ISMRM23 - Motion Detection & Correction Techniques

ISMRM & ISMRT Annual Meeting & Exhibition • 03-08 June 2023 • Toronto, ON, Canada

Motion Detection & Correction Techniques

Oral

Acquisition & Analysis

Wednesday, 07 June 2023

714A/B

15:45 - 17:45

Moderators: Onur Afacan & Andre van der Kouwe

Session Number: O-05

CME Credit

15:45	1009.	Towards rapid and accurate navigators for motion and B0 estimation using QUEEN (QUantitatively-Enhanced parameter Estimation from Navigators) View Presentation Video Yannick Brackenier¹, Nan Wang¹, Congyu Liao¹, Xiaozhi Cao¹, Sophie Schauman¹, Mahmut Yurt², Lucilio Cordero-Grande³, Shaihan J Malik^4,5, Adam Kerr^2,6, Joseph V Hajnal^4,5, and Kawin Setsompop^1,2 ¹Department of Radiology, Stanford University, Stanford, CA, United States, ²Department of Electrical Engineering, Stanford University, Stanford, CA, United States, ³Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politécnica de Madrid and CIBER-BNN, Madrid, Spain, ⁴Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, ⁵Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom, ⁶Cognitive and Neurobiological Imaging (CNI), Stanford University, Stanford, CA, United States Keywords: Motion Correction, Brain ‘Scout-based’ navigators exploit correlations between navigator data and a low-resolution multi-coil pre-scan data (scout) to effectively estimate either motion or B₀-perturbations. Usually, scout data has a fixed contrast, limiting their usage in estimating motion within echo-trains where contrast changes from one readout to the next (e.g. MPRAGE). Furthermore, combined motion and B₀-perturbation estimation from rapid navigators has yet to be achieved. In this work, we propose a quantitative scout (Q-SCOUT) to ‘time-resolve’ navigator contrast, along with a rapid SPINS-navigator (few ms). Q-SCOUT and rapid navigator data are used in our QUEEN method to enable within-echo-train motion and B₀-perturbation estimation.
15:53	1010.	High Temporal Resolution Head Motion Tracking using Pilot Tone and 3D Radials View Presentation Video Tess E Wallace^1,2, Cemre Ariyurek^1,2, Fatih Calakli^1,2, Tobias Kober^3,4,5, Simon K Warfield^1,2, and Onur Afacan^1,2 ¹Computational Radiology Laboratory, Boston Children's Hospital, Boston, MA, United States, ²Department of Radiology, Harvard Medical School, Boston, MA, United States, ³Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland, ⁴Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland, ⁵LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland Keywords: Motion Correction, Brain Radial acquisitions are inherently motion-robust and facilitate self-navigation, however the frequency of motion updates from navigator images is limited. Pilot tone (PT) enables continuous motion sensing, but estimation of quantitative motion parameters requires a subject-specific calibration. In this work, we propose (i) using PT motion detection to guide navigator-based motion estimation from a 3D radial acquisition and (ii) using these measurements to calibrate a PT motion model in order to provide high temporal resolution quantitative motion tracking. This hybrid approach demonstrates improved retrospective correction results with reduced blurring and facilitates PT motion tracking for subsequent scans.
16:01	1011.	Free-breathing renal R2/QSM using 3D multi-echo UTE cones acquisition and motion-resolved reconstruction with image-based self-navigator No Video Available MungSoo Kang¹, Gerald G. Behr², Ilya Glezerman³, Ricardo Otazo^1,2, and Youngwook Kee¹ ¹Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States, ²Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States, ³Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, United States Keywords:* Motion Correction, Image Reconstruction Respiratory motion is a significant challenge for the acquisition of reliable renal R₂^/QSM. The combination of 3D multi-echo UTE cones MRI and respiratory motion-resolved image reconstruction with an image-based self-navigator was developed to enable motion-robust renal R₂^/QSM. Motion-resolved reconstruction with an image-based self-navigator showed better image quality compared to conventional gridding reconstruction and higher apparent SNR and CNR compared to motion-resolved reconstruction using the center of the k-space as navigator. 3D multi-echo UTE cones MRI and motion-resolved image reconstruction with image-based self-navigator demonstrated the feasibility of motion-robust, free-breathing, and high isotropic resolution of renal R₂^*/QSM.
16:09	1012.	Motion-Compensated Slice-by-Slice ∆B0 Shimming with an AC/DC Shim Coil and Dual-Echo vNavs View Presentation Video Nicolas Sebastian Arango¹, Robert Frost^2,3, Paul Wighton², Jason Stockmann^2,3, Ovidiu C Andronesi^2,3, and Andre van der Kouwe^2,3 ¹Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, United States, ²A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States, ³Department of Radiology, Harvard Medical School, Boston, MA, United States Keywords: Motion Correction, fMRI Subject motion results in intra-scan ∆B0 changes which are uncompensated in conventional ∆B0 shimming methods. Rapidly switchable shim currents and ∆B0 vNavigators together enable motion-compensated shimming. We have demonstrated successful measurement, calculation, and application of motion-compensated slice-by-slice shims using and AC/DC coil and vNav ∆B0 maps. Motion-compensated slice-by-slice homogeneity shimming improves shim robustness to subject motion and enables compatibility with changing slice prescriptions of prospective motion correction.
16:17	1013.	2D Self-Navigation Improves Respiratory Motion Tracking Compared with 1D Self-Navigation in 3D Left Atrial LGE using XD-GRASP Reconstruction View Presentation Video KyungPyo Hong¹, Suvai Gunasekaran¹, Mohammed Elbaz¹, Aggelos K Katsaggelos², Saman Nazarian³, Rod Passman⁴, Eugene Kholmovski⁵, and Daniel Kim¹ ¹Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL, United States, ²Electrical and Computer Engineering, Northwestern University Feinberg School of Medicine, Evanston, IL, United States, ³Medicine, Cardiology, Hospital of the University of Pennsylvania, Philadelphia, PA, United States, ⁴Medicine, Cardiology, Northwestern University Feinberg School of Medicine, Chicago, IL, United States, ⁵Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States Keywords: Motion Correction, Arrhythmia, Late Gadolinium Enhancement Previously described left atrial (LA) late gadolinium enhancement (LGE) using a stack-of-stars k-space sampling pattern with XD-GRASP reconstruction may produce blurry LA wall due to signal variation of inversion-recovery-prepared 1D self-navigation caused by arrhythmia. We hypothesize 2D image self-navigation would be less sensitive to arrhythmia for motion tracking in XD-GRASP framework. In this study, we developed a free-breathing, LA LGE pulse sequence with isotropic spatial resolution using a stack-of-stars sampling pattern and 2D self-navigation and compared its performance against conventional 1D self-navigation in patients with atrial fibrillation. Results show that 2D self-navigation improves respiratory motion tracking compared with 1D.
16:25	1014.	Motion Correction for Interleaved EPI Diffusion Imaging using a Markerless Optical Tracking System View Presentation Video Yi Xiao¹, Chunyao Wang¹, Sisi Li¹, Huijun Chen¹, and Hua Guo¹ ¹Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing, China Keywords: Motion Correction, Diffusion Tensor Imaging Multi-shot interleaved EPI can achieve high-resolution diffusion imaging and effectively reduce geometric distortions. However, multi-shot acquisitions are susceptible to bulk motion which causes artifacts. Optical tracking-based motion correction is an effective method to reduce motion artifacts in DWI. Based on a self-developed Structured Light Optical MOtion tracking (SLOMO) system, a retrospective motion correction method was developed for multi-shot interleaved EPI DWI. The performance was evaluated by in-vivo experiments and compared with software-based correction.
16:33	1015.	Self-navigation using fat navigators for motion immune diffusion weighted-imaging via chemical-shift encoded multi-shot EPI View Presentation Video Yiming Dong¹, Kirsten Koolstra², Malte Riedel³, Matthias J.P. van Osch¹, and Peter Börnert^1,4 ¹C.J. Gorter MRI Center, Department of Radiology, LUMC, Leiden, Netherlands, ²Philips, Best, Netherlands, ³University and ETH Zurich, Zurich, Switzerland, ⁴Philips Research, Hamburg, Germany Keywords: Motion Correction, Motion Correction The presence of fat is a challenge in diffusion-weighted EPI. Recently, chemical-shift encoded approaches found interest, as a smart way of signal averaging, doing water/fat separation and diffusion phase navigation in the reconstruction. However, the dominant signal character of fat in diffusion could actually also be exploited as an advantage by forming a shot-specific fat navigator to track and correct for macroscopic in-plane motion, combined with a model-based self-navigated water/fat decomposition. This allows to correct for both physiological and macroscopic in-plane motion effects in DWI when estimating water and fat resolved images from chemical-shift encoded multi-shot EPI data.
16:41	1016.	Selective MRI reacquisition to extend the working range of retrospective motion correction View Presentation Video Malte Laustsen^1,2, Jakob Slipsager², Thomas Gaaß², Robert Frost^3,4, André van der Kouwe^3,4, Melanie Ganz^5,6, and Lars G. Hanson¹ ¹Magnetic Resonance Section, DTU Health Tech, Technical University of Denmark, Kgs. Lyngby, Denmark, ²TracInnovations, Ballerup, Denmark, ³Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States, ⁴Department of Radiology, Harvard Medical School, Boston, MA, United States, ⁵Neurobiology Research Unit, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark, ⁶Department of Computer Science, University of Copenhagen, Copenhagen, Denmark Keywords: Motion Correction, Artifacts Retrospective motion correction (RMC) can substantially reduce motion artifacts in 3D brain MRI. However, for extensive motion, RMC performance is limited. We evaluate RMC with selective reacquisition (RMC+reacq) to expand the range of correctable motion, while directly comparing to prospective motion correction (PMC) for volumetric brain MRI, using external motion tracking. Both approaches lead to significant image quality improvement and the performance of RMC+reacq and PMC was only found statistically significant in 1 of 9 comparisons. These results suggest that RMC with selective reacquisition can match the performance of PMC for 3D-MPRAGE and 3D-FLAIR sequences.
16:49	1017.	Real-time correction of rigid motion and 1st-order shims using rapid 3D orbital navigators View Presentation Video Malte Riedel¹, Thomas Ulrich¹, and Klaas Pruessmann¹ ¹Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland Keywords: Motion Correction, Brain Rigid head motion, which is a challenging problem in itself, is further accompanied by field variations as the object moves in an inhomogeneous background field, and because pose changes lead to varying susceptibility-induced fields. In contrast to external sensors like optical cameras, navigators are naturally sensitive to field variations. We propose a fast, scan-integrated calibration method to sensitize the 3D orbital navigators to rigid motion and 1st order shim fields. The obtained motion and field parameters are used to correct the scan geometry and shim settings in real-time. The performance is evaluated in phantom and in-vivo studies.
16:57	1018.	Spiral-In/Out MR Elastography with Fat-Water Image Reconstruction for the Quantification of Skull and Brain Motion View Presentation Video Alexa M Diano¹, Alex M Cerjanic^1,2, Olivia M Bailey¹, Grace McIlvain¹, and Curtis L Johnson¹ ¹Department of Biomedical Engineering, University of Delaware, Newark, DE, United States, ²Department of Medicine, Massachusetts General Hospital, Boston, MA, United States Keywords: Elastography, Traumatic brain injury This study uses a novel multishot spiral-in/out fat-water magnetic resonance elastography (MRE) pulse sequence to simultaneously measure skull and brain motion in vivo in a single acquisition. Results in a healthy volunteer showed reduced transmission of motion from the skull to the brain in all three directions of motion. Additionally, the motion of the skull and brain appear to be in phase, with the scalp moving out of phase and most overall displacement in the direction of actuation. This research provides a basis for future studies quantifying skull-brain coupling with multiple actuation frequencies and excitation directions.
17:05	1019.	Three-dimensional rigid head motion correction using the Beat Pilot Tone and Gaussian Processes View Presentation Video Niek R.F. Huttinga¹, Suma Anand², Cornelis A.T. van den Berg¹, Alessandro Sbrizzi¹, and Michael Lustig² ¹Computational Imaging Group for MR therapy & Diagnostics, Department of radiotherapy, University Medical Center Utrecht, Utrecht, Netherlands, ²Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, United States Keywords: Motion Correction, Motion Correction, Brain; Pilot Tone; Surrogate Signals In this work we propose a framework based on Gaussian Processes to extract quantitative motion information from Beat Pilot Tones and subsequently correct rigid head motion in 2D and 3D. In a calibration phase, low-resolution images are acquired and registered to build a training set. Next, Gaussian Processes are trained to infer rigid parameters from multi-channel BPTs, exploiting automatic relevance determination of input channels. In the inference phase, rigid parameters are inferred per readout from the BPT, and high-resolution scans are corrected for motion. In practice the method could reduce the need for anesthetics and/or re-scans in e.g. pediatric patients.
17:13	1020.	Towards contact-free motion sensing technique at low-field MRI using beat pilot tone View Presentation Video Suen Chen¹, Haoyu Sun¹, Hao Chen¹, Suma Anand², Michael Lustig², and Zhiyong Zhang¹ ¹School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China, ²Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, United States Keywords: Motion Correction, Low-Field MRI, Pilot Tone To improve the image quality in low field, the conventional method is to repeat scanning many times, and finally increase the SNR by averaging multiple imaging data. Unfortunately, long scan time can make images highly susceptible to motion artifacts. A recent contact-free motion detection technology Beat Pilot Tone (BPT) improves the sensitivity compared with Pilot Tone (PT) and is not limited by Larmor frequency. We introduce BPT in a 0.25T low-field MRI system, and successfully reduce the motion artifacts while improving SNR by binning the continuously acquired data into different motion states in image domain and k-space via BPT signal.
17:21	1021.	Motion Estimation and Retrospective Correction in 2D Cartesian Turbo Spin Echo Prostate Scans View Presentation Video Bryan Clifford¹, Daniel Polak², Wei-Ching Lo¹, Daniel Nicolas Splitthoff², Bradley Bolster³, Vibhas Deshpande⁴, Mukesh G. Harisinghani⁵, Susie Huang⁵, Lawrence L. Wald^6,7, and Stephen Cauley⁶ ¹Siemens Medical Solutions, USA, Boston, MA, United States, ²Siemens Healthcare GmbH, Erlangen, Germany, ³Siemens Medical Solutions, USA, Salt Lake City, UT, United States, ⁴Siemens Medical Solutions, USA, Austin, TX, United States, ⁵Department of Radiology, Massachusetts General Hospital, Boston, MA, United States, ⁶Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States, ⁷Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States Keywords: Motion Correction, Prostate, MR Value, Motion Correction, Body, Clinical Applications, Prostate Non-rigid patient motion is commonly encountered in clinical settings and can degrade the diagnostic quality of MR exams. We apply the SAMER retrospective method for 2D TSE/FSE prostate imaging to quantify and correct for bulk motion in the abdomen. SAMER utilizes a rapid low-resolution scout scan and a small number of calibration samples for separable motion estimation. In controlled phantom and in vivo experiments, SAMER enabled accurate motion parameter estimation across multiple motion patterns. In addition, we demonstrate improved image homogeneity and spatial resolution when SAMER is used for correction of non-rigid motion in the prostate.
17:29	1022.	Real-time automatic field-of-view adjustment in fetal MR scans using Gadgetron View Presentation Video Sara Neves Silva¹, Jordina Aviles Verdera¹, Raphaël Tomi-Tricot^2,3, Radhouene Neji^2,3, Thomas Wilkinson¹, Valéry Ozenne⁴, Alexander Lewin⁵, Lisa Story¹, Enrico De Vita², Mary Rutherford¹, Kuberan Pushparajah², Jo Hajnal¹, and Jana Hutter¹ ¹Perinatal Imaging & Health, King's College London, London, United Kingdom, ²Biomedical Engineering Department, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom, ³MR Research Collaborations, Siemens Healthcare Limited, Frimley, United Kingdom, ⁴Université de Bordeaux, Bordeaux, France, ⁵Forschungszentrum Jülich, Jülich, Germany Keywords: Motion Correction, Fetus MRI provides an ideal tool for characterising fetal brain development and growth. It is, however, a relatively slow imaging technique and therefore extremely susceptible to subject motion. To address this challenge, we are developing an intrinsically motion-robust deep-learning-based fetal MRI method to achieve real-time fetal head tracking and update the acquisition geometry prospectively. Our method uses Gadgetron for real-time reconstruction of the scans and a 3D UNet for fetal head position location and motion estimation. Real-time tracking and correction for functional fetal MRI was demonstrated both in controlled phantom setups and in fetal MRI cases.
17:37	1023.	MR SIGNATURE MATCHING (MRSIGMA) FOR VOLUMETRIC MRI WITH LESS THAN 300MS LATENCY ON A 1.5T MR-LINAC SYSTEM View Presentation Video Syed Saad Siddiq¹, Victor Murray¹, Neelam Tyagi¹, Pim T.S. Borman², Bas W. Raaymakers², Can Wu¹, and Ricardo Otazo^1,3 ¹Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, United States, ²Radiotherapy, University Medical Center Utrecht, Utrecht, Netherlands, ³Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States Keywords: Hybrid & Novel Systems Technology, Radiotherapy The MR-Linac system offers a platform to adapt and monitor radiotherapy of tumors affected by continuous motion in real-time. However, real-time MRI technology is restricted to 2D imaging, which limits performance. MR Signature Matching (MRSIGMA) is a recently developed real-time 3D MRI technique with the MR-Linac as a target. However, MRSIGMA was tested only in a non-real-time scenario. This work develops a real-time implementation of MRSIGMA on the Elekta Unity 1.5T MR-Linac, including raw data transmission to an external computer, deep learning 4D reconstruction and correlation-based matching to demonstrate total imaging latency lower than 300ms.