EPSRC Centre for Future PCI Planning

EPSRC 未来 PCI 规划中心

• 批准号: EP/Z531182/1
• 负责人: Sean McGinty
• 金额: $ 162.53万
• 依托单位: University of Glasgow
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FZ531182%2F1
• 关键词: EPSRC; Centre; Future; PCI; Planning

Percutaneous Coronary Intervention (PCI) is a common clinical procedure used to treat obstructive coronary artery disease, one of the leading causes of death. The overwhelming majority of patients will receive drug-eluting stent devices that act as a supporting scaffold and deliver drugs to counteract renarrowing. While this technology has been truly revolutionary, hundreds of thousands of patients worldwide annually still require an invasive repeat procedure, representing a huge economic burden on society and increasing pressure on health care resources. The key issue is that it is currently not feasible to quantitatively predict the immediate effect of a specific intervention and if/when a patient will suffer from renarrowing in the longer-term. Tools that enable optimisation of the procedure on a patient-specific basis are therefore urgently needed to improve patient outcomes and alleviate the resource burden on healthcare providers.Critical to optimising the procedure is assessment of the individual patient's level of disease. Advances in medical imaging technology now make it possible to visualise the degree of obstruction and, crucially, the composition of the underlying plaque, potentially providing clinicians with a wealth of information to inform and plan PCI. However, decisions are presently left to operator experience and there are no definitive guidelines for how to optimise PCI for a given patient, particularly in complex cases.In recent years, we have seen significant developments in computational models of PCI, that have the potential to inform PCI strategy in the future. However, they suffer from limitations and significant methodological advances are required before they can be routinely integrated within the clinic. These primarily relate to increasing the realism and accuracy of the models, improving their robustness, predictive power and speed of computation. This last point is critical, with the exorbitant run times of current computational models significantly hampering timely decision support and genuine impact in the clinic.The EPSRC Centre for Future PCI Planning will address these challenges by developing a computational decision support tool to assist clinicians with PCI planning. Advances in mathematical modelling of fluid-structure interaction, lesion preparation, drug delivery and growth & remodelling, allied to statistical inference, emulation, uncertainty quantification and optimisation will enable us to create computational tools able to answer key clinical questions like:1) What will a given patient's artery look like immediately after device deployment?2) How should the plaque be modified prior to stent deployment, and what specialist tools should be used to do this?3) What length and diameter of stent should be used, and what should be the balloon deployment inflation pressure?4) What is the optimal placement of the stent?5) In the case of complex bifurcation lesions, where potentially multiple stents and balloons are deployed, what is the optimal technique?6) To what extent is the artery likely to renarrow, over what time course, and how can the PCI strategy be optimised to avoid this?7) Can we effectively plan PCI solely on pre-procedural imaging such as Computed Tomography?Working together with world-leading International Centres, and a range of leading imaging and medical device companies, the EPSRC Centre for Future PCI Planning will develop novel and robust mathematical and statistical methodologies, supported by large clinical data sets, to create the novel, fast and accurate tools that will help realise our vision of integrating computational tools for PCI planning within the clinic.

经皮冠状动脉干预（PCI）是一种常见的临床程序，用于治疗阻塞性冠状动脉疾病，这是死亡的主要原因之一。绝大多数患者将获得洗脱的支架设备，这些设备充当支撑脚手架并提供药物以抵消重生。尽管这项技术确实是革命性的，但全球数十万名患者仍需要进行侵入性重复程序，这代表了社会的巨大经济负担，并增加了对医疗保健资源的压力。关键问题是，目前不可行地预测特定干预的直接影响，以及/何时长期会遭受重生。因此，迫切需要在特定于患者的基础上优化该手术的工具，以改善患者的预后并减轻医疗保健提供者的资源负担。要优化该程序的工具是评估个体患者疾病水平的评估。现在，医学成像技术的进步使您可以看到障碍的程度，并且至关重要的是，基础斑块的组成，有可能为临床医生提供大量信息以告知和计划PCI。但是，目前的决策留给了操作员的经验，并且没有关于如何为特定患者优化PCI的确定指南，尤其是在复杂的情况下。近年来，我们已经看到PCI计算模型的重大发展，可以在未来为PCI策略提供信息。但是，它们遭受局限性，需要在诊所内将它们定期整合起来之前需要大量的方法论进步。这些主要与增加模型的现实主义和准确性有关，提高其鲁棒性，预测能力和计算速度。最后一点至关重要，当前计算模型的过高运行时间大大阻碍了及时的决策支持和对诊所的真正影响。 Advances in mathematical modelling of fluid-structure interaction, lesion preparation, drug delivery and growth & remodelling, allied to statistical inference, emulation, uncertainty quantification and optimisation will enable us to create computational tools able to answer key clinical questions like:1) What will a given patient's artery look like immediately after device deployment?2) How should the plaque be modified prior to stent deployment, and what specialist tools should be used to do这是？3）应该使用什么长度和直径，应该使用气球部署通货膨胀压力？4）支架的最佳位置是什么？5）在复杂的分叉病变的情况下，什么是什么？5）在可能的范围内，有什么能力避免了什么程度的效果？ ？诊所。