Theoretical derivation of SNR, CNR and spatial resolution for a local adaptive strain estimator for elastography

Conventional techniques in elastography estimate the axial strain as the gradient of the displacement (time-delay) estimates obtained using cross-correlation of pre- and temporally stretched postcompression radiofrequency (RF) A-line segments. The use of a constant stretch factor for stretching the postcompression A-line is not adequate in the presence of heterogeneous targets that are commonly encountered. This led to the development of several adaptive strain estimation techniques in elastography. Yet, a theoretical framework for the image quality of adaptive strain estimation has not been established. In this work, we develop theoretical expressions for the image quality [measured in terms of the signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and spatial resolution] of elastograms obtained using an adaptive strain estimator developed by Alam et al. (1998). We show a linear trade-off between the SNR and axial resolution of the strain elastogram with respect to the window length used for strain estimation. The CNR shows a quadratic tradeoff with the axial resolution with respect to the window length. The SNR, CNR and axial resolution are shown to improve with the ultrasonic bandwidth.     

Estimating the elastographic signal-to-noise ratio using correlation coefficients

In conventional elastography, strain is estimated from the gradient of the displacement (time-delay) estimates. The displacement estimates involve estimating the peak location of the cross-correlation function between matching pre- and post-compression A-lines. Bias errors in estimating the peak location of the cross-correlation function, amplified by the gradient operation on the displacement estimates (needed for the computation of the strain), could result in values of elastographic signal-to-noise ratio (SNR(e)) that exceed the theoretical upper bounds, thereby hindering a consistent interpretation of this parameter. These algorithmic errors have not been accounted for by the theory. We propose the use of the measured correlation coefficients in the theoretical SNR(e) expressions to estimate the SNR(e), rather than computing them directly from the elastograms. This methodology results in values of SNR(e) that are lower than the theoretical upper bounds, thereby avoiding the problems associated with computing SNR(e) directly from the elastograms. Using simulated models of uniformly elastic phantoms, a proof of principle of such an SNR(e) measure is shown.     

Estimating axial and lateral strain using a synthetic aperture elastographic imaging system

Model-based elastography is an emerging technique with clinical applications in imaging vascular tissues, guiding minimally invasive therapies and diagnosing breast and prostate cancers. Its usage is limited because ultrasound can measure only the axial component of displacement with high precision. The goal of this study was to assess the effect of lateral sampling frequency, lateral beam-width and the number of active transmission elements on the quality of axial and lateral strain elastograms. Elastographic imaging was performed on gelatin-based phantoms with a modified commercial ultrasound scanner. Three groups of radio-frequency (RF) echo frames were reconstructed from fully synthetic aperture data. In the first group, all 128 transmission elements (corresponding to a lateral beamwidth of 0.22 mm at the center of the field of view) were used to reconstruct RF echo frames with A-line densities that varied from 6.4 lines/mm to 51.2 lines/mm. In the second group, the size of the aperture was varied to produce RF echo frames with lateral beamwidths ranging from 0.22 mm to 0.43 mm and a fixed A-line density of 25.6 lines/mm. In the third group, sparse arrays with varying number of active transmission elements (from 2 to 128) were used to reconstruct RF echo frames, whose A-line density and lateral beamwidth were fixed to 25.6 lines/mm and 0.22 mm, respectively. Applying a two-dimensional (2-D) displacement estimator to the pre- and post-deformed RF echo frames produced displacement elastograms. Axial and lateral strain elastograms were computed from displacement elastograms with a least squares strain estimator. The quality of axial and lateral strain elastograms improved with increasing applied strain and A-line density but decreased with increasing lateral beamwidth and deteriorated as the number of active transmission elements in the sparse arrays were reduced. This work demonstrated that the variance incurred when estimating the lateral component of displacement was reduced considerably when elastography was performed with a synthetic aperture ultrasound imaging system. Satisfactory axial and lateral strain elastograms were produced using a sparse array with as few as 16 active transmission elements.     

Wavelet denoising of displacement estimates in elastography

Wavelet shrinkage denoising of the displacement estimates to reduce noise artefacts, especially at high overlaps in elastography, is presented in this paper. Correlated errors in the displacement estimates increase dramatically with an increase in the overlap between the data segments. These increased correlated errors (due to the increased correlation or similarity between consecutive displacement estimates) generate the so-called "worm" artefact in elastography. However, increases in overlap on the order of 90% or higher are essential to improve axial resolution in elastography. The use of wavelet denoising significantly reduces errors in the displacement estimates, thereby reducing the worm artefacts, without compromising on edge (high-frequency or detail) information in the elastogram. Wavelet denoising is a term used to characterize noise rejection by thresholding the wavelet coefficients. Worm artefacts can also be reduced using a low-pass filter; however, low-pass filtering of the displacement estimates does not preserve local information such as abrupt change in slopes, causing the smoothing of edges in the elastograms. Simulation results using the analytic 2-D model of a single inclusion phantom illustrate that wavelet denoising produces elastograms with the closest correspondence to the ideal mechanical strain image. Wavelet denoising applied to experimental data obtained from an in vitro thermal lesion phantom generated using radiofrequency (RF) ablation also illustrates the improvement in the elastogram noise characteristics.     

Elastographic imaging using staggered strain estimates

Conventional techniques in elastography estimate strain as the gradient of the displacement estimates obtained through crosscorrelation of pre- and postcompression rf A-lines. In these techniques, the displacements are estimated over overlapping windows and the strains are estimated as the gradient of the displacement estimates over adjacent windows. The large amount ofnoise at high window overlaps may result in poor quality elastograms, thus restricting the applicability of conventional strain estimation techniques to low window overlaps, which, in turn, results in a small number of pixels in the image. To overcome this restriction, we propose a multistep strain estimation technique. It computes the first elastogram using nonoverlapped windows. In the next step, the data windows are shifted by a small distance (small fraction of window size) and another elastogram is produced. This is repeated until the cumulative shift equals/exceeds the window size and all the elastograms are staggered to produce the final elastogram. Simulations and experiments were performed using this technique to demonstrate significant improvement in the elastographic signal-to-noise ratio (SNRe) and the contrast-to-noise ratio (CNRe) at high window overlaps over conventional strain estimation techniques, without noticeable loss of spatial resolution. This technique might be suitable for reducing the algorithmic noise in the elastograms at high window overlaps.     

Radial Motion Estimation of Myocardium in Rats with Myocardial Infarction: A Hybrid Method of FNCCGLAM and Polar Transformation

Ultrasound elastography is a novel approach of evaluating regional myocardial systolic function and detecting infarcted area. This study aims to evaluate the radial motion of myocardial infarction (MI) area in left ventricular parasternal short axis (PSAX) view using a hybrid method of fast normalized cross-correlation and global analytic minimization (FNCCGLAM) and polar transformation. Fifteen rats were randomly selected for sham group, MI group and ischemia-reperfusion (IR) group (N = 5 for each group). The ultrasound radiofrequency data of the PSAX view of rat heart were acquired. After polar transformation of the data, the infarcted myocardium with the change of mechanical property was tracked over one myocardial systolic phase by the proposed method in comparison with fast normalized cross-correlation (FNCC) and dynamic programming analytic minimization (DPAM). To obtain a clear visualization of the myocardium, the inverse polar transformation was performed. The results indicated that the use of FNCCGLAM refined the myocardial displacements to obtain high-quality myocardial elastographic map with a higher contrast-to-noise ratio and dynamically tracked the infarcted myocardial segment with a higher success rate in comparison with FNCC and DPAM. It was found that the radial systolic motion of the infarcted anterior segment in the MI group reduced significantly (p < 0.05) in comparison with the sham group, while the systolic function of that myocardial segment in the IR group recovered at some extent. The results in this study suggest that FNCCGLAM is superior to FNCC and DPAM with the improved accuracy and robustness of motion estimation and has potentials as displacement estimator in ultrasound elastography.     

An Ultrasound-Driven Kinematic Model for Deformation of the Infarcted Mouse Left Ventricle Incorporating a Near-Incompressibility Constraint

Mathematical models of varying complexity have proved useful in fitting and interpreting regional cardiac displacements obtained from imaging methods such as ultrasound speckle tracking or MRI tagging. Simpler models, such as the classic thick-walled cylinder model of the left ventricle (LV), can be solved quickly and are easy to implement, but they ignore regional geometric variations and are difficult to adapt to the study of regional pathologies like myocardial infarctions. Complex, anatomically accurate finite-element models work well, but are computationally intensive and require specialized expertise to implement. We developed a kinematic model that offers a compromise between these two traditional approaches, assuming only that displacements in the left ventricle are polynomial functions of initial position and that the myocardium is nearly incompressible, while allowing myocardial motion to vary spatially as would be expected in an ischemic or dyssynchronous LV. Model parameters were determined using an objective function with adjustable weights to account for confidence in individual displacement components and desired strength of the incompressibility constraint. The model accurately represented the motion of both normal and infarcted mouse LVs during the cardiac cycle, with normalized root mean square errors in predicted deformed positions of 8.2 ± 2.3% and 7.4 ± 2.1% for normal and infarcted hearts, respectively.     

Assessment of myocardial infarction in mice by Late Gadolinium Enhancement MR imaging using an inversion recovery pulse sequence at 9.4T

Purpose

To demonstrate the feasibility of using an inversion recovery pulse sequence and to define the optimal inversion time (TI) to assess myocardial infarction in mice by late gadolinium enhancement (LGE) MRI at 9.4T, and to obtain the maximal contrast between the infarcted and the viable myocardium.

Methods

MRI was performed at 9.4T in mice, two days after induction of myocardial infarction (n = 4). For cardiovascular MR imaging, a segmented magnetization-prepared fast low angle shot (MP-FLASH) sequence was used with varied TIs ranging from 40 to 420 ms following administration of gadolinium-DTPA at 0.6 mmol/kg. Contrast-to-noise (CNR) and signal-to-noise ratio (SNR) were measured and compared for each myocardial region of interest (ROI).

Results

The optimal TI, which corresponded to a minimum SNR in the normal myocardium, was 268 ms ± 27.3. The SNR in the viable myocardium was significantly different from that found in the infarcted myocardium (17.2 ± 2.4 vs 82.1 ± 10.8; p = 0.006) leading to a maximal relative SI (Signal Intensity) between those two areas (344.9 ± 60.4).

Conclusion

Despite the rapid heart rate in mice, our study demonstrates that LGE MRI can be performed at 9.4T using a protocol similar to the one used for clinical MR diagnosis of myocardial infarction.     

T1-weighted cine FLASH is superior to IR imaging of post-infarction myocardial viability at 4.7T.

PURPOSE: Data are unavailable for rational selection of pulse sequences to assess postinfarction myocardial viability in rodents at high field strength. We implemented a widely used clinical inversion recovery (IR) sequence at 4.7T and compared the results to a heavily T1-weighted cine FLASH sequence (T1-CF) for assessment of infarction size. MATERIALS AND METHODS: Eleven infarcted rats were examined within 24 h of infarction after injection of Gadophrin-3 contrast agent. Images were acquired using both pulse sequences and a standard cine (SC) sequence. Estimates of infarct size were compared to TTC. Global LV function was compared between the T1-CF and SC sequences. RESULTS: SNR, relative SNR, and CNR for the infarcted and normal myocardium were significantly greater for the IR sequence. Infarction size was overestimated by both sequences, but correlated highly and showed very close agreement with TTC. Global function revealed no significant differences between T1-CF and SC. Conclusion: Both IR and T1-CF produced reliable results for assessment of infarction size at 4.7T. While the IR sequence delivers better overall SNR and CNR, the T1-CF allows concomitant assessment of global cardiac function with a much shorter acquisition time.     

Comparing elastographic strain images with modulus images obtained using nanoindentation: preliminary results using phantoms and tissue samples

Conventional elastography involves quasistatic mechanical compression (external or internal) of the tissue under ultrasonic insonification to obtain radiofrequency (RF) A-lines before and after compression. Cross-correlation of the pre- and postcompression A-lines results in displacement images with axial gradients that produce the strain images (strain elastograms). Though the strain elastograms show structural similarities to the modulus images, they are not related in a simple way to the modulus images because the strains depend on both modulus and geometry of the materials being deformed. Therefore, a quantification of the similarities between the strain and modulus images may enhance the interpretation confidence of strain elastograms in depicting tissue structure. To demonstrate similarities between modulus images and strain elastograms, a feasibility study of using nanoindentation to obtain modulus images of thin slices of tissue and tissue-mimicking phantoms (agar-gelatin mixtures) was performed first, with encouraging results. This was followed by a comparison of modulus images and strain elastograms obtained from the same sample slices. The experimental results indicated that, under certain experimental conditions, it is feasible to perform quantitative comparisons between strain images (using elastography) and modulus images. A good visual, as well as quantitative, correspondence between structures in the modulus and strain images could be obtained at a 3-mm scale.     

Myocardial elastography--a feasibility study in vivo

Early detection of cardiovascular diseases has been a very active research area in the medical imaging field. Assessment of the local and global mechanical functions is one of the major goals of accurate diagnosis. In this study, we investigated the feasibility of elastography for estimation and imaging of the local cardiac muscle displacement and strain in a human heart in vivo. In its noninvasive applications, elastography has been typically used to determine local tissue strain through the use of externally applied compression. For our study, we utilized the cardiac muscle motion during a cardiac cycle as the mechanical stimulus, and acquired successive radiofrequency (RF) data frames of the septal and posterior walls over a few cardiac cycles in parasternal and apical views, respectively. High-quality ciné-loop elastograms were obtained due to high frame rates and the resulting low decorrelation noise. Furthermore, the strain contrast was higher in the parasternal case, when only the posterior wall was imaged, and strain estimation was more robust in the apical view. High repeatability of the results was observed through elastographic measurements over several cardiac cycles. Finally, an M-mode version of elastography was used to follow part of the interventricular septum or the posterior wall over the course of two cardiac cycles. Not only do these preliminary results show that elastography is feasible in cardiac applications in vivo, but also that it can provide new information regarding cardiac motion and mechanical function. Future prospects include assessment of the role of elastography in detection of ischemia and infarction.     

A quantitative comparison of modulus images obtained using nanoindentation with strain elastograms

Tissue stiffness is generally known to be associated with pathologic changes. Ultrasound (US) elastography, on the other hand, is capable of imaging tissue strain, which may or may not be well-correlated with tissue stiffness. Hence, a quantitative comparison between the elastographic tissue strain images and the corresponding tissue modulus images needed to be performed to evaluate the usefulness of elastography in imaging tissue stiffnesss properties. Simulations were performed to demonstrate and quantify the similarities between modulus images and strain elastograms. This was followed by comparing nanoindenter-based modulus images with strain elastograms of thin slices of tissue-mimicking phantoms. Finally, some beef slices, canine prostates, ovine kidneys and breast cancers grown in mice were used to demonstrate the qualitative correspondence between modulus images and strain elastograms. The simulations and the experiments indicated that it is feasible to perform quantitative comparisons between strain images (using elastography) and modulus images on certain tissue structures and geometries. A good quantitative correspondence (correlation values of greater than 0.8) between structures in the modulus and strain images could be obtained at scales equal to or larger than 20 Qlambda (where Q is the quality factor defined as the ratio of the center frequency over the band width and lambda is the wavelength of the US system) modulus contrasts larger than 5, applied strains between 0.5% and 3% and window lengths for computing strain elastograms between 3 Qlambda and 5 Qlambda. The gelatin-phantom experiments showed lower values of correlation (values around 0.5) than with theory and simulations. The decrease in correlation was attributed to the presence of measurement noise in both strain elastography and modulus imaging, an increase of dimensionality of the problem (from 2-D to 3-D), local anisotropy, heterogeneity and nonstationarity. Experiments on real tissue slices showed further decrease in the correlation to around 0.3, possibly due to additional confounding factors such as time-dependent mechanical properties and geometrical distortions in the tissue during imaging. The work presented in this paper demonstrates that there is an intrinsic relationship between strain elastograms and the actual distribution of soft tissue elastic moduli, and bodes well for continued work in the area of elastography.     

Non-Rigid Image Registration Based Strain Estimator for Intravascular Ultrasound Elastography

Intravascular ultrasound elastography (IVUSe) could improve the diagnosis of cardiovascular disease by revealing vulnerable plaques through their mechanical tissue properties. To improve the performance of IVUSe, we developed and implemented a non-rigid image-registration method to visualize the radial and circumferential component of strain within vascular tissues. We evaluated the algorithm's performance with four initialization schemes using simulated and experimentally acquired ultrasound images. Applying the registration method to radio-frequency (RF) echo frames improved the accuracy of displacements compared to when B-mode images were employed. However, strain elastograms measured from RF echo frames produce erroneous results when both the zero-initialization method and the mesh-refinement scheme were employed. For most strain levels, the cross-correlation-initialization method produced the best performance. The simulation study predicted that elastograms obtained from vessels with average strains in the range of 3%–5% should have high elastographic signal-to-noise ratio (SNRe)–on the order of 4.5 and 7.5 for the radial and circumferential components of strain, respectively. The preliminary in vivo validation study (phantom and an atherosclerotic rabbit) demonstrated that the non-rigid registration method could produce useful radial and circumferential strain elastograms under realistic physiologic conditions. The results of this investigation were sufficiently encouraging to warrant a more comprehensive in vivo validation.     

Comparative evaluation of strain-based and model-based modulus elastography

Elastography based on strain imaging currently endures mechanical artefacts and limited contrast transfer efficiency. Solving the inverse elasticity problem (IEP) should obviate these difficulties; however, this approach to elastography is often fraught with problems because of the ill-posed nature of the IEP. The aim of the present study was to determine how the quality of modulus elastograms computed by solving the IEP compared with those produced using standard strain imaging methodology. Strain-based modulus elastograms (i.e., modulus elastograms computed by simply inverting strain elastograms based on the assumption of stress uniformity) and model-based modulus elastograms (i.e., modulus elastograms computed by solving the IEP) were computed from a common cohort of simulated and gelatin-based phantoms that contained inclusions of varying size and modulus contrast. The ensuing elastograms were evaluated by employing the contrast-to-noise ratio (CNR(e)) and the contrast transfer efficiency (CTE(e)) performance metrics. The results demonstrated that, at a fixed spatial resolution, the CNR(e) of strain-based modulus elastograms was statistically equivalent to those computed by solving the IEP. At low modulus contrast, the CTE(e) of both elastographic imaging approaches was comparable; however, at high modulus, the CTE(e) of model-based modulus elastograms was superior.     

Improved measurement of vibration amplitude in dynamic optical coherence elastography

Abstract: Optical coherence elastography employs optical coherence tomography (OCT) to measure the displacement of tissues under load and, thus, maps the resulting strain into an image, known as an elastogram. We present a new improved method to measure vibration amplitude in dynamic optical coherence elastography. The tissue vibration amplitude caused by sinusoidal loading is measured from the spread of the Doppler spectrum, which is extracted using joint spectral and time domain signal processing. At low OCT signal-to-noise ratio (SNR), the method provides more accurate vibration amplitude measurements than the currently used phase-sensitive method. For measurements performed on a mirror at OCT SNR = 5 dB, our method introduces <3% error, compared to >20% using the phase-sensitive method. We present elastograms of a tissue-mimicking phantom and excised porcine tissue that demonstrate improvements, including a 50% increase in the depth range of reliable vibration amplitude measurement.OCIS codes: (110.4500) Optical coherence tomography, (290.5820) Scattering measurements, (170.6935) Tissue characterization     

A finite element model for performing intravascular ultrasound elastography of human atherosclerotic coronary arteries

Intravascular ultrasound (US) elastography measures in an artery the arterial radial strain and displays it in an elastogram. An elastogram adds diagnostic information, such as the proneness of a plaque to rupture and its material composition. However, radial strain depends upon the material properties of an artery, including geometry and used catheter position. Therefore, there is not always a one-to-one correspondence between radial strain and rupture-proneness or material composition. Both the dependence and the correspondence can be quantified after a proper finite element model (FEM) is available. Therefore, this paper proposes a FEM and shows that it can model the arterial strain behavior. Its modelling capability was evaluated by comparing simulated with measured elastograms. Measured elastograms were processed from radiofrequency (RF) data obtained in vitro from six objects: a vessel-mimicking phantom and five excised human atherosclerotic coronary arteries. A FEM was created for each object and used to simulate an elastogram; the material properties and geometry of the FEM were obtained from the histology of the object. Comparison was performed upon high strain regions (HStR), because these regions have proven to contain plaques that show the hallmarks of vulnerable plaques. Eight HStR were automatically identified from the five arteries. Statistical tests showed that there was no significant difference between simulated and corresponding measured elastograms in location, surface area or mean strain value of a HStR. The results demonstrate that the FEM can simulate elastograms measured from arteries. As such, the FEM may help in quantifying strain-dependencies and assist in tissue characterization by reconstructing a Young's modulus image from a measured elastogram.     

Trade-offs between the axial resolution and the signal-to-noise ratio in elastography

Elastography involves tracking the ultrasonic A-mode signals before and after mechanical compression of tissue to form a computed image of the local strains undergone by various tissue components. The quality of the strain estimates in elastography is typically quantified using factors such as the elastographic SNR (SNR(e)), contrast-to-noise ratio (CNR(e)), and the spatial resolution. These quality factors depend on the mechanical parameters (such as the applied strain and the boundary conditions), the acoustic parameters (such as the sonographic SNR, the center frequency, and the bandwidth), and the signal-processing parameters (such as the window length and the window separation). Theoretical developments in elastography have established functional relationships between the SNR(e) and CNR(e) and these parameters. Similarly, simulations have established empirical relationships between the axial resolution and the acoustic and signal-processing parameters. We find that a trade-off exists between the achievable SNR(e) (CNR(e)) and the axial resolution in elastography and that the trade-off occurs only with respect to the signal-processing parameters. Theoretical work on the spatial resolution accompanied with simulations and experiments were used to confirm such an observation. The trade-off between the SNR(e) (CNR(e)) and the resolution was found to be nonlinear, with large improvements in the SNR(e) being possible at the expense of small reductions in the axial resolution. All the quality factors improve with the acoustic parameters, which suggests the preferred use of transducers with high absolute bandwidths and center frequencies.     

Spatial angular compounding for elastography without the incompressibility assumption

Spatial-angular compounding is a new technique that enables the reduction of noise artifacts in ultrasound elastography. Previous results using spatial angular compounding, however, were based on the use of the tissue incompressibility assumption. Compounded elastograms were obtained from a spatially-weighted average of local strain estimated from radiofrequency echo signals acquired at different insonification angles. In this paper, we present a new method for reducing the noise artifacts in the axial strain elastogram utilizing a least-squares approach on the angular displacement estimates that does not use the incompressibility assumption. This method produces axial strain elastograms with higher image quality, compared to noncompounded axial strain elastograms, and is referred to as the least-squares angular-compounding approach for elastography. To distinguish between these two angular compounding methods, the spatial-angular compounding with angular weighting based on the tissue incompressibility assumption is referred to as weighted compounding. In this paper, we compare the performance of the two angular-compounding techniques for elastography using beam steering on a linear-array transducer. Quantitative experimental results demonstrate that least-squares compounding provides comparable but smaller improvements in both the elastographic signal-to-noise ratio and the contrast-to-noise ratio, as compared to the weighted-compounding method. Ultrasound simulation results suggest that the least-squares compounding method performs better and provide accurate and robust results when compared to the weighted compounding method, in the case where the incompressibility assumption does not hold.     

Elastographic imaging of thermal lesions in the liver in vivo following radiofrequency ablation: preliminary results

Radiofrequency (RF) ablation is an interstitial focal ablative therapy that can be used in a percutaneous fashion. This modality provides in situ destruction of hepatic tumors. However, local recurrence rates after RF ablative therapy are as high as 34% to 55%, believed to be due in part to the inability to visualize accurately the zone of necrosis (thermal lesion). This can lead to the incomplete ablation of the tumor, generally in areas near the tumor edges. In this paper, we show that ultrasound (US)-based in vivo elastography can accurately depict thermal lesions after thermal therapy. However, elastography of the liver and other abdominal organs is challenging due to the difficulty in providing controlled and reproducible compression. The use of the RF ablation probe as the compressor/displacement device reduces lateral slippage or nonaxial motion that may occur with externally applied compressions or imaging during the respiratory cycle. This technique also provides controlled and reproducible compressions of the liver for in vivo elastographic imaging. Comparison of elastograms with histology of ablated tissue demonstrates a close relationship between elastographic image features and histopathology.     

定量组织速度成像技术评价急性心肌梗死后左室重构的左室功能

目的应用定量组织速度成像技术对心肌梗死后左室重构的左心功能进行评价,以探讨其应用价值.方法用定量组织速度成像技术测定22例健康者及临床确诊的29例心肌梗死后左室重构的冠心病患者的左室壁各节段的收缩期峰值速度(VS),舒张早期速度(VE),舒张晚期速度(VA)和VE/VA比值.测定二尖瓣口血流频谱的快速充盈速度(E),左房收缩充盈速度(A)和E/A值.容积法测左室射血分数,左室舒张末期容积指数(LVEDVI),左室收缩末期容积指数(LVESVI)及球形指数,并与正常组比较.结果心脏左室长轴方向上心梗组前壁,侧壁,下壁各节段,后间隔心尖段Vs明显下降(P＜0.01),后间隔基底段和中间段Vs无明显差异(P＞0.05);心梗组几乎各节段VE、VA、VE/VA与正常组相比有显著差异(P＜0.05).各节段平均VS与左室射血分数,球形指数等呈线性相关(r值分别为0.79,0.68,P＜0.01),舒张期功能参数平均VE/VA与二尖瓣E/A比值之间存在高度相关性(r=0.62,P＜0.01).心梗组LVEDVI和LVESVI明显增大(P＜0.01).结论定量组织速度成像可客观定位定量的反映心肌梗死局部心肌组织的收缩及舒张功能,又能体现心肌梗死后左室重构的整体功能,为心肌梗死后左室重构的心功能的评价提供了客观依据.