{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T23:42:21Z","timestamp":1787355741167,"version":"build-2736575974"},"reference-count":46,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2013,1,27]],"date-time":"2013-01-27T00:00:00Z","timestamp":1359244800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Skin Research and Technology"],"published-print":{"date-parts":[[2013,5]]},"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>Previous studies have shown statistically significant differences in electrical impedance between various cutaneous lesions. Electrical impedance spectroscopy (EIS) may therefore be able to aid clinicians in differentiating between benign and malignant skin lesions.<\/jats:p><\/jats:sec><jats:sec><jats:title>Objectives<\/jats:title><jats:p>The aim of the study was to develop a classification algorithm to distinguish between melanoma and benign lesions of the skin with a sensitivity of at least 98% and a specificity approximately 20 per cent higher than the diagnostic accuracy of dermatologists.<\/jats:p><\/jats:sec><jats:sec><jats:title>Patients\/Methods<\/jats:title><jats:p>A total of 1300 lesions were collected in a multicentre, prospective, non\u2010randomized clinical trial from 19 centres around Europe. All lesions were excised and subsequently evaluated independently by a panel of three expert dermatopathologists. From the data two classification algorithms were developed and verified.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>For the first classification algorithm, approximately 40% of the data were used for calibration and 60% for testing. The observed sensitivity for melanoma was 98.1% (101\/103), non\u2010melanoma skin cancer 100% (25\/25) and dysplastic nevus with severe atypia 84.2% (32\/38). The overall observed specificity was 23.6% (66\/280). For the second classification algorithm, approximately 55% of the data were used for calibration. The observed sensitivity for melanoma was 99.4% (161\/162), for non\u2010melanoma skin cancer was 98.0% (49\/50) and dysplastic nevus with severe atypia was 93.8% (60\/64). The overall observed specificity was 24.5% (116\/474).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>EIS has the potential to be an adjunct diagnostic tool to help clinicians differentiate between benign and malignant (melanocytic and non\u2010melanocytic) skin lesions. Further studies are needed to confirm the validity of the automatic assessment algorithm.<\/jats:p><\/jats:sec>","DOI":"10.1111\/srt.12008","type":"journal-article","created":{"date-parts":[[2013,1,27]],"date-time":"2013-01-27T19:16:00Z","timestamp":1359314160000},"page":"75-83","source":"Crossref","is-referenced-by-count":81,"title":["Electrical impedance spectroscopy as a potential adjunct diagnostic tool for cutaneous melanoma"],"prefix":"10.1111","volume":"19","author":[{"given":"Peter","family":"Mohr","sequence":"first","affiliation":[{"name":"Department of Dermatology Elbe\u2010Klinikum Buxtehude Buxtehude Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ulrik","family":"Birgersson","sequence":"additional","affiliation":[{"name":"Division of Imaging and Technology Department of Clinical Science Intervention and Technology Karolinska Institutet Huddinge Sweden"},{"name":"SciBase AB Stockholm 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