Some years ago, researchers at Hospital Clínic de Barcelona and Universitat Pompeu Fabra developed a swine model of left bundle branch block (LBBB) for experimental studies of CRT (Rigol et al., J Cardiovasc Transl Res 2013). Radiofrequency applications were performed to induce LBBB, and half of the animals presented a myocardial infarction located at the septal wall. Imaging data and electro-anatomical maps (EAM) were acquired at baseline, with the induced LBBB and after implantation of a CRT devicE. This rich data is well suited for evaluating some features of the different cardiac computational models available nowadays, and will be the basis of the CRT-EPiggy19 challenge. The training data will include two complete infarcted and two non-infarcted datasets (total of 4 cases), while the test data is composed of four cases for each of the two categories (infarcted vs non-infarcted; total of 8 cases). The electrical activation patterns of the training datasets have already been described with detail in Soto-Iglesias et al. (IEEE J Transl Eng Health Med 2016). Check the Datasets section for a preview of the training data and the procedure to download it. Unlike LBBB and CRT activation maps, baseline maps will not initially be released, since they do not necessarily contribute to the prediction of CRT from LBBB.

Some of the main sources of variability in the personalization of cardiac models involve the extraction of anatomical data from medical images and the creation of the geometrical domain where models are run. In order to reduce this variability in the CRT-EPiggy19 challenge, biventricular finite element meshes will be provided to each participant, which were built from the segmentation of cine-MRI data. These meshes will include cardiomyocyte orientation (obtained with rule-based models; see Doste et al. Int J Numer Meth Bio 2019 for details), several regional labels (AHA regions, endo- and epi-cardial walls, different ventricles) and the local activation times projected from EAM data. Additionally, the affected AHA segments and its transmurality will be given for infarcted cases. Furthermore, for visualization and analysis purposes, 2D bi-ventricular representations will be given.