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Skin CancerARTISNCT05246163

ARTIficial Intelligence-based Smartphone Application for Skin Cancer Detection

An observational study of Skin Cancer, run by University Hospital, Ghent at 1 site in Belgium.

Unknown status

Status not confirmed. The sponsor has not verified this record for over two years, so it may be out of date.

Official record
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Trial summary

The aim of this project is to assess whether a specific smartphone application (Skinvision App®) can be used as a tool to preselect skin lesions suspicious for skin cancer that require urgent medical advice. Read more about this study

Who is it for?
Ages 18 years and older
Conditions the study is for
Skin Cancer
How many people
2,500 participants
Where
1 siteBelgium
Study dates
1 Jan 2020to 31 Mar 2025
Phase
Observational
Are there results?
None posted in the registry

Key requirements

Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.

  • Ages 18 years and older
  • All sexes
  • Adult, Older adult

Study population: Patients (> 18 years old) consulting at the Department of Dermatology of the Ghent University Hospital concerned about one or two skin lesions meeting at least one of the specified criteria.

Who may be able to join

  • Patients with one or two lesions meeting at least one of the following criteria:
  • New mole in an adult (> 18 years old);
  • 'Ugly duckling' sign (i.e. mole that looks different from other moles in the same person)
  • Changing mole (size, color, shape or structure);
  • Rapid growing lesion
  • Non-healing lesion
  • Written informed consent of the patient

Who cannot join

  • Lack of informed consent for study participation

Trial locations and contacts

1 site in 1 country.

Julie Kips, MD contact

+32487519041

julie.kips@ugent.be

Amber Shen, MHP contact

+3293322243

amber.shen@uzgent.be

Belgium1 site, 1 recruiting

  • Department of Dermatology, Ghent University Hospital

    Ghent, East Flanders, 9000

    Julie Kips, MD, +32487519041, julie.kips@ugent.be

    Amber Shen, MHP, +3293322243, amber.shen@uzgent.be

    Recruiting

Other trials in Belgium

About this study

Official title: Clinical Performance and Patient Experience of an Artificial Intelligence-based Smartphone Application (Skinvision ®) in the Early Detection of Skin Cancer: A Cross-Sectional Study in a Real-life Setting.

The aim of this project is to assess whether a specific smartphone application (Skinvision App®) can be used as a tool to preselect skin lesions suspicious for skin cancer that require urgent medical advice.

Read the detailed description

Skin cancer is the most frequent cancer diagnosed and its incidence will keep on rising in the next decade. Early detection and treatment are key to improve both morbidity and mortality, and to decrease the cost to society. Persons at risk of developing skin cancer may be subjected to regular checkups. However a considerable number of skin cancers develop in the low-risk general population. Since systematic screening in the general population is not cost-effective, smartphone applications that use inbuilt algorithms are of increasing interest and claim to assist in making a risk assessment in case of concerning skin lesions.

Based on previous research, a so-called triage consultation was installed at the policlinic of Ghent University Hospital for patients with 1 to 2 lesions of concern: changing mole, ugly duckling, new mole in adult, rapidly growing lesion or non-healing lesion. Skin cancer detection rate in this setting was at least 13% with 4% melanoma. This is 6 to 8-fold higher than reported by conventional skin cancer screening programs (PMID: 26466155; PMID: 33480073). The reason for this is that a preselection of lesions meeting specific criteria is done. This lesion-directed screening may be a way to make skin cancer screening in the general population (more) cost-effective.

In this study we will investigate whether the Skinvision app can function as a preselection tool for lesions for which urgent medical advice is needed. Although this app is CE marked and is already promoted to the public, it's performance and value in daily practice have been insufficiently studied and there is a need for independent research.

The 4 main objectives of this study will be:

  1. To calculate diagnostic performance of the Skinvision App Calculation of sensitivity and specificity by comparing application risk gradings with a reference standard defined as the histopathological diagnosis or clinical diagnosis in case no biopsy or excision was performed;
  2. To determine the repeatability and reproducibility of the Skinvision App Identification of factors that influence the risk analysis of the application, including photographer, type of skin lesion, camera position or lighting conditions;
  3. To examine user-experience and confidence concerning the use of medical apps Questionnaire-based evaluation of the user-experience with applications in general, as well as more specific the willingness and confidence to use a skin cancer detection application;
  4. To estimate the performance and cost-effectiveness of the Skinvision App in the general population Estimation of the app performance in the general population (estimated prevalence of skin cancer 1%) in terms of missed diagnoses and degree of preselection (positive predictive value).
Conditions
Skin Cancer
Keywords
Screening, Prevention, Artificial Intelligence, Skinvision App
Medical subject headings
Skin Neoplasms

What is being measured

The primary outcome is the main question the study is designed to answer.

  1. Diagnostic performance of the Skinvision application

    To evaluate the sensitivity and specificity of the application. The risk assessment of the application will be compared to the gold standard. The gold standard is defined as the histopathologic diagnosis (in biopsied and excised lesions) or clinical assessment by one or two experienced dermatologists. The risk assessment of the application is defined as low (green), medium (orange) or high (red) risk. The biopsied or excised skin lesions will be categorized as benign or malignant.

    Measured: Up to 24 months

Secondary outcomes (3)

  1. Usability and reproducibility of the Skinvision application

    To examine the usability and reproducibility of the application. Lesion-specific parameters will be collected (e.g., localization, hair or other disturbing factors, etc). A repeated analysis of one or more specific lesions will be made in different lighting conditions and from different camera positions. Given the evolution of the camera quality, different smartphones will be tested. Finally, the patient will also be asked to perform an analysis to assess the user friendliness.

    Measured: Up to 24 months

  2. User's acceptability of medical smartphone applications

    Patients will be asked about their willingness-to-use medical smartphone applications, including more specifically, a skin cancer detection application. Participants will provide their level of agreement or disagreement for a series of statements with a agree-disagree scale (1 = strongly disagree to 5 = strongly agree).

    Measured: Day 1

  3. User's confidence in using smartphone applications for skin cancer detection

    Patient's confidence will be scored on a 5-point scale (1 = not confident to 5 = highly confident). Higher scores indicate a greater confidence in the evaluation and risk stratification of suspicious lesions by a skin cancer detection application

    Measured: Day 1

Timeline

From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.

  1. First posted18 Feb 2022
  2. Study start1 Jan 2020
  3. Primary completion31 Mar 2025 (estimated)
  4. Study completion31 Mar 2025 (estimated)

Resources

More details

For doctors and researchers: how the study is designed, who runs it, and its registry IDs.

Study design
Study type
Observational
Observational model
Case only
Time perspective
Cross-sectional
Enrolment
2,500 participants (estimated)
IDs, dates and publications
ClinicalTrials.gov ID
NCT05246163
Sponsor's protocol ID
2017/0823 (BC-01191)
Acronym
ARTIS
Status last verified
Jun 2024
First submitted
17 Jan 2022
Last updated
4 Jun 2024
Results posted
No
Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
Individual data sharing
No

Publications

  • Kips J, Papeleu J, Shen A, Mylle S, Genouw E, Hoorens I, Verhaeghe E, Brochez L. Artificial intelligence-based smartphone application for skin cancer detection: a prospective diagnostic accuracy study. Br J Dermatol. 2026 May 19;194(6):1077-1086. doi: 10.1093/bjd/ljag057.

    PubMed 41701029

Questions about this trial

What is this clinical trial studying?

An observational study of Skin Cancer, run by University Hospital, Ghent at 1 site in Belgium.

The full registered description is in the About this study section and the official record.

Who may be eligible to take part?

The sponsor lists 7 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.

Is this clinical trial currently recruiting?

The record says: status not confirmed, as of the sponsor's last update on 4 Jun 2024. Status can change between updates, so confirm with the study contact before making plans.

Where is the study taking place?

The record lists 1 site in Belgium. Whether a site is taking part right now should be confirmed with that site. See every site.

What are the possible benefits and risks?

They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.

Are results available for this study?

Results are not available in the source record.

How can a doctor refer a patient or contact the research team?

Contact Julie Kips, MD (+32487519041, julie.kips@ugent.be), or a site near the patient. AzTrials does not enrol participants or take referrals.

What does the primary outcome measure?

Diagnostic performance of the Skinvision application (time frame: Up to 24 months). It is what the study was designed to measure, not a finding.

Where can I read the original study information?

On the ClinicalTrials.gov record for NCT05246163, which also lists 1 linked publication.

Does a listing mean the treatment is approved or proven to work?

No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.

How often is this information updated?

AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 4 Jun 2024.

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