DERM US and EU Validation Study

Study Overview
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Brief Summary
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This study aims establish the effectiveness of Image Analysing Algorithm (DERM) to identify melanoma, Squamous Cell Carcinoma (SCC) and Basal Cell Carcinoma (BCC) when used to analyse dermoscopic images of skin lesions within the US and European population.

Official Title
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A Clinical Validation Study to Demonstrate the Effectiveness of an Artificial Intelligence Algorithm (DERM) to Identify Skin Cancer in Patients Undergoing a Skin Biopsy

Conditions
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Malignant Skin Melanoma T0, Basal Cell Carcinoma, Squamous Cell Carcinoma

Intervention / Treatment
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* Device: Deep Ensemble for the Recognition of Malignancy (DERM)


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Willing and able to give informed consent for participation in the study, Male or Female, aged 18 years or above, Have at least one suitable skin lesion that will be biopsied due to a suspicion of skin cancer, To be suitable for inclusion, a skin lesion must NOT have ANY of the following limitations: located on an anatomical site of different skin structure: palms of hands or soles of feet (acral lesion), mucosal surfaces (lips and eyes) or under nail (ungal lesion), a diameter greater than the diameter of the dermoscopic lenses, located on an anatomical site unsuitable for photographing, including on surface of genitals and hair-bearing areas, has been previously biopsied, excised, treated or otherwise traumatised, located in an area of visible scarring or tattooing. - In the Investigator's opinion, able and willing to comply with all study requirements. Exclusion Criteria: Any other significant disease or disorder which, in the opinion of the Investigator, may either put the participant at risk because of participation in the study, or may influence the result of the study, or the participant's ability to participate in the study.

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Study Plan
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How is the study designed?
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Arms and Interventions

| Intervention/Treatment |
| --- |
|Device: Deep Ensemble for the Recognition of Malignancy (DERM)|An AI-based diagnosis support tool|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Sensitivity of DERM to detect Malignant conditions | Sensitivity of DERM to detect Melanoma, SCC and BCC combined | Through study completion, on average of 1 day | 
| Specificity of DERM to detect Malignant conditions. | Specificity of DERM to detect Melanoma, SCC and BCC combined | Through study completion, on average of 1 day | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Sensitivity of DERM to detect Melanoma | Sensitivity of DERM to detect Melanoma | Through study completion, on average of 1 day | 
| Specificity of DERM to detect Melanoma | Specificity of DERM to detect Melanoma | Through study completion, on average of 1 day | 
| Sensitivity of DERM to detect Squamous Cell Carcinoma | Sensitivity of DERM to correctly classify SCC | Through study completion, on average of 1 day | 
| Specificity of DERM to detect Squamous Cell Carcinoma | Specificity of DERM to correctly classify SCC | Through study completion, on average of 1 day | 
| Sensitivity of DERM to detect Basal Cell Carcinoma | Sensitivity of DERM to correctly classify BCC | Through study completion, on average of 1 day | 
| Specificity of DERM to detect Basal Cell Carcinoma | Specificity of DERM to correctly classify BCC | Through study completion, on average of 1 day | 
| Accuracy of mole/not mole algorithm | Accuracy of mole/not mole algorithm | Through study completion, on average of 1 day |