Advances in CMR of Post-ablation Atrial Injury

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.

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

Pulmonary vein isolation (PVI) is a common procedure for the treatment of atrial fibrillation (AF) since the initial trigger for AF frequently originates in the pulmonary veins. A successful isolation produces a continuous lesion (scar) completely encircling the veins that stops activation waves from propagating to the atrial body. Unfortunately, the encircling lesion is often incomplete, becoming a combination of scar and gaps of healthy tissue. These gaps are potential causes of AF recurrence, which requires a redo of the isolation procedure. Late-gadolinium enhanced cardiac magnetic resonance (LGE-CMR) is a non-invasive method that may also be used to detect gaps, but it is currently a time-consuming process, prone to high inter-observer variability. In this paper, we present a method to semi-automatically identify and quantify ablation gaps. Gap quantification is performed through minimum path search in a graph where every node is a scar patch and the edges are the geodesic distances between patches. We propose the Relative Gap Measure (RGM) to estimate the percentage of gap around a vein, which is defined as the ratio of the overall gap length and the total length of the path that encircles the vein. Additionally, an advanced version of the RGM has been developed to integrate gap quantification estimates from different scar segmentation techniques into a single figure-of-merit. Population-based statistical and regional analysis of gap distribution was performed using a standardised parcellation of the left atrium. We have evaluated our method on synthetic and clinical data from 50 AF patients who underwent PVI with radiofrequency ablation. The population-based analysis concluded that the left superior PV is more prone to lesion gaps while the left inferior PV tends to have less gaps (p < .05 in both cases), in the processed data. This type of information can be very useful for the optimization and objective assessment of PVI interventions.

Combined Angiography and Late Gadolinium Enhancement Acquisition to Improve Assessment of Pulmonary Vein Isolation for Atrial Fibrillation

PURPOSE

To develop a Shared K-space (SharK) magnetic resonance imaging (MRI) sequence that combines angiographic and late gadolinium enhancement (LGE) acquisitions to improve atrial wall segmentation and scar identification, and to develop a novel visualization method that quantifies scar encirclement of pulmonary veins postablation treatment for atrial fibrillation.

MATERIALS AND METHODS

A SharK sequence was developed and used at 3T to image the left atrium in 11 patients postcryoballoon ablation. The effects of sharing k-space between the angiographic and LGE acquisitions on the accuracy of scar were assessed. The left atrial wall was segmented and points about each pulmonary vein (PV) ostia were projected onto a bullseye to quantitatively compare PV encirclement. The parameters used to quantify encirclement were varied to perform a sensitivity analysis.

RESULTS

Compared to using a complete set of k-space, total atrial scar differences were significant only when sharing >75% k-space (P = 0.014), and 90% sensitivity and specificity for identifying scar was achieved when sharing 50% k-space. In patients, the right PVs showed more intersubject variance in encirclement compared to the left PVs. A 100° anteroinferior portion of the left PVs was always encircled, while the superior segments of both right PVs was ablated in only 6/11 patients.

CONCLUSION

A SharK sequence was developed to combine angiographic and LGE imaging for atrial wall segmentation and scar identification. The PV bullseye quantifies and localizes encirclement about the PVs. The left PVs showed a higher amount of scar encirclement and less variability compared to the right PVs.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:477-486.