Abstract
Abstract Background EACVI recommends the use of an “integrative approach”, using several parameters, in aortic regurgitation (AR) quantification. This approach is easily achieved by echocardiography although cardiovascular magnetic resonance (CMR) remains the gold standard for the quantification of regurgitant fraction (RF). Purpose The aim of the study was to analyze the accuracy of descending aorta (DA) diastolic reverse flow in the assessment of chronic AR severity by CMR to identify an additional parameter. Methods 188 patients (34% female, 54.6±15.6 years) with different severity grades of chronic AR were enrolled. All patients underwent a CMR study. Aortic regurgitation was considered as absent (≤1%), mild (≤15%), moderate (≤15%) or severe (≥30%) depending on RF value at valve level. Furthermore, cine-sequences were used to estimate aortic diameters and distensibilities using Art Fun software. Velocity-time integral (VTI) of reverse flow in DA was calculated from maximum velocity curves by an in-house MatLab code. Results AR was absent in 21 (12%) patients, mild in 114 (62.9%), moderate in 23 (12.7%) and severe in 21 (11.6%).DA VTI reverse flow was significantly higher as was the RF at valve level (r=0.805, p<0.001) (IMG, Table). It also positively correlated withaortic root diameter (r=0.347, p<0.001) and DA distensibility (r=0.279, p<0.001). It did not correlate with age (r=−0.91, p=0.22). In a statistically significant multiple regression model (p<0.001, R2 = 0.697), although VTI reverse flow in DA correlated strongly with RF at valve level (p<0.001; beta = 0.733), it was also influenced by DA distensibility (p<0.001; beta = 0.197) and aortic root diameter (p<0.001; beta= 0.140). Conclusions VTI reverse flow in DA correlates strongly with the degree of AR and may be useful in the assessment of its severity. Neverthless, owing to the influence of other factors (aortic distensibility and aortic root diameter), it cannot be used as a single parameter in the quantification of AR severity by CMR. Scatter Plot graphs Funding Acknowledgement Type of funding source: Other. Main funding source(s): research grant provided by the Cardiopath PhD program
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