Special Section on Cardiovascular Photonics

Laguerre-based method for analysis of time-resolved fluorescence data: application to in-vivo characterization and diagnosis of atherosclerotic lesions

[+] Author Affiliations
Javier A. Jo

University of California — Davis, Department of Biomedical Engineering, Davis, California 95616

Qiyin Fang

McMaster University, Department of Engineering Physics, Hamilton, Ontario, Canada

Thanassis Papaioannou

Cedars-Sinai Medical Center, Department of Surgery, Los Angeles, California

J. Dennis Baker, Amir H. Dorafshar, Todd Reil

University of California Los Angeles, David Geffen School of Medicine, Department of Vascular Surgery, Los Angeles, California

Jian-Hua Qiao, Michael C. Fishbein

University of California Los Angeles, David Geffen School of Medicine, Department of Pathology and Laboratory Medicine, Los Angeles, California

Julie A. Freischlag

Johns Hopkins University, School of Medicine, Baltimore, Maryland

Laura Marcu

University of California — Davis, Department of Biomedical Engineering, Davis, California 95616

J. Biomed. Opt. 11(2), 021004 (March 27, 2006). doi:10.1117/1.2186045
History: Received July 18, 2005; Revised December 01, 2005; Accepted December 01, 2005; Published March 27, 2006
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We report the application of the Laguerre deconvolution technique (LDT) to the analysis of in-vivo time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) data and the diagnosis of atherosclerotic plaques. TR-LIFS measurements were obtained in vivo from normal and atherosclerotic aortas (eight rabbits, 73 areas), and subsequently analyzed using LDT. Spectral and time-resolved features were used to develop four classification algorithms: linear discriminant analysis (LDA), stepwise LDA (SLDA), principal component analysis (PCA), and artificial neural network (ANN). Accurate deconvolution of TR-LIFS in-vivo measurements from normal and atherosclerotic arteries was provided by LDT. The derived Laguerre expansion coefficients reflected changes in the arterial biochemical composition, and provided a means to discriminate lesions rich in macrophages with high sensitivity (>85%) and specificity (>95%). Classification algorithms (SLDA and PCA) using a selected number of features with maximum discriminating power provided the best performance. This study demonstrates the potential of the LDT for in-vivo tissue diagnosis, and specifically for the detection of macrophages infiltration in atherosclerotic lesions, a key marker of plaque vulnerability.

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© 2006 Society of Photo-Optical Instrumentation Engineers

Citation

Javier A. Jo ; Qiyin Fang ; Thanassis Papaioannou ; J. Dennis Baker ; Amir H. Dorafshar, et al.
"Laguerre-based method for analysis of time-resolved fluorescence data: application to in-vivo characterization and diagnosis of atherosclerotic lesions", J. Biomed. Opt. 11(2), 021004 (March 27, 2006). ; http://dx.doi.org/10.1117/1.2186045


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