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Updated: Jul 5, 2025

In vitro Assessment of Aortic Regurgitation Using Four-Dimensional Flow Magnetic Resonance Imaging
Published on: February 25, 2022
The robustness of the flow-gradient classification of severe aortic stenosis
Bart J J Velders1, Michiel D Vriesendorp1, Federico M Asch2
1Cardiothoracic Surgery, Leiden University Medical Center, Leiden, The Netherlands.
Objectives:
A flow-gradient classification is used to determine the indication for intervention for patients with severe aortic stenosis (AS) with discordant echocardiographic parameters. We investigated the agreement in flow-gradient classification by stroke volume (SV) measurement at the left ventricular outflow tract (LVOT) and at the left ventricle.
Methods:
Data were used from a prospective cohort study and patients with severe AS (aortic valve area index ≤0.6 cm2/m2) with preserved ejection fraction (>50%) were selected. SV was determined by an echocardiographic core laboratory at the LVOT and by subtracting the 2-dimensional left ventricle end-systolic from the end-diastolic volume (volumetric). Patients were stratified into 4 groups based on SV index (35 mL/m2) and mean gradient (40 mm Hg). The group composition was compared and the agreement between the SV measurements was investigated using regression, correlation, and limits of agreement. In addition, a systematic LVOT diameter overestimation of 1 mm was simulated to study flow-gradient reclassification.
Results:
Of 1118 patients, 699 were eligible. The group composition changed considerably as agreement on flow state occurred in only 50% of the measurements. LVOT SV was on average 15.1 mL (95% limits of agreement -24.9:55.1 mL) greater than volumetric SV. When a systematic 1-mm LVOT diameter overestimation was introduced, the low-flow groups halved.
Conclusions:
There was poor agreement in the flow-gradient classification of severe AS as a result of large differences between LVOT and volumetric SV. Furthermore, this classification was sensitive to small measurement errors. These results stress that parameters beyond the flow-gradient classification should be considered to ensure accurate recommendations for intervention.
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