Using Atrial Mechanics To Identify Fibrosis In Patients with Atrial Fibrillation

项目总结 房颤是一种高度流行的疾病，影响着520万美国人，每年给美国造成60-260亿美元的损失 年，并增加心血管疾病、中风和死亡的风险。选择最佳治疗方案 每个房颤患者仍然是一个日常的临床挑战，因为没有一个单一的治疗方法是所有病例中最好的。有症状的 患者最常用的治疗方法是药物治疗，或通过导管消融来隔离或摧毁迷走性心房。 组织。然而，两者通常都是无效的，而且没有一致的反应预测因素。 病理性心房纤维化是持续房颤的主要因素，已多次被认为与其有关 发病机制，并被建议作为个性化治疗的生物标志物。我们建议使用心脏磁共振(CMR) 识别局限性心房纤维化的基于力学的方法。心房纤维化导致混乱的电生理学 还可以减弱局部的心房力学，降低收缩能力，增加僵硬。对心房肌的影响 机械学是很重要的。因此，我们假设减弱的心房机械能提供一种可靠的测量方法。 心房纤维化症。这个项目的结果将是第一个经过组织学验证的、可重复的和可重复的 能够评估心房纤维化负担的临床工具。 这笔赠款的目的是利用心房纤维化和心房力学之间的机械联系来开发 并验证用于测量基于力学的纤维化分类器的临床工作流程。总体目标是 建立一种以力学为基础的、经组织学证实的心房纤维化的判别方法。这个 以下目标是为实现这一目标而设计的。 目的1.稳健性测量窦性心律和房颤时的三维心房CMR应变和硬度。心房运动--均匀 在房颤期间--在CMR上很明显。我们的自由呼吸和心律失常不敏感的CMR协议支持 测量心房力学不需要造影剂或超声心动图的限制，也不需要辐射 电脑断层扫描。我们试图通过识别受损的心房力学来检测心房纤维化。 目的2.验证和基准一个基于CMR力学的心房纤维化分类方法。的最优指标 目前尚不清楚是否能从心房力学中识别出局部的心房纤维化。训练和验证分类器需要 基本事实，我们将使用组织学直接测量。然后将对该分类器进行基准测试 心房纤维化的常规标记物(电压标记法和LGE-CMR)。 公共卫生意义-确定对特定治疗有反应的房颤患者 消融等策略是心脏科医生每天面临的挑战。为每个房颤选择最佳治疗方案 耐心仍然是一个开放的挑战。这项工作的结果将使临床医生能够更好地管理患者 通过使用基于心脏MRI的方法，帮助识别心房纤维化负担，从而帮助识别心房颤动。

PROJECT SUMMARY Atrial fibrillation (AF) is a highly prevalent disease affecting 5.2 million Americans, costs the US $6-26 billion per year, and increases the risk of cardiovascular disease, stroke, and death. Selecting the optimal treatment for each AF patient remains a daily clinical challenge as no single treatment is best in all cases. Symptomatic patients are most frequently treated pharmacologically, or by catheter ablation to isolate or destroy aberrant atrial tissue. However, both are commonly ineffective and there are no consistent predictors of response. Pathological atrial fibrosis is a major contributor to sustaining AF, has repeatedly been implicated in its pathogenesis and is proposed as a biomarker for personalizing treatment. We propose to use cardiac MRI (CMR) mechanics-based measures to identify localized atrial fibrosis. Atrial fibrosis fosters chaotic electrophysiology and also attenuates local atrial mechanics, decreases contractility, and increases stiffness. The impact on atrial mechanics is substantial. Therefore, we hypothesize that attenuated atrial mechanics provide a robust measure of atrial fibrosis. The result of this project will be the first histologically validated, reproducible and repeatable clinical tool that enables estimation of atrial fibrosis burden. The aims of this grant will exploit the mechanistic link between atrial fibrosis and atrial mechanics to develop and validate a clinical workflow for measuring a mechanics-based classifier of fibrosis. The overall objective is to establish a mechanics-based and discriminatory measure of histologically validated atrial fibrosis. The following aims are designed to achieve this objective. AIM 1. To robustly measure 3D atrial CMR strain and stiffness in sinus rhythm and AF. Atrial motion – even during AF – is readily apparent on CMR. Our free-breathing and arrhythmia insensitive CMR protocol enables measuring atrial mechanics without the need for contrast or the limitations of echocardiography, nor the radiation of CT. We seek to detect atrial fibrosis by identifying impaired atrial mechanics. AIM 2. Validate and benchmark a CMR mechanics-based classifier of atrial fibrosis. The optimal index for identifying local atrial fibrosis from atrial mechanics is not known. Training and validating a classifier requires a ground truth, which we will measure directly using histology. The classifier will then be benchmarked against conventional markers of atrial fibrosis (voltage mapping and LGE-CMR). Public Health Significance – Identifying patients with atrial fibrillation (AF) that will respond to specific treatment strategies such as ablation is a daily challenge for cardiologists. Selecting the optimal treatment for each AF patient remains an open challenge. The results of this work will enable clinicians to better manage patients with atrial fibrillation by helping to identify the atrial fibrosis burden using cardiac MRI based methods.