{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Qiu Z"],"funding":["Medical Research Council","Siemens Healthineers","NCI NIH HHS","NINDS NIH HHS","National Institutes of Health","NIH HHS","NIGMS NIH HHS"],"pagination":["1978-1993"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC10950540"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["91(5)"],"pubmed_abstract":["<h4>Purpose</h4>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.<h4>Methods</h4>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.<h4>Results</h4>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.<h4>Conclusion</h4>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."],"journal":["Magnetic resonance in medicine"],"pubmed_title":["Self-calibrated subspace reconstruction for multidimensional MR fingerprinting for simultaneous relaxation and diffusion quantification."],"pmcid":["PMC10950540"],"funding_grant_id":["R01 NS109439","T32 GM007250","MR/W031566/1","R01 CA269604","R01 CA282516"],"pubmed_authors":["Qiu Z","Hu S","Jones DK","Griswold MA","Sakaie K","Zhao W","Sun JEP","Ma D"],"additional_accession":[]},"is_claimable":false,"name":"Self-calibrated subspace reconstruction for multidimensional MR fingerprinting for simultaneous relaxation and diffusion quantification.","description":"<h4>Purpose</h4>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.<h4>Methods</h4>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.<h4>Results</h4>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.<h4>Conclusion</h4>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.","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 May","modification":"2025-07-12T03:04:33.928Z","creation":"2025-07-12T03:04:33.928Z"},"accession":"S-EPMC10950540","cross_references":{"pubmed":["38102776"],"doi":["10.1002/mrm.29969"]}}