Paper
22 July 2019 Clinical translation of Raman-based multimodal spectral histopathology for margin assessment during surgery of basal cell carcinoma
Radu Boitor, Kenny Kong, Sandeep Varma, Alexey Koloydenko, Hywel C. Williams, Ioan Notingher
Author Affiliations +
Abstract
Basal cell carcinoma (BCC) is the most common type of cancer in the world. The very high incidence of this type of cancer has given rise to an increase in the number of new prospective treatment procedures. Previously we have described a fully automated multimodal instrument that combines autofluorescence microscopy with Raman spectroscopy for the investigation of the entire resection margins for surgically removed skin tissue samples. This multimodal spectral histopathology (MSH) instrument is capable of investigating surgical resection margins in 30 minutes, which is compatible with Mohs micrographic surgery (MMS). The instrument was first developed and optimized on spare frozen skin tissue samples obtained during MMS [1]. Here we present initial results using this MSH instrument when operated in a typical Mohs surgery clinic, using the real resected tissue. After MSH analysis, the samples were processed for frozen section histopathology, which was used to validate the MSH results. The paper aims to present the difficulties that are encountered during the implementation of the instrument into clinical practice. The operating procedure has been successfully adapted to perform measurements of fresh tissue samples intra-operatively, with an improved accuracy over frozen tissue samples.
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Radu Boitor, Kenny Kong, Sandeep Varma, Alexey Koloydenko, Hywel C. Williams, and Ioan Notingher "Clinical translation of Raman-based multimodal spectral histopathology for margin assessment during surgery of basal cell carcinoma", Proc. SPIE 11079, Medical Laser Applications and Laser-Tissue Interactions IX, 110790G (22 July 2019); https://doi.org/10.1117/12.2526806
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KEYWORDS
Tissues

Blood

Image segmentation

Raman spectroscopy

Surgery

Statistical modeling

Algorithm development

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