Comparing in vivo and ex vivo fiberoptic diffuse reflectance spectroscopy in colorectal cancer. Issue 1 (30th December 2019)

• Record Type: Journal Article
• Authors: Baltussen, Elisabeth J.M.; Brouwer De Koning, Susan G.; Hendriks, Benno H.W.; Jóźwiak, Katarzyna; Sterenborg, Henricus J.C.M.; Ruers, Theo J.M.
• Is Part Of: Translational biophotonics. Volume 1:Issue 1/2(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-12-30
• Subjects: colorectal cancer -- diffuse reflectance spectroscopy -- ex vivo -- in vivo -- tissue classification; Imaging systems in medicine -- Periodicals; Biosensors -- Optical properties -- Periodicals; Photonics -- Periodicals; Imaging systems in medicine; Photonics; Optics and Photonics; Translational Medical Research; Periodicals; Periodical; 621.365
• DOI: 10.1002/tbio.201900008
• Languages: English
• ISSNs: 2627-1850

Abstract

Abstract: In vivo data acquisition using fiberoptic diffuse reflectance spectroscopy (DRS) is more complicated and less controlled compared to ex vivo data acquisition. It would be of great benefit if classifiers for in vivo tissue discrimination based on DRS could be trained on data obtained ex vivo. In this study, in vivo and ex vivo DRS measurements are obtained during colorectal cancer surgery. A mixed model statistical analysis is used to examine the differences between the two datasets. Furthermore, classifiers are trained and tested using in vivo and ex vivo data. It is found that with a classifier trained on ex vivo data and tested on in vivo data, similar results are obtained compared to a classifier trained and tested on in vivo data. In conclusion, under the conditions used in this study, classifiers intended for in vivo tissue discrimination can be trained on ex vivo data. Abstract : In vivo data acquisition using fiberoptic diffuse reflectance spectroscopy (DRS) is more complicated and less controlled compared to ex vivo data acquisition. In this study, in vivo and ex vivo DRS measurements are obtained during colorectal cancer surgery. A mixed model statistical analysis is used to examine the differences between the two datasets. Classifiers are trained and tested using in vivo and ex vivo data. It is found that with a classifier trained on ex vivo data and tested on in vivo data, similar results are obtained compared to a classifier trained and tested on in vivo data.