Rapid automatic segmentation of abnormal tissue in late gadolinium enhancement cardiovascular magnetic resonance images for improved management of long-standing persistent atrial fibrillation

Background: Atrial fibrillation (AF) is the most common heart rhythm disorder. In order for late Gd enhancement cardiovascular magnetic resonance (LGE CMR) to ameliorate the AF management, the ready availability of the accurate enhancement segmentation is required. However, the computer-aided segmentation of enhancement in LGE CMR of AF is still an open question. Additionally, the number of centres that have reported successful application of LGE CMR to guide clinical AF strategies remains low, while the debate on LGE CMR’s diagnostic ability for AF still holds. The aim of this study is to propose a method that reliably distinguishes enhanced (abnormal) from non-enhanced (healthy) tissue within the left atrial wall of (pre-ablation and 3 months post-ablation) LGE CMR data-sets from long-standing persistent AF patients studied at our centre. Methods: Enhancement segmentation was achieved by employing thresholds benchmarked against the statistics of the whole left atrial blood-pool (LABP). The test-set cross-validation mechanism was applied to determine the input feature representation and algorithm that best predict enhancement threshold levels. Results: Global normalized intensity threshold levels T PRE = 1 1/4 and T POST = 1 5/8 were found to segment enhancement in data-sets acquired pre-ablation and at 3 months post-ablation, respectively. The segmentation results were corroborated by using visual inspection of LGE CMR brightness levels and one endocardial bipolar voltage map. The measured extent of pre-ablation fibrosis fell within the normal range for the specific arrhythmia phenotype. 3D volume renderings of segmented post-ablation enhancement emulated the expected ablation lesion patterns. By comparing our technique with other related approaches that proposed different threshold levels (although they also relied on reference regions from within the LABP) for segmenting enhancement in LGE CMR data-sets of AF patients, we illustrated that the cut-off levels employed by other centres may not be usable for clinical studies performed in our centre. Conclusions: The proposed technique has great potential for successful employment in the AF management within our centre. It provides a highly desirable validation of the LGE CMR technique for AF studies. Inter-centre differences in the CMR acquisition protocol and image analysis strategy inevitably impede the selection of a universally optimal algorithm for segmentation of enhancement in AF studies

Standard quasi-conformal flattening of the right and left atria

Two-dimensional standard representations of 3D anatomical structures are a simple and intuitive way for analysing patient information across populations and image modalities. They also allow convenient visualizations that can be included in clinical reports for a fast overview of the whole structure. While cardiac ventricles, especially the left ventricle, have an established standard representation (e.g. bull’s eye plot), the 2D depiction of the left (LA) and right atrium (RA) remains challenging due to their sub-structural complexity. Quasi-conformal flattening techniques, successfully applied to cardiac ventricles, require additional constraints in the case of the atria to correctly place the adjacent structures, i.e. the pulmonary veins, the vena cava (VC) or the appendages. Some registration-based methods exist to flatten the LA but they can be time-consuming and prone to errors if the geometries are very different. We propose a novel atrial flattening methodology where a quasi-conformal 2D map of both (left and right) atria is obtained quickly and without errors related to registration. In our approach the RA is mapped to a standard 2D map where the holes corresponding to superior and inferior VC are fixed within a disk. Similarly, the LA is divided into 5 regions which are then mapped to their analogous two-dimensional regions. We illustrate the application of the method to visualize atrial wall thickness measurements, and late gadolinium enhanced magnetic resonance data.This study was partially funded by the Spanish Ministry of Economy and Competitiveness (DPI2015-71640-R), by the “Fundació La Marató de TV3” (no 20154031) and by European Union Horizon 2020 Programme for Research and Innovation, under grant agreement No. 642676 (CardioFunXion)