Actively Recruiting

Phase Not Applicable
Age: 30Years - 49Years
FEMALE
Healthy Volunteers
ID04859530

Study Protocol for a Two-site Clinical Trial to Validate a Smartphone-based Artificial Intelligence Classifier Identifying Cervical Precancer and Cancer in HPV-positive Women in Cameroon

Led by Prof. Patrick Petignat · Updated on 2025-01-29

5886

Participants Needed

1

Research Sites

4 weeks

Total Duration

On this page

AI-Summary

What this Trial Is About

Cervical cancer remains a significant health issue in low- and middle-income countries due to financial and logistical challenges. Researchers are evaluating an automated smartphone-based image classification device called AVC, designed to improve the accuracy of cervical cancer screening by analyzing videos of the cervix during visual inspection with acetic acid (VIA). This study compares the AVC's performance to current triage tests like VIA and cytology, using histopathological examination as the reference standard, and also examines participant and provider acceptance. The AVC test involves local midwives recording two-minute videos of the cervix immediately after applying acetic acid, using a smartphone fixed on a tripod 15 cm away. The device uses artificial intelligence to classify cervical tissue based on acetowhitening dynamics to distinguish precancerous and cancerous tissue from non-cancerous areas. The study is nested within an existing cervical cancer screening program involving HPV self-sampling for women aged 30 to 49 years, with VIA triage and treatment if needed. Participants will undergo HPV testing followed by VIA and the AVC test if HPV-positive. The study will monitor the accuracy, feasibility, and acceptability of the AVC over two years. Researchers will collect data through video recordings and histopathological exams, focusing on diagnostic accuracy as the primary outcome. The study is categorized as minimal risk and includes follow-up assessments to compare the diagnostic tools and gather feedback on the new technology.

CONDITIONS

Brief Title

Automated Cervical Cancer Screening Using a Smartphone-based Artificial Intelligence Classifier

Who Can Participate

Age: 30Years - 49Years
FEMALE
Healthy Volunteers

Eligibility Criteria

Eligible

You may qualify if you...

  • Free and informed consent to take part in the study on a voluntary basis
Not Eligible

You will not qualify if you...

  • No initiation of sexual intercourse
  • Pregnancy at the screening consultation
  • Any condition altering the cervix visualization at the screening consultation (e.g. heavy vaginal bleeding)
  • History of anogenital cancer or known anogenital cancer at the screening consultation
  • Previous hysterectomy
  • Not sufficiently healthy to participate in the study

AI-Screening

AI-Powered Screening

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Your Study Journey

Screening

Duration - 2 to 4 weeks

Participants are screened for eligibility to participate in the trial.

1 visit (in-person)

Diagnostic Evaluation

Duration - Up to 2 years

Participants undergo the AVC test, a smartphone-based artificial intelligence classifier performed during visual inspection with acetic acid to identify cervical precancer and cancer.

1 visit at enrollment and periodic assessments during follow-up

Long-term Monitoring

Duration - Up to 2 years

Participants are monitored to estimate the accuracy, feasibility, and acceptability of the AVC test over time.

Periodic visits during the 2-year follow-up

Trial Site Locations

Total: 1 location

1

Dschang District Hospital

Dschang, Menoua, Cameroon

Actively Recruiting

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Research Team

P

Patrick Petignat, Pr

I

Inès Baleydier

How is the study designed?

Study Type

INTERVENTIONAL

Masking

NONE

Allocation

NA

Model

SINGLE_GROUP

Primary Purpose

PREVENTION

Number of Arms

1

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Published Research Related To This Trial

Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries.

Freddie Bray, Jacques Ferlay, Isabelle Soerjomataram...

https://pubmed.ncbi.nlm.nih.gov/30207593

Global estimates of human papillomavirus vaccination coverage by region and income level: a pooled analysis.

Laia Bruni, Mireia Diaz, Leslie Barrionuevo-Rosas...

https://pubmed.ncbi.nlm.nih.gov/27340003

Study protocol for a two-site clinical trial to validate a smartphone-based artificial intelligence classifier identifying cervical precancer and cancer in HPV-positive women in Cameroon.

Inès Baleydier, Pierre Vassilakos, Roser Viñals...

https://pubmed.ncbi.nlm.nih.gov/34914727