Is It Feasible to Reconstruct Aortic Pressure Waveform Based On a 1d Uniform Model of the Arterial Tree?

Based on a 1D uniform model of the arterial tree, various machine-learning techniques have been explored to reconstruct aortic pressure waveform (APW) from peripheral pressure waveform (PPW). This study aims to examine the feasibility of such reconstruction. Based on a 1D uniform vibrating-string model, transfer function (TF) of PPW to APW contains four harmonics-dependent parameters: value and phase of reflection coefficient (i.e., load impedance) at periphery and transmission parameter and transmission loss in the aorta-periphery section, and they are all harmonics-dependent. Pressure waveforms and blood velocity waveforms at the ascending aorta (AA), the carotid artery (CA), and the radial artery (RA) at different ages in a database are analyzed to calculate 1) reflection coefficient at the CA and the RA as two peripheries, 2) TF for the AA-CA and AA-RA sections, and 3) transmission parameter and transmission loss in the two sections. Harmonics-dependence of the four parameters varies with aging for both sections, revealing unpracticality of any mathematical model for harmonics-dependence of load impedance. Compared with fluid-loading, arterial non-uniformity significantly affects wave transmission. Transmission loss dramatically alters reconstructed APW, relative to higher harmonics. A 1D uniform model allows accurate reconstruction of APW from PPW, with a caveat that baseline values for the four parameters at different harmonics under different cardiovascular (CV) conditions need to be established a priori. Alternatively, based on the baseline values, PPW can be directly utilized for inferring the CV conditions.