The dermoscopic inverse approach significantly improves the accuracy of human readers for lentigo maligna diagnosis
April 8, 2021
Abstract
Background:
A recently introduced dermoscopic method for the diagnosis of early lentigo maligna (LM) is based on the absence of prevalent patterns of pigmented actinic keratosis and solar lentigo/flat seborrheic keratosis. We term this the inverse approach.
Objective:
To determine whether training on the inverse approach increases the diagnostic accuracy of readers compared to classic pattern analysis.
Methods:
We used clinical and dermoscopic images of histopathologically diagnosed LMs, pigmented actinic keratoses, and solar lentigo/flat seborrheic keratoses. Participants in a dermoscopy masterclass classified the lesions at baseline and after training on pattern analysis and the inverse approach. We compared their diagnostic performance among the 3 timepoints and to that of a trained convolutional neural network.
Results:
The mean sensitivity for LM without training was 51.5%; after training on pattern analysis, it increased to 56.7%; and after learning the inverse approach, it increased to 83.6%. The mean proportions of correct answers at the 3 timepoints were 62.1%, 65.5, and 78.5%. The percentages of readers outperforming the convolutional neural network were 6.4%, 15.4%, and 53.9%, respectively.
Limitations:
The experimental setting and the inclusion of histopathologically diagnosed lesions only.
Conclusions:
The inverse approach, added to the classic pattern analysis, significantly improves the sensitivity of human readers for early LM diagnosis.
Source:
Lallas, A., Lallas, K., Tschandl, P., Kittler, H., Apalla, Z., Longo, C., & Argenziano, G. (2021). The dermoscopic inverse approach significantly improves the accuracy of human readers for lentigo maligna diagnosis. Journal of the American Academy of Dermatology, 84(2), 381-389. doi:10.1016/j.jaad.2020.06.085