Brüning Jan, Hellmeier Florian, Yevtushenko Pavlo, Kühne Titus, Goubergrits Leonid
Institute for Imaging Science and Computational Modelling in Cardiovascular Medicine, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, Forum 4 - 0.0561, 13353, Berlin, Germany.
Department of Congenital Heart Disease - Unit of Cardiovascular Imaging, German Heart Center Berlin, Berlin, Germany.
Cardiovasc Eng Technol. 2018 Dec;9(4):582-596. doi: 10.1007/s13239-018-00381-3. Epub 2018 Oct 3.
Numerical assessment of the pressure drop across an aortic coarctation using CFD is a promising approach to replace invasive catheter-based measurements. The aim of this study was to investigate and quantify the uncertainty of numerical calculation of the pressure drop introduced during two essential steps of medical image processing: segmentation of the patient-specific geometry and measurement of patient-specific flow rates from 4D-flow-MRI.
Based on the baseline segmentation, geometries with different stenosis diameters were generated for a sample of ten patients. The pressure drop generated by these geometries was calculated for different volume flow rates using computational fluid dynamics. Based on these simulations, a second order polynomial fit was calculated. Based on these polynomial fits an uncertainty of pressure drop calculation was quantified.
The calculated pressure drop values varied strongly between the patients. In four patients, pressure drops above and below the clinical threshold of 20 mmHg were found. The median standard deviation of the pressure drop was 2.3 mmHg. The sensitivity of the pressure drop toward changes in the volume flow rate or the stenosis geometry varied between patients.
The uncertainty of numerical pressure drop calculation introduced by uncertainties during image segmentation and measurement of volume flow rates was comparable to the uncertainty of pressure drop measurements using invasive catheterization. However, in some patients this uncertainty would have led to different treatment decision. Therefore, patient-specific uncertainty assessment might help to better understand the reliability of a numerically calculated biomarker as the pressure drop across an aortic coarctation.
使用计算流体动力学(CFD)对主动脉缩窄两端的压降进行数值评估是一种有望取代基于侵入性导管测量的方法。本研究的目的是调查和量化在医学图像处理的两个基本步骤中引入的压降数值计算的不确定性:患者特定几何形状的分割以及从四维流动磁共振成像(4D-flow-MRI)测量患者特定的流速。
基于基线分割,为10名患者的样本生成了具有不同狭窄直径的几何形状。使用计算流体动力学针对不同的体积流量计算这些几何形状产生的压降。基于这些模拟,计算了二阶多项式拟合。基于这些多项式拟合,量化了压降计算的不确定性。
计算出的压降值在患者之间差异很大。在4名患者中,发现压降高于和低于20 mmHg的临床阈值。压降的中位数标准差为2.3 mmHg。压降对体积流量或狭窄几何形状变化的敏感性在患者之间有所不同。
图像分割和体积流量测量过程中的不确定性所导致的数值压降计算的不确定性与使用侵入性导管插入术进行压降测量的不确定性相当。然而,在某些患者中,这种不确定性可能会导致不同的治疗决策。因此,患者特定的不确定性评估可能有助于更好地理解作为主动脉缩窄两端压降的数值计算生物标志物的可靠性。