Assessment of model based (input) impedance, pulse wave velocity, and wave reflection in the Asklepios Cohort

Objectives : Arterial stiffness and wave reflection parameters assessed from both invasive and non-invasive pressure and flow readings are used as surrogates for ventricular and vascular load. They have been reported to predict adverse cardiovascular events, but clinical assessment is laborious and may limit widespread use. This study aims to investigate measures of arterial stiffness and central hemodynamics provided by arterial tonometry alone and in combination with aortic root flows derived by echocardiography against surrogates derived by a mathematical pressure and flow model in a healthy middle-aged cohort. Methods : Measurements of carotid artery tonometry and echocardiography were performed on 2226 ASKLEPIOS study participants and parameters of systemic hemodynamics, arterial stiffness and wave reflection based on pressure and flow were measured. In a second step, the analysis was repeated but echocardiography derived flows were substituted by flows provided by a novel mathematical model. This was followed by a quantitative method comparison. Results : All investigated parameters showed a significant association between the methods. Overall agreement was acceptable for all parameters (mean differences: -0.0102 (0.033 SD) mmHg*s/ml for characteristic impedance, 0.36 (4.21 SD) mmHg for forward pressure amplitude, 2.26 (3.51 SD) mmHg for backward pressure amplitude and 0.717 (1.25 SD) m/s for pulse wave velocity). Conclusion : The results indicate that the use of model-based surrogates in a healthy middle aged cohort is feasible and deserves further attention

Abnormal wave reflections and left ventricular hypertrophy late after coarctation of the aorta repair

Patients with repaired coarctation of the aorta are thought to have increased afterload due to abnormalities in vessel structure and function. We have developed a novel cardiovascular magnetic resonance protocol that allows assessment of central hemodynamics, including central aortic systolic blood pressure, resistance, total arterial compliance, pulse wave velocity, and wave reflections. The main study aims were to (1) characterize group differences in central aortic systolic blood pressure and peripheral systolic blood pressure, (2) comprehensively evaluate afterload (including wave reflections) in the 2 groups, and (3) identify possible biomarkers among covariates associated with elevated left ventricular mass (LVM). Fifty adult patients with repaired coarctation and 25 age- and sex-matched controls were recruited. Ascending aorta area and flow waveforms were obtained using a high temporal-resolution spiral phase-contrast cardiovascular magnetic resonance flow sequence. These data were used to derive central hemodynamics and to perform wave intensity analysis noninvasively. Covariates associated with LVM were assessed using multivariable linear regression analysis. There were no significant group differences (P≥0.1) in brachial systolic, mean, or diastolic BP. However central aortic systolic blood pressure was significantly higher in patients compared with controls (113 versus 107 mm Hg, P=0.002). Patients had reduced total arterial compliance, increased pulse wave velocity, and larger backward compression waves compared with controls. LVM index was significantly higher in patients than controls (72 versus 59 g/m(2), P<0.0005). The magnitude of the backward compression waves was independently associated with variation in LVM (P=0.01). Using a novel, noninvasive hemodynamic assessment, we have shown abnormal conduit vessel function after coarctation of the aorta repair, including abnormal wave reflections that are associated with elevated LVM

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

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

Background: Wave intensity analysis provides valuable information on ventriculo-arterial function, hemodynamics, and energy transfer in the arterial circulation. Widespread use of wave intensity analysis is limited by the need for concurrent measurement of pressure and flow waveforms. We describe a method that can estimate wave intensity patterns using only non-invasive pressure waveforms (pWIA). Methods: Radial artery pressure and left ventricular outflow tract (LVOT) flow velocity waveforms were recorded in 12 participants in the Southall and Brent Revisited (SABRE) study. Pressure waveforms were analyzed using custom-written software to derive the excess pressure (P xs ) which was scaled to peak LVOT velocity and used to calculate wave intensity. These data were compared with wave intensity calculated using the measured LVOT flow velocity waveform. In a separate study, repeat measures of pWIA were performed on 34 individuals who attended two clinic visits at an interval of ≈1 month to assess reproducibility and reliability of the method. Results: P xs waveforms were similar in shape to aortic flow velocity waveforms and the time of peak P xs and peak aortic velocity agreed closely. Wave intensity estimated using pWIA showed acceptable agreement with estimates using LVOT velocity tracings and estimates of wave intensity were similar to values reported previously in the literature. The method showed fair to good reproducibility for most parameters. Conclusion: The P xs is a surrogate of LVOT flow velocity which, when appropriately scaled, allows estimation of aortic wave intensity with acceptable reproducibility. This may enable wider application of wave intensity analysis to large studies

Aortic backward waves derived from wave separation analysis, and end-organ changes

Dissertation submitted to the Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, in fulfillment of the requirements for the degree of Master of Science in Medicine Johannesburg, 2016Aortic backward (reflected) waves are major determinants of cardiovascular events and their impact is independent of brachial blood pressure. Although aortic backward wave pressures (Pb) can be determined using a triangular flow wave form for wave separation analysis, which is a cheaper and time-efficient method, Pb derived from this approach correlates poorly with Pb derived from measured aortic flow waves. However, the comparative ability of these two Pb measurements to predict end-organ changes remains uncertain. Therefore, we aimed to compare Pb obtained using a triangular flow wave method (Pbtri) and Pb obtained using echocardiographic derived aortic flow velocity waves (Pbecho), and their relationships with left ventricular mass indexed to height2.7 (LVMI). In 394 participants from a black African community sample (age>16years), aortic haemodynamics (applanation tonometry, SphygmoCor software), aortic flow velocity and LVMI (echocardiography) were determined. Bland-Altman analysis revealed that Pbtri overestimated the backward wave pressure by an average of 3.65±3.17mmHg. However, the correlation between the two measurements was markedly high (r2=0.82). Independent of confounders, including age, Pbtri was associated with LVMI (partial r=0.14, p=0.02). Importantly, when comparing the association between Pbecho and LVMI (partial r=0.14, p=0.01) no differences were noted (p=0.35, for comparison of partial r values, Z score). The triangular flow wave form employed for wave separation analysis produces Pb values that are as closely associated with LVMI as those derived from echocardiographic aortic flow wave measurements. Thus, risk prediction using simple approaches to aortic wave separation may be employed.MT201

Automated deep phenotyping of the cardiovascular system using magnetic resonance imaging

Across a lifetime, the cardiovascular system must adapt to a great range of demands from the body. The individual changes in the cardiovascular system that occur in response to loading conditions are influenced by genetic susceptibility, and the pattern and extent of these changes have prognostic value. Brachial blood pressure (BP) and left ventricular ejection fraction (LVEF) are important biomarkers that capture this response, and their measurements are made at high resolution. Relatively, clinical analysis is crude, and may result in lost information and the introduction of noise. Digital information storage enables efficient extraction of information from a dataset, and this strategy may provide more precise and deeper measures to breakdown current phenotypes into their component parts. The aim of this thesis was to develop automated analysis of cardiovascular magnetic resonance (CMR) imaging for more detailed phenotyping, and apply these techniques for new biological insights into the cardiovascular response to different loading conditions. I therefore tested the feasibility and clinical utility of computational approaches for image and waveform analysis, recruiting and acquiring additional patient cohorts where necessary, and then applied these approaches prospectively to participants before and after six-months of exercise training for a first-time marathon. First, a multi-centre, multi-vendor, multi-field strength, multi-disease CMR resource of 110 patients undergoing repeat imaging in a short time-frame was assembled. The resource was used to assess whether automated analysis of LV structure and function is feasible on real-world data, and if it can improve upon human precision. This showed that clinicians can be confident in detecting a 9% change in EF or a 20g change in LV mass. This will be difficult to improve by clinicians because the greatest source of human error was attributable to the observer rather than modifiable factors. Having understood these errors, a convolutional neural network was trained on separate multi-centre data for automated analysis and was successfully generalizable to the real-world CMR data. Precision was similar to human analysis, and performance was 186 times faster. This real-world benchmarking resource has been made freely available (thevolumesresource.com). Precise automated segmentations were then used as a platform to delve further into the LV phenotype. Global LVEFs measured from CMR imaging in 116 patients with severe aortic stenosis were broken down into ~10 million regional measurements of structure and function, represented by computational three-dimensional LV models for each individual. A cardiac atlas approach was used to compile, label, segment and represent these data. Models were compared with healthy matched controls, and co-registered with follow-up one year after aortic valve replacement (AVR). This showed that there is a tendency to asymmetric septal hypertrophy in all patients with severe aortic stenosis (AS), rather than a characteristic specific to predisposed patients. This response to AS was more unfavourable in males than females (associated with higher NT-proBNP, and lower blood pressure), but was more modifiable with AVR. This was not detected using conventional analysis. Because cardiac function is coupled with the vasculature, a novel integrated assessment of the cardiovascular system was developed. Wave intensity theory was used to combine central blood pressure and CMR aortic blood flow-velocity waveforms to represent the interaction of the heart with the vessels in terms of traveling energy waves. This was performed and then validated in 206 individuals (the largest cohort to date), demonstrating inefficient ventriculo-arterial coupling in female sex and healthy ageing. CMR imaging was performed in 236 individuals before training for a first-time marathon and 138 individuals were followed-up after marathon completion. After training, systolic/diastolic blood pressure reduced by 4/3mmHg, descending aortic stiffness decreased by 16%, and ventriculo-arterial coupling improved by 14%. LV mass increased slightly, with a tendency to more symmetrical hypertrophy. The reduction in aortic stiffness was equivalent to a 4-year reduction in estimated biological aortic age, and the benefit was greater in older, male, and slower individuals. In conclusion, this thesis demonstrates that automating analysis of clinical cardiovascular phenotypes is precise with significant time-saving. Complex data that is usually discarded can be used efficiently to identify new biology. Deeper phenotypes developed in this work inform risk reduction behaviour in healthy individuals, and demonstrably deliver a more sensitive marker of LV remodelling, potentially enhancing risk prediction in severe aortic stenosis

The aorta after coarctation repair : effects of calibre and curvature on arterial haemodynamics (vol 21, 22, 2019)

In the original version of this article [1], published on 11 April 2019, there is 1 error in the Conclusion' paragraph of the abstract

Different associations between beta-blockers and other antihypertensive medication combinations with brachial blood pressure and aortic waveform parameters

BACKGROUND: Comparing the relationships of antihypertensive medications with brachial blood pressure (BP) and aortic waveform parameters may help clinicians to predict the effect on the latter in brachial BP-based antihypertensive therapy. We aimed to make such comparisons with new waveform measures and a wider range of antihypertensive regimens than examined previously. METHODS: Cross-sectional analysis of 2933 adults (61% male; aged 50–84 years): 1637 on antihypertensive treatment and 1296 untreated hypertensives. Sixteen medicine regimens of up to 4 combinations of drugs from 6 antihypertensive classes were analysed. Aortic systolic BP, augmentation index (AIx), excess pressure integral (EPI), backward pressure amplitude (Pb), reflection index (RI) and pulse wave velocity (PWV) were calculated from aortic pressure waveforms derived from suprasystolic brachial measurement. RESULTS: Forest plots of single-drug class comparisons across regimens with the same number of drugs (for between 1- and 3-drug regimens) revealed that AIx, Pb, RI and/or loge(EPI) were higher (maximum difference = 5.6%, 2.2 mm Hg, 0.0192 and 0.13 loge(mm Hg ⋅ s), respectively) with the use of a beta-blocker compared with vasodilators and diuretics, despite no brachial systolic and diastolic BP differences. These differences were reduced (by 34–57%) or eliminated after adjustment for heart rate, and similar effects occurred when controlling for systolic ejection period or diastolic duration. CONCLUSIONS: Beta-blocker effects on brachial BP may overestimate effects on aortic waveform parameters. Compared to other antihypertensives, beta-blockers have weaker associations with wave reflection measures and EPI; this is predominantly due to influences on heart rate

Feasibility of estimation of aortic wave intensity using non-invasive pressure recordings in the absence of flow velocity in man

Background: Wave intensity analysis provides valuable information on ventriculo-arterial function, hemodynamics, and energy transfer in the arterial circulation. Widespread use of wave intensity analysis is limited by the need for concurrent measurement of pressure and flow waveforms. We describe a method that can estimate wave intensity patterns using only non-invasive pressure waveforms (pWIA). Methods: Radial artery pressure and left ventricular outflow tract (LVOT) flow velocity waveforms were recorded in 12 participants in the Southall and Brent Revisited (SABRE) study. Pressure waveforms were analyzed using custom-written software to derive the excess pressure (Pxs) which was scaled to peak LVOT velocity and used to calculate wave intensity. These data were compared with wave intensity calculated using the measured LVOT flow velocity waveform. In a separate study, repeat measures of pWIA were performed on 34 individuals who attended two clinic visits at an interval of ≈1 month to assess reproducibility and reliability of the method. Results: Pxs waveforms were similar in shape to aortic flow velocity waveforms and the time of peak Pxs and peak aortic velocity agreed closely. Wave intensity estimated using pWIA showed acceptable agreement with estimates using LVOT velocity tracings and estimates of wave intensity were similar to values reported previously in the literature. The method showed fair to good reproducibility for most parameters. Conclusion: The Pxs is a surrogate of LVOT flow velocity which, when appropriately scaled, allows estimation of aortic wave intensity with acceptable reproducibility. This may enable wider application of wave intensity analysis to large studies