Pranav Bhagirath

210 Chapter 11 (2) The capability to facilitate procedural guidance by fusion of CMR-derived LA models with the electro-anatomical mapping (EAM) system, and (3) The correlation between sites of ablation and scar localization on the LA model. It was observed that a comprehensive CMR protocol, consisting of commercially available sequences, can be completed in less than 40 minutes (36 ± 3 minutes) with post-processing of this information requiring 2.8 ± 0.8 minutes. Further analysis of the LA volume and sphericity could be performed using an open source tool without any further post-processing actions. In addition, integration with the EAM could also be performed instantaneously by importing the post-processing results to the EAM system. The gaps identified using late gadolinium enhanced-CMR (LGE-CMR) demonstrated a high correlation with the invasively measured sites of reconnection. However, not all LGE-CMR gaps showed electrical reconnection. Although previous investigations have mentioned non-conducting gaps, 8, 9 no study has yet characterized the temporal electrical course of these gaps. Certain groups of patients develop AF recurrences after the ablation procedure. Therefore, it may be hypothesized that such electrically dormant gaps may demonstrate reconnection in the long-term. In such case, these gaps should be considered a potential ablation site during the redo-procedure. Tissue characteristics The outcome of the previous investigations with regard to scar-maps warrants further study towards the identification of a strategy to differentiate between electrically dormant gaps and gaps associated with the recurrence of AF. To this extent, all available algorithms for scar analysis needed to be evaluated as it is not clear how they compare or perform relative to one another. Furthermore, algorithms have only been tested on center- and vendor-specific images. The translation of such algorithms into the clinical environment thus remains challenging. Benchmarking frameworks, providing a common dataset and evaluation strategies, are important for clinical translation of these algorithms. A benchmarking framework was constructed to provide thirty datasets, with fifteen datasets in each cohort: patient and porcine. Datasets in the two separate cohorts were acquired using different scanner vendors and field strength (1.5T and 3T), resolutions and acquisition protocols (2D and 3D). The ground truth is often absent in such datasets, and to this end, the framework provides with a powerful expert observers’ consensus ground truth. The proposed framework