Deep Tissue Sequencing Using Hypodermoscopy and Augmented Intelligence to Analyze Atypical Pigmented Lesions

Abstract

Background:

Over the past decade, new technologies, devices, and methods have been developed to assist in the diagnosis of cutaneous melanocytic lesions.

Objective:

Our objective was to evaluate the performance of an augmented intelligence system in the assessment of atypical pigmented lesions.

Methods:

Nine atypical pigmented lesions on 8 patients were evaluated prior to surgical removal. No lesions had received previous treatment other than a diagnostic biopsy. Prior to surgical removal, each lesion was evaluated by an Augmented Intelligence Dermal Imager (AID) and the assessment parameters reviewed in light of the final histopathological diagnosis.

Results:

The AID was used to evaluate a limited set of atypical pigmented lesions and showed sensitivity and specificity of 82% and 61%, respectively, based on its internal risk assessment algorithms.

Limitations:

These cases represent early assessments of the AID in a clinical setting, all prior assessments having been carried out on digital images. The information received from these evaluations requires further validation and analysis to be able to extrapolate its clinical usefulness.

Conclusion:

The AID combines dermoscopy, hypodermoscopy, and a trained augmented algorithm to produce a diffusion map representing the features of each lesion compared to the learned characteristics from a database of known dermoscopy images of lesions with definitive prior diagnosis. The information gathered from the diffusion map might be used to calculate a malignancy risk factor for the lesion compared to known melanoma features. This malignancy risk factor could be helpful in providing information to justify the biopsy of an atypical pigmented lesion.