Beat-to-Beat Blood Pressure and Two-dimensional (axial and radial) Motion of the Carotid Artery Wall: Physiological Evaluation of Arterial Stiffness

Arterial pulsations and transmantle pressure synergetically drive glymphatic flow

Clearance of waste material from the brain by the glymphatic system results from net flow of cerebrospinal fluid (CSF) through perivascular spaces surrounding veins and arteries. In periarterial spaces, this bulk flow is directed from the cranial subarachnoid space towards the brain's interior. The precise pumping mechanism explaining this net inflow remains unclear. While in vivo experiments have shown that the pulsatile motion in periarterial spaces is synchronized with arterial pulsations, peristalsis alone has been deemed insufficient to explain bulk flow. In this study we examine an alternative mechanism based on the interaction between arterial pulsations and fluctuations in transmantle pressure. Previously studied using pressure data from a hydrocephalus patient, this mechanism is analyzed here in healthy subjects using in vivo flow measurements obtained via phase-contrast magnetic resonance imaging. Arterial pulsations are derived from flow-rate measurements of arterial blood entering the cranial cavity, while transmantle-pressure fluctuations are computed using measurements of CSF flow in the cerebral aqueduct. The two synchronized waveforms are integrated into a canonical multi-branch model of the periarterial spaces, yielding a closed-form expression for the bulk flow. The results confirm that the dynamic interactions between arterial pulsations and transmantle pressure are sufficient to generate a positive inflow along periarterial spaces.

Blood pressure variability: methodological aspects, clinical relevance and practical indications for management - a European Society of Hypertension position paper ∗

Blood pressure is not a static parameter, but rather undergoes continuous fluctuations over time, as a result of the interaction between environmental and behavioural factors on one side and intrinsic cardiovascular regulatory mechanisms on the other side. Increased blood pressure variability (BPV) may indicate an impaired cardiovascular regulation and may represent a cardiovascular risk factor itself, having been associated with increased all-cause and cardiovascular mortality, stroke, coronary artery disease, heart failure, end-stage renal disease, and dementia incidence. Nonetheless, BPV was considered only a research issue in previous hypertension management guidelines, because the available evidence on its clinical relevance presents several gaps and is based on heterogeneous studies with limited standardization of methods for BPV assessment. The aim of this position paper, with contributions from members of the European Society of Hypertension Working Group on Blood Pressure Monitoring and Cardiovascular Variability and from a number of international experts, is to summarize the available evidence in the field of BPV assessment methodology and clinical applications and to provide practical indications on how to measure and interpret BPV in research and clinical settings based on currently available data. Pending issues and clinical and methodological recommendations supported by available evidence are also reported. The information provided by this paper should contribute to a better standardization of future studies on BPV, but should also provide clinicians with some indications on how BPV can be managed based on currently available data.

Vascular wall motion detection models based on long short-term memory in plane-wave-based ultrasound imaging

Objective.Vascular wall motion can be used to diagnose cardiovascular diseases. In this study, long short-term memory (LSTM) neural networks were used to track vascular wall motion in plane-wave-based ultrasound imaging.Approach.The proposed LSTM and convolutional LSTM (ConvLSTM) models were trained using ultrasound data from simulations and tested experimentally using a tissue-mimicking vascular phantom and anin vivostudy using a carotid artery. The performance of the models in the simulation was evaluated using the mean square error from axial and lateral motions and compared with the cross-correlation (XCorr) method. Statistical analysis was performed using the Bland-Altman plot, Pearson correlation coefficient, and linear regression in comparison with the manually annotated ground truth.Main results.For thein vivodata, the median error and 95% limit of agreement from the Bland-Altman analysis were (0.01, 0.13), (0.02, 0.19), and (0.03, 0.18), the Pearson correlation coefficients were 0.97, 0.94, and 0.94, respectively, and the linear equations were 0.89x+ 0.02, 0.84x+ 0.03, and 0.88x+ 0.03 from linear regression for the ConvLSTM model, LSTM model, and XCorr method, respectively. In the longitudinal and transverse views of the carotid artery, the LSTM-based models outperformed the XCorr method. Overall, the ConvLSTM model was superior to the LSTM model and XCorr method.Significance.This study demonstrated that vascular wall motion can be tracked accurately and precisely using plane-wave-based ultrasound imaging and the proposed LSTM-based models.

Safety of arterial shear wave elastography-ex-vivoassessment of induced strain and strain rates

Shear wave elastography (SWE) is a promising technique for characterizing carotid plaques and assessing local arterial stiffness. The mechanical stress to which the tissue is subjected during SWE using acoustic radiation force (ARF), leading to strain at a certain strain rate, is still relatively unknown. Because SWE is increasingly used for arterial applications where the mechanical stress could potentially lead to significant consequences, it is important to understand the risks of SWE- induced strain and strain rate. The aim of this study was to investigate the safety of SWE in terms of induced arterial strain and strain rateex-vivoand in a human carotid arteryin-vivo. SWE was performed on six porcine aortae as a model of the human carotid artery using different combinations of ARF push parameters (push voltage: 60/90 V, aperture width: f/1.0/1.5, push length: 100/150/200 μs) and distance to push position. The largest induced strain and strain rate were 1.46 % and 54 s^-1(90 V, f/1.0, 200 μs), respectively. Moreover, the SWE-induced strains and strain rates increased with increasing push voltage, aperture, push length, and decreasing distance between the region of interest and the push. In the human carotid artery, the SWE-induced maximum strain was 0.06 % and the maximum strain rate was 1.58 s^-1, compared with the maximum absolute strain and strain rate of 12.61 % and 5.12 s^-1, respectively, induced by blood pressure variations in the cardiac cycle. Our results indicate thatex-vivoarterial SWE does not expose the artery to higher strain rate than normal blood pressure variations, and to strain one order of magnitude higher than normal blood pressure variations, at the push settings and distances from the region of interest used in this study.

Predictive Capacity of Beat-to-Beat Blood Pressure Variability for Cardioautonomic and Vascular Dysfunction in Early Metabolic Challenge

Diabetic patients present established cardiovascular disease at the onset of diagnostic metabolic symptoms. While premature autonomic and vascular deterioration considered risk factors for major cardiovascular complications of diabetes, present in initial stages of metabolic impairment, their early detection remains a significant challenge impeding timely intervention. In the present study, we examine the utility of beat-to-beat blood pressure variability (BPV) parameters in capturing subtle changes in cardiac autonomic and vascular control distinguishing between various risk categories, independent of the average BP. A rat model of mild hypercaloric (HC) intake was used to represent the insidious cardiovascular changes associated with early metabolic impairment. Invasive hemodynamics were used to collect beat-to-beat BP time series in rats of either sex with different durations of exposure to the HC diet. Linear (standard deviation and coefficient of variation) and nonlinear (approximate entropy, ApEn, and self-correlation of detrended fluctuation analysis, α) BPV parameters were calculated to assess the impact of early metabolic impairment across sexes and feeding durations. HC-fed male, but not female, rats developed increased fat:lean ratio as well as hyperinsulinemia. Unlike linear parameters, multivariate analysis showed that HC-fed rats possessed lower ApEn and higher α, consistent with early changes in heart rate variability and blunting of parasympathetic baroreceptor sensitivity, particularly in males. Moreover, logistic regression demonstrated the superiority of nonlinear parameters of diastolic BPV in predicting a prediabetic disease state. Our findings support the use of nonlinear beat-to-beat BPV for early detection of cardiovascular derangements in the initial stages of metabolic impairment.

Beat-to-beat blood pressure variability: an early predictor of disease and cardiovascular risk

Blood pressure (BP) varies on the long, short and very-short term. Owing to the hidden physiological and pathological information present in BP time-series, increasing interest has been given to the study of continuous, beat-to-beat BP variability (BPV) using invasive and noninvasive methods. Different linear and nonlinear parameters of variability are employed in the characterization of BP signals in health and disease. Although linear parameters of beat-to-beat BPV are mainly measures of dispersion, such as standard deviation (SD), nonlinear parameters of BPV quantify the degree of complexity/irregularity- using measures of entropy or self-similarity/correlation. In this review, we summarize the value of linear and nonlinear parameters in reflecting different information about the pathophysiology of changes in beat-to-beat BPV independent of or superior to mean BP. We then provide a comparison of the relative power of linear and nonlinear parameters of beat-to-beat BPV in detecting early and subtle differences in various states. The practical advantage and utility of beat-to-beat BPV monitoring support its incorporation into routine clinical practices.

Motion synchronisation patterns of the carotid atheromatous plaque from B-mode ultrasound

Asynchronous movement of the carotid atheromatous plaque from B-mode ultrasound has been previously reported, and associated with higher risk of stroke, but not quantitatively estimated. Based on the hypothesis that asynchronous plaque motion is associated with vulnerable plaque, in this study, synchronisation patterns of different tissue areas were estimated using cross-correlations of displacement waveforms. In 135 plaques (77 subjects), plaque radial deformation was synchronised by approximately 50% with the arterial diameter, and the mean phase shift was 0.4 s. Within the plaque, the mean phase shifts between the displacements of the top and bottom surfaces were 0.2 s and 0.3 s, in the radial and longitudinal directions, respectively, and the synchronisation about 80% in both directions. Classification of phase-shift-based features using Random Forests yielded Area-Under-the-Curve scores of 0.81, 0.79, 0.89 and 0.90 for echogenicity, symptomaticity, stenosis degree and plaque risk, respectively. Statistical analysis showed that echolucent, high-stenosis and high-risk plaques exhibited higher phase shifts between the radial displacements of their top and bottom surfaces. These findings are useful in the study of plaque kinematics.

Carotid Artery Longitudinal Wall Motion Is Unaffected by 12 Weeks of Endurance, Sprint Interval or Resistance Exercise Training

Carotid artery longitudinal wall motion (CALM) exhibits reduced magnitude in older adults and in individuals with chronic diseases, although longitudinal data are lacking to indicate how changes in CALM might develop over time. Therefore, the aim of this study was to investigate the effect of exercise training in healthy men on CALM using a retrospective design. Carotid ultrasound data were analysed from two previous studies in which men performed 12 wk of moderate-intensity continuous exercise training (n = 9), sprint-interval training (n = 7), higher-repetition resistance exercise training (n = 15) or lower-repetition resistance exercise training (n = 15). The CALM pattern was unaltered after 12 wk of exercise training, regardless of exercise mode, with no differences in systolic or diastolic CALM magnitudes (p > 0.05), similar to carotid intima-media thickness (p > 0.05). Our findings suggest that CALM is resistant to transient changes in lifestyle factors, similar to wall thickness in otherwise healthy populations.

Understanding hypertension in the light of Ayurveda

Different theories have been proposed to explain hypertension from an Ayurvedic perspective, but there is no consensus amongst the experts. A better understanding of the applied physiology and etio-pathogenesis of hypertension in the light of Ayurvedic principles is being attempted to fill this gap. A detailed review of available Ayurvedic literature was carried out to understand the physiology of blood pressure and etio-pathogenesis of hypertension from the perspective of Ayurveda. Many parallels were drawn from the concepts such as Shad Kriyakala (six stages of Dosha imbalance) and Avarana of Doshas (occlusion in the normal functioning of the Doshas) to the modern pathogenesis of hypertension to gain a deeper understanding of it. Hypertension without specific symptoms in its mild and moderate stages cannot be considered as a disease in Ayurveda. It appears to be an early stage of pathogenesis and a risk factor for development of diseases affecting the heart, brain, kidneys and eyes etc. Improper food habits and modern sedentary lifestyle with or without genetic predisposition provokes and vitiates all the Tridoshas to trigger the pathogenesis of hypertension. It is proposed that hypertension is to be understood as the Prasara-Avastha which means spread of vitiated Doshas from their specific sites, specifically of Vyana Vata, Prana Vata, Sadhaka Pitta and Avalambaka Kapha along with Rakta in their disturbed states. The Avarana (occlusion of normal functioning) of Vata Dosha by Pitta and Kapha can be seen in the Rasa-Rakta Dhathus, which in turn hampers the functioning of the respective Srotas (micro-channels) of circulation.

Longitudinal pulsatility in arterial occlusion

This pictorial essay aims to generate attention and inform sonographers and clinicians by remembering the "longitudinal pulsatility" as an evocative B-mode echographic sign of arterial occlusion, when the artery exhibits a systolic axial motion instead of its normal radial pulsatility.

Novel blood pressure and pulse pressure estimation based on pulse transit time and stroke volume approximation

BACKGROUND

Non-invasive continuous blood pressure monitors are of great interest to the medical community due to their value in hypertension management. Recently, studies have shown the potential of pulse pressure as a therapeutic target for hypertension, but not enough attention has been given to non-invasive continuous monitoring of pulse pressure. Although accurate pulse pressure estimation can be of direct value to hypertension management and indirectly to the estimation of systolic blood pressure, as it is the sum of pulse pressure and diastolic blood pressure, only a few inadequate methods of pulse pressure estimation have been proposed.

METHODS

We present a novel, non-invasive blood pressure and pulse pressure estimation method based on pulse transit time and pre-ejection period. Pre-ejection period and pulse transit time were measured non-invasively using electrocardiogram, seismocardiogram, and photoplethysmogram measured from the torso. The proposed method used the 2-element Windkessel model to model pulse pressure with the ratio of stroke volume, approximated by pre-ejection period, and arterial compliance, estimated by pulse transit time. Diastolic blood pressure was estimated using pulse transit time, and systolic blood pressure was estimated as the sum of the two estimates. The estimation method was verified in 11 subjects in two separate conditions with induced cardiovascular response and the results were compared against a reference measurement and values obtained from a previously proposed method.

RESULTS

The proposed method yielded high agreement with the reference (pulse pressure correlation with reference R ≥ 0.927, diastolic blood pressure correlation with reference R ≥ 0.854, systolic blood pressure correlation with reference R ≥ 0.914) and high estimation accuracy in pulse pressure (mean root-mean-squared error ≤ 3.46 mmHg) and blood pressure (mean root-mean-squared error ≤ 6.31 mmHg for diastolic blood pressure and ≤ 8.41 mmHg for systolic blood pressure) over a wide range of hemodynamic changes.

CONCLUSION

The proposed pulse pressure estimation method provides accurate estimates in situations with and without significant changes in stroke volume. The proposed method improves upon the currently available systolic blood pressure estimation methods by providing accurate pulse pressure estimates.

Simulation of phase contrast angiography for renal arterial models

BACKGROUND

With the development of versatile magnetic resonance acquisition techniques there arises a need for more advanced imaging simulation tools to enable adequate image appearance prediction, measurement sequence design and testing thereof. Recently, there is a growing interest in phase contrast angiography (PCA) sequence due to the capabilities of blood flow quantification that it offers. Moreover, as it is a non-contrast enhanced protocol, it has become an attractive option in areas, where usage of invasive contrast agents is not indifferent for the imaged tissue. Monitoring of the kidney function is an example of such an application.

RESULTS

We present a computer framework for simulation of the PCA protocol, both conventional and accelerated with echo-planar imaging (EPI) readout, and its application to the numerical models of kidney vasculatures. Eight patient-specific renal arterial trees were reconstructed following vessel segmentation in real computed tomography angiograms. In addition, a synthetic model was designed using a vascular tree growth simulation algorithm. The results embrace a series of synthetic PCA images of the renal arterial trees giving insight into the image formation and quantification of kidney hemodynamics.

CONCLUSIONS

The designed simulation framework enables quantification of the PCA measurement error in relation to ground-truth flow velocity data. The mean velocity measurement error for the reconstructed renal arterial trees range from 1.5 to 12.8% of the aliasing velocity value, depending on image resolution and flip angle. No statistically significant difference was observed between measurements obtained using EPI with a number of echos (NETL) = 4 and conventional PCA. In case of higher NETL factors peak velocity values can be underestimated up to 34%.