Automating Real-Time Localization of Target Sites in Catheter Ablation of Ventricular Tachycardia

项目摘要 室性心动过速(VT)是心脏病患者死亡和发病的重要原因。 大多数危及生命的室性心动过速发作是由穿过 心肌疤痕内有狭窄的存活组织。导管消融“阻断”治疗疤痕相关性室速 形成环路的幸存通道，通常在环路从疤痕出来的部位。本地化VT的步骤 然而，退出仍然是一个巨大的挑战。一种常见的方法称为速度映射，它利用 室性心动过速起始点决定QRS波群形态的原理 12导联心电图(ECG)。因此它涉及心脏不同部位的重复电模拟， 直到找到在所有12个心电导联上再现室速QRS的部位。虽然佩斯背后的原则- 测绘是经过时间考验的，目前的做法是“试错”性质的，需要快速定性 由临床医生解释心电，这可能是耗时和不准确的。这项研究提出 利用现代机器学习技术来改革速度映射背后的原理的使用方式。 它的目的是了解心室激动的起源与心电形态之间的关系，从而使用 它可以直接从其心电数据中预测室速的退出。为此，该项目将包括以下内容 活动：1)开发基于人口的模型，以提供VT出口的程序前初始本地化 使用标准12导联心电；2)将基于人群的模型与患者特定的模型集成在一起 临床可用的软件，为定位临床的出口部位提供程序内实时指导 VT；以及3)评估拟议软件提高PACE的效率和准确性的能力- 一项前瞻性临床研究中的地图绘制。该项目将由一个多学科团队实施， 拥有卓有成效的合作记录的计算和临床科学家。此项目交付的软件 将为临床医生提供实时帮助，以便在最短的时间内缩小VT出口的范围，并 本地化错误。这将大大减少消融多个室速的工作量，潜在地允许 临床医生需要消融更多甚至所有的室性心动过速。这可能会缩短消融的持续时间 程序，同时改善其结果。软件的开发和部署还增加了最少的 成本或对日常工作流程的干扰。由于临床实施的门槛很低，它将具有真正的潜力 挑战和改进导管消融的标准实践。

Project Summary Ventricular tachycardia (VT) is an important cause of mortality and morbidity in patients with heart diseases. The majority of life-threatening VT episodes are caused by an electrical "short circuit” that travels through narrow strands of surviving tissue inside myocardial scar. Catheter ablation treats scar-related VT by “blocking” the surviving channel that forms the circuit, commonly at the site the circuit exits from the scar. To localize a VT exit, however, remains a significant challenge. A common approach, known as pace-mapping, utilizes the principle that the VT exit serves as the origin of ventricular activation and determines the QRS morphology on 12-lead electrocardiograms (ECGs). It thus involves repetitive electrical simulation at various sites of the heart, until locating the site that reproduces the QRS of the VT on all 12 ECG leads. While the principle behind pace- mapping is time tested, the current practice is of a "trial-and-error" nature and requires rapid qualitative interpretation of the ECG by clinicians, which can be time-consuming and inaccurate. This research proposes to leverage modern machine learning techniques to reform the way the principle behind pace-mapping is used. It aims to learn the relationship between the origin of ventricular activation and ECG morphology, and then use it to directly predict the exit of a VT from its ECG data. To this end, this project will include the following activities: 1) to develop a population-based model to provide pre-procedural initial localizations of VT exits using standard 12-lead ECG; 2) to integrate the population-based model with a patient-specific model in clinically-usable software to provide intra-procedural real-time guidance for localizing the exit site of a clinical VT; and 3) to assess the ability of the proposed software to improve the efficiency and accuracy of pace- mapping in a prospective clinical study. This project will be carried out by a multidisciplinary team of computational and clinical scientists with a fruitful record of collaboration. The software delivered by this project will provide real-time assistance to clinicians for narrowing down a VT exit with a minimum amount of time and localization errors. This will substantially reduce the workload for ablating multiple VTs, potentially allowing clinicians to ablate more or even all VTs seen in a procedure. This may reduce the duration of an ablation procedure while improving its outcome. The development and deployment of the software also adds minimal cost or distractions to routine workflow. With a low barrier to clinical implementation, it will have a real potential to challenge and improve the standard practice of catheter ablation.