Uncertainty Quantification in Prospective and Predictive Patient Specific Cardiac Models

临床诊断很少是决定性的。临床数据嘈杂且稀疏，往往支持多种诊断和潜在的治疗方法。要决定如何最好地治疗患者，需要确定个人的许多可能结果及其相应的概率。在这个项目中，我们将应用为汽车、地质和气象预测开发的不确定性量化数学，结合单个患者生理学和病理生理学的生物物理模型来预测患者结果及其相应的概率。这将展示如何使用患者特有的计算模型来进行前瞻性预测，以指导手术并为不确定的临床决策提供信息。不确定性量化和预测性患者特有模型的使用将应用于房颤患者。房颤是英国最常见的心律失常。在药物治疗无效的患者中，通过导管消融切除或隔离心房的病理性区域。然而，多达40%的晚期(持续性)房颤患者需要进一步消融来治疗房性心动过速(病理性但有规律的激活)，这种心动过速是在进行了初步消融治疗房颤后发展起来的。为了减少额外手术的数量，该项目将根据最初持续性房颤消融程序时记录的测量结果，预测患者发生房性心动过速的可能性和房性心动过速将采取的路径。如果成功，这种方法将在最初的程序中指导预防性消融，以减少重复程序的需要。

Clinical diagnosis is seldom definitive. Clinical data are noisy and sparse, and often support multiple diagnoses and potential therapies. To decide how best to treat a patient requires identifying the many possible outcomes for an individual and their corresponding probabilities. In this project we will apply the mathematics of uncertainty quantification, developed for automotive, geological and meteorological predictions, combined with biophysical models of individual patient physiology and pathophysiology to predict patient outcomes and their corresponding probabilities. This will demonstrate how patient specific computational models can be used to make prospective predictions to guide procedures and inform uncertain clinical decisions.The use of uncertainty quantification and predictive patient specific models will be applied to patients with atrial fibrillation. Atrial fibrillation (AF) is the most common cardiac arrhythmia in the UK. In patients who do not respond to drug treatment, the pathological regions of the atria are removed or isolated through catheter ablation. However, up to 40% of patients with advanced (persistent) AF require further ablations to treat atrial tachycardia (pathological but regular activation) that develops after they have had an initial ablation to treat their AF. To reduce the number of additional procedures, this project will predict the probability that a patient will develop atrial tachycardia and the path that the atrial tachycardia will take, based on measurements recorded at the time of the initial persistent AF ablation procedure. If successful this approach would guide preventative ablations during the initial procedure to reduce the need for repeat procedures.