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Towards personalized clinical in-silico modeling of atrial anatomy and electrophysiology

机译:建立个性化的心房解剖学和电生理学临床计算机模拟模型

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Computational atrial models aid the understanding of pathological mechanisms and therapeutic measures in basic research. The use of biophysical models in a clinical environment requires methods to personalize the anatomy and electrophysiology (EP). Strategies for the automation of model generation and for evaluation are needed. In this manuscript, the current efforts of clinical atrial modeling in the euHeart project are summarized within the context of recent publications in this field. Model-based segmentation methods allow for the automatic generation of ready-to-simulate patient-specific anatomical models. EP models can be adapted to patient groups based on a-priori knowledge and to the individual without significant further data acquisition. ECG and intracardiac data build the basis for excitation personalization. Information from late enhancement (LE) MRI can be used to evaluate the success of radio-frequency ablation (RFA) procedures and interactive virtual atria pave the way for RFA planning. Atrial modeling is currently in a transition from the sole use in basic research to future clinical applications. The proposed methods build the framework for model-based diagnosis and therapy evaluation and planning. Complex models allow to understand biophysical mechanisms and enable the development of simplified models for clinical applications.
机译:计算性心房模型有助于基础研究中的病理机制和治疗措施的理解。在临床环境中使用生物物理模型需要个性化解剖结构和电生理学(EP)的方法。需要用于模型生成自动化和评估的策略。在此手稿中,euHeart项目中当前临床心房建模的工作总结于该领域的最新出版物中。基于模型的分割方法可自动生成易于模拟的患者特定解剖模型。 EP模型可以基于先验知识适用于患者组,也可以适用于个人,而无需大量的进一步数据获取。心电图和心脏内数据为激发个性化打下基础。来自晚期增强(LE)MRI的信息可用于评估射频消融(RFA)程序的成功,而交互式虚拟心房为RFA计划铺平了道路。心房模型目前正在从基础研究的唯一用途过渡到未来的临床应用。所提出的方法建立了基于模型的诊断,治疗评估和计划的框架。复杂模型可以理解生物物理机制,并可以开发用于临床应用的简化模型。

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