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The Sinotubular Junction-to-Aortic Annulus Ratio as a Determinant of Supravalvar Aortic Stenosis Severity
Dana B Gal1, Kirstie M Lechich2, Hanna K Jensen3
1The Heart Institute, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio.
Abstract:
Supravalvar aortic stenosis (SVAS) severity guides management, including decisions for surgery. Physiologic and technical factors limit the determination of SVAS severity by Doppler echocardiography and cardiac catheterization in Williams syndrome (WS). We hypothesized SVAS severity could be determined by the sinotubular junction-to-aortic annulus ratio (STJ:An). We reviewed all preintervention echocardiograms in patients with WS with SVAS cared for at our center. We measured STJ, An, peak and mean Doppler gradients, and calculated STJ:An. We created 2 mean gradient prediction models. Model 1 used the simplified Bernoulli's equation, and model 2 used computational fluid dynamics (CFD). We compared STJ:An to Doppler-derived and CFD gradients. We reviewed catheterization gradients and the waveforms and analyzed gradient variability. We analyzed 168 echocardiograms in 54 children (58% male, median age at scan 1.2 years, interquartile range [IQR] 0.5 to 3.6, median echocardiograms 2, IQR 1 to 4). Median SVAS peak Doppler gradient was 24 mm Hg (IQR 14 to 46.5). Median SVAS mean Doppler gradient was 11 mm Hg (IQR 6 to 21). Median STJ:An was 0.76 (IQR 0.63 to 0.84). Model 1 underpredicted clinical gradients. Model 2 correlated well with STJ:An through all severity ranges and demonstrated increased pressure recovery distance with decreased STJ:An. The median potential variability in catheterization-derived gradients in a given patient was 14.5 mm Hg (IQR 7.5 to 19.3). SVAS severity in WS can be accurately assessed using STJ:An. CFD predicts clinical data well through all SVAS severity levels. STJ:An is independent of physiologic state and has fewer technical limitations than Doppler echocardiography and catheterization. STJ:An could augment traditional methods in guiding surgical management decisions.
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