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J Am Coll Cardiol, 2005; 45:1954-1960, doi:10.1016/j.jacc.2004.10.080 © 2005 by the American College of Cardiology Foundation |
Division of Cardiovascular Medicine, Department of Medical Bioregulation, Yamaguchi University Graduate School of Medicine, Yamaguchi, Japan
Manuscript received June 13, 2004; revised manuscript received October 19, 2004, accepted October 25, 2004.
* Reprint requests and correspondence: Dr. Takafumi Hiro, Division of Cardiovascular Medicine, The Department of Medical Bioregulation, Yamaguchi University Graduate School of Medicine, 1-1-1 Minami Kogushi, Ube, Yamaguchi 755-8505, Japan (Email: thiro{at}yamaguchi-u.ac.jp).
This study was presented in part at the 75th scientific sessions of the American Heart Association, Chicago, Illinois, 2002. Drs. Murashige and Hiro contributed equally to this work.
OBJECTIVES: This study examined the feasibility of using a wavelet analysis of radiofrequency (RF) intravascular ultrasound (IVUS) signals in detecting lipid-laden plaque.
BACKGROUND: Wavelet analysis is a new mathematical model for assessing local changes in a geometrical profile of time-series signals.
METHODS: Radiofrequency IVUS signals of 85 arbitrarily selected vectors were acquired from 27 formalin-fixed noncalcified atherosclerotic plaques from human necropsy with a digitizer at 500 MHz with 8-bit resolution by use of a 40-MHz IVUS catheter. Wavelet analysis of these RF signals was performed using a Daubechies-2 wavelet to obtain a color-coded map of the correlation coefficient with the wavelet reconstructed over the x-y plane of the wavelet scale and the distance from the IVUS catheter. The plaque segment was then examined histologically after being stained with Massons trichrome stain. This technique also was applied in vivo in 29 human coronary plaque segments. These segments were excised subsequently by directional coronary atherectomy and processed for histologic analysis.
RESULTS: In the in vitro study, histologic examination revealed lipid-laden segments in 29 vectors. When performing a wavelet analysis with the Daubechies-2 wavelet, the color-coded mapping revealed a different pattern in lipid-laden plaques compared with other types of plaque. Using this wavelet analysis, lipid-laden plaque could be detected with a sensitivity of 83% (24 of 29) and a specificity of 82% (46 of 56). In the in vivo study, fatty plaque could be detected with a sensitivity of 81% (13 of 16) and a specificity of 85% (11 of 13) with this method.
CONCLUSIONS: Wavelet analysis of RF IVUS signals enabled in vitro as well as in vivo detection of lipid-laden plaque. This method may be useful in assessing plaque vulnerability in patients with coronary artery disease.
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