
under other funding) for use in a community setting, and develop automated algorithms that combine
neovascularization, glycogen depletion and acetowhitening to provide comparable diagnosis to an expert. This work
will be done in a collaboration between 3rd Stone Design, Inc, Duke University and Kenya Medical Research
Institute. The specific aims of this proposal are:
 Aim 1 (Phase I): Improve Pocket colposcope by designing continuous magnification mechanism and
improving device workflow integration to eliminate between-use disinfection through the use of a
disposable optically clear sterile sleeve. Provider feedback on our previously developed Pocket colposcope has
unanimously suggested the addition of a slider mechanism to control coarse zoom and a sleeve consumable to the
Pocket colposcope design.
 Aim 2 (Phase I): Automated algorithms and software for cervical pre-cancer detection We will improve
the specificity of VIA using a novel software application with embedded machine learning diagnostic algorithms for
automated cervical cancer screening. We will apply and validate the individual algorithms for VIA and GIVI (green
illumination vascular imaging) to existing images obtained from a 200-patient clinical study with the Pocket
colposcope. We will then compare the performance of the algorithms to expert physician interpretation of the same
images, with pathology serving as the gold standard.
 Aim 3 (Phase II): Document user experience with Pocket colposcope in Kenya. We will develop a
culturally relevant training package directly in the community healthcare setting. We will collect quantitative and
qualitative data including surveys, in-depth interviews, and clinic observations from both naive providers and patients
and use these findings to and use these findings to improve the introduction of the Pocket colposcope in Kenya and
simultaneously, inform the clinical investigations in Aim 4.
 Aim 4 (Phase II): Compare the performance of the Pocket colposcope to Visual Inspection with
Acetic Acid for triage of HPV+ women in Kenya. We will carry out a cluster-randomized trial among 400 HPV+
women to compare the standard triage with that using the Pocket colposcope in Kisumu, Kenya. All HPV+ women
will undergo biopsy to determine sensitivity, specificity and positive and negative predictive values of the different
triage strategies. Data will be used to model the performance of the algorithm against that of expert colposcopists.
 Aim 5 (Phase II): Assess the costs, incremental cost-effectiveness and population health impact of
HPV-based cervical cancer screening programs with proposed triage strategies. We will determine the
incremental cost-effectiveness ratio and the absolute and relative costs for four triage strategies by measuring the
costs and model population health outcomes (cancer cases, deaths and disability adjusted life years).

## Key facts

- **NIH application ID:** 10618560
- **Project number:** 4R44CA240019-02
- **Recipient organization:** CALLA HEALTH FOUNDATION
- **Principal Investigator:** MARLEE KRIEGER
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $998,014
- **Award type:** 4N
- **Project period:** 2019-09-13 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10618560

## Citation

> US National Institutes of Health, RePORTER application 10618560, Innovations in cervical cancer diagnosis for low resource settings using advanced optical imaging and machine learning diagnostic algorithms. (4R44CA240019-02). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/10618560. Licensed CC0.

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