Risultati scientifici

Non-linear imaging and characterization of atherosclerotic arterial tissue using combined SHG and FLIM microscopy

Anno: 2015

Autori: Cicchi R., Baria E., Matthäus C., Lange M., Lattermann A., Brehm BR., Popp J., Pavone FS.

Affiliazione autori: 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;
Leibniz Institute of Photonic Technology (IPHT-Jena), Albert Einstein Straße 9, 07745, Jena, Germany;
Institute of Biomedical Engineering and Nanotechnology, Ezermalas 6k, Riga, Latvia;
Institute of Pathology, Department of Neuropathology, Jena University Hospital, Friedrich Schiller University, Erlanger Allee 101, 07740 Jena, Germany;
Herz-Neuro-Zentrum Bodensee, Weinberg Strasse 1, 8280 Kreuzlingen, Switzerland,
Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich Schiller University Jena, Helmholtzweg 4, 07743 Jena, 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 one of the leading causes of death in the Western World and its characterization is extremely interesting from the diagnostic point of view. Here, we employed combined SHG-FLIM microscopy to characterize arterial tissue with atherosclerosis. The shorter mean fluorescence lifetime measured within plaque depositions (1260 ± 80 ps) with respect to normal arterial wall (1480 ± 100 ps) allowed discriminating collagen from lipids. SHG measurements and image analysis demonstrated that the normal arterial wall has a more anisotropic Aspect Ratio (0.37 ± 0.02) with respect to plaque depositions (0.61 ± 0.02) and that the correlation length can be used for discriminating collagen fibre bundles (2.0 ± 0.6 µm) from cholesterol depositions (4.1 ± 0.6 µm). The presented method has the potential to find place in a clinical setting as well as to be applied in vivo in the near future. Graphic composition of SHG and FLIM images representing normal arterial wall and plaque depositions. Atherosclerosis is among the most widespread cardiovascular diseases and its early diagnosis is crucial for avoiding life threatening consequences. Non-linear microscopy can diagnose tissues and atherosclerosis in a label-free modality, opening the way for a clinical use of these optical techniques. Combined SHG-FLIM microscopy is demonstrated to be extremely powerful for diagnosing and characterizing atherosclerosis.

Giornale/Rivista: JOURNAL OF BIOPHOTONICS

Volume: 8 (4)      Da Pagina: 347  A: 356

Maggiori informazioni: The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement number 284464, from the Italian Ministry for Education, University and Research in the framework of the Flagship Project NANOMAX, from Fondazione Pisa, from Italian Ministry of Health (GR2011-02349626), from Tuscany Region (EU-FP7-BiophotonicsPlus \”LITE\”) and from Ente Cassa di Risparmio di Firenze. Authors are grateful for support by the European network of excellence Photonics4Life (P4L).
Parole chiavi: Aspect ratio; Collagen; Diseases; Tissue, Arterial tissue; Atherosclerosis; Clinical settings; Collagen fibres; Correlation lengths; Fluorescence lifetimes; Graphic compositions; Nonlinear imaging, Deposition, collagen, animal; artery; atherosclerotic plaque; fluorescence imaging; image processing; metabolism; microscopy; pathology; procedures; rabbit, Animals; Arteries; Collagen; Image Processing, Computer-Assisted; Microscopy; Optical Imaging; Plaque, Atherosclerotic; Rabbits
DOI: 10.1002/jbio.201400142

Citazioni: 16
dati da “WEB OF SCIENCE” (of Thomson Reuters) aggiornati al: 2021-09-19
Riferimenti tratti da Isi Web of Knowledge: (solo abbonati)
Link per visualizzare la scheda su IsiWeb: Clicca qui
Link per visualizzare la citazioni su IsiWeb: Clicca qui

gdpr-image
This site uses cookies. If you decide to continue browsing we consider that you accept their use. For more information about cookies and how to delete them please read our Info Policy on cookies use.
Read more