Single probe light reflectance spectroscopy and parameter spectrum feature extraction in experimental skin cancer detection and classification

David Abookasis, David Shemesh, Arik Litwin, Hava T. Siegelmann, Elena Didkovsky, Dean D. Ad-El

Research output: Contribution to journalArticlepeer-review

Abstract

Skin cancer, an anomalous development of skin cells in the epidermis, is among the most common types of cancer worldwide. Because of its clinical importance and to improve early diagnosis and patient management, there is an urgent need to develop noninvasive, accurate medical diagnostic tools. To this aim, light reflectance spectroscopy over the visible and near-infrared spectral range (400–1000 nm) based on a single-fiber six-around-one optical probe was applied to extract nine features used for diagnostics. These features include skewness, entropy, energy, kurtosis, scattering amplitude, and others, and are spread over each of four different spectral signatures, namely, light reflectance, absorbance, scattering profile approximation, and absorption/scattering ratio. Our preliminary studies focused on 11 adult patients with diagnoses of malignant melanoma (n = 4), basal cell carcinoma (n = 5), and squamous cell carcinoma (n = 2) in a variety of locations on the body. Measurements were taken first in vivo before surgery, at the site of the lesion and from healthy skin of the same patient, and ex vivo after surgical excision, where the lesion was rinsed in saline solution and measurements of the reflected light from the “inside” facing plane of the tissue were taken in the same manner. Overall, experimental results demonstrate that by examining a variety of wavebands, features, and statistical metrics, we can detect and distinguish cancer from normal tissue and different cancer subtypes. Nevertheless, discrepancies in results between in vivo and ex vivo tissue were observed and explanations for these discrepancies are discussed. (Figure presented.)

Original languageEnglish
Article numbere202300001
JournalJournal of Biophotonics
Volume16
Issue number8
DOIs
StatePublished - Aug 2023

Keywords

  • cancer
  • detection and classification
  • extracted features
  • reflectance spectroscopy
  • single optical probe

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