National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA.
Department of Biomedical Engineering, Polytechnique Montreal, Montreal, Canada.
J Magn Reson Imaging. 2017 Oct;46(4):1060-1072. doi: 10.1002/jmri.25659. Epub 2017 Feb 15.
To present and assess an automatic nonrigid image registration framework that compensates motion in cardiac magnetic resonance imaging (MRI) perfusion series and auxiliary images acquired under a wide range of conditions to facilitate myocardial perfusion quantification.
Our framework combines discrete feature matching for large displacement estimation with a dense variational optical flow formulation in a multithreaded architecture. This framework was evaluated on 291 clinical subjects to register 1.5T and 3.0T steady-state free-precession (FISP) and fast low-angle shot (FLASH) dynamic contrast myocardial perfusion images, arterial input function (AIF) images, and proton density (PD)-weighted images acquired under breath-hold (BH) and free-breath (FB) settings.
Our method significantly improved frame-to-frame appearance consistency compared to raw series, expressed in correlation coefficient (R = 0.996 ± 3.735E-3 vs. 0.978 ± 2.024E-2, P < 0.0001) and mutual information (3.823 ± 4.098E-1 vs. 2.967 ± 4.697E-1, P < 0.0001). It is applicable to both BH (R = 0.998 ± 3.217E-3 vs. 0.990 ± 7.527E-3) and FB (R = 0.995 ± 3.410E-3 vs. 0.968 ± 2.257E-3) paradigms as well as FISP and FLASH sequences. The method registers PD images to perfusion T series (9.70% max increase in R vs. no registration, P < 0.001) and also corrects motion in low-resolution AIF series (R = 0.987 ± 1.180E-2 vs. 0.964 ± 3.860E-2, P < 0.001). Finally, we showed the myocardial perfusion contrast dynamic was preserved in the motion-corrected images compared to the raw series (R = 0.995 ± 6.420E-3).
The critical step of motion correction prior to pixel-wise cardiac MR perfusion quantification can be performed with the proposed universal system. It is applicable to a wide range of perfusion series and auxiliary images with different acquisition settings.
3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1060-1072.
提出并评估一种自动非刚性图像配准框架，该框架补偿心脏磁共振成像（MRI）灌注系列和在广泛条件下获得的辅助图像中的运动，以方便心肌灌注定量。
我们的框架将用于大位移估计的离散特征匹配与多线程体系结构中的密集变分光流公式相结合。该框架在 291 名临床受试者上进行了评估，以配准 1.5T 和 3.0T 稳态自由进动（FISP）和快速低角度射击（FLASH）动态对比心肌灌注图像、动脉输入功能（AIF）图像以及在屏气（BH）和自由呼吸（FB）设置下获得的质子密度（PD）加权图像。
与原始系列相比，我们的方法显著提高了帧到帧的外观一致性，用相关系数（R = 0.996 ± 3.735E-3 与 0.978 ± 2.024E-2，P < 0.0001）和互信息（3.823 ± 4.098E-1 与 2.967 ± 4.697E-1，P < 0.0001）表示。它适用于 BH（R = 0.998 ± 3.217E-3 与 0.990 ± 7.527E-3）和 FB（R = 0.995 ± 3.410E-3 与 0.968 ± 2.257E-3）以及 FISP 和 FLASH 序列。该方法将 PD 图像注册到灌注 T 系列（与无注册相比，R 增加 9.70%，P < 0.001），并校正低分辨率 AIF 系列中的运动（R = 0.987 ± 1.180E-2 与 0.964 ± 3.860E-2，P < 0.001）。最后，我们显示与原始系列相比，运动校正后的图像中保留了心肌灌注对比度动态（R = 0.995 ± 6.420E-3）。
在进行像素级心脏磁共振灌注定量之前，运动校正的关键步骤可以使用提出的通用系统来完成。它适用于具有不同采集设置的广泛的灌注系列和辅助图像。
3 技术功效：第 1 阶段 J. Magn. Reson. Imaging 2017;46:1060-1072.
