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Native American individuals are more frequently affected by cerebrovascular diseases including stroke and vascular cognitive decline. The aim of this study was to determine stroke risk factors that are most prevalent in Wisconsin Native Americans and to examine how education at the community and individual level as well as intensive health wellness coaching may influence modification of stroke risk factors. Additionally, we will investigate the role novel stroke biomarkers may play in stroke risk in this population. This paper details the aims and methods employed in the "Stroke Prevention in the Wisconsin Native American Population" (clinicaltrials.gov identifier: NCT04382963) study including participant health assessments, clinical ultrasound exam of the carotid arteries, cognitive testing battery, and structure and execution of the coaching program. [ABSTRACT FROM AUTHOR]

Three-dimensional ultrasound (3D US) imaging with freehand scanning is utilized in cardiac, obstetric, abdominal, and vascular examinations. While 3D US using either a 'wobbler' or 'matrix' transducer suffers from a small field of view and low acquisition rates, freehand scanning offers significant advantages due to its ease of use. However, current 3D US volumetric reconstruction methods with freehand sweeps are limited by imaging plane shifts along the scanning path, i.e., out-of-plane (OOP) motion. Prior studies have incorporated motion sensors attached to the transducer, which is cumbersome and inconvenient in a clinical setting. Recent work has introduced deep neural networks (DNNs) with 3D convolutions to estimate the position of imaging planes from a series of input frames. These approaches, however, fall short for estimating OOP motion. The goal of this paper is to bridge the gap by designing a novel, physics inspired DNN for freehand 3D US reconstruction without motion sensors, aiming to improve the reconstruction quality, and at the same time, to reduce computational resources needed for training and inference. To this end, we present our physics guided learning-based prediction of pose information (PLPPI) model for 3D freehand US reconstruction without 3D convolution. PLPPI yields significantly more accurate reconstructions and offers a major reduction in computation time. It attains a performance increase in the double digits in terms of mean percentage error, with up to 106% speedup and 131% reduction in Graphic Processing Unit (GPU) memory usage, when compared to latest deep learning methods.

Objective: In humans, arterial grayscale ultrasound texture features independently predict adverse cardiovascular disease (CVD) events and change with medical interventions. We performed this study to examine how grayscale ultrasound texture features and elastin fibers change in plaque-free segments of the arterial wall in a murine model prone to atherosclerosis., Methods: A total of 10 Apoe tm1Unc/J mice ( n  = 5 male, n  = 5 female) were imaged at 6, 16, and 24 weeks of age. Two mice were euthanized at 6 and 16 weeks and the remaining mice at 24 weeks. Texture features were extracted from the ultrasound images of the distal 1.0 mm of the common carotid artery wall, and elastin measures were extracted from histology images. Two-way analysis of variance was used to evaluate associations between week, sex, and grayscale texture features. Texture feature and elastin number comparisons between weeks were conducted using the sex-by-week two-way interaction contrasts. Sex-specific correlations between the number of elastin fibers and grayscale texture features were analyzed by conducting non-parametric Spearman's rank correlation analyses., Results: Arterial wall homogeneity changed significantly in male mice from 6 to 24 weeks, with a mean (SD) of 0.14 (0.03) units at 6 weeks and 0.18 (0.03) units at 24 weeks ( p  = 0.026). Spatial gray level dependence matrices-homogeneity (SGLD-HOM) also correlated with carotid artery plaque score ( r s  = 0.707, p  = 0.033). Elastin fibers in the region of interest decreased from 6 to 24 weeks for both male and female mice, although only significantly in male mice. The mean (SD) number of elastin fibers for male mice was 5.32 (1.50) at 6 weeks and 3.59 (0.38) at 24 weeks ( p  = 0.023). For female mice, the mean (SD) number of elastin fibers was 3.98 (0.38) at 6 weeks and 3.46 (0.19) at 24 weeks ( p  = 0.051)., Conclusion: Grayscale ultrasound texture features that are associated with increased risk for CVD events in humans were used in a murine model, and the grayscale texture feature SGLD-HOM was shown to change in male mice from 6 weeks to 24 weeks. Structural alterations of the arterial wall (change in elastin fiber number) were observed during this time and may differ by sex., Competing Interests: CM: W. L. Gore & Associates contracted research grants to the University of Wisconsin-Madison, consulting Acoustic Range Estimates. TV: Research agreement with Fujifilm VisualSonics (Toronto, CA) to acquire photoacoustic radiofrequency data not used in this paper. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2023 Mitchell, Al Mukaddim, Liu, Graham, Eickhoff, Weichmann, Tattersall, Korcarz, Stein, Varghese and Eliceiri.)

Minimum variance (MV) beamforming improves resolution and reduces sidelobes when compared to delay-and-sum (DAS) beamforming for photoacoustic imaging (PAI). However, some level of sidelobe signal and incoherent clutter persist degrading MV PAI quality. Here, an adaptive beamforming algorithm (PSAPMV) combining MV formulation and sub-aperture processing is proposed. In PSAPMV, the received channel data are split into two complementary nonoverlapping sub-apertures and beamformed using MV. A weighting matrix based on similarity between sub-aperture beamformed images was derived and multiplied with the full aperture MV image resulting in suppression of sidelobe and incoherent clutter in the PA image. Numerical simulation experiments with point targets, diffuse inclusions and microvasculature networks are used to validate PSAPMV. Quantitative evaluation was done in terms of main-lobe-to-side-lobe ratio, full width at half maximum (FWHM), contrast ratio (CR) and generalized contrast-to-noise ratio (gCNR). PSAPMV demonstrated improved beamforming performance both qualitatively and quantitatively. PSAPMV had higher resolution (FWHM =0.19 mm) than MV (0.21 mm) and DAS (0.22mm) in point target simulations, better target detectability (gCNR =0.99) than MV (0.89) and DAS (0.84) for diffuse inclusions and improved contrast (CR in microvasculature simulation, DAS = 15.38, MV = 22.42, PSAPMV = 51.74 dB).

A cardiac strain imaging framework with adaptive Bayesian regularization (ABR) is proposed for in vivo assessment of murine cardiac function. The framework uses ultrasound (US) radio-frequency data collected with a high frequency (f c = 30MHz) imaging system and a multi-level block matching algorithm with ABR to derive inter-frame cardiac displacements. Lagrangian cardiac strain (radial, e r and longitudinal, e l ) tensors were derived by segmenting the myocardial wall starting at the ECG R-wave and accumulating interframe deformations over a cardiac cycle. In vivo feasibility was investigated through a longitudinal study with two mice (one ischemia-perfusion (IR) injury and one sham) imaged at five sessions (pre-surgery (BL) and 1,2,7 and 14 days post-surgery). End-systole (ES) strain images and segmental strain curves were derived for quantitative evaluation. Both mice showed periodic variation of e r and e l strain at BL with segmental synchroneity. Infarcted regions of IR mouse at Day 14 were associated with reduced or sign reversed ES e r and e l values while the sham mouse had similar or higher strain than at BL. Infarcted regions identified in vivo were associated with increased collagen content confirmed with Masson's Trichrome stained ex vivo heart sections.Clinical Relevance-Higher quality cardiac strain images derived with RF data and Bayesian regularization can potentially improve the sensitivity and accuracy of non-invasive assessment of cardiovascular disease models.