Clinical trial NCT06788665: Investigation of the Performance of the Medical Device Dermalyser in Determining Melanoma Thickness Based on Dermoscopy Images
Official title: Investigation of the Performance of the Medical Device Dermalyser in Determining Melanoma Thickness Based on Dermoscopy Images - A Single-center, Non-randomized, Parallel, and Double-blinded Prospective Clinical Investigation
Study type: OBSERVATIONAL
Overall status: NOT_YET_RECRUITING
Conditions: Melanoma (Skin Cancer)
Keywords: melanoma
machine learning
artificial intelligence
diagnostic accuracy
clinical desicion supportive tool
Neoplasms by Histologic Type
Neoplasms
Nevi and Melanomas
Skin Neoplasms
Neoplasms by Site
Skin Diseases
Lead sponsor: Vastra Gotaland Region
Sponsor class: OTHER_GOV
First posted: 2025-01-23
Enrollment: 900
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: OTHER
Time perspective: PROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
Study population: The investigational population are patients ≥18 years with suspected cutaneous melanoma with Fitzpatrick skin phototypes I, II, III and IV. We aim to include 300 melanomas with histopathological verification. Importantly, we will include only suspected melanomas, meaning that some lesions will end up being either dysplastic nevi (DN) or other skin tumours. This implies that we need to include up to 600-900 lesions. Considering the non-invasive nature of the investigational product pregnant and breastfeeding women, immune-compromised and elderly subjects will be eligible for inclusion if they fulfil all inclusion criteria.

Brief summary: In Sweden, approximately 9,000 Swedes are affected by melanoma annually, and each year, 500 individuals die from metastatic melanoma. The prognosis for melanoma primarily depends on the thickness of the tumor at diagnosis. Melanomas that only grow in the epidermis and have not yet grown into the dermis are called melanoma in situ or pre-melanoma. These melanomas lack the potential to spread in the body. Melanomas that grow into the dermis, on the other hand, are called invasive or malignant melanomas. Invasive melanomas have the potential to spread in the body.

To improve melanoma diagnostics, a dermatoscope is used. A dermatoscope is a type of magnifying glass equipped with a strong light. Using a dermatoscope makes the structures in the epidermis and dermis clearer. Although most melanomas are relatively easy to detect, it is often difficult to determine whether melanomas are invasive or in situ based on the dermatoscopic image. Despite the fact that all suspected melanomas (regardless of melanoma depth) should be operated on, it is important to form an opinion on whether the melanoma is invasive or in situ. This decision is important because it:

1. Provides guidance on how quickly healthcare must prioritize a patient for surgery.
2. Provides guidance on the margin the surgeon chooses for the first operation.
3. Affects the information we give the patient even before the first operation.

In recent years, several applications of machine learning have shown great potential in research contexts within dermatology and venereology. However, these tools have been evaluated to a very limited extent in clinical trials, which is naturally a prerequisite before they can be safely implemented in routine healthcare.


Eligibility criteria: Inclusion Criteria:

1. Patient needs to be ≥18 years of age at inclusion
2. The patient has a suspected primary melanoma where surgery is planned
3. Willingness and ability to provide informed consent

Exclusion Criteria:

1. The suspected lesion size is too small or too large to fit the white circle in the screen even after zooming in and out at its maximum. The lesion should not be \< 2 mm or \> 20 mm in diameter.
2. As per judgement by the investigator, to exclude when there are factors that may affect the quality of the photo such as when:

   1. Lesion with any form of modifications such as tattoos, pen markings, and/or pigments covering or surrounding skin lesions.
   2. Lesions located on areas such as genitalia, acral skin (foot sole or palm of the hand), mucosal surfaces (mouth, eye, nose, etc.), psoriasis or similar skin conditions.
   3. Lesions masked by an excessive amount of hair, generally found in armpits, scalp, beards or other hairy parts of the body.
   4. Lesions that are scarred, non-intact, injured, previously biopsied or undergone surgery. in areas that are not suitable for dermoscopy imaging.
3. Individuals with skin type V and VI according to the Fitzpatrick scale (darker brown or black coloured skin)
4. Patients that do not perform surgery or die before the planned surgery
5. Missing or uninterpretable diagnostic data from the Department of Pathology.

Primary outcomes:
measure: Area under the curve (AUC) for discrimination between invansive and in situ melanoma for the "in distribution data set".
timeFrame: From enrollment to the end of the inclusion when the images of the lesion have been obtained. This will most often be achieved on the same day as that the patient is included in the study.
Secondary outcomes:
measure: Sensitivity and Specificity
timeFrame: From enrollment to the end of the inclusion when the images of the lesion have been obtained. This will most often be achieved on the same day as that the patient is included in the study.
Other outcomes:
measure: Algorithmic and physicians assessment of the "out of distribution set"
timeFrame: From enrollment to the end of the inclusion when the images of the lesion have been obtained. This will most often be achieved on the same day as that the patient is included in the study.
Locations:
city: Gothenburg
country: Sweden
facility: Department of Dermatology and Venereology Sahlgrenska University Hospital, Gröna stråket 16
Study officials:
References: