Characterization of human arterial tissue affected by atherosclerosis using multimodal nonlinear optical microscopy
Authors: Baria E., Cicchi R., Rotellini M., Nesi G., Massi D., Pavone F.S.
Autors Affiliation: European Laboratory for Non-Linear Spectroscopy (LENS), University of Florence, Via Nello Carrara, 1, Sesto Fiorentino, 50019, Italy; National Institute of Optics, National Research Council (INO-CNR), Largo E. Fermi 6, Florence, 50125, Italy; Division of Pathology, Department of Surgery and Translational Medicine, University of Florence, Viale Morgagni, Italy; Department of Physics, University of Florence, Via Giovanni Sansone 1, Sesto Fiorentino, 50019, Italy
Abstract: Atherosclerosis is a widespread cardiovascular disease caused by the deposition of lipids (such as cholesterol and triglycerides) on the inner arterial wall. The rupture of an atherosclerotic plaque, resulting in a thrombus, is one of the leading causes of death in the Western World. Preventive assessment of plaque vulnerability is therefore extremely important and can be performed by studying collagen organization and lipid composition in atherosclerotic arterial tissues. Routinely used diagnostic methods, such as histopathological examination, are limited to morphological analysis of the examined tissues, whereas an exhaustive characterization requires immune-histochemical examination and a morpho-functional approach. Instead, a label-free and non-invasive alternative is provided by nonlinear microscopy. In this study, we combined SHG and FLIM microscopy in order to characterize collagen organization and lipids in human carotid ex vivo tissues affected by atherosclerosis. SHG and TPF images, acquired from different regions within atherosclerotic plaques, were processed through image pattern analysis methods (FFT, GLCM). The resulting information on collagen and cholesterol distribution and anisotropy, combined with collagen and lipids fluorescence lifetime measured from FLIM images, allowed characterization of carotid samples and discrimination of different tissue regions. The presented method can be applied for automated classification of atherosclerotic lesions and plaque vulnerability. Moreover, it lays the foundation for a potential in vivo diagnostic tool to be used in clinical setting.
KeyWords: Biophysics; Characterization; Cholesterol; Collagen; Diagnosis; Diseases; Fast Fourier transforms; Histology; Lipids; Nonlinear optics, atherosclerosis; Automated classification; Cardio-vascular disease; FLIM; GLCM; Histopathological examinations; Multimodal nonlinear optical microscopies; Nonlinear microscopy, Tissue