Retrospective rigid motion correction of three‐dimensional magnetic resonance fingerprinting of the human brain

Abstract

Purpose To obtain three‐dimensional (3D), quantitative and motion‐robust imaging with magnetic resonance fingerprinting (MRF). Methods Our acquisition is based on a 3D spiral projection k‐space scheme. We compared different orderings of trajectory interleaves in terms of rigid motion‐correction robustness. In all tested orderings, we considered the whole dataset as a sum of 56 segments of 7‐s duration, acquired sequentially with the same flip angle schedule. We performed a separate image reconstruction for each segment, producing whole‐brain navigators that were aligned to the first segment using normalized correlation. The estimated rigid motion was used to correct the k‐space data, and the aligned data were matched with the dictionary to obtain motion‐corrected maps. Results A significant improvement on the motion‐affected maps after motion correction is evident with the suppression of motion artifacts. Correlation with the motionless baseline improved by 20% on average for both T1 and T2 estimations after motion correction. In addition, the average motion‐induced quantification bias of 70 ms for T1 and 18 ms for T2 values was reduced to 12 ms and 6 ms, respectively, improving the reliability of quantitative estimations. Conclusion We established a method that allows correcting 3D rigid motion on a 7‐s timescale during the reconstruction of MRF data using self‐navigators, improving the image quality and the quantification robustness.

Whole brain 3D MR fingerprinting in multiple sclerosis: a pilot study

“…The details of MRF have been described previously [ 13 ] and involve the repeated acquisition of image data over a time course in which acquisition parameters such as the flip angle, pulse repetition rate (TR) and echo time (TE) are intentionally modified [ 13 ]. Because the resultant time evolution of the signal in a given voxel is unique for a certain combination of tissue MR properties such as PD, T 1 and T 2 , MRF derived estimates of these parameters are generated by comparing the signal evolution history of a given voxel to a dictionary of pre-simulated signal evolutions [ 14 ].…”

Whole Brain 3D MR Fingerprinting in Multiple Sclerosis: A Pilot Investigation

“…The ip angle ramped schedule ranged from 0.778 to 70 degrees. Sequence details can be found in (15) and (19). The acquisition FOV was 25.6 x 25.6 x 25.6 cm 3 with 1 mm isotropic voxel resolution.…”

“…The details of MRF have been described previously (13) and involve the repeated acquisition of image data over a time course in which acquisition parameters such as the ip angle, pulse repetition rate (TR) and echo time (TE) are intentionally modi ed (14). Because the resultant time evolution of the signal in a given voxel is unique for a certain combination of tissue MR properties such as PD, T 1 and T 2 , MRF derived estimates of these parameters are generated by comparing the signal evolution history of a given voxel to a dictionary of pre-simulated signal evolutions (15).…”

Whole-brain 3D MR fingerprinting brain imaging: clinical validation and feasibility to patients with meningioma

“…Magnetic resonance fingerprinting (MRF) is a novel MR acquisition method for quantitative assessment of tissue magnetic properties such as T 1 , T 2 and proton density [1][2][3]. Introduced in 2013, MRF involves acquiring either a two or three-dimensional dataset typically using non-Cartesian k-space encoding sampling scheme such as a spiral trajectory [2,4,5]. Unlike conventional acquisitions which commonly require establishment of a steady state of the magnetization before spatial encoding, a MRF pulse sequence modifies acquisition parameters, including the radiofrequency flip angle, the pulse repetition rate (TR) and echo time (TE), over a time interval while continuously acquiring data [6][7][8].…”

“…In addition, slice selective 2D-MRF has been proposed for differentiating intra-parenchymal brain tumors, such as: high-grade gliomas [23,24] (World Health Organization grades III and IV), low-grade gliomas [23,24] (World Health Organization grades I and II) and metastases [23]. Given the mentioned investigations in neuroimaging [22][23][24] studied only selected 2D-MRF slices of the brain, 3D-MRF has been proposed [5,[25][26][27] to allow a fast whole-brain coverage in a Radiation Oncology setting [25] and in patients with Parkinson Disease [28]. These studies [25,28] demonstrated that a fast entire brain coverage was feasible with high resolution, pointing a major advantage of a 3D-MRF acquisition for clinical applications.…”