3.6 NON-INVASIVE, MRI-BASED ESTIMATION OF PATIENT-SPECIFIC AORTIC BLOOD PRESSURE USING ONE-DIMENSIONAL BLOOD FLOW MODELLING
3.6 NON-INVASIVE, MRI-BASED ESTIMATION OF PATIENT-SPECIFIC AORTIC BLOOD PRESSURE USING ONE-DIMENSIONAL BLOOD FLOW MODELLING
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3.6 使用一维血流模型对患者特异性主动脉血压进行无创、基于 MRI 的估计
DOI：
10.1016/j.artres.2017.10.036
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发表时间：
2017
期刊：
影响因子：
0.6
通讯作者：
Alastruey J
中科院分区：
文献类型：
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作者：
Alastruey J
背景和目的临床证据表明，中心（主动脉）血压（CBP）是一个比肱动脉压更好的心血管风险标志物。然而，CBP只能通过导管插入进行侵入性准确测量。我们提出了一种新的方法来估计CBP非侵入性的主动脉MRI数据和非侵入性的外周（肱动脉）压力测量，使用一个一维（1-D）模型的主动脉blood flow.MethodsWe创建了一个虚拟（计算）受试者的人口，每个独特的动脉脉搏波形可在多个动脉位置，以评估我们的方法。这是通过改变较大全身动脉的分布式1-D模型的心脏（每搏输出量、心动周期、收缩时间）和动脉（脉搏波速度、外周血管阻力）参数在广泛的生理学合理值范围内实现的。优化后，我们的算法的主动脉1-D模型在硅片，我们测试了其准确性在临床人群中的8后缩窄repairpatients.ResultsResults从我们的硅片研究，不同的心脏和动脉参数± 30%，收缩压，平均值和舒张期CBP的最大相对误差分别为4.5%，3.6%和4.2%。收缩压、平均压和舒张压的平均相对误差分别为2.7%、0.9%和1.2%。我们临床研究的相应平均相对误差为5.4%，1.5%和8.0%。图1使用主动脉1-D模型对给定虚拟患者进行CBP估计。图2使用主动脉1-D模型对来自计算机和体内数据的参考收缩期CBP值进行收缩期CBP估计。结论我们为患者的无创估计提供了概念证明-使用计算主动脉血流建模结合MRI数据和非侵入性外周压力测量确定特定中心血压。
Background and objectivesClinical evidence shows that central (aortic) blood pressure (CBP) is a better marker of cardiovascular risk than brachial pressure . However, CBP can only be accurately measured invasively, through catheterisation. We propose a novel approach to estimate CBP non-invasively from aortic MRI data and a non-invasive peripheral (brachial) pressure measurement, using a one-dimensional (1-D) model of aortic blood flow.MethodsWe created a population of virtual (computed) subjects, each with distinctive arterial pulse waveforms available at multiple arterial locations, to assess our approach. This was achieved by varying cardiac (stroke volume, cardiac period, time of systole) and arterial (pulse wave velocity, peripheral vascular resistance) parameters of a distributed 1-D model of the larger systemic arteries within a wide range of physiologically plausible values. After optimising our algorithm for the aortic 1-D model in silico, we tested its accuracy in a clinical population of 8 post-coarctation repair patients.ResultsResults from our in silico study, after varying cardiac and arterial parameters by ± 30%, showed maximum relative errors for systolic, mean and diastolic CBP of 4.5%, 3.6% and 4.2%, respectively. Average relative errors for systolic, mean and diastolic CBP were 2.7%, 0.9% and 1.2%, respectively. Corresponding average relative errors from our clinical study were 5.4%, 1.5% and 8.0%.Figure 1CBP estimation using the aortic 1-D model for a given virtual patient.Figure 2Systolic CBP estimated using the aortic 1-D model against reference systolic CBP values fromin silicoandin vivodata.ConclusionsWe have provided a proof of concept for the non-invasive estimation of patient-specific central blood pressure using computational aortic blood flow modelling in combination with MRI data and a non-invasive peripheral pressure measurement.