Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
DERM is a Medical Device that uses artificial intelligence to help doctors check if a skin lesion might be cancerous. It works by analysing close-up pictures of skin lesions taken with a smartphone.
This study aims to demonstrate how consistent (precise) the output of DERM is: i.e. does it provide the same result when it analyses multiple photos of the same lesion (repeatability), and when the same lesion is photographed by different people, or with different cameras (reproducibility).
Adults with at least one skin lesion that doctors are checking for cancer, as part of their standard care, will be able to take part. Suitable lesions will be photographed three times, each by three different people using three sets of image capture hardware (specifically, an iPhone 11 with a DL200/HR dermoscopic lens). Each image will be checked for good image quality as it is captured. Images will then be transferred to DERM, where they'll be analysed.
The DERM output won't be shared with the patients or doctors involved in the study. The patients will continue to have their skin lesion biopsy/excised, in accordance with standard of care. Their diagnosis will be collected and compared to the output from DERM.
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Label | Type | Description | Intervention Names |
|---|---|---|---|
| All patients | All patients will have their skin lesion imaged in the same way |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Deep Ensemble for the Recognition of Malignancy (DERM) | Device | DERM variants "+" and "DS" |
|
| Measure | Description | Time Frame |
|---|---|---|
| Reproducibility: Average Positive Agreement (APA) of DERM on malignant lesions is >80% | Each lesion will be imaged by three users using three sets of the image capture hardware, generating nine data sets (user/hardware combinations) per lesion. Each lesion image data set will consist of 3 repeated measures, resulting in 27 measures per lesion | 1 day |
| Repeatability: Average Positive Agreement (APA) of DERM on malignant lesions is >80% | Each lesion will be imaged by three users using three sets of the image capture hardware, generating nine data sets (user/hardware combinations) per lesion. Each lesion image data set will consist of 3 repeated measures, resulting in 27 measures per lesion. | 1 day |
| Measure | Description | Time Frame |
|---|---|---|
| Reproducibility: Average Negative Agreement (ANA) of DERM on benign lesions is >50% | Each lesion will be imaged by three users using three sets of the image capture hardware, generating nine data sets (user/hardware combinations) per lesion. Each lesion image data set will consist of 3 repeated measures, resulting in 27 measures per lesion. | 1 day |
Not provided
Inclusion Criteria:
Exclusion Criteria:
To be suitable for inclusion, a skin lesion must NOT have ANY of the following limitations:
Not provided
Not provided
Not provided
Patients will be recruited in specialist dermatology clinics in the UK.
Not provided
Not provided
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Norwich and Norfolk Hospitals Trust | Norwich | United Kingdom | ||||
| University Hospitals Dorset |
Subject to constraints in patient consent
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Repeatability: Average Negative Agreement (ANA) of DERM on benign lesions is >50% | Each lesion will be imaged by three users using three sets of the image capture hardware, generating nine data sets (user/hardware combinations) per lesion. Each lesion image data set will consist of 3 repeated measures, resulting in 27 measures per lesion. | 1 day |
| Poole |
| United Kingdom |
| Surrey and Sussex Hospital Trust | Redhill | United Kingdom |
| ID | Term |
|---|---|
| D012878 | Skin Neoplasms |
| D008545 | Melanoma |
| D018307 | Neoplasms, Squamous Cell |
| D018295 | Neoplasms, Basal Cell |
| ID | Term |
|---|---|
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
| D012871 | Skin Diseases |
| D017437 | Skin and Connective Tissue Diseases |
| D018358 | Neuroendocrine Tumors |
| D017599 | Neuroectodermal Tumors |
| D009373 | Neoplasms, Germ Cell and Embryonal |
| D009370 | Neoplasms by Histologic Type |
| D009380 | Neoplasms, Nerve Tissue |
| D018326 | Nevi and Melanomas |
| D009375 | Neoplasms, Glandular and Epithelial |
Not provided
Not provided