Clinical translation of Raman-based multimodal spectral histopathology for margin assessment during surgery of basal cell carcinoma. / Boitor, Radu; Kong, Kenny; Varma, Sandeep; Koloydenko, Alexey; Williams, Hywel; Notingher, Ioan.

Proceedings SPIE, Medical Laser Applications and Laser-Tissue Interactions IX, 110790G . Vol. 11079 SPIE - INT SOC OPTICAL ENGINEERING, 2019. p. 1-4.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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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.
Original languageEnglish
Title of host publicationProceedings SPIE, Medical Laser Applications and Laser-Tissue Interactions IX, 110790G
PublisherSPIE - INT SOC OPTICAL ENGINEERING
Pages1-4
Number of pages4
Volume11079
DOIs
Publication statusPublished - 22 Jul 2019
This open access research output is licenced under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.

ID: 34336435