AUTHOR=Gbaoui Laila , Hoeschen Christoph , Kaniusas Eugenijus , Khatib Saher , Gretschel Stephan , Wellnhofer Ernst 

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

JOURNAL=Frontiers in Cardiovascular Medicine

VOLUME=10

YEAR=2023

URL=https://www.frontiersin.org/journals/cardiovascular-medicine/articles/10.3389/fcvm.2023.1280899

DOI=10.3389/fcvm.2023.1280899

ISSN=2297-055X

ABSTRACT=<sec><title>Background</title><p>Central blood pressure (<italic>cBP</italic>) is a better indicator of cardiovascular morbidity and mortality than peripheral BP (<italic>pBP</italic>). However, direct <italic>cBP</italic> measurement requires invasive techniques and indirect <italic>cBP</italic> measurement is based on rigid and empirical transfer functions applied to <italic>pBP</italic>. Thus, development of a personalized and well-validated method for non-invasive derivation of <italic>cBP</italic> from <italic>pBP</italic> 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 <italic>pBP</italic> into their pressure waveforms composing its dynamics, to identify the compounds that lead to pressure waveform distortion at the periphery, and to estimate the <italic>cBP</italic>. The approach is patient-specific and extracts the underlying blind pressure waveforms in <italic>pBP</italic> without additional brachial cuff calibration or any <italic>a priori</italic> assumption on the arterial model.</p></sec><sec><title>Methods</title><p>The intra-arterial femoral <italic>BP</italic><sub>fe</sub> and intra-aortic pressure <italic>BP</italic><sub>ao</sub> were anonymized digital recordings from previous routine cardiac catheterizations of eight patients at the German Heart Centre Berlin. The underlying pressure waveforms in <italic>BP</italic><sub>fe</sub> were extracted by the single-channel independent component analysis (SCICA). The accuracy of the SCICA model to estimate the whole c<italic>BP</italic> 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 (<italic>PP</italic>) was evaluated by the regression and Bland–Altman analyses.</p></sec><sec><title>Results</title><p>The SCICA tool estimated the c<italic>BP</italic> waveform non-invasively from the intra-arterial <italic>BP</italic><sub>fe</sub> 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 <italic>R</italic><sup>2</sup> 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.</p></sec><sec><title>Conclusions</title><p>The SCICA approach is a powerful tool that identifies sources contributing to morphological distortion at peripheral arteries and estimates <italic>cBP</italic>.</p></sec>