Navigator echoes are frequently used in cardiac magnetic resonance to monitor respiratory motion and have proved particularly useful in coronary artery imaging techniques where they allow the acquisition of data over multiple reproducible breathholds and during free breathing. The large number of variables involved in their use, however, is such that an optimal method of application may yet have to be developed. In this review article, we examine the issues relating to their implementation and describe the ways in which the navigator information obtained may be used.

Background - Adults with repaired tetralogy of Fallot (rTOF) die prematurely from ventricular tachycardia (VT) and sudden cardiac death. Inducible VT predicts mortality. Ventricular scar, the key substrate for VT, can be non-invasively defined with late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) but whether this relates to inducible VT is unknown. Methods - Sixty-nine consecutive rTOF patients (43 male, mean 40{plus minus}15 years) clinically scheduled for invasive programmed VT-stimulation were prospectively recruited for prior 3D LGE CMR. Ventricular LGE was segmented and merged with reconstructed cardiac chambers and LGE volume measured. Results - VT was induced in 22(31%) patients. Univariable predictors of inducible VT included increased RV LGE (OR 1.15;p=0.001 per cm 3 ), increased non-apical vent LV LGE (OR 1.09;p=0.008 per cm 3 ), older age (OR 1.6;p=0.01 per decile), QRS duration ≥180ms (OR 3.5;p=0.02), history of non-sustained VT (OR 3.5; p=0.02) and previous clinical sustained VT (OR 12.8;p=0.003); only prior sustained VT (OR 8.02;p=0.02) remained independent in bivariable analyses after controlling for RV LGE volume (OR 1.14;p=0.003). An RV LGE volume of 25cm 3 had 72% sensitivity and 81% specificity for predicting inducible VT (AUC 0.81;p<0.001). At the extreme cutoffs for 'ruling-out' and 'ruling-in' inducible VT, RV LGE >10cm 3 was 100% sensitive and >36cm 3 was 100% specific for predicting inducible VT. Conclusions - 3D LGE CMR-defined scar burden is independently associated with inducible VT and may help refine patient selection for programmed VT-stimulation when applied to an at least intermediate clinical risk cohort.

Late Gadolinium Enhancement Magnetic Resonance Imaging (LGE MRI) emerges as a routine scan for patients with atrial fibrillation (AF). However, due to the low image quality automating the quantification and analysis of the atrial scars is challenging. In this study, we proposed a fully automated method based on the graph-cut framework, where the potential of the graph is learned on a surface mesh of the left atrium (LA), using an equidistant projection and a deep neural network (DNN). For validation, we employed 100 datasets with manual delineation. The results showed that the performance of the proposed method was improved and converged with respect to the increased size of training patches, which provide important features of the structural and texture information learned by the DNN. The segmentation could be further improved when the contribution from the t-link and n-link is balanced, thanks to the inter-relationship learned by the DNN for the graph-cut algorithm. Compared with the existing methods which mostly acquired an initialization from manual delineation of the LA or LA wall, our method is fully automated and has demonstrated great potentials in tackling this task. The accuracy of quantifying the LA scars using the proposed method was 0.822, and the Dice score was 0.566. The results are promising and the method can be useful in diagnosis and prognosis of AF.

No abstract