TY - JOUR
T1 - Toward complete oral cavity cancer resection using a handheld diffuse reflectance spectroscopy probe
AU - Brouwer de Koning, Susan G.
AU - Baltussen, Elisabeth J.M.
AU - Karakullukcu, M. Baris
AU - Dashtbozorg, Behdad
AU - Smit, Laura A.
AU - Dirven, Richard
AU - Hendriks, Benno H.W.
AU - Sterenborg, Henricus J.C.M.
AU - Ruers, Theo J.M.
PY - 2018/10/19
Y1 - 2018/10/19
N2 - This ex-vivo study evaluates the feasibility of diffuse reflectance spectroscopy (DRS) for discriminating tumor from healthy tissue, with the aim to develop a technology that can assess resection margins for the presence of tumor cells during oral cavity cancer surgery. Diffuse reflectance spectra were acquired on fresh surgical specimens from 28 patients with oral cavity squamous cell carcinoma. The spectra (400 to 1600 nm) were detected after illuminating tissue with a source fiber at 0.3-, 0.7-, 1.0-, and 2.0-mm distances from a detection fiber, obtaining spectral information from different sampling depths. The spectra were correlated with histopathology. A total of 76 spectra were obtained from tumor tissue and 110 spectra from healthy muscle tissue. The first- and second-order derivatives of the spectra were calculated and a classification algorithm was developed using fivefold cross validation with a linear support vector machine. The best results were obtained by the reflectance measured with a 1-mm source-detector distance (sensitivity, specificity, and accuracy are 89%, 82%, and 86%, respectively). DRS can accurately discriminate tumor from healthy tissue in an ex-vivo setting using a 1-mm source-detector distance. Accurate validation methods are warranted for larger sampling depths to allow for guidance during oral cavity cancer excision.
AB - This ex-vivo study evaluates the feasibility of diffuse reflectance spectroscopy (DRS) for discriminating tumor from healthy tissue, with the aim to develop a technology that can assess resection margins for the presence of tumor cells during oral cavity cancer surgery. Diffuse reflectance spectra were acquired on fresh surgical specimens from 28 patients with oral cavity squamous cell carcinoma. The spectra (400 to 1600 nm) were detected after illuminating tissue with a source fiber at 0.3-, 0.7-, 1.0-, and 2.0-mm distances from a detection fiber, obtaining spectral information from different sampling depths. The spectra were correlated with histopathology. A total of 76 spectra were obtained from tumor tissue and 110 spectra from healthy muscle tissue. The first- and second-order derivatives of the spectra were calculated and a classification algorithm was developed using fivefold cross validation with a linear support vector machine. The best results were obtained by the reflectance measured with a 1-mm source-detector distance (sensitivity, specificity, and accuracy are 89%, 82%, and 86%, respectively). DRS can accurately discriminate tumor from healthy tissue in an ex-vivo setting using a 1-mm source-detector distance. Accurate validation methods are warranted for larger sampling depths to allow for guidance during oral cavity cancer excision.
KW - Linear support vector machine
KW - Machine learning
KW - Oral cavity cancer
KW - Resection margin assessment
KW - Tissue recognition
KW - Diffuse reflectance spectroscopy
UR - http://www.scopus.com/inward/record.url?scp=85055078805&partnerID=8YFLogxK
U2 - 10.1117/1.JBO.23.12.121611
DO - 10.1117/1.JBO.23.12.121611
M3 - Article
C2 - 30341837
AN - SCOPUS:85055078805
SN - 1083-3668
VL - 23
SP - 1
EP - 8
JO - Journal of biomedical optics
JF - Journal of biomedical optics
IS - 12
M1 - 121611
ER -