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Automated Estimation of Melanocytic Skin Tumor Thickness by Ultrasonic Radiofrequency Data
Author(s) -
Andrekute Kristina,
Valiukeviciene Skaidra,
Raisutis Renaldas,
Linkeviciute Gintare,
Makstiene Jurgita,
Kliunkiene Renata
Publication year - 2016
Publication title -
journal of ultrasound in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.574
H-Index - 91
eISSN - 1550-9613
pISSN - 0278-4297
DOI - 10.7863/ultra.15.02051
Subject(s) - medicine , high frequency ultrasound , ultrasonic sensor , ultrasound , biomedical engineering , transducer , melanocytic nevus , skin thickness , melanoma , nevus , radiology , pathology , acoustics , physics , cancer research
Objectives High‐frequency (>20‐MHz) ultrasound (US) is a noninvasive preoperative tool for assessment of melanocytic skin tumor thickness. Ultrasonic melanocytic skin tumor thickness estimation is not always easy and is related to the experience of the clinician. In this article, we present an automated thickness measurement method based on time‐frequency analysis of US radiofrequency signals. Methods The study was performed on 52 thin (≤1‐mm) melanocytic skin tumors (46 melanocytic nevi and 6 melanomas). Radiofrequency signals were obtained with a single‐element focused transducer (fundamental frequency, 22 MHz; bandwidth, 12–28 MHz). The radiofrequency data were analyzed in the time‐frequency domain to make the tumor boundaries more noticeable. The thicknesses of the tumors were evaluated by 3 different metrics: histologically measured Breslow thickness, manually measured US thickness, and automatically measured US thickness. Results The results showed a higher correlation coefficient between the automatically measured US thickness and Breslow thickness ( r = 0.83; P < .0001) than the manually measured US thickness ( r = 0.68; P < .0001). The sensitivity of the automated tumor thickness measurement algorithm was 96.55%, and the specificity was 78.26% compared with histologic measurement. The sensitivity of the manually measured US thickness was 75.86%, and the specificity was 73.91%. Conclusions The efficient automated tumor thickness measurement method developed could be used as a tool for preoperative assessment of melanocytic skin tumor thickness.