TY - JOUR
T1 - Diffuse reflectance spectroscopy as a tool for real-time tissue assessment during colorectal cancer surgery
AU - Baltussen, Elisabeth J.M.
AU - Snaebjornsson, Petur
AU - De Koning, Susan G.Brouwer
AU - Sterenborg, Henricus J.C.M.
AU - Aalbers, Arend G.J.
AU - Kok, Niels
AU - Beets, Geerard L.
AU - Hendriks, Benno H.W.
AU - Kuhlmann, Koert F.D.
AU - Ruers, Theo J.M.
PY - 2017
Y1 - 2017
N2 - Colorectal surgery is the standard treatment for patients with colorectal cancer. To overcome two of the main challenges, the circumferential resection margin and postoperative complications, real-time tissue assessment could be of great benefit during surgery. In this ex vivo study, diffuse reflectance spectroscopy (DRS) was used to differentiate tumor tissue from healthy surrounding tissues in patients with colorectal neoplasia. DRS spectra were obtained from tumor tissue, healthy colon, or rectal wall and fat tissue, for every patient. Data were randomly divided into training (80%) and test (20%) sets. After spectral band selection, the spectra were classified using a quadratic classifier and a linear support vector machine. Of the 38 included patients, 36 had colorectal cancer and 2 had an adenoma. When the classifiers were applied to the test set, colorectal cancer could be discriminated from healthy tissue with an overall accuracy of 0.95 (±0.03). This study demonstrates the possibility to separate colorectal cancer from healthy surrounding tissue by applying DRS. High classification accuracies were obtained both in homogeneous and inhomogeneous tissues. This is a fundamental step toward the development of a tool for real-time in vivo tissue assessment during colorectal surgery.
AB - Colorectal surgery is the standard treatment for patients with colorectal cancer. To overcome two of the main challenges, the circumferential resection margin and postoperative complications, real-time tissue assessment could be of great benefit during surgery. In this ex vivo study, diffuse reflectance spectroscopy (DRS) was used to differentiate tumor tissue from healthy surrounding tissues in patients with colorectal neoplasia. DRS spectra were obtained from tumor tissue, healthy colon, or rectal wall and fat tissue, for every patient. Data were randomly divided into training (80%) and test (20%) sets. After spectral band selection, the spectra were classified using a quadratic classifier and a linear support vector machine. Of the 38 included patients, 36 had colorectal cancer and 2 had an adenoma. When the classifiers were applied to the test set, colorectal cancer could be discriminated from healthy tissue with an overall accuracy of 0.95 (±0.03). This study demonstrates the possibility to separate colorectal cancer from healthy surrounding tissue by applying DRS. High classification accuracies were obtained both in homogeneous and inhomogeneous tissues. This is a fundamental step toward the development of a tool for real-time in vivo tissue assessment during colorectal surgery.
KW - colorectal cancer
KW - diffuse reflectance spectroscopy
KW - machine learning
KW - margin assessment
KW - support vector machine
UR - http://resolver.tudelft.nl/uuid:b23e1211-18b7-43c1-9b0c-c9316d22c768
UR - http://www.scopus.com/inward/record.url?scp=85032908831&partnerID=8YFLogxK
U2 - 10.1117/1.JBO.22.10.106014
DO - 10.1117/1.JBO.22.10.106014
M3 - Article
AN - SCOPUS:85032908831
VL - 22
JO - Journal of Biomedical Optics
JF - Journal of Biomedical Optics
SN - 1083-3668
IS - 10
M1 - 106014
ER -