Literature DB >> 31290280

Imaging depth variations in hyperspectral imaging: Development of a method to detect tumor up to the required tumor-free margin width.

Esther Kho1, Lisanne L de Boer1, Anouk L Post1,2, Koen K Van de Vijver3,4, Katarzyna Jóźwiak5, Henricus J C M Sterenborg1,2, Theo J M Ruers1,6.   

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.
© 2019 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  breast-conserving surgery; diffuse reflectance; hyperspectral imaging depth; penetration depth; resection margin assessment; resection margin width

Year:  2019        PMID: 31290280     DOI: 10.1002/jbio.201900086

Source DB:  PubMed          Journal:  J Biophotonics        ISSN: 1864-063X            Impact factor:   3.207


  5 in total

Review 1.  Optoacoustic imaging in endocrinology and metabolism.

Authors:  Angelos Karlas; Miguel A Pleitez; Juan Aguirre; Vasilis Ntziachristos
Journal:  Nat Rev Endocrinol       Date:  2021-04-19       Impact factor: 43.330

Review 2.  Intraoperative imaging in pathology-assisted surgery.

Authors:  Floris J Voskuil; Jasper Vonk; Bert van der Vegt; Schelto Kruijff; Vasilis Ntziachristos; Pieter J van der Zaag; Max J H Witjes; Gooitzen M van Dam
Journal:  Nat Biomed Eng       Date:  2021-11-08       Impact factor: 25.671

3.  Discriminating healthy from tumor tissue in breast lumpectomy specimens using deep learning-based hyperspectral imaging.

Authors:  Lynn-Jade S Jong; Naomi de Kruif; Freija Geldof; Dinusha Veluponnar; Joyce Sanders; Marie-Jeanne T F D Vrancken Peeters; Frederieke van Duijnhoven; Henricus J C M Sterenborg; Behdad Dashtbozorg; Theo J M Ruers
Journal:  Biomed Opt Express       Date:  2022-04-04       Impact factor: 3.562

4.  Over 1000 nm Near-Infrared Multispectral Imaging System for Laparoscopic In Vivo Imaging.

Authors:  Toshihiro Takamatsu; Yuichi Kitagawa; Kohei Akimoto; Ren Iwanami; Yuto Endo; Kenji Takashima; Kyohei Okubo; Masakazu Umezawa; Takeshi Kuwata; Daiki Sato; Tomohiro Kadota; Tomohiro Mitsui; Hiroaki Ikematsu; Hideo Yokota; Kohei Soga; Hiroshi Takemura
Journal:  Sensors (Basel)       Date:  2021-04-09       Impact factor: 3.576

Review 5.  Applications of hyperspectral imaging in the detection and diagnosis of solid tumors.

Authors:  Yating Zhang; Xiaoqian Wu; Li He; Chan Meng; Shunda Du; Jie Bao; Yongchang Zheng
Journal:  Transl Cancer Res       Date:  2020-02       Impact factor: 1.241

  5 in total

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