Publications

@article{doi:10.1002/lsm.23161b,
title = {Toward assessment of resection margins using hyperspectral diffuse reflection imaging (400–1,700 nm) during tongue cancer surgery},
author = { Susan G. Brouwer de Koning and Pim Weijtmans and M. Baris Karakullukcu and Caifeng Shan and Elisabeth J. M. Baltussen and Laura A. Smit and Robert L. P. van Veen and Benno H. W. Hendriks and Henricus J. C. M. Sterenborg and Theo J. M. Ruers},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/lsm.23161},
doi = {10.1002/lsm.23161},
year = {2019},
date = {2019-09-24},
journal = {Lasers in Surgery and Medicine},
volume = {0},
number = {0},
abstract = {Background and Objectives There is a clinical need to assess the resection margins of tongue cancer specimens, intraoperatively. In the current ex vivo study, we evaluated the feasibility of hyperspectral diffuse reflectance imaging (HSI) for distinguishing tumor from the healthy tongue tissue. Study Design/Materials and Methods Fresh surgical specimens (n = 14) of squamous cell carcinoma of the tongue were scanned with two hyperspectral cameras that cover the visible and near-infrared spectrum (400–1,700 nm). Each pixel of the hyperspectral image represents a measure of the diffuse optical reflectance. A neural network was used for tissue-type prediction of the hyperspectral images of the visual and near-infrared data sets separately as well as both data sets combined. Results HSI was able to distinguish tumor from muscle with a good accuracy. The diagnostic performance of both wavelength ranges (sensitivity/specificity of visual and near-infrared were 84%/80% and 77%/77%, respectively) appears to be comparable and there is no additional benefit of combining the two wavelength ranges (sensitivity and specificity were 83%/76%). Conclusions HSI has a strong potential for intra-operative assessment of tumor resection margins of squamous cell carcinoma of the tongue. This may optimize surgery, as the entire resection surface can be scanned in a single run and the results can be readily available. Lasers Surg. Med. © 2019 Wiley Periodicals, Inc.},
keywords = {deep learning, Hyperspectral imaging, resection margin assessment, tissue recognition, tongue cancer},
pubstate = {published},
tppubtype = {article}
}

@article{Li2019,
title = {Hyperspectral imaging for resection margin assessment during cancer surgery},
author = {Kho E and de Boer LL and Van de Vijver K and van Duijnhoven F and Vrancken Peeters MTFD and Sterenborg HJCM and Ruers TJ},
url = {http://clincancerres.aacrjournals.org/content/early/2019/03/16/1078-0432.CCR-18-2089},
doi = {10.1158/1078-0432.CCR-18-2089},
year = {2019},
date = {2019-03-01},
journal = {Clinical Cancer Research},
keywords = {cancer, Hyperspectral imaging, resection margin assessment, surgery},
pubstate = {published},
tppubtype = {article}
}

@article{doi:10.1002/lsm.23161,
title = {Toward assessment of resection margins using hyperspectral diffuse reflection imaging (400–1,700 nm) during tongue cancer surgery},
author = {Susan G Brouwer de Koning and Pim Weijtmans and Baris M Karakullukcu and Caifeng Shan and Elisabeth J M Baltussen and Laura A Smit and Robert L P van Veen and Benno H W Hendriks and Henricus J C M Sterenborg and Theo J M Ruers},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/lsm.23161},
doi = {10.1002/lsm.23161},
journal = {Lasers in Surgery and Medicine},
volume = {0},
number = {0},
abstract = {Background and Objectives There is a clinical need to assess the resection margins of tongue cancer specimens, intraoperatively. In the current ex vivo study, we evaluated the feasibility of hyperspectral diffuse reflectance imaging (HSI) for distinguishing tumor from the healthy tongue tissue. Study Design/Materials and Methods Fresh surgical specimens (n = 14) of squamous cell carcinoma of the tongue were scanned with two hyperspectral cameras that cover the visible and near-infrared spectrum (400–1,700 nm). Each pixel of the hyperspectral image represents a measure of the diffuse optical reflectance. A neural network was used for tissue-type prediction of the hyperspectral images of the visual and near-infrared data sets separately as well as both data sets combined. Results HSI was able to distinguish tumor from muscle with a good accuracy. The diagnostic performance of both wavelength ranges (sensitivity/specificity of visual and near-infrared were 84%/80% and 77%/77%, respectively) appears to be comparable and there is no additional benefit of combining the two wavelength ranges (sensitivity and specificity were 83%/76%). Conclusions HSI has a strong potential for intra-operative assessment of tumor resection margins of squamous cell carcinoma of the tongue. This may optimize surgery, as the entire resection surface can be scanned in a single run and the results can be readily available. Lasers Surg. Med. © 2019 Wiley Periodicals, Inc.},
keywords = {deep learning, Hyperspectral imaging, resection margin assessment, tissue recognition, tongue cancer},
pubstate = {published},
tppubtype = {article}
}