title: Characterizing fibrosis in UUO mice model using multiparametric analysis of phasor distribution from FLIM images.
abstract: Phasor approach to fluorescence lifetime microscopy is used to study development of fibrosis in the unilateral ureteral obstruction model (UUO) of kidney in mice. Traditional phasor analysis has been modified to create a multiparametric analysis scheme that splits the phasor points in four equidistance segments based on the height of peak of the phasor distribution and calculates six parameters including average phasor positions, the shape of each segment, the angle of the distribution and the number of points in each segment. These parameters are used to create a spectrum of twenty four points specific to the phasor distribution of each sample. Comparisons of spectra from diseased and healthy tissues result in quantitative separation and calculation of statistical parameters including AUC values, positive prediction values and sensitivity. This is a new method in the evolving field of analyzing phasor distribution of FLIM data and provides further insights. Additionally, the progression of fibrosis with time is detected using this multiparametric approach to phasor analysis.
authors.affiliation: Laboratory Fluorescence Dynamics, Department of Biomedical Engineering, University of California, Irvine, CA, USA.
authors.forename: Suman
authors.initials: S
authors.lastname: Ranjit
authors.affiliation: Laboratory Fluorescence Dynamics, Department of Biomedical Engineering, University of California, Irvine, CA, USA.
authors.forename: Alexander
authors.initials: A
authors.lastname: Dvornikov
authors.affiliation: Departments of Medicine, University of Colorado-Anschutz Medical Campus, Aurora, Colorado, USA.
authors.forename: Moshe
authors.initials: M
authors.lastname: Levi
authors.affiliation: Departments of Medicine, University of Colorado-Anschutz Medical Campus, Aurora, Colorado, USA.
authors.forename: Seth
authors.initials: S
authors.lastname: Furgeson
authors.affiliation: Laboratory Fluorescence Dynamics, Department of Biomedical Engineering, University of California, Irvine, CA, USA.
authors.forename: Enrico
authors.initials: E
authors.lastname: Gratton
keywords: (100.0100) Image processing; (170.2520) Fluorescence microscopy; (170.3650) Lifetime-based sensing