Comprehensive Comparison of Image Quality Aspects Between Conventional and Plane-Wave Imaging Methods on a Commercial Scanner.

Coherent plane-wave compound imaging (CPWCI) is used as alternative for conventional focused imaging (CFI) to increase frame rates linearly with the ratio number of imaging lines to steering angles. In this study, the image quality was compared between CPWCI and CFI, and the effect of steering angles (range and number) and beamforming strategies was evaluated in CPWCI. In automated breast volume scanners (ABVSs), which suffer from reduced volume rates, CPWCI might be an excellent candidate to replace CFI. Therefore, the image quality of CFI currently in ABVS and CPWCI was also compared in an in vivo breast lesion. Images were obtained by a Siemens Sequoia ultrasound system, and two transducers (14L5 and 10L4) in a CIRS multipurpose phantom (040GSE) and a breast lesion. Phantom results showed that contrast sensitivity and resolution, axial resolution, and generalized contrast-to-noise ratio (gCNR; imaging depths <45 mm) were similar for most imaging sequences. CNR (imaging depths ≥45 mm), penetration, and lateral resolution were significantly improved for CPWCI (15 angles) compared to CFI for both transducers. In CPWCI, certain combinations of steering angles and beamforming methods yielded improved gCNR (small angles and delay-and-sum) or lateral resolution (large angles and Lu's-fk). Image quality seemed similar between CPWCI and CFI (three angles incoherent compounded as in ABVS) by visual inspection of the in vivo breast lesion images.

Radiological Society of North America/Quantitative Imaging Biomarker Alliance Shear Wave Speed Bias Quantification in Elastic and Viscoelastic Phantoms.

OBJECTIVES: To quantify the bias of shear wave speed (SWS) measurements between different commercial ultrasonic shear elasticity systems and a magnetic resonance elastography (MRE) system in elastic and viscoelastic phantoms. METHODS: Two elastic phantoms, representing healthy through fibrotic liver, were measured with 5 different ultrasound platforms, and 3 viscoelastic phantoms, representing healthy through fibrotic liver tissue, were measured with 12 different ultrasound platforms. Measurements were performed with different systems at different sites, at 3 focal depths, and with different appraisers. The SWS bias across the systems was quantified as a function of the system, site, focal depth, and appraiser. A single MRE research system was also used to characterize these phantoms using discrete frequencies from 60 to 500 Hz. RESULTS: The SWS from different systems had mean difference 95% confidence intervals of ±0.145 m/s (±9.6%) across both elastic phantoms and ± 0.340 m/s (±15.3%) across the viscoelastic phantoms. The focal depth and appraiser were less significant sources of SWS variability than the system and site. Magnetic resonance elastography best matched the ultrasonic SWS in the viscoelastic phantoms using a 140 Hz source but had a - 0.27 ± 0.027-m/s (-12.2% ± 1.2%) bias when using the clinically implemented 60-Hz vibration source. CONCLUSIONS: Shear wave speed reconstruction across different manufacturer systems is more consistent in elastic than viscoelastic phantoms, with a mean difference bias of < ±10% in all cases. Magnetic resonance elastographic measurements in the elastic and viscoelastic phantoms best match the ultrasound systems with a 140-Hz excitation but have a significant negative bias operating at 60 Hz. This study establishes a foundation for meaningful comparison of SWS measurements made with different platforms.

Three-dimensional US for Quantification of Volumetric Blood Flow: Multisite Multisystem Results from within the Quantitative Imaging Biomarkers Alliance.

Background Quantitative blood flow (QBF) measurements that use pulsed-wave US rely on difficult-to-meet conditions. Imaging biomarkers need to be quantitative and user and machine independent. Surrogate markers (eg, resistive index) fail to quantify actual volumetric flow. Standardization is possible, but relies on collaboration between users, manufacturers, and the U.S. Food and Drug Administration. Purpose To evaluate a Quantitative Imaging Biomarkers Alliance-supported, user- and machine-independent US method for quantitatively measuring QBF. Materials and Methods In this prospective study (March 2017 to March 2019), three different clinical US scanners were used to benchmark QBF in a calibrated flow phantom at three different laboratories each. Testing conditions involved changes in flow rate (1-12 mL/sec), imaging depth (2.5-7 cm), color flow gain (0%-100%), and flow past a stenosis. Each condition was performed under constant and pulsatile flow at 60 beats per minute, thus yielding eight distinct testing conditions. QBF was computed from three-dimensional color flow velocity, power, and scan geometry by using Gauss theorem. Statistical analysis was performed between systems and between laboratories. Systems and laboratories were anonymized when reporting results. Results For systems 1, 2, and 3, flow rate for constant and pulsatile flow was measured, respectively, with biases of 3.5% and 24.9%, 3.0% and 2.1%, and -22.1% and -10.9%. Coefficients of variation were 6.9% and 7.7%, 3.3% and 8.2%, and 9.6% and 17.3%, respectively. For changes in imaging depth, biases were 3.7% and 27.2%, -2.0% and -0.9%, and -22.8% and -5.9%, respectively. Respective coefficients of variation were 10.0% and 9.2%, 4.6% and 6.9%, and 10.1% and 11.6%. For changes in color flow gain, biases after filling the lumen with color pixels were 6.3% and 18.5%, 8.5% and 9.0%, and 16.6% and 6.2%, respectively. Respective coefficients of variation were 10.8% and 4.3%, 7.3% and 6.7%, and 6.7% and 5.3%. Poststenotic flow biases were 1.8% and 31.2%, 5.7% and -3.1%, and -18.3% and -18.2%, respectively. Conclusion Interlaboratory bias and variation of US-derived quantitative blood flow indicated its potential to become a clinical biomarker for the blood supply to end organs. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Forsberg in this issue.

Novel Method for Ultrasound-Derived Fat Fraction Using an Integrated Phantom.

OBJECTIVES: The purpose of this study was to demonstrate the clinical feasibility of an integrated reference phantom method for quantitative ultrasound by creating an ultrasound-derived fat fraction (UDFF) tool. This tool was evaluated with respect to its diagnostic performance as a biomarker for assessing histologic hepatic steatosis and its agreement with the magnetic resonance imaging (MRI) proton density fat fraction (PDFF). METHODS: Adults (n = 101) with known or suspected nonalcoholic fatty liver disease consented to participate in this prospective cross-sectional study. All patients underwent MRI-PDFF and ultrasound scans, whereas 90 underwent liver biopsy. A linear least-squares analysis used the attenuation coefficient and backscatter coefficient to create the UDFF model for predicting MRI-PDFF. RESULTS: The area under the receiver operating characteristic curve values were 0.94 (95% confidence interval [CI], 0.85-0.98) for histologic steatosis grade 0 (n = 6) versus 1 or higher (n = 84), 0.88 (95% CI, 0.8-0.94) for grade 1 or lower (n = 45) versus 2 or higher (n = 45), and 0.83 (95% CI, 0.73-0.9) for grade 2 or lower (n = 78) versus 3 (n = 12). The Pearson correlation coefficient between UDFF and PDFF was ρ = 0.87 with 95% limits of agreement of ±8.5%. Additionally, the diagnosis of steatosis, defined as MRI-PDFF higher than 5% and 10%, had area under the receiver operating characteristic curve values of 0.97 (95% CI, 0.93-0.99) and 0.95 (95% CI, 0.9-0.98), respectively. The body mass index was not correlated with either UDFF or PDFF. CONCLUSIONS: An on-system, integrated UDFF tool provides a simple, noninvasive, accessible, low-cost, and commercially viable clinical tool for quantifying the hepatic fat fraction with a high degree of agreement with histologic biopsy or the MRI-PDFF biomarker.

Power Spectrum Consistency among Systems and Transducers.

Use of the reference phantom method for computing acoustic attenuation and backscatter is widespread. However, clinical application of these methods has been limited by the need to acquire reference phantom data. We determined that the data acquired from 11 transducers of the same model and five clinical ultrasound systems of the same model produce equivalent estimates of reference phantom power spectra. We describe that the contribution to power spectral density variance among systems and transducers equals that from speckle variance with 59 uncorrelated echo signals. Thus, when the number of uncorrelated lines of data is small, speckle variance will dominate the power spectral density estimate variance introduced by different systems and transducers. These results suggest that, at least for this particular transducer and imaging system combination, one set of reference phantom calibration data is highly representative of the average among equivalent transducers and systems that are in good working order.

Three-dimensional Ultrasound Elasticity Imaging on an Automated Breast Volume Scanning System.

Ultrasound elasticity imaging has demonstrated utility in breast imaging, but it is typically performed with handheld transducers and two-dimensional imaging. Two-dimensional (2D) elastography images tissue stiffness of only a plane and hence suffers from errors due to out-of-plane motion, whereas three-dimensional (3D) data acquisition and motion tracking can be used to track out-of-plane motion that is lost in 2D elastography systems. A commercially available automated breast volume scanning system that acquires 3D ultrasound data with precisely controlled elevational movement of the 1D array ultrasound transducer was employed in this study. A hybrid guided 3D motion-tracking algorithm was developed that first estimated the displacements in one plane using a modified quality-guided search method, and then performed an elevational guided-search for displacement estimation in adjacent planes. To assess the performance of the method, 3D radiofrequency echo data were acquired with this system from a phantom and from an in vivo human breast. For both experiments, the axial displacement fields were smooth and high cross-correlation coefficients were obtained in most of the tracking region. The motion-tracking performance of the new method was compared with a correlation-based exhaustive-search method. For all motion-tracking volume pairs, the average motion-compensated cross-correlation values obtained by the guided-search motion-tracking method were equivalent to those by the exhaustive-search method, and the computation time was about a factor of 10 lesser. Therefore, the proposed 3D ultrasound elasticity imaging method was a more efficient approach to produce a high quality of 3D ultrasound strain image.

Automated 3D ultrasound elastography of the breast: a phantom validation study.

In breast cancer screening, the automated breast volume scanner (ABVS) was introduced as an alternative for mammography since the latter technique is less suitable for women with dense breasts. Although clinical studies show promising results, clinicians report two disadvantages: long acquisition times (>90 s) introducing breathing artefacts, and high recall rates due to detection of many small lesions of uncertain malignant potential. Technical improvements for faster image acquisition and better discrimination between benign and malignant lesions are thus required. Therefore, the aim of this study was to investigate if 3D ultrasound elastography using plane-wave imaging is feasible. Strain images of a breast elastography phantom were acquired by an ABVS-mimicking device that allowed axial and elevational movement of the attached transducer. Pre- and post-deformation volumes were acquired with different constant speeds (between 1.25 and 40.0 mm s(-1)) and by three protocols: Go-Go (pre- and post-volumes with identical start and end positions), Go-Return (similar to Go-Go with opposite scanning directions) and Control (pre- and post-volumes acquired per position, this protocol can be seen as reference). Afterwards, 2D and 3D cross-correlation and strain algorithms were applied to the acquired volumes and the results were compared. The Go-Go protocol was shown to be superior with better strain image quality (CNRe and SNRe) than Go-Return and to be similar as Control. This can be attributed to applying opposite mechanical forces to the phantom during the Go-Return protocol, leading to out-of-plane motion. This motion was partly compensated by using 3D cross-correlation. However, the quality was still inferior to Go-Go. Since these results were obtained in a phantom study with controlled deformations, the effect of possible uncontrolled in vivo tissue motion artefacts has to be addressed in future studies. In conclusion, it seems feasible to implement 3D ultrasound quasi-static elastography on an ABVS-like system and to reduce scan times within one breath-hold (~10 s) by plane-wave acquisitions.