Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana, USA.
School of Mechanical Engineering, Purdue University, West Lafayette, Indiana, USA.
Magn Reson Med. 2025 Jan;93(1):397-410. doi: 10.1002/mrm.30287. Epub 2024 Sep 13.
An automatic method is presented for estimating 4D flow MRI velocity measurement uncertainty in each voxel. The velocity distance (VD) metric, a statistical distance between the measured velocity and local error distribution, is introduced as a novel measure of 4D flow MRI velocity measurement quality.
The method uses mass conservation to assess the local velocity error variance and the standardized difference of means (SDM) velocity to estimate the velocity error correlations. VD is evaluated as the Mahalanobis distance between the local velocity measurement and the local error distribution. The uncertainty model is validated synthetically and tested in vitro under different flow resolutions and noise levels. The VD's application is demonstrated on two in vivo thoracic vasculature 4D flow datasets.
Synthetic results show the proposed uncertainty quantification method is sensitive to aliased regions across various velocity-to-noise ratios and assesses velocity error correlations in four- and six-point acquisitions with correlation errors at or under 3.2%. In vitro results demonstrate the method's sensitivity to spatial resolution, venc settings, partial volume effects, and phase wrapping error sources. Applying VD to assess in vivo 4D flow MRI in the aorta demonstrates the expected increase in measured velocity quality with contrast administration and systolic flow.
The proposed 4D flow MRI uncertainty quantification method assesses velocity measurement error owing to sources including noise, intravoxel phase dispersion, and velocity aliasing. This method enables rigorous comparison of 4D flow MRI datasets obtained in longitudinal studies, across patient populations, and with different MRI systems.
提出一种自动方法，用于估计每个体素中 4D 流 MRI 速度测量的不确定性。引入速度距离（VD）度量作为一种新的 4D 流 MRI 速度测量质量的度量，它是测量速度与局部误差分布之间的统计距离。
该方法使用质量守恒来评估局部速度误差方差和标准化均值差异（SDM）速度，以估计速度误差相关性。VD 被评估为局部速度测量值与局部误差分布之间的马氏距离。该不确定性模型在不同的流分辨率和噪声水平下进行了综合验证和体外测试。VD 的应用在两个体内胸血管 4D 流数据集上得到了演示。
合成结果表明，所提出的不确定性量化方法对各种速度与噪声比的混淆区域敏感，并评估了四点和六点采集的速度误差相关性，相关误差在 3.2%或以下。体外结果表明，该方法对空间分辨率、venc 设置、部分体积效应和相位缠绕误差源敏感。将 VD 应用于评估主动脉中的体内 4D 流 MRI 表明，随着对比剂的给药和收缩期血流的增加，测量速度质量的预期增加。
所提出的 4D 流 MRI 不确定性量化方法评估了由于噪声、体素内相位分散和速度混淆等来源引起的速度测量误差。该方法能够对纵向研究、不同患者群体和不同 MRI 系统获得的 4D 流 MRI 数据集进行严格比较。
