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Proceedings Paper

Design and validation of an intraoperative autofluorescence lifetime imaging device
Author(s): Yong Hu; Andy S. Moon; Peter Pellionisz; Shan Huang; Oscar Stafsudd; Maie St. John
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Paper Abstract

As we know, fluorescence lifetime imaging has demonstrated the ability to accurately detect materials and tissue constituents1–3. Current fluorescence lifetime systems rely on accurate temporal sampling to capture the tails of the decaying emission. These data are often fit to an exponential decay model3,4. Although these methodologies are powerful tools but they are often implemented as point measurement systems and require significant postprocessing to compute decay times or coefficients5–8. In some applications these factors can hinder clinical translation. Based on these observations, our group has developed algorithms and built simple, fast, and wide field imaging system9,10. This method uses a gated charge-coupled device (CCD) and a liquid light cable guided LED to compare the decay-time image intensity vs excited state image intensity, thus generating a spatially resolved maps of relative differences in autofluorescence decay of tissue constituents. This approach ensures very fast updating speed (< 2 sec per frame), big field of view (20 mm x 20 mm), excellent depth of field (up to 6 mm) for surface curvature of interested target at reasonable working distance (~50 mm). This innovative imaging system has a temporal resolution of 0.16 nanosecond, spatial resolution of 70 μm and has proved the capability to differentiate visibly similar tissue types, which has been validated with both fluorescent dyes and ex vivo human tissue samples in comparison to commercially available FLIM microscope. This work establishes a foundation to confirm the utility of our upgraded DOCI system for intraoperative tissue differentiating/imaging. Validation with a larger number of samples is currently ongoing.

Paper Details

Date Published: 19 February 2020
PDF: 6 pages
Proc. SPIE 11213, Imaging, Therapeutics, and Advanced Technology in Head and Neck Surgery and Otolaryngology 2020, 1121309 (19 February 2020);
Show Author Affiliations
Yong Hu, Univ. of California, Los Angeles (United States)
Andy S. Moon, Univ. of California, Los Angeles (United States)
Peter Pellionisz, Univ. of California, Los Angeles (United States)
Shan Huang, Univ. of California, Los Angeles (United States)
Oscar Stafsudd, Univ. of California, Los Angeles (United States)
Maie St. John, Univ. of California, Los Angeles (United States)


Published in SPIE Proceedings Vol. 11213:
Imaging, Therapeutics, and Advanced Technology in Head and Neck Surgery and Otolaryngology 2020
Brian J. F. Wong M.D.; Justus F. Ilgner M.D., Editor(s)

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