How to estimate aortic characteristic impedance from magnetic resonance and applanation tonometry data?

OBJECTIVES:: Compare seven previous methods for the estimation of aortic characteristic impedance, which contributes to left ventricle pulsatile load, from phase-contrast cardiovascular magnetic resonance (CMR) and applanation tonometry data. METHODS:: We studied 77 healthy (43±16 years) individuals and 16 hypertensive (61±9 years) patients, who consecutively underwent ascending aorta CMR and carotid tonometry, resulting in flow and pressure waveforms, respectively. Characteristic impedance was semi-automatically estimated in time domain from these latter waveforms, using seven methods. The methods were based on the following: methods 1-4, magnitudes at specific times; method 5, early-systolic up-slope; method 6, time-derivatives peak; and method 7, pressure-flow loop early-systolic slope. RESULTS:: Aortic characteristic impedance was significantly increased in hypertensive patients when compared to elderly controls (n=32) with a similar mean age of (59±8 years) when using methods based on 95% of peak flow, up-slopes, and derivatives peaks (P<0.05). When considering healthy individuals, impedance indices were significantly correlated to central pulse pressure for all methods (P<0.005). Finally, characteristic impedance was correlated to the frequency-domain reference values (r>0.65, P<0.0001), with a slight superiority for the same three methods as above (r>0.82, P<0.0001). CONCLUSIONS:: This is the first study demonstrating phase-contrast CMR and tonometry usefulness in aortic characteristic impedance temporal estimation. Methods based on 95% of peak flow, as well as those based on derivative peaks and up-slopes, which are fast and independent of curve preprocessing, were slightly superior. They can be easily integrated in a clinical workflow and may help to understand the complementarity of this pulsatile index with other CMR aortic geometry and stiffness measures in the setting of left ventricle-aortic coupling.