title: Laguerre-based method for analysis of time-resolved fluorescence data: application to in-vivo characterization and diagnosis of atherosclerotic lesions.
abstract: 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.
authors: University of California-Davis, Department of Biomedical Engineering, Davis, California 95616, USA.
authors: Javier A
authors: JA
authors: Jo
authors: Qiyin
authors: Q
authors: Fang
authors: Thanassis
authors: T
authors: Papaioannou
authors: J Dennis
authors: JD
authors: Baker
authors: Amir H
authors: AH
authors: Dorafshar
authors: Todd
authors: T
authors: Reil
authors: Jian-Hua
authors: JH
authors: Qiao
authors: Michael C
authors: MC
authors: Fishbein
authors: Julie A
authors: JA
authors: Freischlag
authors: Laura
authors: L
authors: Marcu