Mingwu Gao

Pulse arrival time is not an adequate surrogate for pulse transit time as a marker of blood pressure

Pulse transit time (PTT) is a proven, simple to measure, marker of blood pressure (BP) that could potentially permit continuous, noninvasive, and cuff-less BP monitoring (after an initial calibration). However, pulse arrival time (PAT), which is equal to the sum of PTT and the pre-ejection period, is gaining popularity for BP tracking, because it is even simpler to measure. The aim of this study was to evaluate the hypothesis that PAT is an adequate surrogate for PTT as a marker of BP. PAT and PTT were estimated through the aorta using high-fidelity invasive arterial waveforms obtained from six dogs during wide BP changes induced by multiple interventions. These time delays and their reciprocals were evaluated in terms of their ability to predict diastolic, mean, and systolic BP (DBP, MBP, and SBP) per animal. The root mean squared error (RMSE) between the BP parameter predicted via the time delay and the measured BP parameter was specifically used as the evaluation metric. Taking the reciprocals of the time delays tended to reduce the RMSE values. The DBP, MBP, and SBP RMSE values for 1/PAT were 9.8 ± 5.2, 10.4 ± 5.6, and 11.9 ± 6.1 mmHg, whereas the corresponding values for 1/PTT were 5.3 ± 1.2, 4.8 ± 1.0, and 7.5 ± 2.2 mmHg (P < 0.05). Thus tracking BP via PAT was not only markedly worse than via PTT but also unable to meet the FDA BP error limits. In contrast to previous studies, our results quantitatively indicate that PAT is not an adequate surrogate for PTT in terms of detecting challenging BP changes.

Estimation of Pulse Transit Time as a Function of Blood Pressure Using a Nonlinear Arterial Tube-Load Model

Objective: pulse transit time (PTT) varies with blood pressure (BP) throughout the cardiac cycle, yet, because of wave reflection, only one PTT value at the diastolic BP level is conventionally estimated from proximal and distal BP waveforms. The objective was to establish a technique to estimate multiple PTT values at different BP levels in the cardiac cycle. Methods: a technique was developed for estimating PTT as a function of BP (to indicate the PTT value for every BP level) from proximal and distal BP waveforms. First, a mathematical transformation from one waveform to the other is defined in terms of the parameters of a nonlinear arterial tube-load model accounting for BP-dependent arterial compliance and wave reflection. Then, the parameters are estimated by optimally fitting the waveforms to each other via the model-based transformation. Finally, PTT as a function of BP is specified by the parameters. The technique was assessed in animals and patients in several ways including the ability of its estimated PTT-BP function to serve as a subject-specific curve for calibrating PTT to BP. Results: the calibration curve derived by the technique during a baseline period yielded bias and precision errors in mean BP of 5.1 ± 0.9 and 6.6 ± 1.0 mmHg, respectively, during hemodynamic interventions that varied mean BP widely. Conclusion: the new technique may permit, for the first time, estimation of PTT values throughout the cardiac cycle from proximal and distal waveforms. Significance: the technique could potentially be applied to improve arterial stiffness monitoring and help realize cuff-less BP monitoring.

Comparison of noninvasive pulse transit time estimates as markers of blood pressure using invasive pulse transit time measurements as a reference

Pulse transit time (PTT) measured as the time delay between invasive proximal and distal blood pressure (BP) or flow waveforms (invasive PTT [I‐PTT]) tightly correlates with BP. PTT estimated as the time delay between noninvasive proximal and distal arterial waveforms could therefore permit cuff‐less BP monitoring. A popular noninvasive PTT estimate for this application is the time delay between ECG and photoplethysmography (PPG) waveforms (pulse arrival time [PAT]). Another estimate is the time delay between proximal and distal PPG waveforms (PPG‐PTT). PAT and PPG‐PTT were assessed as markers of BP over a wide physiologic range using I‐PTT as a reference. Waveforms for determining I‐PTT, PAT, and PPG‐PTT through central arteries were measured from swine during baseline conditions and infusions of various hemodynamic drugs. Diastolic, mean, and systolic BP varied widely in each subject (group average (mean ± SE) standard deviation between 25 ± 2 and 36 ± 2 mmHg). I‐PTT correlated well with all BP levels (group average R2 values between 0.86 ± 0.03 and 0.91 ± 0.03). PPG‐PTT also correlated well with all BP levels (group average R2 values between 0.81 ± 0.03 and 0.85 ± 0.02), and its R2 values were not significantly different from those of I‐PTT. PAT correlated best with systolic BP (group average R2 value of 0.70 ± 0.04), but its R2 values for all BP levels were significantly lower than those of I‐PTT (P < 0.005) and PPG‐PTT (P < 0.02). The pre‐ejection period component of PAT was responsible for its inferior correlation with BP. In sum, PPG‐PTT was not different from I‐PTT and superior to the popular PAT as a marker of BP.

Improved Pulse Wave Velocity Estimation Using an Arterial Tube-Load Model

Pulse wave velocity (PWV) is the most important index of arterial stiffness. It is conventionally estimated by noninvasively measuring central and peripheral blood pressure (BP) and/or velocity (BV) waveforms and then detecting the foot-to-foot time delay between the waveforms wherein wave reflection is presumed absent. We developed techniques for improved estimation of PWV from the same waveforms. The techniques effectively estimate PWV from the entire waveforms, rather than just their feet, by mathematically eliminating the reflected wave via an arterial tube-load model. In this way, the techniques may be more robust to artifact while revealing the true PWV in absence of wave reflection. We applied the techniques to estimate aortic PWV from simultaneously and sequentially measured central and peripheral BP waveforms and simultaneously measured central BV and peripheral BP waveforms from 17 anesthetized animals during diverse interventions that perturbed BP widely. Since BP is the major acute determinant of aortic PWV, especially under anesthesia wherein vasomotor tone changes are minimal, we evaluated the techniques in terms of the ability of their PWV estimates to track the acute BP changes in each subject. Overall, the PWV estimates of the techniques tracked the BP changes better than those of the conventional technique (e.g., diastolic BP root-mean-squared errors of 3.4 versus 5.2 mmHg for the simultaneous BP waveforms and 7.0 versus 12.2 mmHg for the BV and BP waveforms (p <; 0.02)). With further testing, the arterial tube-load model-based PWV estimation techniques may afford more accurate arterial stiffness monitoring in hypertensive and other patients.

Perturbationless calibration of pulse transit time to blood pressure

Pulse transit time (PTT) often shows strong correlation with blood pressure (BP) and may therefore represent a means for achieving continuous, non-invasive, and cuff-less BP monitoring. However, construction of the subject-specific curve needed to calibrate PTT to BP conventionally requires simultaneous measurements of PTT and BP during an experimental perturbation that varies BP over a significant range. We propose a technique for perturbationless calibration of PTT to BP. This technique constructs the calibration curve from central and peripheral BP waveforms by exploiting the natural pulsatile variation in the waveforms via a nonlinear tube-load model. We conducted initial testing of the technique in animals by applying it to the waveforms during a baseline period and then predicting mean BP during subsequent major hemodynamic interventions via PTT calibrated with the resulting curve. The bias in the mean BP error was 4.9 mmHg, while the precision in this error was 7.6 mmHg.

Robust, beat-to-beat estimation of the true pulse transit time from central and peripheral blood pressure or flow waveforms using an arterial tube-load model

We proposed a technique for estimating beat-to-beat pulse transit time (PTT) from central and peripheral blood pressure or flow waveforms based on an arterial tube-load model of wave reflection. The technique effectively estimates PTT from the entire waveforms after mathematically eliminating the reflected wave. So, unlike the conventional foot-to-foot detection technique, this technique should be robust to artifact while revealing the true PTT (i.e., the PTT in absence of wave reflection). We compared the two techniques, as applied to blood pressure and flow waveforms, in terms of the ability of their PTT estimates to correlate with blood pressure (a) during baseline (for which the naturally occurring beat-to-beat changes were small), (b) during low heart rate (wherein wave reflection was profound), and (c) in the presence of actual measurement artifact. In all three cases, the PTT estimates of the arterial tube-load model technique yielded markedly superior correlation to blood pressure.

Central Blood Pressure Monitoring via a Standard Automatic Arm Cuff

Current oscillometric devices for monitoring central blood pressure (BP) maintain the cuff pressure at a constant level to acquire a pulse volume plethysmography (PVP) waveform and calibrate it to brachial BP levels estimated with population average methods. A physiologic method was developed to further advance central BP measurement. A patient-specific method was applied to estimate brachial BP levels from a cuff pressure waveform obtained during conventional deflation via a nonlinear arterial compliance model. A physiologically-inspired method was then employed to extract the PVP waveform from the same waveform via ensemble averaging and calibrate it to the brachial BP levels. A method based on a wave reflection model was thereafter employed to define a variable transfer function, which was applied to the calibrated waveform to derive central BP. This method was evaluated against invasive central BP measurements from patients. The method yielded central systolic, diastolic, and pulse pressure bias and precision errors of −0.6 to 2.6 and 6.8 to 9.0 mmHg. The conventional oscillometric method produced similar bias errors but precision errors of 8.2 to 12.5 mmHg (p ≤ 0.01). The new method can derive central BP more reliably than some current non-invasive devices and in the same way as traditional cuff BP.

A comparative analysis of reduced arterial models for hemodynamic monitoring

We performed a comparative analysis of reduced arterial models. These models are characterized by a few parameters that can be uniquely estimated from the limited measurements often available in practice. Hence, they offer a means to improve hemodynamic monitoring. We specifically describe Windkessel, transmission-line, and recursive difference equation models, show how they are related, pinpoint their capabilities and limitations, and review how we have applied them for less invasive cardiac output monitoring.

Central Blood Pressure Monitoring via an Automatic Arm Cuff

Blood pressure (BP) near the heart (i.e., central BP) is clinically more relevant than BP away from the heart. But, BP from the arm is more easily measured with an automatic cuff device. A model-based method was developed to estimate central BP using a standard automatic arm cuff device. The method was initially tested in patients using invasive central BP measurements as a reference. The method achieved central BP estimation errors of 5.6-7.9 mmHg.

Emax monitoring by aortic pressure waveform analysis.

Emax- the maximal left ventricular elastance- is perhaps the best available scalar index of contractility. However, the conventional method for its measurement involves obtaining multiple ventricular pressure-volume loops at different loading conditions and is thus impractical. We previously proposed a more practical technique for tracking Emax from just a single beat of an aortic pressure waveform based on a lumped parameter model of the left ventricle and arteries. Here, we tested the technique against the conventional Emax measurement method in animals during inotropic interventions. Our results show that the estimated Emax changes corresponded fairly well to the reference changes, with a correlation coefficient of 0.793. With further development and testing, the technique could ultimately permit continuous and less invasive monitoring of Emax.