Optimisation of pre- and post-procedural patient assessment for transcatheter heart valve replacement using personalised computer modelling

使用个性化计算机模型优化经导管心脏瓣膜置换术术前和术后患者评估

• 批准号: 2288572
• 金额: --
• 依托单位: King's College London
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2288572
• 关键词: Optimisation; pre; post; procedural; patient

Mitral regurgitation (MR) is more common in patients over the age of 65, however they are often deemed too high risk for mitral replacement via open-heart surgery. The current therapy for patients unfit for surgery is transcatheter mitral valve replacement (TMVR). Unlike its aortic valve counterpart, TMVR is a challenging procedure often associated with unstable anchoring; the left ventricular outflow tract obstruction and thrombus formation. In this complex scenario, an effective preprocedural patient assessment is crucial for success, however clinical metrics like ventricular afterload and preload (pressure gradient analysis) and fluid-dynamic forces acting on the implanted device (stability analysis) are invasive to measure. There is therefore an opportunity for this project to develop a novel, time-efficient method for creating personalised computer models able to predict the ventricular haemodynamics of a patient post-TMVR which, once validated in-vivo, have the potential to significantly enhance current patient selection. This project will focus on the creation of an efficient workflow to create the personalised ventricular models. These models will tailored to the anatomical, kinematic and heamodynamic characteristics of the patient. The commercial software package StarCCM+ (Siemens Software PLM) proposed for the haemodynamics simulations will be verified for this type of problems via available benchmark tests. Medtronic will provide complete datasets including multi-phase CT and transesophageal echocardiography (TOE) and Doppler from patients who participated to the Intrepid Global Trial. Simulations will be performed in a pre-TMVR scenario, and on the LV models combined with a CAD model of a Medtronic Intrepid Device in a post-TMVR scenario that will provide a prediction of the haemodynamic response of the LV to implantation. These predictions will be validated against post-TMVR imaging data for each patient, and the uncertainty in the outcomes quantified

二尖瓣返流（MR）在65岁以上的患者中更为常见，但他们通常被认为通过心内直视手术进行二尖瓣置换的风险太高。目前的治疗方法是经导管二尖瓣置换术（TMVR）。与主动脉瓣手术不同，TMVR是一个具有挑战性的手术，通常与不稳定的锚定有关；左室流出道梗阻及血栓形成。在这种复杂的情况下，有效的术前患者评估是成功的关键，然而临床指标，如心室后负荷和前负荷（压力梯度分析）和作用于植入装置的流体动力（稳定性分析）是侵入性的测量。因此，该项目有机会开发一种新颖、高效的方法来创建个性化的计算机模型，该模型能够预测患者在tmvr后的心室血流动力学，一旦在体内得到验证，就有可能显著提高当前患者的选择。该项目将专注于创建一个高效的工作流程来创建个性化的心室模型。这些模型将根据患者的解剖、运动学和血流动力学特征量身定制。商业软件包StarCCM+（西门子软件PLM）提出的血流动力学模拟将通过可用的基准测试来验证这类问题。美敦力将提供完整的数据集，包括参与Intrepid全球试验的患者的多相CT和经食管超声心动图（TOE）和多普勒。将在tmvr前进行模拟，并在tmvr后的情况下，将LV模型与美敦力Intrepid设备的CAD模型结合进行模拟，以预测LV对植入的血流动力学反应。这些预测将根据每位患者的tmvr后成像数据进行验证，并对结果的不确定性进行量化