ISMRM 23rd Annual Meeting & Exhibition • 30 May - 05 June 2015 • Toronto, Ontario, Canada

Scientific Session • Motion Correction

Thursday 4 June 2015

Constitution Hall 107

10:30 - 12:30


Kevin M. Johnson, Ph.D., Maxim Zaitsev, Ph.D.

10:30 0809.   
Combined free breathing, whole heart self-navigation and "pencil-beam" 2D-T2-Prep for coronary MRA
Andrew J Coristine1,2, Jérôme Chaptinel1,2, Giulia Ginami1,2, Gabriele Bonanno1,2, Ruud B van Heeswijk2, Davide Piccini3,4, and Matthias Stuber2
1Department of Radiology, University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, VD, Switzerland, 2CardioVascular Magnetic Resonance (CVMR) research centre, Centre for Biomedical Imaging (CIBM), Lausanne, VD, Switzerland, 3Department of Radiology, University Hospital (CHUV) and Centre for Biomedical Imaging (CIBM), Lausanne, VD, Switzerland, 4Advanced Clinical Imaging Technology, Siemens Healthcare IM BM PI, Lausanne, VD, Switzerland

Self-navigation may be used to perform respiratory motion correction in whole heart coronary MRA, improving scan efficiency and ease of use when compared to navigator-gated approaches. However, signal from the chest wall complicates motion detection. Additionally, streaking artefacts secondary to displacement correction may be introduced. By incorporating a "pencil beam" 2D RF pulse into a T2-Prep module, one may create a "2D- T2-Prep" that combines T2-weighting with the intrinsic spatial selectivity of a 2D pulse. Here, we combined a 2D- T2-Prep with self-navigation and present initial in vivoresults demonstrating that image quality is improved through the use of a 2D- T2-Prep.

10:42 0810.   Motion Compensated Reconstruction in Accelerated Single-Shot Cardiac MRI
Aurélien Bustin1,2, Anne Menini2, Shufang Liu1,2, Teresa Rincón Domínguez1,2, Darius Burschka1, Martin A Janich2, Steven Wolff3, Oleg Shubayev3, David W Stanley4, Freddy Odille5,6, and Anja C Brau7
1Computer Science, Technische Universitat Munchen, Munich, Germany, 2GE Global Research, Garching, Germany, 3Advanced Cardiovascular Imaging, New York City, New York, United States, 4GE Healthcare, Rochester, Minnesota, United States, 5Imagerie Adaptative Diagnostique et Interventionnelle, Université de Lorraine, Nancy, France, 6U947, INSERM, Nancy, France, 7Cardiac Center of Excellence, GE Healthcare, Garching, Germany

Strong artifacts caused by patient motion during MR scans affect image quality and clinical evaluation. In this work, we propose a novel motion correction framework for free-breathing cardiac MRI with multiple single-shot Late Gadolinium Enhancement data acquisition. The resulting motion-corrected image is recovered through an advanced reconstruction scheme which incorporates a non-rigid registration. The performance and effectiveness of our model was tested off-line through simulation studies. Results achieved by the present technique show significant reduction in blurring artifacts while exhibiting sharper geometric features. This technique holds potential for achieving higher quality LGE images in challenging patient populations compared to conventional methods.

10:54 0811.   Virtual Coil Navigator: A Robust Localized Motion Estimation Approach for Free-Breathing Cardiac MRI
Xinwei Shi1, Joseph Cheng2, Michael Lustig3, John Pauly1, and Shreyas Vasanawala2
1Electrical Engineering, Stanford University, Stanford, CA, United States, 2Radiology, Stanford University, Stanford, CA, United States, 3Electrical Engineering and Computer Science, UC Berkeley, Berkeley, CA, United States

MR scans are sensitive to different sources of motion that are usually spatially-varying and asynchronous. Thus, accurate motion measurement requires spatial localization. Current techniques for localized motion estimation include using navigators obtained in a separate acquisition, using 2D&3D image-based navigators, and cropping image projections. These techniques usually add constraints to the imaging sequences. In this work, we propose a virtual coil navigator approach, which tracks localized motion in chosen 3D ROIs and works for simple navigators. We demonstrate that the virtual coil navigator improves correction for both cardiac motion and respiratory induced motion of the heart in free-breathing cardiac MRI.

11:06 0812.   Imaging in the presence of Motion with Sliding Slice Distortions
Kevin Michael Johnson1, James H Holmes2, and Scott B Reeder1,3
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

Respiratory motion remains a major challenge to the use of MRI in the body and techniques that restrict intra-scan motion utilizing breath-holding or gating are prone to error. In this work, we investigate use of aT1 weighted sliding slice approach that casts intra-scan motion as geometric distortion rather than aliasing. In phantoms and initial volunteer images, we demonstrate improved image quality compared to traditional 3D golden angle radial sampling and a profound robustness to motion.

11:18 0813.   Improved Tracking of Object Motion During MRI Examinations Using Coil Fingerprint Enhanced Signal Navigators.
Kaveh Vahedipour1,2, Thomas Köster1,2, and Fernando Boada1,2
1Center for Advanced Imaging Innovation and Research (CAI2R), NYU Langone Medical Center, New York, NY, United States, 2Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York School of Medicine, New York, NY, United States

We present a new approach for tracking object motion during MRI examinations. The approach is based on the used of spatially encoded coil signatures or “fingerprints”. Using this approach, a motion dictionary can be generated and the corresponding information used to assign readout signals to distinct motion states that have been previously identified during a motion-learning scan. Our results demonstrate that this approach is effective and can be easily incorporated into most high-duty cycle imaging sequences used for body MRI.

11:30 0814.   
Predictive sensor for real-time respiratory motion monitoring
Robin Navest1, Cornelis van den Berg1, Jan Lagendijk1, and Anna Andreychenko1
1Imaging Division, UMC Utrecht, Utrecht, Netherlands

Respiration often leads to artifacts in human torso MR images. To avoid these motion artifacts, triggered or gated MR acquisitions are performed and a reliable motion sensor is a necessity. Therefore a filter is designed and tested to predict the respiration phase real-life per k-line without time delay using thermal noise variance of the receive array.

11:42 0815.   Optical prospective motion correction for high resolution quantitative MRI (qMRI) of the brain
Martina F. Callaghan1, Oliver Josephs1, Michael Herbst2, Maxim Zaitsev2, Nicholas Todd1, and Nikolaus Weiskopf1
1Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, UCL, London, United Kingdom, 2Department of Radiology, University Medical Centre Freiburg, Freiburg, Germany

In this work, prospective motion correction (PMC) via external optical tracking is used to monitor and compensate for head motion by updating the imaging gradients in real time for the purpose of quantitative relaxometry measurements. In the presence of gross motion, the PMC system improves the data quality close to the level of the no motion situation. In the absence of gross motion, the PMC system remains beneficial by further sharpening the GM/WM differentiation.

11:54 0816.   3D FatNav: Prospective Motion Correction for Clinical Brain Imaging
Magnus Mårtensson1,2, Mathias Engström2,3, Enrico Avventi3, Ola Norbeck3, and Stefan Skare2,3
1EMEA Research & Collaboration, GE Applied Science Laboratory, GE Healthcare, Stockholm, Stockholm, Sweden, 2Dept. of Clinical Neuroscience, Karolinska Institutet, Stockholm, Stockholm, Sweden, 3Dept. of Neuroradiology, Karolinska University Hospital, Stockholm, Stockholm, Sweden

In this work we have shown that the previously reported technique FatNav can be used in a clinical setting. A 3dFatNav navigation sequence have been added to a clinical T1 imaging sequence, with and without FatSat. The imaging sequence is prospectively corrected with motion estimates from the navigator sequence which is an EPI based 3dFatNav sequence. Using only the fat signal, which is very spares, extreme acceleration factors can be used, in this work we have used R=16 with a standard clinical 8-ch coil. The high acceleration factors allow for a very short acquisition time for the navigator, <5ms. Using this technique motion artifacts can be greatly reduced, without affecting the main sequence since only the fat signal is used for navigation, not touching water signal, and without increasing the scan time more then ~2-5 %.

12:06 0817.   Simultaneous multi-slice (SMS) accelerated EPI navigators for prospective motion correction in the brain
Himanshu Bhat1, M. Dylan Tisdall2, Stephen F Cauley2, Thomas Witzel2, Kawin Setsompop2, Andre J.W. van der Kouwe2, and Keith Heberlein1
1Siemens Healthcare, Charlestown, MA, United States, 2Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States

The goal of this work was to use SMS acceleration to speed up the acquisition of EPI navigators. Validation studies were performed in phantoms and in-vivo to demonstrate that SMS accelerated navigators can lead to accurate motion detection over a range of motion values. Furthermore, prospective motion correction was demonstrated by adding SMS navigators into an inversion prepared gradient echo (MPRAGE) sequence.

12:18 0818.   On the Resilience of GS-bSSFP to Motion and other Noise-like Artifacts
Michael N Hoff1, Jalal B Andre1, and Qing-San Xiang2,3
1Radiology, University of Washington, Seattle, Washington, United States, 2Physics, University of British Columbia, Vancouver, British Columbia, Canada,3Radiology, University of British Columbia, Vancouver, British Columbia, Canada

A geometric solution (GS) to balanced steady state free precession (bSSFP) signal modulation in MRI has recently shown to additionally mitigate motion artifacts. The underlying mechanism behind its correction of noise-like artifacts is explored through simulations that permit evaluation of the GS solution performance as a function of the base image noise’ radiality relative to the spokes used for GS localization. It is discovered that the GS is resilient to any such radially-oriented noise, indicating GS-bSSFP applications in clinical scenarios that may suffer from noise-like artifacts such as those caused by patient motion, flow, and RF interference.