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Xinyi Gou¹, Yi Wang², Lingli Zhou³, Jianxiu Lian⁴, Zilong Chen⁴, Xiuying Zhang³, Jingyi Cheng¹, Lei Chen¹, Nan Hong¹, and Jin Cheng^1
1Department of Radiology, Peking University People’s Hospital, Beijing, China, ²Department of Ophthalmology, Peking University Third Hospital, Beijing, China, ³Department of Endocrinology, Peking University People’s Hospital, Beijing, China, ⁴Philips Healthcare, Beijing, China

Keywords: Image Reconstruction, Software Tools

For patients with thyroid-associated orbitopathy (TAO) presenting unilateral upper eyelid retraction, the phenomenon that the impaired eye is lower than the healthy eye (“eyeball descending”) has been noticed. This study investigated the eyeballs' position changes by 3D reconstitution of magnetic resonance (MR) images. With reference to the central plane of the healthy side, 70.37% impaired eyeballs (19/27) were found in significantly lower positions, and with significant positive correlations of increased thicknesses of levator palpebrae superioris (LPS), superior rectus (SR), and LPS-SR complex volume. This study provided objective evidence of “eyeball descending” in unilateral upper eyelid retraction TAO patients.

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Srikant Kamesh Iyer¹, Hassan Haji-Valizadeh¹, and Samir Sharma^1
1Canon Medical Research USA, Inc., Mayfield, OH, United States

Keywords: Motion Correction, Motion Correction

A motion correction framework was developed to suppress artifacts from rigid and non-rigid motion using a combination of model-based and ML-based approaches. The performance of this framework was compared with model-based only and ML-based only motion correction approaches on motion-simulated data and motion-corrupted in-vivo data using visual inspection and image quality metrics. The combined approach showed superior image quality than model-based and ML-based approaches applied individually.

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Marina Silic^1,2, Aravinthan Jegatheesan^1,2, Fred Tam², and Simon J Graham^1,2
1Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada, ²Sunnybrook Research Institute, Toronto, ON, Canada

Keywords: Data Acquisition, Motion Correction, Optical Position Tracking

Optical position tracking (OPT) using fiducial markers is advantageous for data acquisition of rigid body head motion parameters and motion correction in magnetic resonance imaging (MRI). Many opportunities still remain to improve OPT through the development of new devices. A promising prototype OPT marker and analysis pathway are described. The marker through-plane degree of freedom (DOF) precision was enhanced via moiré patterns and stereovision. Precision was assessed using positional and rotational stages in all 6DOF. Initial results strongly suggest that with minimal additional work, the OPT marker will provide excellent performance in a 3 T MRI system.

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Wei Zhao¹, Huanjie Li ¹, Yunge Zhang¹, Dongyue Zhou¹, and Fengyu Cong^1,2
1Dalian University of Technology, Dalian, China, ²University of Jyvaskyla, Jyvaskyla, Finland

Keywords: Motion Correction, Artifacts

The fMRI signal has been very noisy for artifacts induced various reasons, and yet the head motion and non-neuronal contributions are always the most tickle one. And too severe of motion corruption usually will lead to abandonment of the participant’s data. In this study, proposed method manages to effectively control these noises meanwhile without losing valuable signals. Proposed method exceeds standard pipeline in both quantitative and qualitative metrics.

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Wanyong Shin¹ and Mark J Lowe^1
1Radiology, Cleveland Clinic, Cleveland, OH, United States

Keywords: Motion Correction, fMRI

In this study, we propose the new inter-/intra-volume motion correction algorithm. To test the proposed method, we modify simulated Prospective Acquisition CorrEcted (SIMPACE) EPI sequence and inject both inter- and intra-volume motion during actual EPI acquisition. Using ex-vivo brain phantom, we synthesize inter-/intra volume motion corrupted MR data.  We evaluate the proposed method, compared to volume motion correction method. We find that the proposed inter-/intra-volume method outperforms volume motion correction method.

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Yantu Huang¹, Daniel Nicolas Splitthoff², Bryan Clifford³, Daniel Polak^2,4, Stephen Cauley^4,5, Wei-Ching Lo³, Nan Xiao¹, and Huixin Tan^1
1Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China, ²Siemens Healthcare GmbH, Erlangen, Germany, ³Siemens Medical Solutions, Boston, MA, United States, ⁴Massachusetts General Hospital, Charlestown, MA, United States, ⁵Harvard Medical School, Boston, MA, United States

Keywords: Motion Correction, Head & Neck/ENT

SAMER uses a fast reference scan (“scout”) and short additional guidance lines in each shot of an MPRAGE sequence (“linear⁺ reordering”) to calculate motion parameters. Optimization of rigid body motion parameters are typically nonlinear. In this work we exploit local linearity with SAMER to improve the performance. During motion estimation, the initial guess of motion parameters for a given shot is taken from the previous most similar shot. Similarity is determined by correlations of the linear⁺ guidance lines. Retrospective reconstructions of volunteer data show the proposed method has very good computation performance and can handle large motion well.

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Anh S Thai^1,2, Carlo Pierpaoli², Lin-Ching Chang¹, and M. Okan Irfanoglu^2
1Catholic University of America, Washington, DC, United States, ²QMI, NIBIB/National Institutes of Health, Bethesda, MD, United States

Keywords: Artifacts, Artifacts, diffusion mri

We propose a novel post-processing method for ghost artifact correction in low-b diffusion weighted images (DWIs) using ghost synthetization and four different phase-encoding direction (PED) images. The results from both simulations and real data show that our method can robustly detect and correct ghost artifacts on b=0 s/mm2 images for artifact-free image.   The proposed method can be used further to generate ground truth training images for a machine-leaning method to remedy ghost artifacts in single PED acquisition. 

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Yuchou Chang¹, Gulfam Ahmed Saju¹, Jasina Yu¹, Reza Abiri², Tianming Liu³, and Zhiqiang Li^4
1Computer and Information Science, University of Massachusetts Dartmouth, North Dartmouth, MA, United States, ²Electrical, Computer and Biomedical Engineering, University of Rhode Island, Kingston, RI, United States, ³Computer Science, University of Georgia, Athens, GA, United States, ⁴Neuroradiology, Barrow Neurological Institute, Phoenix, AZ, United States

Keywords: Motion Correction, Parallel Imaging

PROPELLER blade acquisition has been accelerated by undersampling blade k-space data. Missing data on each blade can be reconstructed by parallel MRI reconstruction methods. However, noise deteriorates the blade and the overall image quality. To enhance the signal-to-noise ratio (SNR), phase-constrained reconstruction is studied for improving the SNR of PROPELLER imaging. Phase-constrained reconstruction can improve PROPELLER imaging SNR when the acceleration of data acquisition is used. Optimal selection of the ACS lines and the outer reduction factors is expected to achieve a better SNR and accelerate the PROPELLER imaging speed simultaneously.

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Jason Daniel van Schoor^1,2, Mark Gosselink³, Dennis Klomp³, Giel Mens³, Hans Hoogduin³, Wim Prins⁴, and Tijl van der Velden^3
1High Field MRI, UMC Utrecht, Utrecht, Netherlands, ²Utrecht University, Utrecht, Netherlands, ³UMC Utrecht, Utrecht, Netherlands, ⁴Philips, Best, Netherlands

Keywords: Motion Correction, Motion Correction, Directional coupler

Motion is a prevalent issue in MRI. Here, we present a fast prospective motion correction (PMC) algorithm using directional couplers as head-motion sensors. The mean reflectances (per volume) of an 8 channel pTx head coil are modelled to head-position recorded by the systems built-in PMC during a calibration scan. Thereafter, the model is used for motion correction at a per RF pulse temporal resolution. Results indicate partial motion correction with error in correcting fast motions due to the necessary presence of filters to remove unidentified low-frequency noise. Mitigating low-frequency noise contributions would allow for less filtering thereby improving dynamic performance.

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Bochao Li¹, Kübra Keskin², Daehyun Yoon³, Nam Gyun Lee¹, Brian Hargreaves³, and Krishna Shrinivas Nayak^2
1Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, United States, ²Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, United States, ³Stanford University, Stanford, CA, United States

Keywords: Artifacts, Low-Field MRI, Metal

Spectrally-encoded multi-spectral imaging (SEMSI) enables imaging adjacent to metal implants without blurring due to off-resonance, and has been demonstrated at 3T. Here, we demonstrate application of this technique at 0.55T with appropriate adjustments to the spectral resolution and RF pulse bandwidth. A total hip arthroplasty phantom was imaged with SEMSI, turbo spin echo (TSE), and Slice Encoding for Metal Artifact Correction (SEMAC). Experiments demonstrate the feasibility of SEMSI at 0.55T, and examine ΔTE  to support multi-echo acquisitions in a single TR.
 

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Fei Tan¹, Ke Wang², Michael Lustig^1,2, and Peder E. Z. Larson^1,3
1UC Berkeley-UCSF Graduate Program in Bioengineering, University of California Berkeley and University of California, San Francisco, San Francisco, CA, United States, ²Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, United States, ³Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States

Keywords: Motion Correction, Motion Correction

This abstract explores the feasibility of machine learning-based motion-compensated reconstruction for free-breathing UTE lung MRI. Specifically, we used respiratory motion-resolved Non-uniform Fourier Transform (NuFFT) reconstruction as input, iterative motion-compensated (iMoCo) reconstruction as target, and a 2D U-Net convolutional neural network. Test results demonstrate a sharper diaphragm and a higher apparent SNR compared to the averaged input. In conclusion, iMoCo-Net accelerates the reconstruction of 3D radial UTE data substantially, shortening the required time from hours to minutes.

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Glen Morrell^1
1Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, United States

Keywords: Artifacts, Relaxometry

Main field B0 inhomogeneity may adversely affect the accuracy of T2* mapping in the abdomen even at locations spatially distant from the B0 variation.  We show this effect in both simulation and phantom studies, and show that it can be ameliorated with the use of two-dimensional spatially selective excitation.  These findings have important ramifications for applications of BOLD imaging in the abdomen such as renal BOLD or liver T2* mapping, where large B0 inhomogeneity is often present in areas of the image volume spatially remote from the organ of interest.

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Ken-Pin Hwang¹, R. Jason Stafford¹, and Tharakeswara K. Bathala^2
1Department of Imaging Physics, The University of Texas M.D. Anderson Cancer Center, Houston, TX, United States, ²Department of Abdominal Imaging, The University of Texas M.D. Anderson Cancer Center, Houston, TX, United States

Keywords: Artifacts, System Imperfections: Measurement & Correction

Diffusion weighted imaging is an essential sequence for diagnosis of prostate cancer but is often impacted by distortion. Current existing phantoms designed for assessing geometric accuracy do not sufficiently simulate the environmental factors that affect distortion in diffusion weighted EPI. In this work we apply a rectilinear tagging technique to visualize and understand patterns of distortion caused by an endorectal coil immersed in water when imaged with a PI-RADS compliant protocol. Maximum spatial distortion including regions of spatial collapse was observed near the coil element. Observed distortion pattern supports proper centering of the coil to avoid distortion.

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Danielle Kara¹, Mark J. Lowe², Christopher T Nguyen¹, and Ken E. Sakaie^2
1Cardiovascular Innovation Research Center, Cleveland Clinic, Cleveland, OH, United States, ²Imaging Institute, Cleveland Clinic, Cleveland, OH, United States

Keywords: Motion Correction, Diffusion/other diffusion imaging techniques, Diffusion Tensor Imaging, Motion Correction, Neuro

Patient motion during acquisition of diffusion weighted (DW) images causes significant signal dropout. To perform motion correction, DW images of the brain were acquired during gross head motion using a first order motion-compensated diffusion gradient scheme and compared to a traditional DW-EPI sequence. Of the images acquired with the motion-compensated sequence, only 1.5% contained significant signal dropout compared to 36% of the images acquired with the traditional sequence. Overall, the motion-compensated sequence reduced signal dropout by 96% compared to the traditional sequence without increasing scan time or introducing new post-processing protocols.  

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SERGE DIDENKO VASYLECHKO¹, CEMRE ARIYUREK², ONUR AFACAN², and SILA KURUGOL^2
1HARVARD MEDICAL SCHOOL, BOSTON, MA, United States, ²RADIOLOGY, BOSTON CHILDREN'S HOSPITAL, HARVARD MEDICAL SCHOOL, BOSTON, MA, United States

Keywords: Motion Correction, Body

Respiratory motion substantially affects the accuracy of quantitative DWI-MR techniques in the upper abdomen. A conventional approach for motion correction in abdominal MRI uses a respiratory belt or other navigators for prospective triggering. This study explores use of a new approach - PilotTone (PT) navigator for binning.

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Yat Lam Wong¹, Hing Chiu Charles Chang², Weiwei Liu³, Weihu Wang³, Yibao Zhang³, Hao Wu³, Victor Ho Fun LEE⁴, Lai Yin Andy Cheung⁵, Tian Li¹, and Jing Cai^1
1Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, Hong Kong, ²Department of Biomedical Engineering, The Chinese University of Hong Kong, Hong Kong, Hong Kong, ³Peking University Cancer Hospital & Institute, Beijing, China, ⁴Department of Clinical Oncology, The University of Hong Kong, Hong Kong, Hong Kong, ⁵Department of Clinical Oncology, Queen Mary Hospital, Hong Kong, Hong Kong

Keywords: Data Processing, Data Processing, 4D-MRI

3D view-sharing sequences have been demonstrated its great promise for abdominal 4D-MRI due to its high temporal resolution and availability in clinical scanners. However, the sub-optimal sampling methods in these sequences under free-breathing condition deteriorates the image quality by ghost artifacts. Here, we propose a novel technique, Artifacts Map-guided Nonlocal Mean (AM-NLM), to suppress motion artifacts and to increase image quality of the 4D-MR images of liver cancer patients acquired by a 3D view-sharing sequence, TRICKS, on a 1.5T scanner.

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Mustafa Utkur^1,2, Tess E Wallace^1,2, Sila Kurugol^1,2, and Onur Afacan^1,2
1Radiology, Harvard Medical School, Boston, MA, United States, ²Computational Radiology Laboratory, Boston Children's Hospital, Boston, MA, United States

Keywords: Motion Correction, Body

Multi-shot EPI can be a promising technique to improve the resolution limits of the single shot EPI. However, its application has been so far limited in the abdominal MRI, as phase errors between shots due to unavoidable breathing motion creates artifacts in the images. Here, we tested a Variable-Flip-Angle Fast Low-angle Excitation Echo planar Technique (VFA-FLEET) pulse sequence and showed that it can be used to create high-resolution motion-robust images with high geometric fidelity without breath holding.

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Yantu Huang¹, Huixin Tan¹, Qiuyi Zhang¹, and Peter Speier^2
1Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China, ²Siemens Healthcare GmbH, Erlangen, Germany

Keywords: Data Processing, Data Processing, physiology signal

Pilot Tone (PT) has been demonstrated to extract respiratory signal successfully. However, RF interferences are not considered. We propose a method to create a high-quality PT respiratory signal, while suppressing RF interference. At beginning of a measurement, initial RF suppression matrix and respiratory combination vector are learned. Then a PT respiratory signal can be generated to trigger measurement. Afterwards, RF suppression matrix is updated during each RF train. We validate our method in a moving phantom and in 39 volunteers against image navigator. Results show that our method can suppress RF interference effectively- highly correlated with image navigator.

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Yael Balbastre^1,2, Robert Frost^1,2, Khushi Morparia^1,3, Richard L Carrington III¹, Yuh-Shin Chang^1,4,5, Brooks P Applewhite^1,4, Marcio Aloisio Bezerra Cavalcanti Rockenbach⁶, and Bruce Fischl^1,2,7,8
1Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States, ²Department of Radiology, Harvard Medical School, Boston, MA, United States, ³Northeastern University, Boston, MA, United States, ⁴Department of Radiology, Massachusetts General Hospital, Boston, MA, United States, ⁵Department of Radiology, Massachusetts Eye and Ear Infirmary, Boston, MA, United States, ⁶Data Science Office, Mass General Brigham, Somerville, MA, United States, ⁷Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology,, Cambridge, MA, United States, ⁸Harvard-MIT Divison of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States

Keywords: Data Analysis, Motion Correction

Intra-scan motion costs tens of thousands of dollars per scanner annually due to the need to repeat non-diagnostic scans¹. When assessing the scale of the problem and potential solutions, radiologists’ ratings of artifacts are considered the gold standard. However, inconsistent and conflicting ratings must be consolidated into a single gold-standard. We introduce a hierarchical label fusion algorithm that infers each rater's performance and promotes consistency across slices from a volume. This algorithm reduces label noise compared to majority votes, and allows non-expert ratings to be calibrated and included as additional silver-standards.

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Habib Rebbah¹ and Timothé Boutelier^1
1Research & Innovation, Olea Medical, La Ciotat, France

Keywords: Machine Learning/Artificial Intelligence, Data Analysis

In cardiac MR field, the slice location along the long axis is a key parameter for the standardization proposed by the American heart association. We explore here the ability of a CNN to estimate it.