Dual-layer spectral computed tomography (CT) parameters for identifying severe aortic regurgitation in aortic valve...

To investigate the diagnostic potential of dual-layer computed tomography (DLCT) in detecting the severe aortic regurgitation (sAR) among patients with aortic valve disease (AVD).

This retrospective study included 53 AVD patients who underwent both transthoracic echocardiography (TTE) and DLCT within one week. Patients were categorised into sAR (n = 16) and nonsevere AR (non-sAR, n = 37) groups based on TTE findings. DLCT parameters, including aortic annulus dimensions (max/min diameter, circumference, area), sinus of Valsalva (SOV) diameter, ascending aorta diameter (AoD), and myocardial extracellular volume (ECV) fraction, were analysed. Logistic regression analysis was employed to identify risk factors for sAR in patients with AVD, and the diagnostic performance of DLCT parameters was evaluated using receiver operating characteristic (ROC) curves.

Patients with sAR were significantly younger and had larger aortic valve parameters compared to the non-sAR group. Computed tomography-ECV (CT-ECV) was notably higher in the sAR group (33.19 ± 3.86% vs 29.05 ± 4.58%, P< 0.05). Logistic regression analysis identified CT-ECV and SOV diameter as independent predictors of sAR (CT-ECV: OR = 1.531, 95% CI: 1.133-2.070, P= 0.006; SOV diameter: OR= 1.198, 95% CI: 1.056-1.359, P= 0.005). Both parameters effectively distinguished sAR from non-sAR patients. Their combined model enhanced diagnostic performance (AUC = 0.867) and maintained excellent accuracy (AUC = 0.819) in the mild-moderate AR (mAR) subgroup.

DLCT-derived CT-ECV and aortic valve parameters effectively identify sAR in AVD patients. The combination of CT-ECV and SOV diameter offers the highest diagnostic accuracy, potentially improving AVD management.