Evaluation of knowledge-based reconstruction for magnetic resonance volumetry of the right ventricle in tetralogy of Fallot.

Abstract

Cardiac magnetic resonance using the Simpson method is the gold standard for right ventricular volumetry. However, this method is time-consuming and not without sources of error. Knowledge-based reconstruction is a novel post-processing approach that reconstructs the right ventricular endocardial shape based on anatomical landmarks and a database of various right ventricular configurations. To assess the feasibility, accuracy and labor intensity of knowledge-based reconstruction in repaired tetralogy of Fallot (TOF). The short-axis cine cardiac MR datasets of 35 children and young adults (mean age 14.4 ± 2.5years) after TOF repair were studied using both knowledge-based reconstruction and the Simpson method. Intraobserver, interobserver and inter-method variability were assessed using Bland-Altman analyses. Knowledge-based reconstruction was feasible and highly accurate as compared to the Simpson method. Intra- and inter-method variability for knowledge-based reconstruction measurements showed good agreement. Volumetric assessment using knowledge-based reconstruction was faster when compared with the Simpson method (10.9 ± 2.0 vs. 7.1 ± 2.4min, P < 0.001). In patients with repaired tetralogy of Fallot, knowledge-based reconstruction is a feasible, accurate and reproducible method for measuring right ventricular volumes and ejection fraction. The post-processing time of right ventricular volumetry using knowledge-based reconstruction was significantly shorter when compared with the routine Simpson method.