Three-dimensional simultaneous brain mapping of T1, T2, [Formula: see text] and magnetic susceptibility with MR Multitasking - PubMed (original) (raw)
. 2022 Mar;87(3):1375-1389.
doi: 10.1002/mrm.29059. Epub 2021 Oct 27.
Sen Ma 1, Nan Wang 1, Sara Gharabaghi 3, Yibin Xie 1, Zhaoyang Fan 1 4, Elliot Hogg 5, Chaowei Wu 1 2, Fei Han 6, Michele Tagliati 5, E Mark Haacke 3 7 8, Anthony G Christodoulou 1 2, Debiao Li 1 2
Affiliations
- PMID: 34708438
- PMCID: PMC8776611
- DOI: 10.1002/mrm.29059
Three-dimensional simultaneous brain mapping of T1, T2, T2∗ and magnetic susceptibility with MR Multitasking
Tianle Cao et al. Magn Reson Med. 2022 Mar.
Abstract
Purpose: To develop a new technique that enables simultaneous quantification of whole-brain T1 , T2 , T2∗ , as well as susceptibility and synthesis of six contrast-weighted images in a single 9.1-minute scan.
Methods: The technique uses hybrid T2 -prepared inversion-recovery pulse modules and multi-echo gradient-echo readouts to collect k-space data with various T1, T2, and T2∗ weightings. The underlying image is represented as a six-dimensional low-rank tensor consisting of three spatial dimensions and three temporal dimensions corresponding to T1 recovery, T2 decay, and multi-echo behaviors, respectively. Multiparametric maps were fitted from reconstructed image series. The proposed method was validated on phantoms and healthy volunteers, by comparing quantitative measurements against corresponding reference methods. The feasibility of generating six contrast-weighted images was also examined.
Results: High quality, co-registered T1 , T2 , and T2∗ susceptibility maps were generated that closely resembled the reference maps. Phantom measurements showed substantial consistency (R2 > 0.98) with the reference measurements. Despite the significant differences of T1 (p < .001), T2 (p = .002), and T2∗ (p = 0.008) between our method and the references for in vivo studies, excellent agreement was achieved with all intraclass correlation coefficients greater than 0.75. No significant difference was found for susceptibility (p = .900). The framework is also capable of synthesizing six contrast-weighted images.
Conclusion: The MR Multitasking-based 3D brain mapping of T1 , T2 , T2∗ , and susceptibility agrees well with the reference and is a promising technique for multicontrast and quantitative imaging.
Keywords: MR Multitasking; MR studies; brain; multiparametric mapping; quantitative MRI.
© 2021 International Society for Magnetic Resonance in Medicine.
Figures
Figure 1.
(A) Sequence diagram for the proposed multitasking T1/T2/T2* mapping framework. Hybrid T2prep/IR (T2-IR) preparation modules were followed by 144 multi-echo GRE readouts, which enable collection of k-space lines with different T1/T2/T2* contrasts. The training data was acquired every 4 readouts. (B) Illustration of readout module. After each α pulse, a total of 3 echoes, each of them fully flow compensated along all directions, were collected in a monopolar way. In the readout direction, each echo is refocused, and flow compensation is naturally achieved at the center of each echo after inserting an appropriate moment nulling gradient before the first echo. In the phase/partition encoding direction, however, bipolar gradient pairs were added for all later echoes. (C) Simplified illustration of k-space sampling pattern. Cartesian acquisition with random Gaussian distribution was adopted along ky and kz axis. k-Space center was acquired every 4 readouts and would serve for tracking temporal dynamics.
Figure 2.
(A) Illustration of multiple temporal dimensions of the low-rank tensor for simultaneous T1, T2, T2*, and susceptibility mapping. The image tensor contains spatial, T2IR preparation duration τ, inversion time TI, echo time TE dimensions, with size [Nx ⋅ Ny ⋅ Nz, 4, 144, 3]. The low-rank tensor structure can be explicitly expressed through tensor factorization between 4 sets of basis functions (U with size [Nx ⋅ Ny ⋅ Nz, _L_], V with size [4, _M_], W with size [144, _N_], Q with size [3, _P_]) assigned to each dimension and a core tensor (G with size [L, M, N, _P_]) governing the interaction between different basis functions. (B) Reconstruction workflow. The reconstructed tensor is given by X^=Φ^×1U^.
Figure 3.
Comparison between Multitasking and references on a standard phantom. Multitasking shows comparable image quality and correlates well with the references, as denoted by R2 and ICC. The solid line represents identity (y = x), and the dotted line represents linear regression fitting.
Figure 4.
(A) Comparison of susceptibility map from Multitasking and references on a Gd phantom, with Gd concentration (in mmol/L) labelled for each tube in the magnitude image. (B) Multitasking susceptibility correlates well with the reference susceptibility, as denoted by R2 and ICC. The solid line represents identity (y = x), and the dotted line represents linear regression fitting. (C) Multitasking susceptibility correlates well with the Gd concentration and yields a slope of 0.338 ppm per mmol/L. The dotted line represents linear regression fitting.
Figure 5.
Representative in-vivo T1/T2/T2* mapping at three slice locations using MR Multitasking (MT) and the corresponding reference (Ref) protocols for a healthy volunteer. Multitasking provides T1/T2/T2* maps with good qualitative agreement with the references.
Figure 6.
Bland - Altman plots comparing Multitasking (A) T1, (B) T2, (C) T2*, and (D) susceptibility measurements with those of the references (N=10). The dotted lines represent 95% confidence level. The solid lines represent mean percentage differences.
Figure 7.
Representative in-vivo QSM at two slice locations using MR Multitasking (MT) and references (Ref) on the same healthy volunteer. Both QSM and SWI/ tSWI (MinIP) images agreed with the reference in terms of deep gray matter and vessel visualization.
Figure 8.
Results from a healthy volunteer including qualitative images and quantitative maps. The first row included quantitative maps and the second row showed all the weighted images. SWI and tSWI were MinIP results with an effective slab thickness of 16mm.
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