Jaume Coll-Font^1,2, Onur Afacan^1,2, Alto Stemmer³, Richard S. Lee^2,4, Jeanne Chow^1,2, Simon Warfield^1,2, and Sila Kurugol^1,2
1Radiology, Boston Children's Hospital, Boston, MA, United States, ²Harvard Medical School, Boston, MA, United States, ³Siemens Healthcare GmbH, Erlangen, Germany, ⁴Urology, Boston Children's Hospital, Boston, MA, United States

Dynamic Radial VIBE (DRV) DCE-MRI can provide high spatio-temporal resolution in the dynamic series of volumes used to evaluate the kidney function. However, bulk motion during the scan corrupts the volumes and deteriorates the quality of the kidney function estimation. We introduce a bulk-motion robust image reconstruction technique to mitigate the effects of motion. Our algorithm detects corrupted k-space data, reconstructs the volumes without signal dropout and aligns them. We applied this approach on non-sedated babies undergoing feed-and-wrap DCE-MRI with DRV. Our results show that our method improves the image quality and the estimation of the kidney function parameters.

Laurence H Jackson¹, Alena Uus¹, Dafnis Batalle^2,3, Jana M Hutter¹, Thomas A Roberts¹, Anthony N Price¹, Alison Ho^2,4, Laura McCabe², Maria Deprez¹, Lucy Chappell⁴, Mary Rutherford², and Joseph V Hajnal^1,2
1Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, Kings College London, London, United Kingdom, ²Centre for the Developing Brain, School of Biomedical Engineering & Imaging Sciences, Kings College London, London, United Kingdom, ³Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology & Neuroscience, Kings College London, London, United Kingdom, ⁴Department of Women and Children’s Health, School of Life Course Sciences, Kings College London, London, United Kingdom

In this work we introduce a novel pipeline for motion correction of SWEEP style acquisition data. The method utilizes local similarity graphs for efficient generation of static volumes by extracting the most coherent slices within a local neighborhood and interpolating over missing data. These static volumes are then used as registration targets for a patch-based deformable slice-to-volume registration. The pipeline produces highly coherent 3D volumes and is demonstrated in adult abdominal and fetal/placental imaging using 2D SWEEP bSSFP and SPGR acquisitions.

Xucheng Zhu^1,2, Frank Ong³, Michael Lustig⁴, and Peder Larson^1,2
1Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States, ²UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco and University of California, Berkeley, Berkeley, CA, United States, ³Electrical Engineering, Stanford University, Stanford, CA, United States, ⁴Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, United States

Respiratory motion is one of the most challenging problems in thoracic and abdominal MRI. Motion resolved reconstruction is introduced to reduce the respiratory motion effects by grouping the data to different motion states, then using compressed sensing techniques to reconstruct different motion states images. Spatio-temporal low-rank constrained reconstruction is one of the widely used techniques. In this work, we proposed a new method incorporating motion compensation into the low-rank model, called MoCoLoR. The proposed method is applied to high resolution free breathing lung MRI, and the results show that MoCoLoR outperforms the standard low-rank constrained reconstruction.

Juliane Ludwig¹, Kirsten Miriam Kerkering¹, Peter Speier², Frank Seifert¹, Tobias Schaeffter^1,3,4, and Christoph Kolbitsch^1,3
1Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany, ²Siemens Healthcare, Erlangen, Germany, ³Division of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom, ⁴Biomedical Engineering and Einstein Center Digital Future, Technische Universität Berlin, Berlin, Germany

Respiratory heart motion during T₁ data acquisition can lead to strong motion artefacts, compromising the quality of reconstructed T₁ maps. Commonly, breathhold techniques are used to minimize respiratory motion but they suffer from low scan efficiency and require patient cooperation. Here, we propose a Pilot tone-based respiratory motion correction approach for free-breathing myocardial T₁ mapping. First, through-plane motion is corrected for by performing prospective slice tracking online during data acquisition. Second, in-plane motion is corrected for retrospectively by applying a phase shift to k-space data before image reconstruction. The feasibility of the proposed approach was demonstrated in four healthy volunteers.

Kristin Quah¹, Srivathsan P. Koundinyan¹, Frank Ong¹, Mario O. Malavé¹, and Dwight Nishimura^1
1Stanford University, Stanford, CA, United States

A whole-heart multiphase coronary angiography method has been developed that extracts a 3D navigator image every heartbeat from the 3D cones high-resolution imaging data. Such 3D self-navigators (sNAVs) enable direct beat-to-beat respiratory motion tracking of the heart for translational and nonrigid correction. 3D sNAVs are derived from the inner k-space region of phyllotaxis-ordered 3D cones interleaves collected over multiple cardiac phases. A multiscale low-rank method is used for reconstruction.

Luis A Torres¹, Xucheng Zhu^2,3, Nathan Sandbo⁴, Mark L Shiebler^4,5, Peder Larson^2,3, and Sean B Fain^1,5,6
1Dept. of Medical Physics, University of Wisconsin - Madison, Madison, WI, United States, ²Dept. of Radiology and Biomedical Imaging, University of California - San Francisco, San Francisco, CA, United States, ³UCSF/UC Berkeley Graduate Program in Bioengineering, University of California - San Francisco, San Francisco, CA, United States, ⁴Dept. of Medicine, University of Wisconsin - Madison, Madison, WI, United States, ⁵Dept. of Radiology, University of Wisconsin - Madison, Madison, WI, United States, ⁶Dept. of Biomedical Engineering, University of Wisconsin - Madison, Madison, WI, United States

Acquiring pulmonary MRI images without motion corruption is a challenging task. In this work, we evaluate several conventional and advanced retrospective motion compensation techniques in subjects with idiopathic pulmonary fibrosis (IPF). We evaluate the effectiveness of each technique using concomitantly acquired CT scans, contrast to noise, and sharpness measures. We find that registration-based techniques show a significant improvement in CNR and sharpness. We also observe significantly improved image quality when referenced side-by-side with CT. We conclude that registration-based techniques could be used to better resolve subtle fibrotic textures in IPF.

Sherry Huang¹, Rasim Boyacioglu², Reid Bolding³, Yong Chen², and Mark A. Griswold^2
1Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States, ²Radiology, Case Western Reserve University, Cleveland, OH, United States, ³Physics, Case Western Reserve University, Cleveland, OH, United States

This study presents a novel free-breathing technique which addresses some of the difficulties in quantitative T₁ and T₂ mapping of the abdomen. The technique integrates Magnetic Resonance Fingerprinting (MRF) and pilot tone (PT) navigator to retrospectively provide simultaneous quantification of multiple tissue properties in the abdomen in inhalation and expiration states of the respiratory motion. The proposed method can be implemented with both 2D and 3D MRF acquisitions.

Ruiqi Geng^1,2, Yuxin Zhang^1,2, Jitka Starekova¹, Lloyd Estkowski³, and Diego Hernando^1,2
1Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States, ²Medical Physics, University of Wisconsin-Madison, Madison, WI, United States, ³MR, GE Healthcare, Waukesha, WI, United States

Diffusion-weighted imaging (DWI) of the abdomen faces multiple challenges, particularly artifacts induced by respiratory, peristaltic, and cardiovascular-related motions. Effects of cardiovascular pulsation on pancreas DWI have not been previously characterized. This motion introduces artifactual signal voids and unreliable apparent diffusion coefficient (ADC) values across the pancreas in DWI, regardless of cardiac phases and diffusion directions. Importantly, these artifacts can be addressed by motion-compensated diffusion gradient waveforms. These findings may facilitate the development of reliable and reproducible DWI of the pancreas.

Alena Uus¹, Jacqueline Matthew¹, Milou P. M. van Poppel¹, Johannes Steinweg¹, Laurence Jackson¹, Mary Rutherford¹, Joseph V. Hajnal¹, and Maria Deprez^1
1Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom

Motion correction for fetal body MRI is particularly challenging due to non-rigid deformations of organs caused by bending and stretching. Rigid slice-to-volume registration (SVR) methods are efficient for 3D fetal brain reconstruction. However, for full body reconstruction, misregistration errors caused by deformable motion lead to degradation of features. We propose a novel deformable SVR (DSVR) method based on hierarchical deformable registration for reconstruction of 3D fetal trunk from multiple motion corrupted stacks. The method is quantitatively evaluated by comparison to the state-of-the-art methods on 20 iFIND fetal MRI datasets. Furthermore, DSVR reconstruction quality is assessed on 100 fetal MRI cases.

Bruno Madore¹, Frank Preiswerk¹, Jeremy Bredfeldt¹, Shenyan Zong¹, and Cheng-Chieh Cheng^1
1Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States

The purpose of this work is to develop MR-compatible sensors that can attach to the patient’s skin, to monitor breathing in a comprehensive manner. In contrast, alternatives such as MRI navigator echoes and optical tracking are typically rigidly fixed to walls or floors and as such cannot accompany a given patient through serial diagnostic and/or therapeutic procedures. We show here that these sensors capture breathing motion in much of its complexity, as validated against MRI and optical tracking data. These sensors could be used to help combine information from different modalities in a manner that takes internal motion into account.