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Non-Cartesian MR Image Reconstruction with Integrated Gradient Non-Linearity Correction

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S Tao

S Tao*, JD Trzasko , TW Polley , Y Shu , MA Bernstein , Mayo Clinic, Rochester, MN

Presentations

SU-E-I-41 Sunday 3:00PM - 6:00PM Room: Exhibit Hall

Purpose: Nonlinearities in the spatial encoding gradients of MRI systems cause geometric distortion in images. Typically, this is retrospectively corrected via image-domain interpolation (a.k.a., “gradwarp”) albeit with a loss of spatial resolution. For non-Cartesian MRI, the latter problem is exaggerated by noise and undersampling artifact. In this study, we describe a novel correction strategy that accounts for gradient nonlinearities during – rather than after – non-Cartesian MRI reconstruction, and demonstrate that this approach mitigates the resolution loss that can occur with standard methods.

Methods: To test the proposed method, the American College of Radiology (ACR) quality control phantom was scanned on at 1.5 T (General Electric, v16.0, “zoom” gradient) using a 1.6x undersampled 3D non-Cartesian Shells trajectory (GRE, FOV=24 cm3, 120 shells, 16552 shots, 512 readout, matrix=2403). Image reconstruction was first performed via standard k-space density-compensated gridding and retrospectively corrected via cubic spline interpolation. Image reconstruction was then separately performed using a k-space and image-domain density-compensated type-3 non-uniform fast Fourier transform (NUFFT), which provides a direct mapping between non-Cartesian k-space samples and warped image space voxel locations. Thus, no separate distortion correction procedure is needed for the proposed approach. The gradient distortion field was determined using vendor provided calibration data.

Results: Phantom scan results show that both processing approaches successfully correct geometric distortion. However, visual inspection of the ACR phantom spatial resolution inserts shows that the proposed strategy preserves the resolution of the nominal (uncorrected) reconstruction while “gradwarp” imparts marked spatial blurring (especially for the 1.0 and 1.1 mm inserts) and thus resolution loss.

Conclusion: We’ve presented a novel reconstruction strategy for non-Cartesian MRI that corrects for gradient nonlinearities during – rather than after – reconstruction, and thus better preserves image resolution than traditional interpolation-based methods. This approach is expected to be especially advantageous when imaging with non-standard magnet geometries.

Funding Support, Disclosures, and Conflict of Interest: NIH RR018898 NIH EB10065


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