Paul I Dubovan^1,2, Kyle M Gilbert^1,2, and Corey A Baron^1,2
1Medical Biophysics, Western University, London, ON, Canada, ²Centre for Functional and Metabolic Mapping, Western University, London, ON, Canada

Concurrent field monitoring (FM) via integration of field probes in a radiofrequency coil provides advantages over sequential field monitoring that include patient-specific corrections, as well as improvements to user workflow. However, specific design considerations can require placing field probes far from isocentre where gradient fields are no longer linear, reducing data integrity when fitting high order spatially varying terms. We propose a three-part correction algorithm that seeks to correct these errors and compare FM data, as well as reconstructed images, before and after correction. Correction improved integrity of FM data and enhanced quality of anatomical and diffusion weighted images.   

Shu-Fu Shih^1,2 and Holden H. Wu^1,2
1Department of Radiological Sciences, University of California Los Angeles, Los Angeles, CA, United States, ²Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, United States

Radial acquisition can be sensitive to hardware imperfections such as gradient non-linearity and B0 field inhomogeneity. This usually becomes accentuated in areas more distant to the isocenter and can lead to streaking artifacts even when nominally fulfilling Nyquist criteria. Previous work demonstrated beamforming-based methods for radial streaking reduction, but did not explicitly consider phase and did not evaluate the artifact-suppression performance on phase explicitly. In this work, we developed a new beamforming formulation based on minimum-variance distortionless response (MVDR) that can suppress streaking artifact while preserving accurate phase information

Willem van Valenberg¹, Gyula Kotek¹, Mika W. Vogel², Juan A. Hernandez-Tamames¹, and Dirk H. J. Poot^1
1Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, Netherlands, ²GE Healthcare, Hoevelaken, Netherlands

Single-shot quantitative methods with spiral sampling can increase the readout duration to reduce  undersampling artifacts in the images and their propagation to the parameter maps. However, a longer readout increases blurring due to the off-resonance field if not accounted for in the reconstruction. We propose an efficient reconstruction that 1. corrects for blurring due to the off-resonance field, and 2. reduces undersampling artifacts by constraining the signal variation in each voxel to a predetermined subspace. The reconstruction method is shown to enable accurate multi-parametric mapping of a single-shot MP-b-nSSFP acquisition with submillimeter resolution in 1.8s.

Yumna Bilal^1,2, Ibtisam Aslam^1,3, Muhammad Faisal Siddiqui¹, and Hammad Omer^1
1Medical Image Processing Research Group (MIPRG), Department of Electrical & Computer Engineering, COMSATS University Islamabad, Islamabad, Pakistan, ²Department of Electrical Engineering, University of Gujrat, GUJRAT, Pakistan, ³Service of Radiology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland

This work aims at incorporating the GROG facilitated Bunch Phase Encoding (BPE) in XD-GRASP reconstruction framework for improved motion compensation in free-breathing Dynamic Contrast Enhanced golden-angle radial MRI data. In the proposed method, the inherent randomness and added redundancy in the BPE data, is exploited by the Compressed Sensing (CS) algorithm resulting in images with higher quality and improved mitigation of respiratory motion artifacts as compared to the conventionally used XD-GRASP method.

Nick Scholand^1,2,3 and Martin Uecker^1,2,3
1Institute of Medical Engineering, Graz University of Technology, Graz, Austria, ²Department of Interventional and Diagnostic Radiology, University Medical Center Göttingen, Göttingen, Germany, ³German Centre for Cardiovascular Research, Göttingen, Germany

Algorithms for pulse optimization, quantitative MRI, or model-based reconstruction require knowledge about partial derivatives of the Bloch equations.While being available for specific analytical solutions, computing them becomes challenging in the general case. Difference quotient techniques can be used, but require perturbation tuning to avoid errors.
In this work, we investigate the use of direct sensitivity analysis to estimate the partial derivatives of the Bloch equations. We validate it with an analytical sequence model and compare it to the difference quotient in an example without analytical solution. In all cases, direct sensitivity analysis provided highly accurate estimates of the partial derivatives.

Gregory Simchick^1,2 and Diego Hernando^1,2
1Radiology, University of Wisconsin-Madison, Madison, WI, United States, ²Medical Physics, University of Wisconsin-Madison, Madison, WI, United States

The intravoxel incoherent motion (IVIM) DWI signal has been shown to depend on both b-value and the first motion moment (M₁). However, traditional pseudo-diffusion IVIM signal models only include b-value dependence. In this work, monopolar and 2D (b-M₁) IVIM acquisitions were acquired using diffusion gradient waveforms with different maximum amplitudes to emulate different gradient hardware. From each acquisition, IVIM estimates were obtained by fitting pseudo-diffusion and physical (M₁ dependent) IVIM signal models. Estimated IVIM parameters were compared across acquisitions. Reproducible physical IVIM estimates were obtained using 2D IVIM-DWI acquisitions, while pseudo-diffusion IVIM estimates obtained using monopolar acquisitions demonstrated poor reproducibility.

Georg Schramm¹, Yongxian Qian², Johan Nuyts¹, and Fernando Boada^2
1KU Leuven, Leuven, Belgium, ²New York University School of Medicine, New York City, NY, United States

Sodium MR signal acquisition and image reconstruction are severely hampered by the fast relaxation properties of the sodium nuclei. Signal decay due to fast transverse relaxation during readout leads to loss of high frequency information and severe partial volume effects (e.g.signal spill over from CSF into GM). In this work, we apply a reconstruction framework including anatomical regularization and signal decay modeling and estimation to dual echo sodium data to three subjects to investigate its effect on cortical grey matter sodium quantification.

Bastien Lecoeur¹, Marco Barbone², Sophie Alexander³, Jessica Gough³, Uwe Oelfke¹, Wayne Luk², and Andreas Wetscherek^1
1Joint Department of Physics, The Institute of Cancer Research, London, United Kingdom, ²Department of Computing, Imperial College London, London, United Kingdom, ³The Royal Marsden NHS Fundation Trust, London, United Kingdom

In the context of MR-guided radiotherapy, 4D-MRI is of particular interest for lung and abdominal cancer treatment, as it enables quantifying the extent of respiratory motion at the time of treatment, facilitating time-efficient midposition treatments. To reduce long reconstruction times of iterative compressed sensing-based reconstructions involving algorithms, such as XD-GRASP, we used a fast C++ implementation. We evaluated the impact of using overlapping respiratory bins and different self-gating signals on image quality and reconstruction time in multiple patients with and without abdominal compression belts.

Chengran Fang¹, Demian Wassermann¹, and Jing-Rebecca Li^1
1INRIA Saclay, PALAISEAU, France

The diffusion MRI community lacks a spectral perspective to investigate the intricate relationship between the diffusion MRI signals and cellular structures. Our study proposes a new simulation method that can provide a Fourier representation of the signal. Common spectral methods suffer from the singularity of the heat kernel, which requires infinite Fourier modes. We overcome the singularity by formulating the solution in a convolutional form and splitting the heat kernel into a singular part and a smooth part. Numerical experiments are performed to demonstrate the convergence of our method.