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Isaac Watson^1,2,3, Martin Trefzer¹, David Mitchell², Angelika Sebald², and Aneurin Kennerley^3,4
1School of Physics, Engineering and Technology, University of York, York, United Kingdom, ²York Cross-disciplinary Centre for Systems Analysis, University of York, York, United Kingdom, ³York Neuroimaging Centre, University of York, York, United Kingdom, ⁴Institute of Sport, Manchester Metropolitan University, Manchester, United Kingdom

Keywords: Data Acquisition, Data Acquisition

 Real time (rt) MRI is currently predominantly a single slice acquisition technique. We show that, by combining compressed sensing, simultaneous multi-slice acquisition and interleaved data ordering with a highly undersampled radial trajectory, multi-slice rtMRI images with a high temporal resolution can be acquired. This offers new opportunities, for example, the non-invasive monitoring of oral and maxillo facial dynamics.

 

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Chaoping Zhang¹, Matthan W.A. Caan^2,3,4, Robin Navest¹, Jonas Teuwen^1,5,6, and Jan-Jakob Sonke^1
1Netherlands Cancer Institute, Amsterdam, Netherlands, ²Amsterdam UMC location University of Amsterdam, Amsterdam, Netherlands, ³Amsterdam Neuroscience, Amsterdam, Netherlands, ⁴Oslo University Hospital, Oslo, Norway, ⁵University of Amsterdam, Amsterdam, Netherlands, ⁶Radboud University Medical Center, Nijmegen, Netherlands

Keywords: Image Reconstruction, Image Reconstruction, radial, radiotherapy, liver, lung, respiratory motion

To accelerate the acquisition and reconstruction of the respiratory correlated (4D) radial MRI for image guided radiotherapy guidance, we propose a 3D radial-RIM network by adapting the forward model for Cartesian k-space in the regular RIM to radial k-space. Experiments show that the radial-RIM reconstructs images with better quality than the XD-GRASP compressed sensing for 3-4 times accelerated 4D radial free-breathing lung/liver acquisitions, with reconstruction time per slice reduced from 2 minutes to 1.9 seconds. Signal correlation exploited by the radial-RIM over the extra motion-state dimension contributes substantially to the image quality.

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Tetsuro Kaga¹, Yoshifumi Noda¹, Nobuyuki Kawai¹, Kimihiro Kajita², Yu Ueda³, Masatoshi Honda³, Fuminori Hyodo⁴, Hiroki Kato¹, and Masayuki Matsuo^1
1Department of radiology, Gifu university, Gifu, Japan, ²Gifu university hospital, Gifu, Japan, ³Philips Japan, Tokyo, Japan, ⁴Institute for Advanced Study, Gifu university, Gifu, Japan

Keywords: Data Acquisition, Liver, Free breathing, Radial sampling

The gadoxetic acid-enhanced hepatobiliary phase imaging is an effective sequence for detecting hepatic lesions; however, degraded image quality is often observed due to poor breath holding. Free-breathing sequence using radial stack-of-stars acquisition (3D VANE) has been introduced and can provide diagnosable image quality. Recently, Compressed SENSE (CS), that is one of the acceleration techniques, has been applicable in 3D VANE. In this study, we evaluated the feasibility of 3D VANE with CS in hepatobiliary phase imaging. Our results showed that 3D VANE with CS at section thickness of 2 mm had almost comparable image quality as conventional breath-holding cartesian sampling.

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Ding Xia¹, Sera Saju¹, Kai Tobias Block², and Li Feng^1
1BioMedical Engineering and Imaging Institute (BMEII), Icahn School of Medicine at Mount Sinai, New York, NY, United States, ²Center for Advanced Imaging Innovation and Research (CAI2R), NYU Grossman School of Medicine, New York, NY, United States

Keywords: Data Acquisition, Motion Correction

This work proposes a new radial sampling scheme called Navistar for highly-accelerated 4D dynamic MRI. Navistar periodically inserts 2D navigators into a golden-angle radial stack-of-stars acquisition. The embedded 2D navigators provide spatially-resolved information that can be used for different purposes, such as improved temporal-basis estimation for image reconstruction or respiratory-motion estimation. In our experiments, we have shown that Navistar sampling can be combined with low-rank subspace-constrained image reconstruction for highly-accelerated free-breathing 4D DCE-MRI of the liver with sub-second temporal resolution, which helps reduce intraframe respiratory blurring and eliminates the need for explicit respiratory-motion compensation.

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Li-Ya Shao¹, Zih-Ci Wang², Bruno Madore³, and Cheng-Chieh Cheng^2
1Department of Electrical Engineering, National Sun Yat-sen University, Kaohsiung, Taiwan, ²Department of Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung, Taiwan, ³Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States

Keywords: Data Acquisition, Relaxometry

Quantitative MRI is emerging as a powerful diagnostic tool for neuroimaging applications. A motion-robust, golden-angle radial acquisition version of the ‘triple-echo steady-state’ (TESS) relaxometry method was implemented here, to mitigate the artifacts induced by the flowing motion of the cerebrospinal fluid (CSF). To improve the scan efficiency, a probability density function-based sparse sampling scheme was introduced in each radial spoke. Close agreement was obtained between reference and TESS scans for both T₁ and T₂ values, using a multi-compartment phantom. In vivo whole-brain results were further obtained (3D T₁ and T₂ maps, 1-mm isotropic resolution, whole-brain coverage, 7.5-minute scan).

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Chetan B. Dhakan¹, Jorge De La Cerda¹, William Schuler¹, Christina J. MacAskill², Chris A. Flask², Mark D Pagel¹, and Gary V. Martinez^3
1Cancer Systems Imaging, MD Anderson Cancer Center, Houston, TX, United States, ²Department of Radiology, Case Western Reserve University, Cleveland, OH, United States, ³Imaging Physics, MD Anderson Cancer Center, Houston, TX, United States

Keywords: MR Fingerprinting/Synthetic MR, Cancer

Quantitative Magnetic Resonance Imaging (MRI) involves pixel-wise mapping of longitudinal relaxation time T1, transverse relaxation time T2 and proton density M0 and other relevant parameters at each location in the tissue to be characterized. The goal of this study is to investigate potential benefits of Magnetic Resonance Fingerprinting in quantifying T1 relaxation times in metastatic breast tumor using radial acquisition in tumor with high temporal and spatial resolution.

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Christopher Huynh¹, Datta Singh Goolaub¹, and Christopher K Macgowan^1,2
1Translational Medicine, Hospital for Sick Children, Toronto, ON, Canada, ²Medical Biophysics, University of Toronto, Toronto, ON, Canada

Keywords: Data Acquisition, Artifacts, Optimized 3D Trajectory

The commonly used golden angle trajectory for 3D radial dynamic MRI suffers from spiral-shaped sample clustering around the z-axis, often resulting in image streaking artifact. We develop a method that corrects for this for center-out 3D radial trajectories. The electric potential energy of the trajectory is minimized through the use of repulsive forces, producing a spherically uniform distribution while maintaining the quasirandom quality of the golden angle trajectory. ELECTRic potential energy Optimized (ELECTRO) trajectories are relatively inexpensive to obtain and can produce images with lower MSE compared to the golden angle counterpart.

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Serhat Ilbey¹, Sebastian Littin¹, Feng Jia¹, Niklas Wehkamp¹, Philipp Amrein¹, Maxim Zaitsev¹, Michael Bock¹, and Ali Caglar Özen^1
1Division of Medical Physics, Department of Radiology, University Medical Center Freiburg, Freiburg, Germany

Keywords: New Trajectories & Spatial Encoding Methods, New Trajectories & Spatial Encoding Methods

The sampling efficiency of radial center-out MRI was increased by using additional oscillating readout gradients, which lead to an accelerated image acquisition. The idea of radial sampling along an oscillating spoke was demonstrated using a clinical MRI system with ultra-fast UTE MRI.

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Sherine Brahma¹, Tobias Schaeffter^1,2,3, Christoph Kolbitsch^1,3, and Andreas Kofler^1
1Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany, ²Department of Biomedical Engineering, Technical University of Berlin, Berlin, Germany, ³School of Imaging Sciences and Biomedical Engineering, King’s College London, London, United Kingdom

Keywords: Image Reconstruction, Cardiovascular, Radial Acquisition

Uncertainty quantification (UQ) can provide important information about deep learning algorithms and help interpret the obtained results. UQ for multi-coil dynamic MRI is challenging due to the large scale of the problem and scarce training data. We approach these issues by learning distributions in a lower dimensional latent space using a conditional Wasserstein autoencoder while utilizing the MR data acquisition model and by exploiting spatio-temporal correlations of the cine MR images. Our results indicate excellent image quality accompanied with uncertainty maps that correlate well with estimation errors.

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Ruoxun Zi¹, Kai Tobias Block¹, Ioannis Koktzoglou², Mahesh Keerthivasan³, Thomas Benkert⁴, Jakob Asslaender¹, Daniel K Sodickson¹, and Robert R Edelman^2
1The Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States, ²Radiology, Northshore University HealthSystem, Evanston, IL, United States, ³Siemens Medical Solutions, New York, NY, United States, ⁴Application Development, Siemens Healthcare GmbH, Erlangen, Germany

Keywords: Data Acquisition, Brain

A new class of sequences, named T1 relaxation-enhanced steady-state (T1RESS), has been recently proposed and showed improved lesion conspicuity in contrast-enhanced exams. T1RESS sequences combine steady-state acquisition, either balanced or unbalanced with weak gradient spoiling, with periodic contrast-modifying preparation pulses to create T1 weighting of the contrast. Here, we present radial versions of T1RESS sequences using the stack-of-stars trajectory, which offer improved motion robustness and enable dynamic imaging through use of advanced reconstructions such as GRASP. Volunteer scans acquired at 3T are shown for both sequences. Moreover, the balanced version is demonstrated at 0.55T to highlight its SNR efficiency. 

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Guanhua Wang¹, Jon-Fredrik Nielsen¹, Jeffrey A. Fessler², and Douglas C. Noll^1
1Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States, ²EECS, University of Michigan, Ann Arbor, MI, United States

Keywords: New Trajectories & Spatial Encoding Methods, Machine Learning/Artificial Intelligence

Efficient k-space trajectories are crucial for accelerated MRI. SNOPY proposes a generalized gradient-based method for optimizing 3D non-Cartesian sampling patterns. The algorithm can simultaneously tune multiple properties of sampling patterns, including image quality, hardware constraints (maximum slew rate and gradient strength), reduced peripheral nerve stimulation (PNS), and parameter-weighted contrast. The proposed method applies to various scenarios, such as optimizing gradient waveforms or optimizing rotation angles of radial/spiral trajectories. We adopted several computational strategies to address this non-convex and large-scale problem. Various simulated and in-vivo experiments demonstrated the effectiveness of SNOPY. 

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Bastien Lecoeur^1,2, Prashant Nair¹, Rosie Goodburn¹, Tom Bruijnen³, Uwe Oelfke¹, Wayne Luk², and Andreas Wetscherek^1
1Joint Department of Physics, The Institue of Cancer Research, Sutton, United Kingdom, ²Department of Computing, Imperial College London, London, United Kingdom, ³Department of Radiotherapy, University Medical Center Utrecht, Utrecht, Netherlands

Keywords: Image Reconstruction, Radiotherapy

Respiratory-resolved 4D-MRIs could measure the extent of respiratory motion for online MR-guided radiotherapy on MR-Linacs. Cartesian spiral (CASPR) trajectories are an alternative to radial sampling for self-gated 4D-MRIs, because they could avoid prohibitively long image reconstruction times related to the non-uniform Fourier Transform. We studied the effect of different sampling parameters on image quality for CASPR-based sequences on an MR-Linac and reconstructed abdominal 4D-MRI, we found that increasing the number of points per spiral arm improved the reconstructed image quality, creating a trade-off between spatial and temporal resolutions.
 

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Carolin M Pirkl¹, Rolf F Schulte¹, Pablo García-Polo², Matteo Cencini³, Sebastian Endt^1,4,5, Laura Biagi³, Michela Tosetti³, and Marion I Menzel^1,4,5
1GE Healthcare, Munich, Germany, ²GE Healthcare, Madrid, Spain, ³IRCCS Stella Maris, Pisa, Italy, ⁴Technische Hochschule Ingolstadt, Ingolstadt, Germany, ⁵Technical University of Munich, Munich, Germany

Keywords: MR Fingerprinting/Synthetic MR, Data Acquisition

Highly accelerated multiparametric MRI techniques are more and more demonstrating their diagnostic potential. To achieve short scan times, these techniques rely on non-Cartesian (under-) sampling. Initially developed for MRI applications in the brain, these sequences are now also applied in body MRI. In this work, we present a phantom and in vivo study to demonstrate and evaluate the strengths and pitfalls of the two most common non-Cartesian – spiral and radial – sampling schemes for the application of rapid, free-breathing 3D T1, T2 and proton density (PD) mapping with quantitative transient-state imaging (QTI) in the prostate gland.

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Christoph Rettenmeier¹, Zidan Yu², and V. Andrew Stenger^3
1Medicine, University of Hawaii, Honolulu, HI, United States, ²Univeristy of Hawaii, Honolulu, HI, United States, ³University of Hawaii, Honolulu, HI, United States

Keywords: Data Acquisition, Brain

High quality brain images at spatial resolutions of 2x2x3 mm3 and 3.3x3.3x3 mm3 were obtained using single-shot 2D rEPI. The approach is based on an R2*, B0 and coil sensitivity informed model-based reconstruction in combination with k-space weighted image contrast (KWIC) filtering. Signal loss due to phase inconsistencies are starkly reduced by the linear phase model and R2* contrast was modifiable by adjusting the target echo time in the model of the reconstruction and KWIC filter. Bold activation maps were generated from fMRI datasets at 2x2 mm2 resolution showing activation in the visual cortex.

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Yan Wen¹, Liling Long¹, Chenhui Li¹, Huiting Zhang², and Xiaodong Zhong^3
1Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China, ²MR Scientific Marketing, Siemens Healthineers Ltd., Wuhan, China, ³MR R&D Collaborations, Siemens Medical Solutions, Los Angeles, CA, United States

Keywords: Image Reconstruction, Head & Neck/ENT

This study aimed to investigate the value of a dynamic contrast-enhanced (DCE)-MRI with golden-angle radial volumetric‑interpolated breath‑hold examination (radial-VIBE) research application sequence by comparing with conventional VIBE in patients with laryngeal and hypopharyngeal squamous cell carcinoma (SCC) under free breathing conditions. Our results showed that compared with conventional contrast-enhanced VIBE images with single phase, the morphological radial-VIBE images of multitemporal synthesis had significantly higher image quality based on subjective (edge, artifact, and confidence) and objective (signal-to-noise ratio, contrast, and contrast-to-noise ratio) assessments. Therefore, radial-VIBE can be used in DCE‑MRI examination in laryngeal and hypopharyngeal SCC in the free breathing state.

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Yu Wang¹, Xiaohui Duan¹, Mengzhu Wang², Lingjie Yang¹, Zhuoheng Yan¹, and Huijun Hu^1
1Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China, ²MR Scientific Marketing, Siemens Healthineers Ltd., Guangzhou, China

Keywords: Data Analysis, Cancer

This study investigated the utility of quantitative parameters of golden-angle radial sparse parallel (GRASP) dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) for evaluation of perfusion and differentiation of benign and malignant liver tumors. The results showed the quantitative parameters in GRASP DCE-MRI can effectively evaluate the perfusion characteristics and differentiation in liver tumors with good diagnostic performance. This indicated that the GRASP quantitative parameters may be useful to evaluate and predict the pathological stage of liver lesions.

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Biao Qu¹, Zuwen Zhang², Yewei Chen², Chen Qian², Taishan Kang³, Jianzhong Lin³, Lihua Chen⁴, Zhigang Wu⁵, Jiazheng Wang⁵, Gaofeng Zheng¹, and Xiaobo Qu^2
1Department of Instrumental and Electrical Engineering, Xiamen University, Xiamen, China, ²Department of Electronic Science, Biomedical Intelligent Cloud R&D Center, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China, ³Department of Radiology, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University,, Xiamen, China, ⁴Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China, ⁵Philips, Beijing, China

Keywords: Image Reconstruction, Image Reconstruction

Radial sampling is a fast magnetic resonance imaging technique. The projected fast iterative soft-thresholding algorithm (pFISTA) has shown the advantage to solved tight frame sparse reconstruction model for removing undersampling image artifacts. However, the convergence of this algorithm under radial sampling has not been clearly set up. In this work, the authors derived a theoretical convergence condition for this algorithm and an optimal step size was further suggested to allow the fastest convergence. Verifications were made in vivo data of static brain imaging and dynamic contrast-enhanced (DCE) liver imaging, demonstrating that the recommended parameter allowed fast convergence in radial MRI.

Xiao-Min Xu¹ and Yu-Chen Chen^1
1Radiology, Nanjing First Hospital, Nanjing, China

Keywords: Head & Neck/ENT, fMRI (resting state)

Alterations of static and dynamic brain function have been found in sensorineural hearing loss (SNHL). The combination of data-driven machine learning based classifiers and multiple imaging features can identify SNHL and healthy controls automatically. The spearman rank correlation with radial basis functional kernel support vector machine (SVM) and sigmoid SVM provides promising neural biomarkers for clinical classifier of SNHL. 

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Chloé Najac¹, Kirsten Koolstra², Tom O’Reilly¹, and Andrew Webb^1
1C.J. Gorter MRI Center, Department of Radiology, Leiden University Medical Center, Leiden, Netherlands, ²Philips, Best, Netherlands

Keywords: Low-Field MRI, New Trajectories & Spatial Encoding Methods

Low-field MRI systems (with B₀<0.1T) for point-of-care applications are becoming increasingly widespread. Imaging at low-field remains challenging due to the low intrinsic SNR. We evaluated speeding up 3D imaging using radial-based Cartesian undersampled phase-encodings (PEs). In phantoms, we tested different undersampling schemes and compared them to full in-out Cartesian PE in terms of peak SNR (PSNR) to take account of spatial resolution and image SNR. Results suggests that a radial-based Cartesian PE trajectory with an overall acceleration factor of two can be implemented while preserving image quality (PSNR~69dB with R=2 vs. ~70dB with R=1.3 in a discrete spatial resolution phantom).  

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Johanna Topalis¹, Balthasar Schachtner¹, Andreas Mittermeier¹, Philipp Wesp¹, Tobias Weber^1,2, Anna Theresa Stüber^1,2, Max Seidensticker¹, Jens Ricke¹, Katia Parodi³, Michael Ingrisch¹, and Olaf Dietrich^1
1Department of Radiology, University Hospital, LMU Munich, Munich, Germany, ²Department of Statistics, LMU Munich, Munich, Germany, ³Department of Medical Physics, Faculty of Physics, LMU Munich, Munich, Germany

Keywords: Image Reconstruction, Machine Learning/Artificial Intelligence, Radial Acquisition; Undersampled; MR-Guided Interventions

To reduce the data acquisition time and increase frame rates for image guidance during percutaneous needle interventions in the liver, k-space data can be acquired with a radial, undersampling acquisition scheme. The purpose of this work was to optimize a deep learning model for the fast reconstruction of k-space data in this context. The proposed deep learning model reconstructed artificial data with a better image quality compared to conventional reconstruction. Successful reconstruction of interventional phantom data suggests its potential for application during percutaneous needle interventions in the liver.