A Locally Adaptive Phase Aberration Correction (LAPAC) Method for Synthetic Aperture Sequences.

Phase aberration is a phenomenon caused by heterogeneity of the speed of sound in tissue, in which the actual speed of sound of the tissue is different than the assumed speed of sound used for beamforming. It reduces the quality and resolution of ultrasonic images and impairs clinical diagnostic capabilities. Although phase aberration correction (PAC) methods can reduce these detrimental effects, most practical implementations of PAC methods are based on the near field phase screen model, which have limited ability to represent the true aberration induced by inhomogeneous tissue. Accordingly, we propose a locally adaptive phase aberration correction (LAPAC) method that is applied through the use of synthetic aperture. The method is tested using full-wave simulations of models of human abdominal wall, experiments with tissue aberrators, and in vivo carotid images. LAPAC is compared with conventional phase aberration correction (cPAC) where aberration profiles are computed at a preselected depth and applied to the beamformer's time delays. For all experiments, LAPAC shows an average of 1 to 2 dB higher contrast than cPAC, and enhancements of 3 to 7 dB with respect to the uncorrected cases. We conclude that LAPAC may be a viable option to enhance ultrasound image quality images even in the presence of clinically relevant aberrating conditions.

Effects of Phase Aberration and Phase Aberration Correction on the Minimum Variance Beamformer.

The minimum variance (MV) beamformer has the potential to enhance the resolution and contrast of ultrasound images but is sensitive to steering vector errors. Robust MV beamformers have been proposed but mainly evaluated in the presence of gross sound speed mismatches, and the impact of phase aberration correction (PAC) methods in mitigating the effects of phase aberration in MV beamformed images has not been explored. In this study, an analysis of the effects of aberration on conventional MV and eigenspace MV (ESMV) beamformers is carried out. In addition, the impact of three PAC algorithms on the performance of MV beamforming is analyzed. The different beamformers were tested on simulated data and on experimental data corrupted with electronic and tissue-based aberration. It is shown that all gains in performance of the MV beamformer with respect to delay-and-sum (DAS) are lost at high aberration strengths. For instance, with an electronic aberration of 60 ns, the lateral resolution of DAS degrades by 17% while MV degrades by 73% with respect to the images with no aberration. Moreover, although ESMV shows robustness at low aberration levels, its degradation at higher aberrations is approximately the same as that of regular MV. It is also shown that basic PAC methods improve the aberrated MV beamformer. For example, in the case of electronic aberration, multi-lag reduces degradation in lateral resolution from 73% to 28% and contrast loss from 85% to 25%. These enhancements allow the combination of MV and PAC to outperform DAS and PAC and ESMV in moderate and strong aberrations. We conclude that the effect of aberration on the MV beamformer is stronger than previously reported in the literature and that PAC is needed to improve its clinical potential.

Temporal artifact minimization in sonoelastography through optimal selection of imaging parameters.

Sonoelastography is an ultrasonic technique that uses Kasai's autocorrelation algorithms to generate qualitative images of tissue elasticity using external mechanical vibrations. In the absence of synchronization between the mechanical vibration device and the ultrasound system, the random initial phase and finite ensemble length of the data packets result in temporal artifacts in the sonoelastography frames and, consequently, in degraded image quality. In this work, the analytic derivation of an optimal selection of acquisition parameters (i.e., pulse repetition frequency, vibration frequency, and ensemble length) is developed in order to minimize these artifacts, thereby eliminating the need for complex device synchronization. The proposed rule was verified through experiments with heterogeneous phantoms, where the use of optimally selected parameters increased the average contrast-to-noise ratio (CNR) by more than 200% and reduced the CNR standard deviation by 400% when compared to the use of arbitrarily selected imaging parameters. Therefore, the results suggest that the rule for specific selection of acquisition parameters becomes an important tool for producing high quality sonoelastography images.

Hippocampal subfield imaging and fractional anisotropy show parallel changes in Alzheimer's disease tau progression using simultaneous tau-PET/MRI at 3T.

INTRODUCTION: Alzheimer's disease (AD) is the most common form of dementia, characterized primarily by abnormal aggregation of two proteins, tau and amyloid beta. We assessed tau pathology and white matter connectivity changes in subfields of the hippocampus simultaneously in vivo in AD. METHODS: Twenty-four subjects were scanned using simultaneous time-of-flight 18F-PI-2620 tau positron emission tomography/3-Tesla magnetic resonance imaging and automated segmentation. RESULTS: We observed extensive tau elevation in the entorhinal/perirhinal regions, intermediate tau elevation in cornu ammonis 1/subiculum, and an absence of tau elevation in the dentate gyrus, relative to controls. Diffusion tensor imaging showed parahippocampal gyral fractional anisotropy was lower in AD and mild cognitive impairment compared to controls and strongly correlated with early tau accumulation in the entorhinal and perirhinal cortices. DISCUSSION: This study demonstrates the potential for quantifiable patterns of 18F-PI2620 binding in hippocampus subfields, accompanied by diffusion and volume metrics, to be valuable markers of AD.

Effects of phase aberration correction methods on the minimum variance beamformer.

The minimum variance (MV) beamformer is a method that has the potential to enhance the resolution and contrast of ultrasound images. However, it suffers from sensitivity to speed of sound errors and aberration. Although there have been several studies on the application of phase aberration correction (PAC) methods to conventional delay-and-sum (DAS) beamforming, the benefits of PAC methods in mitigating the effects of phase aberration in MV beamformed images are not well understood. A study of this type would be helpful in designing a robust beamformer based on PAC knowledge present in the literature. This study analyzes three PAC algorithms (multi-lag cross-correlation, Rigby's beamsum and scaled covariance matrix) and their impact on the performance of the MV beamformer in the presence of second order phase aberrations. The PAC methods in combination with the MV beamformer were tested on simulated and experimental data corrupted with an electronically created near field phase aberrator. It is shown that all gains in performance of the MV beamformer with respect to DAS is lost at high aberration strengths. For instance, at 60 ns of aberration the lateral resolution of DAS degrades by 22% while MV degrades by 600%. It is also shown that basic PAC methods improve the aberrated MV beamformer. PAC methods reduces degradation in lateral resolution from 600% to 5%. Similar improvements are observed in peak sidelobe level (96% to 27%), contrast (88% to 49% for the simulations and 43% to 15% for experiments) and contrast-to-noise ratio (86% to 42% for the simulations and 68% to 55% for experiments). These enhancements allow the MV beamformer to outperform DAS even in the strongest aberration case.