Reduction of Influence of Decrease in Signal-to-Noise Ratio in Measurement of Change in Thickness of Arterial Wall Due to Heartbeat

To diagnose early-stage atherosclerosis, for the local evaluation of the elasticity of the arterial wall it is necessary to increase the spatial resolution in the axial direction of the artery to several millimeters, which corresponds to the size of the lesion on the surface of the arterial wall. Fo...

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Bibliographic Details
Published in:JPN J APPL PHYS PART 1 REGUL PAP SHORT NOTE REV PAP 2000, Vol.39 (5S), p.3257-3261
Main Authors: Hasegawa, Hideyuki, Kanai, Hiroshi, Hoshimiya, Nozomu, Koiwa, Yoshiro
Format: Article
Language:English
Subjects:
Blood vessels
Computer simulation
Diseases
Medical imaging
Modal analysis
Optimization
Signal to noise ratio
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Summary:To diagnose early-stage atherosclerosis, for the local evaluation of the elasticity of the arterial wall it is necessary to increase the spatial resolution in the axial direction of the artery to several millimeters, which corresponds to the size of the lesion on the surface of the arterial wall. For this purpose, we previously proposed a method for measuring the small change in thickness of the arterial wall during the cardiac cycle [H. Kanai et al. .: IEEE Trans. UFFC 43 (1996) 791, H. Kanai et al. .: IEEE Trans. UFFC 44 (1997) 752 and H. Hasegawa et al. .: Electron. Lett. 33 (1997) 340]. The change in thickness cannot be measured from conventional B-mode or M-mode images because of its small amplitude of less than 100 micrometers. Though the change in thickness is useful for in vivo assessment of the local elasticity of the arterial wall, in some cases successful measurements based on only two consecutive echos fail because of the low signal-to-noise ratio (SNR) of the echos. To realize the practical use of the proposed method, this problem must be overcome. In this paper, we propose a method that is more robust in the presence of noise. In this method, more than two echos are employed to estimate their phase shift for reducing the influence of low SNR. Simulations provide an optimal value of the estimation period for each SNR. By evaluating the SNR of in vivo experimental data, the optimal estimation period is determined. In in vivo experiments using an optimal estimation period of 20 ms, the change in thickness can be measured with good reproducibility even in the case of a low SNR of 28 dB.
ISSN:0021-4922
1347-4065
DOI:10.1143/JJAP.39.3257