Wave Speed Maps Research Articles

Scanning acoustic microscopy of biological cryosections: the effect of local thickness on apparent acoustic wave speed

ABSTRACTScanning acoustic microscopy (SAM), when applied to biological samples has the potential to resolve the longitudinal acoustic wave speed and hence stiffness of discrete tissue components. The heterogeneity of biological materials combined with the action of cryosectioning and rehydrating can, however, create variations in section topography. Here, we set out to determine how variations in specimen thickness influence apparent acoustic wave speed measurementsCryosections (5μm nominal thickness) of human skin biopsies were adhered to glass slides before washing and rehydrating in water. Multiple regions (200x200 μm; n = 3) were imaged by SAM to generate acoustic wave speed maps. Subsequently co-localised 30x30 μm sub-regions were imaged by atomic force microscopy (AFM) in fluid. The images were then registered using Image J. Each pixel was allocated both a height and wave speed value before their relationship was then plotted on a scattergram. The mean section thickness measured by AFM was 3.48 ± 1.12 (SD) μm. Regional height variations influenced apparent wave speed measurements. A 3.5 μm height difference was associated with a 400 ms-1 increase in wave speed. In the present study we show that local variations in specimen thickness influence apparent wave speed. We also show that a true measure of wave speed can be calculated if the thickness of the specimen is known at each sampling point.

Comb-Push Ultrasound Shear Elastography (CUSE) With Various Ultrasound Push Beams

Comb-push ultrasound shear elastography (CUSE) has recently been shown to be a fast and accurate 2-D elasticity imaging technique that can provide a full field-of-view (FOV) shear wave speed map with only one rapid data acquisition. The initial version of CUSE was termed U-CUSE because unfocused ultrasound push beams were used. In this paper, we present two new versions of CUSE-focused CUSE (F-CUSE) and marching CUSE (M-CUSE), which use focused ultrasound push beams to improve acoustic radiation force penetration and produce stronger shear waves in deep tissues (e.g., kidney and liver). F-CUSE divides transducer elements into several subgroups which transmit multiple focused ultrasound beams simultaneously. M-CUSE uses more elements for each focused push beam and laterally marches the push beams. Both F-CUSE and M-CUSE can generate comb-shaped shear wave fields that have shear wave motion at each imaging pixel location so that a full FOV 2-D shear wave speed map can be reconstructed with only one data acquisition. Homogeneous phantom experiments showed that U-CUSE, F-CUSE, and M-CUSE can all produce smooth shear wave speed maps with accurate shear wave speed estimates. An inclusion phantom experiment showed that all CUSE methods could provide good contrast between the inclusion and background with sharp boundaries while F-CUSE and M-CUSE require shorter push durations to achieve shear wave speed maps with comparable SNR to U-CUSE. A more challenging inclusion phantom experiment with a very stiff and deep inclusion shows that better shear wave penetration could be gained by using F-CUSE and M-CUSE. Finally, a shallow inclusion experiment showed that good preservations of inclusion shapes could be achieved by both U-CUSE and F-CUSE in the near field. Safety measurements showed that all safety parameters are below FDA regulatory limits for all CUSE methods. These promising results suggest that, using various push beams, CUSE is capable of reconstructing a 2-D full FOV shear elasticity map using only one push-detection data acquisition in a wide range of depths for soft tissue elasticity imaging.

Ultrasound elastic tensor imaging: comparison with MR diffusion tensor imaging in the myocardium

We have previously proven the feasibility of ultrasound-based shear wave imaging (SWI) to non-invasively characterize myocardial fiber orientation in both in vitro porcine and in vivo ovine hearts. The SWI-estimated results were in good correlation with histology. In this study, we proposed a new and robust fiber angle estimation method through a tensor-based approach for SWI, coined together as elastic tensor imaging (ETI), and compared it with magnetic resonance diffusion tensor imaging (DTI), a current gold standard and extensively reported non-invasive imaging technique for mapping fiber architecture. Fresh porcine (n = 5) and ovine (n = 5) myocardial samples (20 × 20 × 30 mm3) were studied. ETI was firstly performed to generate shear waves and to acquire the wave events at ultrafast frame rate (8000 fps). A 2.8 MHz phased array probe (pitch = 0.28 mm), connected to a prototype ultrasound scanner, was mounted on a customized MRI-compatible rotation device, which allowed both the rotation of the probe from −90° to 90° at 5° increments and co-registration between two imaging modalities. Transmural shear wave speed at all propagation directions realized was firstly estimated. The fiber angles were determined from the shear wave speed map using the least-squares method and eigen decomposition. The test myocardial sample together with the rotation device was then placed inside a 7T MRI scanner. Diffusion was encoded in six directions. A total of 270 diffusion-weighted images (b = 1000 s mm−2, FOV = 30 mm, matrix size = 60 × 64, TR = 6 s, TE = 19 ms, 24 averages) and 45 B0 images were acquired in 14 h 30 min. The fiber structure was analyzed by the fiber-tracking module in software, MedINRIA. The fiber orientation in the overlapped myocardial region which both ETI and DTI accessed was therefore compared, thanks to the co-registered imaging system. Results from all ten samples showed good correlation (r2 = 0.81, p < 0.0001) and good agreement (3.05° bias) between ETI and DTI fiber angle estimates. The average ETI-estimated fractional anisotropy (FA) values decreased from subendocardium to subepicardium (p < 0.05, unpaired, one-tailed t-test, N = 10) by 33%, whereas the corresponding DTI-estimated FA values presented a change of −10% (p > 0.05, unpaired, one-tailed t-test, N = 10). In conclusion, we have demonstrated that the fiber orientation estimated by ETI, which assesses the shear wave speed (and thus the stiffness), was comparable to that measured by DTI, which evaluates the preferred direction of water diffusion, and have validated this concept within the myocardium. Moreover, ETI was shown capable of mapping the transmural fiber angles with as few as seven shear wave propagation directions.

Comb-Push Ultrasound Shear Elastography (CUSE): A Novel Method for Two-Dimensional Shear Elasticity Imaging of Soft Tissues

Fast and accurate tissue elasticity imaging is essential in studying dynamic tissue mechanical properties. Various ultrasound shear elasticity imaging techniques have been developed in the last two decades. However, to reconstruct a full field-of-view 2-D shear elasticity map, multiple data acquisitions are typically required. In this paper, a novel shear elasticity imaging technique, comb-push ultrasound shear elastography (CUSE), is introduced in which only one rapid data acquisition (less than 35 ms) is needed to reconstruct a full field-of-view 2-D shear wave speed map (40 × 38 mm). Multiple unfocused ultrasound beams arranged in a comb pattern (comb-push) are used to generate shear waves. A directional filter is then applied upon the shear wave field to extract the left-to-right (LR) and right-to-left (RL) propagating shear waves. Local shear wave speed is recovered using a time-of-flight method based on both LR and RL waves. Finally, a 2-D shear wave speed map is reconstructed by combining the LR and RL speed maps. Smooth and accurate shear wave speed maps are reconstructed using the proposed CUSE method in two calibrated homogeneous phantoms with different moduli. Inclusion phantom experiments demonstrate that CUSE is capable of providing good contrast (contrast-to-noise ratio ≥ 25 dB) between the inclusion and background without artifacts and is insensitive to inclusion positions. Safety measurements demonstrate that all regulated parameters of the ultrasound output level used in CUSE sequence are well below the FDA limits for diagnostic ultrasound.

Imaging quasi-vertical geological faults with earthquake data

SUMMARY We present a method for imaging quasi-vertically dipping faults with surface records of reflected P waves from small earthquakes. Faults are boundaries between geological structures, such as tectonic plates, and are located in earthquake active regions such as Parkfield, California. The high degree of seismic activity enables the use of multiple seismic recordings in our fault identification algorithm. Major challenges occur because of the quasi-vertical orientation of the fault and the fact that the wave reflected by the fault and recorded by the surface receivers is not well modelled by the direct arrival of the propagating wave generated by the earthquake source. Our method uses the 2-D acoustic wave equation as the model for P-wave propagation. We assume that an approximate wave speed map on the reflection side of the fault is available and the source locations are known, for example, from traveltime tomography. We also assume that the source time function is known. The new features of our method arise because earthquake sources are located very close to the fault. This has two implications: (1) the direct arrival and the reflected wave arrive almost simultaneously, so that it is impossible to separate them on a seismogram using standard techniques, and (2) most of the reflections occur above the critical angle which introduces a distortion in the reflected wave. To overcome these difficulties we use a modelled incident wave to (1) remove the direct arrival from the data, and (2) remove the post-critical distortion from the reflected wave. We justify the distortion removal using the leading-order term of an asymptotic expansion, and an optimization procedure. To complete our algorithm we utilize some features of reverse time migration: (1) the use of full acoustic wave equation for modelling and backpropagation, and (2) zero-lag correlation of the backpropagated time reversed reflected and incident fields. We present numerical examples of fault reconstructions with synthetic data.