Methods in Stroke Prevention in the Wisconsin Native American Population.

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.

Carotid Plaque Strain Indices Were Correlated With Cognitive Performance in a Cohort With Advanced Atherosclerosis, and Traditional Doppler Measures Showed no Association.

OBJECTIVES: Traditional Doppler measures have been used to predict cognitive performance in patients with carotid atherosclerosis. Novel measures, such as carotid plaque strain indices (CPSIs), have shown associations with cognitive performance. We hypothesized that lower mean middle cerebral artery (MCA) velocities, higher bulb-internal carotid artery (ICA) velocities, the MCA pulsatility index (PI), and CPSIs would be associated with poorer cognitive performance in individuals with advanced atherosclerosis. METHODS: Neurocognitive testing, carotid ultrasound imaging, transcranial Doppler imaging, and carotid strain imaging were performed on 40 patients scheduled for carotid endarterectomy. Kendall tau correlations were used to examine relationships between cognitive tests and the surgical-side maximum peak systolic velocity (PSV; from the bulb, proximal, mid, or distal ICA), mean MCA velocity and PI, and maximum CPSIs (axial, lateral, and shear strain indices used to characterize plaque deformations with arterial pulsation). Cognitive measures included age-adjusted indices of verbal fluency, verbal and visual learning/memory, psychomotor speed, auditory attention/working memory, visuospatial construction, and mental flexibility. RESULTS: Participants had a median age of 71.0 (interquartile range, 9.75) years; 26 were male (65%), and 14 were female (35%). Traditional Doppler parameters, PSV, mean MCA velocity, and MCA PI did not predict cognitive performance (all P > .05). Maximum CPSIs were significantly associated with cognitive performance (P < .05). CONCLUSIONS: Traditional velocity measurements of the maximum bulb-ICA PSV, mean MCA velocity, and PI were not associated with cognitive performance in patients with advanced atherosclerotic disease; however, maximum CPSIs were associated with cognitive performance. These findings suggest that cognition may be associated with unstable plaque rather than blood flow.

Deep Learning for Carotid Plaque Segmentation using a Dilated U-Net Architecture.

Carotid plaque segmentation in ultrasound longitudinal B-mode images using deep learning is presented in this work. We report on 101 severely stenotic carotid plaque patients. A standard U-Net is compared with a dilated U-Net architecture in which the dilated convolution layers were used in the bottleneck. Both a fully automatic and a semi-automatic approach with a bounding box was implemented. The performance degradation in plaque segmentation due to errors in the bounding box is quantified. We found that the bounding box significantly improved the performance of the networks with U-Net Dice coefficients of 0.48 for automatic and 0.83 for semi-automatic segmentation of plaque. Similar results were also obtained for the dilated U-Net with Dice coefficients of 0.55 for automatic and 0.84 for semi-automatic when compared to manual segmentations of the same plaque by an experienced sonographer. A 5% error in the bounding box in both dimensions reduced the Dice coefficient to 0.79 and 0.80 for U-Net and dilated U-Net respectively.

Carotid artery displacement and cardiovascular disease risk in the Multi-Ethnic Study of Atherosclerosis.

Novel technology permits quantification of common carotid artery (CCA) displacement, which is traditionally ignored. We evaluated associations with CCA displacement and cardiovascular disease (CVD) risk and events in a large, multi-ethnic cohort. Right CCA longitudinal displacement (LD), transverse displacement (TD), and grayscale median (GSM) were evaluated using ultrasound speckle-tracking and texture analysis software in 2050 participants. Regression analyses were used to define relationships between CCA LD, TD, GSM, and CVD risk factors. Cox proportional hazards models were used to assess relationships between LD, TD, and incident CVD events. Participants were mean (SD) 64 (10) years old. There were 791 cases with a CVD event over a 12-year median follow-up. The mean LD was 0.29 (0.20) mm. In multivariable models including age, sex, race/ethnicity, heart rate, and CVD risk factors, LD was associated positively with active smoking (ß = 0.08, p < 0.001) and inversely with black (ß = -0.08, p < 0.001), Chinese (ß = -0.05, p < 0.001), and Hispanic (ß = -0.04, p < 0.05) race/ethnicities relative to white individuals, heart rate (ß = -0.03/10 beats/min, p < 0.001), and diastolic blood pressure (ß = -0.01/5 mmHg, p < 0.05). In fully adjusted models, LD and TD were associated with GSM (p < 0.01), but neither predicted incident CVD events (LD: hazard ratio (HR) 0.77 [0.48 to 1.24], p = 0.3; TD: HR 1.12 [0.8 to 1.57], p = 0.5). CCA LD and TD are associated with race/ethnicity and CVD risk factors but not incident CVD events. LD and TD are not measures of arterial stiffness but their association with GSM suggests that lower LD and TD may be related to structural changes within the carotid arterial wall.

Influence of Ultrasound System and Gain on Grayscale Median Values.

OBJECTIVES: The purpose of this study was to determine the reliability of grayscale median (GSM) measurements across different ultrasound (US) systems and effects of gain on GSM values. METHODS: Two vessels in a grayscale vascular phantom were imaged with 7 US systems at 3 gain settings. Two human participants were imaged at 3 gain settings. Each image was normalized, standardized, and segmented by expert and novice readers using grayscale analysis software. The concordance correlation coefficient (CCC) assessed agreement of GSM values for each system across gain settings and vessels and between readers. The intraclass correlation coefficient (ICC) assessed system-level reader concordance across gain settings and vessels. A general linear mixed model for repeated measures was used to assess within- and between-system mean GSM values. RESULTS: Grayscale median measurements performed on images from the same US system yielded excellent (CCC) (95% confidence intervals): 0.85 (0.75, 0.92) to 0.96 (0.92, 0.98). ICC per system were 0.94 to 0.98 for the expert reader and 0.85 to 0.95 for the novice reader. Gain adjustments above and below an optimal setting contributed to significantly different intrasystem GSM values on 4 of 7 systems in the near zone and 5 of 7 systems in the far zone (P < .05). Intersystem GSM values differed on 5 of 7 systems (P < .05). Images from the human participants showed differences in GSM values at optimum gain values ± 10 dB/%. CONCLUSIONS: Grayscale median measurements are highly reproducible when obtained from the same US system with similar gain settings. Grayscale median values differ significantly across gain values and between systems. Researchers should consider the impact of US system and gain settings on GSM values when working to minimize system- and operator-dependent factors.

Lagrangian carotid strain imaging indices normalized to blood pressure for vulnerable plaque.

OBJECTIVE: Ultrasound Lagrangian carotid strain imaging (LCSI) utilizes physiological deformation caused by arterial pressure variations to generate strain tensor maps of the vessel walls and plaques. LCSI has been criticized for the lack of normalization of magnitude-based strain indices to physiological stimuli, namely blood pressure. We evaluated the impact of normalization of magnitude-based strain indices to blood pressure measured immediately after the acquisition of radiofrequency (RF) data loops for LCSI. MATERIALS AND METHODS: A complete clinical ultrasound examination along with RF data loops for LCSI was performed on 50 patients (30 males and 20 females) who presented with >60% carotid stenosis and were scheduled for carotid endarterectomy. Cognition was assessed using the 60-minute neuropsychological test protocol. RESULTS: For axial strains correlation of maximum accumulated strain indices (MASI), cognition scores were -0.46 for non-normalized and -0.45, -0.49, -0.37, and -0.48 for systolic, diastolic, pulse pressure, and mean arterial pressure normalized data, respectively. The corresponding area under the curve (AUC) values for classifiers designed using maximum likelihood estimation of a binormal distribution with a median-split of the executive function cognition scores were 0.73, 0.70, 0.71, 0.70, and 0.71, respectively. CONCLUSIONS: No significant differences in the AUC estimates were obtained between normalized and non-normalized magnitude-based strain indices.

Lumen segmentation using a Mask R-CNN in carotid arteries with stenotic atherosclerotic plaque.

In patients at high risk for ischemic stroke, clinical carotid ultrasound is often used to grade stenosis, determine plaque burden and assess stroke risk. Analysis currently requires a trained sonographer to manually identify vessel and plaque regions, which is time and labor intensive. We present a method for automatically determining bounding boxes and lumen segmentation using a Mask R-CNN network trained on sonographer assisted ground-truth carotid lumen segmentations. Automatic lumen segmentation also lays the groundwork for developing methods for accurate plaque segmentation, and wall thickness measurements in cases with no plaque. Different training schemes are used to identify the Mask R-CNN model with the highest accuracy. Utilizing a single-channel B-mode training input, our model produces a mean bounding box intersection over union (IoU) of 0.81 and a mean lumen segmentation IoU of 0.75. However, we encountered errors in prediction when the jugular vein is the most prominently visualized vessel in the B-mode image. This was due to the fact that our dataset has limited instances of B-mode images with both the jugular vein and carotid artery where the vein is dominantly visualized. Additional training datasets are anticipated to mitigate this issue.

A Practical Approach to Echocardiographic Imaging in Patients With Hypertrophic Cardiomyopathy.

Hypertrophic cardiomyopathy (HCM) is frequently unrecognized or misdiagnosed. The recently published consensus recommendations from the American Society of Echocardiography provided recommendations for the utilization of multimodality imaging in the care of patients with HCM. This document provides an additional practical framework for optimal image and measurement acquisition and guidance on how to tailor the echocardiography examination for individuals with HCM. It also provides resources for physicians and sonographers to use to develop HCM imaging protocols.

In Vivo Longitudinal Monitoring of Cardiac Remodeling in Murine Ischemia Models With Adaptive Bayesian Regularized Cardiac Strain Imaging: Validation Against Histology.

Adaptive Bayesian regularized cardiac strain imaging (ABR-CSI) uses raw radiofrequency signals to estimate myocardial wall contractility as a surrogate measure of relative tissue elasticity incorporating regularization in the Bayesian sense. We determined the feasibility of using ABR-CSI -derived strain for in vivo longitudinal monitoring of cardiac remodeling in a murine ischemic injury model (myocardial infarction [MI] and ischemia-reperfusion [IR]) and validated the findings against ground truth histology. We randomly stratified 30 BALB/CJ mice (17 females, 13 males, median age = 10 wk) into three surgical groups (MI = 10, IR = 12, sham = 8) and imaged pre-surgery (baseline) and 1, 2, 7 and 14 d post-surgery using a pre-clinical high-frequency ultrasound system (VisualSonics Vevo 2100). We then used ABR-CSI to estimate end-systolic and peak radial (er) and longitudinal (el) strain estimates. ABR-CSI was found to have the ability to serially monitor non-uniform cardiac remodeling associated with murine MI and IR non-invasively through temporal variation of strain estimates post-surgery. Furthermore, radial end-systole (ES) strain images and segmental strain curves exhibited improved discrimination among infarct, border and remote regions around the myocardium compared with longitudinal strain results. For example, the MI group had significantly lower (Friedman's with Bonferroni-Dunn test, p = 0.002) ES er values in the anterior middle (infarcted) region at day 14 (n = 9, 9.23 ± 7.39%) compared with the BL group (n = 9, 44.32 ± 5.49). In contrast, anterior basal (remote region) mean ES er values did not differ significantly (non-significant Friedman's test, χ2 = 8.93, p = 0.06) at day 14 (n = 6, 33.05 ± 6.99%) compared with baseline (n = 6, 34.02 ± 6.75%). Histology slides stained with Masson's trichrome (MT) together with a machine learning model (random forest classifier) were used to derive the ground truth cardiac fibrosis parameter termed histology percentage of myocardial fibrosis (PMF). Both radial and longitudinal strain were found to have strong statistically significant correlations with the PMF parameter. However, radial strain had a higher Spearman's correlation value (εresρ = -0.67, n = 172, p < 0.001) compared with longitudinal strain (εlesρ = -0.60, n = 172, p < 0.001). Overall, the results of this study indicate that ABR-CSI can reliably perform non-invasive detection of infarcted and remote myocardium in small animal studies.

Murine cardiac fibrosis localization using adaptive Bayesian cardiac strain imaging in vivo.

An adaptive Bayesian regularized cardiac strain imaging (ABR-CSI) algorithm for in vivo murine myocardial function assessment is presented. We report on 31 BALB/CJ mice (n = 17 females, n = 14 males), randomly stratified into three surgical groups: myocardial infarction (MI, n = 10), ischemia-reperfusion (IR, n = 13) and control (sham, n = 8) imaged pre-surgery (baseline- BL), and 1, 2, 7 and 14 days post-surgery using a high frequency ultrasound imaging system (Vevo 2100). End-systole (ES) radial and longitudinal strain images were used to generate cardiac fibrosis maps using binary thresholding. Percentage fibrotic myocardium (PFM) computed from regional fibrosis maps demonstrated statistically significant differences post-surgery in scar regions. For example, the MI group had significantly higher PFMRadial (%) values in the anterior mid region (p = 0.006) at Day 14 (n = 8, 42.30 ± 14.57) compared to BL (n = 12, 1.32 ± 0.85). A random forest classifier automatically detected fibrotic regions from ground truth Masson's trichrome stained histopathology whole slide images. Both PFMRadial (r = 0.70) and PFMLongitudinal (r = 0.60) results demonstrated strong, positive correlation with PFMHistopathology (p < 0.001).

Persistent Asthma Is Associated With Carotid Plaque in MESA.

Background Asthma and atherosclerotic cardiovascular disease share an underlying inflammatory pathophysiology. We hypothesized that persistent asthma is associated with carotid plaque burden, a strong predictor of atherosclerotic cardiovascular disease events. Methods and Results The MESA (Multi-Ethnic Study of Atherosclerosis) enrolled adults free of known atherosclerotic cardiovascular disease at baseline. Subtype of asthma was determined at examination 1. Persistent asthma was defined as asthma requiring use of controller medications, and intermittent asthma was defined as asthma without controller medications. B-mode carotid ultrasound was performed to detect carotid plaques (total plaque score [TPS], range 0-12). Multivariable regression modeling with robust variances evaluated the association of asthma subtype and carotid plaque burden. The 5029 participants were a mean (SD) age of 61.6 (10.0) years (53% were women, 26% were Black individuals, 23% were Hispanic individuals, and 12% were Chinese individuals). Carotid plaque was present in 50.5% of participants without asthma (TPS, 1.29 [1.80]), 49.5% of participants with intermittent asthma (TPS, 1.25 [1.76]), and 67% of participants with persistent asthma (TPS, 2.08 [2.35]) (P≤0.003). Participants with persistent asthma had higher interleukin-6 (1.89 [1.61] pg/mL) than participants without asthma (1.52 [1.21] pg/mL; P=0.02). In fully adjusted models, persistent asthma was associated with carotid plaque presence (odds ratio, 1.83 [95% confidence interval, 1.21-2.76]; P<0.001) and TPS (ß=0.66; P<0.01), without attenuation after adjustment for baseline interleukin-6 (P=0.02) or CRP (C-reactive protein) (P=0.01). Conclusions Participants with persistent asthma had higher carotid plaque burden and higher levels of inflammatory biomarkers, compared with participants without asthma. Adjustment for baseline inflammatory biomarkers did not attenuate the association between carotid plaque and asthma subtype, highlighting the increased atherosclerotic cardiovascular disease risk among those with persistent asthma may be multifactorial.

Grayscale Ultrasound Texture Features of Carotid and Brachial Arteries in People With HIV Infection Before and After Antiretroviral Therapy.

Background We aimed to investigate novel grayscale ultrasound characteristics of the carotid and brachial arteries in people with HIV infection before and after starting initial antiretroviral therapy (ART). Methods and Results We performed grayscale ultrasound image analyses of the common carotid artery (CCA) and brachial artery before and after receipt of 1 of 3 randomly allocated ART regimens. We measured arterial wall echogenicity (grayscale median), contrast (gray-level difference statistic method), and entropy. These measures and their changes were compared with atherosclerotic cardiovascular disease risk factors, measures of HIV disease severity, and inflammatory biomarkers before and after ART. Changes in the grayscale measures were evaluated within and between ART arms. Among 201 ART-naïve people with HIV, higher systolic blood pressure, higher body mass index, lower CD4+ T cells, and non-Hispanic White race and ethnicity were associated independently with lower CCA grayscale median. Changes in each CCA grayscale measure from baseline to 144 weeks correlated with changes in soluble CD163: grayscale median (ρ=-0.17; P=0.044), gray-level difference statistic-contrast (ρ=-0.19; P=0.024), and entropy (ρ=-0.21; P=0.016). Within the atazanavir/ritonavir arm, CCA entropy increased (adjusted ß=0.023 [95% CI, 0.001-0.045]; P=0.04), but no other within-arm changes in grayscale measures were seen. Correlations of brachial artery grayscale measures were weaker. Conclusions In ART-naïve people with HIV, CCA grayscale ultrasound measures were associated with atherosclerotic cardiovascular disease risk factors and lower grayscale median was associated with lower CD4+ T cells. Reductions in soluble CD163 with initial ART were associated with improvements in all 3 CCA grayscale measures, suggesting that reductions in macrophage activation with ART initiation may lead to less arterial injury. Registration URL: https://clinicaltrials.gov/; Unique identifiers: NCT00811954; NCT00851799.

Enhancement of in vivo cardiac photoacoustic signal specificity using spatiotemporal singular value decomposition.

SIGNIFICANCE: Photoacoustic imaging (PAI) can be used to infer molecular information about myocardial health non-invasively in vivo using optical excitation at ultrasonic spatial resolution. For clinical and preclinical linear array imaging systems, conventional delay-and-sum (DAS) beamforming is typically used. However, DAS cardiac PA images are prone to artifacts such as diffuse quasi-static clutter with temporally varying noise-reducing myocardial signal specificity. Typically, multiple frame averaging schemes are utilized to improve the quality of cardiac PAI, which affects the spatial and temporal resolution and reduces sensitivity to subtle PA signal variation. Furthermore, frame averaging might corrupt myocardial oxygen saturation quantification due to the presence of natural cardiac wall motion. In this paper, a spatiotemporal singular value decomposition (SVD) processing algorithm is proposed to reduce DAS PAI artifacts and subsequent enhancement of myocardial signal specificity. AIM: Demonstrate enhancement of PA signals from myocardial tissue compared to surrounding tissues and blood inside the left-ventricular (LV) chamber using spatiotemporal SVD processing with electrocardiogram (ECG) and respiratory signal (ECG-R) gated in vivo murine cardiac PAI. APPROACH: In vivo murine cardiac PAI was performed by collecting single wavelength (850 nm) photoacoustic channel data on eight healthy mice. A three-dimensional (3D) volume of complex PAI data over a cardiac cycle was reconstructed using a custom ECG-R gating algorithm and DAS beamforming. Spatiotemporal SVD was applied on a two-dimensional Casorati matrix generated using the 3D volume of PAI data. The singular value spectrum (SVS) was then filtered to remove contributions from diffuse quasi-static clutter and random noise. Finally, SVD processed beamformed images were derived using filtered SVS and inverse SVD computations. RESULTS: Qualitative comparison with DAS and minimum variance (MV) beamforming shows that SVD processed images had better myocardial signal specificity, contrast, and target detectability. DAS, MV, and SVD images were quantitatively evaluated by calculating contrast ratio (CR), generalized contrast-to-noise ratio (gCNR), and signal-to-noise ratio (SNR). Quantitative evaluations were done at three cardiac time points (during systole, at end-systole (ES), and during diastole) identified from co-registered ultrasound M-Mode image. Mean CR, gCNR, and SNR values of SVD images at ES were 245, 115.15, and 258.17 times higher than DAS images with statistical significance evaluated with one-way analysis of variance. CONCLUSIONS: Our results suggest that significantly better-quality images can be realized using spatiotemporal SVD processing for in vivo murine cardiac PAI.

Spatiotemporal Bayesian Regularization for Cardiac Strain Imaging: Simulation and In Vivo Results.

Cardiac strain imaging (CSI) plays a critical role in the detection of myocardial motion abnormalities. Displacement estimation is an important processing step to ensure the accuracy and precision of derived strain tensors. In this paper, we propose and implement Spatiotemporal Bayesian regularization (STBR) algorithms for two-dimensional (2-D) normalized cross-correlation (NCC) based multi-level block matching along with incorporation into a Lagrangian cardiac strain estimation framework. Assuming smooth temporal variation over a short span of time, the proposed STBR algorithm performs displacement estimation using at least four consecutive ultrasound radio-frequency (RF) frames by iteratively regularizing 2-D NCC matrices using information from a local spatiotemporal neighborhood in a Bayesian sense. Two STBR schemes are proposed to construct Bayesian likelihood functions termed as Spatial then Temporal Bayesian (STBR-1) and simultaneous Spatiotemporal Bayesian (STBR-2). Radial and longitudinal strain estimated from a finite-element-analysis (FEA) model of realistic canine myocardial deformation were utilized to quantify strain bias, normalized strain error and total temporal relative error (TTR). Statistical analysis with one-way analysis of variance (ANOVA) showed that all Bayesian regularization methods significantly outperform NCC with lower bias and errors (p < 0.001). However, there was no significant difference among Bayesian methods. For example, mean longitudinal TTR for NCC, SBR, STBR-1 and STBR-2 were 25.41%, 9.27%, 10.38% and 10.13% respectively An in vivo feasibility study using RF data from ten healthy mice hearts were used to compare the elastographic signal-to-noise ratio (SNR e ) calculated using stochastic analysis. STBR-2 had the highest expected SNR e both for radial and longitudinal strain. The mean expected SNR e values for accumulated radial strain for NCC, SBR, STBR-1 and STBR-2 were 5.03, 9.43, 9.42 and 10.58, respectively. Overall results suggest that STBR improves CSI in vivo.

Bayesian Regularized Strain Imaging for Assessment of Murine Cardiac Function In vivo.

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 (fc = 30MHz) imaging system and a multi-level block matching algorithm with ABR to derive inter-frame cardiac displacements. Lagrangian cardiac strain (radial, er and longitudinal, el) 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 er and el strain at BL with segmental synchroneity. Infarcted regions of IR mouse at Day 14 were associated with reduced or sign reversed ES er and el 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.

Study of the Relationship Between Ultrasound Strain Indices and Cognitive Decline for Vulnerable Carotid Plaque.

A relationship between ultrasound strain indices in carotid plaque to cognitive domains of executive and language function are studied in 42 symptomatic and 34 asymptomatic patients. The mean and standard deviation of the percentage stenosis were 72.10 ± 15.19 and 77.41 ± 11.20 for symptomatic and asymptomatic patients respectively. Pearson's correlation between axial, lateral and shear strain indices versus executive and language composite scores was performed.. A significant inverse correlation for both executive and language function for symptomatic patients to strain indices was found. On the other hand, for asymptomatic patients only executive function was inversely correlated with the corresponding strain indices. Our hypothesis that microemboli from vulnerable plaque and possible 'silent strokes' may be responsible for decline in executive function for both symptomatic and asymptomatic patients'. Strokes and transient ischemic attacks may be responsible for further cognitive decline in language function for symptomatic patients.

Attenuation Coefficient Parameter Computations for Tissue Composition Assessment of Carotid Atherosclerotic Plaque in Vivo.

Quantitative ultrasound has been used to assess carotid plaque tissue composition. Here, we compute the attenuation coefficient (AC) in vivo with the optimum power spectral shift estimator (OPSSE) and reference phantom method (RPM), extract AC parameters and form parametric maps. Differences between OPSSE and RPM AC parameters are computed. Relationships between AC parameters, surgical scores and histopathology assessments are examined. Kendall's τ correlations between OPSSE AC and surgical scores are significant, including those between cholesterol and Standard Deviation (adjusted p = 0.038); thrombus and Minimum (adjusted p = 0.002), Maximum (adjusted p = 0.021) and Standard Deviation (adjusted p = 0.001); ulceration and Average (adjusted p = 0.033), Median (unadjusted p = 0.013), Maximum (unadjusted p = 0.039) and Mode (adjusted p = 0.009). The strongest correlations with histopathology are percentage cholesterol and Median OPSSE (unadjusted p = 0.007); percentage hemorrhage and Minimum OPSSE (adjusted p < 0.001); hemosiderin score and Median OPSSE (adjusted p = 0.010); and percentage calcium and Percentage Non-physical RPM Pixels (unadjusted p = 0.014). Kruskal-Wallis H and Dunn's post hoc tests have the ability to distinguish between groups (p < 0.05). Results suggest AC parameters may assist in vivo evaluation of carotid plaque vulnerability.

Protocol of Aerobic Exercise and Cognitive Health (REACH): A Pilot Study.

A growing body of evidence supports that aerobic exercise can decrease the risk of future cognitive impairment and Alzheimer's disease (AD). There is a pressing need to rigorously determine whether cognitively normal yet at-risk individuals stand to benefit from the protective effects of exercise. The present study will test the feasibility of an aerobic exercise intervention in such a population and inform the design of a larger-scale randomized, controlled trial examining the effect of aerobic exercise on biomarkers of AD in late-middle-aged, at-risk individuals. This was a single-site, 1 : 1 block-randomized, parallel, two-arm trial. Cognitively normal participants aged 45-80 with documentation of familial and genetic AD risk factors were randomly assigned to one of two interventions. The Usual Physical Activity group was provided educational materials about exercise. The Enhanced Physical Activity intervention delivered 26 weeks of individualized and supervised aerobic exercise. Exercise duration and intensity were incrementally increased to 150 min/week and 70-80% of heart rate reserve, respectively. Retention and adherence were measured to assess study feasibility. In addition, pre- and post- intervention differences between the two arms were evaluated for cardiorespiratory fitness, physical activity, brain glucose metabolism, cerebral structure, vascular health, memory, executive function, and mood. Data from randomized controlled trials of exercise training are needed to identify the proper exercise prescription for reducing accumulation of AD biomarkers in cognitively normal individuals. The current trial will contribute to filling that gap while informing the design of large-scale trials.

Hierarchical Motion Estimation With Bayesian Regularization in Cardiac Elastography: Simulation and In Vivo Validation.

Cardiac elastography (CE) is an ultrasound-based technique utilizing radio-frequency (RF) signals for assessing global and regional myocardial function. In this work, a complete strain estimation pipeline for incorporating a Bayesian regularization-based hierarchical block-matching algorithm, with Lagrangian motion description and myocardial polar strain estimation is presented. The proposed regularization approach is validated using finite-element analysis (FEA) simulations of a canine cardiac deformation model that is incorporated into an ultrasound simulation program. Interframe displacements are initially estimated using a hierarchical motion estimation framework. Incremental displacements are then accumulated under a Lagrangian description of cardiac motion from end-diastole (ED) to end-systole (ES). In-plane Lagrangian finite strain tensors are then derived from the accumulated displacements. Cartesian to cardiac coordinate transformation is utilized to calculate radial and longitudinal strains for ease of interpretation. Benefits of regularization are demonstrated by comparing the same hierarchical block-matching algorithm with and without regularization. Application of Bayesian regularization in the canine FEA model provided improved ES radial and longitudinal strain estimation with statistically significant ( ) error reduction of 48.88% and 50.16%, respectively. Bayesian regularization also improved the quality of temporal radial and longitudinal strain curves with error reductions of 78.38% and 86.67% ( ), respectively. Qualitative and quantitative improvements were also visualized for in vivo results on a healthy murine model after Bayesian regularization. Radial strain elastographic signal-to-noise ratio (SNRe) increased from 3.83 to 4.76 dB, while longitudinal strain SNRe increased from 2.29 to 4.58 dB with regularization.

Carotid Artery Echolucency, Texture Features, and Incident Cardiovascular Disease Events: The MESA Study.

Background We hypothesized that measures of common carotid artery echolucency and grayscale texture features were associated with cardiovascular disease ( CVD ) risk factors and could predict CVD events. Methods and Results Using a case-cohort design, we measured common carotid artery ultrasound images from 1788 participants in Exam 1 of the MESA study (Multi-Ethnic Study of Atherosclerosis) to derive 4 grayscale features: grayscale median, entropy, gray level difference statistic-contrast, and spatial gray level dependence matrices-angular second moment. CVD risk factor associations were determined by linear regression. Cox proportional hazard models with inverse selection probability weighting and adjustments for age, sex, race/ethnicity, CVD risk factors, and C-reactive protein were used to determine if standardized values for grayscale median, entropy, gray level difference statistic-contrast, and spatial gray level dependence matrices-angular second moment could predict incident coronary heart disease, stroke, and total CVD events over a median 13 years follow-up. Participants were mean ( SD ) 63.1 (10.3) years of age, 52.6% female, 32.1% white, 27.8% black, 23.3% Hispanic, and 16.8% Chinese. There were 283 coronary heart disease, 120 stroke, and 416 CVD events. Several associations of grayscale features with CVD risk factors were identified. In fully adjusted models, higher gray level difference statistic-contrast was associated with a lower risk of incident coronary heart disease (hazard ratio 0.82, 95% CI 0.71-0.94, padj=0.005) and CVD events (hazard ratio 0.87, 95% CI 0.77-0.98, padj=0.018); higher spatial gray level dependence matrices-angular second moment was associated with a higher risk of CVD events (hazard ratio 1.09, 95% CI 1.00-1.19, padj=0.044). Conclusions Gray level difference statistic-contrast and spatial gray level dependence matrices-angular second moment predicted CVD events independent of risk factors, indicating their potential use as biomarkers to assess future CVD risk.