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Proceedings Paper

Endoscopic fluorescence lifetime imaging microscopy (FLIM) images of aortic plaque: an automated classification method
Author(s): Jennifer Phipps; Yinghua Sun; Nisa Hatami; Michael C. Fishbein; Amit Rajaram; Ramez Saroufeem; Laura Marcu
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Paper Abstract

The objective of this study was to develop an automated algorithm which uses fluorescence lifetime imaging microscopy (FLIM) images of human aortic atherosclerotic plaque to provide quantitative and spatial information regarding compositional features related to plaque vulnerability such as collagen degradation, lipid accumulation, and macrophage infiltration. Images were acquired through a flexible fiber imaging bundle with intravascular potential at two wavelength bands optimal to recognizing markers of vulnerability: F377: 377/55 nm and F460: 460/50 nm (center wavelength/bandwidth). A classification method implementing principal components analysis and linear discriminant analysis to correlate FLIM data sets with histopathology was validated on a training set and then used to classify a validation set of FLIM images. The output of this algorithm was a false-color image with each pixel color coded to represent the chemical composition of the sample. Surface areas occupied by elastin, collagen, and lipid components were then calculated and used to define the vulnerability of each imaged location. Four groups were defined: early lesion, stable, mildly vulnerable and extremely vulnerable. Each imaged location was categorized in one of the groups based on histopathology and classification results; sensitivities (SE) and specificities (SP) were calculated (SE %/SP %): early lesion: 95/96, stable: 71/97, mildly vulnerable: 75/94, and extremely vulnerable: 100/93. The capability of this algorithm to use FLIM images to quickly determine the chemical composition of atherosclerotic plaque, particularly related to vulnerability, further enhances the potential of this system for implementation as an intravascular diagnostic modality.

Paper Details

Date Published: 3 March 2010
PDF: 5 pages
Proc. SPIE 7548, Photonic Therapeutics and Diagnostics VI, 754839 (3 March 2010); doi: 10.1117/12.842724
Show Author Affiliations
Jennifer Phipps, Univ. of California, Davis (United States)
Yinghua Sun, Univ. of California, Davis (United States)
NSF Ctr. for Biophotonics, Univ. of California, Davis (United States)
Nisa Hatami, Univ. of California, Davis (United States)
Michael C. Fishbein, UCLA Ctr. for the Health Sciences, Univ. of California, Los Angeles (United States)
Amit Rajaram, UCLA Ctr. for the Health Sciences, Univ. of California, Los Angeles (United States)
Ramez Saroufeem, Univ. of California, Davis (United States)
Laura Marcu, Univ. of California, Davis (United States)
NSF Ctr. for Biophotonics, Univ. of California, Davis (United States)


Published in SPIE Proceedings Vol. 7548:
Photonic Therapeutics and Diagnostics VI
Anita Mahadevan-Jansen; Andreas Mandelis; Brian Jet-Fei Wong; Nikiforos Kollias; Henry Hirschberg; Kenton W. Gregory; Reza S. Malek; E. Duco Jansen; Guillermo J. Tearney; Steen J. Madsen; Bernard Choi; Justus F. R. Ilgner; Haishan Zeng; Laura Marcu, Editor(s)

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