Diagnostic Agreement Among Expert Dermatopathologists on Skin Lesions Clinically Suspicious of Melanoma

Background Several publications suggest that the increasing melanoma incidence may partly be caused by histopathological overdiagnosis (Glasziou, 2020). Pathologists provide the current gold standard in skin lesion diagnostics (Elmore, 2017), most often primarily based on the interpretation of histological slides. Still, it has been suggested that pathologists' diagnostic accuracy and confidence could be improved if they gained access to additional clinical information and in-vivo clinical and dermoscopic images of melanocytic tumors (Scolyer, 2019) (Elder, 2018). This could help the pathologist generate a complete image of the lesion. However, interpreting clinical and dermoscopic images is challenging, and mastery typically requires several years of clinical experience (Ternov 2021). This learning journey can be significantly shortened if the trainee receives comprehensive training in pattern recognition for dermoscopy and clinical images, including immediate, accurate, and individualized feedback and access to a library with a large selection of skin lesion cases (Ericsson, 2015).

This study examines the effect of digital training for pathologists in interpreting dermoscopic and clinical skin tumor images.

Former studies have only focused on melanocytic lesions. Still, most pathologists will receive both melanocytic and pigmented non-melanocytic lesions (seborrheic keratoses, dermatofibromas, etc.) due to clinical suspicion of melanoma. This study includes an un-filtered selection of 211 clinically melanoma-suspect skin lesions excised at a specialized surgical department; this material is named the DAHT cases.

The primary outcome of the upcoming DAHT RCT (Dermoscopy Augmented Histology Trial, a randomized controlled trial) is the diagnostic value (accuracy, sensitivity, and specificity) for the intervention and control group. For this purpose, we need an MPATH-Dx classification and diagnosis for all DAHT cases agreed upon by experts in the field. The DAHT consensus agreement trial strives to establish this through a four-phased Delphi-like process.

Aim: To establish an expert agreeable MPTAH-Dx classification and diagnosis for all DAHT cases.