Automatic Differential Diagnosis of Melanocytic Skin Tumors Using Ultrasound Data

• Published in: Ultrasound in medicine & biology Vol. 42; no. 12; pp. 2834 - 2843
• Main Authors: Andrėkutė, Kristina, Linkevičiūtė, Gintarė, Raišutis, Renaldas, Valiukevičienė, Skaidra, Makštienė, Jurgita
• Format: Journal Article
• Language: English
• Published: England Elsevier Inc 01.12.2016
• Subjects: Adolescent; Adult; Aged; Aged, 80 and over; Automatic diagnosis; Diagnosis, Differential; Female; Humans; Male; Malignant melanoma; Melanoma - diagnostic imaging; Middle Aged; Nevus, Pigmented - diagnostic imaging; Radiofrequency signal; Radiology; Reproducibility of Results; Sensitivity and Specificity; Skin - diagnostic imaging; Skin Neoplasms - diagnostic imaging; Spectral analysis; Tissue characterization; Ultrasonography - methods; Ultrasound; Young Adult; Automatic diagnosis; Ultrasound; Radiofrequency signal; Spectral analysis; Tissue characterization; Malignant melanoma
• ISSN: 0301-5629; 1879-291X
• DOI: 10.1016/j.ultrasmedbio.2016.07.026

Abstract We describe a novel automatic diagnostic system based on quantitative analysis of ultrasound data for differential diagnosis of melanocytic skin tumors. The proposed method has been tested on 160 ultrasound data sets (80 of malignant melanoma and 80 of benign melanocytic nevi). Acoustical, textural and shape features have been evaluated for each segmented lesion. Using parameters selected according to Mahalanobis distance and linear support vector machine classifier, we are able to differentiate malignant melanoma from benign melanocytic skin tumors with 82.4% accuracy (sensitivity = 85.8%, specificity = 79.6%). The results indicate that high-frequency ultrasound has the potential to be used for differential diagnosis of melanocytic skin tumors and to provide supplementary information on lesion penetration depth. The proposed system can be used as an additional tool for clinical decision support to improve the early-stage detection of malignant melanoma.