Feasibility of Estimation of Aortic Wave Intensity Using Non-invasive Pressure Recordings in the Absence of Flow Velocity in Man

Aortic reservoir-excess pressure parameters are associated with worse cognitive function in people with untreated stage II/III hypertension

OBJECTIVE

Hypertension is a recognized risk factor for the development of cognitive impairment and dementia in older adults. Aortic stiffness and altered haemodynamics could promote the transmission of detrimental high pressure pulsatility into the cerebral circulation, potentially damaging brain microvasculature and leading to cognitive impairment. We determined whether reservoir-excess pressure parameters were associated with cognitive function in people with hypertension (HT) and normotension (NT).

METHODS

We studied 35 middle-aged and older treatment-naïve stage II/III HT (office systolic BP 176 ± 17 mmHg) and 35 age-, sex- and body mass index-matched NT (office systolic BP 127 ± 8 mmHg). Parameters derived from reservoir-excess pressure analysis including reservoir pressure integral (INTPR), excess pressure integral (INTXSP), systolic rate constant (SRC), diastolic rate constant (DRC) and pulse wave velocity (PWV) were calculated from an ensemble-averaged aortic pressure waveform derived from radial artery tonometry. Cognitive function was assessed using the Addenbrooke's Cognitive Examination Revised (ACE-R), Trail Making Test Part A (TMT-A) and Part B (TMT-B).

RESULTS

All reservoir-excess pressure parameters were greater in HT than NT (all P < 0.05). Greater INTXSP was associated with lower ACE-R score (rs = -0.31), longer TMT-A (r = 0.31) and TMT-B (r = 0.38). Likewise, greater DRC and PWV were also associated with lower ACE-R score (rs = -0.27 and rs = -0.33), longer TMT-A (r = 0.51 and r = 0.40) and TMT-B (r = 0.38 and r = 0.32). Greater INTXSP, DRC and PWV are consistently associated with worse cognitive function in this study.

CONCLUSIONS

These observations support a potential mechanistic link between adverse haemodynamics and a heightened risk of cognitive impairment in older adults with hypertension.

A new methodology for determining the central pressure waveform from peripheral measurement using Fourier-based machine learning

Radial applanation tonometry is a well-established technique for hemodynamic monitoring and is becoming popular in affordable non-invasive wearable healthcare electronics. To assess the central aortic pressure using radial-based measurements, there is an essential need to develop mathematical approaches to estimate the central pressure waveform. In this study, we propose a new Fourier-based machine learning (F-ML) methodology to transfer non-invasive radial pressure measurements to the central pressure waveform. To test the method, collection of tonometry recordings of the radial and carotid pressure measurements are used from the Framingham Heart Study (2640 individuals, 55 % women) with mean (range) age of 66 (40-91) years. Method-derived estimates are significantly correlated with the measured ones for three major features of the pressure waveform (systolic blood pressure, r=0.97, p < 0.001; diastolic blood pressure, r=0.99, p < 0.001; and mean blood pressure, r=0.99, p < 0.001). In all cases, the Bland-Altman analysis shows negligible bias in the estimations and error is bounded to 5.4 mmHg. Findings also suggest that the F-ML approach reconstructs the shape of the central pressure waveform accurately with the average normalized root mean square error of 5.5 % in the testing population which is blinded to all stages of machine learning development. The results show that the F-ML transfer function outperforms the conventional generalized transfer function, particularly in terms of reconstructing the shape of the central pressure waveform morphology. The proposed F-ML transfer function can provide accurate estimates for the central pressure waveform, and ultimately expand the usage of non-invasive devices for central hemodynamic assessment.

Measures of wave intensity as a non-invasive surrogate for cardiac function predicts mortality in haemodialysis patients

Background

Risk prediction in haemodialysis (HD) patients is challenging due to the impact of the dialysis regime on the patient's volume status and the complex interplay with cardiac function, comorbidities and hypertension. Cardiac function as a key predictor of cardiovascular (CV) mortality in HD patients is challenging to assess in daily routine. Thus the aim of this study was to investigate the association of a novel, non-invasive relative index of systolic function with mortality and to assess its interplay with volume removal.

Methods

A total of 558 (373 male/185 female) HD patients with a median age of 66 years were included in this analysis. They underwent 24-hour ambulatory blood pressure monitoring, including wave intensity analysis [i.e. S:D ratio (SDR)]. All-cause and CV mortality served as endpoints and multivariate proportional hazards models were used for risk prediction. Intradialytic changes were analysed in tertiles according to ultrafiltration volume. During a follow-up of 37.8 months, 193 patients died (92 due to CV reasons).

Results

The SDR was significantly associated with all-cause {univariate hazard ratio [HR] 1.36 [95% confidence interval (CI) 1.20-1.54], P < .001} and CV [univariate HR 1.41 (95% CI 1.20-1.67), P < .001] mortality. The associations remained significant in multivariate analysis accounting for possible confounders. Changes in the SDR from pre-/early- to post-dialytic averages were significantly different for the three ultrafiltration volume groups.

Conclusion

This study provides well-powered evidence for the independent association of a novel index of systolic function with mortality. Furthermore, it revealed a significant association between intradialytic changes of the measure and intradialytic volume removal.

Mechanistic insights on age-related changes in heart-aorta-brain hemodynamic coupling using a pulse wave model of the entire circulatory system

Age-related changes in aortic biomechanics can impact the brain by reducing blood flow and increasing pulsatile energy transmission. Clinical studies have shown that impaired cardiac function in patients with heart failure is associated with cognitive impairment. Although previous studies have attempted to elucidate the complex relationship between age-associated aortic stiffening and pulsatility transmission to the cerebral network, they have not adequately addressed the effect of interactions between aortic stiffness and left ventricle (LV) contractility (neither on energy transmission nor on brain perfusion). In this study, we use a well-established and validated one-dimensional blood flow and pulse wave computational model of the circulatory system to address how age-related changes in cardiac function and vasculature affect the underlying mechanisms involved in the LV-aorta-brain hemodynamic coupling. Our results reveal how LV contractility affects pulsatile energy transmission to the brain, even with preserved cardiac output. Our model demonstrates the existence of an optimal heart rate (near the normal human heart rate) that minimizes pulsatile energy transmission to the brain at different contractility levels. Our findings further suggest that the reduction in cerebral blood flow at low levels of LV contractility is more prominent in the setting of age-related aortic stiffening. Maintaining optimal blood flow to the brain requires either an increase in contractility or an increase in heart rate. The former consistently leads to higher pulsatile power transmission, and the latter can either increase or decrease subsequent pulsatile power transmission to the brain.NEW & NOTEWORTHY We investigated the impact of major aging mechanisms of the arterial system and cardiac function on brain hemodynamics. Our findings suggest that aging has a significant impact on heart-aorta-brain coupling through changes in both arterial stiffening and left ventricle (LV) contractility. Understanding the underlying physical mechanisms involved here can potentially be a key step for developing more effective therapeutic strategies that can mitigate the contributions of abnormal LV-arterial coupling toward neurodegenerative diseases and dementia.

Wave reflection quantification analysis and personalized flow wave estimation based on the central aortic pressure waveform

Pulse wave reflections reflect cardiac afterload and perfusion, which yield valid indicators for monitoring cardiovascular status. Accurate quantification of pressure wave reflections requires the measurement of aortic flow wave. However, direct flow measurement involves extra equipment and well-trained operator. In this study, the personalized aortic flow waveform was estimated from the individual central aortic pressure waveform (CAPW) based on pressure-flow relations. The separated forward and backward pressure waves were used to calculate wave reflection indices such as reflection index (RI) and reflection magnitude (RM), as well as the central aortic pulse transit time (PTT). The effectiveness and feasibility of the method were validated by a set of clinical data (13 participants) and the Nektar1D Pulse Wave Database (4,374 subjects). The performance of the proposed personalized flow waveform method was compared with the traditional triangular flow waveform method and the recently proposed lognormal flow waveform method by statistical analyses. Results show that the root mean square error calculated by the personalized flow waveform approach is smaller than that of the typical triangular and lognormal flow methods, and the correlation coefficient with the measured flow waveform is higher. The estimated personalized flow waveform based on the characteristics of the CAPW can estimate wave reflection indices more accurately than the other two methods. The proposed personalized flow waveform method can be potentially used as a convenient alternative for the measurement of aortic flow waveform.

Sex differences in pressure and flow waveform physiology across the life course

Cardiovascular disease (CVD) has long been deemed a disease of old men. However, in 2019 CVD accounted for 35% of all deaths in women and, therefore, remains the leading cause of death in both men and women. There is increasing evidence to show that risk factors, pathophysiology and health outcomes related to CVD differ in women compared with men, yet CVD in women remains understudied, underdiagnosed and undertreated. Differences exist between the sexes in relation to the structure of the heart and vasculature, which translate into differences in blood pressure and flow waveform physiology. These physiological differences between women and men may represent an important explanatory factor contributing to the sex disparity in CVD presentation and outcomes but remain understudied. In this review we aim to describe sex differences in arterial pressure and flow waveform physiology and explore how they may contribute to differences in CVD in women compared to men. Given that unfavourable alterations in the cardiovascular structure and function can start as early as in utero, we report sex differences in waveform physiology across the entire life course.

Antihypertensive Medication Use and Its Effects on Blood Pressure and Haemodynamics in a Tri-ethnic Population Cohort: Southall and Brent Revisited (SABRE)

Objectives:

We characterised differences in BP control and use of antihypertensive medications in European (EA), South Asian (SA) and African-Caribbean (AC) people with hypertension and investigated the potential role of type 2 diabetes (T2DM), reduced arterial compliance (C_a), and antihypertensive medication use in any differences.

Methods:

Analysis was restricted to individuals with hypertension [age range 59–85 years; N = 852 (EA = 328, SA = 356, and AC =168)]. Questionnaires, anthropometry, BP measurements, echocardiography, and fasting blood assays were performed. BP control was classified according to UK guidelines operating at the time of the study. Data were analysed using generalised structural equation models, multivariable regression and treatment effect models.

Results:

SA and AC people were more likely to receive treatment for high BP and received a greater average number of antihypertensive agents, but despite this a smaller proportion of SA and AC achieved control of BP to target [age and sex adjusted odds ratio (95% confidence interval) = 0.52 (0.38, 0.72) and 0.64 (0.43, 0.96), respectively]. Differences in BP control were partially attenuated by controlling for the higher prevalence of T2DM and reduced C_a in SA and AC. There was little difference in choice of antihypertensive agent by ethnicity and no evidence that differences in efficacy of antihypertensive regimens contributed to ethnic differences in BP control.

Conclusions:

T2DM and more adverse arterial stiffness are important factors in the poorer BP control in SA and AC people. More effort is required to achieve better control of BP, particularly in UK ethnic minorities.

Accuracy and applicability of non-invasive evaluation of aortic wave intensity using only pressure waveforms in humans

Background.Wave intensity (WI) analysis is a well-established method for quantifying the energy carried in arterial waves, providing valuable clinical information about cardiovascular function. The primary drawback of this method is the need for concurrent measurements of both pressure and flow waveforms.Objective. We have for the first time investigated the accuracy of a novel methodology for estimating wave intensity employing only single pressure waveform measurements; we studied both carotid- and radial-based estimations in a large heterogeneous cohort.Approach.Tonometry was performed alongside Doppler ultrasound to acquire measurements of both carotid and radial pressure waveforms as well as aortic flow waveforms in 2640 healthy and diseased participants (1439 female) in the Framingham Heart Study. Patterns consisting of two forward waves (Wf1, Wf2) and one backward wave (Wb1) along with reflection metrics were compared with those obtained from exact WI analysis.Main Results. Carotid-based estimates correlated well for forward peak amplitudes (Wf1,r = 0.85,p < 0.05; Wf2,r = 0.72,p < 0.05) and peak time (Wf1,r = 0.94,p < 0.05; Wf2,r = 0.98,p < 0.05), and radial-based estimates correlated fairly to poorly for amplitudes (Wf1,r = 0.62,p < 0.05; Wf2,r = 0.42,p < 0.05) and peak time (Wf1,r = 0.04,p = 0.10; Wf2,r = 0.75,p < 0.05). In all cases, estimated Wb1 measures were not correlated. Reflection metrics were well correlated for healthy patients (r = 0.67,p < 0.05), moderately correlated for valvular disease (r = 0.59,p < 0.05) and fairly correlated for CVD (r = 0.46,p < 0.05) and heart failure (r = 0.49,p < 0.05).Significance. These findings indicate that pressure-only WI produces accurate results only when forward contributions are of primary interest and only for carotid pressure waveforms. The pressure-only WI estimations of this work provide an important opportunity to further the goal of uncovering clinical insights through wave analysis affordably and non-invasively.

Scalability of cardiovascular intrinsic frequencies: Validations in preclinical models and non-invasive clinical studies

AIMS

Cardiovascular intrinsic frequencies (IFs) are associated with cardiovascular health and disease, separately capturing the systolic and diastolic information contained in a single (uncalibrated) arterial waveform. Previous clinical investigations related to IF have been restricted to studying chronic conditions, and hence its applicability for acute cardiovascular diseases has not been explored. Studies of cardiovascular complications such as acute myocardial infarction are difficult to perform in humans due to the high-risk and invasive nature of such procedures. Although they can be performed in preclinical (animal) models, the corresponding interpretation of IF measures and how they ultimately translate to humans is unknown. Hence, we studied the scalability of IF across species and sensor platforms.

MATERIALS AND METHODS

Scaled values of the two intrinsic frequencies ω1 and ω2 (corresponding to systolic and diastolic dynamics, respectively) were extracted from carotid waveforms acquired either non-invasively (via tonometry, Vivio or iPhone) in humans or invasively in rabbits and rats.

KEY FINDINGS

The scaled IF parameters for all species were found to fall within the same physiological ranges carrying similar statistical characteristics, even though body sizes and corresponding heart rates of the species were substantially different. Additionally, results demonstrated that all non-invasive sensor platforms were significantly correlated with each other for scaled IFs, suggesting that such analysis is device-agnostic and can be applied to upcoming wearable technologies.

SIGNIFICANCE

Ultimately, our results found that IFs are scalable across species, which is particularly valuable for the training of IF-based artificial intelligence systems using both preclinical and clinical data.

Excess pressure as an analogue of blood flow velocity

INTRODUCTION

Derivation of blood flow velocity from a blood pressure waveform is a novel technique, which could have potential clinical importance. Excess pressure, calculated from the blood pressure waveform via the reservoir-excess pressure model, is purported to be an analogue of blood flow velocity but this has never been examined in detail, which was the aim of this study.

METHODS

Intra-arterial blood pressure was measured sequentially at the brachial and radial arteries via fluid-filled catheter simultaneously with blood flow velocity waveforms recorded via Doppler ultrasound on the contralateral arm (n = 98, aged 61 ± 10 years, 72% men). Excess pressure was derived from intra-arterial blood pressure waveforms using pressure-only reservoir-excess pressure analysis.

RESULTS

Brachial and radial blood flow velocity waveform morphology were closely approximated by excess pressure derived from their respective sites of measurement (median cross-correlation coefficient r = 0.96 and r = 0.95 for brachial and radial comparisons, respectively). In frequency analyses, coherence between blood flow velocity and excess pressure was similar for brachial and radial artery comparisons (brachial and radial median coherence = 0.93 and 0.92, respectively). Brachial and radial blood flow velocity pulse heights were correlated with their respective excess pressure pulse heights (r = 0.53, P < 0.001 and r = 0.43, P < 0.001, respectively).

CONCLUSION

Excess pressure is an analogue of blood flow velocity, thus affording the opportunity to derive potentially important information related to arterial blood flow using only the blood pressure waveform.

Wave Reflection and Ventriculo-Arterial Coupling in Bicuspid Aortic Valve Patients With Repaired Aortic Coarctation

BACKGROUND

Ventriculo-arterial (VA) coupling in bicuspid aortic valve (BAV) patients can be affected by the global aortopathy characterizing BAV disease and the presence of concomitant congenital lesions such as aortic coarctation (COA). This study aimed to isolate the COA variable and use cardiovascular magnetic resonance (CMR) imaging to perform wave intensity analysis non-invasively to shed light on VA coupling changes in BAV. The primary hypothesis was that BAV patients with COA exhibit unfavorable VA coupling, and the secondary hypothesis was that BAV patients with COA exhibit increased wave speed as a marker of reduced aortic distensibility despite successful surgical correction.

METHODS

Patients were retrospectively identified from a CMR database and divided into two groups: isolated BAV and BAV associated with repaired COA. Aortic and ventricular dimensions, global longitudinal strain (GLS), and ascending aortic flow data and area were collected and used to derive wave intensity from CMR data. The main variables for the analysis included all wave magnitudes (forward compression/expansion waves, FCW and FEW, respectively, and reflected backward compression wave, BCW) and wave speed.

RESULTS

In the comparison of patients with isolated BAV and those with BAV associated with repaired COA (n = 25 in each group), no differences were observed in left ventricular ejection fraction, GLS, or ventricular volumes, whilst significant increases in FCW and FEW magnitude were noted in the BAV and repaired COA group. The FCW inversely correlated with age and aortic size. Whilst the BCW was not significantly different compared with that in patients with/without COA, its magnitude tends to increase with a lower COA index. Patients with repaired COA exhibited higher wave speed velocity. Aortic wave speed (inversely related to distensibility) was not significantly different between the two groups.

CONCLUSION

In the absence of a significant restenosis, VA coupling in patients with BAV and COA is not negatively affected compared to patients with isolated BAV. A reduction in the magnitude of the early systolic FCW was observed in patients who were older and with larger aortic diameters.

Measurement, Analysis and Interpretation of Pressure/Flow Waves in Blood Vessels

The optimal performance of the cardiovascular system, as well as the break-down of this performance with disease, both involve complex biomechanical interactions between the heart, conduit vascular networks and microvascular beds. ‘Wave analysis’ refers to a group of techniques that provide valuable insight into these interactions by scrutinizing the shape of blood pressure and flow/velocity waveforms. The aim of this review paper is to provide a comprehensive introduction to wave analysis, with a focus on key concepts and practical application rather than mathematical derivations. We begin with an overview of invasive and non-invasive measurement techniques that can be used to obtain the signals required for wave analysis. We then review the most widely used wave analysis techniques—pulse wave analysis, wave separation and wave intensity analysis—and associated methods for estimating local wave speed or characteristic impedance that are required for decomposing waveforms into forward and backward wave components. This is followed by a discussion of the biomechanical phenomena that generate waves and the processes that modulate wave amplitude, both of which are critical for interpreting measured wave patterns. Finally, we provide a brief update on several emerging techniques/concepts in the wave analysis field, namely wave potential and the reservoir-excess pressure approach.