Pulse pressure method and the area method for the estimation of total arterial compliance in dogs: sensitivity to wave reflection intensity

We estimated total arterial compliance (C) in eight anesthetized mongrel dogs with (i) the area method (AM), (ii) the pulse pressure method (PPM), and (iii) the stroke volume-to-pulse pressure ratio (SV/PP). Average compliance was C(AM)=1.1+/-0.73 ml mm Hg(-1) using AM; C(PPM)=0.60+/-0.31 ml mm Hg(-1) using PPM and C(SV/PP)=0.87+/-0.49 ml mm Hg(-1) using SV/PP. Mean aortic pressure was 64+/-23 mm Hg. The overall agreement between C(AM) and C(PPM) was relatively poor (C(AM)=0.15+/-1.61 C(PPM); r2=0.48), with a consistent overestimation of the area method with respect to the pulse pressure method. There was a significant correlation (r=-0.78) between the relative difference between PPM and AM, and the modulus of the first harmonic of the wave reflection coefficient [gamma] which was low in our dog population (0.37+/-0.18). SV/PP overestimated PPM, but both methods were highly correlated (C(SV/PP)=0.06+/-1.60C(PPM); r2=0.97). C(SV/PP) and C(AM) were similar only for [gamma]>0.4. The effect of isolated changes of [gamma] on PPM, AM, and SV/PP was studied using the linear wave separation technique. The area method appeared very sensitive to the wave reflection intensity. For low reflection coefficients, the diastolic wave profile was flattened and compliance was overestimated. PPM and SV/PP were relatively independent of [gamma] and remained even applicable for [gamma]=0. We believe that the pulse pressure method is the most consistent method for the estimation of total arterial compliance in hemodynamic conditions characterized by a low wave reflection intensity.

Total arterial inertance as the fourth element of the windkessel model

Nikolaos Stergiopulos, Nico Westerhof

In earlier studies we found that the three-element windkessel, although an almost perfect load for isolated heart studies, does not lead to accurate estimates of total arterial compliance. To overcome this problem, we introduce an inertial term in parallel with the characteristic impedance. In seven dogs we found that ascending aortic pressure could be predicted better from aortic flow by using the four-element windkessel than by using the three-element windkessel: the root-mean-square errors and the Akaike information criterion and Schwarz criterion were smaller for the four-element windkessel. The three-element windkessel overestimated total arterial compliance compared with the values derived from the area and the pulse pressure method (P = 0.0047, paired t-test), whereas the four-element windkessel compliance estimates were not different (P = 0.81). The characteristic impedance was underestimated using the three-element windkessel, whereas the four-element windkessel estimation differed marginally from the averaged impedance modulus at high frequencies (P = 0.0017 and 0.031, respectively). When applied to the human, the four-element windkessel also was more accurate in these same aspects. Using a distributed model of the systemic arterial tree, we found that the inertial term results from the proper summation of all local inertial terms, and we call it total arterial inertance. We conclude that the fourelement windkessel, with all its elements having a hemodynamic meaning, is superior to the three-element windkessel as a lumped-parameter model of the entire systemic tree or as a model for parameter estimation of vascular properties.

1999

Noninvasive estimation of aortic hemodynamics and cardiac contractility using machine learning

Vasiliki Bikia, Stamatia Zoi Pagoulatou, Georgios Rovas, Nikolaos Stergiopulos

Cardiac and aortic characteristics are crucial for cardiovascular disease detection. However, noninvasive estimation of aortic hemodynamics and cardiac contractility is still challenging. This paper investigated the potential of estimating aortic systolic pressure (aSBP), cardiac output (CO), and end-systolic elastance (E-es) from cuff-pressure and pulse wave velocity (PWV) using regression analysis. The importance of incorporating ejection fraction (EF) as additional input for estimating E-es was also assessed. The models, including Random Forest, Support Vector Regressor, Ridge, Gradient Boosting, were trained/validated using synthetic data (n = 4,018) from an in-silico model. When cuff-pressure and PWV were used as inputs, the normalized-RMSEs/correlations for aSBP, CO, and E-es (best-performing models) were 3.36 +/- 0.74%/0.99, 7.60 +/- 0.68%/0.96, and 16.96 +/- 0.64%/0.37, respectively. Using EF as additional input for estimating E-es significantly improved the predictions (7.00 +/- 0.78%/0.92). Results showed that the use of noninvasive pressure measurements allows estimating aSBP and CO with acceptable accuracy. In contrast, E-es cannot be predicted from pressure signals alone. Addition of the EF information greatly improves the estimated E-es. Accuracy of the model-derived aSBP compared to in-vivo aSBP (n = 783) was very satisfactory (5.26 +/- 2.30%/0.97). Future in-vivo evaluation of CO and E-es estimations remains to be conducted. This novel methodology has potential to improve the noninvasive monitoring of aortic hemodynamics and cardiac contractility.

2020

Acute effects of transcatheter aortic valve replacement on the ventricular-aortic interaction

Vasiliki Bikia, Stamatia Zoi Pagoulatou, Georgios Rovas, Nikolaos Stergiopulos

Transcatheter aortic valve replacement (TAVR) is increasingly used to treat severe aortic stenosis (AS) patients. However, little is known regarding the direct effect of TAVR on the ventricular-aortic interaction. In the present study, we aimed to investigate changes in central hemodynamics after successful TAVR. We retrospectively examined 33 cases of severe AS patients (84 +/- 6 yr) who underwent TAVR. Invasive measurements of left ventricular and aortic pressures as well as echocardiographic aortic flow were acquired before and after TAVR (maximum within 5 days). We examined alterations in key features of central pressure and flow waveforms, including the aortic augmentation index (AIx), and performed wave separation analysis. Arterial parameters were determined via parameter-fitting on a two-element Windkessel model. Resolution of AS resulted in direct increase in the aortic systolic pressure and maximal aortic flow (131 +/- 22 vs. 157 +/- 25 mmHg and 237 +/- 49 vs. 302 +/- 69 mL/s, P < 0.001 for all), whereas the ejection duration decreased (P < 0.001). We noted a significant decrease in the AIx (from 42 +/- 12 to 19 +/- 11%, P < 0.001). Of note, the arterial properties remained unchanged. There was a comparable increase in both forward (61 +/- 20 vs. 77 +/- 20 mmHg, P < 0.001) and backward ( 35 +/- 14 vs. 42 +/- 10 mmHg, P = 0.013) pressure wave amplitudes, while their ratio, i.e., the reflection coefficient, was preserved. Our results highlight the impact of TAVR on the ventricular-aortic interaction by affecting the amplitude, shape, and related attributes of the aortic pressure and flow pulse and challenge the interpretation of AIx as a solely vascular measure in AS patients. NEW & NOTEWORTHY Transcatheter aortic valve replacement (TAVR) is linked with an immediate increase in aortic systolic blood pressure and maximal flow, as well as steeper aortic pressure and flow wave upstrokes. After TAVR, the forward wave pumped by the heart is enhanced. Although the arterial properties remain unchanged, the central augmentation index (AIx) is markedly decreased after TAVR. This challenges the interpretation of AIx as a solely vascular measure in patients with aortic valve stenosis.

AMER PHYSIOLOGICAL SOC2020

Acute effects of transcatheter aortic valve replacement on the ventricular-aortic interaction

Vasiliki Bikia, Stamatia Zoi Pagoulatou, Georgios Rovas, Nikolaos Stergiopulos

AMER PHYSIOLOGICAL SOC2020