Characterization of collagen and cholesterol deposition in atherosclerotic arterial tissue using non-linear microscopy

Year: 2014

Authors: Cicchi R., Matthaeus C., Meyer T., Lattermann A., Dietzek B., Brehm B.R., Popp J., Pavone FS.

Autors Affiliation: National Institute of Optics, National Research Council (INO-CNR), Largo E. Fermi 6, 50125, Florence, Italy; European Laboratory for Non-linear Spectroscopy (LENS), Via Nello Carrara 1, 50019, Sesto Fiorentino, Italy; Institute of Photonic Technology (IPHT-Jena), Albert Einstein Straße 9, 07745 Jena, Germany; Institute of Pathology, Department of Neuropathology, Jena University Hospital, Friedrich Schiller University, Erlanger Allee 101, 07740 Jena, Germany; Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Helmholtzweg 4, 07743 Jena, Germany; Catholic Clinic – Koblenz, Internal Medicine & Cardiology, Rudolf Virchow Str. 9, 56073 Koblenz, Germany; Department of Physics, University of Florence, Via Giovanni Sansone 1, 50019, Sesto Fiorentino, Italy; International Center of Computational Neurophotonics (ICON), Via Nello Carrara 1, 50019, Florence, Italy

Abstract: Atherosclerosis is characterized by the accumulation of lipids within the arterial wall and is commonly diagnosed using standard histology. Non-linear microscopy represents a possible label-free alternative to standard diagnostic methods for imaging various tissue components. Here we employ SHG and CARS microscopy for imaging thin cross-sections of atherosclerotic arterial tissue, demonstrating that both cholesterol deposition in the lumen and collagen in the normal arterial wall can be imaged and discriminated using SHG and CARS microscopy. A simultaneous detection of both forward and backward scattered SHG signals allows distinguishing collagen fibres from cholesterol. Further analysis, based on image pattern evaluation algorithms, is used to characterize collagen organization in the healthy arterial wall against collagen found within plaques. Different values of fibre mean size, distribution and anisotropy are calculated for lumen and media prospectively allowing for automated classification of atherosclerotic lesions. The presented method represents a promising diagnostic tool for evaluating atherosclerotic tissue. ((c) 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)


Volume: 7 (1-2)      Pages from: 135  to: 143

More Information: The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreements number 228334 and 284464, and from the Italian Ministry for Education, University and Research in the framework of the Flagship Project NANOMAX. Furthermore, financial support by the Ente Cassa di Risparmio di Firenze (private foundation) is acknowledged. We are grateful for support by the European network of excellence Photonics4Life (P4L).
KeyWords: Atherosclerosis; Atherosclerotic lesions; Automated classification; Collagen organizations; Diagnostic methods; Forward-and-backward; Nonlinear microscopy; Simultaneous detection, Cholesterol; Coherent scattering; Collagen; Deposition; Diseases; Image analysis, Tissue, cholesterol; collagen, animal; artery; article; atherosclerosis; image analysis; image processing; male; metabolism; methodology; microscopy; nonlinear system; pathology; rabbit; Raman spectrometry; SHG microscopy, atherosclerosis; image analysis; SHG microscopy, Animals; Arteries; Atherosclerosis; Cholesterol; Collagen; Image Processing, Computer-Assisted; Male; Microscopy; Nonlinear Dynamics; Rabbits; Spectrum Analysis, Raman
DOI: 10.1002/jbio.201300055

Citations: 50
data from “WEB OF SCIENCE” (of Thomson Reuters) are update at: 2024-04-14
References taken from IsiWeb of Knowledge: (subscribers only)
Connecting to view paper tab on IsiWeb: Click here
Connecting to view citations from IsiWeb: Click here