Three-dimensional ultrasound strain imaging of skeletal muscles.

In this study, a multi-dimensional strain estimation method is presented to assess local relative deformation in three orthogonal directions in 3D space of skeletal muscles during voluntary contractions. A rigid translation and compressive deformation of a block phantom, that mimics muscle contraction, is used as experimental validation of the 3D technique and to compare its performance with respect to a 2D based technique. Axial, lateral and (in case of 3D) elevational displacements are estimated using a cross-correlation based displacement estimation algorithm. After transformation of the displacements to a Cartesian coordinate system, strain is derived using a least-squares strain estimator. The performance of both methods is compared by calculating the root-mean-squared error of the estimated displacements with the calculated theoretical displacements of the phantom experiments. We observe that the 3D technique delivers more accurate displacement estimations compared to the 2D technique, especially in the translation experiment where out-of-plane motion hampers the 2D technique. In vivo application of the 3D technique in the musculus vastus intermedius shows good resemblance between measured strain and the force pattern. Similarity of the strain curves of repetitive measurements indicates the reproducibility of voluntary contractions. These results indicate that 3D ultrasound is a valuable imaging tool to quantify complex tissue motion, especially when there is motion in three directions, which results in out-of-plane errors for 2D techniques.

Ultrafast vascular strain compounding using plane wave transmission.

Deformations of the atherosclerotic vascular wall induced by the pulsating blood can be estimated using ultrasound strain imaging. Because these deformations indirectly provide information on mechanical plaque composition, strain imaging is a promising technique for differentiating between stable and vulnerable atherosclerotic plaques. This paper first explains 1-D radial strain estimation as applied intravascularly in coronary arteries. Next, recent methods for noninvasive vascular strain estimation in a transverse imaging plane are discussed. Finally, a compounding technique that our group recently developed is explained. This technique combines motion estimates of subsequently acquired focused ultrasound images obtained at various insonification angles. However, because the artery moves and deforms during the multi-angle acquisition, errors are introduced when compounding. Recent advances in computational power have enabled plane wave ultrasound acquisition, which allows 100 times faster image acquisition and thus might resolve the motion artifacts. In this paper the performance of strain imaging using plane wave compounding is investigated using simulations of an artery with a vulnerable plaque and experimental data of a two-layered vessel phantom. The results show that plane wave compounding outperforms 0° focused strain imaging. For the simulations, the root mean squared error reduced by 66% and 50% for radial and circumferential strain, respectively. For the experiments, the elastographic signal-to-noise and contrast-to-noise ratio (SNR(e) and CNR(e)) increased with 2.1 dB and 3.7 dB radially, and 5.6 dB and 16.2dB circumferentially. Because of the high frame rate, the plane wave compounding technique can even be further optimized and extended to 3D in future.

Cardiac biplane strain imaging: initial in vivo experience.

In this study, first we propose a biplane strain imaging method using a commercial ultrasound system, yielding estimation of the strain in three orthogonal directions. Secondly, an animal model of a child's heart was introduced that is suitable to simulate congenital heart disease and was used to test the method in vivo. The proposed approach can serve as a framework to monitor the development of cardiac hypertrophy and fibrosis. A 2D strain estimation technique using radio frequency (RF) ultrasound data was applied. Biplane image acquisition was performed at a relatively low frame rate (<100 Hz) using a commercial platform with an RF interface. For testing the method in vivo, biplane image sequences of the heart were recorded during the cardiac cycle in four dogs with an aortic stenosis. Initial results reveal the feasibility of measuring large radial, circumferential and longitudinal cumulative strain (up to 70%) at a frame rate of 100 Hz. Mean radial strain curves of a manually segmented region-of-interest in the infero-lateral wall show excellent correlation between the measured strain curves acquired in two perpendicular planes. Furthermore, the results show the feasibility and reproducibility of assessing radial, circumferential and longitudinal strains simultaneously. In this preliminary study, three beagles developed an elevated pressure gradient over the aortic valve (Deltap: 100-200 mmHg) and myocardial hypertrophy. One dog did not develop any sign of hypertrophy (Deltap = 20 mmHg). Initial strain (rate) results showed that the maximum strain (rate) decreased with increasing valvular stenosis (-50%), which is in accordance with previous studies. Histological findings corroborated these results and showed an increase in fibrotic tissue for the hearts with larger pressure gradients (100, 200 mmHg), as well as lower strain and strain rate values.

In vivo validation of cardiac output assessment in non-standard 3D echocardiographic images.

Automatic segmentation of the endocardial surface in three-dimensional (3D) echocardiographic images is an important tool to assess left ventricular (LV) geometry and cardiac output (CO). The presence of speckle noise as well as the nonisotropic characteristics of the myocardium impose strong demands on the segmentation algorithm. In the analysis of normal heart geometries of standardized (apical) views, it is advantageous to incorporate a priori knowledge about the shape and appearance of the heart. In contrast, when analyzing abnormal heart geometries, for example in children with congenital malformations, this a priori knowledge about the shape and anatomy of the LV might induce erroneous segmentation results. This study describes a fully automated segmentation method for the analysis of non-standard echocardiographic images, without making strong assumptions on the shape and appearance of the heart. The method was validated in vivo in a piglet model. Real-time 3D echocardiographic image sequences of five piglets were acquired in radiofrequency (rf) format. These ECG-gated full volume images were acquired intra-operatively in a non-standard view. Cardiac blood flow was measured simultaneously by an ultrasound transit time flow probe positioned around the common pulmonary artery. Three-dimensional adaptive filtering using the characteristics of speckle was performed on the demodulated rf data to reduce the influence of speckle noise and to optimize the distinction between blood and myocardium. A gradient-based 3D deformable simplex mesh was then used to segment the endocardial surface. A gradient and a speed force were included as external forces of the model. To balance data fitting and mesh regularity, one fixed set of weighting parameters of internal, gradient and speed forces was used for all data sets. End-diastolic and end-systolic volumes were computed from the segmented endocardial surface. The cardiac output derived from this automatic segmentation was validated quantitatively by comparing it with the CO values measured from the volume flow in the pulmonary artery. Relative bias varied between 0 and -17%, where the nominal accuracy of the flow meter is in the order of 10%. Assuming the CO measurements from the flow probe as a gold standard, excellent correlation (r = 0.99) was observed with the CO estimates obtained from image segmentation.