Extended hybrid-space SENSE for EPI: Off-resonance and eddy current corrected joint interleaved blip-up/down reconstruction

Purpose Cardiac diffusion tensor imaging using EPI readout is prone to image distortions in the presence of field inhomogeneities. In this work, a framework to analyze and correct image distortions in cardiac diffusion tensor imaging is presented. Methods A multi‐coil reconstruction framework was implemented to enable field map‐based off‐resonance correction. Numerical simulations were used to examine reconstruction performance for EPI phase‐encode directions blip up‐down and down‐up for different degrees of off‐resonance gradients and varying field map resolution. The impact of coil encoding was analyzed using the g‐factor and normalized RMSE. Finally, the proposed method was tested on free‐breathing in vivo cardiac diffusion tensor imaging data acquired in healthy subjects at 3 Tesla. Results Depending on the local field map gradient strength and polarity and the selected phase‐encode direction, field inhomogeneities lead to either local spatial compression or stretching with standard image reconstruction. Although spatial compression results in loss of image resolution upon field map‐based reconstruction, spatial stretching can be recovered once multiple receive coils are utilized. Multi‐coil reconstruction was found to reduce the normalized RMSE from 34.3% to 8.1% for image compression, and 33.6% to 1.8% for image stretching, with resulting average g‐factors 14.7 ± 2.9 and 1.2 ± 0.1, respectively. In vivo, multi‐coil field map‐based reconstruction yielded improved alignment of angle maps with anatomical cine data. Conclusion Multi‐coil, field map‐based image reconstruction for echo‐planar cardiac diffusion tensor imaging allows accurate image reconstruction provided that the phase‐encode direction and polarity is chosen to principally align with the direction and polarity of the prominent gradients of field inhomogeneities.

Section: Introductionmentioning

confidence: 99%

Analysis and correction of off‐resonance artifacts in echo‐planar cardiac diffusion tensor imaging

Gorkum

Deuster

Guenthner

et al. 2020

“…This allows reconstructing the readout dimension in an initial run and applying the higher order reconstruction one‐dimensionally in a hybrid space of spatial coordinates and frequencies in the respective dimensions. Similar strategy has been used for the standard ghost correction of multi‐band EPI and for unwarping of multi‐shot EPI with blip reversal …”

Section: Introductionmentioning

confidence: 99%

Echo‐planar imaging of the human head with 100 mT/m gradients and high‐order modeling of eddy current fields

Hennel

Wilm

Roesler

et al. 2020

Purpose:To demonstrate the utility of a high-performance gradient insert for ultrafast MRI of the human head. Methods: EPI was used for the first time with a readout gradient amplitude of 100 mT/m, 1200 T/m/s slew rate, and nearly 1 MHz signal bandwidth for human head scanning. To avoid artefacts due to eddy currents, the magnetic field was dynamically monitored with NMR probes at multiple points, modeled by solid harmonics up to fifth order, and included in the image reconstruction. An approximation of a negligible intra-echo effect of the eddy currents was made to accelerate the high-order reconstruction. The field monitoring-based approach was compared with a recently proposed phase error estimation from separate reconstructions of even and odd echoes. Results: Images obtained with the gradient insert have significantly lower distortions than it is the case with the whole body 30 mT/m, 200 T/m/s gradients of the same system. However, eddy currents of high spatial order must be properly characterized and corrected for in order to avoid a persistent 2D Nyquist ghost. Multi-position monitoring proves to be a robust method to measure the eddy currents and allows higher undersampling rates than the image-based approach. The proposed approximation of the eddy currents effect allows a significant acceleration of the high-order reconstruction by a separate processing of each spatial dimension. Conclusion: Strong gradients with adequate switching rates are highly beneficial for the quality of EPI provided that robust measures are taken to include the contribution of eddy currents to the image encoding. K E Y W O R D Seddy currents, EPI, gradients, higher-order encoding, nyquist ghost

“…To assess the translation of DiTSI into real human applications, we developed a modified version of the Extended Hybrid‐space SENSE for EPI (EHSS‐EPI,) pulse sequence able to collect sPFG and dPFG encoding in both the original dual spin echo (dPFG‐DSE) and the single spin echo (dPFG‐SSE) implementation. This method uses an off‐resonance and eddy current corrected joint interleaved blip‐up/down reconstruction and provides a very efficient method for fast and accurate (ie, distortion‐free) acquisition, which will be critical for practical applications.…”

Section: Resultsmentioning

confidence: 99%

JEDI:JointEstimationDiffusionImaging of macroscopic and microscopic tissue properties

Frank

Zahneisen

Galinsky

2020

Self Cite

Purpose:A new method for enhancing the sensitivity of diffusion MRI (dMRI) by combining the data from single (sPFG) and double (dPFG) pulsed field gradient experiments is presented. Methods: This method uses our JESTER framework to combine microscopic anisotropy information from dFPG experiments using a new method called diffusion tensor subspace imaging (DiTSI) to augment the macroscopic anisotropy information from sPFG data analyzed using our guided by entropy spectrum pathways method. This new method, called joint estimation diffusion imaging (JEDI), combines the sensitivity to macroscopic diffusion anisotropy of sPFG with the sensitivity to microscopic diffusion anisotropy of dPFG methods. Results: Its ability to produce significantly more detailed anisotropy maps and more complete fiber tracts than existing methods within both brain white matter (WM) and gray matter (GM) is demonstrated on normal human subjects on data collected using a novel fast, robust, and clinically feasible sPFG/dPFG acquisition. Conclusions: The potential utility of this method is suggested by an initial demonstration of its ability to mitigate the problem of gyral bias. The capability of more completely characterizing the tissue structure and connectivity throughout the entire brain has broad implications for the utility and scope of dMRI in a wide range of research and clinical applications. K E Y W O R D Sdiffusion anisotropy, diffusion tensor imaging (DTI), diffusion tensor subspace imaging (DiTSI), diffusion weighted imaging (DWI), fiber tractography, gray matter, joint estimation diffusion imaging (JEDI), white matter