Toward assessment of resection margins using hyperspectral diffuse reflection imaging (400–1,700 nm) during tongue cancer surgery

Susan G. Brouwer de Koning*, Pim Weijtmans, M. Baris Karakullukcu, Caifeng Shan, Elisabeth J.M. Baltussen, Laura A. Smit, Robert L.P. van Veen, Benno H.W. Hendriks, Henricus J.C.M. Sterenborg, Theo J.M. Ruers

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

Abstract

Background and Objectives: There is a clinical need to assess the resection margins of tongue cancer specimens, intraoperatively. In the current ex vivo study, we evaluated the feasibility of hyperspectral diffuse reflectance imaging (HSI) for distinguishing tumor from the healthy tongue tissue. Study Design/Materials and Methods: Fresh surgical specimens (n = 14) of squamous cell carcinoma of the tongue were scanned with two hyperspectral cameras that cover the visible and near-infrared spectrum (400–1,700 nm). Each pixel of the hyperspectral image represents a measure of the diffuse optical reflectance. A neural network was used for tissue-type prediction of the hyperspectral images of the visual and near-infrared data sets separately as well as both data sets combined. Results: HSI was able to distinguish tumor from muscle with a good accuracy. The diagnostic performance of both wavelength ranges (sensitivity/specificity of visual and near-infrared were 84%/80% and 77%/77%, respectively) appears to be comparable and there is no additional benefit of combining the two wavelength ranges (sensitivity and specificity were 83%/76%). Conclusions: HSI has a strong potential for intra-operative assessment of tumor resection margins of squamous cell carcinoma of the tongue. This may optimize surgery, as the entire resection surface can be scanned in a single run and the results can be readily available. Lasers Surg. Med.

Original languageEnglish
Pages (from-to)496-502
JournalLasers in Surgery and Medicine
Volume52 (2020)
Issue number6
DOIs
Publication statusPublished - 2019

Keywords

  • deep learning
  • hyperspectral imaging
  • resection margin assessment
  • tissue recognition
  • tongue cancer

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