Method for coregistration of optical measurements of breast tissue with histopathology: the importance of accounting for tissue deformations

Lisanne L. de Boer*, Esther Kho, Jasper Nijkamp, Koen K. van de Vijver, Henricus J.C.M. Sterenborg, Leon C. ter Beek, Theo J.M. Ruers

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

3 Citations (Scopus)
28 Downloads (Pure)

Abstract

For the validation of optical diagnostic technologies, experimental results need to be benchmarked against the gold standard. Currently, the gold standard for tissue characterization is assessment of hematoxylin and eosin (H&E)-stained sections by a pathologist. When processing tissue into H&E sections, the shape of the tissue deforms with respect to the initial shape when it was optically measured. We demonstrate the importance of accounting for these tissue deformations when correlating optical measurement with routinely acquired histopathology. We propose a method to register the tissue in the H&E sections to the optical measurements, which corrects for these tissue deformations. We compare the registered H&E sections to H&E sections that were registered with an algorithm that does not account for tissue deformations by evaluating both the shape and the composition of the tissue and using microcomputer tomography data as an independent measure. The proposed method, which did account for tissue deformations, was more accurate than the method that did not account for tissue deformations. These results emphasize the need for a registration method that accounts for tissue deformations, such as the method presented in this study, which can aid in validating optical techniques for clinical use.

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Original languageEnglish
Article number075002
Pages (from-to)1-12
Number of pages12
JournalJournal of biomedical optics
Volume24
Issue number7
DOIs
Publication statusPublished - 1 Jul 2019

Keywords

  • Diffuse reflectance
  • Gold standard
  • Histopathology
  • Optical techniques
  • Registration algorithm
  • Validation

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