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用于预测 CRT 起搏急性效应的患者特异性心脏机电模型:初步临床验证。

Patient-specific electromechanical models of the heart for the prediction of pacing acute effects in CRT: a preliminary clinical validation.

机构信息

INRIA, Asclepios Project, 2004 route des Lucioles, 06 902 Sophia Antipolis, France.

出版信息

Med Image Anal. 2012 Jan;16(1):201-15. doi: 10.1016/j.media.2011.07.003. Epub 2011 Jul 23.

Abstract

Cardiac resynchronisation therapy (CRT) is an effective treatment for patients with congestive heart failure and a wide QRS complex. However, up to 30% of patients are non-responders to therapy in terms of exercise capacity or left ventricular reverse remodelling. A number of controversies still remain surrounding patient selection, targeted lead implantation and optimisation of this important treatment. The development of biophysical models to predict the response to CRT represents a potential strategy to address these issues. In this article, we present how the personalisation of an electromechanical model of the myocardium can predict the acute haemodynamic changes associated with CRT. In order to introduce such an approach as a clinical application, we needed to design models that can be individualised from images and electrophysiological mapping of the left ventricle. In this paper the personalisation of the anatomy, the electrophysiology, the kinematics and the mechanics are described. The acute effects of pacing on pressure development were predicted with the in silico model for several pacing conditions on two patients, achieving good agreement with invasive haemodynamic measurements: the mean error on dP/dt(max) is 47.5±35mmHgs(-1), less than 5% error. These promising results demonstrate the potential of physiological models personalised from images and electrophysiology signals to improve patient selection and plan CRT.

摘要

心脏再同步治疗(CRT)是充血性心力衰竭和宽 QRS 复合物患者的有效治疗方法。然而,多达 30%的患者在运动能力或左心室逆向重构方面对治疗无反应。在患者选择、靶向导线植入和优化这一重要治疗方法方面仍存在许多争议。开发生物物理模型来预测 CRT 的反应代表了一种解决这些问题的潜在策略。在本文中,我们介绍了如何通过个性化心肌机电模型来预测 CRT 相关的急性血液动力学变化。为了将这种方法引入临床应用,我们需要设计可以从左心室的图像和电生理图中个体化的模型。本文描述了解剖结构、电生理、运动学和力学的个体化。通过对两名患者的几种起搏条件进行模拟,预测了起搏对压力发展的急性影响,与侵入性血液动力学测量结果吻合良好:dP/dt(max)的平均误差为 47.5±35mmHgs(-1),误差小于 5%。这些有希望的结果表明,从图像和电生理信号个性化的生理模型有潜力改善患者选择和 CRT 计划。

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