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Diffuse reflectance spectroscopy: Towards clinical application in breast cancer

  • Daniel J. Evers
  • , Rami Nachabe
  • , Marie-Jeanne Vranken Peeters
  • , Jos A. van der Hage
  • , Hester S. Oldenburg
  • , Emiel J. Rutgers
  • , Gerald W. Lucassen
  • , Benno H. W. Hendriks
  • , Jelle Wesseling
  • , Theo J. M. Ruers
  • Netherlands Cancer Institute
  • Koninklijke Philips N.V.
  • University of Twente

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Diffuse reflectance spectroscopy (DRS) is a promising new technique for breast cancer diagnosis. However, inter-patient variation due to breast tissue heterogeneity may interfere with the accuracy of this technique. To tackle this issue, we aim to determine the diagnostic accuracy of DRS in individual patients. With this approach, DRS measurements of normal breast tissue in every individual patient are directly compared with measurements of the suspected malignant tissue. Breast tissue from 47 female patients was analysed ex vivo by DRS. A total of 1,073 optical spectra were collected. These spectra were analyzed for each patient individually as well as for all patients collectively and results were compared to the pathology analyses. Collective patient data analysis for discrimination between normal and malignant breast tissue resulted in a sensitivity of 90 %, a specificity of 88 %, and an overall accuracy of 89 %. In the individual analyses all measurements per patient were categorized as either benign or malignant. The discriminative accuracy of these individual analyses was nearly 100 %. The diagnosis was classified as uncertain in only one patient. Based on the results presented in this study, we conclude that the analysis of optical characteristics of different tissue classes within the breast of a single patient is superior to an analysis using the results of a cohort data analysis. When integrated into a biopsy device, our results demonstrate that DRS may have the potential to improve the diagnostic workflow in breast cancer. © 2012 Springer Science+Business Media New York.
Original languageEnglish
Pages (from-to)155-165
JournalBreast cancer research and treatment
Volume137
Issue number1
DOIs
Publication statusPublished - Jan 2013
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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