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Integration of a Raman spectroscopy system to a robotic-assisted surgical system for real-time tissue characterization during radical prostatectomy procedures

Authors :
Frederick Dallaire
Michael Pinto
Kevin C. Zorn
Chris Kent
Eric Marple
Frédéric Lesage
Dominique Trudel
Frederic Leblond
Joannie Desroches
Kelly Aubertin
Jean-Philippe Tremblay
Source :
Journal of Biomedical Optics
Publication Year :
2019
Publisher :
Society of Photo-Optical Instrumentation Engineers, 2019.

Abstract

Surgical excision of the whole prostate through a radical prostatectomy procedure is part of the standard of care for prostate cancer. Positive surgical margins (cancer cells having spread into surrounding nonresected tissue) occur in as many as 1 in 5 cases and strongly correlate with disease recurrence and the requirement of adjuvant treatment. Margin assessment is currently only performed by pathologists hours to days following surgery and the integration of a real-time surgical readout would benefit current prostatectomy procedures. Raman spectroscopy is a promising technology to assess surgical margins: its in vivo use during radical prostatectomy could help insure the extent of resected prostate and cancerous tissue is maximized. We thus present the design and development of a dual excitation Raman spectroscopy system (680- and 785-nm excitations) integrated to the robotic da Vinci surgical platform for in vivo use. Following validation in phantoms, spectroscopic data from 20 whole human prostates immediately following radical prostatectomy are obtained using the system. With this dataset, we are able to distinguish prostate from extra prostatic tissue with an accuracy, sensitivity, and specificity of 91%, 90.5%, and 96%, respectively. Finally, the integrated Raman spectroscopy system is used to collect preliminary spectroscopic data at the surgical margin in vivo in four patients.

Details

Language :
English
ISSN :
15602281 and 10833668
Volume :
24
Issue :
2
Database :
OpenAIRE
Journal :
Journal of Biomedical Optics
Accession number :
edsair.doi.dedup.....600544338583761432ba383ed32da14e