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

Background: 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.

Objective: To assess the feasibility, accuracy and labor intensity of knowledge-based reconstruction in repaired tetralogy of Fallot (TOF).

Materials and methods: The short-axis cine cardiac MR datasets of 35 children and young adults (mean age 14.4 ± 2.5 years) 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.

Results: 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 ± 2.4 min, P < 0.001).

Conclusion: 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.