Department of Medical Informatics, Erasmus MC, Rotterdam, the Netherlands; Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands.
Department of Medical Informatics, Erasmus MC, Rotterdam, the Netherlands; Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands.
Magn Reson Imaging. 2021 May;78:80-89. doi: 10.1016/j.mri.2021.02.002. Epub 2021 Feb 14.
To improve image quality of multi-contrast imaging with the proposed Autocalibrated Parallel Imaging Reconstruction for Extended Multi-Contrast Imaging (APIR4EMC).
APIR4EMC reconstructs multi-contrast images in an autocalibrated parallel imaging reconstruction framework by adding contrasts as virtual coils. Compensation of signal evolution along the echo train of different contrasts is performed to improve signal prediction for missing samples. As a proof of concept, we performed prospectively accelerated phantom and in-vivo brain acquisitions with T1, T1-fat saturated (Fatsat), T2, PD, and FLAIR contrasts. The k-space sampling patterns of these acquisitions were jointly optimized. Images were jointly reconstructed with the proposed APIR4EMC method as well as individually with GRAPPA. Root mean square error (RMSE) to fully sampled reference images and g-factor maps were computed for both methods in the phantom experiment. Visual evaluation was performed in the in-vivo experiment.
Compared to GRAPPA, APIR4EMC reduced artifacts and improved SNR of the reconstructed images in the phantom acquisitions. Quantitatively, APIR4EMC substantially reduced noise amplification (g-factor) as well as RMSE compared to GRAPPA. Signal evolution compensation reduced artifacts. In the in-vivo experiments, 1 mm isotropic 3D images with contrasts of T1, T1-Fatsat, T2, PD, and FLAIR were acquired in as little as 7.5 min with the acceleration factor of 9. Reconstruction quality was consistent with the phantom results.
Compared to single contrast reconstruction with GRAPPA, APIR4EMC reduces artifacts and noise amplification in accelerated multi-contrast imaging.
通过提出的 Autocalibrated Parallel Imaging Reconstruction for Extended Multi-Contrast Imaging（APIR4EMC），提高多对比度成像的图像质量。
APIR4EMC 通过将对比度添加为虚拟线圈，在自动校准并行成像重建框架中重建多对比度图像。对不同对比度的回波链信号演化进行补偿，以改善缺失样本的信号预测。作为概念验证，我们对 T1、T1 脂肪饱和（Fatsat）、T2、PD 和 FLAIR 对比度的前瞻性加速体模和体内脑采集进行了前瞻性加速。这些采集的 k 空间采样模式被联合优化。使用所提出的 APIR4EMC 方法以及单独的 GRAPPA 对图像进行联合重建。在体模实验中，对两种方法的全采样参考图像和 g 因子图进行了均方根误差（RMSE）计算。在体内实验中进行了视觉评估。
与 GRAPPA 相比，APIR4EMC 减少了体模采集重建图像中的伪影并提高了 SNR。在定量方面，APIR4EMC 与 GRAPPA 相比，显著降低了噪声放大（g 因子）和 RMSE。信号演化补偿减少了伪影。在体内实验中，使用加速因子 9 在 7.5 分钟内采集了具有 T1、T1-Fatsat、T2、PD 和 FLAIR 对比度的 1 毫米各向同性 3D 图像。重建质量与体模结果一致。
与 GRAPPA 进行单对比度重建相比，APIR4EMC 可减少加速多对比度成像中的伪影和噪声放大。
