基于速度测量误差的加权最小二乘法的四维流动磁共振成像(MRI)压力估计

2019/08/12   下载量： 1 次

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应用领域 医疗/卫生
检测样本 癌细胞/肿瘤细胞
检测项目
参考标准 暂无

采用LaVision新近推出的DaVis10.0图像数据采集和处理分析软件平台，对脑动脉瘤模型内血液流动的磁共振成像数据进行抖盒子处理（STB），获得了模型中流体的四维流场信息，并利用这一结果，进行了压力求解。

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    This work introduces a 4D-flow magnetic resonance imaging (MRI) pressure reconstruction method which employs weighted least-squares (WLS) for pressure integration. Pressure
gradients are calculated from the velocity fields, and velocity errors are estimated from the velocity divergence for incompressible flow. Pressure gradient errors are estimated by
propagating the velocity errors through Navier-Stokes momentum equation. A weight matrix is generated based on the pressure gradient errors, then employed for pressure reconstruction. The pressure reconstruction method was demonstrated and analyzed using synthetic velocity fields as well as Poiseuille flow measured using in vitro 4D-flow MRI. Performance of the proposed WLS method was compared to the method of solving the pressure Poisson equation which has been the primary method used in the previous studies. Error analysis indicated that the proposed method is more robust to velocity measurement errors.
Improvement on pressure results was found to be more significant for the cases with spatially-varying velocity error level, with reductions in error ranging from 50% to over 200%. Finally, the method was applied to flow in a patient-specific cerebral aneurysm. Validation was performed with in vitro flow data collected using Particle Tracking Velocimetry (PTV) and Shake the Box (STB) method, and in vivo flow measurement obtained using 4D-flow MRI. Pressure calculated by WLS, as opposed to the Poisson equation, was more consistent with the flow structures and showed better agreement between the in vivo and in vitro data.
These results suggest the utility of WLS method to obtain reliable pressure field from clinical flow measurement data.

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北京欧兰科技发展有限公司
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