Advances in imaging for atrial fibrillation ablation.

Over the last fifteen years, our understanding of the pathophysiology of atrial fibrillation (AF) has paved the way for ablation to be utilized as an effective treatment option. With the aim of gaining more detailed anatomical representation, advances have been made using various imaging modalities, both before and during the ablation procedure, in planning and execution. Options have flourished from procedural fluoroscopy, electroanatomic mapping systems, preprocedural computed tomography (CT), magnetic resonance imaging (MRI), ultrasound, and combinations of these technologies. Exciting work is underway in an effort to allow the electrophysiologist to assess scar formation in real time. One advantage would be to lessen the learning curve for what are very complex procedures. The hope of these developments is to improve the likelihood of a successful ablation procedure and to allow more patients access to this treatment

CardiacNET: Segmentation of Left Atrium and Proximal Pulmonary Veins from MRI Using Multi-View CNN

Anatomical and biophysical modeling of left atrium (LA) and proximal pulmonary veins (PPVs) is important for clinical management of several cardiac diseases. Magnetic resonance imaging (MRI) allows qualitative assessment of LA and PPVs through visualization. However, there is a strong need for an advanced image segmentation method to be applied to cardiac MRI for quantitative analysis of LA and PPVs. In this study, we address this unmet clinical need by exploring a new deep learning-based segmentation strategy for quantification of LA and PPVs with high accuracy and heightened efficiency. Our approach is based on a multi-view convolutional neural network (CNN) with an adaptive fusion strategy and a new loss function that allows fast and more accurate convergence of the backpropagation based optimization. After training our network from scratch by using more than 60K 2D MRI images (slices), we have evaluated our segmentation strategy to the STACOM 2013 cardiac segmentation challenge benchmark. Qualitative and quantitative evaluations, obtained from the segmentation challenge, indicate that the proposed method achieved the state-of-the-art sensitivity (90%), specificity (99%), precision (94%), and efficiency levels (10 seconds in GPU, and 7.5 minutes in CPU).Comment: The paper is accepted by MICCAI 2017 for publicatio

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 scars provide important information of the pathophysiology and progression of atrial fibrillation (AF). Hence, LA scar segmentation and quantification from LGE MRI can be useful in computer-assisted diagnosis and treatment stratification of AF patients. Since manual delineation 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. Finally, the possible future developments are outlined, with a brief survey on the potential clinical applications of the aforementioned methods. The review shows that the research into this topic is still in early stages. Although several methods have been proposed, especially for LA segmentation, there is still large scope for further algorithmic developments due to performance issues related to the high variability of enhancement appearance and differences in image acquisition.Comment: 23 page

3D MODELLING AND RAPID PROTOTYPING FOR CARDIOVASCULAR SURGICAL PLANNING – TWO CASE STUDIES

In the last years, cardiovascular diagnosis, surgical planning and intervention have taken advantages from 3D modelling and rapid prototyping techniques. The starting data for the whole process is represented by medical imagery, in particular, but not exclusively, computed tomography (CT) or multi-slice CT (MCT) and magnetic resonance imaging (MRI). On the medical imagery, regions of interest, i.e. heart chambers, valves, aorta, coronary vessels, etc., are segmented and converted into 3D models, which can be finally converted in physical replicas through 3D printing procedure. In this work, an overview on modern approaches for automatic and semiautomatic segmentation of medical imagery for 3D surface model generation is provided. The issue of accuracy check of surface models is also addressed, together with the critical aspects of converting digital models into physical replicas through 3D printing techniques. A patient-specific 3D modelling and printing procedure (Figure 1), for surgical planning in case of complex heart diseases was developed. The procedure was applied to two case studies, for which MCT scans of the chest are available. In the article, a detailed description on the implemented patient-specific modelling procedure is provided, along with a general discussion on the potentiality and future developments of personalized 3D modelling and printing for surgical planning and surgeons practice

Use of three-dimensional computed tomography overlay for real-time cryoballoon ablation in atrial fibrillation reduces radiation dose and contrast dye

AIMS: Cryoballoon pulmonary vein (PV) isolation in patients with atrial fibrillation has proven to be effective in short-term and long-term follow-up. To visualise the PV anatomy, pre-ablation contrast pulmonary venography is commonly performed. Three-dimensional (3D) computed tomography (CT) overlay is a new technique creating a live 3D image of the left atrium by integrating a previously obtained CT scan during fluoroscopy. To evaluate the benefits of 3D CT overlay during cryoballoon ablation, we studied the use of 3D CT overlay versus contrast pulmonary venography in a randomised fashion in patients with paroxysmal atrial fibrillation undergoing cryoballoon PV isolation. METHODS AND RESULTS: Between October 2012 and June 2013, 30 patients accepted for PV isolation were randomised to cryoballoon PV isolation using either 3D CT overlay or contrast pulmonary venography. All patients underwent a pre-procedural cardiac CT for evaluation of the anatomy of the left atrium (LA) and the PVs. In the 3D CT overlay group, a 3D reconstruction of the LA and PVs was made. An overlay of the CT reconstruction was then projected over live fluoroscopy. Patients in the contrast pulmonary venography group received significantly more contrast agent (77.1 ± 21.2 cc vs 40.1 ± 17.6 cc, p < 0.001) and radiation (43.0 ± 21.9 Gy.cm2 vs 28.41 ± 11.7 Gy.cm2, p = 0.04) than subjects in the 3D CT overlay group. There was no difference in total procedure time, fluoroscopy time and the amount of cryoapplications between the two groups. CONCLUSION: The use of 3D CT overlay decreases radiation and contrast dye exposure and can assist in guiding cryoballoon-based PV isolation