Clinical trial NCT04605822: Melanoma Detection in Switzerland With VECTRA
Official title: Clinical Performance of the New Artificial-intelligence Powered 3D Total Body Photography System VECTRA® in Early Melanoma Detection and Its Impact on Patients' Burden of Disease: A Prospective Cohort Study in a Real-world Setting
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Melanoma (Skin)
Keywords: 3D total body photography (TBP)
2D sequential digital dermatoscopic imaging (SDDI)
skin malignancy
artificial intelligence (AI)- based tools
3D TBP Vectra® WB360 system
FotoFinder ATBM® Master
SkinVision®
Lead sponsor: University Hospital, Basel, Switzerland
Sponsor class: OTHER
First posted: 2020-10-28
Enrollment: 455
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
Study population: Patients will be recruited during melanoma consultations and the consultation in the outpatient clinic at the Department of Dermatology at the University Hospital Basel from Q4/2020 until Q4/2021.

Brief summary: This study is to compare 2D- and 3D-imaging and routine clinical care in early melanoma detection in a prospective large-scale real-world data set.

Detailed description: This study is to compare the accuracy of combining human and artificial intelligence with its independent application in early melanoma detection. The Artificial Intelligence (AI)-powered 3D Total Body Photography (TBP) Vectra® WB360 system's utility and clinical performance in detecting melanoma in the real-world setting will be compared to the gold standard with clinical assessments by experienced dermatologists, to currently widespread used 2D imaging tools (FotoFinder ATBM® Master) and to the Smartphone-based algorithm application (e.g. SkinVision®). Here included are specific questions regarding the patients' subjective experience, acceptance and evaluation of modern technological examination.

Additionally, the overall psychological burden and worry of melanoma risk or disease, anxiety, depression will be compared in different groups of patients and psychological support need and real uptake of support and its predictors will be investigated in all participants.

To validate the MELVEC (Melanoma Detection in Switzerland with Vectra®) test procedure, an analysis of the measurement repeatability of computer-guided risk assessment scores for early melanoma detection will be performed. A potential benefit of this validation analysis is the optimization of study procedure for future follow-up visits and further enrolled patients in the MELVEC study. Additionally, results will shed light on the reliability of the convolutional neural networks (CNNs) investigated and help formulate recommendations for their current use. Furthermore, results will provide important data for the manufacturers regarding the systems' reliability in clinical application to help future improvement of the respective algorithms.

Eligibility criteria: Inclusion Criteria:

* Written informed consent of the patient
* Sufficient fluency in German language skills to complete all questionnaires of the study without external assistance
* High-risk criteria for melanoma. For "high risk" one of the following criteria needs to be fulfilled:

  * At least one previous melanoma (including melanoma in situ)
  * A diagnosis of ≥ 100 nevi
  * A diagnosis of ≥ 5 atypical nevi
  * A diagnosis of dysplastic nevus syndrome or known CDKN2A mutation
  * A strong family history (≥ 1 first- and/or second-degree relatives)

Exclusion Criteria:

* Lack of informed consent for study participation.
* Fitzpatrick skin type V-VI.
* Acute psychiatric illness or acute crisis

Primary outcomes:
measure: Analyses of histopathology reports of all excised suspectable lesions
timeFrame: up to 24 months
measure: Analyses of dermatologists' assessment of each pigmented skin lesion as benign (melanocytic nevi / dysplastic nevi) or malignant (melanoma) before and after (without and with knowledge of) computer-guided risk assessment scores
timeFrame: up to 24 months
measure: Analyses of 2D FotoFinder® Mole Analyzer scoring of pigmented skin lesions (0.0 - 1.0)
timeFrame: up to 24 months
measure: Analyses of 3D Vectra® WB360 imaging scoring of pigmented skin lesions (0- 10)
timeFrame: up to 24 months
measure: Analyses of Smartphone app Skin Vision® scoring of pigmented skin lesions (low, medium or high risk)
timeFrame: up to 12 months
Secondary outcomes:
measure: Change in Distress thermometer (Patient-reported outcome)
timeFrame: up to 24 months
measure: Change in FACIT G7 Functional Assessment of Cancer Therapy - General - (7 item version).
timeFrame: up to 24 months
measure: Change in Hospital Anxiety and Depression Scale (HADS)
timeFrame: up to 24 months
measure: Change in Melanoma Worry Scale (MWS)
timeFrame: up to 24 months
measure: Change in support need and uptake
timeFrame: up to 24 months
measure: Patients' subjective experience and evaluation of modern technological examination
timeFrame: up to 24 months
Other outcomes:
measure: Comparison of automated naevus counts from 3D total-body photography
timeFrame: Up to 3 years
measure: Impact of sun damage on diagnostic accuracy of DEXI algorithm in melanoma recognition
timeFrame: Up to 3 years
measure: Patient perception of AI utilisation in skin cancer screening via questionaire
timeFrame: Up to 3 years
measure: Comparison of the diagnostic accuracy of different algorithms by using ROC-AUC curves
timeFrame: Up to 3 years
Locations:
city: Basel
country: Switzerland
facility: Department of Dermatology, University Hospital Basel
Study officials:
affiliation: Department of Dermatology, University Hospital Basel
name: Lara Valeska Maul, Dr. med.
role: PRINCIPAL_INVESTIGATOR
References: