Personalised Model Based Optimal Lead Guidance in Cardiac Resynchronisation Therapy

随着每一次心跳，一波电激活扫过心脏，刺激肌肉收缩。在健康的心脏中，激活波从心脏壁的多个位置开始，并迅速激活整个心脏，从而同步、高效和有效地泵送全身血液。在患有不同步心力衰竭的患者中，激活波从心脏的右手侧开始，并缓慢地向心脏的左手侧发展。这种异步激活模式导致血液的异步、低效和无效泵送。为了治疗这些患者，植入起搏装置，导线连接到心脏的左侧和右侧。通过从这两个导联激活心脏的左侧和右侧，患者的激活模式可以被简化，从而导致同步和有效的收缩。这种治疗被称为心脏起搏治疗或CRT。CRT对大多数患者是有效的治疗，但30-50%的患者未能改善或对治疗有反应。由于手术的侵入性和成本，不希望治疗没有反应的患者。目前，由于无法保证在所有情况下都得到最佳治疗，无法确定无法作出反应的患者。因此，无法区分因未接受最佳治疗而无应答的患者和在任何条件下均无法从CRT中获益的患者。目前的指南建议对患者心脏上的电极导线位置采用“一刀切”的方法，尽管有大量证据表明电极导线的位置在确定结果方面起着关键作用。这表明，一些患者可能会响应CRT，但只有当他们收到最佳的铅placement.The项目的目的是确定最佳的位置放置起搏电极导线在心脏左侧的每一个单独的患者接受CRT，根据生理和病理的特定患者的心脏。为了实现这一目标，我们建议使用先进的高保真度和分辨率成像技术来确定患者心脏的形状，潜在的起搏位置以及心脏中任何死亡的非传导组织的位置。我们将结合联合收割机这一解剖信息与电激活时间的测量，以创建一个生物物理模型的电特性的个别病人的心脏。使用该模型，我们将能够模拟患者心脏中每个潜在起搏位置的激活模式。在训练数据集中，我们将比较每个起搏位置的激动模式与测量的泵功能，以确定最佳预测最佳起搏位置的激动模式。然后进行前瞻性临床研究，在手术前为每位患者创建患者特定模型，并确定最佳起搏位置。然后通过测试模型是否正确预测了最佳起搏位置，在植入器械时评价模型的预测能力。该项目代表了患者特定模型的重大进步-从分析患者数据的技术转变为指导患者治疗的工具。改善CRT患者的结局将降低发病率和住院率，减少NHS无反应患者的经济负担，并提高我们确定患者是否对治疗有反应的特征的能力。

With each heart beat a wave of electrical activation sweeps across the heart stimulating the muscles to contract. In the healthy heart the wave is initiated from many locations across the wall and rapidly activates the whole heart leading to a synchronous, efficient and effective pumping of blood around the body.In patients suffering dyssynchronous heart failure the activation wave starts on the right hand side of the heart and slowly progresses to the left hand side of the heart. This asynchronous activation pattern causes an asynchronous, inefficient and ineffective pumping of blood. To treat these patients a pacing device is implanted with leads attached to the left and right hand side of the heart. By activating the left and right side of the heart from these two leads the patient's activation pattern can be resynchronised leading to a synchronous and effective contraction. This treatment is referred to as cardiac resynchronisation therapy or CRT.CRT is an effective treatment in most patients but 30-50% of patients fail to improve or respond to treatment. Due to the invasive nature and cost of the procedure it is undesirable to treat patients who will not respond. Identifying the patients who cannot respond is currently obfuscated by the inability to guarantee optimal treatment in all cases. Hence it is not possible to differentiate from patients that did not respond as they did not receive the optimal treatment from those that were unable to benefit from CRT under any conditions. At present guidelines suggest a "one size fits all" approach to the location of the leads on the patient's heart despite significant evidence that the location of the leads plays a critical role in determining outcome. This indicates that some patients may respond to CRT but only if they receive optimal lead placement.The aim of this project is to determine the best location to place the pacing lead on the left side of the heart in each individual patient receiving CRT, based on the physiology and pathology of the specific patient's heart. To achieve this aim we propose to use advanced high fidelity and resolution imaging techniques to characterise the shape of the patient's heart, the potential pacing locations, and the location of any dead non-conducting tissue in the heart. We will combine this anatomical information with measurements of electrical activation time to create a biophysical model of the electrical properties of the individual patient's heart. Using the model we will be able to simulate the activation patterns in the patient's heart for each potential pacing location. In a training data set we will compare the activation patterns at each pacing location with measured pump function, in response to pacing, to identify the activation pattern that best predicts the optimal pacing location.A prospective clinical study will then be performed where patient specific models will be created for each patient prior to procedure and the optimal pacing site identified. The predictive capacity of the model will then be evaluated when the device is implanted by testing if the model has correctly predicted the optimal pacing location. The project represents a significant advance for patient specific models - moving from a technique for analysing patient data to a tool for guiding patient treatment. Improving outcomes for CRT patients will reduce morbidity and hospitalisation rates, decrease the financial burden of non-responding patients on the NHS and improve our ability to identify what characteristics determine if a patient will respond to treatment.