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Zhang C, Piccini D, Demirel OB, Bonanno G, Roy CW, Yaman B, Moeller S, Shenoy C, Stuber M, Akçakaya M. Large-scale 3D non-Cartesian coronary MRI reconstruction using distributed memory-efficient physics-guided deep learning with limited training data. MAGMA (NEW YORK, N.Y.) 2024:10.1007/s10334-024-01157-8. [PMID: 38743377 DOI: 10.1007/s10334-024-01157-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 02/19/2024] [Accepted: 03/13/2024] [Indexed: 05/16/2024]
Abstract
OBJECT To enable high-quality physics-guided deep learning (PG-DL) reconstruction of large-scale 3D non-Cartesian coronary MRI by overcoming challenges of hardware limitations and limited training data availability. MATERIALS AND METHODS While PG-DL has emerged as a powerful image reconstruction method, its application to large-scale 3D non-Cartesian MRI is hindered by hardware limitations and limited availability of training data. We combine several recent advances in deep learning and MRI reconstruction to tackle the former challenge, and we further propose a 2.5D reconstruction using 2D convolutional neural networks, which treat 3D volumes as batches of 2D images to train the network with a limited amount of training data. Both 3D and 2.5D variants of the PG-DL networks were compared to conventional methods for high-resolution 3D kooshball coronary MRI. RESULTS Proposed PG-DL reconstructions of 3D non-Cartesian coronary MRI with 3D and 2.5D processing outperformed all conventional methods both quantitatively and qualitatively in terms of image assessment by an experienced cardiologist. The 2.5D variant further improved vessel sharpness compared to 3D processing, and scored higher in terms of qualitative image quality. DISCUSSION PG-DL reconstruction of large-scale 3D non-Cartesian MRI without compromising image size or network complexity is achieved, and the proposed 2.5D processing enables high-quality reconstruction with limited training data.
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Affiliation(s)
- Chi Zhang
- Electrical and Computer Engineering, University of Minnesota, 200 Union Street S.E., Minneapolis, MN, 55455, USA
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
| | - Davide Piccini
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthineers International, Lausanne, Switzerland
| | - Omer Burak Demirel
- Electrical and Computer Engineering, University of Minnesota, 200 Union Street S.E., Minneapolis, MN, 55455, USA
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
| | - Gabriele Bonanno
- Advanced Clinical Imaging Technology, Siemens Healthineers International, Lausanne, Switzerland
| | - Christopher W Roy
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Burhaneddin Yaman
- Electrical and Computer Engineering, University of Minnesota, 200 Union Street S.E., Minneapolis, MN, 55455, USA
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
| | - Steen Moeller
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
| | - Chetan Shenoy
- Department of Medicine (Cardiology), University of Minnesota, Minneapolis, MN, 55455, USA
| | - Matthias Stuber
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Center for Biomedical Imaging, Lausanne, Switzerland
| | - Mehmet Akçakaya
- Electrical and Computer Engineering, University of Minnesota, 200 Union Street S.E., Minneapolis, MN, 55455, USA.
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA.
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Chao TC, Peng X, Wang D, Pipe JG. Evaluating efficient SENSE algorithms to deblur spiral MRI with fat/water separation. Magn Reson Med 2023; 90:2190-2197. [PMID: 37379476 DOI: 10.1002/mrm.29773] [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: 02/07/2023] [Revised: 05/05/2023] [Accepted: 06/02/2023] [Indexed: 06/30/2023]
Abstract
PURPOSE The combination of SENSE and spiral imaging with fat/water separation enables high temporal efficiency. However, the corresponding computation increases due to the blurring/deblurring operation across the multi-channel data. This study presents two alternative models to simplify computational complexity in the original full model (model 1). The performances of the models are evaluated in terms of the computation time and reconstruction error. METHODS Two approximated spiral MRI reconstruction models were proposed: the comprehensive blurring before coil operation (model 2) and the regional blurring before coil operation (model 3), respectively, by altering the order of coil-sensitivity encoding process to distribute signals among the multi-channel coils. Four subjects were recruited for scanning both fully sampled T1 - and T2 -weighted brain image data with simulated undersampling for testing the computational efficiency and accuracy on the approximation models. RESULTS Based on the examples, the computation time can be reduced to 31%-47% using model 2, and to 39%-56% using model 3. The quality of the water image remains unchanged among the three models, whereas the primary difference in image quality is in the fat channel. The fat images from model 3 are consistent with those from model 1, but those from model 2 have higher normalized error, differing by up to 4.8%. CONCLUSION Model 2 provides the fastest computation but exhibits higher error in the fat channel, particularly in the high field and with long acquisition window. Model 3, an abridged alternative, is also faster than the full model and can maintain high accuracy in reconstruction.
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Affiliation(s)
- Tzu Cheng Chao
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Xi Peng
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Dinghui Wang
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - James G Pipe
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
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Pal A, Ning L, Rathi Y. A domain-agnostic MR reconstruction framework using a randomly weighted neural network. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.22.533764. [PMID: 36993372 PMCID: PMC10055311 DOI: 10.1101/2023.03.22.533764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
PURPOSE To design a randomly-weighted neural network that performs domain-agnostic MR image reconstruction from undersampled k-space data without the need for ground truth or extensive in-vivo training datasets. The network performance must be similar to the current state-of-the-art algorithms that require large training datasets. METHODS We propose a Weight Agnostic randomly weighted Network method for MRI reconstruction (termed WAN-MRI) which does not require updating the weights of the neural network but rather chooses the most appropriate connections of the network to reconstruct the data from undersampled k-space measurements. The network architecture has three components, i.e. (1) Dimensionality Reduction Layers comprising of 3d convolutions, ReLu, and batch norm; (2) Reshaping Layer is Fully Connected layer; and (3) Upsampling Layers that resembles the ConvDecoder architecture. The proposed methodology is validated on fastMRI knee and brain datasets. RESULTS The proposed method provides a significant boost in performance for structural similarity index measure (SSIM) and root mean squared error (RMSE) scores on fastMRI knee and brain datasets at an undersampling factor of R=4 and R=8 while trained on fractal and natural images, and fine-tuned with only 20 samples from the fastMRI training k-space dataset. Qualitatively, we see that classical methods such as GRAPPA and SENSE fail to capture the subtle details that are clinically relevant. We either outperform or show comparable performance with several existing deep learning techniques (that require extensive training) like GrappaNET, VariationNET, J-MoDL, and RAKI. CONCLUSION The proposed algorithm (WAN-MRI) is agnostic to reconstructing images of different body organs or MRI modalities and provides excellent scores in terms of SSIM, PSNR, and RMSE metrics and generalizes better to out-of-distribution examples. The methodology does not require ground truth data and can be trained using very few undersampled multi-coil k-space training samples.
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Feng L. 4D Golden-Angle Radial MRI at Subsecond Temporal Resolution. NMR IN BIOMEDICINE 2023; 36:e4844. [PMID: 36259951 PMCID: PMC9845193 DOI: 10.1002/nbm.4844] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 09/29/2022] [Accepted: 10/13/2022] [Indexed: 05/14/2023]
Abstract
Intraframe motion blurring, as a major challenge in free-breathing dynamic MRI, can be reduced if high temporal resolution can be achieved. To address this challenge, this work proposes a highly accelerated 4D (3D + time) dynamic MRI framework with subsecond temporal resolution that does not require explicit motion compensation. The method combines standard stack-of-stars golden-angle radial sampling and tailored GRASP-Pro (Golden-angle RAdial Sparse Parallel imaging with imProved performance) reconstruction. Specifically, 4D dynamic MRI acquisition is performed continuously without motion gating or sorting. The k-space centers in stack-of-stars radial data are organized to guide estimation of a temporal basis, with which GRASP-Pro reconstruction is employed to enforce joint low-rank subspace and sparsity constraints. This new basis estimation strategy is the new feature proposed for subspace-based reconstruction in this work to achieve high temporal resolution (e.g., subsecond/3D volume). It does not require sequence modification to acquire additional navigation data, it is compatible with commercially available stack-of-stars sequences, and it does not need an intermediate reconstruction step. The proposed 4D dynamic MRI approach was tested in abdominal motion phantom, free-breathing abdominal MRI, and dynamic contrast-enhanced MRI (DCE-MRI). Our results have shown that GRASP-Pro reconstruction with the new basis estimation strategy enables highly-accelerated 4D dynamic imaging at subsecond temporal resolution (with five spokes or less for each dynamic frame per image slice) for both free-breathing non-DCE-MRI and DCE-MRI. In the abdominal phantom, better image quality with lower root mean square error and higher structural similarity index was achieved using GRASP-Pro compared with standard GRASP. With the ability to acquire each 3D image in less than 1 s, intraframe respiratory blurring can be intrinsically reduced for body applications with our approach, which eliminates the need for explicit motion detection and motion compensation.
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Affiliation(s)
- Li Feng
- Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
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Towards robust in vivo quantification of oscillating biomagnetic fields using Rotary Excitation based MRI. Sci Rep 2022; 12:15375. [PMID: 36100634 PMCID: PMC9469076 DOI: 10.1038/s41598-022-19275-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Accepted: 08/26/2022] [Indexed: 11/28/2022] Open
Abstract
Spin-lock based functional magnetic resonance imaging (fMRI) has the potential for direct spatially-resolved detection of neuronal activity and thus may represent an important step for basic research in neuroscience. In this work, the corresponding fundamental effect of Rotary EXcitation (REX) is investigated both in simulations as well as in phantom and in vivo experiments. An empirical law for predicting optimal spin-lock pulse durations for maximum magnetic field sensitivity was found. Experimental conditions were established that allow robust detection of ultra-weak magnetic field oscillations with simultaneous compensation of static field inhomogeneities. Furthermore, this work presents a novel concept for the emulation of brain activity utilizing the built-in MRI gradient system, which allows REX sequences to be validated in vivo under controlled and reproducible conditions. Via transmission of Rotary EXcitation (tREX), we successfully detected magnetic field oscillations in the lower nano-Tesla range in brain tissue. Moreover, tREX paves the way for the quantification of biomagnetic fields.
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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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Le J, Tian Y, Mendes J, Wilson B, Ibrahim M, DiBella E, Adluru G. Deep learning for radial SMS myocardial perfusion reconstruction using the 3D residual booster U-net. Magn Reson Imaging 2021; 83:178-188. [PMID: 34428512 PMCID: PMC8493758 DOI: 10.1016/j.mri.2021.08.007] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Revised: 08/12/2021] [Accepted: 08/13/2021] [Indexed: 11/24/2022]
Abstract
PURPOSE To develop an end-to-end deep learning solution for quickly reconstructing radial simultaneous multi-slice (SMS) myocardial perfusion datasets with comparable quality to the pixel tracking spatiotemporal constrained reconstruction (PT-STCR) method. METHODS Dynamic contrast enhanced (DCE) radial SMS myocardial perfusion data were obtained from 20 subjects who were scanned at rest and/or stress with or without ECG gating using a saturation recovery radial CAIPI turboFLASH sequence. Input to the networks consisted of complex coil combined images reconstructed using the inverse Fourier transform of undersampled radial SMS k-space data. Ground truth images were reconstructed using the PT-STCR pipeline. The performance of the residual booster 3D U-Net was tested by comparing it to state-of-the-art network architectures including MoDL, CRNN-MRI, and other U-Net variants. RESULTS Results demonstrate significant improvements in speed requiring approximately 8 seconds to reconstruct one radial SMS dataset which is approximately 200 times faster than the PT-STCR method. Images reconstructed with the residual booster 3D U-Net retain quality of ground truth PT-STCR images (0.963 SSIM/40.238 PSNR/0.147 NRMSE). The residual booster 3D U-Net has superior performance compared to existing network architectures in terms of image quality, temporal dynamics, and reconstruction time. CONCLUSION Residual and booster learning combined with the 3D U-Net architecture was shown to be an effective network for reconstructing high-quality images from undersampled radial SMS datasets while bypassing the reconstruction time of the PT-STCR method.
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Affiliation(s)
- Johnathan Le
- Utah Center for Advanced Imaging Research (UCAIR), Department of Radiology and Imaging Sciences, University of Utah Salt Lake City, UT, USA; Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, USA
| | - Ye Tian
- Utah Center for Advanced Imaging Research (UCAIR), Department of Radiology and Imaging Sciences, University of Utah Salt Lake City, UT, USA; Department of Physics and Astronomy, University of Utah, Salt Lake City, UT, USA; Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, USA
| | - Jason Mendes
- Utah Center for Advanced Imaging Research (UCAIR), Department of Radiology and Imaging Sciences, University of Utah Salt Lake City, UT, USA
| | - Brent Wilson
- Department of Cardiology, University of Utah, Salt Lake City, UT, USA
| | - Mark Ibrahim
- Department of Cardiology, University of Utah, Salt Lake City, UT, USA
| | - Edward DiBella
- Utah Center for Advanced Imaging Research (UCAIR), Department of Radiology and Imaging Sciences, University of Utah Salt Lake City, UT, USA; Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, USA
| | - Ganesh Adluru
- Utah Center for Advanced Imaging Research (UCAIR), Department of Radiology and Imaging Sciences, University of Utah Salt Lake City, UT, USA; Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, USA.
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Sakurama A, Fushimi Y, Nakajima S, Sakata A, Hinoda T, Oshima S, Otani S, Wicaksono KP, Liu W, Maki T, Okada T, Takahashi R, Nakamoto Y. Clinical Application of MPRAGE Wave Controlled Aliasing in Parallel Imaging (Wave-CAIPI): A Comparative Study with MPRAGE GRAPPA. Magn Reson Med Sci 2021; 21:633-647. [PMID: 34602534 PMCID: PMC9618934 DOI: 10.2463/mrms.mp.2021-0065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/05/2022] Open
Abstract
Purpose: To compare reliability and elucidate clinical application of magnetization-prepared rapid gradient-echo (MPRAGE) with 9-fold acceleration by using wave-controlled aliasing in parallel imaging (Wave-CAIPI 3 × 3) in comparison to conventional MPRAGE accelerated by using generalized autocalibrating partially parallel acquisition (GRAPPA) 2 × 1. Methods: A total of 26 healthy volunteers and 33 patients were included in this study. Subjects were scanned with two MPRAGEs, GRAPPA 2 × 1 and Wave-CAIPI 3 × 3 acquired in 5 min 21 s and 1 min 42 s, respectively, on a 3T MR scanner. Healthy volunteers underwent additional two MPRAGEs (CAIPI 3 × 3 and GRAPPA 3 × 3). The image quality of the four MPRAGEs was visually evaluated with a 5-point scale in healthy volunteers, and the SNR of four MPRAGEs was also calculated by measuring the phantom 10 times with each MPRAGE. Based on the results of the visual evaluation, voxel-based morphometry (VBM) analyses, including subfield analysis, were performed only for GRAPPA 2 × 1 and Wave-CAIPI 3 × 3. Correlation of segmentation results between GRAPPA 2 × 1 and Wave-CAIPI 3 × 3 was assessed. Results: In visual evaluations, scores for MPRAGE GRAPPA 2 × 1 (mean rank: 4.00) were significantly better than those for Wave-CAIPI 3 × 3 (mean rank: 3.00), CAIPI 3 × 3 (mean rank: 1.83), and GRAPPA 3 × 3 (mean rank: 1.17), and scores for Wave-CAIPI 3×3 were significantly better than those for CAIPI 3 × 3 and GRAPPA 3 × 3. Image noise was evident at the center for additional MPRAGE CAIPI 3 × 3 and GRAPPA 3 × 3. The correlation of segmentation results between GRAPPA 2 × 1 and Wave-CAIPI 3 × 3 was higher than 0.85 in all VOIs except globus pallidus. Subfield analysis of hippocampus also showed a high correlation between GRAPPA 2 × 1 and Wave-CAIPI 3 × 3. Conclusion: MPRAGE Wave-CAIPI 3 × 3 shows relatively better contrast, despite of its short scan time of 1 min 42 s. The volumes derived from automated segmentation of MPRAGE Wave-CAIPI are considered to be reliable measures.
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Affiliation(s)
- Azusa Sakurama
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University
| | - Yasutaka Fushimi
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University
| | - Satoshi Nakajima
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University
| | - Akihiko Sakata
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University
| | - Takuya Hinoda
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University
| | - Sonoko Oshima
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University
| | - Sayo Otani
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University
| | - Krishna Pandu Wicaksono
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University
| | - Wei Liu
- Siemens Shenzhen Magnetic Resonance Ltd
| | - Takakuni Maki
- Department of Neurology, Graduate School of Medicine, Kyoto University
| | - Tomohisa Okada
- Human Brain Research Center, Graduate School of Medicine, Kyoto University
| | - Ryosuke Takahashi
- Department of Neurology, Graduate School of Medicine, Kyoto University
| | - Yuji Nakamoto
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University
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Feng L, Liu F, Soultanidis G, Liu C, Benkert T, Block KT, Fayad ZA, Yang Y. Magnetization-prepared GRASP MRI for rapid 3D T1 mapping and fat/water-separated T1 mapping. Magn Reson Med 2021; 86:97-114. [PMID: 33580909 PMCID: PMC8197608 DOI: 10.1002/mrm.28679] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Revised: 12/18/2020] [Accepted: 12/22/2020] [Indexed: 12/22/2022]
Abstract
PURPOSE This study aimed to (i) develop Magnetization-Prepared Golden-angle RAdial Sparse Parallel (MP-GRASP) MRI using a stack-of-stars trajectory for rapid free-breathing T1 mapping and (ii) extend MP-GRASP to multi-echo acquisition (MP-Dixon-GRASP) for fat/water-separated (water-specific) T1 mapping. METHODS An adiabatic non-selective 180° inversion-recovery pulse was added to a gradient-echo-based golden-angle stack-of-stars sequence for magnetization-prepared 3D single-echo or 3D multi-echo acquisition. In combination with subspace-based GRASP-Pro reconstruction, the sequence allows for standard T1 mapping (MP-GRASP) or fat/water-separated T1 mapping (MP-Dixon-GRASP), respectively. The accuracy of T1 mapping using MP-GRASP was evaluated in a phantom and volunteers (brain and liver) against clinically accepted reference methods. The repeatability of T1 estimation was also assessed in the phantom and volunteers. The performance of MP-Dixon-GRASP for water-specific T1 mapping was evaluated in a fat/water phantom and volunteers (brain and liver). RESULTS ROI-based mean T1 values are correlated between the references and MP-GRASP in the phantom (R2 = 1.0), brain (R2 = 0.96), and liver (R2 = 0.73). MP-GRASP achieved good repeatability of T1 estimation in the phantom (R2 = 1.0), brain (R2 = 0.99), and liver (R2 = 0.82). Water-specific T1 is different from in-phase and out-of-phase composite T1 (composite T1 when fat and water signal are mixed in phase or out of phase) both in the phantom and volunteers. CONCLUSION This work demonstrated the initial performance of MP-GRASP and MP-Dixon-GRASP MRI for rapid 3D T1 mapping and 3D fat/water-separated T1 mapping in the brain (without motion) and in the liver (during free breathing). With fat/water-separated T1 estimation, MP-Dixon-GRASP could be potentially useful for imaging patients with fatty-liver diseases.
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Affiliation(s)
- Li Feng
- Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Fang Liu
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Georgios Soultanidis
- Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Chenyu Liu
- Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Thomas Benkert
- MR Application Development, Siemens Healthcare GmbH, Erlangen, Germany
| | - Kai Tobias Block
- MR Application Development, Siemens Healthcare GmbH, Erlangen, Germany
- Center for Advanced Imaging Innovation and Research (CAIR), New York University School of Medicine, New York, NY, USA
| | - Zahi A. Fayad
- Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Yang Yang
- Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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Shahzadi I, Siddiqui MF, Aslam I, Omer H. Respiratory motion compensation using data binning in dynamic contrast enhanced golden-angle radial MRI. Magn Reson Imaging 2020; 70:115-125. [PMID: 32360531 DOI: 10.1016/j.mri.2020.03.011] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2019] [Revised: 02/12/2020] [Accepted: 03/31/2020] [Indexed: 11/16/2022]
Abstract
GRASP (Golden-Angle Radial Sparse Parallel MRI) is a data acquisition and reconstruction technique that combines parallel imaging and golden-angle radial sampling. The continuously acquired free breathing Dynamic Contrast Enhanced (DCE) golden-angle radial MRI data of liver and abdomen has artifacts due to respiratory motion, resulting in low vessel-tissue contrast that makes GRASP reconstructed images less suitable for diagnosis. In this paper, DCE golden-angle radial MRI data of abdomen and liver perfusion is sorted into different motion states using the self-gating property of radial acquisition and then reconstructed using GRASP. Three methods of amplitude-based data binning namely uniform binning, adaptive binning and optimal binning are applied on the DCE golden-angle radial data to extract different motion states and a comparison is performed with the conventional GRASP reconstruction. Also, a comparison among the amplitude-based data binning techniques is performed and benefits of each of these binning techniques are discussed from a clinical perspective. The image quality assessment in terms of hepatic vessel clarity, liver edge sharpness, contrast enhancement clarity and streaking artifacts is performed by a certified radiologist. The results show that DCE golden-angle radial trajectories benefit from all the three types of amplitude-based data binning methods providing improved reconstruction results. The choice of binning technique depends upon the clinical application e.g. uniform and adaptive binning are helpful for a detailed analysis of lesion characteristic and contrast enhancement in different motion states while optimal binning can be used when clinical analysis requires a single image per contrast enhancement phase with no motion blurring artifacts.
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Affiliation(s)
- Iram Shahzadi
- Medical Image Processing Research Group (MIPRG), Department of Electrical and Computer Engineering, COMSATS University Islamabad, Islamabad 45550, Pakistan
| | - Muhammad Faisal Siddiqui
- Medical Image Processing Research Group (MIPRG), Department of Electrical and Computer Engineering, COMSATS University Islamabad, Islamabad 45550, Pakistan.
| | - Ibtisam Aslam
- Department of Radiology & Medical Informatics, Hospital University of Geneva, Geneva, Switzerland
| | - Hammad Omer
- Medical Image Processing Research Group (MIPRG), Department of Electrical and Computer Engineering, COMSATS University Islamabad, Islamabad 45550, Pakistan
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Staniszewski M, Klose U. Improvement of Fast Model-Based Acceleration of Parameter Look-Locker T 1 Mapping. SENSORS (BASEL, SWITZERLAND) 2019; 19:s19245371. [PMID: 31817483 PMCID: PMC6960582 DOI: 10.3390/s19245371] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/17/2019] [Revised: 12/02/2019] [Accepted: 12/04/2019] [Indexed: 06/10/2023]
Abstract
Quantitative mapping is desirable in many scientific and clinical magneric resonance imaging (MRI) applications. Recent inverse recovery-look locker sequence enables single-shot T1 mapping with a time of a few seconds but the main computational load is directed into offline reconstruction, which can take from several minutes up to few hours. In this study we proposed improvement of model-based approach for T1-mapping by introduction of two steps fitting procedure. We provided analysis of further reduction of k-space data, which lead us to decrease of computational time and perform simulation of multi-slice development. The region of interest (ROI) analysis of human brain measurements with two different initial models shows that the differences between mean values with respect to a reference approach are in white matter-0.3% and 1.1%, grey matter-0.4% and 1.78% and cerebrospinal fluid-2.8% and 11.1% respectively. With further improvements we were able to decrease the time of computational of single slice to 6.5 min and 23.5 min for different initial models, which has been already not achieved by any other algorithm. In result we obtained an accelerated novel method of model-based image reconstruction in which single iteration can be performed within few seconds on home computer.
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Affiliation(s)
- Michał Staniszewski
- Institute of Informatics, Silesian University of Technology, Gliwice 44-100, Poland
| | - Uwe Klose
- Department of Diagnostic and Interventional Neuroradiology, Eberhard Karls University, Tübingen 72076, Germany;
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Chieh SW, Kaveh M, Akçakaya M, Moeller S. Self-calibrated interpolation of non-Cartesian data with GRAPPA in parallel imaging. Magn Reson Med 2019; 83:1837-1850. [PMID: 31722128 DOI: 10.1002/mrm.28033] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2019] [Revised: 08/20/2019] [Accepted: 09/17/2019] [Indexed: 12/22/2022]
Abstract
PURPOSE To develop a non-Cartesian k-space reconstruction method using self-calibrated region-specific interpolation kernels for highly accelerated acquisitions. METHODS In conventional non-Cartesian GRAPPA with through-time GRAPPA (TT-GRAPPA), the use of region-specific interpolation kernels has demonstrated improved reconstruction quality in dynamic imaging for highly accelerated acquisitions. However, TT-GRAPPA requires the acquisition of a large number of separate calibration scans. To reduce the overall imaging time, we propose Self-calibrated Interpolation of Non-Cartesian data with GRAPPA (SING) to self-calibrate region-specific interpolation kernels from dynamic undersampled measurements. The SING method synthesizes calibration data to adapt to the distinct shape of each region-specific interpolation kernel geometry, and uses a novel local k-space regularization through an extension of TT-GRAPPA. This calibration approach is used to reconstruct non-Cartesian images at high acceleration rates while mitigating noise amplification. The reconstruction quality of SING is compared with conjugate-gradient SENSE and TT-GRAPPA in numerical phantoms and in vivo cine data sets. RESULTS In both numerical phantom and in vivo cine data sets, SING offers visually and quantitatively similar reconstruction quality to TT-GRAPPA, and provides improved reconstruction quality over conjugate-gradient SENSE. Furthermore, temporal fidelity in SING and TT-GRAPPA is similar for the same acceleration rates. G-factor evaluation over the heart shows that SING and TT-GRAPPA provide similar noise amplification at moderate and high rates. CONCLUSION The proposed SING reconstruction enables significant improvement of acquisition efficiency for calibration data, while matching the reconstruction performance of TT-GRAPPA.
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Affiliation(s)
- Seng-Wei Chieh
- Electrical and Computer Engineering, University of Minnesota, Minneapolis, Minnesota
| | - Mostafa Kaveh
- Electrical and Computer Engineering, University of Minnesota, Minneapolis, Minnesota
| | - Mehmet Akçakaya
- Electrical and Computer Engineering, University of Minnesota, Minneapolis, Minnesota.,Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota
| | - Steen Moeller
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota
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Liu F, Samsonov A, Chen L, Kijowski R, Feng L. SANTIS: Sampling-Augmented Neural neTwork with Incoherent Structure for MR image reconstruction. Magn Reson Med 2019; 82:1890-1904. [PMID: 31166049 PMCID: PMC6660404 DOI: 10.1002/mrm.27827] [Citation(s) in RCA: 50] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2019] [Revised: 05/02/2019] [Accepted: 05/03/2019] [Indexed: 12/23/2022]
Abstract
PURPOSE To develop and evaluate a novel deep learning-based reconstruction framework called SANTIS (Sampling-Augmented Neural neTwork with Incoherent Structure) for efficient MR image reconstruction with improved robustness against sampling pattern discrepancy. METHODS With a combination of data cycle-consistent adversarial network, end-to-end convolutional neural network mapping, and data fidelity enforcement for reconstructing undersampled MR data, SANTIS additionally utilizes a sampling-augmented training strategy by extensively varying undersampling patterns during training, so that the network is capable of learning various aliasing structures and thereby removing undersampling artifacts more effectively and robustly. The performance of SANTIS was demonstrated for accelerated knee imaging and liver imaging using a Cartesian trajectory and a golden-angle radial trajectory, respectively. Quantitative metrics were used to assess its performance against different references. The feasibility of SANTIS in reconstructing dynamic contrast-enhanced images was also demonstrated using transfer learning. RESULTS Compared to conventional reconstruction that exploits image sparsity, SANTIS achieved consistently improved reconstruction performance (lower errors and greater image sharpness). Compared to standard learning-based methods without sampling augmentation (e.g., training with a fixed undersampling pattern), SANTIS provides comparable reconstruction performance, but significantly improved robustness, against sampling pattern discrepancy. SANTIS also achieved encouraging results for reconstructing liver images acquired at different contrast phases. CONCLUSION By extensively varying undersampling patterns, the sampling-augmented training strategy in SANTIS can remove undersampling artifacts more robustly. The novel concept behind SANTIS can particularly be useful for improving the robustness of deep learning-based image reconstruction against discrepancy between training and inference, an important, but currently less explored, topic.
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Affiliation(s)
- Fang Liu
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Alexey Samsonov
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Lihua Chen
- Department of Radiology, Southwest Hospital, Chongqing, China
| | - Richard Kijowski
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Li Feng
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, USA
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14
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Qi H, Bustin A, Cruz G, Jaubert O, Chen H, Botnar RM, Prieto C. Free-running simultaneous myocardial T1/T2 mapping and cine imaging with 3D whole-heart coverage and isotropic spatial resolution. Magn Reson Imaging 2019; 63:159-169. [DOI: 10.1016/j.mri.2019.08.008] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2019] [Revised: 08/10/2019] [Accepted: 08/15/2019] [Indexed: 12/14/2022]
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15
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Feng L, Wen Q, Huang C, Tong A, Liu F, Chandarana H. GRASP-Pro: imProving GRASP DCE-MRI through self-calibrating subspace-modeling and contrast phase automation. Magn Reson Med 2019; 83:94-108. [PMID: 31400028 DOI: 10.1002/mrm.27903] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2019] [Accepted: 06/25/2019] [Indexed: 12/19/2022]
Abstract
PURPOSE To propose a highly accelerated, high-resolution dynamic contrast-enhanced MRI (DCE-MRI) technique called GRASP-Pro (golden-angle radial sparse parallel imaging with imProved performance) through a joint sparsity and self-calibrating subspace constraint with automated selection of contrast phases. METHODS GRASP-Pro reconstruction enforces a combination of an explicit low-rank subspace-constraint and a temporal sparsity constraint. The temporal basis used to construct the subspace is learned from an intermediate reconstruction step using the low-resolution portion of radial k-space, which eliminates the need for generating the basis using auxiliary data or a physical signal model. A convolutional neural network was trained to generate the contrast enhancement curve in the artery, from which clinically relevant contrast phases are automatically selected for evaluation. The performance of GRASP-Pro was demonstrated for high spatiotemporal resolution DCE-MRI of the prostate and was compared against standard GRASP in terms of overall image quality, image sharpness, and residual streaks and/or noise level. RESULTS Compared to GRASP, GRASP-Pro reconstructed dynamic images with enhanced sharpness, less residual streaks and/or noise, and finer delineation of the prostate without prolonging reconstruction time. The image quality improvement reached statistical significance (P < 0.05) in all the assessment categories. The neural network successfully generated contrast enhancement curves in the artery, and corresponding peak enhancement indexes correlated well with that from the manual selection. CONCLUSION GRASP-Pro is a promising method for rapid and continuous DCE-MRI. It enables superior reconstruction performance over standard GRASP and allows reliable generation of artery enhancement curve to guide the selection of desired contrast phases for improving the efficiency of GRASP MRI workflow.
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Affiliation(s)
- Li Feng
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Qiuting Wen
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana
| | - Chenchan Huang
- Department of Radiology, New York University School of Medicine, New York, New York
| | - Angela Tong
- Department of Radiology, New York University School of Medicine, New York, New York
| | - Fang Liu
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin
| | - Hersh Chandarana
- Department of Radiology, New York University School of Medicine, New York, New York.,Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, New York, New York
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16
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Tian Y, Mendes J, Pedgaonkar A, Ibrahim M, Jensen L, Schroeder JD, Wilson B, DiBella EVR, Adluru G. Feasibility of multiple-view myocardial perfusion MRI using radial simultaneous multi-slice acquisitions. PLoS One 2019; 14:e0211738. [PMID: 30742641 PMCID: PMC6370206 DOI: 10.1371/journal.pone.0211738] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2018] [Accepted: 01/18/2019] [Indexed: 11/18/2022] Open
Abstract
Purpose Dynamic contrast enhanced MRI of the heart typically acquires 2–4 short-axis (SA) slices to detect and characterize coronary artery disease. This acquisition scheme is limited by incomplete coverage of the left ventricle. We studied the feasibility of using radial simultaneous multi-slice (SMS) technique to achieve SA, 2-chamber and/or 4-chamber long-axis (2CH LA and/or 4CH LA) coverage with and without electrocardiography (ECG) gating using a motion-robust reconstruction framework. Methods 12 subjects were scanned at rest and/or stress, free breathing, with or without ECG gating. Multiple sets of radial SMS k-space were acquired within each cardiac cycle, and each SMS set sampled 3 parallel slices that were either SA, 2CH LA, or 4CH LA slices. The radial data was interpolated onto Cartesian space using an SMS GRAPPA operator gridding method. Self-gating and respiratory states binning of the data were done. The binning information as well as a pixel tracking spatiotemporal constrained reconstruction method were applied to obtain motion-robust image reconstructions. Reconstructions with and without the pixel tracking method were compared for signal-to-noise ratio and contrast-to-noise ratio. Results Full coverage of the heart (at least 3 SA and 3 LA slices) during the first pass of contrast at every heartbeat was achieved by using the radial SMS acquisition. The proposed pixel tracking reconstruction improves the average SNR and CNR by 21% and 30% respectively, and reduces temporal blurring for both gated and ungated acquisitions. Conclusion Acquiring simultaneous multi-slice SA, 2CH LA and/or 4CH LA myocardial perfusion images in every heartbeat is feasible in both gated and ungated acquisitions. This can add confidence when detecting and characterizing coronary artery disease by revealing ischemia in different views, and by providing apical coverage that is improved relative to SA slices alone. The proposed pixel tracking framework improves the reconstruction while adding little computational cost.
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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, United States of America
- Department of Physics and Astronomy, University of Utah, Salt Lake City, Utah, United States of America
| | - Jason Mendes
- Utah Center for Advanced Imaging Research (UCAIR), Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah, United States of America
| | - Apoorva Pedgaonkar
- Utah Center for Advanced Imaging Research (UCAIR), Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah, United States of America
| | - Mark Ibrahim
- Division of Cardiology, University of Utah, Salt Lake City, Utah, United States of America
| | - Leif Jensen
- Utah Center for Advanced Imaging Research (UCAIR), Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah, United States of America
| | - Joyce D. Schroeder
- Utah Center for Advanced Imaging Research (UCAIR), Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah, United States of America
| | - Brent Wilson
- Division of Cardiology, University of Utah, Salt Lake City, Utah, United States of America
| | - Edward V. R. DiBella
- Utah Center for Advanced Imaging Research (UCAIR), Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah, United States of America
| | - Ganesh Adluru
- Utah Center for Advanced Imaging Research (UCAIR), Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah, United States of America
- * E-mail:
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17
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Becker KM, Schulz‐Menger J, Schaeffter T, Kolbitsch C. Simultaneous high‐resolution cardiac T
1
mapping and cine imaging using model‐based iterative image reconstruction. Magn Reson Med 2018; 81:1080-1091. [DOI: 10.1002/mrm.27474] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2018] [Revised: 06/08/2018] [Accepted: 07/09/2018] [Indexed: 12/26/2022]
Affiliation(s)
- Kirsten M. Becker
- Physikalisch‐Technische Bundesanstalt (PTB) Braunschweig and Berlin Germany
| | - Jeanette Schulz‐Menger
- Charité‐Universitätsmedizin Berlin Freie Universität Berlin, Humboldt‐Universität zu Berlin Berlin Institute of Health, DZHK Berlin Germany
- Working Group Cardiovascular Magnetic Resonance, Experimental and Clinical Research Center Charité Medical Faculty Max‐Delbrueck Center for Molecular Medicine HELIOS Klinikum Berlin Buch Department of Cardiology and Nephrology Berlin Germany
| | - Tobias Schaeffter
- Physikalisch‐Technische Bundesanstalt (PTB) Braunschweig and Berlin Germany
- Division of Imaging Sciences and Biomedical Engineering King's College London London United Kingdom
| | - Christoph Kolbitsch
- Physikalisch‐Technische Bundesanstalt (PTB) Braunschweig and Berlin Germany
- Division of Imaging Sciences and Biomedical Engineering King's College London London United Kingdom
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18
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Li YY, Rashid S, Cheng YJ, Schapiro W, Gliganic K, Yamashita AM, Tang J, Grgas M, Mendez M, Haag E, Pang J, Stoeckel B, Leidecker C, Cao JJ. Real-time cardiac MRI with radial acquisition and k-space variant reduced-FOV reconstruction. Magn Reson Imaging 2018; 53:98-104. [PMID: 30036652 DOI: 10.1016/j.mri.2018.07.008] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2018] [Revised: 07/19/2018] [Accepted: 07/20/2018] [Indexed: 12/01/2022]
Abstract
This work aims to demonstrate that radial acquisition with k-space variant reduced-FOV reconstruction can enable real-time cardiac MRI with an affordable computation cost. Due to non-uniform sampling, radial imaging requires k-space variant reconstruction for optimal performance. By converting radial parallel imaging reconstruction into the estimation of correlation functions with a previously-developed correlation imaging framework, Cartesian k-space may be reconstructed point-wisely based on parallel imaging relationship between every Cartesian datum and its neighboring radial samples. Furthermore, reduced-FOV correlation functions may be used to calculate a subset of Cartesian k-space data for image reconstruction within a small region of interest, making it possible to run real-time cardiac MRI with an affordable computation cost. In a stress cardiac test where the subject is imaged during biking with a heart rate of >100 bpm, this k-space variant reduced-FOV reconstruction is demonstrated in reference to several radial imaging techniques including gridding, GROG and SPIRiT. It is found that the k-space variant reconstruction outperforms gridding, GROG and SPIRiT in real-time imaging. The computation cost of reduced-FOV reconstruction is ~2 times higher than that of GROG. The presented work provides a practical solution to real-time cardiac MRI with radial acquisition and k-space variant reduced-FOV reconstruction in clinical settings.
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Affiliation(s)
- Yu Y Li
- Cardiac Imaging, DeMatteis Center for Cardiac Research and Education, St. Francis Hospital, New York, United States; Radiology and Biomedical Engineering, Stony Brook University, New York, United States.
| | - Shams Rashid
- Cardiac Imaging, DeMatteis Center for Cardiac Research and Education, St. Francis Hospital, New York, United States
| | - Yang J Cheng
- Cardiac Imaging, DeMatteis Center for Cardiac Research and Education, St. Francis Hospital, New York, United States
| | - William Schapiro
- Cardiac Imaging, DeMatteis Center for Cardiac Research and Education, St. Francis Hospital, New York, United States
| | - Kathleen Gliganic
- Cardiac Imaging, DeMatteis Center for Cardiac Research and Education, St. Francis Hospital, New York, United States
| | - Ann-Marie Yamashita
- Cardiac Imaging, DeMatteis Center for Cardiac Research and Education, St. Francis Hospital, New York, United States
| | - John Tang
- Cardiac Imaging, DeMatteis Center for Cardiac Research and Education, St. Francis Hospital, New York, United States
| | - Marie Grgas
- Cardiac Imaging, DeMatteis Center for Cardiac Research and Education, St. Francis Hospital, New York, United States
| | - Michelle Mendez
- Cardiac Imaging, DeMatteis Center for Cardiac Research and Education, St. Francis Hospital, New York, United States
| | - Elizabeth Haag
- Cardiac Imaging, DeMatteis Center for Cardiac Research and Education, St. Francis Hospital, New York, United States
| | - Jianing Pang
- Siemens Healthneers, Siemens Medical Solutions USA, Inc., United States
| | - Bernd Stoeckel
- Siemens Healthneers, Siemens Medical Solutions USA, Inc., United States
| | | | - J Jane Cao
- Cardiac Imaging, DeMatteis Center for Cardiac Research and Education, St. Francis Hospital, New York, United States; Clinical Medicine, Stony Brook University, New York, United States
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19
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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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20
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Single-shot late Gd enhancement imaging of myocardial infarction with retrospectively adjustable contrast and heart-phase. Magn Reson Imaging 2018; 47:48-53. [DOI: 10.1016/j.mri.2017.10.008] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2017] [Revised: 10/23/2017] [Accepted: 10/31/2017] [Indexed: 12/12/2022]
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21
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Feng L, Huang C, Shanbhogue K, Sodickson DK, Chandarana H, Otazo R. RACER-GRASP: Respiratory-weighted, aortic contrast enhancement-guided and coil-unstreaking golden-angle radial sparse MRI. Magn Reson Med 2017; 80:77-89. [PMID: 29193260 DOI: 10.1002/mrm.27002] [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: 08/24/2017] [Revised: 10/18/2017] [Accepted: 10/19/2017] [Indexed: 12/25/2022]
Abstract
PURPOSE To develop and evaluate a novel dynamic contrast-enhanced imaging technique called RACER-GRASP (Respiratory-weighted, Aortic Contrast Enhancement-guided and coil-unstReaking Golden-angle RAdial Sparse Parallel) MRI that extends GRASP to include automatic contrast bolus timing, respiratory motion compensation, and coil-weighted unstreaking for improved imaging performance in liver MRI. METHODS In RACER-GRASP, aortic contrast enhancement (ACE) guided k-space sorting and respiratory-weighted sparse reconstruction are performed using aortic contrast enhancement and respiratory motion signals extracted directly from the acquired data. Coil unstreaking aims to weight multicoil k-space according to streaking artifact level calculated for each individual coil during image reconstruction, so that coil elements containing a high level of streaking artifacts contribute less to the final results. Self-calibrating GRAPPA operator gridding was applied as a pre-reconstruction step to reduce computational burden in the subsequent iterative reconstruction. The RACER-GRASP technique was compared with standard GRASP reconstruction in a group of healthy volunteers and patients referred for clinical liver MR examination. RESULTS Compared with standard GRASP, RACER-GRASP significantly improved overall image quality (average score: 3.25 versus 3.85) and hepatic vessel sharpness/clarity (average score: 3.58 versus 4.0), and reduced residual streaking artifact level (average score: 3.23 versus 3.94) in different contrast phases. RACER-GRASP also enabled automatic timing of the arterial phases. CONCLUSIONS The aortic contrast enhancement-guided sorting, respiratory motion suppression and coil unstreaking introduced by RACER-GRASP improve upon the imaging performance of standard GRASP for free-breathing dynamic contrast-enhanced MRI of the liver. Magn Reson Med 80:77-89, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Li Feng
- Center for Advanced Imaging Innovation and Research (CAI2R), and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - Chenchan Huang
- Center for Advanced Imaging Innovation and Research (CAI2R), and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - Krishna Shanbhogue
- Center for Advanced Imaging Innovation and Research (CAI2R), and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - Daniel K Sodickson
- Center for Advanced Imaging Innovation and Research (CAI2R), and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - Hersh Chandarana
- Center for Advanced Imaging Innovation and Research (CAI2R), and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - Ricardo Otazo
- Center for Advanced Imaging Innovation and Research (CAI2R), and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
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22
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Benkert T, Tian Y, Huang C, DiBella EVR, Chandarana H, Feng L. Optimization and validation of accelerated golden-angle radial sparse MRI reconstruction with self-calibrating GRAPPA operator gridding. Magn Reson Med 2017; 80:286-293. [PMID: 29193380 DOI: 10.1002/mrm.27030] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2017] [Revised: 11/02/2017] [Accepted: 11/10/2017] [Indexed: 12/24/2022]
Abstract
PURPOSE Golden-angle radial sparse parallel (GRASP) MRI reconstruction requires gridding and regridding to transform data between radial and Cartesian k-space. These operations are repeatedly performed in each iteration, which makes the reconstruction computationally demanding. This work aimed to accelerate GRASP reconstruction using self-calibrating GRAPPA operator gridding (GROG) and to validate its performance in clinical imaging. METHODS GROG is an alternative gridding approach based on parallel imaging, in which k-space data acquired on a non-Cartesian grid are shifted onto a Cartesian k-space grid using information from multicoil arrays. For iterative non-Cartesian image reconstruction, GROG is performed only once as a preprocessing step. Therefore, the subsequent iterative reconstruction can be performed directly in Cartesian space, which significantly reduces computational burden. Here, a framework combining GROG with GRASP (GROG-GRASP) is first optimized and then compared with standard GRASP reconstruction in 22 prostate patients. RESULTS GROG-GRASP achieved approximately 4.2-fold reduction in reconstruction time compared with GRASP (∼333 min versus ∼78 min) while maintaining image quality (structural similarity index ≈ 0.97 and root mean square error ≈ 0.007). Visual image quality assessment by two experienced radiologists did not show significant differences between the two reconstruction schemes. With a graphics processing unit implementation, image reconstruction time can be further reduced to approximately 14 min. CONCLUSION The GRASP reconstruction can be substantially accelerated using GROG. This framework is promising toward broader clinical application of GRASP and other iterative non-Cartesian reconstruction methods. Magn Reson Med 80:286-293, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Thomas Benkert
- Center for Advanced Imaging Innovation and Research (CAI2R), and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - Ye Tian
- 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
| | - Chenchan Huang
- Center for Advanced Imaging Innovation and Research (CAI2R), and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - Edward V R DiBella
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah, USA
| | - Hersh Chandarana
- Center for Advanced Imaging Innovation and Research (CAI2R), and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - Li Feng
- Center for Advanced Imaging Innovation and Research (CAI2R), and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
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23
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Chen Z, Kang L, Xia L, Wang Q, Li Y, Hu X, Liu F, Huang F. Technical Note: Sequential combination of parallel imaging and dynamic artificial sparsity framework for rapid free-breathing golden-angle radial dynamic MRI: K-T ARTS-GROWL. Med Phys 2017; 45:202-213. [DOI: 10.1002/mp.12639] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2017] [Revised: 09/17/2017] [Accepted: 10/18/2017] [Indexed: 12/25/2022] Open
Affiliation(s)
- Zhifeng Chen
- Department of Biomedical Engineering; Zhejiang University; Hangzhou China
| | - Liyi Kang
- Department of Biomedical Engineering; Zhejiang University; Hangzhou China
| | - Ling Xia
- Department of Biomedical Engineering; Zhejiang University; Hangzhou China
- State Key Lab of CAD&CG; Zhejiang University; Hangzhou China
| | - Qiuliang Wang
- Division of Superconducting Magnet Science and Technology; Institute of Electrical Engineering; Chinese Academy of Sciences; Beijing China
| | - Yi Li
- Division of Superconducting Magnet Science and Technology; Institute of Electrical Engineering; Chinese Academy of Sciences; Beijing China
| | - Xinning Hu
- Division of Superconducting Magnet Science and Technology; Institute of Electrical Engineering; Chinese Academy of Sciences; Beijing China
| | - Feng Liu
- School of Information Technology and Electrical Engineering; The University of Queensland; Brisbane QLD Australia
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24
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Tian Y, Erb KC, Adluru G, Likhite D, Pedgaonkar A, Blatt M, Kamesh Iyer S, Roberts J, DiBella E. Technical Note: Evaluation of pre-reconstruction interpolation methods for iterative reconstruction of radial k-space data. Med Phys 2017; 44:4025-4034. [PMID: 28543266 DOI: 10.1002/mp.12357] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2016] [Revised: 05/04/2017] [Accepted: 05/12/2017] [Indexed: 12/12/2022] Open
Abstract
PURPOSE To evaluate the use of three different pre-reconstruction interpolation methods to convert non-Cartesian k-space data to Cartesian samples such that iterative reconstructions can be performed more simply and more rapidly. METHODS Phantom as well as cardiac perfusion radial datasets were reconstructed by four different methods. Three of the methods used pre-reconstruction interpolation once followed by a fast Fourier transform (FFT) at each iteration. The methods were: bilinear interpolation of nearest-neighbor points (BINN), 3-point interpolation, and a multi-coil interpolator called GRAPPA Operator Gridding (GROG). The fourth method performed a full non-Uniform FFT (NUFFT) at each iteration. An iterative reconstruction with spatiotemporal total variation constraints was used with each method. Differences in the images were quantified and compared. RESULTS The GROG multicoil interpolation, the 3-point interpolation, and the NUFFT-at-each-iteration approaches produced high quality images compared to BINN, with the GROG-derived images having the fewest streaks among the three preinterpolation approaches. However, all reconstruction methods produced approximately equal results when applied to perfusion quantitation tasks. Pre-reconstruction interpolation gave approximately an 83% reduction in reconstruction time. CONCLUSION Image quality suffers little from using a pre-reconstruction interpolation approach compared to the more accurate NUFFT-based approach. GROG-based pre-reconstruction interpolation appears to offer the best compromise by using multicoil information to perform the interpolation to Cartesian sample points prior to image reconstruction. Speed gains depend on the implementation and relatively standard optimizations on a MATLAB platform result in preinterpolation speedups of ~ 6 compared to using NUFFT at every iteration, reducing the reconstruction time from around 42 min to 7 min.
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Affiliation(s)
- Ye Tian
- Department of Physics and Astronomy, University of Utah, Salt Lake City, UT, 84112, USA.,Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, 84108, USA
| | - Kay Condie Erb
- Department of Physics and Astronomy, University of Utah, Salt Lake City, UT, 84112, USA
| | - Ganesh Adluru
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, 84108, USA
| | - Devavrat Likhite
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, 84108, USA.,Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, UT, 84108, USA
| | - Apoorva Pedgaonkar
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, 84108, USA.,Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, UT, 84108, USA
| | - Michael Blatt
- Department of Bioengineering, University of Utah, Salt Lake City, UT, 84108, USA
| | - Srikant Kamesh Iyer
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, 84108, USA
| | - John Roberts
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, 84108, USA
| | - Edward DiBella
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, 84108, USA.,Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, UT, 84108, USA.,Department of Bioengineering, University of Utah, Salt Lake City, UT, 84108, USA
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25
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Heule R, Pfeuffer J, Bieri O. Snapshot whole-brain T1relaxometry using steady-state prepared spiral multislice variable flip angle imaging. Magn Reson Med 2017; 79:856-866. [DOI: 10.1002/mrm.26746] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2017] [Revised: 04/11/2017] [Accepted: 04/13/2017] [Indexed: 01/05/2023]
Affiliation(s)
- Rahel Heule
- Division of Radiological Physics; Department of Radiology, University Hospital Basel, University of Basel; Basel Switzerland
- Department of Biomedical Engineering; University of Basel; Basel Switzerland
| | - Josef Pfeuffer
- Siemens Healthcare, Application Development; Erlangen Germany
| | - Oliver Bieri
- Division of Radiological Physics; Department of Radiology, University Hospital Basel, University of Basel; Basel Switzerland
- Department of Biomedical Engineering; University of Basel; Basel Switzerland
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26
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Slawig A, Wech T, Ratz V, Tran-Gia J, Neubauer H, Bley T, Köstler H. Multifrequency reconstruction for frequency-modulated bSSFP. Magn Reson Med 2017; 78:2226-2235. [DOI: 10.1002/mrm.26630] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2016] [Revised: 12/02/2016] [Accepted: 01/09/2017] [Indexed: 11/10/2022]
Affiliation(s)
- Anne Slawig
- Department of Diagnostic and Interventional Radiology; University of Würzburg; Würzburg Germany
| | - Tobias Wech
- Department of Diagnostic and Interventional Radiology; University of Würzburg; Würzburg Germany
| | - Valentin Ratz
- Department of Diagnostic and Interventional Radiology; University of Würzburg; Würzburg Germany
| | - Johannes Tran-Gia
- Department of Diagnostic and Interventional Radiology; University of Würzburg; Würzburg Germany
- Department of Nuclear Medicine; University of Würzburg; Würzburg Germany
| | - Henning Neubauer
- Department of Diagnostic and Interventional Radiology; University of Würzburg; Würzburg Germany
| | - Thorsten Bley
- Department of Diagnostic and Interventional Radiology; University of Würzburg; Würzburg Germany
| | - Herbert Köstler
- Department of Diagnostic and Interventional Radiology; University of Würzburg; Würzburg Germany
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27
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Zhou Z, Han F, Yan L, Wang DJJ, Hu P. Golden-ratio rotated stack-of-stars acquisition for improved volumetric MRI. Magn Reson Med 2017; 78:2290-2298. [PMID: 28168738 DOI: 10.1002/mrm.26625] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2016] [Revised: 12/22/2016] [Accepted: 01/09/2017] [Indexed: 11/06/2022]
Abstract
PURPOSE To develop and evaluate an improved stack-of-stars radial sampling strategy for reducing streaking artifacts. METHODS The conventional stack-of-stars sampling strategy collects the same radial angle for every partition (slice) encoding. In an undersampled acquisition, such an aligned acquisition generates coherent aliasing patterns and introduces strong streaking artifacts. We show that by rotating the radial spokes in a golden-angle manner along the partition-encoding direction, the aliasing pattern is modified, resulting in improved image quality for gridding and more advanced reconstruction methods. Computer simulations were performed and phantom as well as in vivo images for three different applications were acquired. RESULTS Simulation, phantom, and in vivo experiments confirmed that the proposed method was able to generate images with less streaking artifact and sharper structures based on undersampled acquisitions in comparison with the conventional aligned approach at the same acceleration factors. By combining parallel imaging and compressed sensing in the reconstruction, streaking artifacts were mostly removed with improved delineation of fine structures using the proposed strategy. CONCLUSIONS We present a simple method to reduce streaking artifacts and improve image quality in 3D stack-of-stars acquisitions by re-arranging the radial spoke angles in the 3D partition direction, which can be used for rapid volumetric imaging. Magn Reson Med 78:2290-2298, 2017. © 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
| | - Lirong Yan
- Laboratory of Functional MRI Technology (LOFT), Stevens Neuroimaging and Informatics Institute, Department of Neurology, University of Southern California, Los Angeles, California, USA
| | - Danny J J Wang
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, California, USA.,Laboratory of Functional MRI Technology (LOFT), Stevens Neuroimaging and Informatics Institute, Department of Neurology, 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.,Biomedical Physics Interdepartmental Graduate Program, University of California, Los Angeles, California, USA
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Chen Z, Xia L, Liu F, Wang Q, Li Y, Zhu X, Huang F. An improved non-Cartesian partially parallel imaging by exploiting artificial sparsity. Magn Reson Med 2016; 78:271-279. [DOI: 10.1002/mrm.26360] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2015] [Revised: 06/16/2016] [Accepted: 07/07/2016] [Indexed: 12/13/2022]
Affiliation(s)
- Zhifeng Chen
- Department of Biomedical Engineering; Zhejiang University; Hangzhou Zhejiang People's Republic of China
| | - Ling Xia
- Department of Biomedical Engineering; Zhejiang University; Hangzhou Zhejiang People's Republic of China
- State Key Lab of CAD & CG; Zhejiang University; Hangzhou Zhejiang People's Republic of China
| | - Feng Liu
- School of Information Technology and Electrical Engineering; The University of Queensland; Brisbane QLD Australia
| | - Qiuliang Wang
- Division of Superconducting Magnet Science and Technology, Institute of Electrical Engineering, Chinese Academy of Sciences; Beijing People's Republic of China
| | - Yi Li
- Division of Superconducting Magnet Science and Technology, Institute of Electrical Engineering, Chinese Academy of Sciences; Beijing People's Republic of China
| | - Xuchen Zhu
- Division of Superconducting Magnet Science and Technology, Institute of Electrical Engineering, Chinese Academy of Sciences; Beijing People's Republic of China
| | - Feng Huang
- Philips Healthcare; Suzhou Jiangsu People's Republic of China
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29
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Wech T, Seiberlich N, Schindele A, Grau V, Diffley L, Gyngell ML, Borzì A, Köstler H, Schneider JE. Development of Real-Time Magnetic Resonance Imaging of Mouse Hearts at 9.4 Tesla--Simulations and First Application. IEEE TRANSACTIONS ON MEDICAL IMAGING 2016; 35:912-920. [PMID: 26595913 PMCID: PMC4948122 DOI: 10.1109/tmi.2015.2501832] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
A novel method for real-time magnetic resonance imaging for the assessment of cardiac function in mice at 9.4 T is proposed. The technique combines a highly undersampled radial gradient echo acquisition with an image reconstruction utilizing both parallel imaging and compressed sensing. Simulations on an in silico phantom were performed to determine the achievable acceleration factor and to optimize regularization parameters. Several parameters characterizing the quality of the reconstructed images (such as spatial and temporal image sharpness or compartment areas) were calculated for this purpose. Subsequently, double-gated segmented cine data as well as non-gated undersampled real-time data using only six projections per timeframe (temporal resolution ∼ 10 ms) were acquired in a mid-ventricular slice of four normal mouse hearts in vivo. The highly accelerated data sets were then subjected to the introduced reconstruction technique and results were validated against the fully sampled references. Functional parameters obtained from real-time and fully sampled data agreed well with a comparable accuracy for left-ventricular volumes and a slightly larger scatter for mass. This study introduces and validates a real-time cine-MRI technique, which significantly reduces scan time in preclinical cardiac functional imaging and has the potential to investigate mouse models with abnormal heart rhythm.
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Affiliation(s)
- Tobias Wech
- Department of Diagnostic and Interventional Radiology, University of Würzburg, Würzburg, Germany, and with the Comprehensive Heart Failure Center, University of Würzburg, Würzburg
| | - Nicole Seiberlich
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
| | | | - Vicente Grau
- Department of Engineering Science, University of Oxford, UK
| | - Leonie Diffley
- Radcliffe Department of Medicine, Division of Cardiovascular Medicine, University of Oxford, UK
| | | | - Alfio Borzì
- Institute of Mathematics, University of Würzburg, Würzburg, Germany
| | - Herbert Köstler
- Department of Diagnostic and Interventional Radiology, University of Würzburg, Würzburg, Germany, and with the Comprehensive Heart Failure Center, University of Würzburg, Würzburg
| | - Jürgen E. Schneider
- Radcliffe Department of Medicine, Division of Cardiovascular Medicine, University of Oxford, UK
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30
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Tran-Gia J, Bisdas S, Köstler H, Klose U. A model-based reconstruction technique for fast dynamic T1 mapping. Magn Reson Imaging 2015; 34:298-307. [PMID: 26597832 DOI: 10.1016/j.mri.2015.10.016] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2015] [Revised: 09/15/2015] [Accepted: 10/17/2015] [Indexed: 11/27/2022]
Abstract
PURPOSE To present a technique for dynamic T1 mapping. MATERIALS AND METHODS A recently proposed model-based reconstruction entitled IR-MAP allows T1 mapping of a single slice from a single radial inversion recovery Look-Locker FLASH acquisition. To enable dynamic T1 mapping, multiple of these acquisitions are consecutively performed, each followed by a waiting period of 3s for relaxation. Next, IR-MAP is used to reconstruct an individual T1 map for each of these acquisitions. Finally, T1 errors caused by insufficient relaxation between subsequent IR pulses are iteratively corrected. RESULTS The functionality of the proposed setup was validated in a phantom and in seven healthy volunteers. Systematic deviations between subsequent T1 maps originating from insufficient relaxation periods were effectively corrected. Additionally, the approach was successfully applied to monitor the T1 dynamic in a patient with primary lymphoma after the intravenous injection of contrast agent. CONCLUSION The proposed setup enables dynamic T1 mapping of a single slice with a spatial resolution of 1.6 mm × 1.6 mm × 3 mm and a temporal resolution of one parameter map every 9 s. It therefore represents a new opportunity to track changes in T1 over time, as it is desirable in many applications such as dynamic contrast-enhanced MRI.
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Affiliation(s)
- Johannes Tran-Gia
- Department of Diagnostic and Interventional Radiology, University of Würzburg, Würzburg, Germany; Department of Nuclear Medicine, University of Würzburg, Würzburg, Germany.
| | - Sotirios Bisdas
- Department of Diagnostic and Interventional Neuroradiology, Eberhard Karls University, Tübingen, Germany; Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, University College London Hospitals, London, United Kingdom
| | - Herbert Köstler
- Department of Diagnostic and Interventional Radiology, University of Würzburg, Würzburg, Germany
| | - Uwe Klose
- Department of Diagnostic and Interventional Neuroradiology, Eberhard Karls University, Tübingen, Germany
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31
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Tran-Gia J, Lohr D, Weng AM, Ritter CO, Stäb D, Bley TA, Köstler H. A model-based reconstruction technique for quantitative myocardial perfusion imaging. Magn Reson Med 2015; 76:880-7. [PMID: 26414857 DOI: 10.1002/mrm.25921] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2015] [Revised: 07/19/2015] [Accepted: 08/14/2015] [Indexed: 12/20/2022]
Abstract
PURPOSE To reduce saturation effects in the arterial input function (AIF) estimation of quantitative myocardial first-pass saturation recovery perfusion imaging by employing a model-based reconstruction. THEORY AND METHODS Imaging was performed with a saturation recovery prepared radial FLASH sequence. A model-based reconstruction was applied for reconstruction. By exploiting prior knowledge about the relaxation process, an image series with different saturation recovery times was reconstructed. By evaluating images with an effective saturation time of approximately 3 ms, saturation effects in the AIF determination were reduced. In a volunteer study, this approach was compared with a standard prebolus technique. RESULTS In comparison to the low-dose injection of a prebolus acquisition, saturation effects were further reduced in the AIFs determined using the model-based approach. These effects, which were clearly visible for all six volunteers, were reflected in a statistically significant difference of up to 20% in the absolute perfusion values. CONCLUSION The application of model-based reconstruction algorithms in quantitative myocardial perfusion imaging promises a significant improvement of the AIF determination. In addition to greatly reducing saturation effects that occur even for the prebolus methods, only a single bolus has to be applied. Magn Reson Med 76:880-887, 2016. © 2015 Wiley Periodicals, Inc.
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Affiliation(s)
- Johannes Tran-Gia
- Department of Diagnostic and Interventional Radiology, University of Würzburg, Germany.,Department of Nuclear Medicine, University of Würzburg, Germany
| | - David Lohr
- Department of Diagnostic and Interventional Radiology, University of Würzburg, Germany.,Comprehensive Heart Failure Center Würzburg, University of Würzburg, Germany
| | - Andreas Max Weng
- Department of Diagnostic and Interventional Radiology, University of Würzburg, Germany
| | - Christian Oliver Ritter
- Department of Diagnostic and Interventional Radiology, University of Würzburg, Germany.,Department of Diagnostic and Interventional Radiology, University Medical Center Göttingen, Germany
| | - Daniel Stäb
- Department of Diagnostic and Interventional Radiology, University of Würzburg, Germany.,Centre for Advanced Imaging, University of Queensland, Brisbane, Australia
| | | | - Herbert Köstler
- Department of Diagnostic and Interventional Radiology, University of Würzburg, Germany.,Comprehensive Heart Failure Center Würzburg, University of Würzburg, Germany
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32
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Campbell-Washburn AE, Faranesh AZ, Lederman RJ, Hansen MS. Magnetic Resonance Sequences and Rapid Acquisition for MR-Guided Interventions. Magn Reson Imaging Clin N Am 2015; 23:669-79. [PMID: 26499283 DOI: 10.1016/j.mric.2015.05.006] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Interventional MR uses rapid imaging to guide diagnostic and therapeutic procedures. One of the attractions of MR-guidance is the abundance of inherent contrast mechanisms available. Dynamic procedural guidance with real-time imaging has pushed the limits of MR technology, demanding rapid acquisition and reconstruction paired with interactive control and device visualization. This article reviews the technical aspects of real-time MR sequences that enable MR-guided interventions.
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Affiliation(s)
- Adrienne E Campbell-Washburn
- Cardiovascular and Pulmonary Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, 9000 Rockville Pike, Building 10, Room B1D416, Bethesda, MD 20892, USA.
| | - Anthony Z Faranesh
- Cardiovascular and Pulmonary Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, 9000 Rockville Pike, Building 10, Room 2C713, Bethesda, MD 20892, USA
| | - Robert J Lederman
- Cardiovascular and Pulmonary Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, 9000 Rockville Pike, Building 10, Room 2C713, Bethesda, MD 20892, USA
| | - Michael S Hansen
- Cardiovascular and Pulmonary Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, 9000 Rockville Pike, Building 10, Room B1D416, Bethesda, MD 20892, USA
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Tran-Gia J, Wech T, Bley T, Köstler H. Model-based acceleration of look-locker T1 mapping. PLoS One 2015; 10:e0122611. [PMID: 25860381 PMCID: PMC4393277 DOI: 10.1371/journal.pone.0122611] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2014] [Accepted: 02/23/2015] [Indexed: 11/19/2022] Open
Abstract
Mapping the longitudinal relaxation time T1 has widespread applications in clinical MRI as it promises a quantitative comparison of tissue properties across subjects and scanners. Due to the long scan times of conventional methods, however, the use of quantitative MRI in clinical routine is still very limited. In this work, an acceleration of Inversion-Recovery Look-Locker (IR-LL) T1 mapping is presented. A model-based algorithm is used to iteratively enforce an exponential relaxation model to a highly undersampled radially acquired IR-LL dataset obtained after the application of a single global inversion pulse. Using the proposed technique, a T1 map of a single slice with 1.6mm in-plane resolution and 4mm slice thickness can be reconstructed from data acquired in only 6s. A time-consuming segmented IR experiment was used as gold standard for T1 mapping in this work. In the subsequent validation study, the model-based reconstruction of a single-inversion IR-LL dataset exhibited a T1 difference of less than 2.6% compared to the segmented IR-LL reference in a phantom consisting of vials with T1 values between 200ms and 3000ms. In vivo, the T1 difference was smaller than 5.5% in WM and GM of seven healthy volunteers. Additionally, the T1 values are comparable to standard literature values. Despite the high acceleration, all model-based reconstructions were of a visual quality comparable to fully sampled references. Finally, the reproducibility of the T1 mapping method was demonstrated in repeated acquisitions. In conclusion, the presented approach represents a promising way for fast and accurate T1 mapping using radial IR-LL acquisitions without the need of any segmentation.
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Affiliation(s)
- Johannes Tran-Gia
- Department of Diagnostic and Interventional Radiology, University of Würzburg, Würzburg, Germany
- * E-mail:
| | - Tobias Wech
- Department of Diagnostic and Interventional Radiology, University of Würzburg, Würzburg, Germany
- Comprehensive Heart Failure Center (CHFC) Würzburg, University of Würzburg, Würzburg, Germany
| | - Thorsten Bley
- Department of Diagnostic and Interventional Radiology, University of Würzburg, Würzburg, Germany
- Comprehensive Heart Failure Center (CHFC) Würzburg, University of Würzburg, Würzburg, Germany
| | - Herbert Köstler
- Department of Diagnostic and Interventional Radiology, University of Würzburg, Würzburg, Germany
- Comprehensive Heart Failure Center (CHFC) Würzburg, University of Würzburg, Würzburg, Germany
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Viallon M, Cuvinciuc V, Delattre B, Merlini L, Barnaure-Nachbar I, Toso-Patel S, Becker M, Lovblad KO, Haller S. State-of-the-art MRI techniques in neuroradiology: principles, pitfalls, and clinical applications. Neuroradiology 2015; 57:441-67. [PMID: 25859832 DOI: 10.1007/s00234-015-1500-1] [Citation(s) in RCA: 55] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2014] [Accepted: 02/04/2015] [Indexed: 12/20/2022]
Abstract
This article reviews the most relevant state-of-the-art magnetic resonance (MR) techniques, which are clinically available to investigate brain diseases. MR acquisition techniques addressed include notably diffusion imaging (diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), and diffusion kurtosis imaging (DKI)) as well as perfusion imaging (dynamic susceptibility contrast (DSC), arterial spin labeling (ASL), and dynamic contrast enhanced (DCE)). The underlying models used to process these images are described, as well as the theoretic underpinnings of quantitative diffusion and perfusion MR imaging-based methods. The technical requirements and how they may help to understand, classify, or follow-up neurological pathologies are briefly summarized. Techniques, principles, advantages but also intrinsic limitations, typical artifacts, and alternative solutions developed to overcome them are discussed. In this article, we also review routinely available three-dimensional (3D) techniques in neuro MRI, including state-of-the-art and emerging angiography sequences, and briefly introduce more recently proposed 3D quantitative neuro-anatomy sequences, and new technology, such as multi-slice and multi-transmit imaging.
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Affiliation(s)
- Magalie Viallon
- CREATIS, UMR CNRS 5220 - INSERM U1044, INSA de Lyon, Université de Lyon, Lyon, France,
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Deshmane A, Blaimer M, Breuer F, Jakob P, Duerk J, Seiberlich N, Griswold M. Self-calibrated trajectory estimation and signal correction method for robust radial imaging using GRAPPA operator gridding. Magn Reson Med 2015; 75:883-96. [PMID: 25765372 DOI: 10.1002/mrm.25648] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2014] [Revised: 01/13/2015] [Accepted: 01/13/2015] [Indexed: 11/09/2022]
Abstract
PURPOSE In radial imaging, projections may become "miscentered" due to gradient errors such as delays and eddy currents. These errors may result in image artifacts and can disrupt the reliability of direct current (DC) navigation. The proposed parallel imaging-based technique retrospectively estimates trajectory error from miscentered radial data without extra acquisitions, hardware, or sequence modification. THEORY AND METHODS After phase correction, self-calibrated GRAPPA operator gridding (GROG) weights are iteratively applied to shift-miscentered projections toward the center of k-space. A search algorithm identifies the shift that aligns the peak k-space signals by maximizing the sum-of-squares DC signal estimate of each projection. The algorithm returns a trajectory estimate and a corrected radial k-space signal. RESULTS Data from a spherical phantom, the head, and the heart demonstrate that image reconstruction with the estimated trajectory restores image quality and reduces artifacts such as streaks and signal voids. The DC signal level is increased and variability is reduced. CONCLUSION Retrospective phase correction and iterative application of GROG can be used to successfully estimate the trajectory error in two-dimensional radial acquisitions for improved image reconstruction without requiring extra data acquisition or sequence modification.
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Affiliation(s)
- Anagha Deshmane
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Martin Blaimer
- Research Center Magnetic-Resonance-Bavaria (MRB), Würzburg, Germany
| | - Felix Breuer
- Research Center Magnetic-Resonance-Bavaria (MRB), Würzburg, Germany
| | - Peter Jakob
- Research Center Magnetic-Resonance-Bavaria (MRB), Würzburg, Germany
| | - Jeffrey Duerk
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.,Department of Radiology, University Hospitals, Cleveland, Ohio, USA
| | - Nicole Seiberlich
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Mark Griswold
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.,Department of Radiology, University Hospitals, Cleveland, Ohio, USA
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Tran-Gia J, Wech T, Hahn D, Bley TA, Köstler H. Consideration of slice profiles in inversion recovery Look-Locker relaxation parameter mapping. Magn Reson Imaging 2014; 32:1021-30. [PMID: 24960366 DOI: 10.1016/j.mri.2014.05.012] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2014] [Revised: 05/08/2014] [Accepted: 05/26/2014] [Indexed: 10/25/2022]
Abstract
PURPOSE To include the flip angle distribution caused by the slice profile into the model used for describing the relaxation curves observed in inversion recovery Look-Locker FLASH T1 mapping for a more accurate determination of the relaxation parameters. MATERIALS AND METHODS For each inversion time, the flip angle dependent signal of the mono-exponential relaxation model is integrated across the slice profile. The resulting Consideration of Slice Profiles (CSP) relaxation curves are compared to the mono-exponential signal model in numerical simulations as well as in phantom and in-vivo experiments. RESULTS All measured relaxation curves showed systematic deviations from a mono-exponential curve increasing with flip angle and T1 but decreasing with repetition time. Additionally, the accuracy of T1 was found to be largely dependent on the temporal coverage of the relaxation curve. All these systematic errors were largely reduced by the CSP model. CONCLUSION The proposed CSP model represents a useful extension of the conventionally used mono-exponential relaxation model. Despite inherent model inaccuracies, the mono-exponential model was found to be sufficient for many T1 mapping situations. However, if only a poor temporal coverage of the relaxation process is achievable or a very precise modeling of the relaxation course is needed as in model-based techniques, the mono-exponential model leads to systematic errors and the CSP model should be used instead.
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Affiliation(s)
- Johannes Tran-Gia
- Department of Diagnostic and Interventional Radiology, University of Würzburg, Würzburg, Germany.
| | - Tobias Wech
- Department of Diagnostic and Interventional Radiology, University of Würzburg, Würzburg, Germany; Comprehensive Heart Failure Center Würzburg, University of Würzburg, Würzburg, Germany
| | - Dietbert Hahn
- Department of Diagnostic and Interventional Radiology, University of Würzburg, Würzburg, Germany
| | - Thorsten A Bley
- Department of Diagnostic and Interventional Radiology, University of Würzburg, Würzburg, Germany; Comprehensive Heart Failure Center Würzburg, University of Würzburg, Würzburg, Germany
| | - Herbert Köstler
- Department of Diagnostic and Interventional Radiology, University of Würzburg, Würzburg, Germany; Comprehensive Heart Failure Center Würzburg, University of Würzburg, Würzburg, Germany
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Li Y. Correlation imaging with arbitrary sampling trajectories. Magn Reson Imaging 2014; 32:551-62. [PMID: 24629517 PMCID: PMC4056256 DOI: 10.1016/j.mri.2014.02.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2013] [Revised: 01/29/2014] [Accepted: 02/02/2014] [Indexed: 10/25/2022]
Abstract
The presented work aims to develop a generalized linear approach to image reconstruction with arbitrary sampling trajectories for high-speed MRI. This approach is based on a previously developed image reconstruction framework, "correlation imaging". In the presented work, correlation imaging with arbitrary sampling trajectories is implemented in a multi-dimensional hybrid space that is formed from the physical sampling space and a virtually defined space. By introducing an undersampling trajectory with both uniformity and randomness in the hybrid space, correlation imaging may take advantage of multiple image reconstruction mechanisms including coil sensitivity encoding, data sparsity and information sharing. This hybrid-space implementation is demonstrated in multi-slice 2D imaging, multi-scan imaging, and radial dynamic imaging. Since more information is used in image reconstruction, it is found that hybrid-space correlation imaging outperforms several conventional techniques. The presented approach will benefit clinical MRI by enabling correlation imaging to be used to accelerate multi-scan clinical protocols that need different sampling trajectories in different scans.
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Affiliation(s)
- Yu Li
- Imaging Research Center, Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
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Wech T, Tran-Gia J, Bley TA, Köstler H. Using self-consistency for an iterative trajectory adjustment (SCITA). Magn Reson Med 2014; 73:1151-7. [PMID: 24803085 DOI: 10.1002/mrm.25244] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2013] [Revised: 02/12/2014] [Accepted: 03/17/2014] [Indexed: 11/06/2022]
Abstract
PURPOSE To iteratively correct for deviations in radial trajectories with no need of additionally performed calibration scans. THEORY AND METHODS Radially acquired data sets-even when undersampled to a certain extend-inherently feature an oversampled area in the center of k-space. Thus, for a perfectly measured trajectory and neglecting noise, information is consistent between multiple measurements gridded to the same Cartesian position within this region. In the case of erroneous coordinates, this accordance-and therefore a correction of the trajectory-can be enforced by an algorithm iteratively shifting the projections with respect to each other by applying the GRAPPA operator. The method was validated in numerical simulations, as well as in radial acquisitions of a phantom and in vivo images at 3T. The results of the correction were compared to a previously proposed correction method. RESULTS The newly introduced technique allowed for a reliable trajectory correction in each of the presented examples. The method was able to remove artifacts as effectively as methods that are based on data from additional calibration scans. CONCLUSION The iterative technique introduced in this paper allows for a correction of trajectory errors in radial imaging with no need for additional calibration data.
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Affiliation(s)
- Tobias Wech
- Department of Radiology, University of Würzburg, Würzburg, Germany; Comprehensive Heart Failure Center (CHFC) Würzburg, University of Würzburg, Würzburg, Germany
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Li S, Chan C, Stockmann JP, Tagare H, Adluru G, Tam LK, Galiana G, Constable RT, Kozerke S, Peters DC. Algebraic reconstruction technique for parallel imaging reconstruction of undersampled radial data: application to cardiac cine. Magn Reson Med 2014; 73:1643-53. [PMID: 24753213 DOI: 10.1002/mrm.25265] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2013] [Revised: 04/03/2014] [Accepted: 04/04/2014] [Indexed: 11/07/2022]
Abstract
PURPOSE To investigate algebraic reconstruction technique (ART) for parallel imaging reconstruction of radial data, applied to accelerated cardiac cine. METHODS A graphics processing unit (GPU)-accelerated ART reconstruction was implemented and applied to simulations, point spread functions and in 12 subjects imaged with radial cardiac cine acquisitions. Cine images were reconstructed with radial ART at multiple undersampling levels (192 Nr × Np = 96 to 16). Images were qualitatively and quantitatively analyzed for sharpness and artifacts, and compared to filtered back-projection, and conjugate gradient SENSE. RESULTS Radial ART provided reduced artifacts and mainly preserved spatial resolution, for both simulations and in vivo data. Artifacts were qualitatively and quantitatively less with ART than filtered back-projection using 48, 32, and 24 Np , although filtered back-projection provided quantitatively sharper images at undersampling levels of 48-24 Np (all P < 0.05). Use of undersampled radial data for generating auto-calibrated coil-sensitivity profiles resulted in slightly reduced quality. ART was comparable to conjugate gradient SENSE. GPU-acceleration increased ART reconstruction speed 15-fold, with little impact on the images. CONCLUSION GPU-accelerated ART is an alternative approach to image reconstruction for parallel radial MR imaging, providing reduced artifacts while mainly maintaining sharpness compared to filtered back-projection, as shown by its first application in cardiac studies.
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Affiliation(s)
- Shu Li
- Department of Radiology, Yale Medical School, New Haven, Connecticut, USA; Institute for Biomedical Engineering, University and ETH Zurich, Switzerland
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Real-time imaging with radial GRAPPA: Implementation on a heterogeneous architecture for low-latency reconstructions. Magn Reson Imaging 2014; 32:747-58. [PMID: 24690453 DOI: 10.1016/j.mri.2014.02.022] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2013] [Revised: 02/11/2014] [Accepted: 02/14/2014] [Indexed: 11/23/2022]
Abstract
Combination of non-Cartesian trajectories with parallel MRI permits to attain unmatched acceleration rates when compared to traditional Cartesian MRI during real-time imaging. However, computationally demanding reconstructions of such imaging techniques, such as k-space domain radial generalized auto-calibrating partially parallel acquisitions (radial GRAPPA) and image domain conjugate gradient sensitivity encoding (CG-SENSE), lead to longer reconstruction times and unacceptable latency for online real-time MRI on conventional computational hardware. Though CG-SENSE has been shown to work with low-latency using a general purpose graphics processing unit (GPU), to the best of our knowledge, no such effort has been made for radial GRAPPA. Radial GRAPPA reconstruction, which is robust even with highly undersampled acquisitions, is not iterative, requiring only significant computation during initial calibration while achieving good image quality for low-latency imaging applications. In this work, we present a very fast, low-latency, reconstruction framework based on a heterogeneous system using multi-core CPUs and GPUs. We demonstrate an implementation of radial GRAPPA that permits reconstruction times on par with or faster than acquisition of highly accelerated datasets in both cardiac and dynamic musculoskeletal imaging scenarios. Acquisition and reconstruction times are reported.
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Usman M, Vaillant G, Atkinson D, Schaeffter T, Prieto C. Compressive manifold learning: Estimating one-dimensional respiratory motion directly from undersampled k-space data. Magn Reson Med 2013; 72:1130-40. [DOI: 10.1002/mrm.25010] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2013] [Revised: 09/06/2013] [Accepted: 10/02/2013] [Indexed: 11/07/2022]
Affiliation(s)
- Muhammad Usman
- King's College London, Division of Imaging Sciences and Biomedical Engineering, British Heart Foundation (BHF) Centre of Excellence, Medical Engineering Centre of Research Excellence, London, United Kingdom
| | - Ghislain Vaillant
- King's College London, Division of Imaging Sciences and Biomedical Engineering, British Heart Foundation (BHF) Centre of Excellence, Medical Engineering Centre of Research Excellence, London, United Kingdom
| | - David Atkinson
- University College London, Centre for Medical Imaging, London, United Kingdom
| | - Tobias Schaeffter
- King's College London, Division of Imaging Sciences and Biomedical Engineering, British Heart Foundation (BHF) Centre of Excellence, Medical Engineering Centre of Research Excellence, London, United Kingdom
| | - Claudia Prieto
- King's College London, Division of Imaging Sciences and Biomedical Engineering, British Heart Foundation (BHF) Centre of Excellence, Medical Engineering Centre of Research Excellence, London, United Kingdom
- Pontificia Universidad Católica de Chile, Escuela de Ingeniería, Santiago, Chile
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Edelman RR, Giri S, Dunkle E, Galizia M, Amin P, Koktzoglou I. Quiescent-inflow single-shot magnetic resonance angiography using a highly undersampled radial k-space trajectory. Magn Reson Med 2013; 70:1662-8. [PMID: 23348595 DOI: 10.1002/mrm.24596] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2012] [Revised: 11/01/2012] [Accepted: 11/26/2012] [Indexed: 11/09/2022]
Abstract
PURPOSE We hypothesized that high undersampling factors could be used in conjunction with radial quiescent-inflow single-shot magnetic resonance angiography (MRA) to accelerate the data acquisition and enable multislice acquisitions. METHODS Seven subjects were imaged on a 1.5 T MRI system. For multislice quiescent-inflow single-shot MRA, the venous saturation radiofrequency pulse, in-plane saturation radiofrequency pulse, and quiescent interval were applied only once before the first slice. RESULTS The mean (standard deviation) measurements for the intra-arterial signal-to-noise ratio were as follows: Cartesian 1 slice-29.3 (5.5); radial 1 slice, 92 views-22.3 (3.6); radial 1 slice, 46 views-18.5 (2.0); radial 2 slices, 46 views-18.3 (3.2); and radial 3 slices, 32 views-21.7 (3.9), normalized for pixel size to 15.8. Horizontal striping was present with multislice radial quiescent-inflow single-shot MRA (especially with the three-slice acquisition) due to variable T1 relaxation between the concurrently acquired slices, but the image quality remained diagnostic. Vascular pathology in patients with peripheral arterial disease was well shown by all techniques. CONCLUSION Very high undersampling factors in excess of 18 have been demonstrated for nonenhanced MRA using a radial quiescent-inflow single-shot technique, enabling the acquisition of two to three slices per cardiac cycle. Scan time for a complete peripheral MRA could be shortened to 2 min or less.
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Affiliation(s)
- R R Edelman
- NorthShore University HealthSystem, Evanston, Illinois, USA; Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
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Tran-Gia J, Stäb D, Wech T, Hahn D, Köstler H. Model-based Acceleration of Parameter mapping (MAP) for saturation prepared radially acquired data. Magn Reson Med 2013; 70:1524-34. [PMID: 23315831 DOI: 10.1002/mrm.24600] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2012] [Revised: 10/20/2012] [Accepted: 11/21/2012] [Indexed: 11/06/2022]
Abstract
A reconstruction technique called Model-based Acceleration of Parameter mapping (MAP) is presented allowing for quantification of longitudinal relaxation time and proton density from radial single-shot measurements after saturation recovery magnetization preparation. Using a mono-exponential model in image space, an iterative fitting algorithm is used to reconstruct one well resolved and consistent image for each of the projections acquired during the saturation recovery relaxation process. The functionality of the algorithm is examined in numerical simulations, phantom experiments, and in-vivo studies. MAP reconstructions of single-shot acquisitions feature the same image quality and resolution as fully sampled reference images in phantom and in-vivo studies. The longitudinal relaxation times obtained from the MAP reconstructions are in very good agreement with the reference values in numerical simulations as well as phantom and in-vivo measurements. Compared to available contrast manipulation techniques, no averaging of projections acquired at different time points of the relaxation process is required in MAP imaging. The proposed technique offers new ways of extracting quantitative information from single-shot measurements acquired after magnetization preparation. The reconstruction simultaneously yields images with high spatiotemporal resolution fully consistent with the acquired data as well as maps of the effective longitudinal relaxation parameter and the relative proton density.
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Li S, Galiana G, Tam L, Kozerke S, Stockmann JP, Constable RT, Peters DC. Cardiac cine with ART for radial parallel imaging reconstruction. J Cardiovasc Magn Reson 2013. [PMCID: PMC3559413 DOI: 10.1186/1532-429x-15-s1-e34] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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Saybasili H, Derbyshire JA, Kellman P, Griswold MA, Ozturk C, Lederman RJ, Seiberlich N. RT-GROG: parallelized self-calibrating GROG for real-time MRI. Magn Reson Med 2010; 64:306-12. [PMID: 20577983 PMCID: PMC3406175 DOI: 10.1002/mrm.22351] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2009] [Accepted: 12/16/2009] [Indexed: 11/07/2022]
Abstract
A real-time implementation of self-calibrating Generalized Autocalibrating Partially Parallel Acquisitions (GRAPPA) operator gridding for radial acquisitions is presented. Self-calibrating GRAPPA operator gridding is a parallel-imaging-based, parameter-free gridding algorithm, where coil sensitivity profiles are used to calculate gridding weights. Self-calibrating GRAPPA operator gridding's weight-set calculation and image reconstruction steps are decoupled into two distinct processes, implemented in C++ and parallelized. This decoupling allows the weights to be updated adaptively in the background while image reconstruction threads use the most recent gridding weights to grid and reconstruct images. All possible combinations of two-dimensional gridding weights G(x)(m)G(y)(n) are evaluated for m,n = {-0.5, -0.4, ..., 0, 0.1, ..., 0.5} and stored in a look-up table. Consequently, the per-sample two-dimensional weights calculation during gridding is eliminated from the reconstruction process and replaced by a simple look-up table access. In practice, up to 34x faster reconstruction than conventional (parallelized) self-calibrating GRAPPA operator gridding is achieved. On a 32-coil dataset of size 128 x 64, reconstruction performance is 14.5 frames per second (fps), while the data acquisition is 6.6 fps.
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Affiliation(s)
- Haris Saybasili
- Translational Medicine Branch, National Institutes of Health/National Heart, Lung and Blood Institute (NHLBI), Department of Health and Human Services (DHHS), Bethesda, Maryland 20892-1061, USA.
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Saybasili H, Derbyshire JA, Kellman P, Griswold MA, Ozturk C, Seiberlich N. Real-time low-latency self-calibrating grog for interventional mri. J Cardiovasc Magn Reson 2010. [DOI: 10.1186/1532-429x-12-s1-p61] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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47
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Seiberlich N, Breuer FA, Ehses P, Moriguchi H, Blaimer M, Jakob PM, Griswold MA. Using the GRAPPA operator and the generalized sampling theorem to reconstruct undersampled non-Cartesian data. Magn Reson Med 2009; 61:705-15. [PMID: 19145634 DOI: 10.1002/mrm.21891] [Citation(s) in RCA: 14] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
As expected from the generalized sampling theorem of Papoulis, the use of a bunched sampling acquisition scheme in conjunction with a conjugate gradient (CG) reconstruction algorithm can decrease scan time by reducing the number of phase-encoding lines needed to generate an unaliased image at a given resolution. However, the acquisition of such bunched data requires both modified pulse sequences and high gradient performance. A novel method of generating the "bunched" data using self-calibrating GRAPPA operator gridding (GROG), a parallel imaging method that shifts data points by small distances in k-space (with Deltak usually less than 1.0, depending on the receiver coil) using the GRAPPA operator, is presented here. With the CG reconstruction method, these additional "bunched" points can then be used to reconstruct an image with reduced artifacts from undersampled data. This method is referred to as GROG-facilitated bunched phase encoding (BPE), or GROG-BPE. To better understand how the patterns of bunched points, maximal blip size, and number of bunched points affect the reconstruction quality, a number of simulations were performed using the GROG-BPE approach. Finally, to demonstrate that this method can be combined with a variety of trajectories, examples of images with reduced artifacts reconstructed from undersampled in vivo radial, spiral, and rosette data are shown.
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Affiliation(s)
- Nicole Seiberlich
- Department of Radiology, University Hospitals of Cleveland, Cleveland, Ohio 44106, USA.
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