Clinical trial NCT04859530: Automated Cervical Cancer Screening Using a Smartphone-based Artificial Intelligence Classifier
Official title: 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
Study type: INTERVENTIONAL
Overall status: RECRUITING
Phase: NA
Conditions: Cervical Cancer
HPV
Keywords: Cervical cancer screening
HPV-related cervical precancer and cancer
Artificial Intelligence
Image processing
Automated VIA Classifier
Lead sponsor: University Hospital, Geneva
Sponsor class: OTHER
First posted: 2021-04-26
Enrollment: 5886
Sex: FEMALE
Minimum age (years): 30
Maximum age (years): 49
Standard ages: ADULT
Accepts healthy volunteers: yes
Allocation: NA
Intervention model: SINGLE_GROUP
Primary purpose: PREVENTION

Brief summary: Cervical cancer remains a major public health challenge in low- and middle-income countries (LMICs) due to financial and logistical issues. The World Health Organization (WHO) recommendation for cervical cancer screening in LMICs includes Human Papillomavirus (HPV) testing as primary screening followed by visual inspection with acetic acid (VIA) and treatment. However, VIA is a subjective procedure dependent on the healthcare provider's experience. Therefore, an objective approach based on quantitative diagnostic algorithms is desirable to improve performance of VIA.

With this objective and in a collaboration between the Gynecology and Obstetrics Department of the Geneva University Hospital (HUG) and the Swiss Institute of Technology (EPFL), our group started the development of an automated smartphone-based image classification device called AVC (for Automatic VIA Classifier). Two-minute videos of the cervix are recorded during VIA and classified using an artificial neural network (ANN) and image processing techniques to differentiate precancer and cancer from non-neoplastic cervical tissue. The result is displayed on the smartphone screen with a delimitation map of the lesions when appropriate. The key feature used for classification is the dynamic of cervical acetowhitening during the 120 second following the application of acetic acid. Precancerous and cancerous cells whiten more rapidly than non-cancerous ones and their whiteness persists stronger overtime.

Our aim is to assess the diagnostic performance of the AVC and to compare it with the performance of current triage tests (VIA and cytology). Histopathological examination will serve as reference standard. Participants' and providers' acceptability will also be considered as part of the study.

The study will be nested in an ongoing cervical cancer screening program called "3T-approach" (for Test, Triage and Treat) which includes HPV self-sampling for women aged 30 to 49 years, followed by VIA triage and treatment if needed. The AVC will be evaluated in this context.

The study's risk category is A according to swiss ethical guidelines. This decision is based on the fact that the planned measures for sampling biological material or collecting personal data entail only minimal risks and burdens.


Eligibility criteria: Inclusion Criteria:

* Free and informed consent to take part in the study on a voluntary basis

Exclusion Criteria:

* 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

Primary outcomes:
measure: Estimate accuracy of the AVC test
timeFrame: 2 years
Secondary outcomes:
measure: Compare accuracy of the AVC test and VIA to detect cervical precancer and cancer
timeFrame: 2 years
measure: Compare accuracy of the AVC test and cytology to detect cervical precancer and cancer
timeFrame: 2 years
measure: Estimate feasibility of the AVC test
timeFrame: 2 years
measure: Estimate acceptability of the AVC test
timeFrame: 2 years
Other outcomes:
Locations:
city: Dschang
country: Cameroon
facility: Dschang District Hospital
state: Menoua
Study officials:
affiliation: University Hospital, Geneva
name: Patrick Petignat
role: PRINCIPAL_INVESTIGATOR
References:
citation: Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018 Nov;68(6):394-424. doi: 10.3322/caac.21492. Epub 2018 Sep 12.
citation: Bruni L, Diaz M, Barrionuevo-Rosas L, Herrero R, Bray F, Bosch FX, de Sanjose S, Castellsague X. Global estimates of human papillomavirus vaccination coverage by region and income level: a pooled analysis. Lancet Glob Health. 2016 Jul;4(7):e453-63. doi: 10.1016/S2214-109X(16)30099-7.
citation: Baleydier I, Vassilakos P, Vinals R, Wisniak A, Kenfack B, Tsuala Fouogue J, Enownchong Enow Orock G, Lemoupa Makajio S, Foguem Tincho E, Undurraga M, Cattin M, Makohliso S, Schonenberger K, Gervaix A, Thiran JP, Petignat P. 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. PLoS One. 2021 Dec 16;16(12):e0260776. doi: 10.1371/journal.pone.0260776. eCollection 2021.