Towards the use of diffuse reflectance spectroscopy for real-time in vivo detection of breast cancer during surgery |
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Authors: | Lisanne L. de Boer Torre M. Bydlon Frederieke van Duijnhoven Marie-Jeanne T. F. D. Vranken Peeters Claudette E. Loo Gonneke A. O. Winter-Warnars Joyce Sanders Henricus J. C. M. Sterenborg Benno H. W. Hendriks Theo J. M. Ruers |
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Affiliation: | 1.Department of Surgery,the Netherlands Cancer Institute–Antoni van Leeuwenhoek,Amsterdam,The Netherlands;2.In-body Systems, Philips Research, High Tech,Eindhoven,The Netherlands;3.Department of Radiology,the Netherlands Cancer Institute–Antoni van Leeuwenhoek,Amsterdam,The Netherlands;4.Department of Pathology,the Netherlands Cancer Institute–Antoni van Leeuwenhoek,Amsterdam,The Netherlands;5.Biomedical Engineering and Physics, Amsterdam UMC,University of Amsterdam,Amsterdam,The Netherlands;6.Biomechanical Engineering,Delft University of Technology,Delft,The Netherlands;7.Technical Medical Centre,University of Twente,Enschede,The Netherlands |
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Abstract: |
BackgroundBreast cancer surgeons struggle with differentiating healthy tissue from cancer at the resection margin during surgery. We report on the feasibility of using diffuse reflectance spectroscopy (DRS) for real-time in vivo tissue characterization.MethodsEvaluating feasibility of the technology requires a setting in which measurements, imaging and pathology have the best possible correlation. For this purpose an optical biopsy needle was used that had integrated optical fibers at the tip of the needle. This approach enabled the best possible correlation between optical measurement volume and tissue histology. With this optical biopsy needle we acquired real-time DRS data of normal tissue and tumor tissue in 27 patients that underwent an ultrasound guided breast biopsy procedure. Five additional patients were measured in continuous mode in which we obtained DRS measurements along the entire biopsy needle trajectory. We developed and compared three different support vector machine based classification models to classify the DRS measurements.ResultsWith DRS malignant tissue could be discriminated from healthy tissue. The classification model that was based on eight selected wavelengths had the highest accuracy and Matthews Correlation Coefficient (MCC) of 0.93 and 0.87, respectively. In three patients that were measured in continuous mode and had malignant tissue in their biopsy specimen, a clear transition was seen in the classified DRS measurements going from healthy tissue to tumor tissue. This transition was not seen in the other two continuously measured patients that had benign tissue in their biopsy specimen.ConclusionsIt was concluded that DRS is feasible for integration in a surgical tool that could assist the breast surgeon in detecting positive resection margins during breast surgery. Trail registration NIH US National Library of Medicine–clinicaltrails.gov, NCT01730365. Registered: 10/04/2012 https://clinicaltrials.gov/ct2/show/study/NCT01730365 |
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