In vivo Study to Evaluate an Intelligent Algorithm for Time Efficient Detection of Malignant Melanoma Using Dermatofluoroscopy.

Abstract

Introduction: Dermatofluoroscopy is an optical noninvasive method of melanoma/nevus differentiation that has shown 89% sensitivity and 45% specificity in clinical trials, but long measurement duration hinders clinical use. An intelligent algorithm was developed to shorten the measurement time without compromising its diagnostic accuracy. It uses dermoscopic images of the skin lesions to be measured to select measurement points based on the assessment of color values.

Methods: 27 patients with a total of 29 lesions suggestive of cutaneous melanoma were included in a clinical study and measured with both methods, conventional dermatofluoroscopy and the newly developed intelligent algorithm. The results were compared to the independent findings of two histopathologists to evaluate diagnostic accuracy and time saved.

Results: There was a median reduction of measurement points from 265 to 158 (40%). Meanwhile, the intelligent algorithm showed a higher diagnostic accuracy than conventional dermatofluoroscopy (area under the curve of 72% vs. 63%).

Conclusion: The intelligent algorithm did not perform inferior to the conventional method while saving 40% of time. However, measurement times remain long compared to other noninvasive methods of diagnosing malignant melanoma. Further studies are needed to evaluate clinical suitability.

Introduction: Dermatofluoroscopy is an optical noninvasive method of melanoma/nevus differentiation that has shown 89% sensitivity and 45% specificity in clinical trials, but long measurement duration hinders clinical use. An intelligent algorithm was developed to shorten the measurement time without compromising its diagnostic accuracy. It uses dermoscopic images of the skin lesions to be measured to select measurement points based on the assessment of color values.

Methods: 27 patients with a total of 29 lesions suggestive of cutaneous melanoma were included in a clinical study and measured with both methods, conventional dermatofluoroscopy and the newly developed intelligent algorithm. The results were compared to the independent findings of two histopathologists to evaluate diagnostic accuracy and time saved.

Results: There was a median reduction of measurement points from 265 to 158 (40%). Meanwhile, the intelligent algorithm showed a higher diagnostic accuracy than conventional dermatofluoroscopy (area under the curve of 72% vs. 63%).

Conclusion: The intelligent algorithm did not perform inferior to the conventional method while saving 40% of time. However, measurement times remain long compared to other noninvasive methods of diagnosing malignant melanoma. Further studies are needed to evaluate clinical suitability.