Aortic Blood Pressure Waveform Research Articles

Patient-specific non-invasive estimation of the aortic blood pressure waveform by ultrasound and tonometry

Background and ObjectiveAortic blood pressure (ABP) is a more effective prognostic indicator of cardiovascular disease than peripheral blood pressure. A highly accurate algorithm for non-invasively deriving the ABP wave, based on ultrasonic measurement of aortic flow combined with peripheral pulse wave measurements, has been proposed elsewhere. However, it has remained at the proof-of-concept stage because it requires a priori knowledge of the ABP waveform to calculate aortic pulse wave velocity (PWV). The objective of this study is to transform this proof-of-concept algorithm into a clinically feasible technique. MethodsWe used the Bramwell-Hill equation to non-invasively calculate aortic PWV which was then used to reconstruct the ABP waveform from non-invasively determined aortic blood flow velocity, aortic diameter, and radial pressure. The two aortic variables were acquired by an ultrasound system from 90 subjects, followed by recordings of radial pressure using a SphygmoCor device. The ABPs estimated by the new algorithm were compared with reference values obtained by cardiac catheterization (invasive validation, 8 subjects aged 62.3 ± 12.7 years) and a SphygmoCor device (non-invasive validation, 82 subjects aged 45.0 ± 17.8 years). ResultsIn the invasive comparison, there was good agreement between the estimated and directly measured pressures: the mean error in systolic blood pressure (SBP) was 1.4 ± 0.8 mmHg; diastolic blood pressure (DBP), 0.9 ± 0.8 mmHg; mean blood pressure (MBP), 1.8 ± 1.2 mmHg and pulse pressure (PP), 1.4 ± 1.1 mmHg. In the non-invasive comparison, the estimated and directly measured pressures also agreed well: the errors being: SBP, 2.0 ± 1.4 mmHg; DBP, 0.8 ± 0.1 mmHg; MBP, 0.1 ± 0.1 mmHg and PP, 2.3 ± 1.6 mmHg. The significance of the differences in mean errors between calculated and reference values for SBP, DBP, MBP and PP were assessed by paired t-tests. The agreement between the reference methods and those obtained by applying the new approach was also expressed by correlation and Bland-Altman plots. ConclusionThe new method proposed here can accurately estimate ABP, allowing this important variable to be obtained non-invasively, using standard, well validated measurement techniques. It thus has the potential to relocate ABP estimation from a research environment to more routine use in the cardiac clinic. Short AbstractA highly accurate algorithm for non-invasively deriving the ABP wave has been proposed elsewhere. However, it has remained at the proof-of-concept stage because it requires a priori knowledge of the ABP waveform to calculate aortic pulse wave velocity (PWV). This study aims to transform this proof-of-concept algorithm into a clinically feasible technique. We used the Bramwell-Hill equation to non-invasively calculate aortic PWV which was then used to reconstruct the ABP waveform. The ABPs estimated by the new algorithm were compared with reference values obtained by cardiac catheterization or a SphygmoCor device. The results showed that there was good agreement between the estimated and directly measured pressures. The new method proposed can accurately estimate ABP, allowing this important variable to be obtained non-invasively, using standard, well validated measurement techniques. It thus has the potential to relocate ABP estimation from a research environment to more routine use in the cardiac clinic.

Central Aortic Blood Pressure Waveform Estimation with a Temporal Convolutional Network.

A novel temporal convolutional network (TCN) model is utilized to reconstruct the central aortic blood pressure (aBP) waveform from the radial blood pressure waveform. The method does not need manual feature extraction as traditional transfer function approaches. The data acquired by the SphygmoCor CVMS device in 1,032 participants as a measured database and a public database of 4,374 virtual healthy subjects were used to compare the accuracy and computational cost of the TCN model with the published convolutional neural network and bi-directional long short-term memory (CNN-BiLSTM) model. The TCN model was compared with CNN-BiLSTM in the root mean square error (RMSE). The TCN model generally outperformed the existing CNN-BiLSTM model in terms of accuracy and computational cost. For the measured and public databases, the RMSE of the waveform using the TCN model was 0.55 ± 0.40 mmHg and 0.84 ± 0.29 mmHg, respectively. The training time of the TCN model was 9.63 min and 25.51 min for the entire training set; the average test time was around 1.79 ms and 8.58 ms per test pulse signal from the measured and public databases, respectively. The TCN model is accurate and fast for processing long input signals, and provides a novel method for measuring the aBP waveform. This method may contribute to the early monitoring and prevention of cardiovascular disease.

A study on transfer function to estimate the central aortic blood pressure waveform

Noninvasive measurement of the central aortic blood pressure has become an important technique that has generated a lot of interest around the medicine industry because it can estimate the central aortic blood pressure waveform without inserting a pressure-sensing catheter into the ascending aorta. The accuracy of noninvasive estimation of aortic hemodynamics and cardiac contractility is still debatable in noninvasive measurement of the central aortic blood methods. The objective of this project is to investigate the transfer functions available for converting radial blood pressure waveforms to central aortic blood pressure waveforms. In this project, three different transfer functions will be investigated which are The Generalized Transfer Function, N-Point Moving Average and Adaptive Transfer Function in order to recommend the effective method in terms of accuracy. The study methodology will be conducted through the software MATLAB R2021b. The investigation of these three methods will be conducted with data collected from virtual subjects from the HaeMod database. The Generalized transfer function, N-Point Moving Average and Adaptive Transfer Function will be coded, evaluated, and analyzed as part of the methodology. The determination of the most effective method among the three transfer functions will be attributed according to output comparison of Systolic peak differences, the RMSE and the MAPE between the estimated central aortic blood pressure and the measured central aortic blood pressure.

Accuracy of Estimated Central Systolic Blood Pressure and Augmentation Index in Patients With Type 2 Diabetes Mellitus

It has been suggested that transfer functions to estimate central aortic systolic blood pressure (SBP) and central BP waveform parameters (i.e., augmentation index) may be less accurate in patients with type 2 diabetes mellitus (T2DM). However, these observations have not been confirmed in a large sample, which was the aim of this study. Consecutive patients with and without T2DM undergoing coronary angiography at the Royal Hobart Hospital had BP recorded at the ascending aorta and radial artery with a fluid-filled catheter. Radial BP waveforms were processed using the SphygmoCor Cardiovascular Management System (CVMS) transfer function (AtCor, Sydney) to estimate central BP. Two invasive waveform calibration methods were used: 1) aortic mean arterial pressure/diastolic BP (MAP/DBP); and 2) radial SBP and DBP (SBP/DBP). between-group analyses were performed unadjusted and adjusted for age, sex, hypertension, hypercholesterolaemia, body mass index, and coronary artery disease. Data from 64 patients with T2DM (61±11 years, 73% male) and 186 patients without T2DM (62±8 years, 70% male) were analysed. There was no difference in the accuracy of estimated central SBP between groups when compared with invasive aortic SBP from MAP/DBP calibration (T2DM –1.8±6 mmHg vs –1.1±5 mmHg; p=0.37; adjusted p=0.59) or radial SBP/DBP calibration (T2DM –1.2±9 mmHg vs –2.0±9 mmHg; p=0.57; adjusted p=0.66). Augmentation index was not significantly different between patients with and without T2DM 0.8±12% vs 3.7±14%; p=0.13, respectively). Estimated central SBP and augmentation index do not appear to be less accurate in patients with T2DM when waveforms are calibrated with invasive BP.

PS-C07-8: CENTRAL BLOOD PRESSURE ESTIMATION USING THE RADIAL ARTERIAL PRESSURE WAVEFORM IN CHILDREN, ADOLESCENTS, AND YOUNG ADULTS

Objective: Evaluation of central blood pressure is useful in prevention and treatment of cardiovascular diseases. In this study, we examined the accuracy of non-invasively measured central blood pressure in children, adolescents, and young adults. Design and Method: This study enrolled 23 patients who had undergone a cardiac catheterization below 30 years old (10.4 ± 7.2 years, 16 males and 7 females). Ascending aortic blood pressure waveforms were invasively recorded using a pressure sensor-mounted catheter (model SPC-454D, Millar Instrument, Inc., Houston, Texas). Simultaneously, radial artery pulse waveforms were non-invasively recorded by tonometry (HEM-9000AI, Omron Healthcare Co., Ltd., Kyoto, Japan). The measurements were performed before and after angiogram (injection of contrast media) except for one case. We analyzed the degree of coincidence between ascending aortic systolic blood pressure (aSBP) and estimated central systolic blood pressure calculated by the instrument (estCBP) in 45 simultaneous recording of aSBP and estCBP. The HEM-9000AI calculates estCBP using rSBP2, which indicates reflected pressure on radial artery. Results: The aSBP was 96.2 ± 13.4 mmHg and estCBP was 92.9 ± 14.7mmHg. There was no significant correlation between the aSBPs before and after angiogram in the same case. There was a significant relationship between aSBP and estCBP (r = 0.83, p < 0.0001). The mean difference of the estSBP minus aSBP was -3.3 ± 8.3 mmHg by Bland-Altman analysis. The relationship between aSBP and rSBP1, which indicates forward pressure on radial artery, was stronger than the relationship between aSBP and rSBP2 (r = 0.88, p < 0.0001 vs. r = 0.83, p < 0.0001). The relationship between aSBP and the average of rSBP1 and rSBP2 (r = 0.90, p < 0.0001) was stronger than the relationship between aSBP and estCBP. Conclusions: The estSBP calculated using rSBP2 method by HEM 9000AI was significantly correlated to aSBP in children, adolescents, and young adults. However, the correlation coefficient between aSBP and rSBP2 was smaller than that between aSBP and rSBP1. The estCBP calculated by rSBP1 and rSBP2 was strongly correlated to aSBP rather than estCBP by rSBP2 alone.

Abstract 13669: Ascending Aortic Augmentation Pressure Does Not Decrease During Exercise in HFpEF: Implications for SV Reserve Impairment

Aortic augmentation pressure (aAP; difference between first [aP1] and second [aP2] peaks of the aortic pressure waveform) decreases during exercise in young healthy individuals, lowering mid-late systolic afterload, an important determinant of cardiac work and stroke volume (SV). In patients with heart failure and preserved ejection fraction (HFpEF), SV responses to exercise (i.e. SV reserve) are often abnormal (≤ 50%). A lack of fall in aAP during exercise in HFpEF could contribute to impairments in SV reserve. Therefore, we studied 15 HFpEF patients (age, 71 ± 6 years; 10 women; BMI 39.2 ± 6.2 kg/m 2 ) in the seated upright position. During rest and six-minutes of cycling at 20 Watts, we recorded beat-by-beat radial arterial blood pressure and estimated ascending aortic blood pressure waveforms in real-time via a generalized inverse transfer function (SphygmoCor). SV was calculated from cardiac output (Qc, acetylene rebreathe) and heart rate (ECG), with total peripheral resistance (TPR) calculated as the quotient of radial MAP and Qc. HR (Rest: 75 ± 14 vs 20W: 93 ± 12 bpm, P < 0.0001), SV (Rest: 61 ± 17 vs 20W: 84 ± 19 ml, P = 0.0003) and Qc (Rest: 4.5 ± 1.0 vs 20W: 7.7 ± 1.6 L/min, P < 0.0001) increased from rest to 20 Watts, whilst TPR decreased (Rest: 21.3 ± 4.4 vs 20W: 14.0 ± 3.8 mmHg/L/min, P < 0.0001); SV reserve was 43 ± 33 %. Aortic diastolic pressure did not change (Rest: 70 ± 12 vs 20W: 76 ± 15 mmHg, P = 0.0976), whereas aP1 (Rest: 112 ± 18 vs 20W: 130 ± 20 ml, P = 0.0002) and aP2 (Rest: 123 ± 26 vs 20W: 142 ± 25 ml, P = 0.0021) increased during exercise (Figure). Notably, aAP was not different between rest and exercise (Rest: 11 ± 11 vs 20W12 ± 11 mmHg, P = 0.4969). Therefore, the contribution of aAP to mid-late systolic afterload is unchanged during exercise in HFpEF, unlike in young healthy adults. Unchanged aAP may be a mechanism of high mid-late systolic afterload during exercise in HFpEF, which could contribute to impairments in SV reserve related to reduced ventricular contractile reserve.

A novel electrical impedance function to estimate central aortic blood pressure waveforms

Background and objectiveCentral aortic blood pressure waveforms convey imperative information about cardiovascular risk, but these measurements are obtained invasively. The study aims to develop an electrical impedance function (EIF) to estimate the central (aortic) blood pressure waveform from the radial blood pressure waveform without the need of invasive procedures. MethodsThis paper shows a method of using the four-element Windkessel model to derive an EIF using circuit analysis to estimate the central aortic blood pressure. The four elements were identified from radial waveforms by using the Nelder-Mead simplex algorithm and then used to construct the EIF to obtain the aortic pressure waveform, given the radial waveform. ResultsWaveforms generated by EIF gave the lowest values for Root Mean Square Error (RMSE) (5.69) and Mean Average Percentage Error (MAPE) (0.0402) compared to the generalized transfer function (GTF) and N-point moving average (NPMA), and the lowest MAPE and a comparable RMSE when compared to the Adaptive Transfer Function (ATF). Moreover, EIF has a significantly lower computing time (0.008 ms) when compared with GTF, NPMA and ATF. ConclusionsThe proposed function had comparable or better performance to existing methods when tested on both simulated and actual patient data, and was able to give a better signal shape retention at the dicrotic notch (99.94 % correlation), which is a crucial feature for cardiovascular disease detection. SignificanceOverall the EIF performance validates its use in estimating central aortic pressure waveforms, making it potentially viable for better embedded systems for non-invasive central blood pressure monitoring due to its low computation time and high accuracy.

Mechanisms behind altered pulsatile intracranial pressure in idiopathic normal pressure hydrocephalus: role of vascular pulsatility and systemic hemodynamic variables

BackgroundThe dementia subtype idiopathic normal pressure hydrocephalus (iNPH) has unknown etiology, but one characteristic is elevated intracranial pressure (ICP) wave amplitudes in those individuals who respond with clinical improvement following cerebrospinal fluid (CSF) diversion. To explore the mechanisms behind altered ICP wave amplitudes, we correlated central aortic blood pressure (BP) and ICP waveform amplitudes (intracranial aortic amplitude correlation) and examined how this correlation relates to ICP wave amplitude levels and systemic hemodynamic parameters.MethodsThe study included 29 patients with probable iNPH who underwent continuous multi-hour measurement of ICP, radial artery BP, and systemic hemodynamic parameters. The radial artery BP waveforms were used to estimate central aortic BP waveforms, and the intracranial aortic amplitude correlation was determined over consecutive 4-min periods.ResultsThe average intracranial aortic amplitude correlation was 0.28 ± 0.16 at the group level. In the majority of iNPH patients, the intracranial aortic amplitude correlation was low, while in about 1/5 patients, the correlation was rather high (average Pearson correlation coefficient > 0.4). The degree of correlation was hardly influenced by systemic hemodynamic parameters.ConclusionsIn about 1/5 iNPH patients of this study, the intracranial aortic amplitude correlation (IAACAORTIC) was rather high (average Pearson correlation coefficient > 0.4), suggesting that cerebrovascular factors to some extent may affect the ICP wave amplitudes in a subset of patients. However, in 14/19 (74%) iNPH patients with elevated ICP wave amplitudes, the intracranial aortic amplitude correlation was low, indicating that the ICP pulse amplitude in most iNPH patients is independent of central vascular excitation, ergo it is modulated by local cerebrospinal physiology. In support of this assumption, the intracranial aortic amplitude correlation was not related to most systemic hemodynamic variables. An exception was found for a subgroup of the patients with high systemic vascular resistance, where there was a correlation.

Observer-Based Deconvolution of Deterministic Input in Coprime Multichannel Systems With Its Application to Noninvasive Central Blood Pressure Monitoring.

Estimating central aortic blood pressure (BP) is important for cardiovascular (CV) health and risk prediction purposes. CV system is a multichannel dynamical system that yields multiple BPs at various body sites in response to central aortic BP. This paper concerns the development and analysis of an observer-based approach to deconvolution of unknown input in a class of coprime multichannel systems applicable to noninvasive estimation of central aortic BP. A multichannel system yields multiple outputs in response to a common input. Hence, the relationship between any pair of two outputs constitutes a hypothetical input-output system with unknown input embedded as a state. The central idea underlying our approach is to derive the unknown input by designing an observer for the hypothetical input-output system. In this paper, we developed an unknown input observer (UIO) for input deconvolution in coprime multichannel systems. We provided a universal design algorithm as well as meaningful physical insights and inherent performance limitations associated with the algorithm. The validity and potential of our approach were illustrated using a case study of estimating central aortic BP waveform from two noninvasively acquired peripheral arterial pulse waveforms. The UIO could reduce the root-mean-squared error (RMSE) associated with the central aortic BP by up to 27.5% and 28.8% against conventional inverse filtering (IF) and peripheral arterial pulse scaling techniques.

Integrating Patient-Specific Electrocardiogram Signals and Image-Based Computational Fluid Dynamics Method to Analyze Coronary Blood Flow in Patients during Cardiac Arrhythmias

PurposeThe aim of this study was to use the computational fluid dynamics (CFD) method, patient-specific electrocardiogram (ECG) signals, and computed tomography three-dimensional image reconstruction technique to investigate the blood flow in coronary arteries during cardiac arrhythmia.MethodsTwo patients with premature ventricular contraction-type cardiac arrhythmia and one with atrial fibrillation-type cardiac arrhythmia were investigated. The inlet velocity of the coronary artery in simulation was applied with the measured velocity profile of the left ventricular outflow tract (LVOT) from the Doppler echocardiography. The measured patient central aortic blood pressure waveform was employed for the coronary artery outlet in simulation. The no-slip boundary condition was applied to the arterial wall.ResultsFor the patient with irregular cardiac rhythms (Case I), the coronary blood flow rate under the shortened and lengthened cardiac rhythms were 0.66 and 0.96 mL/s, respectively. In Case II, the maximum velocity at the LVOT under a normal heartbeat was found to be 101 cm/s, whereas the average value was 73 cm/s. In Case III, the patient was also diagnosed with a congenital stenosis problem at the myocardial bridge (MCB) at the LAD. The measured blood flow rate at the MCB of the LAD for the three heartbeats in Case III was found to be 0.68, 1.08, and 1.14 mL/s.ConclusionThe integration of patient-specific ECG signals and image-based CFD methods can clearly analyze hemodynamic information for patients during cardiac arrhythmia. The cardiac arrhythmia can reduce the blood flow in the coronary arteries.

Tapered vs. Uniform Tube-Load Modeling of Blood Pressure Wave Propagation in Human Aorta.

In this paper, tapered vs. uniform tube-load models are comparatively investigated as mathematical representation for blood pressure (BP) wave propagation in human aorta. The relationship between the aortic inlet and outlet BP waves was formulated based on the exponentially tapered and uniform tube-load models. Then, the validity of the two tube-load models was comparatively investigated by fitting them to the experimental aortic and femoral BP waveform signals collected from 13 coronary artery bypass graft surgery patients. The two tube-load models showed comparable goodness of fit: (i) the root-mean-squared error (RMSE) was 3.3+/−1.1 mmHg in the tapered tube-load model and 3.4+/−1.1 mmHg in the uniform tube-load model; and (ii) the correlation was r = 0.98+/−0.02 in the tapered tube-load model and r = 0.98+/−0.01 mmHg in the uniform tube-load model. They also exhibited frequency responses comparable to the non-parametric frequency response derived from the aortic and femoral BP waveforms in most patients. Hence, the uniform tube-load model was superior to its tapered counterpart in terms of the Akaike Information Criterion (AIC). In general, the tapered tube-load model yielded the degree of tapering smaller than what is physiologically relevant: the aortic inlet-outlet radius ratio was estimated as 1.5 on the average, which was smaller than the anatomically plausible typical radius ratio of 3.5 between the ascending aorta and femoral artery. When the tapering ratio was restricted to the vicinity of the anatomically plausible typical value, the exponentially tapered tube-load model tended to underperform the uniform tube-load model (RMSE: 3.9+/−1.1 mmHg; r = 0.97+/−0.02). It was concluded that the uniform tube-load model may be more robust and thus preferred as the representation for BP wave propagation in human aorta; compared to the uniform tube-load model, the exponentially tapered tube-load model may not provide valid physiological insight on the aortic tapering, and its efficacy on the goodness of fit may be only marginal.

Augmentation index is not a proxy for wave reflection magnitude: mechanistic analysis using a computational model.

The augmentation index (AIx) is deemed to capture the deleterious effect on left ventricular (LV) work of increased wave reflection associated with stiffer arteries. However, its validity as a proxy for wave reflection magnitude has been questioned. We hypothesized that, in addition to increased wave reflection due to increased pulse wave velocity, LV myocardial shortening velocity influences AIx. Using a computational model of the circulation, we investigated the isolated and combined influences of myocardial shortening velocity vs,LV and arterial stiffness on AIx. Aortic blood pressure waveforms were characterized using AIx and the reflected wave pressure amplitude (, obtained using wave separation analysis). Our reference simulation (normal vs,LV and arterial stiffness) was characterized by an AIx of 21%. A realistic reduction in vs,LV caused AIx to increase from 21 to 42%. An arterial stiffness increase, characterized by a relevant 1.0 m/s increase in carotid-femoral pulse wave velocity, caused AIx to increase from 21 to 41%. Combining the reduced vs,LV and increased arterial stiffness resulted in an AIx of 54%. In a multistep parametric analysis, both vs,LV and arterial stiffness were about equal determinants of AIx, whereas was only determined by arterial stiffness. Furthermore, the relation between increased AIx and LV stroke work was only ≈50% explained by an increase in arterial stiffness, the other factor being vs,LV. The , on the other hand, related less ambiguously to LV stroke work. We conclude that the AIx reflects both cardiac and vascular properties and should not be considered an exclusively vascular parameter.NEW & NOTEWORTHY We used a state-of-the-art computational model to mechanistically investigate the validity of the augmentation index (AIx) as a proxy for (changes in) wave reflection. In contrary to current belief, we found that LV contraction velocity influences AIx as much as increased arterial stiffness, and increased AIx does not necessarily relate to an increase in LV stroke work. Wave reflection magnitude derived from considering pressure, as well as flow, does qualify as a determinant of LV stroke work.

Transfer Function Between Intracranial Pressure and Aortic Blood Pressure and Carotid Blood Flow.

The compliance of the intracranial space is such that the intracranial pressure (ICP) waveform is approximately the aortic blood pressure (BP) waveform minus the dominant harmonic (heart rate (HR)) of that waveform. This has been tested across species of different resting HR. Whether this filter characteristic holds true for large changes in HR, or under changed ICP, has not been examined. This study tested these changes in 11 anesthetized rats instrumented to measure and change ICP, HR, aortic BP, and carotid blood flow. The aortic BP to ICP and carotid blood flow to ICP transfer function was determined for normal ICP at paced HRs of 300, 400 and 500 bpm, and at raised ICP at HRs of 400 and 500 bpm. The aortic BP to ICP transfer function magnitude showed a dependency on HR HR (-0.15±0.04 ×10-3 bpm-1, p<0.001) and mean ICP (4.4±0.6 ×10-3 mmHg-1). The carotid blood flow to ICP transfer function magnitude showed a dependency on mean ICP (11.1±1.8 ×10-3 mmHg/ml/min/mmHg, p<0.001) but not on HR. The changes with different HRs indicates a degree of non-linearity in the system. Though small, this may need to be accounted for in understanding the relationship between systemic BP and flow and ICP. This data is useful in understanding the relationship between cardiovascular signals and ICP, valuable in advancing the ability to estimate ICP non-invasively.

Non-invasive Estimation of the Intracranial Pressure Waveform from the Central Arterial Blood Pressure Waveform in Idiopathic Normal Pressure Hydrocephalus Patients

This study explored the hypothesis that the central aortic blood pressure (BP) waveform may be used for non-invasive estimation of the intracranial pressure (ICP) waveform. Simultaneous invasive ICP and radial artery BP waveforms were measured in 29 individuals with idiopathic normal pressure hydrocephalus (iNPH). The central aortic BP waveforms were estimated from the radial artery BP waveforms using the SphygmoCor system. For each individual, a transfer function estimate between the central aortic BP and the invasive ICP waveforms was found (Intra-patient approach). Thereafter, the transfer function estimate that gave the best fit was chosen and applied to the other individuals (Inter-patient approach). To validate the results, ICP waveform parameters were calculated for the estimates and the measured golden standard. For the Intra-patient approach, the mean absolute difference in invasive versus non-invasive mean ICP wave amplitude was 1.9 ± 1.0 mmHg among the 29 individuals. Correspondingly, the Inter-patient approach resulted in a mean absolute difference of 1.6 ± 1.0 mmHg for the 29 individuals. This method gave a fairly good estimate of the wave for about a third of the individuals, but the variability is quite large. This approach is therefore not a reliable method for use in clinical patient management.

Model-Based Blind System Identification Approach to Estimation of Central Aortic Blood Pressure Waveform From Noninvasive Diametric Circulatory Signals

This paper presents a model-based blind system identification approach to estimation of central aortic blood pressure (BP) waveform from noninvasive diametric circulatory signals. First, we developed a mathematical model to reproduce the relationship between central aortic BP waveform and a class of noninvasive circulatory signals at diametric locations by combining models to represent wave propagation in the artery, arterial pressure–volume relationship, and mechanics of the measurement instrument. Second, we formulated the problem of estimating central aortic BP waveform from noninvasive diametric circulatory signals into a blind system identification problem. Third, we performed identifiability analysis to show that the mathematical model could be identified and its parameters determined up to an unknown scale. Finally, we illustrated the feasibility of the approach by applying it to estimate central aortic BP waveform from two diametric pulse volume recording (PVR) signals. Experimental results from ten human subjects showed that the proposed approach could estimate central aortic BP waveform accurately: the average root-mean-squared error (RMSE) associated with the central aortic BP waveform was 4.1 mm Hg (amounting to 4.5% of the underlying mean BP) while the average errors associated with central aortic systolic pressure (SP) and pulse pressure (PP) were 2.4 mm Hg and 2.0 mm Hg (amounting to 2.5% and 2.1% of the underlying mean BP). The proposed approach may contribute to the improved monitoring of cardiovascular (CV) health by enabling estimation of central aortic BP waveform from conveniently measurable diametric circulatory signals.

Use of the Kalman Filter for Aortic Pressure Waveform Noise Reduction.

Clinical applications that require extraction and interpretation of physiological signals or waveforms are susceptible to corruption by noise or artifacts. Real-time hemodynamic monitoring systems are important for clinicians to assess the hemodynamic stability of surgical or intensive care patients by interpreting hemodynamic parameters generated by an analysis of aortic blood pressure (ABP) waveform measurements. Since hemodynamic parameter estimation algorithms often detect events and features from measured ABP waveforms to generate hemodynamic parameters, noise and artifacts integrated into ABP waveforms can severely distort the interpretation of hemodynamic parameters by hemodynamic algorithms. In this article, we propose the use of the Kalman filter and the 4-element Windkessel model with static parameters, arterial compliance C, peripheral resistance R, aortic impedance r, and the inertia of blood L, to represent aortic circulation for generating accurate estimations of ABP waveforms through noise and artifact reduction. Results show the Kalman filter could very effectively eliminate noise and generate a good estimation from the noisy ABP waveform based on the past state history. The power spectrum of the measured ABP waveform and the synthesized ABP waveform shows two similar harmonic frequencies.

Optimization of a generalized radial-aortic transfer function using parametric techniques

The central aortic blood pressure (cBP) waveform, which is different to that of peripheral locations, is a clinically important parameter for assessing cardiovascular function, however the gold standard for measuring cBP involves invasive catheter-based techniques. The difficulties associated with invasive measurements have given rise to the development of a variety of noninvasive methods. An increasingly applied method for the noninvasive derivation of cBP involves the application of transfer function (TF) techniques to a non-invasively measured radial blood pressure (BP) waveform. The purpose of the current study was to investigate the development of a general parametric model for determination of cBP from tonometrically transduced radial BP waveforms. The study utilized simultaneously measured invasive central aortic and noninvasive radial BP waveform measurements. Data sets were available from 92 subjects, a large cohort for a study of this nature. The output error (OE) model was empirically identified as the most appropriate model structure. A generalized model was developed using a pre-specified derivation cohort and then applied to a validation data set to estimate the recognized features of the cBP waveform. While our results showed that many relevant BP parameters could be derived within acceptable limits, the estimated augmentation index (AI) displayed only a weak correlation compared to the invasively measured value, indicating that any clinical diagnosis or interpretation based on estimated AI should be undertaken with caution.

Central Pulsatile Pressure and Flow Relationship in the Time and Frequency Domain to Characterise Hydraulic Input to the Brain and Cerebral Vascular Impedance.

In the time domain, pulsatile flow and pressure can be characterised as the ratio of the late systolic boost of flow or pressure to the pulse amplitude so as to estimate the hydraulic input to the brain. While vascular impedance has been widely used to represent the load presented to the heart by the systemic circulation, it has not been applied to the cerebral circulation.We set out to study the relationship between the pressure and the flow augmentation index (AIx) in the time domain and to determine cerebral vascular impedance using aortic blood pressure and cerebral blood flow waveforms in the frequency domain. Twenty-four young subjects (aged 21-39 years) were recruited; aortic pressure was derived using SphygmoCor from radial pressure. Flow waveforms were recorded from the middle cerebral artery. In three subjects, we performed the Valsalva manoeuvre to investigate their response to physiological intervention. There was a linear relationship between flow and pressure AIx, and cerebral impedance values were similar to those estimated for low resistance vascular beds. Substantial change in pressure and flow wave contour was observed during the Valsalva manoeuvre; however, the relationship in both the time and the frequency domains were unchanged. This confirms that aortic pressure and cerebral flow waveform can be used to study cerebral impedance.

Children and Adolescent Obesity Associates with Pressure-Dependent and Age-Related Increase in Carotid and Femoral Arteries' Stiffness and Not in Brachial Artery, Indicative of Nonintrinsic Arterial Wall Alteration.

Aim. To analyze if childhood obesity associates with changes in elastic, transitional, and/or muscular arteries' stiffness. Methods. 221 subjects (4–15 years, 92 females) were assigned to normal weight (NW, n = 137) or obesity (OB, n = 84) groups, considering their body mass index z-score. Age groups were defined: 4–8; 8–12; 12–15 years old. Carotid, femoral, and brachial artery local stiffness was determined through systodiastolic pressure-diameter and stress-strain relationships. To this end, arterial diameter and peripheral and aortic blood pressure (BP) levels and waveforms were recorded. Carotid-femoral, femoropedal, and carotid-radial pulse wave velocities were determined to evaluate aortic, lower-limb, and upper-limb regional arterial stiffness, respectively. Correlation analysis between stiffness parameters and BP was done. Results. Compared to NW, OB subjects showed higher peripheral and central BP and carotid and femoral stiffness, reaching statistical significance in subjects aged 12 and older. Arterial stiffness differences disappeared when levels were normalized for BP. There were no differences in intrinsic arterial wall stiffness (elastic modulus), BP stiffness relationships, and regional stiffness parameters. Conclusion. OB associates with BP-dependent and age-related increase in carotid and femoral (but not brachial) stiffness. Stiffness changes would not be explained by intrinsic arterial wall alterations but could be associated with the higher BP levels observed in obese children.

Effect of acute nitrate ingestion on central hemodynamic load in hypoxia

Acute hypoxia results in local vasodilation that may temporarily unload the left ventricle (LV) through nitric oxide (NO)-mediated mechanisms. Whether increasing NO levels augments LV unloading and improves ventricular-vascular coupling in hypoxia remains unknown. PurposeInvestigate the effect of acute nitrate ingestion on central hemodynamic load in hypoxia. Methods20 Healthy men (23 ± 3 yrs, BMI 24.6 ± 2.8 kg m−2) consumed 70 mL of either a) 0.45 g nitrate (NIT) or b) an inert placebo (PLA) prior to 105 min of normobaric hypoxia (11.6 ± 0.1%) in this randomized, double-blind, crossover-design study. Wave reflection index (RIX; ratio of forward to reflected wave pressure), augmentation index (AIX75) and pulse wave velocity were calculated as measures of wave reflection magnitude and aortic stiffness, respectively, from the aortic blood pressure (BP) waveform. LV wasted pressure effort (WPE) was calculated as an index of LV work due to wave reflections. Subendocardial viability ratio (SEVR) was assessed a measure of myocardial O2 supply/demand ratio. ResultsAortic diastolic BP decreased in hypoxia compared to normoxia (p < 0.05). Aortic RIX, AIX75, and LV WPE significantly decreased in hypoxia compared to normoxia (p < 0.05). Aortic systolic BP, SEVR, and PWV were unaffected by hypoxia (p > 0.05). Compared to placebo, nitrate ingestion did not significantly alter central hemodynamics in hypoxia (p > 0.05). ConclusionsAcute hypoxic exposure unloads the LV (WPE, AIX75, and RIX) without disturbing myocardial O2 supply-demand ratio (SEVR). Reductions in LV work with hypoxia are likely due to reductions in pressure from wave reflections as hypoxia had negligible effects on aortic stiffness. Nitrate ingestion did not affect the central hemodynamic response to acute systemic hypoxia.