Rüdiger Stirnberg^{1}, Yiming Dong^{1}, Jonas Bause^{2,3}, Philipp Ehses^{1}, and Tony Stöcker^{1,4}

We propose a novel Inversion-Recovery Look-Locker 3D-EPI sequence for rapid T_{1} mapping. The inherent SNR benefit of a 3D acquisition, segmentation along both phase encode directions and a turbofactor introduced to reduce the number of required inversions can be traded freely for acquisition speed, SNR, resolution and geometric distortions. Aside from quantitative validation, two high-resolution T_{1} mapping applications are demonstrated at 7T: whole-brain with minimal distortions, and reduced field-of-view with geometric distortions matched to corresponding fMRI data. The results show high T_{1} accuracy for several turbofactor and flip angle combinations compared to a single-slice inversion-recovery 2D-EPI reference.

Accurate $$$T_1$$$ maps can be computed from multiple inversion
time (TI) images
acquired along the actual ($$$T_1$$$) or effective
($$$T_1^\ast$$$) inversion
recovery (IR) curve. Compared to slice-selective approaches, 3D acquisitions do
not suffer from slice-profile effects and inherently provide more SNR at high
resolutions. Tailored at high SNR efficiency^{1}, we propose a novel
Inversion-Recovery Look-Locker^{2} 3D-EPI^{3} (IR-LL-3D-EPI)
sequence with adaptable EPI- and turbofactor. Driving this sequence in a
steady-state mode, we show that high $$$T_1$$$ accuracy can be obtained at 7T in short scan
times with minimal geometric distortions. Alternatively, data can be acquired
in an fMRI-distortion-matched space^{4}.

A custom 3D-EPI sequence segmented
along both phase encode directions (PE1=blip/PE2=slab direction)^{5}
was modified to play out TR-FOCI inversion pulses^{6} according to the
loop order depicted in Fig. 1A. Avoiding additional recovery periods, a
steady-state Look-Locker signal^{1,7} is assumed (Fig. 1B). Per
default, the same $$$k$$$-space
trajectory is acquired $$$N$$$ times across the IR curve for $$$N$$$ different IR contrasts. A turbofactor, $$$TF\geq 1$$$, is
introduced to acquire as many PE2 indices per inversion as fit into the desired
TI spacing, $$$\Delta TI=TF\cdot TR$$$. Thus, only $$$s\cdot\lceil N_{PE2}/TF\rceil$$$ inversions are required, where $$$s\geq 1$$$ denotes the number of PE1-segments to reduce
the EPI-factor (and therefore distortions). The $$$N_{PE2}$$$ PE2 indices are looped linearly
according to TF such that the signal envelope is as smooth as
possible and non-periodic. The effective TI of the $$$n$$$th image is
given by $$$TI_n = n\Delta TI +TR\cdot(TF-1)/2$$$, where $$$n=0,\dots,N-1$$$.

Three experiments were conducted with one subject with informed consent and approval by the local ethics committee on a 7T research scanner (Siemens Healthineers) using a 32/1(Rx/Tx)-channel coil (Nova Medical):

- Low-resolution whole-brain (axial, 2mm isotropic, matrix=$$$96\times 96\times 72$$$, s=4, TE/TR=4ms/9ms) repeated with varying nominal flip angle (FA) and varying TF ($$$N\cdot TF=420=\text{const}$$$).
- High-resolution whole-brain (axial, 1mm isotropic, matrix=$$$192\times 192\times 144$$$, s=9, TE/TR=5.5ms/13ms, FA=$$$5^\circ$$$) repeated with varying TF.
- High-resolution fMRI (1mm isotropic 3D-EPI, coronal slab across occipital lobe, matrix=$$$192\times 192\times 60$$$, PE1 partial Fourier 6/8, s=1, TE/TR
_{vol}=22ms/3.4s, FA=$$$15^\circ$$$, PE1=left-right) and IR-LL-3D-EPI with identical resolution and distortions (TE/TR=19ms/55ms, FA=$$$12^\circ$$$, s=1, TF=1, TA=3:50min). A flickering checkerboard stimulus was presented during the 6min fMRI scan (repeating 16.5s off- and on-intervals). FMRI analysis was performed using FSL's^{8}FEAT.

All 3D-EPI scans used GRAPPA $$$R=3\times 1$$$. A 3DREAM^{9} B1 map was acquired for FA correction (2mm
isotropic, matrix=$$$96\times 96\times 72$$$,
segmentation=8, TA=1:10min). As a reference, a single-slice IR-2D-EPI sequence was
acquired (2mm isotropic, 10s recovery period, 11 linearly
increasing TIs between 120 and 2200ms, 5 exponentially increasing TIs up to 6000ms).

At ultra-high fields, a three-parameter $$$T_1$$$ fit may be preferable over assuming a fixed inversion efficiency (e.g. MP2RAGE^{10} $$$T_1$$$ estimation). Therefore, the IR-LL-3D-EPI data was fit to

$$S(TI) = S_\infty[1-(1+E)\cdot\exp(-TI/T_1^{\ast})]$$

using non-linear least squares following phase-based correction of the magnitude sign. Here, $$$E$$$ denotes the inversion efficiency and $$$S_\infty$$$ is the steady-state signal. $$$T_1$$$ was then calculated using

$$T_1=[1/T_1^{\ast}+\ln(\cos(\gamma FA))/TR]^{-1}\quad ,$$

where the FA scaling factor, $$$\gamma$$$, was obtained from the 3DREAM B1 map interpolated to the target 3D-EPI (affine-based using FSL's FLIRT) and smoothed by a 8mm gaussian filter. Common regions-of-interest (ROI) were defined as the intersection of all WM/GM/CSF ROIs obtained by tissue segmentation (FSL's FAST applied on all $$$T_1$$$ maps).

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