P137 Estimating Left Ventricular Elastance from Noninvasive Aortic Flow and Brachial Pressure Measurements

Abstract

Background and Aim

Left Ventricular (LV) End-systolic elastance (Ees) serves as a major determinant of cardiac systolic contractility. Traditional Methods: to evaluate the ventricular mechanics directly from measurements require intraventricular pressure and volume recordings during an acute preload alteration. The noninvasive derivation of Ees remains thus challenging. Here, we present a novel method to estimate the LV pressure-volume loop and ela-stance in humans from given aortic flow waveforms, LV ejection fraction and brachial pressure using a 1-D model of the cardiovascular system (1).

Methods

Initially, the measured aortic flow waveform is used as the input to the default 1-D model and the output brachial systolic and diastolic pressure are compared with the ‘real’ values. Subsequently, arterial compliance and peripheral resistance are modified accordingly until peripheral pressure is accurately predicted. In a second step, this person-specific model is used to estimate the elastance parameters that produce the ‘real’ aortic flow waveform. Additional knowledge of the LV ejection fraction can allow us to derive the entire pressure-volume loop, including end-diastolic elastance. The method was tested on a database of 50 different in silico hemodynamic cases generated after varying cardiac and arterial model parameters.

Results

Implementation of the method yielded good agreement (r = 0.99) and accuracy (n-RMSE = 4%) between ‘real’ and estimated values of Ees (Figure 1). Furthermore, a sensitivity analysis revealed that errors due to poor arterial adjustment and measurements are small (≤8% for Ees).

Conclusion

The insilico validation of the proposed method gave promising results and we are currently planning its testing against in vivo data.