Potential use of spectral image analysis for the quantitative evaluation of estrogen receptors in breast cancer

Authors

  • Zvi Malik
  • I. Barshack
  • A. Gil
  • I. Goldberg
  • J. Kopolovic
  • C. Rothmann

Keywords:

spectral image analysis, quantification, breast cancer, prognostic factors, estrogen receptors

Abstract

Evaluation of estrogen receptor (ER) content is an important factor in the choice of therapy and prognosis of breast cancer patients. In this study, we demonstrate a new spectral image analysis technique for objective and quantitative evaluations of stained specimens. The SpectraCubeTM system was used to analyze nuclear antigens in thirteen cases of breast cancer stained by the immunoperoxidase method with hematoxylin counterstain. Spectral imaging segregated the spectrum of diaminobenzidine (DAB) from the background color of hematoxylin and a spectral index was calculated. The spectral index essentially agreed with the pathologist's index (on a scale of 0 to 3) in seven out of the thirteen cases. A substantial number of ER positive pixels was detected in the two cases scored as 0 by the pathologist's index. In a test case scored as 1 by the pathologist's index we detected a significant number of pixels, representing 47% of the nuclei, with DAB-intensity values higher than the cut-off value of 1.2. These data suggest that spectral image analysis is a sensitive method providing intensive information with high reproducibility. Our spectral imaging method is highly flexible, enabling the user to define the spatial resolution of the analyzed specimen by choosing the number of pixels per one nucleus.

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