Diffuse Reflectance Spectroscopy for Skin Tumor Margin Assessment

Author(s):  
Yao Zhang ◽  
Austin J. Moy ◽  
Xu Feng ◽  
Hieu T. M. Nguyen ◽  
Jason S. Reichenberg ◽  
...  
2021 ◽  
Vol 108 (Supplement_9) ◽  
Author(s):  
Scarlet Nazarian ◽  
Ioannis Gkouzionis ◽  
Michal Kawka ◽  
Nisha Patel ◽  
Ara Darzi ◽  
...  

Abstract Background Diffuse reflectance spectroscopy (DRS) is a technique that allows discrimination of normal and abnormal tissue based on spectral data. It is a promising technique for cancer margin assessment. However, application in a clinical setting is limited by the inability of DRS to mark the tissue that has been scanned and its lack of continuous real-time spectral measurements. This aim of this study was to develop a real-time tracking system to enable localisation of the tip of a handheld DRS probe to aid classification of tumour and non-tumour tissue. Methods A coloured marker was attached to the DRS fibre probe and was detected using colour segmentation. A Kalman filter was used to estimate the probe’s tip position during scanning of the tissue specimen. In this way, the system was robust to partial occlusion allowing real-time detection and tracking. Supervised classification algorithms were used for the discrimination between tumour and non-tumour tissue, and evaluated in terms of overall accuracy, sensitivity, specificity, and the area under the curve (AUC). A live augmented view with all the tracked and classified optical biopsy sites were presented, providing visual feedback to the surgeons. Results A green coloured marker was successfully used to track the DRS probe. The measured root mean square error of probe tip tracking was 1.18±0.58mm and 1.05±0.28mm for the X and Y directions, respectively, whilst the maximum measured error was 1.76mm. Overall, 47 distinct sets of tumour and non-tumour tissue data were recorded through real-time tracking of ex vivo oesophageal and gastric tissue. The overall diagnostic accuracy of the system to classify tumour and non-tumour tissue in real-time was 94% for stomach and 96% for the oesophagus. Conclusions We have been able to successfully develop a real-time tracking system for a DRS probe when used on stomach and oesophageal tissue for tumour detection, and the accuracy derived demonstrates the strength and clinical value of the technique. The method allows real-time tracking and classification with short data acquisition time to aid margin assessment in cancer resection surgery.


2014 ◽  
Vol 40 (11) ◽  
pp. S40
Author(s):  
L.L. De Boer ◽  
B.G. Molenkamp ◽  
J. Wesseling ◽  
B.H.W. Hendriks ◽  
T.M. Bydlon ◽  
...  

2014 ◽  
Vol 25 ◽  
pp. iv105 ◽  
Author(s):  
L.L. De Boer ◽  
B.G. Molenkamp ◽  
J. Wesseling ◽  
B.H.W. Hendriks ◽  
T.M. Bydlon ◽  
...  

2011 ◽  
Author(s):  
Alejandro Garcia-Uribe ◽  
Cheng-Chung Chang ◽  
Jun Zou ◽  
Bhaskar Banerjee ◽  
John Kuczynski ◽  
...  

2020 ◽  
Vol 2 (3) ◽  
Author(s):  
Yao Zhang ◽  
Austin J. Moy ◽  
Xu Feng ◽  
Hieu T. M. Nguyen ◽  
Katherine R. Sebastian ◽  
...  

Materials ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 7502
Author(s):  
Polina S. Tseregorodtseva ◽  
Kirill E. Buiankin ◽  
Boris P. Yakimov ◽  
Armais A. Kamalov ◽  
Gleb S. Budylin ◽  
...  

Diffuse reflectance spectroscopy (DRS) and imaging are increasingly being used in surgical guidance for tumor margin detection during endoscopic operations. However, the accuracy of the boundary detection with optical techniques may depend on the acquisition parameters, and its evaluation is in high demand. In this work, using optical phantoms with homogeneous and heterogeneous distribution of chromophores mimicking normal and pathological bladder tissues, the accuracy of tumor margin detection using single-fiber diffuse reflectance spectroscopy and spatial frequency domain imaging was evaluated. We also showed how the diffuse reflectance response obtained at different spatial frequencies with the spatial frequency domain imaging technique could be used not only to quantitatively map absorption and scattering coefficients of normal tissues and tumor-like heterogeneities but also to estimate the tumor depth localization. The demonstrated results could be helpful for proper analysis of the DRS data measured in vivo and for translation of optical techniques for tumor margin detection to clinics.


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