Hyperspectral Imaging for Non-invasive Diagnostics of Melanocytic Lesions

Authors

  • John Paoli Department of Dermatology and Venereology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Guthenburg, Sweden; Department of Dermatology and Venereology, Region Västra Götaland, Sahlgrenska University Hospital, Gothenburg, Sweden
  • Ilkka Pölönen Faculty of Information Technology, University of Jyväskylä, Finland
  • Mari Salmivuori Department of Dermatology and Allergology, Päijät-Häme Social and Health Care Group, Lahti, Finland; Department of Dermatology and Allergology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
  • Janne Räsänen Department of Dermatology and Allergology, Päijät-Häme Social and Health Care Group, Lahti, Finland; Department of Dermatology, Tampere University Hospital and Faculty of Medicine and Medical technology, Tampere University, Tampere, Finland
  • Oscar Zaar Department of Dermatology and Venereology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Guthenburg, Sweden; Department of Dermatology and Venereology, Region Västra Götaland, Sahlgrenska University Hospital, Gothenburg, Sweden
  • Sam Polesie Department of Dermatology and Venereology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Guthenburg, Sweden; Department of Dermatology and Venereology, Region Västra Götaland, Sahlgrenska University Hospital, Gothenburg, Sweden
  • Sari Koskenmies Department of Dermatology and Allergology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
  • Sari Pitkänen Department of Dermatology and Allergology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
  • Meri Övermark Department of Dermatology and Allergology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
  • Kirsi Isoherranen Department of Dermatology and Allergology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
  • Susanna Juteau Department of Pathology, University of Helsinki and HUSLAB, Helsinki, Finland
  • Annamari Ranki Department of Dermatology and Allergology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
  • Mari Grönroos Department of Dermatology and Allergology, Päijät-Häme Social and Health Care Group, Lahti, FinlanDepartment of Dermatology and Allergology, Päijät-Häme Social and Health Care Group, Lahti, Finland
  • Noora Neittaanmäki Department of Dermatology and Venereology, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Guthenburg, Sweden; Department of Laboratory Medicine, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Department of Clinical Pathology, Region Västra Götaland, Sahlgrenska University Hospital, Gothenburg, Sweden

DOI:

https://doi.org/10.2340/actadv.v102.2045

Keywords:

hyperspectral imaging, non-invasive diagnostic, machine learning, malignant melanoma

Abstract

Malignant melanoma poses a clinical diagnostic problem, since a large number of benign lesions are excised to find a single melanoma. This study assessed the accuracy of a novel non-invasive diagnostic technology, hyperspectral imaging, for melanoma detection. Lesions were imaged prior to excision and histopathological analysis. A deep neural network algorithm was trained twice to distinguish between histopathologically verified malignant and benign melanocytic lesions and to classify the separate subgroups. Furthermore, 2 different approaches were used: a majority vote classification and a pixel-wise classification. The study included 325 lesions from 285 patients. Of these, 74 were invasive melanoma, 88 melanoma in situ, 115 dysplastic naevi, and 48 non-dysplastic naevi. The study included a training set of 358,800 pixels and a validation set of 7,313 pixels, which was then tested with a training set of 24,375 pixels. The majority vote classification achieved high overall sensitivity of 95% and a specificity of 92% (95% confidence interval (95% CI) 0.024–0.029) in differentiating malignant from benign lesions. In the pixel-wise classification, the overall sensitivity and specificity were both 82% (95% CI 0.005–0.005). When divided into 4 subgroups, the diagnostic accuracy was lower. Hyperspectral imaging provides high sensitivity and specificity in distinguishing between naevi and melanoma. This novel method still needs further validation.

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Published

2022-11-14

How to Cite

Paoli, J., Pölönen, I., Salmivuori, M., Räsänen, J., Zaar, O., Polesie, S., Koskenmies, S., Pitkänen, S., Övermark, M., Isoherranen, K., Juteau, S., Ranki, A., Grönroos, M., & Neittaanmäki, N. (2022). Hyperspectral Imaging for Non-invasive Diagnostics of Melanocytic Lesions. Acta Dermato-Venereologica, 102, adv00815. https://doi.org/10.2340/actadv.v102.2045