Gastao Cruz¹, David Atkinson², Markus Henningsson¹, René Botnar¹, and Claudia Prieto^1
1Division of Imaging Sciences & Biomedical Engineering, King's College London, London, United Kingdom, ²University College London, London, United Kingdom

Non-invasive visualization of both coronary lumen and vessel wall is desired for assessment of coronary atherosclerosis. An interleaved acquisition was recently proposed to obtain both 3D images with MRI. However, this approach is susceptible to motion artifacts and dual respiratory gating results in long and unpredictable scan times. Here, we propose a ~100% scan efficiency, two-step motion correction method using translational and nonrigid correction to produce co-registered coronary lumen and vessel wall images. The proposed method shows significant improvements over translational correction and similar lumen quality to a reference navigator-gated (6mm) scan, despite a scan time reduction of ~1.8x.

Dongxiao Li^1,2, Juerong Wu¹, Kofi M. Deh², Thanh D. Nguyen², Martin R. Prince², Yi Wang^2,3, and Pascal Spincemaille^2
1College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China, People's Republic of, ²Department of Radiology, Weill Cornell Medical College, New York, NY, United States,³Department of Biomedical Engineering, Cornell University, Ithaca, NY, United States

Free breathing liver perfusion analysis requires non-rigid motion registration of the unavoidable respiratory motion in the dynamic data. Traditional non-rigid methods rely on spatially smooth motion parameters, which is problematic for the sliding motion of the liver against the abdominal wall. In this work, truncated L1 regularized Minimum Spanning Tree based motion clustering combined with a Markov Random Field optimization is proposed to perform liver registration without the need for manual segmentation. Results on breath-hold liver images acquired at various positions of the respiratory cycle demonstrated this method allows superior liver motion estimation when compared to traditional methods.

Thomas Küstner^1,2, Christian Würslin^1,3, Martin Schwartz^1,2, Petros Martirosian¹, Sergios Gatidis¹, Konstantin Nikolaou¹, Fritz Schick¹, Bin Yang², Nina F. Schwenzer¹, and Holger Schmidt^1
1University Hospital Tübingen, Tübingen, Germany, ²Institute of Signal Processing and System Theory, University of Stuttgart, Stuttgart, Germany, ³University of Stanford, Palo Alto, CA, United States

In oncologic imaging, simultaneous Positron-Emission-Tomography/Magnetic Resonance (PET/MR) scanners offer a great potential for improving diagnostic accuracy. An accurate diagnosis requires a high PET image quality reflecting in long PET examination times under free movement conditions (respiration and heartbeat). Hence, to ensure this high image quality one has to overcome the motion-induced artifacts. The simultaneous acquisition allows performing a MR-based non-rigid motion correction of the PET image. We propose a clinical feasible respiratory and cardiac motion correction system with a reduced scan time of only 60s, freeing time for additional diagnostic MR sequences. In-vivo patient data substantiates the diagnostic improvements.

Fei Han¹, Ziwu Zhou¹, Paul J Finn¹, and Peng Hu^1
1Radiology, University of California, Los Angeles, Los Angeles, CA, United States

Cardiac-phase-resolved 4D MR angiography (MRA) is a promising technique for evaluating patients with cardiovascular disorder. However, current approaches usually has low scan efficiency (20-40%) due to the gating based respiratory motion compensation and therefore suffered from prolonged yet unpredictable scan time. In this work, we proposed a motion correction strategy in which complex non-rigid respiratory motion is modeled using voxel-based linear translations, which are estimated using 3D image registration. Our preliminary result shows that the proposed technique could compensate for complex motion across the large field-of-view of 4D MRA and potentially improve the scan efficiency by including more k-space data in the reconstruction.  

Xin Chen¹, Muhammad Usman¹, Christian Baumgartner², Claudia Prieto¹, and Andrew King^1
1Division of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom, ²Biomedical Image Analysis Group, Imperial College, London, United Kingdom

We present a novel method based on manifold alignment, which enables reconstruction of motion-free abdominal images throughout the respiratory cycle to better capture respiratory intra- and inter-cycle variations. The proposed method was evaluated on both simulated and in-vivo 2D acquisitions. Based on virtual navigator measurement, the reconstructed dynamic sequence achieved Pearson correlation coefficient of 0.9504 with the ground truth of the simulated dataset. The proposed method enables much richer profile data to be used for self-gating, resulting in less blurring when compared to conventional central k-space self-gating method for the in-vivo acquisition.

Kevin M Johnson¹, James H Holmes², and Scott B Reeder^1,3,4
1Medical Physics, University of Wisconsin - Madison, Madison, WI, United States, ²Global MR Applications and Workflow, GE Healthcare, Madison, WI, United States, ³Radiology, University of Wisconsin - Madison, Madison, WI, United States, ⁴Biomedical Engineering, University of Wisconsin - Madison, Madison, WI, United States

Sliding slice MRI is a technique which uses a magnetization prepared sliding 2D slice to cast respiratory motion artifacts as geometric distortions rather than diagnostically obscuring ghosting routinely associated with 3D phase-encoding. In this work, we present the combination of simultaneous-multi-slice with pseudo-random Cartesian based sliding slice sampling. This combination allows increased frame rates, FOV tailoring, and reduces sensitivity to off-resonance compared to past non-Cartesian radial and spiral based approaches. Preliminary results are shown in moving phantoms and in-vivo free breathing DCE, demonstrating very good image quality.

Christopher M Rank¹, Sebastian Sauppe¹, Thorsten Heußer¹, Andreas Wetscherek¹, and Marc Kachelrieß^1
1Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany

We propose a new method for 5D respiratory and cardiac motion compensation (MoCo), which employs highly undersampled MR data and thus requires acquisition times as low as 2 minutes. Radial MR data of the thorax of three free-breathing patients were acquired. Respiratory and cardiac motion vector fields were estimated allowing for 5D MoCo reconstructions, which employ 100% of the measured raw data for reconstruction of each combination of respiratory and cardiac phase. These 5D MoCo reconstructions clearly resolve different combinations of respiratory and cardiac phases while achieving high temporal and spatial resolution as well as low noise and artifact levels.

Ziwu Zhou¹, Fei Han¹, Takegawa Yoshida¹, Kim-Lien Nguyen¹, Paul Finn¹, and Peng Hu^1
1Radiological Sciences, University of California, Los Angeles, Los Angeles, CA, United States

In this study, we proposed a respiratory and cardiac dual soft-gated technique that efficiently suppresses respiratory motion and resolves cardiac motion in 4D cardiovascular MRI. Comparing with existing methods that exploited data redundancy in respiratory and cardiac dimensions using joint reconstruction, proposed method weights data consistency according to the degree of motion corruption. A big advantage of this approach is its short reconstruction time and low computation burden, making it feasible for practical usage.

Bragi Sveinsson¹, Garry Gold¹, and Brian Hargreaves^1
1Stanford University, Stanford, CA, United States

The double-echo in steady-state (DESS) sequence offers both 3D anatomical imaging and 3D quantitative mapping (SNR-efficient 3D maps of T2 and apparent diffusion coefficent) in various applications, such as breast imaging or knee cartilage imaging. The complicated signal behavior remains a challenge for quantitative imaging, and strong spoiling can lead to motion artifacts. Here, we introduce simplified methods for modeling DESS signals, enabling more accurate T2 measurements and better motion artifact reduction.

André Fischer^1,2, Anne Menini¹, Aurelien Bustin^1,3, Kevin M Johnson⁴, Christopher J Francois⁵, and Anja C.S. Brau^2
1GE Global Research, Garching bei München, Germany, ²Cardiac Center of Excellence, GE Healthcare, Garching bei München, Germany, ³Computer Science, Technical University Munich, München, Germany,⁴Medical Physics, University of Wisconsin, Madison, WI, United States, ⁵Radiology, University of Wisconsin, Madison, WI, United States

Cardiac MRI is affected by both cardiac and respiratory motion. While ECG-gated imaging in breath hold is the clinical method of choice, free-breathing methods are needed in patients with limited breath hold capability. This works describes a method to obtain free-breathing cine datasets with high SNR and high spatial resolution (1.4mm in-plane) from a completely self-gated Golden Angle radial scan within an 11s scan time. The motion compensated reconstruction technique takes advantage of calibrated displacement fields extracted from the radial data to recover motion artifact-free cardiac phases. Beyond cine imaging, contrast-enhanced cardiac imaging can also be expected to benefit from this motion compensated reconstruction strategy.