First-arrival traveltime sound speed inversion with a priori information

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.

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.

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.

Error analysis of speed of sound reconstruction in ultrasound limited angle transmission tomography

We have investigated limited angle transmission tomography to estimate speed of sound (SOS) distributions for breast cancer detection. That requires both accurate delineations of major tissues, in this case by segmentation of prior B-mode images, and calibration of the relative positions of the opposed transducers. Experimental sensitivity evaluation of the reconstructions with respect to segmentation and calibration errors is difficult with our current system. Therefore, parametric studies of SOS errors in our bent-ray reconstructions were simulated. They included mis-segmentation of an object of interest or a nearby object, and miscalibration of relative transducer positions in 3D. Close correspondence of reconstruction accuracy was verified in the simplest case, a cylindrical object in homogeneous background with induced segmentation and calibration inaccuracies. Simulated mis-segmentation in object size and lateral location produced maximum SOS errors of 6.3% within 10 mm diameter change and 9.1% within 5 mm shift, respectively. Modest errors in assumed transducer separation produced the maximum SOS error from miscalibrations (57.3% within 5 mm shift), still, correction of this type of error can easily be achieved in the clinic. This study should aid in designing adequate transducer mounts and calibration procedures, and in specification of B-mode image quality and segmentation algorithms for limited angle transmission tomography relying on ray tracing algorithms.

Acoustic attenuation imaging of tissue bulk properties with a priori information

Attenuation of ultrasound waves traversing a medium is not only a result of absorption and scattering within a given tissue, but also of coherent scattering, including diffraction, refraction, and reflection of the acoustic wave at tissue boundaries. This leads to edge enhancement and other artifacts in most reconstruction algorithms, other than 3D wave migration with currently impractical, implementations. The presented approach accounts for energy loss at tissue boundaries by normalizing data based on variable sound speed, and potential density, of the medium using a k-space wave solver. Coupled with a priori knowledge of major sound speed distributions, physical attenuation values within broad ranges, and the assumption of homogeneity within segmented regions, an attenuation image representative of region bulk properties is constructed by solving a penalized weighted least squares optimization problem. This is in contradistinction to absorption or to conventional attenuation coefficient based on overall insertion loss with strong dependence on sound speed and impedance mismatches at tissue boundaries. This imaged property will be referred to as the bulk attenuation coefficient. The algorithm is demonstrated on an opposed array setup, with mean-squared-error improvements from 0.6269 to 0.0424 (dB/cm/MHz)² for a cylindrical phantom, and 0.1622 to 0.0256 (dB/cm/MHz)² for a windowed phantom.

Automated 3D ultrasound image segmentation to aid breast cancer image interpretation

Segmentation of an ultrasound image into functional tissues is of great importance to clinical diagnosis of breast cancer. However, many studies are found to segment only the mass of interest and not all major tissues. Differences and inconsistencies in ultrasound interpretation call for an automated segmentation method to make results operator-independent. Furthermore, manual segmentation of entire three-dimensional (3D) ultrasound volumes is time-consuming, resource-intensive, and clinically impractical. Here, we propose an automated algorithm to segment 3D ultrasound volumes into three major tissue types: cyst/mass, fatty tissue, and fibro-glandular tissue. To test its efficacy and consistency, the proposed automated method was employed on a database of 21 cases of whole breast ultrasound. Experimental results show that our proposed method not only distinguishes fat and non-fat tissues correctly, but performs well in classifying cyst/mass. Comparison of density assessment between the automated method and manual segmentation demonstrates good consistency with an accuracy of 85.7%. Quantitative comparison of corresponding tissue volumes, which uses overlap ratio, gives an average similarity of 74.54%, consistent with values seen in MRI brain segmentations. Thus, our proposed method exhibits great potential as an automated approach to segment 3D whole breast ultrasound volumes into functionally distinct tissues that may help to correct ultrasound speed of sound aberrations and assist in density based prognosis of breast cancer.

Modeling of wave propagation for medical ultrasound: a review

Numerical modeling of medical ultrasound has advanced tremendously in the past two decades. This opens up a great number of opportunities for medical ultrasound and associated technologies. Numerous new governing equations and algorithms have emerged and been applied to studying various medical ultrasound applications, including ultrasound imaging, photo-acoustic imaging, and therapeutic ultrasound. In addition, thanks to the rapid development of computers, modeling acoustic wave propagation in three-dimensional, large-scale domains has become a reality. This article will provide an indepth literature and technical review of recent progress on numerical modeling of medical ultrasound. Future challenges will also be discussed.

Towards clinical computed ultrasound tomography in echo-mode: Dynamic range artefact reduction

Computed ultrasound tomography in echo-mode (CUTE) allows imaging the speed of sound inside tissue using hand-held pulse-echo ultrasound. This technique is based on measuring the changing local phase of beamformed echoes when changing the transmit beam steering angle. Phantom results have shown a spatial resolution and contrast that could qualify CUTE as a promising novel diagnostic modality in combination with B-mode ultrasound. Unfortunately, the large intensity range of several tens of dB that is encountered in clinical images poses difficulties to echo phase tracking and results in severe artefacts. In this paper we propose a modification to the original technique by which more robust echo tracking can be achieved, and we demonstrate in phantom experiments that dynamic range artefacts are largely eliminated. Dynamic range artefact reduction also allowed for the first time a clinical implementation of CUTE with sufficient contrast to reproducibly distinguish the different speed of sound in different tissue layers of the abdominal wall and the neck.