Qiu Zhilang, Hu Siyuan, Zhao Walter, Sakaie Ken, Sun Jessie E P, Griswold Mark A, Jones Derek K, Ma Dan
Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.
Imaging Institute, Cleveland Clinic, Cleveland, Ohio, USA.
Magn Reson Med. 2024 May;91(5):1978-1993. doi: 10.1002/mrm.29969. Epub 2023 Dec 15.
To propose a new reconstruction method for multidimensional MR fingerprinting (mdMRF) to address shading artifacts caused by physiological motion-induced measurement errors without navigating or gating.
The proposed method comprises two procedures: self-calibration and subspace reconstruction. The first procedure (self-calibration) applies temporally local matrix completion to reconstruct low-resolution images from a subset of under-sampled data extracted from the k-space center. The second procedure (subspace reconstruction) utilizes temporally global subspace reconstruction with pre-estimated temporal subspace from low-resolution images to reconstruct aliasing-free, high-resolution, and time-resolved images. After reconstruction, a customized outlier detection algorithm was employed to automatically detect and remove images corrupted by measurement errors. Feasibility, robustness, and scan efficiency were evaluated through in vivo human brain imaging experiments.
The proposed method successfully reconstructed aliasing-free, high-resolution, and time-resolved images, where the measurement errors were accurately represented. The corrupted images were automatically and robustly detected and removed. Artifact-free T1, T2, and ADC maps were generated simultaneously. The proposed reconstruction method demonstrated robustness across different scanners, parameter settings, and subjects. A high scan efficiency of less than 20 s per slice has been achieved.
The proposed reconstruction method can effectively alleviate shading artifacts caused by physiological motion-induced measurement errors. It enables simultaneous and artifact-free quantification of T1, T2, and ADC using mdMRF scans without prospective gating, with robustness and high scan efficiency.
提出一种用于多维磁共振指纹成像（mdMRF）的新重建方法，以解决由生理运动引起的测量误差导致的阴影伪影，而无需导航或门控。
所提出的方法包括两个步骤：自校准和子空间重建。第一步（自校准）应用时间局部矩阵补全，从从k空间中心提取的欠采样数据子集中重建低分辨率图像。第二步（子空间重建）利用从低分辨率图像中预先估计的时间子空间进行时间全局子空间重建，以重建无混叠、高分辨率和时间分辨的图像。重建后，采用定制的离群值检测算法自动检测并去除因测量误差而损坏的图像。通过体内人脑成像实验评估了可行性、鲁棒性和扫描效率。
所提出的方法成功重建了无混叠、高分辨率和时间分辨的图像，其中准确表示了测量误差。自动且稳健地检测并去除了损坏的图像。同时生成了无伪影的T1、T2和ADC图。所提出的重建方法在不同的扫描仪、参数设置和受试者之间表现出鲁棒性。实现了每切片少于20秒的高扫描效率。
所提出的重建方法可以有效减轻由生理运动引起的测量误差导致的阴影伪影。它能够在无前瞻性门控的情况下，使用mdMRF扫描同时对T1、T2和ADC进行无伪影定量，具有鲁棒性和高扫描效率。
