Arterial viscoelasticity: role in the dependency of pulse wave velocity on heart rate in conduit arteries

Role of Microtubule Network in the Passive Anisotropic Viscoelasticity of Healthy Right Ventricle

Cardiomyocytes are viscoelastic and key determinants of right ventricle (RV) mechanics. Intracellularly, microtubules are found to impact the viscoelasticity of isolated cardiomyocytes or trabeculae; whether they contribute to the tissue-level viscoelasticity is unknown. Our goal was to reveal the role of the microtubule network in the passive anisotropic viscoelasticity of the healthy RV. Equibiaxial stress relaxation tests were conducted in healthy RV free wall (RVFW) under early (6%) and end (15%) diastolic strain levels, and at sub- and physiological stretch rates. The viscoelasticity was assessed at baseline and after the removal of microtubule network. Furthermore, a quasi-linear viscoelastic (QLV) model was applied to delineate the contribution of microtubules to the relaxation behavior of RVFW. After removing the microtubule network, RVFW elasticity and viscosity were reduced at the early diastolic strain level and in both directions. The reduction in elasticity was stronger in the longitudinal direction, whereas the degree of changes in viscosity were equivalent between directions. There was insignificant change in RVFW viscoelasticity at late diastolic strain level. Finally, the modeling showed that the tissue's relaxation strength was reduced by the removal of the microtubule network, but the change was present only at a later time scale. These new findings suggest a critical role of cytoskeleton filaments in RVFW passive mechanics in physiological conditions.

Type 2 diabetes exacerbates changes in blood pressure-independent arterial stiffness: cross-sectional and longitudinal evidence from the SUMMIT study

Greater central artery stiffness is observed in people with type 2 diabetes (T2DM). Elevated blood pressure (BP) and altered arterial wall structure/composition in T2DM are generally considered as main drivers for this alteration. However, because conventional arterial stiffness measures are BP-dependent and as such an influence of BP remains in a measure, it is unclear if greater central artery stiffness is a function of greater BP, or due to changes in the structure and composition of the arterial wall. We aimed to measure BP-independent arterial stiffness (β0) cross-sectionally and longitudinally in T2DM. We studied 753 adults with T2DM (DM+) and 436 adults without (DM-) at baseline (Phase 1), and 310 DM+ and 210 DM- adults at 3-yr follow-up (Phase 2). We measured carotid-femoral pulse wave velocity and used it to calculate β0. In Phase 1, β0 was significantly greater in DM+ than DM- after adjusting for age and sex [27.5 (26.6-28.3) vs. 23.6 (22.4-24.8) au, P < 0.001]. Partial correlation analyses after controlling for age and sex showed that β0 was significantly associated with hemoglobin A1c (r = 0.15 P < 0.001) and heart rate [(HR): r = 0.23 P < 0.001)] in DM+. In Phase 2, percentage-change in β0 was significantly greater in DM+ than DM- [19.5 (14.9-24.0) vs. 5.0 (-0.6 to 10.6) %, P < 0.001] after adjusting for age, sex, and baseline β0. β0 was greater in DM+ than DM- and increased much more in DM+ than in DM- over 3 yr. This suggests that T2DM exacerbates BP-independent arterial stiffness and may have a complemental utility to existing arterial stiffness indices.NEW & NOTEWORTHY We demonstrate in this study a greater BP-independent arterial stiffness β0 in people with type 2 diabetes (T2DM) compared to those without, and also a greater change in β0 over 3 yr in people with T2DM than those without. These findings suggest that the intrinsic properties of the arterial wall may change in a different and more detrimental way in people with T2DM and likely represents accumulation of cardiovascular risk.

Peripheral artery disease diagnosis based on deep learning-enabled analysis of non-invasive arterial pulse waveforms

This paper intends to investigate the feasibility of peripheral artery disease (PAD) diagnosis based on the analysis of non-invasive arterial pulse waveforms. We generated realistic synthetic arterial blood pressure (BP) and pulse volume recording (PVR) waveform signals pertaining to PAD present at the abdominal aorta with a wide range of severity levels using a mathematical model that simulates arterial blood circulation and arterial BP-PVR relationships. We developed a deep learning (DL)-enabled algorithm that can diagnose PAD by analyzing brachial and tibial PVR waveforms, and evaluated its efficacy in comparison with the same DL-enabled algorithm based on brachial and tibial arterial BP waveforms as well as the ankle-brachial index (ABI). The results suggested that it is possible to detect PAD based on DL-enabled PVR waveform analysis with adequate accuracy, and its detection efficacy is close to when arterial BP is used (positive and negative predictive values at 40 % abdominal aorta occlusion: 0.78 vs 0.89 and 0.85 vs 0.94; area under the ROC curve (AUC): 0.90 vs 0.97). On the other hand, its efficacy in estimating PAD severity level is not as good as when arterial BP is used (r value: 0.77 vs 0.93; Bland-Altman limits of agreement: -32%-+32 % vs -20%-+19 %). In addition, DL-enabled PVR waveform analysis significantly outperformed ABI in both detection and severity estimation. In sum, the findings from this paper suggest the potential of DL-enabled non-invasive arterial pulse waveform analysis as an affordable and non-invasive means for PAD diagnosis.

Gender and age disparities in small-to-medium arterial stiffness among the Chinese population

BACKGROUND AND AIMS

Arterial pressure-volume index (API) is a non-invasive tool for assessing small-to-medium-sized arterial stiffness. This study aimed to investigate the potential age- and sex-related differences in the API and explore the practical implications of such differences.

METHODS AND RESULTS

The study analysed 7620 subjects for whom API measurements were available. Linear regression and restrictive cubic spline models were used to investigate the associations between potential risk conditions and the API. Additionally, this study employed a backward stepwise regression method to identify the independent factors associated with a high API. Middle-aged to older women had higher API values and a higher prevalence of high API than men in the same age group. However, the opposite was observed among younger individuals, with women having lower API values than men. This study also identified a J-shaped relationship between API and age, where API values began to increase at a certain age and rapidly increased after that. In women, the API started to increase at 31 years of age and rapidly increased after 54 years of age. In men, the API started to increase at 38 years of age, followed by a rapid increase after 53 years of age.

CONCLUSION

This study's observation of a significant age-sex interaction in small-to-medium-sized arterial stiffening offers a valuable explanation for cardiovascular disease risk and provides important parameters for using API measurements to evaluate such risk.

The Role of Heart Rate Variability (HRV) in Different Hypertensive Syndromes

Cardiac innervation by the parasympathetic nervous system (PNS) and the sympathetic nervous system (SNS) modulates the heart rate (HR) (chronotropic activity) and the contraction of the cardiac muscle (inotropic activity). The peripheral vasculature is controlled only by the SNS, which is responsible for peripheral vascular resistance. This also mediates the baroreceptor reflex (BR), which in turn mediates blood pressure (BP). Hypertension (HTN) and the autonomic nervous system (ANS) are closely related, such that derangements can lead to vasomotor impairments and several comorbidities, including obesity, hypertension, resistant hypertension, and chronic kidney disease. Autonomic dysfunction is also associated with functional and structural changes in target organs (heart, brain, kidneys, and blood vessels), increasing cardiovascular risk. Heart rate variability (HRV) is a method of assessing cardiac autonomic modulation. This tool has been used for clinical evaluation and to address the effect of therapeutic interventions. The present review aims (a) to approach the heart rate (HR) as a CV risk factor in hypertensive patients; (b) to analyze the heart rate variability (HRV) as a "tool" to estimate the individual risk stratum for Pre-HTN (P-HTN), Controlled-HTN (C-HTN), Resistant and Refractory HTN (R-HTN and Rf-HTN, respectively), and hypertensive patients with chronic renal disease (HTN+CKD).

Central Arterial Dynamic Evaluation from Peripheral Blood Pressure Waveforms Using CycleGAN: An In Silico Approach

Arterial stiffness is a major condition related to many cardiovascular diseases. Traditional approaches in the assessment of arterial stiffness supported by machine learning techniques are limited to the pulse wave velocity (PWV) estimation based on pressure signals from the peripheral arteries. Nevertheless, arterial stiffness can be assessed based on the pressure-strain relationship by analyzing its hysteresis loop. In this work, the capacity of deep learning models based on generative adversarial networks (GANs) to transfer pressure signals from the peripheral arterial region to pressure and area signals located in the central arterial region is explored. The studied signals are from a public and validated virtual database. Compared to other works in which the assessment of arterial stiffness was performed via PWV, in the present work the pressure-strain hysteresis loop is reconstructed and evaluated in terms of classical machine learning metrics and clinical parameters. Least-square GAN (LSGAN) and Wasserstein GAN with gradient penalty (WGAN-GP) adversarial losses are compared, yielding better results with LSGAN. LSGAN mean ± standard deviation of error for pressure and area pulse waveforms are 0.8 ± 0.4 mmHg and 0.1 ± 0.1 cm², respectively. Regarding the pressure-strain elastic modulus, it is achieved a mean absolute percentage error of 6.5 ± 5.1%. GAN-based deep learning models can recover the pressure-strain loop of central arteries while observing pressure signals from peripheral arteries.

High Pulsatile Load Decreases Arterial Stiffness: An ex vivo Study

Measuring arterial stiffness has recently gained a lot of interest because it is a strong predictor for cardiovascular events and all-cause mortality. However, assessing blood vessel stiffness is not easy and the in vivo measurements currently used provide only limited information. Ex vivo experiments allow for a more thorough investigation of (altered) arterial biomechanical properties. Such experiments can be performed either statically or dynamically, where the latter better corresponds to physiological conditions. In a dynamic setup, arterial segments oscillate between two predefined forces, mimicking the diastolic and systolic pressures from an in vivo setting. Consequently, these oscillations result in a pulsatile load (i.e., the pulse pressure). The importance of pulse pressure on the ex vivo measurement of arterial stiffness is not completely understood. Here, we demonstrate that pulsatile load modulates the overall stiffness of the aortic tissue in an ex vivo setup. More specifically, increasing pulsatile load softens the aortic tissue. Moreover, vascular smooth muscle cell (VSMC) function was affected by pulse pressure. VSMC contraction and basal tonus showed a dependence on the amplitude of the applied pulse pressure. In addition, two distinct regions of the aorta, namely the thoracic descending aorta (TDA) and the abdominal infrarenal aorta (AIA), responded differently to changes in pulse pressure. Our data indicate that pulse pressure alters ex vivo measurements of arterial stiffness and should be considered as an important variable in future experiments. More research should be conducted in order to determine which biomechanical properties are affected due to changes in pulse pressure. The elucidation of the underlying pulse pressure-sensitive properties would improve our understanding of blood vessel biomechanics and could potentially yield new therapeutic insights.

An integrated set-up for ex vivo characterisation of biaxial murine artery biomechanics under pulsatile conditions

Ex vivo characterisation of arterial biomechanics enables detailed discrimination of the various cellular and extracellular contributions to arterial stiffness. However, ex vivo biomechanical studies are commonly performed under quasi-static conditions, whereas dynamic biomechanical behaviour (as relevant in vivo) may differ substantially. Hence, we aim to (1) develop an integrated set-up for quasi-static and dynamic biaxial biomechanical testing, (2) quantify set-up reproducibility, and (3) illustrate the differences in measured arterial stiffness between quasi-static and dynamic conditions. Twenty-two mouse carotid arteries were mounted between glass micropipettes and kept fully vasodilated. While recording pressure, axial force (F), and inner diameter, arteries were exposed to (1) quasi-static pressure inflation from 0 to 200 mmHg; (2) 300 bpm dynamic pressure inflation (peaking at 80/120/160 mmHg); and (3) axial stretch (λ_z) variation at constant pressures of 10/60/100/140/200 mmHg. Measurements were performed in duplicate. Single-point pulse wave velocities (PWV; Bramwell-Hill) and axial stiffness coefficients (c_ax = dF/dλ_z) were calculated at the in vivo value of λ_z. Within-subject coefficients of variation were ~ 20%. Dynamic PWVs were consistently higher than quasi-static PWVs (p < 0.001); c_ax increased with increasing pressure. We demonstrated the feasibility of ex vivo biomechanical characterisation of biaxially-loaded murine carotid arteries under pulsatile conditions, and quantified reproducibility allowing for well-powered future study design.

Synthetic photoplethysmography (PPG) of the radial artery through parallelized Monte Carlo and its correlation to body mass index (BMI)

Cardiovascular disease is one of the leading causes of death in the United States and obesity significantly increases the risk of cardiovascular disease. The measurement of blood pressure (BP) is critical in monitoring and managing cardiovascular disease hence new wearable devices are being developed to make BP more accessible to physicians and patients. Several wearables utilize photoplethysmography from the wrist vasculature to derive BP assessment although many of these devices are still at the experimental stage. With the ultimate goal of supporting instrument development, we have developed a model of the photoplethysmographic waveform derived from the radial artery at the volar surface of the wrist. To do so we have utilized the relation between vessel biomechanics through Finite Element Method and Monte Carlo light transport model. The model shows similar features to that seen in PPG waveform captured using an off the shelf device. We observe the influence of body mass index on the PPG signal. A degradation the PPG signal of up to 40% in AC to DC signal ratio was thus observed.

Effects of aerobic, resistance and concurrent exercise on pulse wave reflection and autonomic modulation in men with elevated blood pressure

The acute effects of exercise modes on pulse wave reflection (PWR) and their relationship with autonomic control remain undefined, particularly in individuals with elevated blood pressure (BP). We compared PWR and autonomic modulation after acute aerobic (AE), resistance (RE), and concurrent exercise (CE) in 15 men with stage-1 hypertension (mean ± SE: 34.7 ± 2.5 years, 28.4 ± 0.6 kg/m², 133 ± 1/82 ± 2 mmHg). Participants underwent AE, RE, and CE on different days in counterbalanced order. Applanation tonometry and heart rate variability assessments were performed before and 30-min postexercise. Aortic pressure decreased after AE (− 2.4 ± 0.7 mmHg; P = 0.01), RE (− 2.2 ± 0.6 mmHg; P = 0.03), and CE (− 3.1 ± 0.5 mmHg; P = 0.003). Augmentation index remained stable after RE, but lowered after AE (− 5.1 ± 1.7%; P = 0.03) and CE (− 7.6 ± 2.4% P = 0.002). Systolic BP reduction occurred after CE (− 5.3 ± 1.9 mmHg). RR-intervals and parasympathetic modulation lowered after all conditions (~ 30–40%; P < 0.05), while the sympathovagal balance increased after RE (1.2 ± 0.3–1.3 ± 0.3 n.u., P < 0.05). Changes in PWR correlated inversely with sympathetic and directly with vagal modulation in CE. In conclusion, AE, RE, and CE lowered central aortic pressure, but only AE and CE reduced PWR. Overall, those reductions related to decreased parasympathetic and increased sympathetic outflows. Autonomic fluctuations seemed to represent more a consequence than a cause of reduced PWR.

Deep Learning-Based Diagnosis of Peripheral Artery Disease via Continuous Property-Adversarial Regularization: Preliminary in Silico Study

This paper presents a novel deep learning-based arterial pulse wave analysis (PWA) approach to diagnosis of peripheral artery occlusive disease (PAD). Naïve application of deep learning to PAD diagnosis can be hampered by the fact that securing a large amount of longitudinal dataset encompassing diverse PAD severity as well as anatomical and physiological variability presents formidable challenge. Training of a deep neural network (DNN) to a small training dataset raises the risk of overfitting the PAD diagnosis algorithm only to the individuals in the training dataset while deteriorating its ability to generalize also to other individuals who may exhibit a large variability in anatomical and physiological characteristics beyond the training dataset. To overcome these obstacles, we propose a continuous property-adversarial regularization (CPAR) approach to robust generalization of a DNN against scarce datasets. Our approach fosters the exploitation of latent features that can facilitate the intended task independently of confounding property-induced disturbances. by regularizing the extraction of disturbance-dependent latent features in the network's feature extraction layer. By training and testing a deep convolutional neural network (CNN) for PAD diagnosis using scarce virtual datasets, we illustrated that the CNN trained by our approach was superior to a conventionally trained CNN in detecting and assessing the severity of PAD against disturbances originating from diversity in the patients' height and arterial stiffness: when trained with one-time pulse wave signal measurement at ankle and brachial arteries in a small number of patients, our approach achieved detection accuracy of >90% and severity assessment of 0.83 in r² value, which were >15% and >40% improvement over conventional approach without CPAR. In addition, we ascertained the advantage of our approach in efficient training and robust generalization of DNN by contrasting it to multi-task learning which promotes the exploitation (as opposed to regularization in CPAR) of disturbance-dependent latent features in fulfilling the intended tasks.

Study on the Relationship Between Orthostatic Hypotension and Heart Rate Variability, Pulse Wave Velocity Index, and Frailty Index in the Elderly: A Retrospective Observational Study

Background: Orthostatic hypotension (OH) is a common disease of the elderly. It is generally believed that the pathogenesis of OH is related to the impairment of autonomic nerve function and the decreased vascular capacity regulation. This study aims to explore the relationship between OH and heart rate variability (HRV) parameters, which reflects autonomic nerve function; ankle-brachial pressure index (ABI), which reflects the degree of vascular stenosis; pulse wave velocity (PWV) index, which reflects vascular stiffness; and frailty index (FI), which reflects the overall health status of the elderly. Methods: From January to September 2018, 24-h HOLTER monitoring, PWV, and ABI were performed in 108 elderly patients with OH and 64 elderly patients who underwent physical examination in our hospital. Analysis software was used to record the subject's standard deviation of the cardiac cycle (SDNN), the standard deviation of the 5-min average cardiac cycle (SDANN), the square root of the average square sum of consecutive n-interval differences (rMSSD), the percentage of the number of adjacent cardiac interval differences >50 ms (pNN50), low frequency (LF), high frequency (HF), very low frequency (VLF), and low frequency/high frequency ratio (LF/HF). Then, FI was evaluated qualitatively and quantitatively in the form of a scale. Results: There was no statistical difference between the two groups on the basis of age, sex, body mass index (BMI), low-density lipoprotein (LDL), resting heart rate, blood pressure, fasting blood glucose, long-term medication, etc. There were significant differences in PWV, SDNN, LF, VLF, and LF/HF between the two groups (P < 0.05). The risk factor of OH in the qualitative (P = 0.04) and quantitative (P = 0.007) index FI was higher in the OH group than in the control group. The risk factors of OH were PWV, SDNN, VLF, LF/HF, and FI, where FI was positively correlated and LF/HF was negatively correlated. Conclusions: The pathogenesis of OH is related to vascular stiffness, imbalance of autonomic nerve regulation, and its comprehensive health status in the elderly. However, arteriosclerosis has not been confirmed as an independent risk factor. Clinical Trial Registration: Retrospectively registered, http://www.chictr.org.cn.

Detection and Severity Assessment of Peripheral Occlusive Artery Disease via Deep Learning Analysis of Arterial Pulse Waveforms: Proof-of-Concept and Potential Challenges

Toward the ultimate goal of affordable and non-invasive screening of peripheral occlusive artery disease (PAD), the objective of this work is to investigate the potential of deep learning-based arterial pulse waveform analysis in detecting and assessing the severity of PAD. Using an established transmission line model of arterial hemodynamics, a large number of virtual patients associated with PAD of a wide range of severity and the corresponding arterial pulse waveform data were created. A deep convolutional neural network capable of detecting and assessing the severity of PAD based on the analysis of brachial and ankle arterial pulse waveforms was constructed, evaluated for efficacy, and compared with the state-of-the-art ankle-brachial index (ABI) using the virtual patients. The results suggested that deep learning may diagnose PAD more accurately and robustly than ABI. In sum, this work demonstrates the initial proof-of-concept of deep learning-based arterial pulse waveform analysis for affordable and convenient PAD screening as well as presents challenges that must be addressed for real-world clinical applications.

Assessment of Fractional-Order Arterial Windkessel as a Model of Aortic Input Impedance

Goal: Fractional-order Windkessel model is proposed to describe the aortic input impedance. Compared with the conventional arterial Windkessel, the main advantage of the proposed model is the consideration of the viscoelastic nature of the arterial wall using the fractional-order capacitor (FOC). Methods: The proposed model, along with the standard two-element Windkessel, three-element Windkessel, and the viscoelastic Windkessel models, are assessed and compared using in-silico data. Results: The results show that the fractional-order model fits better the moduli of the aortic input impedance and fairly approximates the phase angle. In addition, by its very nature, the pseudo-capacitance of FOC makes the proposed model's dynamic compliance complex and frequency-dependent. Conclusions: The analysis of the proposed fractional-order model indicates that fractional-order impedance yields a powerful tool for a flexible characterization of the arterial hemodynamics.

Measuring Arterial Stiffness in Animal Experimental Studies

The arterial wall is a composite material of elastin, collagen, and extracellular matrix with acutely modifiable material properties through the action of smooth muscle cells. Therefore, arterial stiffness is a complex parameter that changes not only with long-term remodeling of the wall constituents but also with acute contraction or relaxation of smooth muscle or with changes in the acute distending pressure to which the artery is exposed. It is not possible to test all these aspects using noninvasive or even invasive techniques in humans. Full characterization of the mechanical properties of the artery and the specific arterial factors causing changes to stiffness with disease or modified lifestyle currently require animal studies. This article summarizes the major in vivo and ex vivo techniques to measure the different aspects of arterial stiffness in animal studies.

Multimodal Image-Free Ultrasound Technique for Evaluation of Arterial Viscoelastic Properties: A Feasibility Study

In this article, we have presented a multimodal system and a novel probe design that was built around an image-free ultrasound technology, ARTSENS®, for measurement of arterial viscoelastic properties. ARTSENS® was extensively validated over the years, for performing measurements of arterial wall dynamics and stiffness with an accuracy that meets clinical standards. Concerning this work, several enhancements were incorporated to this basic technology that allowed high frame rate A-scan imaging (1 kHz) and integration of a pressure measuring module for automated measurements of the viscoelastic parameter (elastic index, viscous index and wall buffering function). The functionality of the developed multimodal system and probe were investigated by conducting an in-vivo on 8 young subjects (both normotensive and hypertensive were included). The beat-to-beat measurements of the viscoelastic parameters exhibited acceptable repeatability with a variability <; 6.5%. It was observed that the group average for viscosity index and the wall buffering function were higher for hypertensive subjects as compared to normotensive subjects. The study observations were consistent with the reported literature. The proposed system addresses several issues associated with the traditional image-based systems and offers huge advantage of field amenability thus making it favorable for large population screening and studies.

Estimation of wave reflection in aorta from radial pulse waveform by artificial neural network: a numerical study

BACKGROUND AND OBJECTIVE

Wave reflection in aorta has been shown to have incremental value for predicting cardiovascular events. However, its estimation by wave separation analysis (WSA) is complex.

METHODS

In this study, a novel method was proposed based on a cascade artificial neural network (ANN) for wave reflection estimation by the frequency features of radial pressure waveform alone. The simulation database of 4000 samples was generated by a 55-segment transmission line model of human arterial tree and was used for evaluating the ANN with 10-fold cross validation for the estimation of reflection magnitude (RM_ANN) and reflection index (RI_ANN) of wave reflection in aorta. RM and RI also were estimated by the WSA with a triangle waveform of aortic flow (RM_WSA and RI_WSA) and with a real aortic flow waveform (RM_Ref and RI_Ref) as reference values.

RESULTS

The results showed the correlation coefficient and mean difference between RM_ANN and RM_Ref (R² = 0.92, mean ± standard deviation (SD) = 0.0 ± 0.02) and those between RI_ANN and RI_Ref (R² = 0.91, mean ± SD = 0.0 ± 0.01) were better than those between RM_WSA and RM_Ref (R² = 0.51, mean ± SD = 0.01 ± 0.07) and those between RI_WSA and RI_Ref (R² = 0.50, mean ± SD = 0.0 ± 0.02). As the sample diversity in the simulation database was increased but the total number of samples keeps constant, the advantage of the ANN, though decreased slightly, became more significant than those of WSA (RM_ANN VS. RM_Ref and RI_ANN VS. RI_Ref: R² = 0.88 and 0.88, mean ± SD = 0.0 ± 0.05 and 0.0 ± 0.05; RM_WSA VS. RM_Ref and RI_WSA VS. RI_Ref: R² = 0.24 and 0.24, mean ± SD = 0.07 ± 0.24 and 0.02 ± 0.08, respectively). In addition, the ANN can achieve better results than the traditional method WSA even only two hidden neurons are used.

CONCLUSIONS

ANN is a potential method for the estimation of wave reflection in aorta by a single radial pulse waveform, but further validation of this method in clinic trials is needed.

Smooth muscle cell and arterial aging: basic and clinical aspects

Arterial aging engages a plethora of key signalling pathways that act in concert to induce vascular smooth muscle cell (VSMC) phenotypic changes leading to vascular degeneration and extracellular matrix degradation responsible for alterations of the mechanical properties of the vascular wall. This review highlights proof-of-concept examples of components of the extracellular matrix, VSMC receptors which connect extracellular and intracellular structures, and signalling pathways regulating changes in mechanotransduction and vascular homeostasis in aging. Furthermore, it provides a new framework for understanding how VSMC stiffness and adhesion to extracellular matrix contribute to arterial stiffness and how interactions with endothelial cells, platelets, and immune cells can regulate vascular aging. The identification of the key players of VSMC changes operating in large and small-sized arteries in response to increased mechanical load may be useful to better elucidate the causes and consequences of vascular aging and associated progression of hypertension, arteriosclerosis, and atherosclerosis.

Isolated systolic hypertension in the young: a position paper endorsed by the European Society of Hypertension

: Whether isolated systolic hypertension in the young (ISHY) implies a worse outcome and needs antihypertensive treatment is still a matter for dispute. ISHY is thought to have different mechanisms than systolic hypertension in the elderly. However, findings from previous studies have provided inconsistent results. From the analysis of the literature, two main lines of research and conceptualization have emerged. Simultaneous assessment of peripheral and central blood pressure led to the identification of a condition called pseudo or spurious hypertension, which was considered an innocent condition. However, an increase in pulse wave velocity has been found by some authors in about 20% of the individuals with ISHY. In addition, obesity and metabolic disturbances have often been documented to be associated with ISHY both in children and young adults. The first aspect to consider whenever evaluating a person with ISHY is the possible presence of white-coat hypertension, which has been frequently found in this condition. In addition, assessment of central blood pressure is useful for identifying ISHY patients whose central blood pressure is normal. ISHY is infrequently mentioned in the guidelines on diagnosis and treatment of hypertension. According to the 2013 European Guidelines on the management of hypertension, people with ISHY should be followed carefully, modifying risk factors by lifestyle changes and avoiding antihypertensive drugs. Only future clinical trials will elucidate if a benefit can be achieved with pharmacological treatment in some subgroups of ISHY patients with associated risk factors and/or high central blood pressure.

No association between aortic stiffness and liver steatosis in morbidly obese patients

BACKGROUND AND AIMS

Patients with non-alcoholic fatty liver disease are characterized by increased aortic stiffness, but it is unclear whether this is related to non-alcoholic fatty liver disease itself or concomitant metabolic syndrome components, including hypertension and diabetes. Previous studies were methodologically limited by ultrasound-based assessment of liver steatosis or performing liver biopsy in patients with more severe disease. Therefore, we prospectively measured aortic pulse wave velocity (aPWV) in non-selected obese subjects admitted for bariatric surgery with liver biopsy, allowing assessment of the association between aortic stiffness and biopsy-confirmed liver steatosis.

METHODS

We evaluated 120 consecutive severely obese patients (79 females; mean age 42 ± 10 years, mean body mass index 45.0 ± 5.3 kg/m²) without cardiac disease or alcohol-induced liver disease, who were admitted for bariatric surgery. The presence or absence of liver steatosis was defined by wedge liver biopsy. aPWV was measured with the Doppler method at the time of preoperative transthoracic echocardiography.

RESULTS

Based on liver biopsy results, 82 patients (68%) had liver steatosis and 38 (32%) had no steatosis. Univariate linear regression analysis showed that age, mean arterial pressure, liver steatosis, heart rate, female gender, and diabetes were significantly associated with aPWV. However, only age, mean arterial pressure, heart rate, and diabetes remained significant in the multivariate model (p ≤ 0.001).

CONCLUSIONS

We found no independent association between biopsy-confirmed liver steatosis and aortic stiffness measured by Doppler aPWV in morbidly obese individuals. Aortic stiffness in these subjects is related to comorbidities and not to non-alcoholic fatty liver disease itself.

Constitutive interpretation of arterial stiffness in clinical studies: a methodological review

Clinical assessment of arterial stiffness relies on noninvasive measurements of regional pulse wave velocity or local distensibility. However, arterial stiffness measures do not discriminate underlying changes in arterial wall constituent properties (e.g., in collagen, elastin, or smooth muscle), which is highly relevant for development and monitoring of treatment. In arterial stiffness in recent clinical-epidemiological studies, we systematically review clinical-epidemiological studies (2012–) that interpreted arterial stiffness changes in terms of changes in arterial wall constituent properties (63 studies included of 514 studies found). Most studies that did so were association studies (52 of 63 studies) providing limited causal evidence. Intervention studies (11 of 63 studies) addressed changes in arterial stiffness through the modulation of extracellular matrix integrity (5 of 11 studies) or smooth muscle tone (6 of 11 studies). A handful of studies (3 of 63 studies) used mathematical modeling to discriminate between extracellular matrix components. Overall, there exists a notable gap in the mechanistic interpretation of stiffness findings. In constitutive model-based interpretation, we first introduce constitutive-based modeling and use it to illustrate the relationship between constituent properties and stiffness measurements (“forward” approach). We then review all literature on modeling approaches for the constitutive interpretation of clinical arterial stiffness data (“inverse” approach), which are aimed at estimation of constitutive properties from arterial stiffness measurements to benefit treatment development and monitoring. Importantly, any modeling approach requires a tradeoff between model complexity and measurable data. Therefore, the feasibility of changing in vivo the biaxial mechanics and/or vascular smooth muscle tone should be explored. The effectiveness of modeling approaches should be confirmed using uncertainty quantification and sensitivity analysis. Taken together, constitutive modeling can significantly improve clinical interpretation of arterial stiffness findings.

Measuring Blood Pulse Wave Velocity with Bioimpedance in Different Age Groups

In this project, we have studied the use of electrical impedance cardiography as a possible method for measuring blood pulse wave velocity, and hence be an aid in the assessment of the degree of arteriosclerosis. Using two different four-electrode setups, we measured the timing of the systolic pulse at two locations, the upper arm and the thorax, and found that the pulse wave velocity was in general higher in older volunteers and furthermore that it was also more heart rate dependent for older subjects. We attribute this to the fact that the degree of arteriosclerosis typically increases with age and that stiffening of the arterial wall will make the arteries less able to comply with increased heart rate (and corresponding blood pressure), without leading to increased pulse wave velocity. In view of these findings, we conclude that impedance cardiography seems to be well suited and practical for pulse wave velocity measurements and possibly for the assessment of the degree of arteriosclerosis. However, further studies are needed for comparison between this approach and reference methods for pulse wave velocity and assessment of arteriosclerosis before any firm conclusions can be drawn.

Three-Element Fractional-Order Viscoelastic Arterial Windkessel Model

Arterial hemodynamic assessment has always been essential for clinical Cardiovascular System (CVS) diagnosis. Using Windkessel (WK) lumped parametric model as non-invasive measurement tool provides the potential of achieving a very convenient, computational inexpensive and accurate prediction of the arterial parameters. Many versions of WK models have been proposed and extensively studied, over the last century. In general, they can be classified into two categories: elastic and viscoelastic models. Recently, several studies have discussed the potential of describing the arterial wall viscoelasticity using fractional order models, reducing the number of parameters and exposing a natural response. Hence, a key missing item in the arterial Windkessel modeling is a fractional-order analog component that can provide a reliable, realistic and reduced representation of the fractional viscoelasticity behavior. In this paper, we present, for the first time, a three-element fractional-order viscoelastic Windkessel model. The proposed model incorporates a fractional-order capacitor that substitutes the ideal capacitor of standard three-elements WK model. The latter non-ideal element combines both resistive and capacitive properties which displays viscoelastic behavior of the arterial vessel. The contribution of both properties is controlled by the fractional differentiation order α enabling an accurate and reliable physiological description.

Proinflammatory Arterial Stiffness Syndrome: A Signature of Large Arterial Aging

Age-associated structural and functional remodeling of the arterial wall produces a productive environment for the initiation and progression of hypertension and atherosclerosis. Chronic aging stress induces low-grade proinflammatory signaling and causes cellular proinflammation in arterial walls, which triggers the structural phenotypic shifts characterized by endothelial dysfunction, diffuse intimal-medial thickening, and arterial stiffening. Microscopically, aged arteries exhibit an increase in arterial cell senescence, proliferation, invasion, matrix deposition, elastin fragmentation, calcification, and amyloidosis. These characteristic cellular and matrix alterations not only develop with aging but can also be induced in young animals under experimental proinflammatory stimulation. Interestingly, these changes can also be attenuated in old animals by reducing low-grade inflammatory signaling. Thus, mitigating age-associated proinflammation and arterial phenotype shifts is a potential approach to retard arterial aging and prevent the epidemic of hypertension and atherosclerosis in the elderly.

Statistical considerations in reporting cardiovascular research

The problem of inadequate statistical reporting is long standing and widespread in the biomedical literature, including in cardiovascular physiology. Although guidelines for reporting statistics have been available in clinical medicine for some time, there are currently no guidelines specific to cardiovascular physiology. To assess the need for guidelines, we determined the type and frequency of statistical tests and procedures currently used in the American Journal of Physiology-Heart and Circulatory Physiology. A PubMed search for articles published in the American Journal of Physiology-Heart and Circulatory Physiology between January 1, 2017, and October 6, 2017, provided a final sample of 146 articles evaluated for methods used and 38 articles for indepth analysis. The t-test and ANOVA accounted for 71% (212 of 300 articles) of the statistical tests performed. Of six categories of post hoc tests, Bonferroni and Tukey tests were used in 63% (62 of 98 articles). There was an overall lack in details provided by authors publishing in the American Journal of Physiology-Heart and Circulatory Physiology, and we compiled a list of recommended minimum reporting guidelines to aid authors in preparing manuscripts. Following these guidelines could substantially improve the quality of statistical reports and enhance data rigor and reproducibility.

Physics of fractional imaging in biomedicine

The mathematics of imaging is a growing field of research and is evolving rapidly parallel to evolution in the field of imaging. Imaging, which is a sub-field of biomedical engineering, considers novel approaches to visualize biological tissues with the general goal of improving health. "Medical imaging research provides improved diagnostic tools in clinical settings and supports the development of drugs and other therapies. The data acquisition and diagnostic interpretation with minimum error are the important technical aspects of medical imaging. The image quality and resolution are really important in portraying the internal aspects of patient's body. Although there are several user friendly resources for processing image features, such as enhancement, colour manipulation and compression, the development of new processing methods is still worthy of efforts. In this article we aim to present the role of fractional calculus in imaging with the aid of practical examples.