This study demonstrates the feasibility of wideband LGE MRI for suppression of image artefacts induced by ICD at 3T.

Introduction: Radiofrequency (RF) and cryoablation are routinely used to treat arrhythmias, but the extent and time course of edema associated with the two different modalities is unknown. Our goal was to follow the lesion maturation and edema formation after RF and cryoablation using serial magnetic resonance imaging (MRI).Methods and Results: Ventricular ablation was performed in a canine model (n = 11) using a cryo or an irrigated RF catheter. T2-weighted (T2w) edema imaging and late gadolinium enhancement (LGE)-MRI were done immediately (0 day: acute), 1 to 2 weeks (subacute), and 8 to 12 weeks (chronic) after ablation. After the final MRI, excised hearts underwent pathological evaluation. As a result, 45 ventricular lesions (cryo group: 20; RF group: 25) were evaluated. Acute LGE volume was not significantly different but acute edema volume in cryo group was significantly smaller (1225.0 ± 263.5 vs 1855.2 ± 520.5 mm 3 ; P = 0.01). One week after ablation, edema still existed in both group but was similar in size. Two weeks after ablation there was no edema in either of the groups. In the chronic phase, the lesion volume for cryo and RF in LGE-MRI (296.7 ± 156.4 vs 281.6 ± 140.8 mm 3 ; P = 0.73); and pathology (243.3 ± 125.9 vs 214.5 ± 148.6 mm 3 ; P = 0.49), as well as depth, was comparable.Conclusions: When comparing cryo and RF lesions of similar chronic size, acute edema is larger for RF lesions. Edema resolves in both cryo and RF lesions in 1 to 2 weeks. K E Y W O R D S catheter ablation, cryoablation, late gadolinium enhancement, magnetic resonance imaging, radiofrequency 1 | INTRODUCTION Cryo and radiofrequency (RF) ablations are routinely used to treat cardiac arrhythmias. 1 Ablation success depends on creating durable lesions. Despite best efforts, arrhythmia recurrence following catheter ablation is commonly observed. 2,3 Prior studies have shown that there can be a significant edema formation during ablation 4 and some of the recurrences has been attributed to the creation of this edema and as a J Cardiovasc Electrophysiol. 2019;30:255-262. wileyonlinelibrary.com/journal/jce © 2018 Wiley Periodicals, Inc. | 255 O R I G I N A L A R T I C L Eresult, reversible block. 5 Deeper and bigger lesions can be made by using higher contact force, but higher contact force is also associated with more complications like steam pops as well as edema. 6,7 We have also recently reported the large extent of edema that is associated with RF ablation and that it resolves over the span of few weeks. 8 However, the differences between the creation and timeline of edema associated with cryo vs RF are still unknown.Late gadolinium enhancement magnetic resonance imaging (LGE-MRI) has been used to estimate myocardial scar after catheter ablation and T2-weighted (T2w) MRI has been used to estimate edema. [9][10][11] Our goal in this study was to study the timeline and differences between edema and lesion maturation between cryo and RF ablation by using serial MRI for acute and chronic ablation lesions of similar size.

In this study, a radio-frequency (RF) phased array coil was built to image the breast in conjunction with a Magnetic Resonance guided High Intensity Focused Ultrasound (MRgHIFU) device designed specifically to treat the breast in a treatment cylinder with reduced water volume. The MRgHIFU breast coil was comprised of a 10-channel phased array coil placed around an MRgHIFU treatment cylinder where nearest-neighbor decoupling was achieved with capacitive decoupling in a shared leg. In addition a single loop coil was placed at the chest wall making a total of 11-channels. The RF coil array design presented in this work was chosen based on ease of implementation, increased visualization into the treatment cylinder, image reconstruction speed, temporal resolution, and resulting signal-to-noise-ratio (SNR) profiles. This work presents a dedicated 11-channel coil for imaging of the breast tissue in the MRgHIFU setup without obstruction of the ultrasound beam and, specifically, compares its performance in SNR, overall imaging time, and temperature measurement accuracy to that of the standard single chest-loop coil typically used in breast MRgHIFU.

Statistical shape modeling (SSM) has proven useful in many areas of biology and medicine as a new generation of morphometric approaches for the quantitative analysis of anatomical shapes. Recently, the increased availability of high-resolution in vivo images of anatomy has led to the development and distribution of open-source computational tools to model anatomical shapes and their variability within populations with unprecedented detail and statistical power. Nonetheless, there is little work on the evaluation and validation of such tools as related to clinical applications that rely on morphometric quantifications for treatment planning. To address this lack of validation, we systematically assess the outcome of widely used off-the-shelf SSM tools, namely ShapeWorks, SPHARM-PDM, and Deformetrica, in the context of designing closure devices for left atrium appendage (LAA) in atrial fibrillation (AF) patients to prevent stroke, where an incomplete LAA closure may be worse than no closure. This study is motivated by the potential role of SSM in the geometric design of closure devices, which could be informed by population-level statistics, and patient-specific device selection, which is driven by anatomical measurements that could be automated by relating patient-level anatomy to population-level morphometrics. Hence, understanding the consequences of different SSM tools for the final analysis is critical for the careful choice of the tool to be deployed in real clinical scenarios. Results demonstrate that estimated measurements from ShapeWorks model are more consistent compared to models from Deformetrica and SPHARM-PDM. Furthermore, ShapeWorks and Deformetrica shape models capture clinically relevant population-level variability compared to SPHARM-PDM models.

Left atrium shape has been shown to be an independent predictor of recurrence after atrial fibrillation (AF) ablation. Shape-based representation is imperative to such an estimation process, where correspondencebased representation offers the most flexibility and ease-of-computation for population-level shape statistics. Nonetheless, population-level shape representations in the form of image segmentation and correspondence models derived from cardiac MRI require significant human resources with sufficient anatomy-specific expertise. In this paper, we propose a machine learning approach that uses deep networks to estimate AF recurrence by predicting shape descriptors directly from MRI images, with NO image pre-processing involved. We also propose a novel data augmentation scheme to effectively train a deep network in a limited training data setting. We compare this new method of estimating shape descriptors from images with the state-of-the-art correspondence-based shape modeling that requires image segmentation and correspondence optimization. Results show that the proposed method and the current state-of-the-art produce statistically similar outcomes on AF recurrence, eliminating the need for expensive pre-processing pipelines and associated human labor.