Application of Deep Learning to Predict Optimal Ablation Therapy for Atrial Fibrillation from Magnetic Resonance Imaging Data

心房纤颤（AF）的患病率以流行病的比例增加：全世界超过3300万个体患有AF（Chugh等人，2014）。该疾病与发病率和死亡率水平增加、发生心力衰竭和中风的高风险相关，因此患者住院率非常高。AF的总体经济负担占英国总医疗费用的1%以上。维持窦性心律的节律控制策略，如抗心律失常药物，可显著改善心输出量和生活质量。然而，AF的治疗因其自我维持机制而变得复杂，例如存在AF诱导的电和结构重塑，其产生更难治性心律失常（Nattel和Harada，2014）。射频导管消融（CA）治疗旨在通过导管输送高能量破坏心房中的致炎组织区域，已成为AF的一线治疗方法，并且是唯一具有经证实的长期疗效的治疗方法（Kirchhof等人，2016）。然而，即使是先进的CA程序在患有慢性形式的AF的患者中也具有次优的长期结果：超过一半的患者在三年内返回进行额外治疗（Calkins等人，2017年）。这可以通过CA治疗的高度经验性来解释，其针对“通常可疑”区域，而不了解潜在机制。据信，来自肺静脉（PV）的异位电搏动可以触发AF，并且由这种异位波的击穿产生的折返驱动器（RD）可以维持AF。然而，基于肺静脉（PV）的电隔离的经验性CA治疗在慢性AF患者中具有低成功率，其中通常应用重构的非PV区域的广泛消融（Roten等人，2012年）。这保证了新方法的开发，可以提高CA治疗的疗效和临床结果在一个大的患者群体。

The prevalence of atrial fibrillation (AF) is increasing in epidemic proportions: worldwide over 33 million individuals have AF (Chugh et al., 2014). The disease is associated with increased levels of morbidity and mortality, high risks of developing heart failure and stroke, and hence very high rates of patient hospitalizations. The overall economic burden of AF amounts to over 1% of total healthcare costs in the UK. Rhythm control strategies for maintaining sinus rhythm, such as antiarrhythmic drugs, can lead to significant improvements of cardiac output and quality of life. However, treatments of AF are complicated by its mechanisms for self-sustenance, such as the presence of AF-induced electrical and structural remodelling that generates more treatment-resistant arrhythmia (Nattel and Harada, 2014). Radiofrequency catheter ablation (CA) therapy, which is aimed at destroying arrhythmogenic tissue areas in the atria via high energy delivery through a catheter, has become a first-line treatment for AF, and it is the only treatment with a proven long-term curative effect (Kirchhof et al., 2016). However, even advanced CA procedures have suboptimal long-term outcomes in patients with chronic forms of AF: over half of the patients return for additional treatment within three years (Calkins et al., 2017). This can be explained by the highly empirical nature of CA therapy, which targets "usual suspect" areas without knowledge of the underlying mechanisms. It is believed that ectopic electrical beats from the pulmonary veins (PV) can trigger AF, and that re-entrant drivers (RDs) generated by breakdown of such ectopic waves can sustain AF. However, empirical CA therapy based on electrical isolation of the pulmonary veins (PV) has low success rates in chronic AF patients, where extensive ablation of remodelled non-PV areas is commonly applied (Roten et al., 2012). This warrants the development of novel approaches that can improve the efficacy of CA therapy and clinical outcomes in a large patient population.