Document Type
Article
Publication Date
12-15-2023
Abstract
Purpose: 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. Methods: 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. Results: 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. Conclusion: 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.
Keywords
diffusion MRI, low-rank matrix completion, low-rank subspace reconstruction, mr fingerprinting, time-resolved image reconstruction
Language
English
Publication Title
Magnetic Resonance in Medicine
Grant
R01 CA269604
Rights
© 2023 The Authors. This is an Open Access work distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Recommended Citation
Qiu Z, Hu S, Zhao W, et al. Self-calibrated subspace reconstruction for multidimensional MR fingerprinting for simultaneous relaxation and diffusion quantification. Magn Reson Med. 2024; 91: 1978-1993. doi: 10.1002/mrm.29969
Manuscript Version
Final Publisher Version