Mind the gap: Quantification of incomplete ablation patterns after pulmonary vein isolation using minimum path search

Medical image analysis on left atrial LGE MRI for atrial fibrillation studies: A review

Late gadolinium enhancement magnetic resonance imaging (LGE MRI) is commonly used to visualize and quantify left atrial (LA) scars. The position and extent of LA scars provide important information on the pathophysiology and progression of atrial fibrillation (AF). Hence, LA LGE MRI computing and analysis are essential for computer-assisted diagnosis and treatment stratification of AF patients. Since manual delineations can be time-consuming and subject to intra- and inter-expert variability, automating this computing is highly desired, which nevertheless is still challenging and under-researched. This paper aims to provide a systematic review on computing methods for LA cavity, wall, scar, and ablation gap segmentation and quantification from LGE MRI, and the related literature for AF studies. Specifically, we first summarize AF-related imaging techniques, particularly LGE MRI. Then, we review the methodologies of the four computing tasks in detail and summarize the validation strategies applied in each task as well as state-of-the-art results on public datasets. Finally, the possible future developments are outlined, with a brief survey on the potential clinical applications of the aforementioned methods. The review indicates that the research into this topic is still in the early stages. Although several methods have been proposed, especially for the LA cavity segmentation, there is still a large scope for further algorithmic developments due to performance issues related to the high variability of enhancement appearance and differences in image acquisition.

Applications of multimodality imaging for left atrial catheter ablation

Atrial arrhythmias, including atrial fibrillation and atrial flutter, may be treated through catheter ablation. The process of atrial arrhythmia catheter ablation, which includes patient selection, pre-procedural planning, intra-procedural guidance, and post-procedural assessment, is typically characterized by the use of several imaging modalities to sequentially inform key clinical decisions. Increasingly, advanced imaging modalities are processed via specialized image analysis techniques and combined with intra-procedural electrical measurements to inform treatment approaches. Here, we review the use of multimodality imaging for left atrial ablation procedures. The article first outlines how imaging modalities are routinely used in the peri-ablation period. We then describe how advanced imaging techniques may inform patient selection for ablation and ablation targets themselves. Ongoing research directions for improving catheter ablation outcomes by using imaging combined with advanced analyses for personalization of ablation targets are discussed, together with approaches for their integration in the standard clinical environment. Finally, we describe future research areas with the potential to improve catheter ablation outcomes.

Fast Quasi-Conformal Regional Flattening of the Left Atrium

Two-dimensional representation of 3D anatomical structures is a simple and intuitive way for analysing patient information across populations and image modalities. While cardiac ventricles, especially the left ventricle, have an established standard representation (bull's eye plot), the 2D depiction of the left atrium (LA) remains challenging due to its sub-structural complexity including the pulmonary veins (PV) and the left atrial appendage (LAA). Quasi-conformal flattening techniques, successfully applied to cardiac ventricles, require additional constraints in the case of the LA to place the PV and LAA in the same geometrical 2D location for different cases. Some registration-based methods have been proposed but surface registration is time-consuming and prone to errors when the geometries are very different. We propose a novel atrial flattening methodology where a 2D standardised map of the LA is obtained quickly and without errors related to registration. The LA is divided into five regions which are then mapped to their analogue two-dimensional regions. 67 human left atria from magnetic resonance images (MRI) were studied to derive a population-based template representing the averaged relative locations of the PVs and LAA. The clinical application of our methodology is illustrated on different use cases including the integration of MRI and electroanatomical data.

CemrgApp: An interactive medical imaging application with image processing, computer vision, and machine learning toolkits for cardiovascular research

Personalised medicine is based on the principle that each body is unique and will respond to therapies differently. In cardiology, characterising patient specific cardiovascular properties would help in personalising care. One promising approach for characterising these properties relies on performing computational analysis of multimodal imaging data. An interactive cardiac imaging environment, which can seamlessly render, manipulate, derive calculations, and otherwise prototype research activities, is therefore sought-after. We developed the Cardiac Electro-Mechanics Research Group Application (CemrgApp) as a platform with custom image processing and computer vision toolkits for applying statistical, machine learning and simulation approaches to study physiology, pathology, diagnosis and treatment of the cardiovascular system. CemrgApp provides an integrated environment, where cardiac data visualisation and workflow prototyping are presented through a common graphical user interface.

Delayed Gadolinium Enhancement Magnetic Resonance Imaging Detected Anatomic Gap Length in Wide Circumferential Pulmonary Vein Ablation Lesions Is Associated With Recurrence of Atrial Fibrillation

BACKGROUND

There is limited knowledge about the impact of anatomic gaps as assessed by delayed gadolinium enhancement cardiac magnetic resonance on atrial fibrillation (AF) recurrence after first pulmonary vein (PV) isolation.

METHODS

Consecutive patients underwent delayed gadolinium enhancement cardiac magnetic resonance 3 months after radiofrequency circumferential PV isolation. Delayed gadolinium enhancement cardiac magnetic resonance images were assessed from 360 PV resulting in 2880 segments in the 2×8-segment model from 94 patients (52±11 years, 62% paroxysmal AF). Left atria were segmented using dedicated software. Anatomic gap was defined as discontinuation of the ablation line by ≥3 mm. Relative gap length was calculated as absolute gap length divided by the total length of the ablation line. AF recurrence was assessed after a mean follow-up duration of 15±10 months Results: Mean number of anatomic gaps was 5.4 per patient. Recurrence within the first year of ablation was observed in 21 patients with paroxysmal AF (36%) and 19 patients with persistent AF (53%). In the univariate analysis, CHA₂DS₂-VASc score, AF type, and relative gap length were predictive of recurrence. In the multivariate analysis, only relative gap length was significantly associated with recurrence (hazard ratio, 1.16 [1.02-1.31] per each 10% of gap).

CONCLUSIONS

The total relative gap length but not the number of anatomic gaps in the PV ablation line as assessed by delayed gadolinium enhancement cardiac magnetic resonance was associated with AF recurrence 1 year after first PV isolation. An increase of 10% relative gap length increased the likelihood of AF recurrence by 16%.