Validation of a novel and existing algorithms for the estimation of pulse transit time: advancing the accuracy in pulse wave velocity measurement.

Research paper by Orestis O Vardoulis, Theodore G TG Papaioannou, Nikolaos N Stergiopulos

Indexed on: 23 Apr '13Published on: 23 Apr '13Published in: American journal of physiology. Heart and circulatory physiology


The method used for pulse transit time (PTT) estimation critically affects the accuracy and precision of regional pulse wave velocity (PWV) measurements. Several methods of PTT estimation exist, often yielding substantially different PWV values. Since there is no analytic way to determine PTT in vivo, these methods cannot be validated except by using in silico or in vitro models of known PWV and PTT values. We aimed to validate and compare the most commonly used "foot-to-foot" algorithms, namely, the " diastole-minimum," "tangential," "maximum first derivative," and "maximum second derivative" methods. Also, we propose a new "diastole-patching" method aiming to increase the accuracy and precision in PWV measurements. We simulated 2,000 cases under different hemodynamic conditions using an accurate, validated, distributed, one-dimensional arterial model. The new algorithm detects and "matches" a specific region of the pressure wave foot between the proximal and distal waveforms instead of determining characteristic points. The diastole-minimum and diastole-patching methods showed excellent agreement compared with "real" PWV values of the model, as indicated by high values of the intraclass correlation coefficient (>0.86). The diastole-patching method resulted in low bias (absolute mean difference: 0.26 m/s). In contrast, PWV estimated by the maximum first derivative, maximum second derivative, and tangentia methods presented low to moderate agreement and poor accuracy (intraclass correlation coefficient: <0.79 and bias: >0.9 m/s). The diastole-patching method yielded PWV measurements with the highest agreement, accuracy, and precision and lowest variability.