Near-infrared Fourier transformed-Raman spectroscopy for laser angioplasty

Shuming Nie, Qiushi Ren, Douglas C.B. Redd, Spencer B. King, Nai Teng Yu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

To provide a database for various arterial tissues, near-infrared (NIR) Fourier-transform Raman spectra were collected in vitro from human arterial walks and atherosclerotic plaques (including calcified regions, noncalcified regions of varing morphology and color, and the plaque-covering tissues). Comparison with the Raman spectrum of pure animal fat reveals that the very intense and sharp line at 1439 cm-1 is the most prominent fat signal, which is far removed from the collagen signal at 1450 cm-1 and can be conveniently used for the purpose of tissue recognition. Moreover, the NIR Raman spectra carry information about the structure and chemical compositions of the various atherosclerotic deposits. For example, the intense 961-cm-1 line (apatite P-O stretching mode) indicates the status of tissue calcification and the presence of protein and collagen are reflected by Raman lines at ca. 1667, 1520, 1270, 1129, 1029, 880, 852, 700 and 426 cm-1.

Original languageEnglish (US)
Title of host publicationProceedings of the Annual Conference on Engineering in Medicine and Biology
PublisherPubl by IEEE
Pages1773-1774
Number of pages2
Editionpt 4
ISBN (Print)0780302168
StatePublished - 1991
Externally publishedYes
EventProceedings of the 13th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Orlando, FL, USA
Duration: Oct 31 1991Nov 3 1991

Publication series

NameProceedings of the Annual Conference on Engineering in Medicine and Biology
Numberpt 4
Volume13
ISSN (Print)0589-1019

Other

OtherProceedings of the 13th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
CityOrlando, FL, USA
Period10/31/9111/3/91

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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