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Proceedings Paper

Autofluorescence lifetime imaging during transoral robotic surgery: a clinical validation study of tumor detection (Conference Presentation)
Author(s): João L. Lagarto; Jennifer E. Phipps; Jakob Unger; Leta M. Faller; Dimitris Gorpas; Dinglong M. Ma; Julien Bec; Michael G. Moore; Arnaud F. Bewley; Diego R. Yankelevich; Jonathan M. Sorger; Gregory D. Farwell; Laura Marcu
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Paper Abstract

Autofluorescence lifetime spectroscopy is a promising non-invasive label-free tool for characterization of biological tissues and shows potential to report structural and biochemical alterations in tissue owing to pathological transformations. In particular, when combined with fiber-optic based instruments, autofluorescence lifetime measurements can enhance intraoperative diagnosis and provide guidance in surgical procedures. We investigate the potential of a fiber-optic based multi-spectral time-resolved fluorescence spectroscopy instrument to characterize the autofluorescence fingerprint associated with histologic, morphologic and metabolic changes in tissue that can provide real-time contrast between healthy and tumor regions in vivo and guide clinicians during resection of diseased areas during transoral robotic surgery. To provide immediate feedback to the surgeons, we employ tracking of an aiming beam that co-registers our point measurements with the robot camera images and allows visualization of the surgical area augmented with autofluorescence lifetime data in the surgeon’s console in real-time. For each patient, autofluorescence lifetime measurements were acquired from normal, diseased and surgically altered tissue, both in vivo (pre- and post-resection) and ex vivo. Initial results indicate tumor and normal regions can be distinguished based on changes in lifetime parameters measured in vivo, when the tumor is located superficially. In particular, results show that autofluorescence lifetime of tumor is shorter than that of normal tissue (p < 0.05, n = 3). If clinical diagnostic efficacy is demonstrated throughout this on-going study, we believe that this method has the potential to become a valuable tool for real-time intraoperative diagnosis and guidance during transoral robot assisted cancer removal interventions.

Paper Details

Date Published: 19 April 2017
PDF: 1 pages
Proc. SPIE 10039, Optical Imaging, Therapeutics, and Advanced Technology in Head and Neck Surgery and Otolaryngology, 100390E (19 April 2017); doi: 10.1117/12.2253226
Show Author Affiliations
João L. Lagarto, Univ. of California, Davis (United States)
Jennifer E. Phipps, Univ. of California, Davis (United States)
Jakob Unger, Univ. of California, Davis (United States)
Leta M. Faller, Univ. of California, Davis (United States)
Dimitris Gorpas, Univ. of California, Davis (United States)
Dinglong M. Ma, Univ. of California, Davis (United States)
Julien Bec, Univ. of California, Davis (United States)
Michael G. Moore, UC Davis Health System (United States)
Arnaud F. Bewley, UC Davis Health System (United States)
Diego R. Yankelevich, Univ. of California, Davis (United States)
Jonathan M. Sorger, Intuitive Surgical, Inc. (United States)
Gregory D. Farwell, UC Davis Health System (United States)
Laura Marcu, Univ. of California, Davis (United States)


Published in SPIE Proceedings Vol. 10039:
Optical Imaging, Therapeutics, and Advanced Technology in Head and Neck Surgery and Otolaryngology
Brian J. F. Wong; Justus F. Ilgner; Krzysztof Izdebski, Editor(s)

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