Melanoma Detection in Switzerland With VECTRA (MELVEC)

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

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.

Study Overview

• Status: Completed
• Conditions: Melanoma (Skin)
• Intervention / Treatment: Device: 3D imaging Total Body Photography Vectra® WB360; Device: 2D imaging FotoFinder ATBM® Master imaging system; Device: Smartphone application (SkinVision®); Other: Standard-of-care clinical assessment of the skin

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.

• Study Type: Observational
• Enrollment (Actual): 455

Contacts and Locations

Study Locations

• Switzerland
  • Basel, Switzerland, 4031
    • Department of Dermatology, University Hospital Basel

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No

• 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.

Description

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

Study Plan

How is the study designed?

Design Details

• Observational Models: Cohort
• Time Perspectives: Prospective

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Analyses of histopathology reports of all excised suspectable lesions	The primary outcome, the sensitivity of human and artificial intelligence in detecting melanoma, will be measured at every study visit in case of a suspected melanoma by analysing histopathology reports of all excised suspectable lesions. The diagnosis of melanoma will be confirmed by histology. The biopsied pigmented skin lesions will be categorized as benign (melanocytic nevi / dysplastic nevi) or malignant (melanoma).	up to 24 months
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	Analyses of dermatologists' assessment of each pigmented skin lesion as benign (melanocytic nevi / dysplastic nevi) or malignant (melanoma) before and after computer-guided risk assessment scores by Vectra® WB360 and FotoFinder® Mole Analyzer and smartphone app.	up to 24 months
Analyses of 2D FotoFinder® Mole Analyzer scoring of pigmented skin lesions (0.0 - 1.0)	The primary outcome, the sensitivity of human and artificial intelligence in detecting melanoma, will be measured at every study visit in case of a suspected melanoma by 2D FotoFinder® Mole Analyzer scoring of pigmented skin lesions (0.0 - 1.0). Scores 0.0 - 1.0; 0 indicating no suspicion for melanoma, 1 indicating a high suspicion for melanoma).	up to 24 months
Analyses of 3D Vectra® WB360 imaging scoring of pigmented skin lesions (0- 10)	The primary outcome, the sensitivity of human and artificial intelligence in detecting melanoma, will be measured at every study visit in case of a suspected melanoma by analysing 3D Vectra® WB360 imaging scoring of pigmented skin lesions (0- 10). Score 0 - 10; 0 indicating no suspicion for melanoma, 10 indicating a high suspicion for melanoma).	up to 24 months
Analyses of Smartphone app Skin Vision® scoring of pigmented skin lesions (low, medium or high risk)	The primary outcome, the sensitivity of human and artificial intelligence in detecting melanoma, will be measured at every study visit in case of a suspected melanoma by analysing Smartphone app Skin Vision® scoring of pigmented skin lesions (low, medium or high risk).	up to 12 months

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Change in Distress thermometer (Patient-reported outcome)	Distress thermometer on a scale from 0-10 to address psychological distress: German version of the NCCN Distress Thermometer is used with Problem List (PL) as the screening tool for self-reported psychosocial distress, and to identify the causes of expressed distress.	up to 24 months
Change in FACIT G7 Functional Assessment of Cancer Therapy - General - (7 item version).	The FACIT Measurement System is a collection of QOL questionnaires targeted to the management of chronic illness.	up to 24 months
Change in Hospital Anxiety and Depression Scale (HADS)	The HADS is a 14-item self-administered questionnaire widely used to detect anxiety and depression in physically ill patients and is validated for the German language. The questionnaire has two subscales (anxiety and depression) with seven items each and a total score for each subscale (values from 0-21). Subscale scores between 0-7 indicate normal anxiety and depression levels, scores between 8-10 indicate borderline levels of anxiety and depression, and scores between 11-21 indicate clinical levels of anxiety or depression	up to 24 months
Change in Melanoma Worry Scale (MWS)	MWS comprises four items, score 1 to 4, with possible scores ranging from 4 to 17, a higher score indicating higher levels of worry	up to 24 months
Change in support need and uptake	Support need and uptake will be collected by questions regarding participants' prospective intention to use psycho-oncological support services ("Do you intend to use the in-house psycho-oncological support service in the next months?", answer options: yes, maybe, no), the recommendation by the dermatologist for psychological support as well as patients' real uptake (hospital record).	up to 24 months
Patients' subjective experience and evaluation of modern technological examination	Study specific questions concerning the individuals' perceptions focusing the benefits by potentially improved sensitivity and specificity and possible disadvantages of the additional technology (3D TBP) in melanoma screening will be asked. The psychological impact of 3D TBP usage in melanoma screening and its effect on patients' cancer worry will be evaluated.	up to 24 months

Other Outcome Measures

Outcome Measure	Measure Description	Time Frame
Comparison of automated naevus counts from 3D total-body photography	Comparison of automated naevus counts from 3D total-body photography generated by collegues in Australia	Up to 3 years
Impact of sun damage on diagnostic accuracy of DEXI algorithm in melanoma recognition	Determination of the impact of sun damage on diagnostic accuracy of DEXI algorithm in melanoma recognition	Up to 3 years
Patient perception of AI utilisation in skin cancer screening via questionaire	Including willingness to pay for 3D TBP	Up to 3 years
Comparison of the diagnostic accuracy of different algorithms by using ROC-AUC curves	Investigating how different algorithms might change diagnostic accuracy	Up to 3 years

Collaborators and Investigators

• Sponsor: University Hospital, Basel, Switzerland
• Investigators: Principal Investigator: Lara Valeska Maul, Dr. med., Department of Dermatology, University Hospital Basel

Study record dates

Study Major Dates

• Study Start (Actual): January 25, 2021
• Primary Completion (Actual): January 31, 2024
• Study Completion (Actual): January 31, 2024

Study Registration Dates

• First Submitted: October 21, 2020
• First Submitted That Met QC Criteria: October 21, 2020
• First Posted (Actual): October 28, 2020

Study Record Updates

• Last Update Posted (Actual): March 19, 2024
• Last Update Submitted That Met QC Criteria: March 18, 2024
• Last Verified: March 1, 2024

More Information

Terms related to this study

• 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®
• Additional Relevant MeSH Terms: Skin Diseases; Neoplasms by Histologic Type; Neoplasms; Neoplasms by Site; Neuroectodermal Tumors; Neoplasms, Germ Cell and Embryonal; Neoplasms, Nerve Tissue; Neuroendocrine Tumors; Nevi and Melanomas; Skin Neoplasms; Melanoma
• Other Study ID Numbers: 2020-02482; sp20Maul

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No