Improving Skin cancer Management with ARTificial Intelligence (SMARTI): protocol for a preintervention/postintervention trial of an artificial intelligence system used as a diagnostic aid for skin cancer management in a specialist dermatology setting

Abstract

IntroductionConvolutional neural networks (CNNs) can diagnose skin cancers with impressive accuracy in experimental settings, however, their performance in the real-world clinical setting, including comparison to teledermatology services, has not been validated in prospective clinical studies.Methods and analysisParticipants will be recruited from dermatology clinics at the Alfred Hospital and Skin Health Institute, Melbourne. Skin lesions will be imaged using a proprietary dermoscopic camera. The artificial intelligence (AI) algorithm, a CNN developed by MoleMap Ltd and Monash eResearch, classifies lesions as benign, malignant or uncertain. This is a preintervention/postintervention study. In the preintervention period, treating doctors are blinded to AI lesion assessment. In the postintervention period, treating doctors review the AI lesion assessment in real time, and have the opportunity to then change their diagnosis and management. Any skin lesions of concern and at least two benign lesions will be selected for imaging. Each participant’s lesions will be examined by a registrar, the treating consultant dermatologist and later by a teledermatologist. At the conclusion of the preintervention period, the safety of the AI algorithm will be evaluated in a primary analysis by measuring its sensitivity, specificity and agreement with histopathology where available, or the treating consultant dermatologists’ classification. At trial completion, AI classifications will be compared with those of the teledermatologist, registrar, treating dermatologist and histopathology. The impact of the AI algorithm on diagnostic and management decisions will be evaluated by: (1) comparing the initial management decision of the registrar with their AI-assisted decision and (2) comparing the benign to malignant ratio (for lesions biopsied) between the preintervention and postintervention periods.Ethics and disseminationHuman Research Ethics Committee (HREC) approval received from the Alfred Hospital Ethics Committee on 14 February 2019 (HREC/48865/Alfred-2018). Findings from this study will be disseminated through peer-reviewed publications, non-peer reviewed media and conferences.Trial registration numberNCT04040114.

Basic principles of artificial intelligence in dermatology explained using melanoma

“…Felmingham et al described the algorithm ARTificial Intelligence (SMARTI), run by a CNN. 50 Specifically designed cameras with the ability to take both dermatoscopic and macroscopic pictures were used. The application installed on a computer shows the patient's images alongside diagnostic advice.…”

“…Felmingham et al. described the algorithm ARTificial Intelligence (SMARTI), run by a CNN 50 . Specifically designed cameras with the ability to take both dermatoscopic and macroscopic pictures were used.…”

Grundprinzipien der künstlichen Intelligenz in der Dermatologie erklärt am Beispiel des Melanoms

“…Felmingham et al. beschrieben den Algorithmus ARTificial Intelligence (SMARTI), der von einem CNN betrieben wird 50 . Es wurden speziell entwickelte Kameras verwendet, die sowohl dermatoskopische als auch makroskopische Bilder aufnehmen können.…”

“…Felmingham et al beschrieben den Algorithmus ARTificial Intelligence (SMARTI), der von einem CNN betrieben wird. 50 Es wurden speziell entwickelte Kameras verwendet, die sowohl dermatoskopische als auch makroskopische Bilder aufnehmen können. Die auf einem Computer installierte Anwendung zeigt die Bilder der Patienten zusammen mit diagnostischen Hinweisen an.…”

The role of mobile teledermoscopy in skin cancer triage and management during the COVID-19 pandemic

“…There is some initial evidence for the effectiveness of artificial intelligence in the detection of melanoma, even demonstrating its higher accuracy compared to specialist dermatologists in several studies, [42][43][44][45] though more studies evaluating its implementation in clinical practice are required. A prospective clinical trial being conducted in Australia is one of the first to evaluate the use of artificial intelligence as a diagnostic aid for skin cancer in a real-world setting.…”