Imaging depth variations in hyperspectral imaging: Development of a method to detect tumor up to the required tumor‐free margin width. Issue 11 (23rd July 2019)

• Record Type: Journal Article
• Authors: Kho, Esther; de Boer, Lisanne L.; Post, Anouk L.; Van de Vijver, Koen K.; Jóźwiak, Katarzyna; Sterenborg, Henricus J.C.M.; Ruers, Theo J.M.
• Is Part Of: Journal of biophotonics. Volume 12:Issue 11(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-07-23
• Subjects: breast‐conserving surgery -- diffuse reflectance -- hyperspectral imaging depth -- penetration depth -- resection margin assessment -- resection margin width; Photonics -- Periodicals; Optical materials -- Periodicals; Optics -- Periodicals; Medical instruments and apparatus -- Periodicals; 621.3605
• DOI: 10.1002/jbio.201900086
• Languages: English
• ISSNs: 1864-063X

Abstract

Abstract: Hyperspectral imaging is a promising technique for resection margin assessment during cancer surgery. Thereby, only a specific amount of the tissue below the resection surface, the clinically defined margin width, should be assessed. Since the imaging depth of hyperspectral imaging varies with wavelength and tissue composition, this can have consequences for the clinical use of hyperspectral imaging as margin assessment technique. In this study, a method was developed that allows for hyperspectral analysis of resection margins in breast cancer. This method uses the spectral slope of the diffuse reflectance spectrum at wavelength regions where the imaging depth in tumor and healthy tissue is equal. Thereby, tumor can be discriminated from healthy breast tissue while imaging up to a similar depth as the required tumor‐free margin width of 2 mm. Applying this method to hyperspectral images acquired during surgery would allow for robust margin assessment of resected specimens. In this paper, we focused on breast cancer, but the same approach can be applied to develop a method for other types of cancer. Abstract : Hyperspectral imaging is a promising technique for assessing the entire resection surface during cancer surgery. However, variations in imaging depth with hyperspectral imaging may have consequences for its clinical use since only the clinically relevant margin width should be assessed. As such, we investigated this imaging depth and developed a method that was able to discriminate tumor from healthy breast tissue for the clinically relevant margin width of 2 mm.