Hyperspectral imaging for resection margin assessment during breast cancer surgery

Esther Kho

Research output: ThesisPhD Thesis - Research external, graduation UT

125 Downloads (Pure)

Abstract

Complete tumor removal during breast-conserving surgery remains challenging due to the lack of optimal intraoperative margin assessment techniques. This thesis investigates the potential of hyperspectral imaging to assess the resection margin during surgery. Hyperspectral imaging is a non-invasive, optical imaging technique that measures differences in the optical properties of tissue. These differences in optical properties are measured in the form of diffuse reflectance spectra and can be used to differentiate tumor from healthy tissue. By imaging and analyzing the resection margin of a specimen during surgery, direct feedback can be given to the surgeon.
We started our research with imaging breast tissue slices, that were obtained after gross-sectioning lumpectomy specimen. We developed a registration method to obtain a high correlation of these optical measurements with histopathology and, thereby, created an extensive hyperspectral database that was used to research the maximum capability of hyperspectral imaging to differentiate tissue types. The highest classification results were obtained using both the visual and near-infrared wavelength range. On hyperspectral signals, representing a single tissue type, we report a sensitivity and specificity above 98%, which indicates that the optical differences in tissue composition and morphology can be used to distinguish tumor from healthy breast tissue. On hyperspectral signals, representing a mixture of tissue classes, the sensitivity and specificity decrease to 80% and 93%, respectively. This is related to the percentage of a specific tissue class in the measured volume. The next step was to image lumpectomy specimen during surgery to verify the feasibility of using hyperspectral imaging during surgery. Hyperspectral imaging was fast and could provide feedback over the entire resection surface of one side of the specimen in 3 minutes. In combination with the classification performance on the tissue slices, these findings support that hyperspectral imaging can become a powerful tool for margin assessment during breast-conserving surgery.


Original promotion date: April 24, 2020 (COVID-19)
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • University of Twente
Supervisors/Advisors
  • Ruers, Theo J.M., Supervisor
  • Sterenborg, Henricus J.C.M., Co-Supervisor, External person
Thesis sponsors
Award date2 Oct 2020
Place of PublicationEnschede
Publisher
Print ISBNs978-90-365-4924-0
DOIs
Publication statusPublished - 2 Oct 2020

Keywords

  • Hyperspectral imaging
  • Breast cancer
  • Diffuse reflectance
  • Resection margin assessment

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