Clinical performance of a novel hyperspectral imaging device for cutaneous melanoma and pigmented skin lesions in Caucasian skin

Skin Res Technol. 2021 Sep;27(5):803-809. doi: 10.1111/srt.13023. Epub 2021 Mar 2.

Abstract

Background: The quest for diagnostic tools for the detection of cutaneous malignant melanoma (cMM) is ongoing. A challenge in cMM care is not overlooking cMM at an early stage, while simultaneously avoiding unnecessary biopsies or excisions of benign pigmented skin lesions (PSLs). A novel hyperspectral imaging (HSI) device is shown to have potential for differentiating equivocal PSLs in Asian skin types. Our objective was to assess the accuracy of the HSI device in distinguishing between cMM and benign PSLs in patients with Caucasian skin types.

Methods: Patients with Caucasian skin types (Fitzpatrick I-II), enrolled for excisional biopsies of PSLs were included and examined using the HSI device. The discrimination index (DI) was used to demonstrate the sensitivity (SE) and specificity (SP) in comparison with the re-evaluated histopathology diagnoses.

Results: In 186 patients, 202 pigmented skin lesions were included. The sensitivity to detect cMM was 96.7% (87/90), and the specificity for benign lesions was 42.1% (45/107). The AUC was 0.800 (95% confidence interval (CI): 0.740-0.861).

Conclusions: Our novel HSI device showed a high sensitivity in detecting malignant lesions in patients with Caucasian skin types. Compared with analogous technologies, as multispectral imaging or electrical impedance spectroscopy, our device showed similar or better accuracy in differentiating cMM from benign PSLs. Therefore, it might be a useful clinical tool in skin types I-IV and where further triage of pigmented skin lesions is important.

Keywords: Caucasian skin type; hyperspectral imaging; melanoma; pigmented skin lesions.

MeSH terms

  • Humans
  • Hyperspectral Imaging
  • Melanoma* / diagnostic imaging
  • Pigmentation Disorders*
  • Sensitivity and Specificity
  • Skin Neoplasms* / diagnostic imaging