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首页> 美国卫生研究院文献>Healthcare Technology Letters >Towards personalised management of atherosclerosis via computational models in vascular clinics: technology based on patient-specific simulation approach
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Towards personalised management of atherosclerosis via computational models in vascular clinics: technology based on patient-specific simulation approach

机译：通过血管诊所中的计算模型实现动脉粥样硬化的个性化管理：基于患者特定模拟方法的技术

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摘要

The development of a new technology based on patient-specific modelling for personalised healthcare in the case of atherosclerosis is presented. Atherosclerosis is the main cause of death in the world and it has become a burden on clinical services as it manifests itself in many diverse forms, such as coronary artery disease, cerebrovascular disease/stroke and peripheral arterial disease. It is also a multifactorial, chronic and systemic process that lasts for a lifetime, putting enormous financial and clinical pressure on national health systems. In this Letter, the postulate is that the development of new technologies for healthcare using computer simulations can, in the future, be developed as in-silico management and support systems. These new technologies will be based on predictive models (including the integration of observations, theories and predictions across a range of temporal and spatial scales, scientific disciplines, key risk factors and anatomical sub-systems) combined with digital patient data and visualisation tools. Although the problem is extremely complex, a simulation workflow and an exemplar application of this type of technology for clinical use is presented, which is currently being developed by a multidisciplinary team following the requirements and constraints of the Vascular Service Unit at the University College Hospital, London.
机译：提出了基于患者特定模型的新技术的开发，用于动脉粥样硬化情况下的个性化医疗保健。动脉粥样硬化是世界上主要的死亡原因，并且由于它以多种多样的形式表现出来，例如冠状动脉疾病，脑血管疾病/中风和周围动脉疾病，它已经成为临床服务的负担。它也是一个多因素，慢性和系统性过程，持续一生，给国家卫生系统带来巨大的财务和临床压力。在这封信中，假设是将来可以使用计算机模拟开发用于医疗保健的新技术，作为电子管理和支持系统。这些新技术将基于预测模型（包括在一系列时空尺度，科学学科，关键风险因素和解剖子系统中的观察，理论和预测的集成）与数字患者数据和可视化工具相结合。尽管问题非常复杂，但仍提出了这种技术在临床上的仿真工作流程和样板应用，目前，这是由多学科团队根据大学医院的血管服务部门的要求和约束条件开发的，伦敦。

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