Automated Cervical Cancer Screening Using a Smartphone-based Artificial Intelligence Classifier
NCT ID: NCT04859530
Last Updated: 2025-01-29
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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RECRUITING
NA
5886 participants
INTERVENTIONAL
2018-08-01
2025-09-30
Brief Summary
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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.
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Detailed Description
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Conditions
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Study Design
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NA
SINGLE_GROUP
PREVENTION
NONE
Study Groups
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AVC test
AVC test
The AVC test will be performed during VIA by local midwives: 120 second videos focused on the cervix will be taken right after the application of acetic acid on the cervix. The recording smartphone will be fixed on a tripod situated 15cm away from the cervix.
Interventions
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AVC test
The AVC test will be performed during VIA by local midwives: 120 second videos focused on the cervix will be taken right after the application of acetic acid on the cervix. The recording smartphone will be fixed on a tripod situated 15cm away from the cervix.
Other Intervention Names
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Eligibility Criteria
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Inclusion Criteria
Exclusion Criteria
* 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
30 Years
49 Years
FEMALE
Yes
Sponsors
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Prof. Patrick Petignat
OTHER
Responsible Party
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Prof. Patrick Petignat
Director of the gynaecology department
Principal Investigators
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Patrick Petignat
Role: PRINCIPAL_INVESTIGATOR
University Hospital, Geneva
Locations
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Dschang District Hospital
Dschang, Menoua, Cameroon
Countries
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Central Contacts
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Facility Contacts
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References
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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.
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.
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.
Other Identifiers
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2017-01110b
Identifier Type: -
Identifier Source: org_study_id
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