| Research Abstract |
Decreases of myocardial motion caused by changes in tissue stiffness often appear in the early stage of ischemic heart disease. Since the myocardium exhibits complex 3-D motion, 3-D assessment of the stiffness distribution is required for accurate diagnosis. However, conventional tissue Doppler and strain-rate imaging techniques cannot meet the above requirement completely because they are angle-dependent and in-plane (2-D) processing, and have the aliasing issue for large myocardial motion.
In order to overcome these problems, we propose novel methods to track the 3-D motion by using a 2-D phased array with a small aperture and to assess myocardial malfunction based on full strain tensors obtained by 3-D motion analysis. As a new method of 3-D myocardial motion tracking, we incorporated our phase-gradient method, which is capable of real-time 3-D displacement vector measurement based on the phase shifts obtained at each element on a 2-D phased array, and our combined autocorrelation me
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thod, which accurately measures large phase shifts at each element without aliasing. As a new method of assessing myocardial tissue stiffness, the full strain tensor invariant obtained by the measured 3-D vectors is visualized as a strain invariant image. Since strain tensor invariants are independent of the coordinate system, visual axis and beam direction, valid myocardial stiffness can be assessed independently of incident angle.
We evaluated the feasibilities of the proposed methods by numerically simulating the left ventricle short-axis imaging of a 3-D elliptic myocardial model. This model includes a hard infarction, located between 1 and 3 o'clock, where it is difficult to detect by, conventional tissue Doppler and strain-rate imaging. RF signals received at each element on the 2-D array probe were faithfully simulated by convoluting the PSF and the scatter coefficients in the model. When the simulated echoes were processed by the proposed methods, the invariant image obtained by the full strain tensor clearly depicted the hard infarction area where conventional imaging could not. Less
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