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Correcting CT-derived aortic valve area for LVOT ellipticity: A novel approach
Yoav Niv Granot1, Solomon W Bienstock1, Daniel Karlsberg2
1Mount Sinai Fuster Heart Hospital, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
Background:
A limitation of echocardiography is its tendency to underestimate the left ventricular outflow tract (LVOT) area due to reliance on single diameter. While substituting CT-derived LVOT area in aortic valve area calculations (AVA_CT) increases the calculated valve area, this does not improve its clinical utility. In fact, AVA_CT overestimates the AVA, requiring a higher threshold for defining severe aortic stenosis [AS] (<1.2 cm2). This phenomenon may be attributed to differences in fluid flow dynamics between circular (assumed by echocardiography) and elliptical conduits.
Aim:
Demonstrate the differences between the calculated AVA before and after implementing a mathematical correction factor for flow in a non-circular conduit.
Methods:
662 patients with severe AS who underwent aortic valve replacement between 06/2021 and 07/2023. AVA calculated using the continuity equation with both echocardiography and CT data. A correction factor (CF) for elliptical flow was applied per patient.
Results:
AVA_CT was significantly higher than AVA_Echo, showing a 23 % increase. After correcting for the elliptical shape of the LVOT, AVA_CT-corrected was lower and closer to AVA_Echo (mean absolute difference of 0.06 cm2) and had superior correlation with invasive measurement. Several patients were reclassified from severe to moderate AS when using AVA_CT; however, applying the correction factor significantly reduced the reclassification.
Conclusion:
Incorporating a correction factor for the elliptical geometry of the LVOT improves the accuracy of AVA estimation. The corrected AVA demonstrates better agreement with echocardiographic measurements and reduces the overestimation inherent in CT-based calculations. This approach minimizes discrepancies in patientclassification across AS severity categories.

