High-resolution distortion-free diffusion imaging using hybrid spin-warp and echo-planar PSF-encoding approach

Author’s Accepted Manuscript High-Resolution Distortion-Free Diffusion Imaging using Hybrid Spin-Warp and Echo-Planar PSFEncoding Approach Myung-Ho In, Oleg Posnansky, Oliver Speck www.elsevier.com

PII: DOI: Reference:

S1053-8119(17)30008-3 http://dx.doi.org/10.1016/j.neuroimage.2017.01.008 YNIMG13712

To appear in: NeuroImage Received date: 13 June 2016 Revised date: 9 December 2016 Accepted date: 4 January 2017 Cite this article as: Myung-Ho In, Oleg Posnansky and Oliver Speck, HighResolution Distortion-Free Diffusion Imaging using Hybrid Spin-Warp and Echo-Planar PSF-Encoding Approach, NeuroImage, http://dx.doi.org/10.1016/j.neuroimage.2017.01.008 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

High-Resolution Distortion-Free Diffusion Imaging using Hybrid Spin-Warp and Echo-Planar PSF-Encoding Approach Myung-Ho In1,2, Oleg Posnansky1, Oliver Speck1,3,4,5 1

Department of Biomedical Magnetic Resonance, Institute for Experimental Physics, Otto-von-Guericke

University Magdeburg, Germany 2

Department of Neurologic Surgery, Mayo Clinic, Rochester, MN, USA

3

German Centre for Neurodegenerative Diseases (DZNE), Site Magdeburg, Germany

4

Leibniz Institute for Neurobiology, Magdeburg, Germany

5

Center for Behavioral Brain Sciences, Magdeburg, Germany



Corresponding author at: Myung-Ho In, Ph.D. Department of Biomedical Magnetic Resonance, Institute

for Experimental Physics, Otto-von-Guericke University Magdeburg, Germany Leipziger Strasse 44, 39120 Magdeburg, Germany Tel.: +49 391 6117 124; fax: +49 391 6117 115. [email protected]

1

Abstract High-resolution diffusion-weighted imaging (DWI) has great potential to provide unique information about tissue microstructure in-vivo. Although single-shot echo-planar imaging (EPI) is a most popular tool for DWI, its application for high-resolution DWI is limited due to T2* blurring and susceptibilityand eddy-current-induced geometric distortions, especially at ultra-high field (UHF) such as 7T. In this study, we adapt a hybrid spin-warp and echo-planar encoding strategy inspired by point spread function (PSF) mapping and optimize it for high-resolution and distortion-free diffusion imaging applications. More specifically, a 2D navigator echo is added into the original sequence for shot-to-shot motioninduced phase error estimation and correction. The spatial encoding is shared between the PSF and the EPI phase encoding dimension allowing short echo trains to preserve the diffusion and navigator signals efficiently at UHF, where T2 decay is relatively fast. In addition, variable k-space spacing was applied in the PSF dimension and combined with parallel imaging in the EPI-PE dimension to further accelerate the PSF acquisition. The results demonstrate that this method can yield isotropic submillimeter resolution without T2* blurring and geometric distortions at 7T and enables a clear and detailed delineation of human brain structures in-vivo with the diffusion contrasts. In addition, results of the proposed approach for high-resolution diffusion imaging at 3T are presented.

Keywords diffusion imaging, point spread function, high resolution, ultra-high field, diffusion-weighted image

Introduction Diffusion-weighted imaging (DWI) (Le Bihan and Breton, 1985; Merboldt et al., 1985; Taylor and Bushell, 1985) and its advanced applications such as diffusion tensor imaging (DTI) (Basser et al., 1994) provide unique information about tissue microstructure in-vivo. However, DWI still faces limitations in increasing the spatial resolution with single-shot echo planar imaging (EPI), which is the most popular sequence for DWI. Although DWI acquisition at ultra-high field (UHF) can potentially achieve high spatial resolution due to an improved sensitivity of signal detection, long echo time (TE) is required for diffusion encoding and faster T2 relaxation counteracts the signal gain at UHF (Heidemann et al., 2010). Thus, it is still difficult to reach sub-millimeter resolution using single-shot EPI-based DWI. In addition, severe T2* blurring and susceptibility- and eddy-current-induced geometric distortions along the phaseencoding (PE) direction cause a loss of intrinsic spatial resolution in the acquired image, especially at 2

UHF. Currently, DWI is commonly restricted to the investigation of white matter structures due to limited resolution and sensitivity. As alternative techniques to standard single-shot EPI, several multi-shot EPI approaches including readout-segmented (Holdsworth et al., 2008; Porter and Heidemann, 2009), interleaved (Jeong et al., 2013), and PROPELLER EPI (Wang et al., 2005) have been proposed to mitigate aforementioned problems and to achieve higher spatial resolution. In these techniques, only a portion of k-space is filled within a single-shot and multiple-shots are required to fill entire k-space. Since a shorter (effective) echospacing leading to higher bandwidth in the PE direction can be achieved with an increased number of shots, the strength of susceptibility- and eddy-current-induced distortions is reduced accordingly. Nevertheless, these approaches are not free from susceptibility- and eddy-current-induced geometric distortions and T2* blurring effects. Therefore, careful attention to remedy these problems is still required in these approaches. In this study, as a variant of multi-shot EPI, a hybrid approach is adapted and optimized for very highresolution distortion-free diffusion imaging. The proposed acquisition and processing scheme is based on the point spread function (PSF) mapping approach (Robson et al., 1997; Zaitsev et al., 2004; Chung et al., 2011; In and Speck, 2012) that was previously applied as calibration to correct geometric distortions of consecutive acquisitions. In the proposed method, the PSF-measurement itself is diffusion weighted. Due to the multi-shot nature of PSF mapping (similar to 3D acquisitions), signal is effectively averaged in addition to encoding spatial distortions, which can enable sufficient SNR in very high spatial resolution diffusion imaging that otherwise may require averaging and thus similar scan times. In contrast to other multi-shot EPI approaches (Holdsworth et al., 2008; Porter and Heidemann, 2009; Jeong et al., 2013), this novel approach enables DWI free from susceptibility- and eddy-current-induced geometric distortions and T2* blurring, which can be calculated by an integral of the 3D PSF data along the distorted coordinate. In this work, acquisition of a 2D navigator echo is added into the PSF sequence to correct motion-induced phase perturbations between shots. To demonstrate the efficiency in achieving high-resolution diffusion data the proposed method was performed not only at 7T, but also at 3T.

Material and Methods

3

Figure 1. A PSF-based diffusion-weighted sequence diagram with navigator echo (A), corresponding reconstructed 3D PSF data (B), and zoomed 2D PSF image planes I(s,y) of the region with field inhomogeneity appearing as deviations of the PSFs ∆B(s) from the diagonal line (C). Note that PSF phase-encoded and corresponding rewinder gradients are applied before and after the PSF phaseencoded acquisition (see red arrows in A) Distortion-free image reconstruction from the 3D PSF data In the PSF mapping sequence, a conventional spin-warp (referred to here as PSF) PE gradient is added to the PE direction of a 2D EPI sequence, which results in 3D k-space data consisting of readout (kx), EPIPE (ky), and PSF-PE (ks) dimensions (Robson et al., 1997) (Fig. 1A). The two PE gradients encode the same spatial dimension and the reconstructed PSFs are represented along the correlation (or diagonal) line in the PSF- (s) and EPI-PE coordinates (y) after 3D inverse Fourier transformation (iFT) of the 3D kspace data. Since a very high pixel bandwidth (>1KHz) is commonly used during the readout acquisition and the conventional spin-warp (or PSF) PE can be considered as a distortion-free dimension, distortions in the EPI readout (x), EPI-PE (y), and PSF-PE coordinates (s) of the reconstructed 3D data are assumed to be negligible, severe, and absent, respectively. Since it is reasonable to assume that the EPI readout dimension (x) is independent of the two PE dimensions (y and s) and the distortion in readout dimension 4

is negligible, the reconstructed PSF data can be simplified as (Robson et al., 1997; Zaitsev et al., 2004; Chung et al., 2011; In and Speck, 2012): (

)

( ) (

),

(1)

where (

)

( ))

(

∫

(

( ))

(2)

is the PSF, M(y) is a function of blurring representing the spatial shift and broadening effects of T2/T2* relaxation, eddy-currents, and field inhomogeneity within the EPI readout acquisition window, and ∆B(s) is the shift of the PSF caused by field inhomogeneity-induced geometric distortion (see Figs. 1B and 1C). When ky is equal to zero, Eq. 1 simply becomes a spin-echo image I(s), which is free of T2* blurring and off-resonance effects. Therefore, integration of the PSF data I(s,y) along the distortion-free dimension (s) or the distorted dimension (y) yields a distorted I(y) or distortion-free image I(s), respectively: ( )

∫ (

)

( )

∫ (

)

,

(3) (4)

where y (EPI-PE) and s (PSF-PE) represent coordinates in image space, respectively. Note that when ∆B(s) is zero (i.e. H(s,y) = M(s-y)), the original PSF-mapping approach (Eq. 3) yields a geometric distortionfree, but not T2* blurring-free image. While spin echo imaging generally compensates field inhomogeneity effects by the refocusing radio frequency (RF) pulse, spin-echo EPI still suffers from field inhomogeneities along the long readout echo train. Therefore, integration of the complex 3D PSF data causes intra-voxel dephasing effects and results in an image with lower SNR. To minimize the effects, the integration of Eqs. 3 and 4 is performed based on the magnitude PSF data: ( )

√∫ (

)

(

)

(5)

( )

√∫ (

)

(

)

(6)

where * indicates complex conjugate and become the sum-of-square method. PSF mapping combined with a 2D navigator echo. In general, multi-shot EPI approaches suffer from shot-to-shot motion-related phase errors induced by strong diffusion gradients resulting in ghost artifacts in the reconstructed image. The same problem 5

appears in the proposed distortion-free image due to the multi-shot nature of the PSF sequence. To avoid this problem, a 2D navigator echo covering the center of k-space is acquired after each PSF phaseencoded 2D acquisition (Fig. 1A). Since a rewinder gradient for PSF-PE is added before the navigator echo acquisition, the navigator echoes cover identical k-space portions in all shots (see red arrows in Fig. 1A). In addition, the navigator echo is acquired without refocusing (180°) RF pulse to reduce specific absorption rate (SAR), which otherwise requires prolonged TR at UHF. When the PSF-PE gradient moment ∆ks is zero, this sequence acquires multi-echo (i.e. two) EPI images with identical echo spacing and resolution, but at different TE.

Figure 2. PSF acquisitions with full sampling (A), rFOV=2 (B), rFOV=5 (C), both rFOV=5 and GRAPPA in ky=3 (D), rR=2 (E), and all of rR=2, rFOV=5, and GRAPPA in ky=3 (F). The sampling schemes in the two phase encoding dimensions ks and ky, corresponding reconstructed images, and simple PSF unfolding along the distortion-free coordinate (s) when rFOV>1 are illustrated in (a), (b), and (c), respectively. In (b), the reconstructed 2D PSF near the center in x direction I(s,y), distorted I(y), and distortion-free images I(s) are shown. While both image FOV and matrix size of the distortion-free coordinate (s) are reduced by rFOV (B-D), only the matrix size of the distorted coordinate (y) is reduced by rR and the image blurring rather than image FOV reduction is caused by rR (E and F). A simple PSF unfolding cannot resolve aliasing artifacts when the remaining FOV is smaller than the maximum deviations (i.e. distortions) of PSF (C-c). If a GRAPPA factor of 3 is used in ky, the distortion strength is reduced, which results in aliasing-free PSF data even with rFOV=5 (D-c). When both rFOV and rR are used, image interpolation is performed along the distorted coordinate (y) before PSF unfolding in order to apply identical PSF unfolding as to the PSF data without rR (F-c). In D-b and F-b, the reconstructed images after GRAPPA reconstruction (red dots in D-a and F-a) are shown. PSF acceleration with a reduced field of view (rFOV) in the PSF-PE dimension. The proposed 2D PE scheme can be viewed as shared spatial encoding between the EPI-PE and the 6

PSF-PE coordinates. Due to the sparsity of the PSF data aligned along the diagonal direction in the 2D PE space, a rFOV in the PSF-PE dimension can be utilized as sub-sampling approach for the accelerated PSF acquisition resulting in folding of the 2D PE image along the PSF-PE direction. However, the PSF data can be unfolded without aliasing artifacts until half of the remaining FOV is bigger than the maximum deviation ∆B(s) (i.e. distortion) of the PSF from the diagonal line (Zaitsev et al., 2004) (Fig. 2B). Thus, the PE resolution of the distorted coordinate (y) is required to fully unfold the PSF data acquired with rFOV accelerations in the proposed approach, which results in a distortion-free image I(s) without aliasing artifacts. Reduced resolution (rR) combined with parallel imaging in the EPI-PE dimension. Note that the EPI-PE and PSF-PE dimension have identical resolution when the rR factor is equal to 1. As shown in Eq. 6 and Fig. 1, the PE resolution of the final distortion-free image is determined only by that of the distortion-free coordinate (s). Since blurring rather than folding of the PSF is caused by the resolution reduction and appears only along the EPI-PE direction, this effect is not present in the final distortion-free image (see Figs. 2B and 2D). By applying a reduced resolution in the EPI-PE direction the echo time (TE) can be minimized. This allows higher signal of the PSF phase-encoded as well as the navigator echo acquisition data even at UHF, where T2 is relatively short. In addition, more slices within a given repetition time (TR) can be measured. Note that an identical rR factor is applied to both the PSF phase-encoded and the navigator echo acquisitions in order to match the resolution, matrix size, and distortion strength in both images, which is particularly important for robust 2D phase correction. Instead of high acceleration in the PSF-PE dimension (Zaitsev et al., 2004), parallel imaging (Griswold et al., 2002) with a high acceleration factor of 3 is additionally applied in the EPI-PE dimension. If either the maximum off-resonance frequency ∆B(s)fmax or the maximum pixel deviation ∆B(s)pmax of the image slice is known or assumed, the maximum rFOV factor available for the corresponding PSF scan can be estimated by:

|

( )

|

|

( )

|

,

(7)

where Ns, ∆tesp, and AF are the image matrix of the distortion-free target image in the PE direction, echo spacing, and parallel imaging factor in the EPI-PE dimension, respectively. For example, if the target image matrix size in the PE direction is 160 and the maximum distortion is 22 pixels, a maximum rFOV factor of up to 3 can be applied. Otherwise, aliasing artifacts occur in the final distortion-free image (Fig. 2C). The application of parallel imaging enables shorter (effective) echo-spacing leading to higher bandwidth and thus reduced distortion (i.e. deviation of the PSF ∆B(s)) in the corresponding EPI-PE direction (Figs. 2D and 2F). Thus, further FOV reduction in the PSF-PE dimension is possible without 7

aliasing of the PSF, which results in further accelerated PSF acquisition. Due to a substantial overlap between the segments of the PSF acquisition, this can also be viewed as a mutli-shot segmented acquisition with overlapping segments in the PE direction. In particular, the acquisition with a substantial resolution reduction factor becomes very similar to segmented spin-warp acquisition. However, the proposed technique allows for a substantial overlap between the segments and applies image reconstruction inspired by the PSF mapping approach to further improve the image quality and SNR. The readout-segmented k-space acquisition approaches (Holdsworth et al., 2008; Porter and Heidemann, 2009) also exploit k-space overlap between the segments, however, in the readout direction and still suffer from susceptibility-induced geometric distortions in the PE direction. In contrast to the 3D k-space data of the proposed approach, furthermore, a 2D k-space is finally filled with the segmented data to yield an image in the readout-segmented approaches.” Experiments Phantom and in-vivo scans were performed on a 7T whole body system (Siemens Healthcare, Erlangen, Germany) with a maximum gradient strength of 70 mT/m and slew rate of 200 T/m/s using a 32-channel head coil (Nova Medical, Wilmington MA, USA). The Stejskal-Tanner diffusion encoding scheme was adopted instead of an eddy-current compensated double-echo scheme for the use of a minimized echotime (TE) enabling a higher signal to noise ratio (SNR) efficiency in the acquisition. Due to higher SAR at 7T, longer excitation (5120 µs) and refocusing RF pulses (10240 µs) were used. All PSF scans were carried out without and with diffusion gradients. For each PSF scan, an acceleration factor of 5 was achieved by rFOV in the PSF-PE dimension afforded by the use of a GRAPPA factor of 3 in the EPI-PE dimension providing an acceptable g-factor penalty. When an echo-spacing time of 1090 µs, a GRAPPA factor of 3, and a matrix size of 320 in the PE direction were chosen as the EPI acquisition parameters, distortions of up to 29.1 pixel shifts occur for the maximum off-resonance frequency of 250 (Hz) at 7T. Thus, a maximum rFOV factor of 5 (covering ±275 Hz as off-resonance frequency) is estimated by Eq. 7. In addition, a rR factor of 4 resulting in a four times shorter readout echo train in the EPI-PE dimension (ky, Fig. 2E) was applied to achieve short TE and thus high signal of the PSF-encoded (TE1 in Table 1) and navigator acquisition (TE2 in Table 1), which enabled to use a minimum TE1 between 50 and 60 ms and TE2 less than 100 ms, respectively. No cardiac gating was applied. The detailed imaging protocols are listed in Table 1. Anatomical images with 0.6 mm isotropic resolution including 3D gradient-echo (GE) and MPRAGE were measured as geometrically correct reference and compared with the reconstructed distortion-free image with 0.8 mm isotropic resolution calculated from the 3D PSF data. Since spin-warp PE was used in both (i.e. PE and slice-PE) directions of the axial slice for the 3D anatomical imaging, the anatomical images can be assumed to be distortion-free. The imaging protocols for the anatomical imaging were 8

TR(MPRAGE)/TR(GE)/TI(MPRAGE)/TE = 2500/1710/1050/1.51 ms, flip angle = 5°, readout bandwidth = 723 Hz/px, matrix size [x, y, z] = 384×384×352. A phantom experiment was carried out using a home-made spherical geometry phantom to test the fidelity of distortion-correction. Since there is no motion in the phantom, 2D navigator data were not acquired. For human experiments, five healthy subjects were scanned after institutional review boardapproved written consent. To evaluate the efficiency of the proposed method in achieving high-resolution diffusion data at more common field strength, in-vivo experiments were additionally performed on a 3T Skyra (40 mT/m) and a Prisma (80 mT/m) scanner (Siemens Healthcare, Erlangen, Germany) using product 32 and 64 channel head coils, respectively. A comparison study was performed to demonstrate the effectiveness of the proposed method in yielding very high-resolution data without susceptibility-induced distortions at 7T. Using a readoutsegmented EPI approach (Porter and Heidemann, 2009), 0.7 mm in-plane resolution diffusion imaging was performed at 7T. The imaging protocols were matched to Table 1-7 used for the proposed method, with the exceptions of TR/TE1/TE2 = 2700/68/117 ms, readout bandwidth = 237 Hz/pixel, and no partial Fourier. To minimize distortion in the readout-segmented EPI and to match the scan time, the maximum number of shots (equal to 31) available in the sequence was chosen. Note that since all TEs (TE1 and TE2) and pixel BW were automatically determined by the sequence according to the target matrix size and number of shots, a longer TR was required to match the identical maximum number of slice to the proposed method. Without considering the preparation time, the total scan time for the readout-segmented EPI and the proposed data acquisition were 9 minutes 44 seconds (= 2700 ms × 31 segments × 7 (one non-diffusion weighted and six diffusion weighted directions) = 586 seconds) and 9 minutes 46 seconds (= 2000 ms × 42 segments × 7 = 588 seconds), respectively. Readout-segmented EPI images were calculated through the vendor-provided reconstruction.

Figure 3. Flowchart of the proposed reconstruction pipeline. Data processing

9

A schematic diagram of the proposed reconstruction is shown in Figure 3. All PSF data were reconstructed offline in Matlab (The MathWorks, Inc., USA). Initially, 2D-EPI reconstruction including regridding (ramp-sampling), Nyquist ghost correction, and GRAPPA was carried out with all PSF phaseencoded and navigator echo data in the EPI-PE (ky) and readout dimension (kx). To correct motioninduced phase errors, a 2D phase correction was applied to all PSF phase-encoded images (x,y,ks) after 2D iFT in kx and ky. Each navigator echo was windowed in k-space by a triangular function in both the readout and PE directions prior to 2D iFT (Holdsworth et al., 2008). The multi-channel data of PSF phase-encoded and navigator echo images were combined with the adaptive coil combination (Walsh et al., 2000) to generate complex image data with floor noise reduction. This simplified the calculation of phase differences between 2D navigator echoes and enhanced the quality of motion-induced phase correction due to the reduced noise in the combined data. Note that the proposed gradient-echo 2D navigator echoes include not only motion-induced phase errors, but also phase accumulation caused by field inhomogeneity effects between the PSF phase-encoded echo and the navigator echo (i.e. between TE1 and TE2 in Table 1) and the latter should be removed before correction of motion-induced phase errors. The shot-to-shot phase incoherencies were calculated by subtraction of each navigator echo from the first navigator echo. An additional iFT in ks yields complex 3D PSF data with reduced resolution in the EPI-PE coordinate (y) and PSF folding in the PSF-PE coordinate (s). After image interpolation was applied to retain the original matrix size in the EPI-PE coordinate (y) of the magnitude PSF data, PSF unfolding followed in the PSF-PE coordinates (s) (Fig. 2F-c). Finally, a distortion-free image was obtained by Eq. 6 from the PSF data. Note that zero-filing in k-space is possible for image interpolation, but was not applied in this study due to the large 3D matrix size. Instead, computationally efficient bspline interpolation (Zaitsev et al., 2004) was applied to the magnitude 3D PSF data, which resulted in a distortion-free image without ringing artifacts caused by improper image interpolation. Rigid-body motion correction of all non-DWI and DWI images was carried out with only six degrees of freedom since all data were free from geometric distortions including susceptibility- and eddy-currentinduced distortions. Finally, diffusion tensor calculation followed, which resulted in fractional anisotropy (FA) and color-coded FA maps. FSL (http://fsl.fmrib.ox.ac.uk/fsl/) was used for the image registration and FA map calculation.

Results

10

Figure 4. Distorted (A) and distortion-free (B) non-DW spin-echo images calculated from complex (A-a and B-a) and magnitude 3D PSF data (A-b and B-b) and corresponding anatomical images without geometric distortions (C) including gradient-echo (C-a) and MPRAGE images (C-b). For the geometric comparison, a brain boundary (green contour) and arteries within the brain (red contours) were calculated from the distortion-free non-DW (B-b) and the MPRAGE image (C-b), respectively. The reconstructed voxel sizes [x, y, z] are 0.8×2.4×0.8 and 0.8×0.8×0.8 mm3 for distorted (A) and distortionfree image (B), respectively. The acquisition protocols are listed in Table 1-4. Due to the use of a reduced resolution factor of 4 in the EPI-PE dimension, the distorted images (A) have a four times lower resolution in the PE coordinate. The voxel size of anatomical images (C) is 0.6×0.6×0.6 mm3

Distortion-free DW images from 3D DW-PSF data Figure 4 demonstrates that a distortion-free non-DW image calculated from magnitude 3D PSF data is free from susceptibility-induced geometric distortions and intra-voxel dephasing effects. When both distorted (Fig. 4A-a) and distortion-free non-DW images (Fig. 4B-a) were calculated from complex 3D PSF data by Eqs. 3 and 4, respectively, very noisy images were obtained. In contrast, SNR was dramatically improved when the magnitude PSF data were used in the calculation (Figs. 4A-b and 4B-b) and thus field induced phase variations that lead to incoherent averaging were avoided. Even with a high parallel imaging factor of 3 in the EPI-PE dimension, strong geometric distortions appeared in the reconstructed distorted images representing geometric distortions similar to single-shot 11

EPI at 7T (Fig. 4A). Note that the distorted images (Fig. 4A) have a four times lower resolution, compared to the distortion-free images (Fig. 4B) due to the reduced resolution factor of 4 in the EPI-PE dimension. In contrast, the brain boundary calculated from the distortion-free image (Fig. 4B-b) is matched very well with that of the anatomical GE image (Fig. 4C) (see green contour). In addition, red contours of artery regions appearing as bright and dark signals, respectively in non-DW (Fig. 4B-b) and MPRAGE images (Fig. 4C-b) demonstrate the geometrical match within the brain.

Figure 5. Distorted (A) and distortion-free DW images (B) calculated from 3D DW-PSF data: (a) and (b) DW images with two sets of non-collinear gradient directions [Gx, Gy, Gz]: (2-1/2){[0, 1, -1]; [1, 1, 0]}, (c) the difference map between (a) and (b). The acquisition voxel size is 1.2×1.2×1.2 mm3 (Table 1-6). Figure 5 shows that a distortion-free DW-image obtained from 3D DW-PSF data can avoid both susceptibility- and eddy-current-induced geometric distortions. In addition to strong susceptibilityinduced geometric distortions, the geometric distortions varied severely due to eddy-currents according to different diffusion-encoding gradients, as shown in the difference map (Fig. 5A-c). In contrast, both effects can be corrected in the proposed approach, as shown in the difference map (Fig. 5B-c) between DW distortion-free images (Figs. 5B-a and 5B-b).

12

Figure 6. Reconstructed distortion-free non-DW image (A), DW images without (B) and with motioninduced phase error correction (C), and distorted DW image with a four times lower resolution in the EPI-PE dimension (D). For demonstration purpose, sagittal (upper row) and axial slices (bottom row) are chosen from a 3D brain volume and white arrows indicate the geometrical differences between distortion-free (A-C) and distorted images (D). The reconstructed voxel size of the distortion-free images is 1.2×1.2×1.2 mm3 (Table 1-5). Motion-induced phase error correction of in-vivo data Figure 6 demonstrates that the proposed motion-induced phase correction can correct ghost artifacts in the reconstructed images of in-vivo data. Unlike the non-DW image (Fig. 6A) obtained from the non-DWPSF data, severe ghost artifacts occurred in the DW in-vivo brain data (Fig. 6B). Since the distortion-free dimension (ks) of the 3D DW-PSF data is filled in multiple shots, these artifacts appeared in the distortion-free image I(x,s) only (Fig. 6B), but not in the distorted single-shot image I(x,y) (Fig. 6D) when diffusion encoding was applied. After the proposed motion-induced phase correction, however, no ghost artifacts are visible over the entire brain volume (Fig. 6C). Combined with motion-induced phase error correction, therefore, the proposed method allows robust reconstruction of a ghost- and distortion-free image (see white arrows in Fig. 6).

13

Figure 7. Reconstructed full FOV (A) and zoomed images (B) of the yellow rectangular box area indicated in (A-a): non-DW image (a), DW image (b), fractional anisotropy (FA) map (c), and colorcoded FA map (d) are shown. In (B-a), instead of an enlarged image of the full FOV non-DW image (A-a), a color-coded vector map overlaid on the FA map is shown to demonstrate cortical diffusion anisotropy and its radial diffusion orientation in in-vivo human brain. The acquisition voxel size is 0.7×0.7×2.8 mm3 (Table 1-3). High-resolution diffusion data of the human brain at 7T Figure 7 demonstrates stable and robust high spatial resolution DWI. Due to the longer scan time (2 min. 26 sec.) for each PSF scan for 20 slices leading to a high averaging effect (equal to 64 segments), a DW image for b-value = 1000 s/mm2 was obtained without blurring and with high spatial resolution using the proposed method. Even without cardiac gating, a ghost artifact-free DW image was successfully reconstructed from the 3D DW-PSF data (Fig. 7A-b). Furthermore, since this approach doesn’t suffer from any geometric distortions (Figs. 4 and 5), a very clear interface between white and gray matter areas (Fig. 7B-c) as well as anisotropic diffusion even in gray matter regions (Fig. 7B-a) was observed with the high-resolution in-vivo diffusion data.

14

Figure 8. High in-plane (A) and isotropic (B) resolution diffusion data in in-vivo human cerebrum (upper row) and brainstem (bottom row) at 7T. Full FOV (a) and zoomed images (b) are shown to demonstrate anatomical details with diffusion contrast. Structural abbreviations in the zoomed images are: Tap: the tapetum of the corpus callosum, PTR: posterior thalamic radiation, SLF: superior longitudinal fasciculus, CST: corticospinal tract, tpf: transverse pontine fibers, SCP: superior cerebellar peduncle. Acquisition voxel sizes [x, y, z] for high in-plane (A and Table 1-3) and isotropic resolution (B and Table 1-4) are 0.7×0.7×2.8 and 0.8×0.8×0.8 mm3, respectively. Very high spatial resolution diffusion data with 0.7 mm in-plane (Fig. 8A) and 0.8 mm isotropic resolution (Fig. 8B) in in-vivo human cerebrum and brainstem are shown in Figure 8. With the contrasts of high-resolution diffusion in-vivo data, the superior longitudinal fasciculus, posterior thalamic radiations, and tapetum near the posterior horn of the lateral ventricles are clearly appreciated (upper row in Figs. 8b). In addition, the corticospinal tract (bottom row, blue in Figs. 8b) and transverse pontine fibers (bottom row, red in Figs. 8b) can be distinguished well in the human brainstem in-vivo. The mean SNR of the brain in the non-DW images were 35.8 and 45.0 in the 0.8 mm isotropic and 0.7 mm in-plane resolution data, respectively. Although the SNR of the 0.8 mm isotropic resolution data (Fig. 8B) was slightly lower than 0.7 mm in-plane resolution data (Fig. 8A) due to approximately 2.7 times higher spatial resolution, partially compensated by 2.4 times longer scan time, the FA maps were overall very similar in both in-vivo data since the main anatomical structures in the selected slices are mainly perpendicular to the slice direction. Therefore, these results validate that the proposed method is able to achieve reliable diffusion data with sub-millimeter isotropic resolution in in-vivo human brain at 7T.

15

Figure 9. High in-plane resolution diffusion data at 3T. Two slices acquired at 3T (A, Skyra) and (B, Prisma) are chosen for demonstration purpose. Acquisition voxel sizes are 0.75×0.75×2.8 (Table 1-1) and 0.7×0.7×2.8 mm3 (Table 1-2), respectively. High in-plane resolution diffusion data at 3T Figure 9 shows high in-plane resolution diffusion data acquired at 3T. Due to higher gradient strength on the 3T Prisma and 7T Magnetom, high-resolution readout acquisition was possible with high readout bandwidth. In contrast, 0.7 mm in-plane resolution was not available within the default protocol range of our custom-build sequence due to the lower maximum gradient strength of 40 mT/m at 3T Skyra and slightly lower in-plane resolution diffusion data were acquired (Fig. 9A). In addition, a longer TE was required for the acquisition (Table 1). Therefore, these demonstrate benefits of higher gradient strength in achieving higher spatial resolution. With the proposed approach, nevertheless, diffusion data demonstrating a high level of anatomical detail were obtained on both scanners.

16

Figure 10. Comparison between the readout-segmented (A) and the proposed method (B) at 7T. For the comparison, a slice from a non-DW phantom (a), non-DW in-vivo (b), and DW in-vivo images (c) are chosen. Voxel sizes in both A and B are 0.75×0.75×2.8 mm3. The imaging protocols for the proposed method (B) are shown in Table 1-7. Comparison between the readout-segmented and the proposed method at 7T Figure 10 demonstrates that the proposed method is superior to the readout-segmented EPI approach, especially in yielding very high-resolution distortion-free data. In readout-segmented EPI, geometric distortions were reduced using the highest possible number of shots (equal to 31) and a GRAPPA factor 17

of 3 in the PE dimension. However, local distortions and blurring are still clearly visible in both phantom and in-vivo images (see white arrows and dashed lines in Fig. 10). Since the effective echo spacing and the measured maximum off resonance frequency were 106.7 µs and 189 Hz, respectively, the maximum pixel distortion was about 6.5 (corresponding to 4.5 mm). In addition, longer TEs were required for both imaging (68 ms) and navigator data acquisitions (117 ms) of the segmented approach, which resulted in stronger T2 weighting (Fig. 10A-b) and a DW image with non-optimal phase correction (Fig. 10A-c). In contrast, shorter TEs (54 and 78 ms) are possible with a rR factor of 4 in the proposed method. Therefore, clearer and distortion-free brain images were obtained even in regions with strong field inhomogeneity, where even shorter T2* appears (see dashed line in Figs. 10B-b and 10B-c). The mean SNR in the nonDW phantom data were 170.4 (Fig. 10A-a) and 174.8 (Fig. 10B-a), respectively for the readoutsegmented EPI and the proposed method. In non-DW in-vivo images, the SNR values were 26.5 (Fig. 10A-b) and 48.5 (Fig. 10B-b), respectively. Note that although a partial Fourier factor of 42/46 in the PSF-PE direction was applied for the proposed reconstruction in both phantom and in-vivo data (Table 1), there were no noticeable differences between the reconstructed images without and with zero filled partial Fourier reconstruction (supplementary figure 1).

Discussion In this study, a hybrid approach inspired by the PSF mapping approach is proposed for very highresolution and distortion-free diffusion imaging. The main difference to PSF-based distortion correction schemes (Oh et al., 2012; In et al., 2015; In et al., 2016) suggested previously is that the PSF data are not used to correct DWI data acquired separately, but that the PSF data itself are diffusion weighted and reconstructed into a distortion-free DWI. A 2D navigator echo acquisition is added into the PSF sequence and corresponding phase correction was applied to avoid ghost artifacts in the reconstructed distortionfree image. This approach allows reconstruction of DWI without any T2* blurring and eddy-current- or susceptibility-induced geometric distortions. The results demonstrate that the proposed method enables very high-resolution diffusion data providing a clear demonstration of anatomical details in in-vivo human brain. The proposed approach is similar to the conventional spin-echo diffusion imaging, but enables faster and more robust diffusion imaging. Even without any parallel imaging technique, the use of an acceleration (i.e. rFOV) factor of 3 is possible in the PSF acquisition. If this is combined with parallel imaging in either or both PSF- (Zaitsev et al., 2004; Speck et al., 2008) and EPI-PE dimensions, further accelerations for the PSF scan are possible. In this study, a rFOV factor of up to 5 was applied for the PSF acceleration with a GRAPPA factor of 3 in the EPI-PE dimension, which enabled unfolding of the PSF data even in the regions with the most severe geometric distortions at 7T. In the regions of small distortions, thus, it is possible to apply even higher rFOV factors for PSF acquisition (Fig. 10). In addition, 18

while a line signal acquisition from each shot allows only 1D motion-induced phase correction in the conventional spin-echo diffusion imaging, the proposed approach acquires 2D images within an EPI readout acquisition window and enables 2D motion-induced phase correction using the 2D navigator echo that is more reliable. Furthermore, the robust phase correction is an important prerequisite for the successful application of parallel imaging in the spin-warp PE dimension for both approaches. Compared to FSE-based distortion-free approaches (Pipe et al., 2002), furthermore, the proposed approach does not suffer from effects of unwanted non-CPMG signal components (Bammer et al., 2002) and severe SAR limitations at UHF. Therefore, this approach might be an attractive alternative to other distortion-free diffusion approaches. Highly reduced resolution in the EPI-PE dimension leading to shorter TE was helpful to acquire sufficient signal at UHF, where T2 decay is fast. Hence, the overall SNR for each segment can be maintained well in both PSF-encoded and navigator echo image at 7T. The reduced resolution scheme in the EPI-PE dimension can be useful at high field for very high-resolution imaging exploiting the shared encoding in PE and PSF dimension. In addition, blurring in the EPI-PE dimension including T2* blurring is avoided in the final distortion-free image since all effects within the EPI readout acquisition window were constant along the PSF-PE direction and were integrated by Eq. 6, as expected in the conventional spin-echo imaging with multi-echo acquisitions. In this case, however, the maximum pixel deviation ∆B(s)pmax including the described blurring should be considered in Eq. 7. A high level of anatomical detail demonstrated with the contrasts of high-resolution in-vivo diffusion data supports very well the previous observations in ex-vivo studies (McNab et al., 2009; Miller et al., 2011; Aggarwal et al., 2013). As examples, clear cortical anisotropy with the principal diffusion orientation consistently oriented perpendicular to the adjacent white matter (Fig. 7b in McNab et al., 2009 and Fig. 11 in Miller et al., 2011) and demarcation of the superior longitudinal fasciculus, posterior thalamic radiations and tapetum on color-coded FA maps (see Figs. 7cd in McNab et al., 2009 and Fig. 7a in Miller et al., 2011) were shown in previous ex-vivo studies. The corresponding anatomical details were observed in in-vivo human brain, as shown in Fig. 7 and the upper row of Fig. 8. Although the spatial resolution is lower than ultra-high-resolution diffusion data of ex-vivo human brainstem acquired on an 11.7T animal scanner (Fig. 6e in Aggarwal et al., 2013), it is still possible to distinguish the overall anatomical structures even in in-vivo human brainstem diffusion data (bottom row of Fig. 8). Furthermore, comparable anatomical details can be seen at 3T with slightly lower resolution (Fig. 9). Instead of a spin-echo 2D navigator echo commonly used in previous multi-shot approaches (Holdsworth et al., 2008; Porter and Heidemann, 2009; Jeong et al., 2013), a gradient-echo 2D navigator echo is acquired after each PSF phase-encoded 2D acquisition in our proposed sequence (Fig. 1A). Since the navigator echo is acquired without refocusing RF pulse, SAR is significantly reduced for application at 7T. Compared to a spin-echo based navigator, the overall SNR of gradient-echo based navigator data 19

decreases notably with the time difference between TE1 and TE2 due to its T2* relaxation, especially in strongly compressed regions, where strong intra-voxel dephasing effects (i.e. intensity distortions) appear. Since this effect could result in reduced performance of shot-to-shot phase correction, both TE2 for navigator data acquisition and time difference between both TEs should be minimized. In general, without refocusing RF pulse TE2 for gradient-echo based navigator data becomes shorter (~10 ms), which partially compensates the lower SNR. If partial Fourier acquisition is applied, TE reduction can be achieved in both the PSF phase-encoded and the navigator echo acquisitions, and an accumulated reduction of TE2 is possible in addition to the reduction of the time difference between the imaging and navigator data acquisitions. Finally, echo times are further reduced by the proposed reduced resolution scheme combined with paralleling imaging. For 0.7 mm in-plane resolution (Table 1-7), the minimum TE2 and the time difference between TE1 and TE2 were 78 and 24 ms in the proposed method, rather than 118 and 49 ms in the readout-segmented EPI. The level of SNR was 12.8 ± 0.3 throughout the whole navigator data (i.e. 42 segments) in the in-vivo experiment shown in Fig. 10. Therefore, the proposed motion-induced phase correction performed very well even though phase accumulations induced by field inhomogeneity between TE1 and TE2 are additionally included in the gradient-echo 2D navigator echo (see Figs. 7A-b and 10B-c). Otherwise, errors in the FA calculation were increased due to the imperfect phase correction, especially at regions surrounding strong susceptibility (see the center areas of the bottom slice in Fig. 9A). Therefore, these two factors should be considered for robust phase correction when a gradient-echo based navigator echo acquisition scheme is utilized. Large head motion may cause significant variations of field inhomogeneity in the object and may limit this approach. In general, since a particular property of the PSF-PE scheme is the shift of the 2D k-space plane encoded by the EPI echo train with a PE prewinder (i.e. PSF-PE), the center portion of k-space is covered with each shot, but encoded at slightly different effective echo times. Therefore, the phase difference between the low-resolution data of the center k-space lines with different PSF-PE steps contain field inhomogeneity effects as well as motion-induced phase errors, as measured in gradient-echo 2D navigator-echoes. Future research may include the evaluation of the possibilities to extract motion induced phase variation between shots from the PSF phase-encoded EPI data directly instead of a 2D navigator. Although quantitative evaluation of high-resolution diffusion imaging regarding field strength and hardware configuration would be valuable, this was beyond the scope of this study. Since several parameters are related to each other, more controlled and systematic experiments are required to fully optimize the acquisition protocol for each field strength and hardware configuration. In the readout-segmented EPI, minimizing the echo spacing is limited by the gradient performance and this approach still suffers from distortions in the PE dimension. With a minimum effective echo spacing of 106.7 µs achieved for 0.7 mm in-plane resolution, maximum distortions of 6 mm are expected for an 20

off-resonance frequency of 250 Hz at 7T. Although distortions can become negligible in interleaved multi-shot EPI with a high number of shots, a large mismatch of geometric distortion occurs between imaging and navigator data acquired with and without high acceleration, respectively. In contrast, the level of distortion and resolution can be matched in the proposed method and robust phase correction is possible. The results clearly demonstrate that the proposed method is beneficial to yield very highresolution distortion-free data without ghost artifacts at 7T. A major challenge of this approach is to further reduce the scan time. A higher rFOV factor up to 5 can be applied for the PSF acquisition due to the use of a parallel imaging factor of 3 in the EPI-PE dimension leading to reduced distortion strength in the distorted coordinate of the 3D PSF data. A longer scan time may be necessary to achieve very high-resolution diffusion imaging since the PSF encoding generally acts as averaging leading to a higher SNR. However, this limits the opportunity for acquisition of images with a high number of diffusion directions, which is often preferred as a way to characterize the underlying fiber connections in the presence of multiple intravoxel fiber orientations (Tuch et al., 2002). To further accelerate the scan time, the proposed method combined with two approaches including view angle tilting (VAT) (Ahn and Hu, 2012) and multi-band imaging such as CAIPIRINHA (Breuer et al., 2005; Setsompop et al., 2012) should be considered in future studies. The VAT technique can further reduce the distortion strength in the EPI-PE coordinate and even higher rFOV factors can be used for the PSF acquisition. This approach usually suffers from severe blurring in the EPI-PE coordinate (Ahn and Hu, 2012). As discussed above, this blurring can be avoided in the distortion-free coordinates and thus in the proposed distortion-free image. In the proposed approach combined with CAIPIRINHA, the multiple simultaneously excited slices would be aligned along the diagonal line in 3D PSF space. Since these slices appear at different locations and are generally sparsely occupied in 3D PSF space, this should lead to low g-factor penalty (i.e. loss of SNR) and more robust separation of the multiple slices would be expected. In addition, due to two PE dimensions of the proposed method, this approach may utilize both, the original gradient-echo and the EPI-based multi-band imaging approaches. Interestingly, since the direction of shifts of multiple slices in 3D PSF data is different (i.e. perpendicular) for original- (Breuer et al., 2005) and blipped-CAIPIRINHA (Setsompop et al., 2012), it is expected that an optimal scheme combining both CAIPIRINHA techniques could allow an aliased pattern of multiple slices with minimum overlap in 3D PSF-space and minimize g-factor penalty for separation. Rigid-body motion correction within the PSF acquisition was not considered in this study, which also needs to be considered for future development. Note that only phase errors caused by non-rigid-body motions such as pulsations can be corrected using the 2D navigator echo in this study. To correct rigidbody displacement, the motion parameters can be calculated by means of an image-based registration using the 2D navigator echoes, as suggested in a previous study (Holdsworth et al., 2009). Unlike partial 2D k-space coverage in readout-segmented approaches, the full coverage of the proposed 2D navigator 21

echo would be beneficial to robustly estimate the motion parameters for large rigid-body motion. Nevertheless, a reacquisition (Porter and Heidemann, 2009) or prospective motion correction scheme (Speck et al., 2006; Zaitsev et al., 2006) would be more suitable in such cases.

Conclusions We introduce a novel hybrid approach for high-resolution distortion-free diffusion imaging at high field strength. With the 2D navigator echo added into the PSF sequence, stable imaging can be achieved even without cardiac gating. The results demonstrate that very high-resolution DWI without geometric distortions and T2*-blurring is possible with the proposed method, which results in a clear delineation of brain and cortical structures. In addition, very high-resolution diffusion imaging is possible not only at 7T, but also at 3T. Therefore, this technique can be a powerful tool to characterize in-vivo human brain anatomy for basic research as well as clinical applications.

ACKNOWLEDGEMENTS This study was supported by DFG-grant (SP632-4)

22

REFERENCES Aggarwal, M., Zhang, J., Pletnikova, O., Crain, B., Troncoso, J., Mori, S., 2013. Feasibility of creating a high-resolution 3D diffusion tensor imaging based atlas of the human brainstem: a case study at 11.7 T. Neuroimage 74, 117-127. Ahn, S., Hu, X.P., 2012. View angle tilting echo planar imaging for distortion correction. Magnetic resonance in medicine 68, 1211-1219. Bammer, R., Augustin, M., Prokesch, R.W., Stollberger, R., Fazekas, F., 2002. Diffusion‐ weighted imaging of the spinal cord: Interleaved echo-planar imaging is superior to fast spin‐ echo. Journal of Magnetic Resonance Imaging 15, 364-373. Basser, P.J., Mattiello, J., LeBihan, D., 1994. Estimation of the effective self-diffusion tensor from the NMR spin echo. Journal of Magnetic Resonance, Series B 103, 247-254. Breuer, F.A., Blaimer, M., Heidemann, R.M., Mueller, M.F., Griswold, M.A., Jakob, P.M., 2005. Controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA) for multi-slice imaging. Magnetic resonance in medicine 53, 684-691. Chung, J.Y., In, M.H., Oh, S.H., Zaitsev, M., Speck, O., Cho, Z.H., 2011. An improved PSF mapping method for EPI distortion correction in human brain at ultra high field (7.0 T) Magn. Reson. Mater. Phy. 24, 179-190. Griswold, M.A., Jakob, P.M., Heidemann, R.M., Nittka, M., Jellus, V., Wang, J., Kiefer, B., Haase, A., 2002. Generalized autocalibrating partially parallel acquisitions (GRAPPA). Magn Reson Med 47, 12021210. Heidemann, R.M., Porter, D.A., Anwander, A., Feiweier, T., Heberlein, K., Knösche, T.R., Turner, R., 2010. Diffusion imaging in humans at 7T using readout-segmented EPI and GRAPPA. Magn. Reson. Med. 64, 9-14. Holdsworth, S.J., Skare, S., Newbould, R.D., Bammer, R., 2009. Robust GRAPPA-accelerated diffusionweighted readout-segmented (RS)-EPI. Magnetic resonance in medicine 62, 1629-1640. Holdsworth, S.J., Skare, S., Newbould, R.D., Guzmann, R., Blevins, N.H., Bammer, R., 2008. Readoutsegmented EPI for rapid high resolution diffusion imaging at 3T. European journal of radiology 65, 36-46. In, M.H., Posnansky, O., Beall, E.B., Lowe, M.J., Speck, O., 2015. Distortion correction in EPI using an extended PSF method with a reversed phase gradient approach. PLoS ONE 10, e0116320. doi:0116310.0111371/journal.pone.0116320. In, M.H., Posnansky, O., Speck, O., 2016. PSF mapping‐ based correction of eddy-current-induced distortions in diffusion-weighted echo-planar imaging. Magnetic resonance in medicine 75, 2055-2063. In, M.H., Speck, O., 2012. Highly accelerated PSF-mapping for EPI distortion correction with improved fidelity. Magn. Reson. Mater. Phy. 25, 183-192. Jeong, H.K., Gore, J.C., Anderson, A.W., 2013. High‐ resolution human diffusion tensor imaging using 23

2‐ D navigated multishot SENSE EPI at 7 T. Magnetic resonance in medicine 69, 793-802. Le Bihan, D., Breton, E., 1985. Imagerie de diffusion in-vivo par résonance magnétique nucléaire. Comptes-Rendus de l'Académie des Sciences 93, 27-34. McNab, J.A., Jbabdi, S., Deoni, S.C., Douaud, G., Behrens, T.E., Miller, K.L., 2009. High resolution diffusion-weighted imaging in fixed human brain using diffusion-weighted steady state free precession. Neuroimage 46, 775-785. Merboldt, K.-D., Hanicke, W., Frahm, J., 1985. Self-diffusion NMR imaging using stimulated echoes. Journal of Magnetic Resonance (1969) 64, 479-486. Miller, K.L., Stagg, C.J., Douaud, G., Jbabdi, S., Smith, S.M., Behrens, T.E., Jenkinson, M., Chance, S.A., Esiri, M.M., Voets, N.L., 2011. Diffusion imaging of whole, post-mortem human brains on a clinical MRI scanner. Neuroimage 57, 167-181. Oh, S.H., Chung, J.Y., In, M.H., Zaitsev, M., Kim, Y.B., Speck, O., Cho, Z.H., 2012. Distortion correction in EPI at ultra high-field-MRI using PSF mapping with optimal combination of shift detection dimension. Magn. Reson. Med. 68, 1239-1246. Pipe, J.G., Farthing, V.G., Forbes, K.P., 2002. Multishot diffusion‐ weighted FSE using PROPELLER MRI. Magnetic resonance in medicine 47, 42-52. Porter, D.A., Heidemann, R.M., 2009. High resolution diffusion-weighted imaging using readoutsegmented echo-planar imaging, parallel imaging and a two-dimensional navigator-based reacquisition. Magnetic resonance in medicine 62, 468-475. Robson, M.D., Gore, J.C., Constable, R.T., 1997. Measurement of the point spread function in MRI using constant time imaging. Magn Reson Med 38, 733-740. Setsompop, K., Gagoski, B.A., Polimeni, J.R., Witzel, T., Wedeen, V.J., Wald, L.L., 2012. Blippedcontrolled aliasing in parallel imaging for simultaneous multislice echo planar imaging with reduced gfactor penalty. Magnetic resonance in medicine 67, 1210-1224. Speck, O., Hennig, J., Zaitsev, M., 2006. Prospective real-time slice-by-slice motion correction for fMRI in freely moving subjects. Magn Reson Mater Phy 19, 55-61. Speck, O., Stadler, J., Zaitsev, M., 2008. High resolution single-shot EPI at 7T. Magn Reson Mater Phy 21, 73-86. Taylor, D., Bushell, M., 1985. The spatial mapping of translational diffusion coefficients by the NMR imaging technique. Physics in medicine and biology 30, 345. Tuch, D.S., Reese, T.G., Wiegell, M.R., Makris, N., Belliveau, J.W., Wedeen, V.J., 2002. High angular resolution diffusion imaging reveals intravoxel white matter fiber heterogeneity. Magnetic resonance in medicine 48, 577-582. Walsh, D.O., Gmitro, A.F., Marcellin, M.W., 2000. Adaptive reconstruction of phased array MR imagery. Magnetic resonance in medicine 43, 682-690. 24

Wang, F.N., Huang, T.Y., Lin, F.H., Chuang, T.C., Chen, N.K., Chung, H.W., Chen, C.Y., Kwong, K.K., 2005. PROPELLER EPI: an MRI technique suitable for diffusion tensor imaging at high field strength with reduced geometric distortions. Magnetic resonance in medicine 54, 1232-1240. Zaitsev, M., Dold, C., Sakas, G., Hennig, J., Speck, O., 2006. Magnetic resonance imaging of freely moving objects: prospective real-time motion correction using an external optical motion tracking system. Neuroimage 31, 1038-1050. Zaitsev, M., Hennig, J., Speck, O., 2004. Point spread function mapping with parallel imaging techniques and high acceleration factors: Fast, robust, and flexible method for echo planar imaging distortion correction. Magn Reson Med 52, 1156-1166.

25

Table 1. Experimental imaging protocols at 3 and 7T partia Scan rR l rFOV b-value time for GRAP factor InFouri factor (s/mm2 a PSF Slice TR / PA (matr *Tot plane FOV Matr er (segmen )/ scan Field Experi thickne TE1(PSF) Slic factor ix al resoluti (mm ix (EPIts) Diffusi (= strength -ment ss / TE2(NE) 2 es size) scan on ) size PE) on TR×rep. (mm) (ms) time (mm2) directio + ns preparati EPI-PE PSF-PE on time) 3T 2100/70/1 2 1000 / 27 2 2 2 1 in-vivo 0.75 2.8 225 300 10 5/8 3 5 (60) 137 sec. Skyra 23 (150) 12 min. 3T 2800/48/7 4 1000 / 39 2 in-vivo 0.72 2.8 2242 3202 20 6/8 3 5 (64) 193 sec. Prisma 4 (80) 12 min. 2170/54/7 4 1000 / 30 3 in-vivo 0.72 2.8 2242 3202 20 6/8 3 5 (64) 146 sec. 8 (80) 12 min. 5230/55/7 4 750 / 74 4 in-vivo 0.82 0.8 2082 2602 50 7/8 2 4 (65) 352 sec. 8 (65) 12 min. 7T Magnet 6770/48/6 4 1000 / 36 5 in-vivo 1.22 1.2 2162 1802 82 6/8 3 4 (45) 339 sec. om 2 (65) 6 min. phanto 1 1000 / 14 6 1.22 1.2 3000/59 2162 1802 12 7/8 3 5 (40) 138 sec. m (180) 6 min. 7* phanto 2000/54/7 4 1000 / 10 0.72 2.8 2242 3202 6 6/8 3 7 (42) 94 sec. * m 8 (80) 6 min. & in*Note that thevivo total scan time (=TR×segments×(diffusion directions+1)) was calculated without considering the

preparation time (10~15 sec. per each PSF scan). **To match the scan time for the readout-segmented EPI data acquisition, only 42 segments among 46 (= total matrix size along the PE direction/rFOV factor = 320/7) were included in the proposed reconstruction, which was identical to zero filled partial Fourier (= 42/46 = 7.3/8) in the PSF-PE direction.

Highlights • A new variant of multi-shot EPI for high-resolution diffusion-weighted MRI is presented. • The method allows distortion-free imaging without T2* blurring. • A clear delineation of brain structures with diffusion contrast at 7T is shown. • High-resolution diffusion imaging is possible also at 3T.

26

37