Use of self-navigation to enable efficient 3D DWI SE-EPI multislab multiband imaging
Steen Moeller1, Sudhir Ramanna1, Edward Auerbach1, Pramod Pisharady1, Christophe Lenglet1, Mehmet Akcakaya1,2, and Kamil Ugurbil1

1University of Minnesota, Minneapolis, MN, United States, 2Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN, United States


A method is proposed for self-navigation of DWI 3D multislab multiband SE-EPI, to enable whole brain high-resolution imaging, with optimal imaging TR for higher SNR efficiency. Data for high b-value (b=3k s/mm2) and 1mm3 resolution is presented.


The use of SMS/MB SE-EPI increases SNR per unit time for diffusion weighted MRI (dMRI), achieving near optimal TR’s for moderate resolutions (e.g. >1 mm isotropic) for whole brain coverage. For higher resolution imaging, however, the 2D accelerated approach is less SNR efficient than an optimized 3D approach because it leads to TR’s that are much longer than T1. The 3D approach enables imaging with the optimal TR (~1.2*T1 [1,2]), but requires multiple repetitions to fully encode the volume. For either a 2D or 3D segmented dMRI SE-EPI acquisition, the need for correcting for physiologically induced phase variations between segments, requires computational approaches for 2D [3,4] and/or additional measurements, such as 2D navigators for 3D [1,5] acquired after diffusion weighting. Such additional measurements reduce the efficiency of 3D approaches by 30-50% [1] and are SNR dependent.

In this work, we propose a self-navigated approach to correct modulations in kz-segmented 3D EPI, which enables an efficient real-time processing for integration into existing 3D reconstruction frameworks, and is suitable for high b-values/low SNR protocols. Use of self-navigation for removing macroscopic sensitivity to B0 induced phase variations from physiology [5] eliminates the need for 2D navigators, increasing efficiency. Additionally, we demonstrate a combination with SMS/MB using simultaneously excited multiple slabs (multislab-multiband) for large FOV coverage at optimal TRs. We use a SQUASHER-type encoding for introducing quadratic phase across the slab [6] - spreading the signal in kz - to estimate accurately the signals for self-navigation through kz. Additionally, with SQUASHER, the peak power is reduced enabling high bandwidth multiband which imparts significant advantages with respect to Fourier/sinc encoding.


Imaging: Diffusion‐weighted data were acquired on healthy volunteers using a 32‐channel receiver head-coil on 3T Prisma system (Siemens) equipped with 80 mT/m gradients with a slew rate of 200 T/m/s, using the following : MB1: Excitation/Refocusing = HS2R12/HS2R14, duration 7680us, 1mm3, TE/TR of 92.2/1610ms with 12slice/slab, 10 slabs, FOV 210x210x120 mm3, iPAT=2, Volume acquisition time (VAT)=26s (TR=9.5s for an equivalent 2D SMS/MB coverage with [MBxiPAT=2x2]) MB2: Excitation/Refocusing = HS2R10/HS2R12, duration 7680us, 1mm3, TE/TR of 92.4/1500ms with 10slice/slab, 16 slabs, FOV 210x210x160 mm3, iPAT=2, VAT= 21s (TR=12.5s for an equivalent 2D SMS/MB coverage with [MBxiPAT=2x2])). For 2D, the total acceleration is limited to less than 2x2 due to g-factors. For the prescribed whole brain FOV using MB1 the 3D sequence has a 300% longer VAT compared to a 2D SMS sequence, but the 3D sequence has 16 more averages. For the larger FOV the 3D MB2 acquisition has 70% longer VAT, and 14 more averages than the 2D acquisition. The excitation profiles were designed with 1 slice overlap, and acquisition is with 2 slice oversampling.

Self-navigated segmentation correction: For each kz-plane a relative phase reference map is calculated from an (uncorrupted) b=0 acquisition. A kz-dependent phase is calculated for b>0, and updated with a low-pass filtered difference relative to the reference phase, see flowdiagram in figure 1.

Image Analysis: Final images were generated with SENSE-1 combination [8]. These were subsequently processed with TOPUP, EDDY and bedpostX in FSL [9] and visualized with FSLeyes and Connectome Workbench [10].


The quadratic phase in SQUASHER spreads the signal in the kz direction (Figure 2A). b=0 images using SQUASHER and standard encoding with the Siemens default SE-EPI are shown in Figure 1B. The zoomed regions depict sharper band profiles with the higher bandwidth pulses in SQUASHER. The extracted physiological induced phase variations $$$\Phi_b(x,y,k_z)$$$ and the reference slab phase-variation $$$\Phi_{b=0}(x,y,k_z)$$$ are shown in Figure 3A,B for a representative slab. Representative image slices from a slab without and with the proposed self-navigation are depicted in Figure 3C,D for b=1500 s/mm2.

The reconstructed SQUASHER 3D SE-EPI images, with an axial orientation acquisition, before and after correction for slab discontinuity for b=0, 1500, 3000 s/mm2 images are shown in Figure 4 (row 1, 2 and 3 respectively, with sagittal (left) and coronal (right) orientation), including profile correction after the weighted-slab combined signal. The average correction for different b-values is plotted in Figure 4B, showing that a b-value dependent correction is preferred [5].

The extracted FA maps and fiber orientations results shown in Figure 5 have a high degree of similarity between the MB1 and MB2 data without any evidence of the common slab-boundary issues in the FA maps.


An efficient 3D SE-EPI Multislab-Multiband sequence and reconstruction method is proposed. They combine quadratic slab phase, self-navigated segmentation correction, and data-driven slab banding artifact removal. Results are demonstrated with raw images, FA maps, and MB accelerated volumetric acquisitions. High b-values were used to evaluate the utility of the method under challenging low-SNR conditions. SQUASHER shows increased image quality and better signal localization relative to the conventional vendor-optimized pulses.


U01 EB025144, P41 EB015894, P30 NS076408, 1S10OD017974-01, NIH R00HL111410


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Figure 1: Flow diagram of the reconstruction pipeline. The self-navigation is the phase update in steps, 3 and 4, with a hamming window filtered phase (see also figure 3b), where Cn are slab wise sensitivity profiles. The 1D whole volume correction applied at step 9, uses a smooth profile function for reference to update from [1]. Parallel Imaging reconstruction in ky is with GRAPPA using FLEET for ACS, and slice-GRAPPA with slice-blocking for SMS/MB unaliasing.

Figure 2 :A; The signal in the hybrid space [x,y,kz] for SQUASHER and the Siemens optimized sequence B: Image reconstruction for each slab and concatenated without removing oversampled slices. In the insert, the difference between a high bandwidth SQUASHER sequence and the Siemens optimized SE-EPI show the higher spatial specificity in areas with high ΔB0.

Figure 3: Physiological induced phase variation for b=1500 s/mm2 A: High-resolution reference phase pr. kz plane in a slab in [x,y,kz] space. B: Estimated low resolution phase variation pr. kz-plane estimated from the data itself. C: Reconstruction of slices in a slab without accounting for the physiological induced phase variation. D: Reconstruction of slices in a slab after accounting for the physiological induced phase variation

Figure 4: Removal of slab boundary effects. A: the progression of axial 3D slab images from Raw 3D images with over sampling, to profile averaged slabs, to 1D profile corrected volumes in both sagittal (left) and coronal view (right). The three rows are for b=0,1500,3000 s/mm2 respectively. B/ The average 1D profile for b=0,1500,3000 s/mm2 respectively. Each volume is corrected with it’s own profile which is close to the average for a given b-value.

Figure 5: Diffusion data were acquired with two shells (b=1500 and b=3000 s/mm2), with 36 diffusion encoding directions, and repeated with AP/PA phase encoding.Color coded fiber orientations modulated with FA (upper panels) and FA maps (middle panels) from DTI model fitting to MB1 (left panels) and MB2 (right panels) data. Lower panels show color coded multiple fiber orientations at high resolution, resolved by ball and stick partial volume model, at a region of interest highlighted in red in the middle panel. The background in lower panels is the sum of the estimated anisotropic fiber volume fractions.

Proc. Intl. Soc. Mag. Reson. Med. 27 (2019)