82. Margin assessment in breast cancer lumpectomy specimens with infra-red diffuse reflectance spectroscopy (DRS)

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 ◽  
...  

2003 ◽  
Vol 50 (11) ◽  
pp. 1233-1242 ◽  
Author(s):  
G.M. Palmer ◽  
Changfang Zhu ◽  
T.M. Breslin ◽  
Fushen Xu ◽  
K.W. Gilchrist ◽  
...  

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.


2012 ◽  
Vol 137 (1) ◽  
pp. 155-165 ◽  
Author(s):  
Daniel J. Evers ◽  
Rami Nachabe ◽  
Marie-Jeanne Vranken Peeters ◽  
Jos A. van der Hage ◽  
Hester S. Oldenburg ◽  
...  

2008 ◽  
Vol 13 (2) ◽  
pp. 024012 ◽  
Author(s):  
Zoya Volynskaya ◽  
Abigail S. Haka ◽  
Kate L. Bechtel ◽  
Maryann Fitzmaurice ◽  
Robert Shenk ◽  
...  

2012 ◽  
Vol 23 ◽  
pp. ix532
Author(s):  
T.J.M. Ruers ◽  
D. Evers ◽  
R. Nachabé ◽  
M.J. Vranken Peeters ◽  
J. van der Hage ◽  
...  

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