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| Name | Class |
|---|---|
| Innovate UK | OTHER_GOV |
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This study aims to establish the effectiveness of an Artificial Intelligence (AI) algorithm (DERM) to determine the presence of Basal Cell Carcinoma (BCC) and Squamous Cell Carcinoma (SCC) and frequently observed benign conditions, when used to analyse images of skin lesions taken by commonly available smart phone cameras.
DERM, an Artificial Intelligence (AI)-based diagnosis support tool, has been shown to be able to accurately identify Non-melanoma skin cancers (NMSC) and other conditions from historical images of suspicious skin lesions (moles). This study aims to establish how well DERM determines the presence of these conditions in images of skin lesions collected in a clinical setting.
Suspicious skin lesions that are due to be assessed by a dermatologist and a patch of healthy skin will be photographed using three commonly available smart phone cameras with a specific lens attachment. The images will be analysed by DERM, and the results compared to the clinician's diagnosis (all lesions) and histologically-conformed diagnosis (any lesion that is biopsied).
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| All patients | Recruited participants will be attending a dermatology clinic with at least one skin lesion where there is a suspicion of skin cancer. All suspicious lesions suitable for photographing will be photographed six times in a single visit. A macro and dermoscopic image of each lesion will be captured by three different mobile phones: an iPhone, a Samsung and a Nokia smart phone, without (macro image) or with (dermoscopic image) a Dermlite DL1 lens attached. Dermoscopic images of healthy skin will also be captured by each camera. Images of the lesions will be analysed by DERM. The DERM results for lesions biopsied will be compared to the biopsy result; the DERM results for lesions not biopsied will be compared to the clinical assessment. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Deep Ensemble for the Recognition of Malignancy (DERM) | Device | An AI-based diagnosis support tool |
|
| Measure | Description | Time Frame |
|---|---|---|
| AUROC of DERM performance when analysing images of biopsied lesions | Area Under the Receiver Operating Characteristic Curve (AUROC) of the DERM result of biopsied lesions, using histopathological-confirmed diagnosis as gold standard | Study completion |
| Measure | Description | Time Frame |
|---|---|---|
| AUROC of DERM performance when analysing images of non-biopsied lesions | Area Under the Receiver Operating Characteristic Curve (AUROC) of the DERM result of biopsied lesions, using clinical diagnosis as gold standard | Study completion: on average 2 days |
| The sensitivity of DERM when used to assess biopsied lesions |
| Measure | Description | Time Frame |
|---|---|---|
| Impact of patient characteristics on the DERM and clinician assessment | The impact of patient characteristics (such as sex, age, location of lesion, total body lesion count, Fitzpatrick skin type, past medical history of skin cancer) on the diagnostic accuracy of DERM and clinician assessment; | Study completion: on average 2 days |
Inclusion Criteria:
Exclusion Criteria:
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Patients attending a dermatology clinic with at least 1 suspicious skin lesion
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Royal Free London NHS Foundation Trust | London | NW3 2QG | United Kingdom | |||
| Royal Victoria Infirmary |
Research to improve or test the performance of DERM only allowed in consent
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The sensitivity of DERM when used to assess biopsied lesions |
| Study completion: on average 2 days |
| The specificity of DERM when used to assess biopsied lesions | The specificity of DERM when used to assess biopsied lesions | Study completion: on average 2 days |
| The false positive rate of DERM when used to assess biopsied lesions | The false positive rate of DERM when used to assess biopsied lesions | Study completion: on average 2 days |
| The false negative rate of DERM when used to assess biopsied lesions | The false negative rate of DERM when used to assess biopsied lesions | Study completion: on average 2 days |
| The positive predictive value of DERM when used to assess biopsied lesions | The positive predictive value of DERM when used to assess biopsied lesions | Study completion: on average 2 days |
| The negative predictive value of DERM when used to assess biopsied lesions | The negative predictive value of DERM when used to assess biopsied lesions | Study completion: on average 2 days |
| The sensitivity of DERM when used to assess non-biopsied lesions | The sensitivity of DERM when used to assess non-biopsied lesions | Study completion: on average 2 days |
| The specificity of DERM when used to assess non-biopsied lesions | The specificity of DERM when used to assess non-biopsied lesions | Study completion: on average 2 days |
| The false positive rate of DERM when used to assess non-biopsied lesions | The false positive rate of DERM when used to assess non-biopsied lesions | Study completion: on average 2 days |
| The false negative rate of DERM when used to assess non-biopsied lesions | The false negative rate of DERM when used to assess non-biopsied lesions | Study completion: on average 2 days |
| The positive predictive value of DERM when used to assess non-biopsied lesions | The positive predictive value of DERM when used to assess non-biopsied lesions | Study completion: on average 2 days |
| The negative predictive value of DERM when used to assess non-biopsied lesions | The negative predictive value of DERM when used to assess non-biopsied lesions | Study completion: on average 2 days |
| Concordance of clinician assessment with histologically confirmed diagnosis | Concordance of clinician assessment with histologically confirmed diagnosis | Study completion: on average 2 days |
| The concordance of DERM result generated using images from each camera | The concordance of DERM result generated using images from each camera | Study completion: on average 2 days |
| The proportion of skin lesions with 3 images that can be analysed by DERM; | The proportion of skin lesions with 3 images that can be analysed by DERM; | Study completion: on average 2 days |
| The proportion of skin lesions with at least 1 readable image that can be analysed by DERM | The proportion of skin lesions with at least 1 readable image that can be analysed by DERM | Study completion: on average 2 days |
| Impact of lesion characteristics on the DERM and clinician assessment |
The impact of lesions characteristic (such as growth over last 6 months, stage and sub-type) on the diagnostic accuracy of DERM and clinician assessment |
| Study completion: on average 2 days |
| The impact of image variables on the diagnostic accuracy of DERM assessment | The impact of image variables (such as macro and dermoscopic images) on the diagnostic accuracy of DERM assessment | Study completion: on average 2 days |
| DERM performance (AUROC) when macro images are used both to train the algorithm and as test images | Exploration of whether macro images can be used as part of DERM's assessment | Study completion: on average 2 days |
| Newcastle upon Tyne |
| NE7 7DN |
| United Kingdom |
| Poole General Hospital | Poole | BH15 2JB | United Kingdom |