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

项目概要 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都是由穿过电路的电气“短路”引起的。 心肌疤痕内残留的狭窄组织。导管消融通过“阻断”治疗疤痕相关室速 形成电路的幸存通道，通常位于电路从疤痕退出的位置。本地化 VT 然而，退出仍然是一个重大挑战。一种常见的方法，称为步速映射，利用 VT 出口作为心室激动的起点并决定 QRS 形态的原理 12 导联心电图 (ECG)。因此，它涉及在心脏的各个部位进行重复的电模拟， 直到找到在所有 12 条 ECG 导联上重现 VT QRS 的站点。虽然步伐背后的原则是 绘图是经过时间考验的，目前的做法具有“试错”性质，需要快速定性 临床医生对心电图的解释可能既耗时又不准确。这项研究提出 利用现代机器学习技术来改革步速映射原理的使用方式。 旨在了解心室激动的起源与心电图形态之间的关系，然后利用 它可以根据 ECG 数据直接预测 VT 的退出。为此，该项目将包括以下内容 活动：1) 开发基于人群的模型，以提供 VT 出口的程序前初始定位 使用标准 12 导联心电图； 2）将基于人群的模型与患者特定模型相结合 临床可用的软件，为定位临床出口部位提供程序内实时指导 VT； 3）评估所提出的软件提高速度效率和准确性的能力 - 前瞻性临床研究中的绘图。该项目将由多学科团队执行 计算和临床科学家之间有着卓有成效的合作记录。本项目交付的软件 将为临床医生提供实时帮助，以最短的时间缩小 VT 退出范围，并且 本地化错误。这将大大减少消融多个 VT 的工作量，从而可能允许 临床医生可以消融手术中看到的更多甚至全部室速。这可能会缩短消融的持续时间 程序，同时改善其结果。软件的开发和部署也增加了最少的 日常工作流程的成本或干扰。由于临床实施的门槛较低，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.