Excess pressure as an analogue of blood flow velocity

Aortic pressure-only wave separation analysis in adolescents: accuracy and associations with left ventricular mass index

Early-life exposure to high blood pressure (BP) is associated with cardiovascular target organ damage but not all BP-related risk is attributable to systolic and diastolic BP alone. In adolescence, aortic wave separation (WS) parameters are associated with increased left ventricular mass index (LVMI) but this approach is limited by the requirement for aortic flow measurements. Several methods for estimating the aortic flow waveform from pressure waveforms have emerged, but their accuracy and associations with LVMI have never been tested in adolescents, which was the aim of our study. Carotid pressure waveforms were acquired by tonometry from 58 adolescents (age 16 ± 1.5 years, 59% female). Measured (aortic) flow and LVMI were acquired via 2D echocardiography. Three pressure-only approximations of aortic flow were synthesized, including triangular, excess, and individualized-physiologic flow. A 4th aortic flow (average flow) was approximated from the average of all 58 measured flow waveforms. Forward (Pf) and backward (Pb) pressure and reflection magnitude (Rm) were derived from WS analysis. The individualized-physiologic flow produced the best approximations of Pf (mean difference ± SD, -0.15 ± 2.38 mmHg), Pb (0.14 ± 0.25 mmHg), and Rm (0.01 ± 0.02 mmHg). Pf derived using measured, individualized-physiologic, and average flow, was similarly associated with LVMI adjusting for age, brachial systolic BP, cardiac output, and BMI (P ≤ 0.03 all). Pb derived using all flow waveforms was associated with LVMI and all associations yielded similar effect estimates. Of the estimated flow waveforms, individualized-physiologic flow yielded the best approximation of WS parameters and may provide important physiological and clinical insight among adolescents.

Estimation of central blood pressure waveform from femoral blood pressure waveform by blind sources separation

Background

Central blood pressure (cBP) is a better indicator of cardiovascular morbidity and mortality than peripheral BP (pBP). However, direct cBP measurement requires invasive techniques and indirect cBP measurement is based on rigid and empirical transfer functions applied to pBP. Thus, development of a personalized and well-validated method for non-invasive derivation of cBP from pBP is necessary to facilitate the clinical routine. The purpose of the present study was to develop a novel blind source separation tool to separate a single recording of pBP into their pressure waveforms composing its dynamics, to identify the compounds that lead to pressure waveform distortion at the periphery, and to estimate the cBP. The approach is patient-specific and extracts the underlying blind pressure waveforms in pBP without additional brachial cuff calibration or any a priori assumption on the arterial model.

Methods

The intra-arterial femoral BPfe and intra-aortic pressure BPao were anonymized digital recordings from previous routine cardiac catheterizations of eight patients at the German Heart Centre Berlin. The underlying pressure waveforms in BPfe were extracted by the single-channel independent component analysis (SCICA). The accuracy of the SCICA model to estimate the whole cBP waveform was evaluated by the mean absolute error (MAE), the root mean square error (RMSE), the relative RMSE (RRMSE), and the intraclass correlation coefficient (ICC). The agreement between the intra-aortic and estimated parameters including systolic (SBP), diastolic (DBP), mean arterial pressure (MAP), and pulse pressure (PP) was evaluated by the regression and Bland-Altman analyses.

Results

The SCICA tool estimated the cBP waveform non-invasively from the intra-arterial BPfe with an MAE of 0.159 ± 1.629, an RMSE of 5.153 ± 0.957 mmHg, an RRMSE of 5.424 ± 1.304%, and an ICC of 0.94, as well as two waveforms contributing to morphological distortion at the femoral artery. The regression analysis showed a strong linear trend between the estimated and intra-aortic SBP, DBP, MAP, and PP with high coefficient of determination R2 of 0.98, 0.99, 0.99, and 0.97 respectively. The Bland-Altman plots demonstrated good agreement between estimated and intra-aortic parameters with a mean error and a standard deviation of difference of -0.54 ± 2.42 mmHg [95% confidence interval (CI): -5.28 to 4.20] for SBP, -1.97 ± 1.62 mmHg (95% CI: -5.14 to 1.20) for DBP, -1.49 ± 1.40 mmHg (95% CI: -4.25 to 1.26) for MAP, and 1.43 ± 2.79 mmHg (95% CI: -4.03 to 6.90) for PP.

Conclusions

The SCICA approach is a powerful tool that identifies sources contributing to morphological distortion at peripheral arteries and estimates cBP.