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Shen Q, Wu W, Chiew M, Ji Y, Woods JG, Okell TW. Efficient 3D cone trajectory design for improved combined angiographic and perfusion imaging using arterial spin labeling. Magn Reson Med 2024; 92:1568-1583. [PMID: 38767321 DOI: 10.1002/mrm.30149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Revised: 03/25/2024] [Accepted: 04/22/2024] [Indexed: 05/22/2024]
Abstract
PURPOSE To improve the spatial resolution and repeatability of a non-contrast MRI technique for simultaneous time resolved 3D angiography and perfusion imaging by developing an efficient 3D cone trajectory design. METHODS A novel parameterized 3D cone trajectory design incorporating the 3D golden angle was integrated into 4D combined angiography and perfusion using radial imaging and arterial spin labeling (CAPRIA) to achieve higher spatial resolution and sampling efficiency for both dynamic angiography and perfusion imaging with flexible spatiotemporal resolution. Numerical simulations and physical phantom scanning were used to optimize the cone design. Eight healthy volunteers were scanned to compare the original radial trajectory in 4D CAPRIA with our newly designed cone trajectory. A locally low rank reconstruction method was used to leverage the complementary k-space sampling across time. RESULTS The improved sampling in the periphery of k-space obtained with the optimized 3D cone trajectory resulted in improved spatial resolution compared with the radial trajectory in phantom scans. Improved vessel sharpness and perfusion visualization were also achieved in vivo. Less dephasing was observed in the angiograms because of the short TE of our cone trajectory and the improved k-space sampling efficiency also resulted in higher repeatability compared to the original radial approach. CONCLUSION The proposed 3D cone trajectory combined with 3D golden angle ordering resulted in improved spatial resolution and image quality for both angiography and perfusion imaging and could potentially benefit other applications that require an efficient sampling scheme with flexible spatial and temporal resolution.
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Affiliation(s)
- Qijia Shen
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Wenchuan Wu
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Mark Chiew
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
- Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Yang Ji
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Joseph G Woods
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Thomas W Okell
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
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Kolokythas O, Yaman Akcicek E, Akcicek H, Briller N, Rajamohan N, Yokoo T, Peeters HM, Revels JW, Moura Cunha G, Sahani DV, Mileto A. T1-weighted Motion Mitigation in Abdominal MRI: Technical Principles, Clinical Applications, Current Limitations, and Future Prospects. Radiographics 2024; 44:e230173. [PMID: 38990776 DOI: 10.1148/rg.230173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/13/2024]
Abstract
T1-weighted (T1W) pulse sequences are an indispensable component of clinical protocols in abdominal MRI but usually require multiple breath holds (BHs) during the examination, which not all patients can sustain. Patient motion can affect the quality of T1W imaging so that key diagnostic information, such as intrinsic signal intensity and contrast enhancement image patterns, cannot be determined. Patient motion also has a negative impact on examination efficiency, as multiple acquisition attempts prolong the duration of the examination and often remain noncontributory. Techniques for mitigation of motion-related artifacts at T1W imaging include multiple arterial acquisitions within one BH; free breathing with respiratory gating or respiratory triggering; and radial imaging acquisition techniques, such as golden-angle radial k-space acquisition (stack-of-stars). While each of these techniques has inherent strengths and limitations, the selection of a specific motion-mitigation technique is based on several factors, including the clinical task under investigation, downstream technical ramifications, patient condition, and user preference. The authors review the technical principles of free-breathing motion mitigation techniques in abdominal MRI with T1W sequences, offer an overview of the established clinical applications, and outline the existing limitations of these techniques. In addition, practical guidance for abdominal MRI protocol strategies commonly encountered in clinical scenarios involving patients with limited BH abilities is rendered. Future prospects of free-breathing T1W imaging in abdominal MRI are also discussed. ©RSNA, 2024 See the invited commentary by Fraum and An in this issue.
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Affiliation(s)
- Orpheus Kolokythas
- From the Department of Radiology, University of Washington, 1959 NE Pacific St, Box 357115, Seattle, WA 98195 (O.K., N.B., G.M.C., D.V.S., A.M.); Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah (E.Y.A., H.A.); Department of Radiology, UT Southwestern Medical Center, Dallas, Tex (N.R., T.Y.); Department of MRI Development, Philips Healthcare, Best, the Netherlands (H.M.P.); Department of Radiology, New York University Langone Health-Long Island Division, New York, NY (J.W.R.)
| | - Ebru Yaman Akcicek
- From the Department of Radiology, University of Washington, 1959 NE Pacific St, Box 357115, Seattle, WA 98195 (O.K., N.B., G.M.C., D.V.S., A.M.); Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah (E.Y.A., H.A.); Department of Radiology, UT Southwestern Medical Center, Dallas, Tex (N.R., T.Y.); Department of MRI Development, Philips Healthcare, Best, the Netherlands (H.M.P.); Department of Radiology, New York University Langone Health-Long Island Division, New York, NY (J.W.R.)
| | - Halit Akcicek
- From the Department of Radiology, University of Washington, 1959 NE Pacific St, Box 357115, Seattle, WA 98195 (O.K., N.B., G.M.C., D.V.S., A.M.); Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah (E.Y.A., H.A.); Department of Radiology, UT Southwestern Medical Center, Dallas, Tex (N.R., T.Y.); Department of MRI Development, Philips Healthcare, Best, the Netherlands (H.M.P.); Department of Radiology, New York University Langone Health-Long Island Division, New York, NY (J.W.R.)
| | - Noah Briller
- From the Department of Radiology, University of Washington, 1959 NE Pacific St, Box 357115, Seattle, WA 98195 (O.K., N.B., G.M.C., D.V.S., A.M.); Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah (E.Y.A., H.A.); Department of Radiology, UT Southwestern Medical Center, Dallas, Tex (N.R., T.Y.); Department of MRI Development, Philips Healthcare, Best, the Netherlands (H.M.P.); Department of Radiology, New York University Langone Health-Long Island Division, New York, NY (J.W.R.)
| | - Naveen Rajamohan
- From the Department of Radiology, University of Washington, 1959 NE Pacific St, Box 357115, Seattle, WA 98195 (O.K., N.B., G.M.C., D.V.S., A.M.); Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah (E.Y.A., H.A.); Department of Radiology, UT Southwestern Medical Center, Dallas, Tex (N.R., T.Y.); Department of MRI Development, Philips Healthcare, Best, the Netherlands (H.M.P.); Department of Radiology, New York University Langone Health-Long Island Division, New York, NY (J.W.R.)
| | - Takeshi Yokoo
- From the Department of Radiology, University of Washington, 1959 NE Pacific St, Box 357115, Seattle, WA 98195 (O.K., N.B., G.M.C., D.V.S., A.M.); Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah (E.Y.A., H.A.); Department of Radiology, UT Southwestern Medical Center, Dallas, Tex (N.R., T.Y.); Department of MRI Development, Philips Healthcare, Best, the Netherlands (H.M.P.); Department of Radiology, New York University Langone Health-Long Island Division, New York, NY (J.W.R.)
| | - Hans M Peeters
- From the Department of Radiology, University of Washington, 1959 NE Pacific St, Box 357115, Seattle, WA 98195 (O.K., N.B., G.M.C., D.V.S., A.M.); Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah (E.Y.A., H.A.); Department of Radiology, UT Southwestern Medical Center, Dallas, Tex (N.R., T.Y.); Department of MRI Development, Philips Healthcare, Best, the Netherlands (H.M.P.); Department of Radiology, New York University Langone Health-Long Island Division, New York, NY (J.W.R.)
| | - Jonathan W Revels
- From the Department of Radiology, University of Washington, 1959 NE Pacific St, Box 357115, Seattle, WA 98195 (O.K., N.B., G.M.C., D.V.S., A.M.); Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah (E.Y.A., H.A.); Department of Radiology, UT Southwestern Medical Center, Dallas, Tex (N.R., T.Y.); Department of MRI Development, Philips Healthcare, Best, the Netherlands (H.M.P.); Department of Radiology, New York University Langone Health-Long Island Division, New York, NY (J.W.R.)
| | - Guilherme Moura Cunha
- From the Department of Radiology, University of Washington, 1959 NE Pacific St, Box 357115, Seattle, WA 98195 (O.K., N.B., G.M.C., D.V.S., A.M.); Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah (E.Y.A., H.A.); Department of Radiology, UT Southwestern Medical Center, Dallas, Tex (N.R., T.Y.); Department of MRI Development, Philips Healthcare, Best, the Netherlands (H.M.P.); Department of Radiology, New York University Langone Health-Long Island Division, New York, NY (J.W.R.)
| | - Dushyant V Sahani
- From the Department of Radiology, University of Washington, 1959 NE Pacific St, Box 357115, Seattle, WA 98195 (O.K., N.B., G.M.C., D.V.S., A.M.); Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah (E.Y.A., H.A.); Department of Radiology, UT Southwestern Medical Center, Dallas, Tex (N.R., T.Y.); Department of MRI Development, Philips Healthcare, Best, the Netherlands (H.M.P.); Department of Radiology, New York University Langone Health-Long Island Division, New York, NY (J.W.R.)
| | - Achille Mileto
- From the Department of Radiology, University of Washington, 1959 NE Pacific St, Box 357115, Seattle, WA 98195 (O.K., N.B., G.M.C., D.V.S., A.M.); Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah (E.Y.A., H.A.); Department of Radiology, UT Southwestern Medical Center, Dallas, Tex (N.R., T.Y.); Department of MRI Development, Philips Healthcare, Best, the Netherlands (H.M.P.); Department of Radiology, New York University Langone Health-Long Island Division, New York, NY (J.W.R.)
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Yang H, Wang G, Li Z, Li H, Zheng J, Hu Y, Cao X, Liao C, Ye H, Tian Q. Artificial intelligence for neuro MRI acquisition: a review. MAGMA (NEW YORK, N.Y.) 2024; 37:383-396. [PMID: 38922525 DOI: 10.1007/s10334-024-01182-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Revised: 06/11/2024] [Accepted: 06/14/2024] [Indexed: 06/27/2024]
Abstract
OBJECT To review recent advances of artificial intelligence (AI) in enhancing the efficiency and throughput of the MRI acquisition workflow in neuroimaging, including planning, sequence design, and correction of acquisition artifacts. MATERIALS AND METHODS A comprehensive analysis was conducted on recent AI-based methods in neuro MRI acquisition. The study focused on key technological advances, their impact on clinical practice, and potential risks associated with these methods. RESULTS The findings indicate that AI-based algorithms have a substantial positive impact on the MRI acquisition process, improving both efficiency and throughput. Specific algorithms were identified as particularly effective in optimizing acquisition steps, with reported improvements in workflow efficiency. DISCUSSION The review highlights the transformative potential of AI in neuro MRI acquisition, emphasizing the technological advances and clinical benefits. However, it also discusses potential risks and challenges, suggesting areas for future research to mitigate these concerns and further enhance AI integration in MRI acquisition.
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Affiliation(s)
- Hongjia Yang
- School of Biomedical Engineering, Tsinghua University, Beijing, China
| | - Guanhua Wang
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
| | - Ziyu Li
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Haoxiang Li
- School of Biomedical Engineering, Tsinghua University, Beijing, China
| | - Jialan Zheng
- School of Biomedical Engineering, Tsinghua University, Beijing, China
| | - Yuxin Hu
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Xiaozhi Cao
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Congyu Liao
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Huihui Ye
- State Key Laboratory of Extreme Photonics and Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, China
| | - Qiyuan Tian
- School of Biomedical Engineering, Tsinghua University, Beijing, China.
- Tsinghua Laboratory of Brain and Intelligence, Tsinghua University, Beijing, China.
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Vitouš J, Jiřík R, Stračina T, Hendrych M, Nádeníček J, Macíček O, Tian Y, Krátká L, Dražanová E, Nováková M, Babula P, Panovský R, DiBella E, Starčuk Z. T1 mapping of myocardium in rats using self-gated golden-angle acquisition. Magn Reson Med 2024; 91:368-380. [PMID: 37811699 DOI: 10.1002/mrm.29846] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 07/19/2023] [Accepted: 08/10/2023] [Indexed: 10/10/2023]
Abstract
PURPOSE The aim of this study is to design a method of myocardial T1 quantification in small laboratory animals and to investigate the effects of spatiotemporal regularization and the needed acquisition duration. METHODS We propose a compressed-sensing approach to T1 quantification based on self-gated inversion-recovery radial two/three-dimensional (2D/3D) golden-angle stack-of-stars acquisition with image reconstruction performed using total-variation spatiotemporal regularization. The method was tested on a phantom and on a healthy rat, as well as on rats in a small myocardium-remodeling study. RESULTS The results showed a good match of the T1 estimates with the results obtained using the ground-truth method on a phantom and with the literature values for rats myocardium. The proposed 2D and 3D methods showed significant differences between normal and remodeling myocardium groups for acquisition lengths down to approximately 5 and 15 min, respectively. CONCLUSIONS A new 2D and 3D method for quantification of myocardial T1 in rats was proposed. We have shown the capability of both techniques to distinguish between normal and remodeling myocardial tissue. We have shown the effects of image-reconstruction regularization weights and acquisition length on the T1 estimates.
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Affiliation(s)
- Jiří Vitouš
- Institute of Scientific Instruments, Czech Academy of Sciences, Brno, Czechia
- Faculty of Electrical Engineering and Communication, Brno University of Technology, Brno, Czechia
| | - Radovan Jiřík
- Institute of Scientific Instruments, Czech Academy of Sciences, Brno, Czechia
| | - Tibor Stračina
- Department of Physiology, Masaryk University, Faculty of Medicine, Brno, Czechia
| | - Michal Hendrych
- First Department of Pathology, St. Anne's University Hospital and Faculty of Medicine Masaryk University, Brno, Czechia
| | - Jaroslav Nádeníček
- Department of Physiology, Masaryk University, Faculty of Medicine, Brno, Czechia
| | - Ondřej Macíček
- Institute of Scientific Instruments, Czech Academy of Sciences, Brno, Czechia
| | - Ye Tian
- Viterbi School of Engineering, University of Southern California, Los Angeles, California, USA
| | - Lucie Krátká
- Institute of Scientific Instruments, Czech Academy of Sciences, Brno, Czechia
| | - Eva Dražanová
- Institute of Scientific Instruments, Czech Academy of Sciences, Brno, Czechia
- Department of Pharmacology, Faculty of Medicine, Masaryk University, Brno, Czechia
| | - Marie Nováková
- Department of Physiology, Masaryk University, Faculty of Medicine, Brno, Czechia
| | - Petr Babula
- Department of Physiology, Masaryk University, Faculty of Medicine, Brno, Czechia
| | - Roman Panovský
- International Clinical Research Center, St. Anne's Faculty Hospital, Faculty of Medicine, Masaryk University, Brno, Czechia
- 1st Department of Internal Medicine/Cardioangiology, St. Anne's Faculty Hospital, Faculty of Medicine, Masaryk University, Brno, Czechia
| | - Edward DiBella
- School of Medicine, University of Utah, Salt Lake City, Utah, USA
| | - Zenon Starčuk
- Institute of Scientific Instruments, Czech Academy of Sciences, Brno, Czechia
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Wang G, Nielsen JF, Fessler JA, Noll DC. Stochastic optimization of three-dimensional non-Cartesian sampling trajectory. Magn Reson Med 2023; 90:417-431. [PMID: 37066854 PMCID: PMC10231878 DOI: 10.1002/mrm.29645] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Revised: 02/10/2023] [Accepted: 03/07/2023] [Indexed: 04/18/2023]
Abstract
PURPOSE Optimizing three-dimensional (3D) k-space sampling trajectories is important for efficient MRI yet presents a challenging computational problem. This work proposes a generalized framework for optimizing 3D non-Cartesian sampling patterns via data-driven optimization. METHODS We built a differentiable simulation model to enable gradient-based methods for sampling trajectory optimization. The algorithm can simultaneously optimize 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 can either optimize the gradient waveform (spline-based freeform optimization) or optimize properties of given sampling trajectories (such as the rotation angle of radial trajectories). Notably, the method can optimize sampling trajectories synergistically with either model-based or learning-based reconstruction methods. We proposed several strategies to alleviate the severe nonconvexity and huge computation demand posed by the large scale. The corresponding code is available as an open-source toolbox. RESULTS We applied the optimized trajectory to multiple applications including structural and functional imaging. In the simulation studies, the image quality of a 3D kooshball trajectory was improved from 0.29 to 0.22 (NRMSE) with Stochastic optimization framework for 3D NOn-Cartesian samPling trajectorY (SNOPY) optimization. In the prospective studies, by optimizing the rotation angles of a stack-of-stars (SOS) trajectory, SNOPY reduced the NRMSE of reconstructed images from 1.19 to 0.97 compared to the best empirical method (RSOS-GR). Optimizing the gradient waveform of a rotational EPI trajectory improved participants' rating of the PNS from "strong" to "mild." CONCLUSION SNOPY provides an efficient data-driven and optimization-based method to tailor non-Cartesian sampling trajectories.
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Affiliation(s)
- Guanhua Wang
- Biomedical Engineering, University of Michigan, Michigan, United States
| | | | - Jeffrey A. Fessler
- Biomedical Engineering, University of Michigan, Michigan, United States
- EECS, University of Michigan, Michigan, United States
| | - Douglas C. Noll
- Biomedical Engineering, University of Michigan, Michigan, United States
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Li Z, Huang C, Tong A, Chandarana H, Feng L. Kz-accelerated variable-density stack-of-stars MRI. Magn Reson Imaging 2023; 97:56-67. [PMID: 36577458 PMCID: PMC10072203 DOI: 10.1016/j.mri.2022.12.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 10/17/2022] [Accepted: 12/23/2022] [Indexed: 12/26/2022]
Abstract
This work aimed to develop a modified stack-of-stars golden-angle radial sampling scheme with variable-density acceleration along the slice (kz) dimension (referred to as VD-stack-of-stars) and to test this new sampling trajectory with multi-coil compressed sensing reconstruction for rapid motion-robust 3D liver MRI. VD-stack-of-stars sampling implements additional variable-density undersampling along the kz dimension, so that slice resolution (or volumetric coverage) can be increased without prolonging scan time. The new sampling trajectory (with increased slice resolution) was compared with standard stack-of-stars sampling with fully sampled kz (with standard slice resolution) in both non-contrast-enhanced free-breathing liver MRI and dynamic contrast-enhanced MRI (DCE-MRI) of the liver in volunteers. For both sampling trajectories, respiratory motion was extracted from the acquired radial data, and images were reconstructed using motion-compensated (respiratory-resolved or respiratory-weighted) dynamic radial compressed sensing reconstruction techniques. Qualitative image quality assessment (visual assessment by experienced radiologists) and quantitative analysis (as a metric of image sharpness) were performed to compare images acquired using the new and standard stack-of-stars sampling trajectories. Compared to standard stack-of-stars sampling, both non-contrast-enhanced and DCE liver MR images acquired with VD-stack-of-stars sampling presented improved overall image quality, sharper liver edges and increased hepatic vessel clarity in all image planes. The results have suggested that the proposed VD-stack-of-stars sampling scheme can achieve improved performance (increased slice resolution or volumetric coverage with better image quality) over standard stack-of-stars sampling in free-breathing DCE-MRI without increasing scan time. The reformatted coronal and sagittal images with better slice resolution may provide added clinical value.
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Affiliation(s)
- Zhitao Li
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Chenchan Huang
- Department of Radiology, New York University School of Medicine, New York, NY, USA
| | - Angela Tong
- Department of Radiology, New York University School of Medicine, New York, NY, USA
| | - Hersh Chandarana
- Department of Radiology, New York University School of Medicine, New York, NY, USA; Center for Advanced Imaging Innovation and Research (CAI(2)R), and Bernard and Irene Schwartz Center for Biomedical Imaging, New York University School of Medicine, New York, NY, USA
| | - Li Feng
- Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, USA.
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Li P, Chen J, Nan D, Zou J, Lin D, Hu Y. Motion-Aligned 4D-MRI Reconstruction using Higher Degree Total Variation and Locally Low-Rank Regularization. Magn Reson Imaging 2022; 93:97-107. [DOI: 10.1016/j.mri.2022.08.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 06/29/2022] [Accepted: 08/02/2022] [Indexed: 11/25/2022]
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Shao HC, Li T, Dohopolski MJ, Wang J, Cai J, Tan J, Wang K, Zhang Y. Real-time MRI motion estimation through an unsupervised k-space-driven deformable registration network (KS-RegNet). Phys Med Biol 2022; 67. [DOI: 10.1088/1361-6560/ac762c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2022] [Accepted: 06/06/2022] [Indexed: 11/12/2022]
Abstract
Abstract
Purpose. Real-time three-dimensional (3D) magnetic resonance (MR) imaging is challenging because of slow MR signal acquisition, leading to highly under-sampled k-space data. Here, we proposed a deep learning-based, k-space-driven deformable registration network (KS-RegNet) for real-time 3D MR imaging. By incorporating prior information, KS-RegNet performs a deformable image registration between a fully-sampled prior image and on-board images acquired from highly-under-sampled k-space data, to generate high-quality on-board images for real-time motion tracking. Methods. KS-RegNet is an end-to-end, unsupervised network consisting of an input data generation block, a subsequent U-Net core block, and following operations to compute data fidelity and regularization losses. The input data involved a fully-sampled, complex-valued prior image, and the k-space data of an on-board, real-time MR image (MRI). From the k-space data, under-sampled real-time MRI was reconstructed by the data generation block to input into the U-Net core. In addition, to train the U-Net core to learn the under-sampling artifacts, the k-space data of the prior image was intentionally under-sampled using the same readout trajectory as the real-time MRI, and reconstructed to serve an additional input. The U-Net core predicted a deformation vector field that deforms the prior MRI to on-board real-time MRI. To avoid adverse effects of quantifying image similarity on the artifacts-ridden images, the data fidelity loss of deformation was evaluated directly in k-space. Results. Compared with Elastix and other deep learning network architectures, KS-RegNet demonstrated better and more stable performance. The average (±s.d.) DICE coefficients of KS-RegNet on a cardiac dataset for the 5- , 9- , and 13-spoke k-space acquisitions were 0.884 ± 0.025, 0.889 ± 0.024, and 0.894 ± 0.022, respectively; and the corresponding average (±s.d.) center-of-mass errors (COMEs) were 1.21 ± 1.09, 1.29 ± 1.22, and 1.01 ± 0.86 mm, respectively. KS-RegNet also provided the best performance on an abdominal dataset. Conclusion. KS-RegNet allows real-time MRI generation with sub-second latency. It enables potential real-time MR-guided soft tissue tracking, tumor localization, and radiotherapy plan adaptation.
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Li S, Shen C, Ding Z, She H, Du YP. Accelerating multi-echo chemical shift encoded water-fat MRI using model-guided deep learning. Magn Reson Med 2022; 88:1851-1866. [PMID: 35649172 DOI: 10.1002/mrm.29307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 04/30/2022] [Accepted: 05/02/2022] [Indexed: 11/10/2022]
Abstract
PURPOSE To accelerate chemical shift encoded (CSE) water-fat imaging by applying a model-guided deep learning water-fat separation (MGDL-WF) framework to the undersampled k-space data. METHODS A model-guided deep learning water-fat separation framework is proposed for the acceleration using Cartesian/radial undersampling data. The proposed MGDL-WF combines the power of CSE water-fat imaging model and data-driven deep learning by jointly using a multi-peak fat model and a modified residual U-net network. The model is used to guide the image reconstruction, and the network is used to capture the artifacts induced by the undersampling. A data consistency layer is used in MGDL-WF to ensure the output images to be consistent with the k-space measurements. A Gauss-Newton iteration algorithm is adapted for the gradient updating of the networks. RESULTS Compared with the compressed sensing water-fat separation (CS-WF) algorithm/2-step procedure algorithm, the MGDL-WF increased peak signal-to-noise ratio (PSNR) by 5.31/5.23, 6.11/4.54, and 4.75 dB/1.88 dB with Cartesian sampling, and by 4.13/6.53, 2.90/4.68, and 1.68 dB/3.48 dB with radial sampling, at acceleration rates (R) of 4, 6, and 8, respectively. By using MGDL-WF, radial sampling increased the PSNR by 2.07 dB at R = 8, compared with Cartesian sampling. CONCLUSIONS The proposed MGDL-WF enables exploiting features of the water images and fat images from the undersampled multi-echo data, leading to improved performance in the accelerated CSE water-fat imaging. By using MGDL-WF, radial sampling can further improve the image quality with comparable scan time in comparison with Cartesian sampling.
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Affiliation(s)
- Shuo Li
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Chenfei Shen
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Zekang Ding
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Huajun She
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Yiping P Du
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
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10
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Feng L. Golden-Angle Radial MRI: Basics, Advances, and Applications. J Magn Reson Imaging 2022; 56:45-62. [PMID: 35396897 PMCID: PMC9189059 DOI: 10.1002/jmri.28187] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 03/23/2022] [Accepted: 03/24/2022] [Indexed: 12/21/2022] Open
Abstract
In recent years, golden‐angle radial sampling has received substantial attention and interest in the magnetic resonance imaging (MRI) community, and it has become a popular sampling trajectory for both research and clinical use. However, although the number of relevant techniques and publications has grown rapidly, there is still a lack of a review paper that provides a comprehensive overview and summary of the basics of golden‐angle rotation, the advantages and challenges/limitations of golden‐angle radial sampling, and recommendations in using different types of golden‐angle radial trajectories for MRI applications. Such a review paper is expected to be helpful both for clinicians who are interested in learning the potential benefits of golden‐angle radial sampling and for MRI physicists who are interested in exploring this research direction. The main purpose of this review paper is thus to present an overview and summary about golden‐angle radial MRI sampling. The review consists of three sections. The first section aims to answer basic questions such as: what is a golden angle; how is the golden angle calculated; why is golden‐angle radial sampling useful, and what are its limitations. The second section aims to review more advanced trajectories of golden‐angle radial sampling, including tiny golden‐angle rotation, stack‐of‐stars golden‐angle radial sampling, and three‐dimensional (3D) kooshball golden‐angle radial sampling. Their respective advantages and limitations and potential solutions to address these limitations are also discussed. Finally, the third section reviews MRI applications that can benefit from golden‐angle radial sampling and provides recommendations to readers who are interested in implementing golden‐angle radial trajectories in their MRI studies.
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Affiliation(s)
- Li Feng
- BioMedical Engineering and Imaging Institute (BMEII) and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
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11
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Bardo DME, Rubert N. Radial sequences and compressed sensing in pediatric body magnetic resonance imaging. Pediatr Radiol 2022; 52:382-390. [PMID: 34009408 DOI: 10.1007/s00247-021-05097-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/02/2021] [Revised: 03/11/2021] [Accepted: 04/28/2021] [Indexed: 12/28/2022]
Abstract
Magnetic resonance imaging (MRI) is often an ideal imaging modality for children of any age for any anatomy and for many pathologies. MRI sequences can be prescribed to produce high-resolution images of anatomical structures, characterize tissue composition, and detect physiological states and organ function. Shortening imaging sequences in any manner possible has been a topic of research and development in MRI since its emergence. Selection of imaging sequence parameters influences more than just the appearance and signal qualities of the imaged tissues; these details along with spatial encoding and data readout steps determine the time it takes to acquire an image. As each piece of image data is acquired and encoded with spatial and temporal information it is stored in k-space. As k-space is filled, either completely or partially, a diagnostic image or physiological data can be reconstructed. Shortening the length of time required for the readout step by efficiently filling k-space using compressed sensing and radial techniques is the subject of this manuscript.
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Affiliation(s)
- Dianna M E Bardo
- Phoenix Children's Hospital, 1919 E. Thomas Road, Phoenix, AZ, 85016, USA.
| | - Nicholas Rubert
- Phoenix Children's Hospital, 1919 E. Thomas Road, Phoenix, AZ, 85016, USA
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12
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Rettenmeier CA, Maziero D, Stenger VA. Three dimensional radial echo planar imaging for functional MRI. Magn Reson Med 2022; 87:193-206. [PMID: 34411342 PMCID: PMC8616809 DOI: 10.1002/mrm.28980] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Revised: 07/07/2021] [Accepted: 07/31/2021] [Indexed: 01/03/2023]
Abstract
PURPOSE To demonstrate a novel 3D radial echo planar imaging (3D REPI) sequence for flexible, rapid, and motion-robust sampling in fMRI. METHODS The 3D REPI method expands on the recently described golden angle rotated EPI trajectory using radial batched internal navigator echoes (TURBINE) approach by exploiting the unused perpendicular direction in the EPI readout to form fast analogues of rotated stack of stars or spirals trajectories that cover all 3 dimensions of k-space. An iterative conjugate gradient algorithm with SENSE reconstruction and time-segmented non-uniform fast Fourier transform (FFT) was used for parallel imaging acceleration and to account for the effects of B0 inhomogeneity. The golden angle rotation allowed for sliding window reconstruction schemes to be applied in brain BOLD fMRI experiments. RESULTS Combined whole brain visual and motor fMRI experiments were successfully carried out on a clinical 3T scanner at 2 mm isotropic and 1 × 1 × 2 mm3 resolutions using the 3D REPI design. Improved sampling characteristics and image quality were observed for twisted trajectories at the expense of prolonged readout times and off-resonance effects. The ability to correct for rigid motion correction was also demonstrated. CONCLUSIONS 3D REPI presents a flexible approach for segmented volumetric fMRI with motion correction and high in-plane spatial resolutions. Improved BOLD fMRI brain activation maps were obtained using a sliding window reconstruction.
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Affiliation(s)
- Christoph A. Rettenmeier
- Department of Medicine, John A. Burns School of Medicine, University of Hawaii, Honolulu, Hawaii, USA,Corresponding author: Christoph Rettenmeier, Ph.D., University of Hawaii John A. Burns School of Medicine, 1356 Lusitana Street, 7th floor, Honolulu, 96813 Hawaii, USA, , tel. +1 808 691 5163
| | - Danilo Maziero
- Department of Radiation Oncology, University of Miami, Miller School of Medicine, Sylvester Comprehensive Cancer Center, Miami, Florida
| | - V. Andrew Stenger
- Department of Medicine, John A. Burns School of Medicine, University of Hawaii, Honolulu, Hawaii, USA
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13
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Voskuilen L, Schoormans J, Gurney-Champion OJ, Balm AJM, Strijkers GJ, Smeele LE, Nederveen AJ. Dynamic MRI of swallowing: real-time volumetric imaging at 12 frames per second at 3 T. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2021; 35:411-419. [PMID: 34779971 PMCID: PMC9188511 DOI: 10.1007/s10334-021-00973-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/24/2021] [Revised: 10/10/2021] [Accepted: 10/18/2021] [Indexed: 11/25/2022]
Abstract
Objective Dysphagia or difficulty in swallowing is a potentially hazardous clinical problem that needs regular monitoring. Real-time 2D MRI of swallowing is a promising radiation-free alternative to the current clinical standard: videofluoroscopy. However, aspiration may be missed if it occurs outside this single imaged slice. We therefore aimed to image swallowing in 3D real time at 12 frames per second (fps). Materials and methods At 3 T, three 3D real-time MRI acquisition approaches were compared to the 2D acquisition: an aligned stack-of-stars (SOS), and a rotated SOS with a golden-angle increment and with a tiny golden-angle increment. The optimal 3D acquisition was determined by computer simulations and phantom scans. Subsequently, five healthy volunteers were scanned and swallowing parameters were measured. Results Although the rotated SOS approaches resulted in better image quality in simulations, in practice, the aligned SOS performed best due to the limited number of slices. The four swallowing phases could be distinguished in 3D real-time MRI, even though the spatial blurring was stronger than in 2D. The swallowing parameters were similar between 2 and 3D. Conclusion At a spatial resolution of 2-by-2-by-6 mm with seven slices, swallowing can be imaged in 3D real time at a frame rate of 12 fps. Supplementary Information The online version contains supplementary material available at 10.1007/s10334-021-00973-6.
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Affiliation(s)
- Luuk Voskuilen
- Department of Head and Neck Oncology and Surgery, Netherlands Cancer Institute, Antoni van Leeuwenhoek, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands. .,Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, University of Amsterdam, Cancer Center Amsterdam, Amsterdam, The Netherlands. .,Academic Centre for Dentistry Amsterdam and Academic Medical Center, University of Amsterdam and VU University Amsterdam, Amsterdam, The Netherlands.
| | - Jasper Schoormans
- Biomedical Engineering and Physics, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Oliver J Gurney-Champion
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, University of Amsterdam, Cancer Center Amsterdam, Amsterdam, The Netherlands
| | - Alfons J M Balm
- Department of Head and Neck Oncology and Surgery, Netherlands Cancer Institute, Antoni van Leeuwenhoek, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands.,Department of Oral and Maxillofacial Surgery, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands.,Robotics and Mechatronics, faculty of EEMCS, TechMed Center, University of Twente, Enschede, The Netherlands
| | - Gustav J Strijkers
- Biomedical Engineering and Physics, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Ludi E Smeele
- Department of Head and Neck Oncology and Surgery, Netherlands Cancer Institute, Antoni van Leeuwenhoek, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands.,Department of Oral and Maxillofacial Surgery, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands
| | - Aart J Nederveen
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, University of Amsterdam, Cancer Center Amsterdam, Amsterdam, The Netherlands
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14
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McLean M, Parker DL, Odéen H, Payne A. A T1-based correction method for proton resonance frequency shift thermometry in breast tissue. Med Phys 2021; 48:4719-4729. [PMID: 34265109 DOI: 10.1002/mp.15085] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 05/30/2021] [Accepted: 06/01/2021] [Indexed: 11/06/2022] Open
Abstract
PURPOSE Develop and evaluate the effectiveness of a T1-based correction method for errors in proton resonant frequency shift thermometry due to non-local field effects caused by heating in fatty breast tissues. METHODS Computational models of human breast tissue were created by segmenting MRI data from a healthy human volunteer. MR-guided focused ultrasound (MRgFUS) heating and MR thermometry measurements were simulated in several locations in the heterogeneous segmented breast models. A T1-based correction method for PRF thermometry errors was applied and the maximum positive and negative errors and the root mean squared error (RMSE) in a region around each heating location was evaluated with and without correction. The method uses T1 measurements to estimate the temperature change in fatty tissues and correct for their influence. Experimental data from a heating study in cadaver breast tissue were analyzed, and the expected PRFS error computed. RESULTS The simulated MR thermometry had maximum single voxel errors ranging between 10% and 18% when no correction was applied. Applying the correction led to a considerable improvement, lowering the maximum error range to 2%-5%. The 5th to 95th percentile interval of the temperature error distribution was also lowered with correction, from approximately 3.5 to 1°C. This correction worked even when T1 times were uniformly raised or lowered by 5%-10%. The experimental data showed predicted errors of 15%. CONCLUSIONS This simulation study demonstrates that the T1-based correction method reduces MR thermometry errors due to non-local effects from heating in fatty tissues, potentially improving the accuracy of thermometry measurements during MRgFUS treatments. The presented correction method is reliant on having a patient-specific 3D model of the breast, and may be limited by the accuracy of the fat temperatures which in turn may be limited by noise or bias present in the T1 measurements.
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15
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Balasch A, Büttner MS, Metze P, Stumpf K, Beer M, Rottbauer W, Rasche V. Tiny golden angle stack-of-stars (tygaSoS) free-breathing functional lung imaging. Magn Reson Imaging 2021; 82:24-30. [PMID: 34153438 DOI: 10.1016/j.mri.2021.06.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Revised: 04/21/2021] [Accepted: 06/15/2021] [Indexed: 11/26/2022]
Abstract
PURPOSE MRI of the lung parenchyma is still challenging due to cardiac and respiratory motion, and the low proton density and short T2*. Clinical feasible MRI methods for functional lung assessment are of great interest. It was the objective of this study to evaluate the potential of combining the ultra-short echo-time stack-of-stars approach with tiny golden angle (tyGASoS) profile ordering for self-gated free-breathing lung imaging. METHODS Free-breathing tyGASoS data were acquired in 10 healthy volunteers (3 smoker (S), 7 non-smoker (NS)). Images in different respiratory phases were reconstructed applying an image-based self-gating technique. Resulting image quality and sharpness, and parenchyma visibility were qualitatively scored by three blinded independent reader, and the signal-to-noise ratio (SNR), proton fraction (fP) and fractional ventilation (FV) quantified. RESULT The imaging protocol was well tolerated by all volunteers. Image quality was sufficient for subsequent quantitative analysis in all cases with good to excellent inter-reader reliability. Between expiration (EX) and inspiration (IN) significant differences (p < 0.001) were observed in SNR (EX: 3.73 ± 0.89, IN: 3.14 ± 0.74) and fP (EX: 0.27 ± 0.09, IN: 0.25 ± 0.08). A significant (p < 0.05) higher fP (EX/IN: 0.22 ± 0.07/0.21 ± 0.07 (NS), 0.33 ± 0.07/0.30 ± 0.06 (S)) was observed in the smoker group. No significant FV differences resulted between S and NS. CONCLUSION The study proves the feasibility of free-breathing tyGASoS for multiphase lung imaging. Changes in fP may indicate an initial response in the smoker group and as such proves the sensitivity of the proposed technique. A major limitation in FV quantification rises from the large inter-subject variability of breathing patterns and amplitudes, requiring further consideration.
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Affiliation(s)
- A Balasch
- Department of Internal Medicine II, Ulm University Medical Centre, Ulm, Germany.
| | - M S Büttner
- Department of Radiology, Ulm University Medical Centre, Ulm, Germany.
| | - P Metze
- Department of Internal Medicine II, Ulm University Medical Centre, Ulm, Germany.
| | - K Stumpf
- Department of Internal Medicine II, Ulm University Medical Centre, Ulm, Germany.
| | - M Beer
- Department of Radiology, Ulm University Medical Centre, Ulm, Germany.
| | - W Rottbauer
- Department of Internal Medicine II, Ulm University Medical Centre, Ulm, Germany.
| | - V Rasche
- Department of Internal Medicine II, Ulm University Medical Centre, Ulm, Germany.
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16
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Wang X, Rosenzweig S, Scholand N, Holme HCM, Uecker M. Model-based reconstruction for simultaneous multi-slice T1 mapping using single-shot inversion-recovery radial FLASH. Magn Reson Med 2021; 85:1258-1271. [PMID: 32936487 PMCID: PMC10409492 DOI: 10.1002/mrm.28497] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Revised: 08/03/2020] [Accepted: 08/04/2020] [Indexed: 01/17/2023]
Abstract
PURPOSE To develop a single-shot multi-slice T 1 mapping method by combing simultaneous multi-slice (SMS) excitations, single-shot inversion-recovery (IR) radial fast low-angle shot (FLASH), and a nonlinear model-based reconstruction method. METHODS SMS excitations are combined with a single-shot IR radial FLASH sequence for data acquisition. A previously developed single-slice calibrationless model-based reconstruction is extended to SMS, formulating the estimation of parameter maps and coil sensitivities from all slices as a single nonlinear inverse problem. Joint-sparsity constraints are further applied to the parameter maps to improve T 1 precision. Validations of the proposed method are performed for a phantom and for the human brain and liver in 6 healthy adult subjects. RESULTS Phantom results confirm good T 1 accuracy and precision of the simultaneously acquired multi-slice T 1 maps in comparison to single-slice references. In vivo human brain studies demonstrate the better performance of SMS acquisitions compared to the conventional spoke-interleaved multi-slice acquisition using model-based reconstruction. Aside from good accuracy and precision, the results of 6 healthy subjects in both brain and abdominal studies confirm good repeatability between scan and re-scans. The proposed method can simultaneously acquire T 1 maps for 5 slices of a human brain ( 0.75 × 0.75 × 5 mm 3 ) or 3 slices of the abdomen ( 1.25 × 1.25 × 6 mm 3 ) within 4 seconds. CONCLUSIONS The IR SMS radial FLASH acquisition together with a nonlinear model-based reconstruction enable rapid high-resolution multi-slice T 1 mapping with good accuracy, precision, and repeatability.
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Affiliation(s)
- Xiaoqing Wang
- Institute for Diagnostic and Interventional Radiology of the University Medical Center Göttingen, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Göttingen, Germany
| | - Sebastian Rosenzweig
- Institute for Diagnostic and Interventional Radiology of the University Medical Center Göttingen, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Göttingen, Germany
| | - Nick Scholand
- Institute for Diagnostic and Interventional Radiology of the University Medical Center Göttingen, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Göttingen, Germany
| | - H. Christian M. Holme
- Institute for Diagnostic and Interventional Radiology of the University Medical Center Göttingen, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Göttingen, Germany
| | - Martin Uecker
- Institute for Diagnostic and Interventional Radiology of the University Medical Center Göttingen, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Göttingen, Germany
- Cluster of Excellence “Multiscale Bioimaging: from Molecular Machines to Networks of Excitable Cells” (MBExC), University of Göttingen, Germany
- Campus Institute Data Science (CIDAS), University of Göttingen, Germany
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Zhao Z, Lim Y, Byrd D, Narayanan S, Nayak KS. Improved 3D real-time MRI of speech production. Magn Reson Med 2021; 85:3182-3195. [PMID: 33452722 DOI: 10.1002/mrm.28651] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2020] [Revised: 10/29/2020] [Accepted: 11/26/2020] [Indexed: 01/21/2023]
Abstract
PURPOSE To provide 3D real-time MRI of speech production with improved spatio-temporal sharpness using randomized, variable-density, stack-of-spiral sampling combined with a 3D spatio-temporally constrained reconstruction. METHODS We evaluated five candidate (k, t) sampling strategies using a previously proposed gradient-echo stack-of-spiral sequence and a 3D constrained reconstruction with spatial and temporal penalties. Regularization parameters were chosen by expert readers based on qualitative assessment. We experimentally determined the effect of spiral angle increment and kz temporal order. The strategy yielding highest image quality was chosen as the proposed method. We evaluated the proposed and original 3D real-time MRI methods in 2 healthy subjects performing speech production tasks that invoke rapid movements of articulators seen in multiple planes, using interleaved 2D real-time MRI as the reference. We quantitatively evaluated tongue boundary sharpness in three locations at two speech rates. RESULTS The proposed data-sampling scheme uses a golden-angle spiral increment in the kx -ky plane and variable-density, randomized encoding along kz . It provided a statistically significant improvement in tongue boundary sharpness score (P < .001) in the blade, body, and root of the tongue during normal and 1.5-times speeded speech. Qualitative improvements were substantial during natural speech tasks of alternating high, low tongue postures during vowels. The proposed method was also able to capture complex tongue shapes during fast alveolar consonant segments. Furthermore, the proposed scheme allows flexible retrospective selection of temporal resolution. CONCLUSION We have demonstrated improved 3D real-time MRI of speech production using randomized, variable-density, stack-of-spiral sampling with a 3D spatio-temporally constrained reconstruction.
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Affiliation(s)
- Ziwei Zhao
- Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA
| | - Yongwan Lim
- Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA
| | - Dani Byrd
- Department of Linguistics, Dornsife College of Letters, Arts and Sciences, University of Southern California, Los Angeles, CA, USA
| | - Shrikanth Narayanan
- Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA.,Department of Linguistics, Dornsife College of Letters, Arts and Sciences, University of Southern California, Los Angeles, CA, USA
| | - Krishna S Nayak
- Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA
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Darçot E, Yerly J, Hilbert T, Colotti R, Najdenovska E, Kober T, Stuber M, van Heeswijk RB. Compressed sensing with signal averaging for improved sensitivity and motion artifact reduction in fluorine-19 MRI. NMR IN BIOMEDICINE 2021; 34:e4418. [PMID: 33002268 DOI: 10.1002/nbm.4418] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/26/2019] [Revised: 09/09/2020] [Accepted: 09/11/2020] [Indexed: 06/11/2023]
Abstract
Fluorine-19 (19 F) MRI of injected perfluorocarbon emulsions (PFCs) allows for the non-invasive quantification of inflammation and cell tracking, but suffers from a low signal-to-noise ratio and extended scan time. To address this limitation, we tested the hypotheses that a 19 F MRI pulse sequence that combines a specific undersampling regime with signal averaging has both increased sensitivity and robustness against motion artifacts compared with a non-averaged fully sampled pulse sequence, when both datasets are reconstructed with compressed sensing. As a proof of principle, numerical simulations and phantom experiments were performed on selected variable ranges to characterize the point spread function of undersampling patterns, as well as the vulnerability to noise of undersampling and reconstruction parameters with paired numbers of x signal averages and acceleration factor x (NAx-AFx). The numerical simulations demonstrated that a probability density function that uses 25% of the samples to fully sample the k-space central area allowed for an optimal balance between limited blurring and artifact incoherence. At all investigated noise levels, the Dice similarity coefficient (DSC) strongly depended on the regularization parameters and acceleration factor. In phantoms, the motion robustness of an NA8-AF8 undersampling pattern versus NA1-AF1 was evaluated with simulated and real motion patterns. Differences were assessed with the DSC, which was consistently higher for the NA8-AF8 compared with the NA1-AF1 strategy, for both simulated and real cyclic motion patterns (P < 0.001). Both strategies were validated in vivo in mice (n = 2) injected with perfluoropolyether. Here, the images displayed a sharper delineation of the liver with the NA8-AF8 strategy than with the NA1-AF1 strategy. In conclusion, we validated the hypotheses that in 19 F MRI the combination of undersampling and averaging improves both the sensitivity and the robustness against motion artifacts.
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Affiliation(s)
- Emeline Darçot
- Department of Radiology, University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Jérôme Yerly
- Department of Radiology, University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Lausanne and Geneva, Switzerland
| | - Tom Hilbert
- Department of Radiology, University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Advanced Clinical Imaging Technology (HC CMEA SUI DI PI), Siemens Healthcare AG, Lausanne, Switzerland
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Roberto Colotti
- Department of Radiology, University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Elena Najdenovska
- Department of Radiology, University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Lausanne and Geneva, Switzerland
| | - Tobias Kober
- Department of Radiology, University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Advanced Clinical Imaging Technology (HC CMEA SUI DI PI), Siemens Healthcare AG, Lausanne, Switzerland
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Matthias Stuber
- Department of Radiology, University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Lausanne and Geneva, Switzerland
| | - Ruud B van Heeswijk
- Department of Radiology, University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Lausanne and Geneva, Switzerland
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19
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Heidari Pahlavian S, Geri O, Russin J, Ma SJ, Amar A, Wang DJJ, Ben Bashat D, Yan L. Semiautomatic cerebrovascular territory mapping based on dynamic ASL MR angiography without vessel-encoded labeling. Magn Reson Med 2020; 85:2735-2746. [PMID: 33347641 DOI: 10.1002/mrm.28623] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Revised: 11/07/2020] [Accepted: 11/09/2020] [Indexed: 11/11/2022]
Abstract
PURPOSE Characterizing vessel territories can provide crucial information for evaluation of cerebrovascular disorders. In this study, we present a novel postprocessing pipeline for vascular territorial imaging of cerebral arteries based on a noncontrast enhanced time-resolved 4D magnetic resonance angiography (MRA). METHODS Eight healthy participants, 1 Moyamoya patient, and 1 arteriovenous malformations patient were recruited. Territorial segmentation and relative blood flow rate calculations of cerebral arteries including left and right middle cerebral arteries and left and right posterior cerebral arteries were carried out based on the 4D MRA-derived arterial arrival time maps of intracranial vessels. RESULTS Among healthy young subjects, the average relative blood flow rate values corresponding to left and right middle cerebral arteries and left and right posterior cerebral arteries were 35.9 ± 5.9%, 32.9 ± 7.5%, 15.4 ± 3.8%, and 15.9 ± 2.5%, respectively. Excellent agreement was observed between relative blood flow rate values obtained from the proposed 4D MRA-based method and reference 2D phase contrast MRI. Abnormal cerebral circulations were visualized and quantified on both patients using the developed technique. CONCLUSION The vascular territorial imaging technique developed in this study allowed for the generation of territorial maps with user-defined level of details within a clinically feasible scan time, and as such may provide useful information to assess cerebral circulation balance in different pathologies.
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Affiliation(s)
- Soroush Heidari Pahlavian
- USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.,Department of Neurology, University of Southern California, Los Angeles, CA, USA
| | | | - Jonathan Russin
- Department of Neurosurgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Samantha J Ma
- USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.,Department of Neurology, University of Southern California, Los Angeles, CA, USA
| | - Arun Amar
- Department of Neurosurgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Danny J J Wang
- USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.,Department of Neurology, University of Southern California, Los Angeles, CA, USA
| | - Dafna Ben Bashat
- Sagol Brain Institute, Tel Aviv Sourasky Medical Center, Sackler Faculty of Medicine & Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - Lirong Yan
- USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.,Department of Neurology, University of Southern California, Los Angeles, CA, USA
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Rosenzweig S, Scholand N, Holme HCM, Uecker M. Cardiac and Respiratory Self-Gating in Radial MRI Using an Adapted Singular Spectrum Analysis (SSA-FARY). IEEE TRANSACTIONS ON MEDICAL IMAGING 2020; 39:3029-3041. [PMID: 32275585 DOI: 10.1109/tmi.2020.2985994] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Cardiac Magnetic Resonance Imaging (MRI) is time-consuming and error-prone. To ease the patient's burden and to increase the efficiency and robustness of cardiac exams, interest in methods based on continuous steady-state acquisition and self-gating has been growing in recent years. Self-gating methods extract the cardiac and respiratory signals from the measurement data and then retrospectively sort the data into cardiac and respiratory phases. Repeated breathholds and synchronization with the heart beat using some external device as required in conventional MRI are then not necessary. In this work, we introduce a novel self-gating method for radially acquired data based on a dimensionality reduction technique for time-series analysis (SSA-FARY). Building on Singular Spectrum Analysis, a zero-padded, time-delayed embedding of the auto-calibration data is analyzed using Principle Component Analysis. We demonstrate the basic functionality of SSA-FARY using numerical simulations and apply it to in-vivo cardiac radial single-slice bSSFP and Simultaneous Multi-Slice radiofrequency-spoiled gradient-echo measurements, as well as to Stack-of-Stars bSSFP measurements. SSA-FARY reliably detects the cardiac and respiratory motion and separates it from noise. We utilize the generated signals for high-dimensional image reconstruction using parallel imaging and compressed sensing with in-plane wavelet and (spatio-)temporal total-variation regularization.
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Utzschneider M, Müller M, Gast LV, Lachner S, Behl NGR, Maier A, Uder M, Nagel AM. Towards accelerated quantitative sodium MRI at 7 T in the skeletal muscle: Comparison of anisotropic acquisition- and compressed sensing techniques. Magn Reson Imaging 2020; 75:72-88. [PMID: 32979516 DOI: 10.1016/j.mri.2020.09.019] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2020] [Revised: 08/25/2020] [Accepted: 09/14/2020] [Indexed: 12/14/2022]
Abstract
PURPOSE To compare three anisotropic acquisition schemes and three compressed sensing (CS) approaches for accelerated tissue sodium concentration (TSC) quantification using 23Na MRI at 7 T. MATERIALS AND METHODS Three anisotropic 3D-radial acquisition sequences were evaluated using simulations, phantom- and in vivo TSC measurements: An anisotropic density-adapted 3D-radial sequence (3DPR-C), a 3D acquisition-weighted density-adapted stack-of-stars sampling scheme (SOS) and a SOS approach with golden-ratio rotation (SOS-GR). Eight healthy volunteers were examined at a 7 Tesla MRI system. TSC measurements of the calf were conducted with a nominal spatial resolution of Δx = (3.0 × 3.0 × 15.0) mm3 and a field of view of (156.0 × 156.0 × 240.0) mm3 for multiple undersampling factors (USF). Three CS reconstructions were evaluated: Total variation CS (TV-CS), 3D dictionary-learning compressed sensing (3D-DLCS) and TV-CS with a block matching prior (TV-BL-CS). Results of the simulations and measurements were compared to a simulated ground truth (GT) or a fully sampled reference measurement (FS), respectively. The deviation of the mean TSC evaluated in multiple ROI (mEGT/FS) and the normalized root-mean-squared error (NRMSE) for simulations were evaluated for CS and NUFFT reconstructions. RESULTS In simulations, the SOS-GR yielded the lowest NRMSE and mEGT (< 4%) with NUFFT for an acquisition time (TA) of less than 2 min. CS further improved the results. In simulations and measurements, the best TSC quantification results were obtained with 3D-DLCS and SOS-GR (lowest NRMSE, mEGT < 2.6% in simulations, mEGT < 10.7% for phantom measurements and mEFS < 6% in vivo) with an USF = 4.1 (TA < 2 min). TV-CS showed no or only slight improvements to NUFFT. The results of TV-BL-CS were similar to 3D-DLCS. DISCUSSION The TA for TSC measurements could be reduced to less than 2 min by using adapted sequences such as SOS-GR and CS reconstruction approaches such as 3D-DLCS or TV-BL-CS, while the quantitative accuracy stays comparable to a fully sampled NUFFT reconstruction (approx. 8 min TA). In future, the lower TA could improve clinical applicability of TSC measurements.
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Affiliation(s)
- Matthias Utzschneider
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany; Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.
| | - Max Müller
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Lena V Gast
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany; Institute of Medical Physics, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Sebastian Lachner
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Nicolas G R Behl
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Andreas Maier
- Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Michael Uder
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Armin M Nagel
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany; Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany; Institute of Medical Physics, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
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22
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Munsch F, Taso M, Zhao L, Lebel RM, Guidon A, Detre JA, Alsop DC. Rotated spiral RARE for high spatial and temporal resolution volumetric arterial spin labeling acquisition. Neuroimage 2020; 223:117371. [PMID: 32931943 PMCID: PMC9470008 DOI: 10.1016/j.neuroimage.2020.117371] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Revised: 09/08/2020] [Accepted: 09/09/2020] [Indexed: 12/29/2022] Open
Abstract
Background: Arterial Spin Labeling (ASL) MRI can provide quantitative images that are sensitive to both time averaged blood flow and its temporal fluctuations. 3D image acquisitions for ASL are desirable because they are more readily compatible with background suppression to reduce noise, can reduce signal loss and distortion, and provide uniform flow sensitivity across the brain. However, single-shot 3D acquisition for maximal temporal resolution typically involves degradation of image quality through blurring or noise amplification by parallel imaging. Here, we report a new approach to accelerate a common stack of spirals 3D image acquisition by pseudo golden-angle rotation and compressed sensing reconstruction without any degradation of time averaged blood flow images. Methods: 28 healthy volunteers were imaged at 3T with background-suppressed unbalanced pseudo-continuous ASL combined with a pseudo golden-angle Stack-of-Spirals 3D RARE readout. A fully-sampled perfusion-weighted volume was reconstructed by 3D non-uniform Fast Fourier Transform (nuFFT) followed by sum-of-squares combination of the 32 individual channels. Coil sensitivities were estimated followed by reconstruction of the 39 single-shot volumes using an L1-wavelet Compressed-Sensing reconstruction. Finally, brain connectivity analyses were performed in regions where BOLD signal suffers from low signal-to-noise ratio and susceptibility artifacts. Results: Image quality, assessed with a non-reference 3D blurring metric, of full time averaged blood flow was comparable to a conventional interleaved acquisition. The temporal resolution provided by the acceleration enabled identification and quantification of resting-state networks even in inferior regions such as the amygdala and inferior frontal lobes, where susceptibility artifacts can degrade conventional resting-state fMRI acquisitions. Conclusion: This approach can provide measures of blood flow modulations and resting-state networks for free within any research or clinical protocol employing ASL for resting blood flow.
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Affiliation(s)
- Fanny Munsch
- Division of MRI Research, Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, 330 Brookline Avenue, Boston, MA 02215, USA.
| | - Manuel Taso
- Division of MRI Research, Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, 330 Brookline Avenue, Boston, MA 02215, USA
| | - Li Zhao
- Diagnostic Imaging and Radiology, Children's National Hospital, Washington, DC, USA
| | - R Marc Lebel
- Global MR Applications and Workflow, GE Healthcare, Calgary, AB, Canada
| | - Arnaud Guidon
- Global MR Applications and Workflow, GE Healthcare, Boston, MA, USA
| | - John A Detre
- Departments of Neurology and Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - David C Alsop
- Division of MRI Research, Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, 330 Brookline Avenue, Boston, MA 02215, USA
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23
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Tian Y, Mendes J, Wilson B, Ross A, Ranjan R, DiBella E, Adluru G. Whole-heart, ungated, free-breathing, cardiac-phase-resolved myocardial perfusion MRI by using Continuous Radial Interleaved simultaneous Multi-slice acquisitions at sPoiled steady-state (CRIMP). Magn Reson Med 2020; 84:3071-3087. [PMID: 32492235 DOI: 10.1002/mrm.28337] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2019] [Revised: 04/28/2020] [Accepted: 05/01/2020] [Indexed: 11/09/2022]
Abstract
PURPOSE To develop a whole-heart, free-breathing, non-electrocardiograph (ECG)-gated, cardiac-phase-resolved myocardial perfusion MRI framework (CRIMP; Continuous Radial Interleaved simultaneous Multi-slice acquisitions at sPoiled steady-state) and test its quantification feasibility. METHODS CRIMP used interleaved radial simultaneous multi-slice (SMS) slice groups to cover the whole heart in 9 or 12 short-axis slices. The sequence continuously acquired data without magnetization preparation, ECG gating or breath-holding, and captured multiple cardiac phases. Images were reconstructed by a motion-compensated patch-based locally low-rank reconstruction. Bloch simulations were performed to study the signal-to-noise ratio/contrast-to-noise ratio (SNR/CNR) for CRIMP and to study the steady-state signal under motion. Seven patients were scanned with CRIMP at stress and rest to develop the sequence. One human and two dogs were scanned at rest with a dual-bolus method to test the quantification feasibility of CRIMP. The dual-bolus scans were performed using both CRIMP and an ungated radial SMS saturation recovery (SMS-SR) sequence with injection dose = 0.075 mmol/kg to compare the sequences in terms of SNR, cardiac phase resolution and quantitative myocardial blood flow (MBF). RESULTS Perfusion images with multiple cardiac phases in all image slices with a temporal resolution of 72 ms/frame were obtained. Simulations and in-vivo acquisitions showed CRIMP kept the inner slices in steady-state regardless of motion. CRIMP outperformed SMS-SR in slice coverage (9 over 6), SNR (mean 20% improvement), and provided cardiac phase resolution. CRIMP and SMS-SR sequences provided comparable MBF values (rest systolic CRIMP = 0.58 ± 0.07, SMS-SR = 0.61 ± 0.16). CONCLUSION CRIMP allows for whole-heart, cardiac-phase-resolved myocardial perfusion images without ECG-gating or breath-holding. The sequence can provide MBF if an accurate arterial input function is obtained separately.
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Affiliation(s)
- Ye Tian
- Utah Center for Advanced Imaging Research (UCAIR), Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah, USA.,Department of Physics and Astronomy, University of Utah, Salt Lake City, Utah, USA
| | - Jason Mendes
- Utah Center for Advanced Imaging Research (UCAIR), Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah, USA
| | - Brent Wilson
- Division of Cardiovascular Medicine, University of Utah, Salt Lake City, Utah, USA
| | - Alexander Ross
- Division of Cardiovascular Medicine, University of Utah, Salt Lake City, Utah, USA
| | - Ravi Ranjan
- Division of Cardiovascular Medicine, University of Utah, Salt Lake City, Utah, USA
| | - Edward DiBella
- Utah Center for Advanced Imaging Research (UCAIR), Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah, USA.,Department of Biomedical Engineering, University of Utah, Salt Lake City, Utah, USA
| | - Ganesh Adluru
- Utah Center for Advanced Imaging Research (UCAIR), Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah, USA.,Department of Biomedical Engineering, University of Utah, Salt Lake City, Utah, USA
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24
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Utzschneider M, Behl NGR, Lachner S, Gast LV, Maier A, Uder M, Nagel AM. Accelerated quantification of tissue sodium concentration in skeletal muscle tissue: quantitative capability of dictionary learning compressed sensing. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2020; 33:495-505. [DOI: 10.1007/s10334-019-00819-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2019] [Revised: 11/22/2019] [Accepted: 12/17/2019] [Indexed: 12/11/2022]
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25
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Zhang L, Armstrong T, Li X, Wu HH. A variable flip angle golden-angle-ordered 3D stack-of-radial MRI technique for simultaneous proton resonant frequency shift and T 1 -based thermometry. Magn Reson Med 2019; 82:2062-2076. [PMID: 31257639 DOI: 10.1002/mrm.27883] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2019] [Revised: 06/02/2019] [Accepted: 06/07/2019] [Indexed: 02/06/2023]
Abstract
PURPOSE To develop and evaluate a variable-flip-angle golden-angle-ordered 3D stack-of-radial MRI technique for simultaneous proton resonance frequency shift (PRF) and T1 -based thermometry in aqueous and adipose tissues, respectively. METHODS The proposed technique acquires multiecho radial k-space data in segments with alternating flip angles to measure 3D temperature maps dynamically on the basis of PRF and T1 . A sliding-window k-space weighted image contrast filter is used to increase temporal resolution. PRF is measured in aqueous tissues and T1 in adipose tissues using fat/water masks. The accuracy for T1 quantification was evaluated in a reference T1 /T2 phantom. In vivo nonheating experiments were conducted in healthy subjects to evaluate the stability of PRF and T1 in the brain, prostate, and breast. The proposed technique was used to monitor high-intensity focused ultrasound (HIFU) ablation in ex vivo porcine fat/muscle tissues and compared to temperature probe readings. RESULTS The proposed technique achieved 3D coverage with 1.1-mm to 1.3-mm in-plane resolution and 2-s to 5-s temporal resolution. During 20 to 30 min of nonheating in vivo scans, the temporal coefficient of variation for T1 was <5% in the brain, prostate, and breast fatty tissues, while the standard deviation of relative PRF temperature change was within 3°C in aqueous tissues. During ex vivo HIFU ablation, the temperatures measured by PRF and T1 were consistent with temperature probe readings, with an absolute mean difference within 2°C. CONCLUSION The proposed technique achieves simultaneous PRF and T1 -based dynamic 3D MR temperature mapping in aqueous and adipose tissues. It may be used to improve MRI-guided thermal procedures.
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Affiliation(s)
- Le Zhang
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Tess Armstrong
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California.,Physics in Biology and Medicine Interdepartmental Graduate Program, University of California Los Angeles, Los Angeles, California
| | - Xinzhou Li
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California.,Department of Bioengineering, University of California Los Angeles, Los Angeles, California
| | - Holden H Wu
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California.,Physics in Biology and Medicine Interdepartmental Graduate Program, University of California Los Angeles, Los Angeles, California.,Department of Bioengineering, University of California Los Angeles, Los Angeles, California
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26
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Luo T, Noll DC, Fessler JA, Nielsen JF. A GRAPPA algorithm for arbitrary 2D/3D non-Cartesian sampling trajectories with rapid calibration. Magn Reson Med 2019; 82:1101-1112. [PMID: 31050011 DOI: 10.1002/mrm.27801] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2019] [Revised: 04/03/2019] [Accepted: 04/16/2019] [Indexed: 12/11/2022]
Abstract
PURPOSE GRAPPA is a popular reconstruction method for Cartesian parallel imaging, but is not easily extended to non-Cartesian sampling. We introduce a general and practical GRAPPA algorithm for arbitrary non-Cartesian imaging. METHODS We formulate a general GRAPPA reconstruction by associating a unique kernel with each unsampled k-space location with a distinct constellation, that is, local sampling pattern. We calibrate these generalized kernels using the Fourier transform phase shift property applied to fully gridded or separately acquired Cartesian Autocalibration signal (ACS) data. To handle the resulting large number of different kernels, we introduce a fast calibration algorithm based on nonuniform FFT (NUFFT) and adoption of circulant ACS boundary conditions. We applied our method to retrospectively under-sampled rotated stack-of-stars/spirals in vivo datasets, and to a prospectively under-sampled rotated stack-of-spirals functional MRI acquisition with a finger-tapping task. RESULTS We reconstructed all datasets without performing any trajectory-specific manual adaptation of the method. For the retrospectively under-sampled experiments, our method achieved image quality (i.e., error and g-factor maps) comparable to conjugate gradient SENSE (cg-SENSE) and SPIRiT. Functional activation maps obtained from our method were in good agreement with those obtained using cg-SENSE, but required a shorter total reconstruction time (for the whole time-series): 3 minutes (proposed) vs 15 minutes (cg-SENSE). CONCLUSIONS This paper introduces a general 3D non-Cartesian GRAPPA that is fast enough for practical use on today's computers. It is a direct generalization of original GRAPPA to non-Cartesian scenarios. The method should be particularly useful in dynamic imaging where a large number of frames are reconstructed from a single set of ACS data.
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Affiliation(s)
- Tianrui Luo
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan
| | - Douglas C Noll
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan
| | - Jeffrey A Fessler
- Department of Electrical and Computer Engineering, University of Michigan, Ann Arbor, Michigan
| | - Jon-Fredrik Nielsen
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan
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27
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Svedin BT, Payne A, Parker DL. Simultaneous proton resonance frequency shift thermometry and T 1 measurements using a single reference variable flip angle T 1 method. Magn Reson Med 2019; 81:3138-3152. [PMID: 30652347 DOI: 10.1002/mrm.27643] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2018] [Revised: 11/20/2018] [Accepted: 11/29/2018] [Indexed: 12/31/2022]
Abstract
PURPOSE Implement simultaneous proton resonance frequency (PRF) shift and T1 measurements with equivalent temporal resolution using a single reference variable flip angle method. This novel method allows for simultaneous thermometry in both aqueous and fatty tissue. METHODS This method acquires a single reference image at the lower flip angle and all dynamic images at the higher angle. T1 is calculated using a single reference variable flip angle method, which accounts for the reference image temperature remaining constant. Monte Carlo simulations determined the optimal dynamic flip angle for combined PRF and T1 measurements. This method was evaluated in MR-guided focused ultrasound heating experiments using a gelatin phantom and human cadaver breasts. In vivo measurement precision was demonstrated in healthy female volunteers under nonheating conditions. RESULTS Temperature rise during MR-guided focused ultrasound heating was measured in aqueous tissue with both PRF and T1 . Both measures show good qualitative agreement in both space and time in aqueous tissue. The T1 change due to temperature increase was measured in fat, demonstrating the expected temporal response. The dynamic flip angle that produces optimal SNR for PRF measurements is lower than the optimal angle for T1 measurements, necessitating the selection of a compromise angle. CONCLUSION The single reference variable flip angle method provides a reliable way to simultaneously measure PRF temperature and T1 change and overcomes PRF's inability to simultaneously monitor temperature in aqueous and adipose tissues. Future work will calibrate T1 change to temperature, enabling real-time temperature in fat and increasing patient safety and treatment efficacy during thermal interventional treatments.
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Affiliation(s)
- Bryant T Svedin
- Utah Center for Advanced Imaging Research, University of Utah, Salt Lake City, Utah
| | - Allison Payne
- Utah Center for Advanced Imaging Research, University of Utah, Salt Lake City, Utah
| | - Dennis L Parker
- Utah Center for Advanced Imaging Research, University of Utah, Salt Lake City, Utah
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28
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Rosenzweig S, Holme HCM, Uecker M. Simple auto‐calibrated gradient delay estimation from few spokes using Radial Intersections (RING). Magn Reson Med 2018; 81:1898-1906. [DOI: 10.1002/mrm.27506] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2018] [Revised: 07/02/2018] [Accepted: 08/08/2018] [Indexed: 12/14/2022]
Affiliation(s)
- Sebastian Rosenzweig
- Institute for Diagnostic and Interventional RadiologyUniversity Medical Center Göttingen Göttingen Germany
| | - H. Christian M. Holme
- Institute for Diagnostic and Interventional RadiologyUniversity Medical Center Göttingen Göttingen Germany
- German Centre for Cardiovascular Research (DZHK), Partner site Göttingen Göttingen Germany
| | - Martin Uecker
- Institute for Diagnostic and Interventional RadiologyUniversity Medical Center Göttingen Göttingen Germany
- German Centre for Cardiovascular Research (DZHK), Partner site Göttingen Göttingen Germany
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29
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Roeloffs V, Rosenzweig S, Holme HCM, Uecker M, Frahm J. Frequency-modulated SSFP with radial sampling and subspace reconstruction: A time-efficient alternative to phase-cycled bSSFP. Magn Reson Med 2018; 81:1566-1579. [PMID: 30357904 DOI: 10.1002/mrm.27505] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2018] [Revised: 07/05/2018] [Accepted: 08/03/2018] [Indexed: 11/11/2022]
Abstract
PURPOSE A novel subspace-based reconstruction method for frequency-modulated balanced steady-state free precession (fmSSFP) MRI is presented. In this work, suitable data acquisition schemes, subspace sizes, and efficiencies for banding removal are investigated. THEORY AND METHODS By combining a fmSSFP MRI sequence with a 3D stack-of-stars trajectory, scan efficiency is maximized as spectral information is obtained without intermediate preparation phases. A memory-efficient reconstruction routine is implemented by introducing the low-frequency Fourier transform as a subspace which allows for the formulation of a convex reconstruction problem. The removal of banding artifacts is investigated by comparing the proposed acquisition and reconstruction technique to phase-cycled bSSFP MRI. Aliasing properties of different undersampling schemes are analyzed and water/fat separation is demonstrated by reweighting the reconstructed subspace coefficients to generate virtual spectral responses in a post-processing step. RESULTS A simple root-of-sum-of-squares combination of the reconstructed subspace coefficients yields high-SNR images with the characteristic bSSFP contrast but without banding artifacts. Compared to Golden-Angle trajectories, turn-based sampling schemes were superior in minimizing aliasing across reconstructed subspace coefficients. Water/fat separated images of the human knee were obtained by reweighting subspace coefficients. CONCLUSIONS The novel subspace-based fmSSFP MRI technique emerges as a time-efficient alternative to phase-cycled bSFFP. The method does not need intermediate preparation phases, offers high SNR and avoids banding artifacts. Reweighting of the reconstructed subspace coefficients allows for generating virtual spectral responses with applications to water/fat separation.
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Affiliation(s)
- Volkert Roeloffs
- Biomedizinische NMR Forschungs GmbH am Max-Planck-Institut für biophysikalische Chemie, Göttingen, Germany
| | - Sebastian Rosenzweig
- Institute for Diagnostic and Interventional Radiology, University Medical Center, Göttingen, Germany.,German Centre for Cardiovascular Research (DZHK), Göttingen, Germany
| | - H Christian M Holme
- Institute for Diagnostic and Interventional Radiology, University Medical Center, Göttingen, Germany.,German Centre for Cardiovascular Research (DZHK), Göttingen, Germany
| | - Martin Uecker
- Institute for Diagnostic and Interventional Radiology, University Medical Center, Göttingen, Germany.,German Centre for Cardiovascular Research (DZHK), Göttingen, Germany
| | - Jens Frahm
- Biomedizinische NMR Forschungs GmbH am Max-Planck-Institut für biophysikalische Chemie, Göttingen, Germany.,German Centre for Cardiovascular Research (DZHK), Göttingen, Germany
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30
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Svedin BT, Dillon CR, Parker DL. Effect of k-space-weighted image contrast and ultrasound focus size on the accuracy of proton resonance frequency thermometry. Magn Reson Med 2018; 81:247-257. [PMID: 30058224 DOI: 10.1002/mrm.27383] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2018] [Revised: 05/07/2018] [Accepted: 05/08/2018] [Indexed: 12/30/2022]
Abstract
PURPOSE To construct a predictive model that describes how the duration and symmetry of a k-space-weighted image contrast (KWIC) window affects the temporal resolution of differently sized ultrasound foci when using a pseudo-golden angle stack-of-stars acquisition. METHODS We performed a modulation analysis of proton resonance frequency temperature measurements to create the temporal modulation transfer function for KWIC windows of different symmetry and temporal duration. We reconstructed simulated ultrasound heating trajectories and stack-of-stars k-space data as well as experimental phantom data using the same trajectories. Images were reconstructed using symmetric and asymmetric KWIC windows of 3 different temporal durations. Simulated results were compared against temporal modulation transfer function predictions, experimental results, and the original simulated temperatures. RESULTS The temporal modulation transfer function shows that temporal resolution with KWIC reconstructions depend on the object size. The KWIC window duration affected SNR and severity of undersampling artifacts. Accuracy and response delay improved as the KWIC window duration decreased or the size of the heated region within the KWIC plane increased. Precision worsened as the window duration decreased. Using a symmetric window eliminated the response delay to heated region size but introduced a large reconstruction delay. CONCLUSION The accuracy and precision of proton resonance frequency temperature measurements from a stack-of-stars acquisition using a sliding KWIC window reconstruction are dependent on the size of the KWIC window and the size and shape of the heated region. The temporal modulation transfer function of KWIC reconstructions for any object size can predict the temporal response to changes in signal being acquired, such as temperature and contrast enhancement.
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Affiliation(s)
- Bryant T Svedin
- Utah Center for Advanced Imaging Research, University of Utah, Salt Lake City, Utah
| | - Christopher R Dillon
- Utah Center for Advanced Imaging Research, University of Utah, Salt Lake City, Utah
| | - Dennis L Parker
- Utah Center for Advanced Imaging Research, University of Utah, Salt Lake City, Utah
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31
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The Influence of Radial Undersampling Schemes on Compressed Sensing in Cardiac DTI. SENSORS 2018; 18:s18072388. [PMID: 30041419 PMCID: PMC6069122 DOI: 10.3390/s18072388] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/09/2018] [Revised: 07/09/2018] [Accepted: 07/12/2018] [Indexed: 12/16/2022]
Abstract
Diffusion tensor imaging (DTI) is known to suffer from long acquisition time, which greatly limits its practical and clinical use. Undersampling of k-space data provides an effective way to reduce the amount of data to acquire while maintaining image quality. Radial undersampling is one of the most popular non-Cartesian k-space sampling schemes, since it has relatively lower sensitivity to motion than Cartesian trajectories, and artifacts from linear reconstruction are more noise-like. Therefore, radial imaging is a promising strategy of undersampling to accelerate acquisitions. The purpose of this study is to investigate various radial sampling schemes as well as reconstructions using compressed sensing (CS). In particular, we propose two randomly perturbed radial undersampling schemes: golden-angle and random angle. The proposed methods are compared with existing radial undersampling methods, including uniformity-angle, randomly perturbed uniformity-angle, golden-angle, and random angle. The results on both simulated and real human cardiac diffusion weighted (DW) images show that, for the same amount of k-space data, randomly sampling around a random radial line results in better reconstruction quality for DTI indices, such as fractional anisotropy (FA), mean diffusivities (MD), and that the randomly perturbed golden-angle undersampling yields the best results for cardiac CS-DTI image reconstruction.
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32
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Slawig A, Wech T, Ratz V, Neubauer H, Bley T, Köstler H. Frequency-modulated bSSFP for phase-sensitive separation of water and fat. Magn Reson Imaging 2018; 53:82-88. [PMID: 29902564 DOI: 10.1016/j.mri.2018.06.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2017] [Revised: 04/27/2018] [Accepted: 06/10/2018] [Indexed: 10/28/2022]
Abstract
Our study proposes the use of a frequency-modulated acquisition which suppresses banding artefacts in combination with a phase-sensitive water-fat separation algorithm. The performance of the phase-sensitive separation for standard bSSFP, complex sum combination thereof, and frequency-modulated bSSFP were compared in in vivo measurements of the upper and lower legs at 1.5 and 3 T. It is shown, that the standard acquisition suffered from banding artefacts and major swaps between tissues. The dual-acquisition bSSFP could alleviate banding artefacts and only minor swaps occurred, but it comes at the expense of a doubled acquisition. In the frequency-modulated acquisitions all banding artefacts and the associated phase jumps were eliminated and no swaps between tissues occurred. It therefore provides a means to robustly separate water and fat, in one single radial bSSFP scan, using the phase-sensitive approach, even in the presence of high field inhomogeneities.
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Affiliation(s)
- Anne Slawig
- University of Würzburg, Department of Diagnostic and Interventional Radiology, Oberdürrbacher Str. 6, 97080 Würzburg, Germany.
| | - Tobias Wech
- University of Würzburg, Department of Diagnostic and Interventional Radiology, Oberdürrbacher Str. 6, 97080 Würzburg, Germany
| | - Valentin Ratz
- University of Würzburg, Department of Diagnostic and Interventional Radiology, Oberdürrbacher Str. 6, 97080 Würzburg, Germany
| | - Henning Neubauer
- University of Würzburg, Department of Diagnostic and Interventional Radiology, Oberdürrbacher Str. 6, 97080 Würzburg, Germany; SRH Clinic of Radiology, Albert-Schweitzer-Str. 2, 98527 Suhl, Germany
| | - Thorsten Bley
- University of Würzburg, Department of Diagnostic and Interventional Radiology, Oberdürrbacher Str. 6, 97080 Würzburg, Germany
| | - Herbert Köstler
- University of Würzburg, Department of Diagnostic and Interventional Radiology, Oberdürrbacher Str. 6, 97080 Würzburg, Germany
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Rosenzweig S, Holme HCM, Wilke RN, Voit D, Frahm J, Uecker M. Simultaneous multi‐slice MRI using cartesian and radial FLASH and regularized nonlinear inversion: SMS‐NLINV. Magn Reson Med 2017; 79:2057-2066. [DOI: 10.1002/mrm.26878] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2017] [Revised: 07/27/2017] [Accepted: 07/30/2017] [Indexed: 12/31/2022]
Affiliation(s)
- Sebastian Rosenzweig
- Institute for Diagnostic and Interventional Radiology, University Medical Center GöttingenGöttingen Germany
| | - Hans Christian Martin Holme
- Institute for Diagnostic and Interventional Radiology, University Medical Center GöttingenGöttingen Germany
- German Centre for Cardiovascular Research (DZHK), Partner site GöttingenGöttingen Germany
| | - Robin N. Wilke
- Institute for Diagnostic and Interventional Radiology, University Medical Center GöttingenGöttingen Germany
- German Centre for Cardiovascular Research (DZHK), Partner site GöttingenGöttingen Germany
| | - Dirk Voit
- Biomedizinische NMR Forschungs GmbH am Max‐Planck‐Institut für biophysikalische ChemieGöttingen Germany
| | - Jens Frahm
- German Centre for Cardiovascular Research (DZHK), Partner site GöttingenGöttingen Germany
- Biomedizinische NMR Forschungs GmbH am Max‐Planck‐Institut für biophysikalische ChemieGöttingen Germany
| | - Martin Uecker
- Institute for Diagnostic and Interventional Radiology, University Medical Center GöttingenGöttingen Germany
- German Centre for Cardiovascular Research (DZHK), Partner site GöttingenGöttingen Germany
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Zhou Z, Han F, Yu S, Yu D, Rapacchi S, Song HK, Wang DJJ, Hu P, Yan L. Accelerated noncontrast-enhanced 4-dimensional intracranial MR angiography using golden-angle stack-of-stars trajectory and compressed sensing with magnitude subtraction. Magn Reson Med 2017; 79:867-878. [PMID: 28480537 DOI: 10.1002/mrm.26747] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2017] [Revised: 04/12/2017] [Accepted: 04/14/2017] [Indexed: 11/10/2022]
Abstract
PURPOSE To evaluate the feasibility and performance of compressed sensing (CS) with magnitude subtraction regularization in accelerating non-contrast-enhanced dynamic intracranial MR angiography (NCE-dMRA). METHODS A CS algorithm was introduced in NCE-dMRA by exploiting the sparsity of the magnitude difference of the control and label images. The NCE-dMRA data were acquired using golden-angle stack-of-stars trajectory on six healthy volunteers and one patient with arteriovenous fistula. Images were reconstructed using (i) the proposed magnitude-subtraction CS (MS-CS); (ii) complex-subtraction CS; (iii) independent CS; and (iv) view-sharing with k-space weighted image contrast (KWIC). The dMRA image quality was compared across the four reconstruction strategies. The proposed MS-CS method was further compared with KWIC for temporal fidelity of depicting dynamic flow. RESULTS The proposed MS-CS method was able to reconstruct NCE-dMRA images with detailed vascular structures and clean background. It provided better subjective image quality than the other two CS strategies (P < 0.05). Compared with KWIC, MS-CS showed similar image quality, but reduced temporal blurring in delineating the fine distal arteries. CONCLUSIONS The MS-CS method is a promising CS technique for accelerating NCE-dMRA acquisition without compromising image quality and temporal fidelity. Magn Reson Med 79:867-878, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Ziwu Zhou
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, California, USA.,Department of Bioengineering, University of California, Los Angeles, California, USA
| | - Fei Han
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, California, USA.,Department of Bioengineering, University of California, Los Angeles, California, USA
| | - Songlin Yu
- Department of Neurology, University of California, Los Angeles, California, USA.,Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Dandan Yu
- Department of Neurology, University of California, Los Angeles, California, USA
| | - Stanislas Rapacchi
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, California, USA
| | - Hee Kwon Song
- Department of Radiology, University of Pennsylvania Medical Center, Philadelphia, Pennsylvania, USA
| | - Danny J J Wang
- Laboratory of Functional MRI Technology, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Peng Hu
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, California, USA.,Department of Bioengineering, University of California, Los Angeles, California, USA
| | - Lirong Yan
- Laboratory of Functional MRI Technology, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
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