In vivo human brain submillimeter diffusion MRI on the Connectome 2.0 scanner

2363 

Abstract Submission 

Gabriel Ramos Llorden^1,2, Mirsad Mahmutovic³, Daniel J. Park¹, Chiara Maffei^1,2, Hong-Hsi Lee^1,2, Lawrence L. Wald^1,2, Thomas Witzel⁴, Boris Keil^3,5, Susie Huang^1,2

¹Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, ²Harvard Medical School, Boston, MA, ³Institute of Medical Physics and Radiation Protection, Mittelhessen University of Applied Science, Giessen, Germany, ⁴Q Bio Inc, San Carlos, CA, ⁵Department of Diagnostic and Interventional Radiology, University Hospital Marburg, Philipps University of Marburg, Marburg, Germany

Gabriel Ramos Llorden  
Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital|Harvard Medical School
Charlestown, MA|Boston, MA

Mirsad Mahmutovic  
Institute of Medical Physics and Radiation Protection, Mittelhessen University of Applied Science
Giessen, Germany

Daniel J. Park  
Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital
Charlestown, MA

Chiara Maffei  
Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital|Harvard Medical School
Charlestown, MA|Boston, MA

Hong-Hsi Lee, MD PhD  
Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital|Harvard Medical School
Charlestown, MA|Boston, MA

Lawrence L. Wald  
Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital|Harvard Medical School
Charlestown, MA|Boston, MA

Thomas Witzel  
Q Bio Inc
San Carlos, CA

Boris Keil  
Institute of Medical Physics and Radiation Protection, Mittelhessen University of Applied Science|Department of Diagnostic and Interventional Radiology, University Hospital Marburg, Philipps University of Marburg
Giessen, Germany|Marburg, Germany

Susie Huang, MD PhD  
Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital|Harvard Medical School
Charlestown, MA|Boston, MA

Maximizing the benefits afforded by high-performance gradient technology[1,3,6] for diffusion MRI requires overcoming the technical challenges associated with strong diffusion gradients, including more pronounced high-order eddy currents and pervasive concomitant field effects. This work investigates the impact of eddy currents from ultra-strong diffusion gradients (500 mT/m) of the Connectome 2.0 scanner [6] on the long image readouts of high-spatial-resolution diffusion MRI acquisitions. We show the limitations of conventional ghosting-removal methods to provide high-quality images. We achieve eddy-current-induced geometric distortion- and ghosting-free submillimeter in vivo human diffusion MRI at unprecedentedly short echo time at G_max = 500 mT/m with concurrent field monitoring integrated into a custom-built 72-ch in vivo coil.

Acquisition protocol: A healthy volunteer (23Y, female) underwent a diffusion MRI scan on the Connectome 2.0 scanner [6] (MAGNETOM Connectom.X, Siemens Healthineers, Erlangen, Germany) with a custom-built 72-ch head coil. The coil was equipped with a 16-channel 19F clip-on field probe system (Skope, Inc., Zurich, Switzerland) for concurrent field monitoring (Fig. 1a).[10]
Whole brain was acquired with a 2D Pulsed-Field Gradient Spin Echo (PGSE) EPI sequence with axial slices, 0.9 mm in-plane resolution, slice thickness = 0.9 mm, TR/TE = 12,000/47 ms, phase encoding direction A>P, in-plane acceleration factor = 2, PF = 6/8, no SMS, BW = 1912 Hz, echo spacing = 0.57 ms. Readout time = 46 ms, Total acquisition time = 7.2 min. Thirty diffusion encoding directions at b = 1,200 s/mm² (G_max = 500 mT/m, ∆=8.7 ms, δ=2.9 ms) + 1b0-image. A gradient-recalled echo (GRE) scan was also performed to estimate the coil sensitivities.
Image reconstruction:
The 2D-PGSE EPI sequence was modified by incorporating triggers and synchronization pulses (beginning of the sequence) to ensure accurate synchronization between the monitored field and the k-space data during the image readout.[10] A third-order spherical harmonics (SH) model was fitted to the 16 NMR probes' signal phase with a linear least squares (LLS) algorithm.[10] B0-eddy-current compensation (B0-ECC) applied by the scanner was removed prior to reconstruction. Images were reconstructed within a SENSE reconstruction framework, with the image encoding matrix informed by the phase evolution[10,7] The ESPIRiT algorithm was used to estimate the coil sensitivities.[9]
Validation: Concurrent field monitoring-based image reconstruction was compared with standard GRAPPA[4] reconstruction with 1D navigators[2] for Nyquist ghosting correction based on a linear phase model (1D LPC), and with Dual Polarity Grappa (DPG).[5] Reconstructed images with GRAPPA-1D LPC and DPG were corrected for eddy current-induced geometric distortion with the FSL post-processing tool 'eddy''.

Eddy currents from the ultra-strong diffusion gradients perturb the image encoding, causing each DWI's k-space trajectory to deviate from the b0 k-space trajectory (Fig. 1b). High-order phase terms are also prominent with the asymmetric Connectome 2.0 head gradient coil (Fig. 1c) and diffusion-direction dependent due to remaining long-decay eddy currents. Phase differences between odd/even EPI lines are non-linear in space and vary among DWIs (Fig. 2a) Ghosting artifacts remain visible with GRAPPA-1D LPC but are largely mitigated with DPG and slightly more with concurrent field monitoring-based reconstruction (Fig. 2b). Axial, coronal, and sagittal views of a diffusion-weighted image reconstructed with concurrent field monitoring are shown in Fig. 2c as well as the averaged DWI map (Fig. 2d).

We show here that concurrent field monitoring effectively reduces non-linear Nyquist ghosting and geometric distortions generated by eddy currents from ultra-high-strength diffusion gradients on Connectome 2.0.

White Matter Anatomy, Fiber Pathways and Connectivity ²

Diffusion MRI ¹

Cortex

White Matter

Other - high-spatial-resolution