Spatial domain reconstruction for imaging speed-of-sound with pulse-echo ultrasound: simulation and in vivo study

Real-Time Speed-of-Sound Estimation In Vivo via Steered Plane Wave Ultrasound

Speed-of-sound (SoS) is an intrinsic acoustic property of human tissues and has been regarded as a potential biomarker of tissue health. To foster the clinical use of this emerging biomarker in medical diagnostics, it is important for SoS estimates to be derived and displayed in real time. Here, we demonstrate that concurrent global SoS estimation and B-mode imaging can be achieved live on a portable ultrasound scanner. Our innovation is hinged upon the design of a novel pulse-echo SoS estimation framework that is based on steered plane wave imaging. It has accounted for the effects of refraction and imaging depth when the medium SoS differs from the nominal value of 1540 m/s that is conventionally used in medical imaging. The accuracy of our SoS estimation framework was comparatively analyzed with through-transmit time-of-flight measurements in vitro on 15 custom agar phantoms with different SoS values (1508-1682 m/s) and in vivo on human calf muscles ( N = 9 ; SoS range: 1560-1586 m/s). Our SoS estimation framework has a mean signed difference (MSD) of - 0.6 ± 2.3 m/s in vitro and - 2.2 ± 11.2 m/s in vivo relative to the reference measurements. In addition, our real-time system prototype has yielded simultaneous SoS estimates and B-mode imaging at an average frame rate of 18.1 fps. Overall, by realizing real-time tissue SoS estimation with B-mode imaging, our innovation can foster the use of tissue SoS as a biomarker in medical ultrasound diagnostics.

Improved Transcranial Plane-Wave Imaging With Learned Speed-of-Sound Maps

Although transcranial ultrasound plane-wave imaging (PWI) has promising clinical application prospects, studies have shown that variable speed-of-sound (SoS) would seriously damage the quality of ultrasound images. The mismatch between the conventional constant velocity assumption and the actual SoS distribution leads to the general blurring of ultrasound images. The optimization scheme for reconstructing transcranial ultrasound image is often solved using iterative methods like full-waveform inversion. These iterative methods are computationally expensive and based on prior magnetic resonance imaging (MRI) or computed tomography (CT) information. In contrast, the multi-stencils fast marching (MSFM) method can produce accurate time travel maps for the skull with heterogeneous acoustic speed. In this study, we first propose a convolutional neural network (CNN) to predict SoS maps of the skull from PWI channel data. Then, use these maps to correct the travel time to reduce transcranial aberration. To validate the performance of the proposed method, numerical, phantom and intact human skull studies were conducted using a linear array transducer (L11-5v, 128 elements, pitch = 0.3 mm). Numerical simulations demonstrate that for point targets, the lateral resolution of MSFM-restored images increased by 65%, and the center position shift decreased by 89%. For the cyst targets, the eccentricity of the fitting ellipse decreased by 75%, and the center position shift decreased by 58%. In the phantom study, the lateral resolution of MSFM-restored images was increased by 49%, and the position shift was reduced by 1.72 mm. This pipeline, termed AutoSoS, thus shows the potential to correct distortions in real-time transcranial ultrasound imaging, as demonstrated by experiments on the intact human skull.

Pulse-echo ultrasound attenuation tomography

Objective.We present the first fully two-dimensional attenuation imaging technique developed for pulse-echo ultrasound systems. Unlike state-of-the-art techniques, which use line-by-line acquisitions, our method uses steered emissions to constrain attenuation values at each location with multiple crossing wave paths, essential to resolve the spatial variations of this tissue property.Approach.At every location, we compute normalized cross-correlations between the beamformed images that are obtained from emissions at different steering angles. We demonstrate that their log-amplitudes provide the changes between attenuation-induced amplitude losses undergone by the different incident waves. This allows us to formulate a linear tomographic problem, which we efficiently solve via a Tikhonov-regularized least-squares approach.Main results.The performance of our tomography technique is first validated in numerical examples and then experimentally demonstrated in custom-made tissue-mimicking phantoms with inclusions of varying size, echogenicity, and attenuation. We show that this technique is particularly good at resolving lateral variations in tissue attenuation and remains accurate in media with varying echogenicity.Significance.Based on a similar principle, this method can be easily combined with computed ultrasound tomography in echo mode for speed-of-sound imaging, paving the way towards a multi-modal ultrasound tomography framework characterizing multiple acoustic tissue properties simultaneously.

A New Method of Plane-Wave Ultrasound Imaging Based on Reverse Time Migration

Coherent plane-wave compounding technique enables rapid ultrasound imaging with comparable image quality to traditional B-mode imaging that relies on focused beam transmission. However, existing methods assume homogeneity in the imaged medium, neglecting the heterogeneity in sound velocities and densities present in real tissues, resulting in noise reverberation. This study introduces the Reverse Time Migration (RTM) method for ultrasound plane-wave imaging to overcome this limitation, which is combined with a method for estimating the speed of sound in layered media. Simulation results in a homogeneous background demonstrate that RTM reduces side lobes and grating lobes by approximately 30 dB, enhancing the contrast-to-noise ratio by 20% compared to conventional delay and sum (DAS) beamforming. Moreover, RTM achieves superior imaging outcomes with fewer compounding angles. The lateral resolution of the RTM with 5-9 angle compounding is able to achieve the effectiveness of the DAS method with 15-19 angle compounding, and the CNR of the RTM with 11-angle compounding is almost the same as that of the DAS with 21-angle compounding. In a heterogeneous background, experimental simulations and in vitro wire phantom experiments confirm RTM's capability to correct depth imaging, focusing reflected waves on point targets. In vitro porcine tissue experiments enable accurate imaging of layer interfaces by estimating the velocities of multiple layers containing muscle and fat. The proposed imaging procedure optimizes velocity estimation in complex media, compensates for the impact of velocity differences, provides more reliable imaging results.

Demonstration Study of Reflector-Based Volumetric Speed-of-Sound Imaging With Linear Ultrasound Arrays

Conventional B-mode ultrasound imaging has difficulty in delineating homogeneous soft tissues with similar acoustic impedances, as the reflectivity depends on the acoustic impedance at the interface. As a quantitative imaging biomarker sensitive to alteration of biomechanical properties, speed-of-sound (SoS) holds promising potential for tissue and disease differentiation such as delineation of different breast tissue types with similar acoustic impedance. Compared to two-dimensional (2D) SoS images, three-dimensional (3D) volumetric SoS images achieved through a full-angle ultrasound scan can reveal more intricate morphological structures of tissues; however, they generally require a ring transducer. In this study, we introduce a 3D SoS reconstruction system that utilizes hand-held linear arrays instead. This system employs a passive reflector positioned opposite the linear arrays, serving as an echogenic reference for time-of-flight (ToF) measurements, and a high-definition camera to track the location corresponding to each group of transmit-receive data. To merge these two streams of ToF measurements and location tracking, a voxel-based reconstruction algorithm is implemented. Experimental results with gelatin phantom and ex vivo tissue have demonstrated the stability of our proposed method. Moreover, the results underscore the potential of this system as a complementary diagnostic modality, particularly in the context of diseases such as breast cancer.

Windowed Radon Transform for Robust Speed-of-Sound Imaging With Pulse-Echo Ultrasound

In recent years, methods estimating the spatial distribution of tissue speed of sound with pulse-echo ultrasound are gaining considerable traction. They can address limitations of B-mode imaging, for instance in diagnosing fatty liver diseases. Current state-of-the-art methods relate the tissue speed of sound to local echo shifts computed between images that are beamformed using restricted transmit and receive apertures. However, the aperture limitation affects the robustness of phase-shift estimations and, consequently, the accuracy of reconstructed speed-of-sound maps. Here, we propose a method based on the Radon transform of image patches able to estimate local phase shifts from full-aperture images. We validate our technique on simulated, phantom and in-vivo data acquired on a liver and compare it with a state-of-the-art method. We show that the proposed method enhances the stability to changes of beamforming speed of sound and to a reduction of the number of insonifications. In particular, the deployment of pulse-echo speed-of-sound estimation methods onto portable ultrasound devices can be eased by the reduction of the number of insonifications allowed by the proposed method.

Investigating pulse-echo sound speed estimation in breast ultrasound with deep learning

Ultrasound is an adjunct tool to mammography that can quickly and safely aid physicians in diagnosing breast abnormalities. Clinical ultrasound often assumes a constant sound speed to form diagnostic B-mode images. However, the components of breast tissue, such as glandular tissue, fat, and lesions, differ in sound speed. Given a constant sound speed assumption, these differences can degrade the quality of reconstructed images via phase aberration. Sound speed images can be a powerful tool for improving image quality and identifying diseases if properly estimated. To this end, we propose a supervised deep-learning approach for sound speed estimation from analytic ultrasound signals. We develop a large-scale simulated ultrasound dataset that generates representative breast tissue samples by modeling breast gland, skin, and lesions with varying echogenicity and sound speed. We adopt a fully convolutional neural network architecture trained on a simulated dataset to produce an estimated sound speed map. The simulated tissue is interrogated with a plane wave transmit sequence, and the complex-value reconstructed images are used as input for the convolutional network. The network is trained on the sound speed distribution map of the simulated data, and the trained model can estimate sound speed given reconstructed pulse-echo signals. We further incorporate thermal noise augmentation during training to enhance model robustness to artifacts found in real ultrasound data. To highlight the ability of our model to provide accurate sound speed estimations, we evaluate it on simulated, phantom, and in-vivo breast ultrasound data.

Ultrasonic Sound Speed Estimation for Liver Fat Quantification: A Review by the AIUM-RSNA QIBA Pulse-Echo Quantitative Ultrasound Initiative

Non-alcoholic fatty liver disease (NAFLD) is a significant cause of diffuse liver disease, morbidity and mortality worldwide. Early and accurate diagnosis of NALFD is critical to identify patients at risk of disease progression. Liver biopsy is the current gold standard for diagnosis and prognosis. However, a non-invasive diagnostic tool is desired because of the high cost and risk of complications of tissue sampling. Medical ultrasound is a safe, inexpensive and widely available imaging tool for diagnosing NAFLD. Emerging sonographic tools to quantitatively estimate hepatic fat fraction, such as tissue sound speed estimation, are likely to improve diagnostic accuracy, precision and reproducibility compared with existing qualitative and semi-quantitative techniques. Various pulse-echo ultrasound speed of sound estimation methodologies have been investigated, and some have been recently commercialized. We review state-of-the-art in vivo speed of sound estimation techniques, including their advantages, limitations, technical sources of variability, biological confounders and existing commercial implementations. We report the expected range of hepatic speed of sound as a function of liver steatosis and fibrosis that may be encountered in clinical practice. Ongoing efforts seek to quantify sound speed measurement accuracy and precision to inform threshold development around meaningful differences in fat fraction and between sequential measurements.

Robust Imaging of Speed of Sound Using Virtual Source Transmission

Speed of sound (SoS) is a novel imaging biomarker for assessing the biomechanical characteristics of soft tissues. SoS imaging in the pulse-echo mode using conventional ultrasound (US) systems with hand-held transducers has the potential to enable new clinical uses. Recent work demonstrated that diverging waves (DWs) from a single element (SE) transmit to outperform plane-wave sequences. However, SE transmits have severely limited power and hence produce a low signal-to-noise ratio (SNR) in echo data. We herein propose Walsh-Hadamard (WH) coded and virtual-source (VS) transmit sequences for the improved SNR in SoS imaging. We additionally present an iterative method of estimating beamforming (BF) SoS in the medium, which otherwise confounds SoS reconstructions due to beamforming inaccuracies in the images used for reconstruction. Through numerical simulations, phantom experiments, and in vivo imaging data, we show that WH is not robust against motion, which is often unavoidable in clinical imaging scenarios. Our proposed VS sequence is shown to provide the highest SoS reconstruction performance, especially robust to motion artifacts. In phantom experiments, despite having a comparable SoS root-mean-square error (RMSE) of 17.5-18.0 m/s at rest, with a minor axial probe motion of ≈ 0.67 mm/s the RMSE for SE, WH, and VS already deteriorate to 20.2, 105.4, and 19.0 m/s, respectively, showing that WH produces unacceptable results, not robust to motion. In the clinical data, the high SNR and motion resilience of VS sequences are seen to yield superior contrast compared to SE and WH sequences.

Aberration correction in diagnostic ultrasound: A review of the prior field and current directions

Medical ultrasound images are reconstructed with simplifying assumptions on wave propagation, with one of the most prominent assumptions being that the imaging medium is composed of a constant sound speed. When the assumption of a constant sound speed are violated, which is true in most in vivoor clinical imaging scenarios, distortion of the transmitted and received ultrasound wavefronts appear and degrade the image quality. This distortion is known as aberration, and the techniques used to correct for the distortion are known as aberration correction techniques. Several models have been proposed to understand and correct for aberration. In this review paper, aberration and aberration correction are explored from the early models and correction techniques, including the near-field phase screen model and its associated correction techniques such as nearest-neighbor cross-correlation, to more recent models and correction techniques that incorporate spatially varying aberration and diffractive effects, such as models and techniques that rely on the estimation of the sound speed distribution in the imaging medium. In addition to historical models, future directions of ultrasound aberration correction are proposed.

Excluding Echo Shift Noise in Real-Time Pulse-Echo Speed-of-Sound Imaging

Computed ultrasound tomography in echo mode (CUTE) allows real-time imaging of the tissue speed of sound (SoS) using handheld ultrasound. The SoS is retrieved by inverting a forward model that relates the spatial distribution of the tissue SoS to echo shift maps detected between varying transmit and receive angles. Despite promising results, in vivo SoS maps often show artifacts due to elevated noise in echo shift maps. To minimize artifacts, we propose a technique where an individual SoS map is reconstructed for each echo shift map separately, as opposed to a single SoS map from all echo shift maps simultaneously. The final SoS map is then obtained as a weighted average over all SoS maps. Due to the partial redundancy between different angle combinations, artifacts that appear only in a subset of the individual maps can be excluded via the averaging weights. We investigate this real-time capable technique in simulations using two numerical phantoms, one with a circular inclusion and one with two layers. Our results demonstrate that the SoS maps reconstructed using the proposed technique are equivalent to the ones using simultaneous reconstruction when considering uncorrupted data but show significantly reduced artifact level for data that are corrupted by noise.

Analytical estimation of beamforming speed-of-sound using transmission geometry

Most ultrasound imaging techniques necessitate the fundamental step of converting temporal signals received from transducer elements into a spatial echogenecity map. This beamforming (BF) step requires the knowledge of speed-of-sound (SoS) value in the imaged medium. An incorrect assumption of BF SoS leads to aberration artifacts, not only deteriorating the quality and resolution of conventional brightness mode (B-mode) images, hence limiting their clinical usability, but also impairing other ultrasound modalities such as elastography and spatial SoS reconstructions, which rely on faithfully beamformed images as their input. In this work, we propose an analytical method for estimating BF SoS. We show that pixel-wise relative shifts between frames beamformed with an assumed SoS is a function of geometric disparities of the transmission paths and the error in such SoS assumption. Using this relation, we devise an analytical model, the closed form solution of which yields the difference between the assumed and the true SoS in the medium. Based on this, we correct the BF SoS, which can also be applied iteratively. Both in simulations and experiments, lateral B-mode resolution is shown to be improved by ≈25% compared to that with an initial SoS assumption error of 3.3% (50m/s), while localization artifacts from beamforming are also corrected. After 5 iterations, our method achieves BF SoS errors of under 0.6m/s in simulations. Residual time-delay errors in beamforming 32 numerical phantoms are shown to reduce down to 0.07μs, with average improvements of up to 21 folds compared to initial inaccurate assumptions. We additionally show the utility of the proposed method in imaging local SoS maps, where using our correction method reduces reconstruction root-mean-square errors substantially, down to their lower-bound with actual BF SoS.

Fast volumetric ultrasound facilitates high-resolution 3D mapping of tissue compartments

Volumetric ultrasound imaging has the potential for operator-independent acquisition and enhanced field of view. Panoramic acquisition has many applications across ultrasound; spanning musculoskeletal, liver, breast, and pediatric imaging; and image-guided therapy. Challenges in high-resolution human imaging, such as subtle motion and the presence of bone or gas, have limited such acquisition. These issues can be addressed with a large transducer aperture and fast acquisition and processing. Programmable, ultrafast ultrasound scanners with a high channel count provide an unprecedented opportunity to optimize volumetric acquisition. In this work, we implement nonlinear processing and develop distributed beamformation to achieve fast acquisition over a 47-centimeter aperture. As a result, we achieve a 50-micrometer -6-decibel point spread function at 5 megahertz and resolve in-plane targets. A large volume scan of a human limb is completed in a few seconds, and in a 2-millimeter dorsal vein, the image intensity difference between the vessel center and surrounding tissue was ~50 decibels, facilitating three-dimensional reconstruction of the vasculature.

Optimization of reconstruction time of ultrasound computed tomography with a piecewise homogeneous region-based refract-ray model

In this article, a novel ultrasound computed tomography (USCT) reconstruction algorithm for breast imaging is proposed. This algorithm is based on an ultrasound propagation model, the refract-ray model (RRM). In this model, the field of imaging is assumed as piecewise homogenous and is divided into several regions. The ultrasound propagation paths are considered polylines that only refract at the borders of the regions. The edge information is provided by B-mode imaging. Both simulations and experiments are implemented to validate the proposed algorithm. Compared with the traditional bent-ray model (BRM), the time of reconstructions using RRM decreases by over 90 %. In simulations, the imaging qualities for RRM and BRM are comparable, in terms of the root mean square error, the Tenengrad value, and the deformation of digital phantom. In the experiments, a cylindrical agar phantom is imaged using a customized imaging system. When imaging using RRM, the estimate of the phantom radius is about 0.1 mm in error, while it is about 0.3 mm in error using BRM. Moreover, the Tenengrad value of the result using RRM is much higher than that using BRM (9.76 compared to 0.79). The results show that the proposed algorithm can better delineate the phantom within a water bath. In future work, further experimental work is required to validate the method for improving imaging quality under breast-mimicking imaging conditions.

A Signal Domain Object Segmentation Method for Ultrasound and Photoacoustic Computed Tomography

Image segmentation is important in improving the diagnostic capability of ultrasound computed tomography (USCT) and photoacoustic computed tomography (PACT), as it can be included in the image reconstruction process to improve image quality and quantification abilities. Segmenting the imaged object out of the background using image domain methods is easily complicated by low contrast, noise, and artifacts in the reconstructed image. Here, we introduce a new signal domain object segmentation method for USCT and PACT which does not require image reconstruction beforehand and is automatic, robust, computationally efficient, accurate, and straightforward. We first establish the relationship between the time-of-flight of the received first arrival waves and the object's boundary which is described by ellipse equations. Then, we show that the ellipses are tangent to the boundary. By looking for tangent points on the common tangent of neighboring ellipses, the boundary can be approximated with high fidelity. Imaging experiments of human fingers and mice cross-sections showed that our method provided equivalent or better segmentations than the optimal ones by active contours. In summary, our method greatly reduces the overall complexity of object segmentation and shows great potential in eliminating user dependency without sacrificing segmentation accuracy. The method can be further seamlessly incorporated into algorithms for other processing purposes in USCT and PACT, such as high-quality image reconstruction.

Distributed Aberration Correction Techniques Based on Tomographic Sound Speed Estimates

Phase aberration is widely considered a major source of image degradation in medical pulse-echo ultrasound. Traditionally, near-field phase aberration correction techniques are unable to account for distributed aberrations due to a spatially varying speed of sound in the medium, while most distributed aberration correction techniques require the use of point-like sources and are impractical for clinical applications where diffuse scattering is dominant. Here, we present two distributed aberration correction techniques that utilize sound speed estimates from a tomographic sound speed estimator that builds on our previous work with diffuse scattering in layered media. We first characterize the performance of our sound speed estimator and distributed aberration correction techniques in simulations where the scattering in the media is known a priori. Phantom and in vivo experiments further demonstrate the capabilities of the sound speed estimator and the aberration correction techniques. In phantom experiments, point target resolution improves from 0.58 to 0.26 and 0.27 mm, and lesion contrast improves from 17.7 to 23.5 and 25.9 dB, as a result of distributed aberration correction using the eikonal and wavefield correlation techniques, respectively.

Local Sound Speed Estimation for Pulse-Echo Ultrasound in Layered Media

Our previous methodology in local sound speed estimation utilized time delays measured by the cross correlation of delayed full-synthetic aperture channel data to estimate the average speed of sound. However, focal distortions in this methodology lead to biased estimates of the average speed of sound, which, in turn, leads to biased estimates of the local speed of sound. Here, we demonstrate the bias in the previous methodology and introduce a coherence-based average sound speed estimator that eliminates this bias and is computationally much cheaper in practice. Because this coherence-based approach estimates the average sound speed in the medium over an equally spaced grid in depth rather than time, we derive a refined model that relates the local and average speeds of sound as a function of depth in layered media. A fast, closed-form inversion of this model yields highly accurate local sound speed estimates. The root-mean-square (rms) error of local sound speed reconstruction in simulations of two-layer media is 4.6 and 2.5 m/s at 4 and 8 MHz, respectively. This work examines the impact of frequency, f -number, aberration, and reverberation on sound speed estimation. Phantom and in vivo experiments in rats further validate the coherence-based sound speed estimator.

Quantitative ultrasound imaging of soft biological tissues: a primer for radiologists and medical physicists

Quantitative ultrasound (QUS) aims at quantifying interactions between ultrasound and biological tissues. QUS techniques extract fundamental physical properties of tissues based on interactions between ultrasound waves and tissue microstructure. These techniques provide quantitative information on sub-resolution properties that are not visible on grayscale (B-mode) imaging. Quantitative data may be represented either as a global measurement or as parametric maps overlaid on B-mode images. Recently, major ultrasound manufacturers have released speed of sound, attenuation, and backscatter packages for tissue characterization and imaging. Established and emerging clinical applications are currently limited and include liver fibrosis staging, liver steatosis grading, and breast cancer characterization. On the other hand, most biological tissues have been studied using experimental QUS methods, and quantitative datasets are available in the literature. This educational review addresses the general topic of biological soft tissue characterization using QUS, with a focus on disseminating technical concepts for clinicians and specialized QUS materials for medical physicists. Advanced but simplified technical descriptions are also provided in separate subsections identified as such. To understand QUS methods, this article reviews types of ultrasound waves, basic concepts of ultrasound wave propagation, ultrasound image formation, point spread function, constructive and destructive wave interferences, radiofrequency data processing, and a summary of different imaging modes. For each major QUS technique, topics include: concept, illustrations, clinical examples, pitfalls, and future directions.

2D speed of sound mapping using a multilook reflection ultrasound tomography framework

Quantitative ultrasound (QUS) has emerged as a viable tool in diagnosing and staging the onset and progression of various diseases. Within the field of QUS, shear wave elastography (SWE) has emerged as the clinical standard for quantifying and correlating the stiffness of tissue to its underlying pathology. Despite its widespread use, SWE suffers from drawbacks that limit its widespread clinical use; among these are low-frame rates, long settling times, and high sensitivity to operating conditions. Longitudinal speed of sound (SOS) has emerged as a viable alternative to SWE. We propose a framework to obtain 2D sound speed maps using a commercial ultrasound probe. A commercial ultrasound probe is localized in space and used to scan a domain of interest from multiple vantage points; the use of a reflector at the far end of the domain allows us to measure the round trip travel times to and from it. The known locations of the probe and the measured travel times are used to estimate the depth and inclination of the reflector as well as the unknown sound speed map. The use of multiple looks increases the effective aperture of the ultrasound probe and allows for a higher fidelity reconstruction of sound speed maps. We validate the framework using simulated and experimental data and propose a rigorous framework to quantify the uncertainty of the estimated sound speed maps.

Speed-of-sound imaging using diverging waves

PURPOSE

Due to its safe, low-cost, portable, and real-time nature, ultrasound is a prominent imaging method in computer-assisted interventions. However, typical B-mode ultrasound images have limited contrast and tissue differentiation capability for several clinical applications.

METHODS

Recent introduction of imaging speed-of-sound (SoS) in soft tissues using conventional ultrasound systems and transducers has great potential in clinical translation providing additional imaging contrast, e.g., in intervention planning, navigation, and guidance applications. However, current pulse-echo SoS imaging methods relying on plane wave (PW) sequences are highly prone to aberration effects, therefore suboptimal in image quality. In this paper we propose using diverging waves (DW) for SoS imaging and study this comparatively to PW.

RESULTS

We demonstrate wavefront aberration and its effects on the key step of displacement tracking in the SoS reconstruction pipeline, comparatively between PW and DW on a synthetic example. We then present the parameterization sensitivity of both approaches on a set of simulated phantoms. Analyzing SoS imaging performance comparatively indicates that using DW instead of PW, the reconstruction accuracy improves by over 20% in root-mean-square-error (RMSE) and by 42% in contrast-to-noise ratio (CNR). We then demonstrate SoS reconstructions with actual US acquisitions of a breast phantom. With our proposed DW, CNR for a high contrast tumor-representative inclusion is improved by 42%, while for a low contrast cyst-representative inclusion a 2.8-fold improvement is achieved.

CONCLUSION

SoS imaging, so far only studied using a plane wave transmission scheme, can be made more reliable and accurate using DW. The high imaging contrast of DW-based SoS imaging will thus facilitate the clinical translation of the method and utilization in computer-assisted interventions such as ultrasound-guided biopsies, where B-Mode contrast is often to low to detect potential lesions.

Technical Note: Range verification of pulsed proton beams from fixed-field alternating gradient accelerator by means of time-of-flight measurement of ionoacoustic waves

PURPOSE

Ionoacoustics is one of the promising approaches to verify the beam range in proton therapy. However, the weakness of the wave signal remains a main hindrance to its application in clinics. Here we studied the potential use of a fixed-field alternating gradient accelerator (FFA), one of the accelerator candidates for future proton therapy. For such end, magnitude of the pressure wave and range accuracy achieved by the short-pulsed beam of FFA were assessed, using both simulation and experimental procedure.

METHODS

A 100 MeV proton beam from the FFA was applied on a water phantom, through the acrylic wall. The beam range measured by the Bragg peak (BP)-ionization chamber (BPC) was 77.6 mm, while the maximum dose at BP was estimated to be 0.35 Gy/pulse. A hydrophone was placed 20 mm downstream of the BP, and signals were amplified and stored by a digital oscilloscope, averaged, and low-pass filtered. Time-of-flight (TOF) and two relative TOF values were analyzed in order to determine the beam range. Furthermore, an acoustic wave transport simulation was conducted to estimate the amplitude of the pressure waves.

RESULTS

The range calculated when using two relative TOF was 78.16 ± 0.01 and 78.14 ± 0.01 mm, respectively, both values being coherent with the range measured by the BPC (the difference was 0.5-0.6 mm). In contrast, utilizing the direct TOF resulted in a range error of 1.8 mm. Fivefold and 50-fold averaging were required to suppress the range variation to below 1 mm for TOF and relative TOF measures, respectively. The simulation suggested the magnitude of pressure wave at the detector exceeded 7 Pascal.

CONCLUSION

A submillimeter range accuracy was attained with a pulsed beam of about 21 ns from an FFA, at a clinical energy using relative TOF. To precisely quantify the range with a single TOF measurement, subsequent improvement in the measuring system is required.

Robust Single-Probe Quantitative Ultrasonic Imaging System with a Target-Aware Deep Neural Network

OBJECTIVE

The speed of sound (SoS) has great potential as a quantitative imaging biomarker since it is sensitive to pathological changes in tissues. In this paper, a target-aware deep neural (TAD) network reconstructing an SoS image quantitatively from pulse-echo phase-shift maps gathered from a single conventional ultrasound probe is presented.

METHODS

In the proposed TAD network, the reconstruction process is guided by feature maps created from segmented target images for accuracy and contrast. In addition, the feature extraction process utilizes phase difference information instead of direct pulse-echo radio frequency (RF) data for robust image reconstruction against noise in the pulse-echo data.

RESULTS

The TAD network outperforms the fully convolutional network in root mean square error (RMSE), contrast-to-noise ratio (CNR), and structural similarity index (SSIM) in the presence of nearby reflectors. The measured RMSE and CNR are 5.4 m/s and 22 dB, respectively with the tissue attenuation coefficient of 2 dB/cm/MHz, which are 72% and 13 dB improvement over the state of the art design in RMSE and CNR, respectively. In the in-vivo test, the proposed method classifies the tissues in the neck area using SoS with a p-value below 0.025.

CONCLUSION

The proposed TAD network is the most accurate and robust single-probe SoS image reconstruction method reported to date.

SIGNIFICANCE

The accuracy and robustness demonstrated by the proposed SoS imaging method open up the possibilities of wide-spread clinical application of the single-probe SoS imaging system.

Comparison of ultrasound speed-of-sound of the lower extremity and lumbar muscle assessed with computed tomography for muscle loss assessment

To compare the speed of propagation of ultrasound (US) waves (SoS) of the lower leg with the clinical reference standard computed tomography (CT) at the level of lumbar vertebra 3 (L3) for muscle loss assessment. Both calf muscles of 50 patients scheduled for an abdominal CT were prospectively examined with ultrasound. A plexiglas-reflector located on the opposite side of the probe with the calf in between was used as a timing reference for SoS (m/s). CT measurements were performed at the level of L3 and included area (cm2) and attenuation (HU) of the psoas muscle, abdominal muscles, subcutaneous fat, visceral fat and abdominal area. Correlations between SoS, body mass index (BMI) and CT were determined using Pearson's correlation coefficient. Based on reported CT sarcopenia threshold values, receiver operating characteristic (ROC) analysis was performed for SoS. Inter-examiner agreement was assessed with the median difference, inter-quartile range (IQR) and intraclass correlation coefficients. SoS of the calf correlated moderately with abdominal muscle attenuation (r = 0.48; P < .001), psoas muscle attenuation (r = 0.40; P < .01), abdominal area (r = -0.44; P < .01) and weakly with subcutaneous fat area (r = -0.37; P < .01). BMI correlated weakly with psoas attenuation (r = -0.28; P < .05) and non-significantly with abdominal muscle attenuation. Normalization with abdominal area resulted in moderate correlations with abdominal muscle area for SoS (r = 0.43; P < .01) and BMI (r = -0.46; P < .001). Based on sarcopenia threshold values for skeletal muscle attenuation (SMRA), area under curve (AUC) for SoS was 0.724. Median difference between both examiners was -3.4 m/s with IQR = 15.1 m/s and intraclass correlation coefficient = 0.794. SoS measurements of the calf are moderately accurate based on CT sarcopenia threshold values, thus showing potential for muscle loss quantification.

So you think you can DAS? A viewpoint on delay-and-sum beamforming

Delay-and-sum (DAS) is the most widespread digital beamformer in high-frame-rate ultrasound imaging. Its implementation is simple and compatible with real-time applications. In this viewpoint article, we describe the fundamentals of DAS beamforming. The underlying theory and numerical approach are detailed so that users can be aware of its functioning and limitations. In particular, we discuss the importance of the f-number and speed of sound on image quality, and propose one solution to set their values from a physical viewpoint. We suggest determining the f-number from the directivity of the transducer elements and the speed of sound from the phase dispersion of the delayed signals. Simplified Matlab codes are provided for the sake of clarity and openness. The effect of the f-number and speed of sound on the lateral resolution and contrast-to-noise ratio was investigated in vitro and in vivo. If not properly preset, these two factors had a substantial negative impact on standard metrics of image quality (namely CNR and FWHM). When beamforming with DAS in vitro or in vivo, it is recommended to optimize these parameters in order to use it wisely and prevent image degradation.

Bayesian Approach for a Robust Speed-of-Sound Reconstruction Using Pulse-Echo Ultrasound

Computed ultrasound tomography in echo mode (CUTE) is a promising ultrasound (US) based multi-modal technique that allows to image the spatial distribution of speed of sound (SoS) inside tissue using hand-held pulse-echo US. It is based on measuring the phase shift of echoes when detected under varying steering angles. The SoS is then reconstructed using a regularized inversion of a forward model that describes the relation between the SoS and echo phase shift. Promising results were obtained in phantoms when using a Tikhonov-type regularization of the spatial gradient (SG) of SoS. In-vivo, however, clutter and aberration lead to an increased phase noise. In many subjects, this phase noise causes strong artifacts in the SoS image when using the SG regularization. To solve this shortcoming, we propose to use a Bayesian framework for the inverse calculation, which includes a priori statistical properties of the spatial distribution of the SoS to avoid noise-related artifacts in the SoS images. In this study, the a priori model is based on segmenting the B-Mode image. We show in a simulation and phantom study that this approach leads to SoS images that are much more stable against phase noise compared to the SG regularization. In a preliminary in-vivo study, a reproducibility in the range of 10 ms^-1 was achieved when imaging the SoS of a volunteer's liver from different scanning locations. These results demonstrate the diagnostic potential of CUTE for example for the staging of fatty liver disease.

Basic concept and clinical applications of quantitative ultrasound (QUS) technologies

In the field of clinical ultrasound, the full digitalization of diagnostic equipment in the 2000s enabled the technological development of quantitative ultrasound (QUS), followed by multiple diagnostic technologies that have been put into practical use in recent years. In QUS, tissue characteristics are quantified and parameters are calculated by analyzing the radiofrequency (RF) echo signals returning to the transducer. However, the physical properties (and pathological level structure) of the biological tissues responsible for the imaging features and QUS parameters have not been sufficiently verified as there are various conditions for observing living tissue with ultrasound and inevitable discrepancies between theoretical and actual measurements. A major issue of QUS in clinical application is that the evaluation results depend on the acquisition conditions of the RF echo signal as the source of the image information, and also vary according to the model of the diagnostic device. In this paper, typical examples of QUS techniques for evaluating attenuation, speed of sound, amplitude envelope characteristics, and backscatter coefficient in living tissues are introduced. Exemplary basic research and clinical applications related to these technologies, and initiatives currently being undertaken to establish the QUS method as a true tissue characterization technology, are also discussed.

Training Variational Networks With Multidomain Simulations: Speed-of-Sound Image Reconstruction

Speed-of-sound (SoS) has been shown as a potential biomarker for breast cancer imaging, successfully differentiating malignant tumors from benign ones. SoS images can be reconstructed from time-of-flight measurements from ultrasound images acquired using conventional handheld ultrasound transducers. Variational networks (VNs) have recently been shown to be a potential learning-based approach for optimizing inverse problems in image reconstruction. Despite earlier promising results, these methods, however, do not generalize well from simulated to acquired data, due to the domain shift. In this work, we present for the first time a VN solution for a pulse-echo SoS image reconstruction problem using diverging waves with conventional transducers and single-sided tissue access. This is made possible by incorporating simulations with varying complexity into training. We use loop unrolling of gradient descent with momentum, with an exponentially weighted loss of outputs at each unrolled iteration in order to regularize the training. We learn norms as activation functions regularized to have smooth forms for robustness to input distribution variations. We evaluate reconstruction quality on the ray-based and full-wave simulations as well as on the tissue-mimicking phantom data, in comparison with a classical iterative [limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS)] optimization of this image reconstruction problem. We show that the proposed regularization techniques combined with multisource domain training yield substantial improvements in the domain adaptation capabilities of VN, reducing the median root mean squared error (RMSE) by 54% on a wave-based simulation data set compared to the baseline VN. We also show that on data acquired from a tissue-mimicking breast phantom, the proposed VN provides improved reconstruction in 12 ms.

Improved forward model for quantitative pulse-echo speed-of-sound imaging

Computed ultrasound tomography in echo mode (CUTE) allows determining the spatial distribution of speed-of-sound (SoS) inside tissue using handheld pulse-echo ultrasound (US). This technique is based on measuring the changing phase of beamformed echoes obtained under varying transmit (Tx) and/or receive (Rx) steering angles. The SoS is reconstructed by inverting a forward model describing how the spatial distribution of SoS is related to the spatial distribution of the echo phase shift. Thanks to the straight-ray approximation, this forward model is linear and can be inverted in real-time when implemented in a state-of-the art system. Here we demonstrate that the forward model must contain two features that were not taken into account so far: (a) the phase shift must be detected between pairs of Tx and Rx angles that are centred around a set of common mid-angles, and (b) it must account for an additional phase shift induced by the offset of the reconstructed position of echoes. In a phantom study mimicking hepatic and cancer imaging, we show that both features are required to accurately predict echo phase shift among different phantom geometries, and that substantially improved quantitative SoS images are obtained compared to the model that has been used so far. The importance of the new model is corroborated by a preliminary volunteer result.

Multiperspective Ultrasound Strain Imaging of the Abdominal Aorta

Current decision-making for clinical intervention of abdominal aortic aneurysms (AAAs) is based on the maximum diameter of the aortic wall, but this does not provide patient-specific information on rupture risk. Ultrasound (US) imaging can assess both geometry and deformation of the aortic wall. However, low lateral contrast and resolution are currently limiting the precision of both geometry and local strain estimates. To tackle these drawbacks, a multiperspective scanning mode was developed on a dual transducer US system to perform strain imaging at high frame rates. Experimental imaging was performed on porcine aortas embedded in a phantom of the abdomen, pressurized in a mock circulation loop. US images were acquired with three acquisition schemes: Multiperspective ultrafast imaging, single perspective ultrafast imaging, and conventional line-by-line scanning. Image registration was performed by automatic detection of the transducer surfaces. Multiperspective images and axial displacements were compounded for improved segmentation and tracking of the aortic wall, respectively. Performance was compared in terms of image quality, motion tracking, and strain estimation. Multiperspective compound displacement estimation reduced the mean motion tracking error over one cardiac cycle by a factor 10 compared to conventional scanning. Resolution increased in radial and circumferential strain images, and circumferential signal-to-noise ratio (SNRe) increased by 10 dB. Radial SNRe is high in wall regions moving towards the transducer. In other regions, radial strain estimates remain cumbersome for the frequency used. In conclusion, multiperspective US imaging was demonstrated to improve motion tracking and circumferential strain estimation of porcine aortas in an experimental set-up.

Frequency-dependent attenuation reconstruction with an acoustic reflector

Attenuation of ultrasound waves varies with tissue composition, hence its estimation offers great potential for tissue characterization and diagnosis and staging of pathology. We recently proposed a method that allows to spatially reconstruct the distribution of the overall ultrasound attenuation in tissue based on computed tomography, using reflections from a passive acoustic reflector. This requires a standard ultrasound transducer operating in pulse-echo mode and a calibration protocol using water measurements, thus it can be implemented on conventional ultrasound systems with minor adaptations. Herein, we extend this method by additionally estimating and imaging the frequency-dependent nature of local ultrasound attenuation for the first time. Spatial distributions of attenuation coefficient and exponent are reconstructed, enabling an elaborate and expressive tissue-specific characterization. With simulations, we demonstrate that our proposed method yields a low reconstruction error of 0.04 dB/cm at 1 MHz for attenuation coefficient and 0.08 for the frequency exponent. With tissue-mimicking phantoms and ex-vivo bovine muscle samples, a high reconstruction contrast as well as reproducibility are demonstrated. Attenuation exponents of a gelatin-cellulose mixture and an ex-vivo bovine muscle sample were found to be, respectively, 1.4 and 0.5 on average, consistently from different images of their heterogeneous compositions. Such frequency-dependent parametrization could enable novel imaging and diagnostic techniques, as well as facilitate attenuation compensation of other ultrasound-based imaging techniques.

Role of Ultrasound and Photoacoustic Imaging in Photodynamic Therapy for Cancer

Photodynamic therapy (PDT) is a phototoxic treatment with high spatial and temporal control and has shown tremendous promise in the management of cancer due to its high efficacy and minimal side effects. PDT efficacy is dictated by a complex relationship between dosimetry parameters such as the concentration of the photosensitizer at the tumor site, its spatial localization (intracellular or extracellular), light dose and distribution, oxygen distribution and concentration, and the heterogeneity of the inter- and intratumoral microenvironment. Studying and characterizing these parameters, along with monitoring tumor heterogeneity pre- and post-PDT, provides essential data for predicting therapeutic response and the design of subsequent therapies. In this review, we elucidate the role of ultrasound (US) and photoacoustic imaging in improving PDT-mediated outcomes in cancer-from tracking photosensitizer uptake and vascular destruction, to measuring oxygenation dynamics and the overall evaluation of tumor responses. We also present recent advances in multifunctional theranostic nanomaterials that can improve either US or photoacoustic imaging contrast, as well as deliver photosensitizers specifically to tumors. Given the wide availability, low-cost, portability and nonionizing nature of US and photoacoustic imaging, together with their capabilities of providing multiparametric morphological and functional information, these technologies are thusly inimitable when deployed in conjunction with PDT.

Breast Cancer Assessment With Pulse-Echo Speed of Sound Ultrasound From Intrinsic Tissue Reflections: Proof-of-Concept

PURPOSE

The aim of this study was to differentiate malignant and benign solid breast lesions with a novel ultrasound (US) technique, which measures speed of sound (SoS) using standard US transducers and intrinsic tissue reflections and scattering (speckles) as internal reference.

MATERIALS AND METHODS

This prospective, institutional review board-approved, Health Insurance Portability and Accountability Act-compliant prospective comparison study was performed with prior written informed consent from 20 women. Ten women with histological proven breast cancer and 10 with fibroadenoma were measured. A conventional US system with a linear probe was used for SoS-US (SonixTouch; Ultrasonix, Richmond, British Columbia, Canada). Tissue speckle reflections served as a timing reference for the US signals transmitted through the breasts. Relative phase inconsistencies were detected using plane wave measurements from different angular directions, and SoS images with 0.5-mm resolution were generated using a spatial domain reconstruction algorithm. The SoS of tumors were compared with the breast density of a larger cohort of 106 healthy women.

RESULTS

Breast lesions show focal increments ΔSoS (meters per second) with respect to the tissue background. Peak ΔSoS values were evaluated. Breast carcinoma showed significantly higher ΔSoS than fibroadenomas ([INCREMENT]SoS > 41.64 m/s: sensitivity, 90%; specificity, 80%; area under curve, 0.910) and healthy breast tissue of different densities (area under curve, 0.938; sensitivity, 90%; specificity, 96.5%). The lesion localization in SoS-US images was consistent with B-mode imaging and repeated SoS-US measurements were reproducible.

CONCLUSIONS

Using SoS-US, based on conventional US and tissue speckles as timing reference, breast carcinoma showed significantly higher SoS values than fibroadenoma and healthy breast tissue of different densities. The SoS presents a promising technique for differentiating solid breast lesions.

The convolutional interpretation of registration-based plane wave steered pulse-echo local sound speed estimators

Pulse-echo reconstruction of sound speed has long been considered a difficult problem within the domain of quantitative biomedical ultrasound. However, recent results (Jaeger 2015 Ultrasound Med. Biol. 41 235-50; Jaeger and Frenz 2015 Ultrasonics 62 299-304; Jaeger et al 2015 Phys. Med. Biol. 60 4497-515) have demonstrated that pulse-echo reconstructions of sound speed are achievable by exploiting correlations in post-beamformed data from steered, plane-wave excitations in the presence of diffuse scatterers. Despite these recent advances, a coherent theoretical imaging framework for describing the approach and results is lacking in the literature. In this work, the problem of sound speed reconstruction using steered, plane-wave excitations is reformulated as a truncated convolutional problem, and the theoretical implications of this reformulation are explored. Additionally, a matrix-free algorithm is proposed that leverages the computational and storage advantages of the fast Fourier transform (FFT) while simultaneously avoiding FFT wraparound artifacts. In particular, the storage constraints of the approach are reduced down from [Formula: see text] to [Formula: see text] over full matrix reconstruction, making this approach a better candidate for large reconstructions on clinical machines. This algorithm was then tested in the open source simulation package k-Wave to assess its robustness to modeling error and resolution reduction was demonstrated under full-wave propagation conditions relative to ideal straight-ray simulations. The method was also validated in a phantom experiment.

Speed-of-Sound Imaging Based on Reflector Delineation

OBJECTIVE

Speed-of-sound (SoS) has large potential for tissue and pathology differentiation. We aim to develop a novel Ultrasound Computed Tomography (USCT) technique that can reconstruct local SoS in tissue on conventional ultrasound machines with hand-held linear arrays.

METHODS

A passive reflector is placed opposite the tissue sample as an echogenic reference to measure the time-of-flight (ToF) of ultrasound wave- fronts. A Dynamic Programming algorithm provides a robust ToF measurements based on global optimization of all transmit- receive echo data. An Anisotropically-Weighted Total Variation (AWTV) algorithm allows sharp delineation of focal lesions based on limited-angle USCT data.

RESULTS

Inclusions, which are not visible in conventional ultrasound, could be delineated in SoS images. AWTV allows to reconstruct focal lesions with a contrast-ratio of 93.7% of their nominal value, compared to that of 31.5% with conventional least-squares based algebraic tomographic reconstruction. In full-wave simulations of realistic heterogeneous breast models, a high CR of 84.3% is observed, with the reconstruction filtering out background heterogeneity. In experiments, our proposed method quantifies SoS in a homogeneous background with an accuracy of 0.93ms, allowing to differentiate several tissue types.

CONCLUSION

We validate our method using numerical simulations with ray-tracing and full- wave models, and phantom and ex-vivo data. Preliminary in- vivo results show the potential of this new technique to detect and differentiate malignant and benign lesions in the breast.

SIGNIFICANCE

Breast cancer is the most common cancer in women. Ultrasound B-mode only provides qualitative information about breast lesions, whereas USCT can provide quantitative tissue imaging biomarkers, such as SoS. The proposed method can potentially be implemented as a complementary modality to ultrasound for tissue and disease differentiation.