Hyperspectral imaging for tissue classification, a way toward smart laparoscopic colorectal surgery

Elisabeth J. M. Baltussen; Esther N. D. Kok; Susan G. Brouwer de Koning; Joyce Sanders; Arend G. J. Aalbers; Niels F. M. Kok; Geerard L. Beets; Claudie C. Flohil; Sjoerd C. Bruin; Koert F. D. Kuhlmann; Henricus J. C. M. Sterenborg; Theo J. M. Ruers

doi:10.1117/1.JBO.24.1.016002

30 January 2019 Hyperspectral imaging for tissue classification, a way toward smart laparoscopic colorectal surgery

Elisabeth J. M. Baltussen, Esther N. D. Kok, Susan G. Brouwer de Koning, Joyce Sanders, Arend G. J. Aalbers, Niels F. M. Kok, Geerard L. Beets, Claudie C. Flohil, Sjoerd C. Bruin, Koert F. D. Kuhlmann, Henricus J. C. M. Sterenborg, Theo J. M. Ruers

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Funded by: Stichting Stop Darmkanker

Journal of Biomedical Optics, Vol. 24, Issue 1, 016002 (January 2019). https://doi.org/10.1117/1.JBO.24.1.016002

Abstract

In the last decades, laparoscopic surgery has become the gold standard in patients with colorectal cancer. To overcome the drawback of reduced tactile feedback, real-time tissue classification could be of great benefit. In this ex vivo study, hyperspectral imaging (HSI) was used to distinguish tumor tissue from healthy surrounding tissue. A sample of fat, healthy colorectal wall, and tumor tissue was collected per patient and imaged using two hyperspectral cameras, covering the wavelength range from 400 to 1700 nm. The data were randomly divided into a training (75%) and test (25%) set. After feature reduction, a quadratic classifier and support vector machine were used to distinguish the three tissue types. Tissue samples of 32 patients were imaged using both hyperspectral cameras. The accuracy to distinguish the three tissue types using both hyperspectral cameras was 0.88 (STD = 0.13) on the test dataset. When the accuracy was determined per patient, a mean accuracy of 0.93 (STD = 0.12) was obtained on the test dataset. This study shows the potential of using HSI in colorectal cancer surgery for fast tissue classification, which could improve clinical outcome. Future research should be focused on imaging entire colon/rectum specimen and the translation of the technique to an intraoperative setting.

CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Elisabeth J. M. Baltussen, Esther N. D. Kok, Susan G. Brouwer de Koning, Joyce Sanders, Arend G. J. Aalbers, Niels F. M. Kok, Geerard L. Beets, Claudie C. Flohil, Sjoerd C. Bruin, Koert F. D. Kuhlmann, Henricus J. C. M. Sterenborg, and Theo J. M. Ruers "Hyperspectral imaging for tissue classification, a way toward smart laparoscopic colorectal surgery," Journal of Biomedical Optics 24(1), 016002 (30 January 2019). https://doi.org/10.1117/1.JBO.24.1.016002

Received: 17 September 2018; Accepted: 11 January 2019; Published: 30 January 2019

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