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Feng L, Chandarana H. Accelerated Abdominal MRI: A Review of Current Methods and Applications. J Magn Reson Imaging 2025. [PMID: 40103292 DOI: 10.1002/jmri.29750] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2024] [Revised: 02/11/2025] [Accepted: 02/12/2025] [Indexed: 03/20/2025] Open
Abstract
MRI is widely used for the diagnosis and management of various abdominal diseases involving organs such as the liver, pancreas, and kidneys. However, one major limitation of MRI is its relatively slow imaging speed compared to other modalities. In addition, respiratory motion poses a significant challenge in abdominal MRI, often requiring patients to hold their breath multiple times during an exam. This requirement can be particularly challenging for sick, elderly, and pediatric patients, who may have reduced breath-holding capacity. As a result, rapid imaging plays an important role in routine clinical abdominal MRI exams. Accelerated data acquisition not only reduces overall exam time but also shortens breath-hold durations, thereby improving patient comfort and compliance. Over the past decade, significant advancements in rapid MRI have led to the development of various accelerated imaging techniques for routine clinical use. These methods improve abdominal MRI by enhancing imaging speed, motion compensation, and overall image quality. Integrating these techniques into clinical practice also enables new applications that were previously challenging. This paper provides a concise yet comprehensive overview of rapid imaging techniques applicable to abdominal MRI and discusses their advantages, limitations, and potential clinical applications. By the end of this review, readers are expected to learn the latest advances in accelerated abdominal MRI and explore new frontiers in this evolving field. Evidence Level: N/A Technical Efficacy: Stage 5.
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Affiliation(s)
- Li Feng
- Center for Advanced Imaging Innovation and Research (CAI2R), New York University Grossman School of Medicine, New York, New York, USA
| | - Hersh Chandarana
- Center for Advanced Imaging Innovation and Research (CAI2R), New York University Grossman School of Medicine, New York, New York, USA
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Najeeb F, Amjad K, Ullah I, Omer H. SC-GROG followed by L+S reconstruction with multiple sparsity constraints for accelerated Golden-angle-radial DCE-MRI. PLoS One 2025; 20:e0318102. [PMID: 39951435 PMCID: PMC11828349 DOI: 10.1371/journal.pone.0318102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Accepted: 01/09/2025] [Indexed: 02/16/2025] Open
Abstract
The GRASP (Golden-angle-radial Sparse Parallel MRI) is a contemporary method for reconstructing dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). This method combines the temporal incoherence of stack-of-stars Golden-angle-radial sampling pattern and acceleration capability of parallel MRI (PI) and compressed sensing (CS) for highly accelerated free-breathing DCE-MRI reconstruction. GRASP uses Temporal Total Variation (TV) norm as a sparsity transform to promote sparsity among multi-coil MRI data and Nonlinear Conjugate Gradient (NL-CG) algorithm to obtain an optimal solution. Additionally, GRASP uses NUFFT gridding to map Golden-angle-radial data to Cartesian grid before NL-CG based CS reconstruction. However, major limitations of GRASP include the temporal averaging effect due to Temporal TV, leading to a degradation in the dynamic contrast of DCE-MRI, and a high computational burden/reconstruction time due to repeated NUFFT gridding/degridding in NL-CG reconstruction. This paper introduces a novel approach to address limitations in GRASP reconstruction technique for free-breathing DCE-MRI. The proposed method combines SC-GROG gridding with low-rank plus sparse (L+S) reconstruction using multiple sparsity constraints for accelerated Golden-angle-radial DCE-MRI with improved temporal resolution and dynamic contrast. Monotone FISTA with variable acceleration (MFISTA-VA) is used to optimize the L+S optimization problem. Further, SC-GROG gridding is used to map Golden-angle radial data to Cartesian grid before L+S reconstruction. The proposed method is tested on two different 3T free-breathing in-vivo DCE-MRI datasets. Reconstruction results of the proposed method are evaluated by using: (i) convergence error, (ii) peak and mean values of arterial signal intensity in the selected region of interest (ROI) of DCE MR Images, and (iii) reconstruction time. Results show that the proposed method provides significant improvements in the reconstruction time and dynamic contrast than the conventional Golden-angle-radial DCE-MRI reconstruction techniques (i.e., GRASP, XD-GRASP). Furthermore, convergence analysis shows that integration of MFISTA-VA in L+S reconstruction provides faster convergence compared to conventional L+S reconstruction.
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Affiliation(s)
- Faisal Najeeb
- MIPRG Research Group, Electrical and Computer Engineering Department, COMSATs University Islamabad, Islamabad, Pakistan
| | - Kashif Amjad
- College of Computer Engineering & Science, Prince Mohammad Bin Fahd University, Khobar, Saudi Arabia
| | - Irfan Ullah
- MIPRG Research Group, Electrical and Computer Engineering Department, COMSATs University Islamabad, Islamabad, Pakistan
| | - Hammad Omer
- MIPRG Research Group, Electrical and Computer Engineering Department, COMSATs University Islamabad, Islamabad, Pakistan
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Xu X, Leforestier R, Xia D, Block KT, Feng L. MRI of GlycoNOE in the human liver using GraspNOE-Dixon. Magn Reson Med 2025; 93:507-518. [PMID: 39367632 DOI: 10.1002/mrm.30270] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Revised: 08/06/2024] [Accepted: 08/07/2024] [Indexed: 10/06/2024]
Abstract
PURPOSE The objective of this study was to develop a new MRI technique for non-invasive, free-breathing imaging of glycogen in the human liver using the nuclear Overhauser effect (NOE). METHODS The proposed method, called GraspNOE-Dixon, uses a novel MRI sequence that combines steady-state saturation-transfer preparation with multi-echo golden-angle radial stack-of-stars sampling. Multi-echo acquisition enables fat/water-separated imaging for quantification of water-specific NOE. Image reconstruction is performed using the improved golden-angle radial sparse parallel imaging (GRASP-Pro) technique to exploit spatiotemporal correlations in dynamic images. To evaluate the proposed technique, imaging experiments were first performed on glycogen phantoms, followed by in vivo studies involving healthy volunteers and patients with fatty liver disease. In addition, a comparative assessment of signal changes before and after a 12-h fasting period was performed. RESULTS Evaluation experiments on glycogen phantoms showed a robust linear correlation between the NOE signal and glycogen concentration. In vivo experiments demonstrated motion-robust NOE-weighted images, with potential for further acceleration. In subjects with varying liver fat content, the fat/water separation approach resulted in distortion-free Z-spectra, enabling the quantification of glycogen NOE. An approximately one-third reduction in the NOE signal was observed following a 12-h fasting period, consistent with a decrease in glycogen level. CONCLUSION This study introduces a clinically feasible imaging technique, GraspNOE-Dixon, for free-breathing volumetric multi-echo imaging of hepatic glycogen at 3 T. The motion robust imaging technique developed here may also have applications in other body areas beyond liver imaging.
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Affiliation(s)
- Xiang Xu
- BioMedical Engineering and Imaging Institute (BMEII), Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Department of Diagnostic, Molecular and Interventional Radiology, The Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Rodolphe Leforestier
- BioMedical Engineering and Imaging Institute (BMEII), Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Department of Diagnostic, Molecular and Interventional Radiology, The Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Ding Xia
- BioMedical Engineering and Imaging Institute (BMEII), Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Department of Diagnostic, Molecular and Interventional Radiology, The Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Kai Tobias Block
- Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - Li Feng
- BioMedical Engineering and Imaging Institute (BMEII), Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Department of Diagnostic, Molecular and Interventional Radiology, The Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University School of Medicine, New York, New York, USA
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Mertens AJ, Cheng HLM. Accelerated dynamic magnetic resonance imaging from Spatial-Subspace Reconstructions (SPARS). PLoS One 2025; 20:e0317271. [PMID: 39888888 PMCID: PMC11785264 DOI: 10.1371/journal.pone.0317271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Accepted: 12/24/2024] [Indexed: 02/02/2025] Open
Abstract
Dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) ideally requires a high spatial and a high temporal resolution, but hardware limitations prevent acquisitions from achieving both simultaneously-either high temporal resolution is exchanged for spatial resolution, or vice versa. Even state-of-the-art image reconstruction techniques that infer missing data in a sparse acquisition space cannot recover the loss of spatial detail, especially at high temporal acceleration rates. The purpose of this paper is to introduce the concept of spatial subspace reconstructions (SPARS) and demonstrate its ability to reconstruct high spatial resolution dynamic images from as few as one acquired k-space spoke per time frame in a dynamic series. Briefly, a low-temporal-high-spatial resolution organization of the acquired raw data is used to estimate the basis vectors of the spatial subspace in which the high-temporal-high-spatial ground truth data resides. This subspace is then used to estimate entire images from single k-space spokes. In both simulated and human in-vivo data, the proposed SPARS reconstruction method outperformed standard GRASP and GRASP-Pro reconstruction, providing a shorter reconstruction time and yielding higher accuracy from both a spatial and temporal perspective.
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Affiliation(s)
- Alexander J. Mertens
- The Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, Toronto, Canada
- Ted Rogers Centre for Heart Research, Translational Biology & Engineering Program, Toronto, Canada
| | - Hai-Ling Margaret Cheng
- The Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, Toronto, Canada
- Ted Rogers Centre for Heart Research, Translational Biology & Engineering Program, Toronto, Canada
- Institute of Biomedical Engineering, University of Toronto, Toronto, Canada
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Wennen M, Stehling W, Marcus JT, Kuijer JPA, Lavini C, Heunks LMA, Strijkers GJ, Coolen BF, Nederveen AJ, Gurney‐Champion OJ. A signal model for fat-suppressed T 1-mapping and dynamic contrast-enhanced MRI with interrupted spoiled gradient-echo readout. NMR IN BIOMEDICINE 2025; 38:e5289. [PMID: 39571186 PMCID: PMC11617136 DOI: 10.1002/nbm.5289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/23/2024] [Revised: 10/16/2024] [Accepted: 10/17/2024] [Indexed: 12/06/2024]
Abstract
The conventional gradient-echo steady-state signal model is the basis of various spoiled gradient-echo (SPGR) based quantitative MRI models, including variable flip angle (VFA) MRI and dynamic contrast-enhanced MRI (DCE). However, including preparation pulses, such as fat suppression or saturation bands, disrupts the steady-state and leads to a bias in T1 and DCE parameter estimates. This work introduces a signal model that improves the accuracy of VFA T1-mapping and DCE for interrupted spoiled gradient-echo (I-SPGR) acquisitions. The proposed model was applied to a VFA T1-mapping I-SPGR sequence in the Gold Standard T1-phantom (3 T), in the brain of four healthy volunteers (3 T), and to an abdominal DCE examination (1.5 T). T1-values obtained with the proposed and conventional model were compared to reference T1-values. Bland-Altman analysis (phantom) and analysis of variance (in vivo) were used to test whether bias from both methods was significantly different (p = 0.05). The proposed model outperformed the conventional model by decreasing the bias in the phantom with respect to the phantom reference values (mean bias -2 vs. -35% at 3 T) and in vivo with respect to the conventional SPGR (-6 vs. -37% bias in T1, p < 0.01). The proposed signal model estimated approximately 48% (depending on baseline T1) higher contrast concentrations in vivo, which resulted in decreased DCE pharmacokinetic parameter estimates of up to 35%. The proposed signal model improves the accuracy of quantitative parameter estimation from disrupted steady-state I-SPGR sequences. It therefore provides a flexible method for applying fat suppression, saturation bands, and other preparation pulses in VFA T1-mapping and DCE.
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Affiliation(s)
- Myrte Wennen
- Department of Radiology and Nuclear MedicineAmsterdam University Medical CenterAmsterdamThe Netherlands
- Department of Intensive CareErasmus Medical CenterRotterdamThe Netherlands
| | - Wilhelm Stehling
- Department of Radiology and Nuclear MedicineAmsterdam University Medical CenterAmsterdamThe Netherlands
| | - J. Tim Marcus
- Department of Radiology and Nuclear MedicineAmsterdam University Medical CenterAmsterdamThe Netherlands
| | - Joost P. A. Kuijer
- Department of Radiology and Nuclear MedicineAmsterdam University Medical CenterAmsterdamThe Netherlands
| | - Cristina Lavini
- Department of Radiology and Nuclear MedicineAmsterdam University Medical CenterAmsterdamThe Netherlands
| | - Leo M. A. Heunks
- Department of Intensive CareRadboud University Medical CenterNijmegenThe Netherlands
| | - Gustav J. Strijkers
- Department of Biomedical Engineering & PhysicsAmsterdam University Medical CenterAmsterdamThe Netherlands
| | - Bram F. Coolen
- Department of Biomedical Engineering & PhysicsAmsterdam University Medical CenterAmsterdamThe Netherlands
| | - Aart J. Nederveen
- Department of Radiology and Nuclear MedicineAmsterdam University Medical CenterAmsterdamThe Netherlands
| | - Oliver J. Gurney‐Champion
- Department of Radiology and Nuclear MedicineAmsterdam University Medical CenterAmsterdamThe Netherlands
- Cancer Center Amsterdam, Imaging and BiomarkersAmsterdamThe Netherlands
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Chen J, Huang C, Shanbhogue K, Xia D, Bruno M, Huang Y, Block KT, Chandarana H, Feng L. DCE-MRI of the liver with sub-second temporal resolution using GRASP-Pro with navi-stack-of-stars sampling. NMR IN BIOMEDICINE 2024; 37:e5262. [PMID: 39323100 PMCID: PMC11998610 DOI: 10.1002/nbm.5262] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/11/2024] [Revised: 09/09/2024] [Accepted: 09/10/2024] [Indexed: 09/27/2024]
Abstract
Respiratory motion-induced image blurring and artifacts can compromise image quality in dynamic contrast-enhanced MRI (DCE-MRI) of the liver. Despite remarkable advances in respiratory motion detection and compensation in past years, these techniques have not yet seen widespread clinical adoption. The accuracy of image-based motion detection can be especially compromised in the presence of contrast enhancement and/or in situations involving deep and/or irregular breathing patterns. This work proposes a framework that combines GRASP-Pro (Golden-angle RAdial Sparse Parallel MRI with imProved performance) MRI with a new radial sampling scheme called navi-stack-of-stars for free-breathing DCE-MRI of the liver without the need for explicit respiratory motion compensation. A prototype 3D golden-angle radial sequence with a navi-stack-of-stars sampling scheme that intermittently acquires a 2D navigator was implemented. Free-breathing DCE-MRI of the liver was conducted in 24 subjects at 3T including 17 volunteers and 7 patients. GRASP-Pro reconstruction was performed with a temporal resolution of 0.34-0.45 s per volume, whereas standard GRASP reconstruction was performed with a temporal resolution of 15 s per volume. Motion compensation was not performed in all image reconstruction tasks. Liver images in different contrast phases from both GRASP and GRASP-Pro reconstructions were visually scored by two experienced abdominal radiologists for comparison. The nonparametric paired two-tailed Wilcoxon signed-rank test was used to compare image quality scores, and the Cohen's kappa coefficient was calculated to evaluate the inter-reader agreement. GRASP-Pro MRI with sub-second temporal resolution consistently received significantly higher image quality scores (P < 0.05) than standard GRASP MRI throughout all contrast enhancement phases and across all assessment categories. There was a substantial inter-reader agreement for all assessment categories (ranging from 0.67 to 0.89). The proposed technique using GRASP-Pro reconstruction with navi-stack-of-stars sampling holds great promise for free-breathing DCE-MRI of the liver without respiratory motion compensation.
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Affiliation(s)
- Jingjia Chen
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
- Center for Advanced Imaging Innovation and Research (CAIR), Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
| | - Chenchan Huang
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
- Center for Advanced Imaging Innovation and Research (CAIR), Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
| | - Krishna Shanbhogue
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
- Center for Advanced Imaging Innovation and Research (CAIR), Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
| | - Ding Xia
- BioMedical Engineering and Imaging Institute (BMEII), Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Mary Bruno
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
- Center for Advanced Imaging Innovation and Research (CAIR), Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
| | - Yuhui Huang
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
- Center for Advanced Imaging Innovation and Research (CAIR), Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
| | - Kai Tobias Block
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
- Center for Advanced Imaging Innovation and Research (CAIR), Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
| | - Hersh Chandarana
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
- Center for Advanced Imaging Innovation and Research (CAIR), Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
| | - Li Feng
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
- Center for Advanced Imaging Innovation and Research (CAIR), Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
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Ding Z, She H, Chen Q, Du YP. Reduction of ringing artifacts induced by diaphragm drifting in free-breathing dynamic pulmonary MRI using 3D koosh-ball acquisition. Magn Reson Med 2024; 92:2021-2036. [PMID: 38968132 DOI: 10.1002/mrm.30207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2024] [Revised: 06/13/2024] [Accepted: 06/14/2024] [Indexed: 07/07/2024]
Abstract
PURPOSE To reduce the ringing artifacts of the motion-resolved images in free-breathing dynamic pulmonary MRI. METHODS A golden-step based interleaving (GSI) technique was proposed to reduce ringing artifacts induced by diaphragm drifting. The pulmonary MRI data were acquired using a superior-inferior navigated 3D radial UTE sequence in an interleaved manner during free breathing. Successive interleaves were acquired in an incoherent fashion along the polar direction. Four-dimensional images were reconstructed from the motion-resolved k-space data obtained by retrospectively binning. The reconstruction algorithms included standard nonuniform fast Fourier transform (NUFFT), Voronoi-density-compensated NUFFT, extra-dimensional UTE, and motion-state weighted motion-compensation reconstruction. The proposed interleaving technique was compared with a conventional sequential interleaving (SeqI) technique on a phantom and eight subjects. RESULTS The quantified ringing artifacts level in the motion-resolved image is positively correlated with the quantified nonuniformity level of the corresponding k-space. The nonuniformity levels of the end-expiratory and end-inspiratory k-space binned from GSI data (0.34 ± 0.07, 0.33 ± 0.05) are significantly lower with statistical significance (p < 0.05) than that binned from SeqI data (0.44 ± 0.11, 0.42 ± 0.12). Ringing artifacts are substantially reduced in the dynamic images of eight subjects acquired using the proposed technique in comparison with that acquired using the conventional SeqI technique. CONCLUSION Ringing artifacts in the motion-resolved images induced by diaphragm drifting can be reduced using the proposed GSI technique for free-breathing dynamic pulmonary MRI. This technique has the potential to reduce ringing artifacts in free-breathing liver and kidney MRI based on full-echo interleaved 3D radial acquisition.
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Affiliation(s)
- Zekang Ding
- National Engineering Research Center of Advanced Magnetic Resonance Technologies for Diagnosis and Therapy, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
- Central Research Institute, United Imaging Group, Shanghai, China
| | - Huajun She
- National Engineering Research Center of Advanced Magnetic Resonance Technologies for Diagnosis and Therapy, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Qun Chen
- Central Research Institute, United Imaging Group, Shanghai, China
| | - Yiping P Du
- National Engineering Research Center of Advanced Magnetic Resonance Technologies for Diagnosis and Therapy, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
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Muslu Y, Tamada D, Roberts NT, Cashen TA, Mandava S, Kecskemeti SR, Hernando D, Reeder SB. Free-breathing, fat-corrected T 1 mapping of the liver with stack-of-stars MRI, and joint estimation of T 1, PDFF, R 2 * , and B 1 + . Magn Reson Med 2024; 92:1913-1932. [PMID: 38923009 DOI: 10.1002/mrm.30182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 05/03/2024] [Accepted: 05/16/2024] [Indexed: 06/28/2024]
Abstract
PURPOSE Quantitative T1 mapping has the potential to replace biopsy for noninvasive diagnosis and quantitative staging of chronic liver disease. Conventional T1 mapping methods are confounded by fat andB 1 + $$ {B}_1^{+} $$ inhomogeneities, resulting in unreliable T1 estimations. Furthermore, these methods trade off spatial resolution and volumetric coverage for shorter acquisitions with only a few images obtained within a breath-hold. This work proposes a novel, volumetric (3D), free-breathing T1 mapping method to account for multiple confounding factors in a single acquisition. THEORY AND METHODS Free-breathing, confounder-corrected T1 mapping was achieved through the combination of non-Cartesian imaging, magnetization preparation, chemical shift encoding, and a variable flip angle acquisition. A subspace-constrained, locally low-rank image reconstruction algorithm was employed for image reconstruction. The accuracy of the proposed method was evaluated through numerical simulations and phantom experiments with a T1/proton density fat fraction phantom at 3.0 T. Further, the feasibility of the proposed method was investigated through contrast-enhanced imaging in healthy volunteers, also at 3.0 T. RESULTS The method showed excellent agreement with reference measurements in phantoms across a wide range of T1 values (200 to 1000 ms, slope = 0.998 (95% confidence interval (CI) [0.963 to 1.035]), intercept = 27.1 ms (95% CI [0.4 54.6]), r2 = 0.996), and a high level of repeatability. In vivo imaging studies demonstrated moderate agreement (slope = 1.099 (95% CI [1.067 to 1.132]), intercept = -96.3 ms (95% CI [-82.1 to -110.5]), r2 = 0.981) compared to saturation recovery-based T1 maps. CONCLUSION The proposed method produces whole-liver, confounder-corrected T1 maps through simultaneous estimation of T1, proton density fat fraction, andB 1 + $$ {B}_1^{+} $$ in a single, free-breathing acquisition and has excellent agreement with reference measurements in phantoms.
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Affiliation(s)
- Yavuz Muslu
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Daiki Tamada
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | | | | | | | | | - Diego Hernando
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Scott B Reeder
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Medicine, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Department of Emergency Medicine, University of Wisconsin-Madison, Madison, Wisconsin, USA
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Chen L, Xu J, Liu D, Ji B, Wang J, Zeng X, Zhang J, Feng L. High-resolution free-breathing hepatobiliary phase MRI of the liver using XD-GRASP. Magn Reson Imaging 2024; 109:42-48. [PMID: 38447629 DOI: 10.1016/j.mri.2024.03.002] [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: 10/25/2023] [Revised: 02/25/2024] [Accepted: 03/01/2024] [Indexed: 03/08/2024]
Abstract
PURPOSE To evaluate the performance of high-resolution free-breathing (FB) hepatobiliary phase imaging of the liver using the eXtra-Dimension Golden-angle RAdial Sparse Parallel (XD-GRASP) MRI technique. METHODS Fifty-eight clinical patients (41 males, mean age = 52.9 ± 12.9) with liver lesions who underwent dynamic contrast-enhanced MRI with a liver-specific contrast agent were prospectively recruited for this study. Both breath-hold volumetric interpolated examination (BH-VIBE) imaging and FB imaging were performed during the hepatobiliary phase. FB images were acquired using a stack-of-stars golden-angle radial sequence and were reconstructed using the XD-GRASP method. Two experienced radiologists blinded to acquisition schemes independently scored the overall image quality, liver edge sharpness, hepatic vessel clarity, conspicuity of lesion, and overall artifact level of each image. The non-parametric paired two-tailed Wilcoxon signed-rank test was used for statistical analysis. RESULTS Compared to BH-VIBE images, XD-GRASP images received significantly higher scores (P < 0.05) for the liver edge sharpness (4.83 ± 0.45 vs 4.29 ± 0.46), the hepatic vessel clarity (4.64 ± 0.67 vs 4.15 ± 0.56) and the conspicuity of lesion (4.75 ± 0.53 vs 4.31 ± 0.50). There were no significant differences (P > 0.05) between BH-VIBE and XD-GRASP images for the overall image quality (4.61 ± 0.50 vs 4.74 ± 0.47) and the overall artifact level (4.13 ± 0.44 vs 4.05 ± 0.61). CONCLUSION Compared to conventional BH-VIBE MRI, FB radial acquisition combined with XD-GRASP reconstruction facilitates higher spatial resolution imaging of the liver during the hepatobiliary phase. This enhancement can significantly improve the visualization and evaluation of the liver.
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Affiliation(s)
- Lihua Chen
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China
| | - Jian Xu
- Department of General Surgery, 904th Hospital, Wuxi, Jiangsu, China
| | - Daihong Liu
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China
| | - Bing Ji
- Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Jian Wang
- Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Xianchun Zeng
- Department of Radiology, Guizhou Provincial People's Hospital, Guizhou, China.
| | - Jiuquan Zhang
- Department of Radiology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing, China.
| | - 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, NY 10016, USA
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Xu P, Meersmann T, Wang J, Wang C. Review of oxygen-enhanced lung mri: Pulse sequences for image acquisition and T 1 measurement. Med Phys 2023; 50:5987-6007. [PMID: 37345214 DOI: 10.1002/mp.16553] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Revised: 03/23/2023] [Accepted: 05/16/2023] [Indexed: 06/23/2023] Open
Abstract
Oxygen-enhanced MR imaging (OE-MRI) is a special proton imaging technique that can be performed without modifying the scanner hardware. Many fundamental studies have been conducted following the initial reporting of this technique in 1996, illustrating the high potential for its clinical application. This review aims to summarise and analyse current pulse sequences and T1 measurement methods for OE-MRI, including fundamental theories, existing pulse sequences applied to OE-MRI acquisition and T1 mapping. Wash-in and wash-out time identify lung function and are sensitive to ventilation; thus, dynamic OE-MRI is also discussed in this review. We compare OE-MRI with the primary competitive technique, hyperpolarised gas MRI. Finally, an overview of lower-field applications of OE-MRI is highlighted, as relatively recent publications demonstrated positive results. Lower-field OE-MRI, which is lower than 1.5 T, could be an alternative modality for detecting lung diseases. This educational review is aimed at researchers who want a quick summary of the steps needed to perform pulmonary OE-MRI with a particular focus on sequence design, settings, and quantification methods.
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Affiliation(s)
- Pengfei Xu
- Department of Electrical and Electronic Engineering, Faculty of Science and Engineering, University of Nottingham Ningbo China, Ningbo, China
| | - Thomas Meersmann
- Sir Peter Mansfield Magnetic Imaging Centre, University of Nottingham, Nottingham, UK
- Nottingham Ningbo China Beacons of Excellence Research and Innovation Institute, Ningbo, China
| | - Jing Wang
- Department of Electrical and Electronic Engineering, Faculty of Science and Engineering, University of Nottingham Ningbo China, Ningbo, China
- Nottingham Ningbo China Beacons of Excellence Research and Innovation Institute, Ningbo, China
| | - Chengbo Wang
- Department of Electrical and Electronic Engineering, Faculty of Science and Engineering, University of Nottingham Ningbo China, Ningbo, China
- Nottingham Ningbo China Beacons of Excellence Research and Innovation Institute, Ningbo, China
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Feng L. Live-view 4D GRASP MRI: A framework for robust real-time respiratory motion tracking with a sub-second imaging latency. Magn Reson Med 2023; 90:1053-1068. [PMID: 37203314 PMCID: PMC10330383 DOI: 10.1002/mrm.29700] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 04/21/2023] [Accepted: 04/21/2023] [Indexed: 05/20/2023]
Abstract
PURPOSE To propose a framework called live-view golden-angle radial sparse parallel (GRASP) MRI for low-latency and high-fidelity real-time volumetric MRI. METHODS Live-view GRASP MRI has two stages. The first one is called an off-view stage and the second one is called a live-view stage. In the off-view stage, 3D k-space data and 2D navigators are acquired alternatively using a new navi-stack-of-stars sampling scheme. A 4D motion database is then generated that contains time-resolved MR images at a sub-second temporal resolution, and each image is linked to a 2D navigator. In the live-view stage, only 2D navigators are acquired. At each time point, a live-view 2D navigator is matched to all the off-view 2D navigators. A 3D image that is linked to the best-matched off-view 2D navigator is then selected for this time point. This framework places the typical acquisition and reconstruction burden of MRI in the off-view stage, enabling low-latency real-time 3D imaging in the live-view stage. The accuracy of live-view GRASP MRI and the robustness of 2D navigators for characterizing respiratory variations and/or body movements were assessed. RESULTS Live-view GRASP MRI can efficiently generate real-time volumetric images that match well with the ground-truth references, with an imaging latency below 500 ms. Compared to 1D navigators, 2D navigators enable more reliable characterization of respiratory variations and/or body movements that may occur throughout the two imaging stages. CONCLUSION Live-view GRASP MRI represents a novel, accurate, and robust framework for real-time volumetric imaging, which can potentially be applied for motion adaptive radiotherapy on MRI-Linac.
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Affiliation(s)
- Li Feng
- Center for Advanced Imaging Innovation and Research (CAI2R), New York University Grossman School of Medicine, New York, New York, USA
- BioMedical Engineering and Imaging Institute (BMEII), Icahn School of Medicine at Mount Sinai, New York, New York, USA
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12
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Li Z, Huang C, Tong A, Chandarana H, Feng L. Kz-accelerated variable-density stack-of-stars MRI. Magn Reson Imaging 2023; 97:56-67. [PMID: 36577458 PMCID: PMC10072203 DOI: 10.1016/j.mri.2022.12.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 10/17/2022] [Accepted: 12/23/2022] [Indexed: 12/26/2022]
Abstract
This work aimed to develop a modified stack-of-stars golden-angle radial sampling scheme with variable-density acceleration along the slice (kz) dimension (referred to as VD-stack-of-stars) and to test this new sampling trajectory with multi-coil compressed sensing reconstruction for rapid motion-robust 3D liver MRI. VD-stack-of-stars sampling implements additional variable-density undersampling along the kz dimension, so that slice resolution (or volumetric coverage) can be increased without prolonging scan time. The new sampling trajectory (with increased slice resolution) was compared with standard stack-of-stars sampling with fully sampled kz (with standard slice resolution) in both non-contrast-enhanced free-breathing liver MRI and dynamic contrast-enhanced MRI (DCE-MRI) of the liver in volunteers. For both sampling trajectories, respiratory motion was extracted from the acquired radial data, and images were reconstructed using motion-compensated (respiratory-resolved or respiratory-weighted) dynamic radial compressed sensing reconstruction techniques. Qualitative image quality assessment (visual assessment by experienced radiologists) and quantitative analysis (as a metric of image sharpness) were performed to compare images acquired using the new and standard stack-of-stars sampling trajectories. Compared to standard stack-of-stars sampling, both non-contrast-enhanced and DCE liver MR images acquired with VD-stack-of-stars sampling presented improved overall image quality, sharper liver edges and increased hepatic vessel clarity in all image planes. The results have suggested that the proposed VD-stack-of-stars sampling scheme can achieve improved performance (increased slice resolution or volumetric coverage with better image quality) over standard stack-of-stars sampling in free-breathing DCE-MRI without increasing scan time. The reformatted coronal and sagittal images with better slice resolution may provide added clinical value.
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Affiliation(s)
- Zhitao Li
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Chenchan Huang
- Department of Radiology, New York University School of Medicine, New York, NY, USA
| | - Angela Tong
- Department of Radiology, New York University School of Medicine, New York, NY, USA
| | - Hersh Chandarana
- Department of Radiology, New York University School of Medicine, New York, NY, USA; Center for Advanced Imaging Innovation and Research (CAI(2)R), and Bernard and Irene Schwartz Center for Biomedical Imaging, New York University School of Medicine, New York, NY, USA
| | - Li Feng
- Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, USA.
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13
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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: 0.5] [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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14
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Fu Z, Johnson K, Altbach MI, Bilgin A. Cancellation of streak artifacts in radial abdominal imaging using interference null space projection. Magn Reson Med 2022; 88:1355-1369. [PMID: 35608238 PMCID: PMC9973517 DOI: 10.1002/mrm.29285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Revised: 03/03/2022] [Accepted: 04/13/2022] [Indexed: 11/06/2022]
Abstract
PURPOSE In radial abdominal imaging, it has been commonly observed that signal from the arms cause streaks due to system imperfections. We previously introduced a streak removal technique (B-STAR), which is inherently spatially variant and limited to work in image space. In this work, we propose a spatially invariant streak cancellation technique (CACTUS), which can be applied in either image space or k-space and is compatible with iterative reconstructions. THEORY AND METHODS Streak sources are typically spatially localized and can be represented using a low-dimensional subspace. CACTUS identifies the streak subspace by leveraging the spatial redundancy of receiver coils and projects the data onto the streak null space to eliminate the streaks. When applied in k-space, CACTUS can be combined with iterative reconstructions. CACTUS was tested in phantoms and in vivo abdominal imaging using a radial turbo spin-echo pulse sequence. RESULTS In phantoms, CACTUS improved T2 estimation in comparison to previous de-streaking methods. In vivo experiments showed that CACTUS reduced streaks and yielded T2 estimation, in regions affected by streaks, closer to a streak-free reference. Evaluation using a clinical abdominal dataset (n = 20) showed that CACTUS is comparable to B-STAR and yields significantly better signal preservation and streak cancellation than coil removal and suppression methods. CONCLUSION CACTUS provides superior signal preservation and streak reduction performance compared to coil removal and suppression methods. As a clear advantage over B-STAR, CACTUS can be integrated with iterative reconstruction methods. In abdominal T2 mapping, CACTUS improves the accuracy of parameter estimation in areas affected by streaks.
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Affiliation(s)
- Zhiyang Fu
- Department of Medical Imaging, The University of Arizona, Tucson, Arizona, USA
- Department of Electrical and Computer Engineering, The University of Arizona, Tucson, Arizona, USA
| | - Kevin Johnson
- Department of Medical Imaging, The University of Arizona, Tucson, Arizona, USA
| | - Maria I. Altbach
- Department of Medical Imaging, The University of Arizona, Tucson, Arizona, USA
- Department of Biomedical Engineering, The University of Arizona, Tucson, Arizona, USA
| | - Ali Bilgin
- Department of Medical Imaging, The University of Arizona, Tucson, Arizona, USA
- Department of Electrical and Computer Engineering, The University of Arizona, Tucson, Arizona, USA
- Department of Biomedical Engineering, The University of Arizona, Tucson, Arizona, USA
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15
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Li Z, Xu X, Yang Y, Feng L. Repeatability and robustness of MP-GRASP T 1 mapping. Magn Reson Med 2022; 87:2271-2286. [PMID: 34971467 PMCID: PMC10061203 DOI: 10.1002/mrm.29131] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Revised: 12/03/2021] [Accepted: 12/06/2021] [Indexed: 12/14/2022]
Abstract
PURPOSE To demonstrate the repeatability of fast 3D T1 mapping using Magnetization-Prepared Golden-angle RAdial Sparse Parallel (MP-GRASP) MRI and its robustness to variation of imaging parameters including flip angle and spatial resolution in phantoms and the brain. THEORY AND METHODS Multiple imaging experiments were performed to (1) assess the robustness of MP-GRASP T1 mapping to B1 inhomogeneity using a single tube phantom filled with uniform MnCl2 liquid; (2) compare the repeatability of T1 mapping between MP-GRASP and inversion recovery-based spin-echo (IR-SE; over 12 scans), using a commercial T1MES phantom; (3) evaluate the longitudinal variation of T1 estimation using MP-GRASP with varying imaging parameters, including spatial resolution, flip angle, TR/TE, and acceleration rate, using the T1MES phantom (106 scans performed over a period of 12 months); and (4) evaluate the variation of T1 estimation using MP-GRASP with varying imaging parameters in the brain (24 scans in a single visit). In addition, the accuracy of MP-GRASP T1 mapping was also validated against IR-SE by performing linear correlation and calculating the Lin's concordance correlation coefficient (CCC). RESULTS MP-GRASP demonstrates good robustness to B1 inhomogeneity, with intra-slice variability below 1% in the single tube phantom experiment. The longitudinal variability is good both in the phantom (below 2.5%) and in the brain (below 2%) with varying imaging parameters. The T1 values estimated from MP-GRASP are accurate compared to that from the IR-SE imaging (R2 = 0.997, Lin's CCC = 0.996). CONCLUSION MP-GRASP shows excellent repeatability of T1 estimation over time, and it is also robust to variation of different imaging parameters evaluated in this study.
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Affiliation(s)
- Zhitao Li
- Department of Radiology, Stanford University, Palo Alto, California, United States
| | - Xiang Xu
- Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Yang Yang
- Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Li Feng
- Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
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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: 66] [Impact Index Per Article: 22.0] [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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17
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Ding Z, Cheng Z, She H, Liu B, Yin Y, Du YP. Dynamic pulmonary MRI using motion-state weighted motion-compensation (MostMoCo) reconstruction with ultrashort TE: A structural and functional study. Magn Reson Med 2022; 88:224-238. [PMID: 35388914 DOI: 10.1002/mrm.29204] [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: 09/27/2021] [Revised: 12/24/2021] [Accepted: 02/01/2022] [Indexed: 11/11/2022]
Abstract
PURPOSE To improve the quality of structural images and the quantification of ventilation in free-breathing dynamic pulmonary MRI. METHODS A 3D radial ultrashort TE (UTE) sequence with superior-inferior navigators was used to acquire pulmonary data during free breathing. All acquired data were binned into different motion states according to the respiratory signal extracted from superior-inferior navigators. Motion-resolved images were reconstructed using eXtra-Dimensional (XD) UTE reconstruction. The initial motion fields were generated by registering images at each motion state to other motion states in motion-resolved images. A motion-state weighted motion-compensation (MostMoCo) reconstruction algorithm was proposed to reconstruct the dynamic UTE images. This technique, termed as MostMoCo-UTE, was compared with XD-UTE and iterative motion-compensation (iMoCo) on a porcine lung and 10 subjects. RESULTS MostMoCo reconstruction provides higher peak SNR (37.0 vs. 35.4 and 34.2) and structural similarity (0.964 vs. 0.931 and 0.947) compared to XD-UTE and iMoCo in the porcine lung experiment. Higher apparent SNR and contrast-to-noise ratio are achieved using MostMoCo in the human experiment. MostMoCo reconstruction better preserves the temporal variations of signal intensity of parenchyma compared to iMoCo, shows reduced random noise and improved sharpness of anatomical structures compared to XD-UTE. In the porcine lung experiment, the quantification of ventilation using MostMoCo images is more accurate than that using XD-UTE and iMoCo images. CONCLUSION The proposed MostMoCo-UTE provides improved quality of structural images and quantification of ventilation for free-breathing pulmonary MRI. It has the potential for the detection of structural and functional disorders of the lung in clinical settings.
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Affiliation(s)
- Zekang Ding
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.,Central Research Institute, United Imaging Healthcare, Shanghai, China
| | - Zenghui Cheng
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai, China
| | - Huajun She
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Bei Liu
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Yongfang Yin
- Department of Radiology, People's Hospital of Jilin Province, Changchun, China
| | - Yiping P Du
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
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Breit HC, Block TK, Winkel DJ, Gehweiler JE, Glessgen CG, Seifert H, Wetterauer C, Boll DT, Heye TJ. Revisiting DCE-MRI: Classification of Prostate Tissue Using Descriptive Signal Enhancement Features Derived From DCE-MRI Acquisition With High Spatiotemporal Resolution. Invest Radiol 2021; 56:553-562. [PMID: 33660631 PMCID: PMC8373655 DOI: 10.1097/rli.0000000000000772] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
METHODS A retrospective study (from January 2016 to July 2019) including 75 subjects (mean, 65 years; 46-80 years) with 2.5-second temporal resolution DCE-MRI and PIRADS 4 or 5 lesions was performed. Fifty-four subjects had biopsy-proven prostate cancer (Gleason 6, 15; Gleason 7, 20; Gleason 8, 13; Gleason 9, 6), whereas 21 subjects had negative MRI/ultrasound fusion-guided biopsies. Voxel-wise analysis of contrast signal enhancement was performed for all time points using custom-developed software, including automatic arterial input function detection. Seven descriptive parameter maps were calculated: normalized maximum signal intensity, time to start, time to maximum, time-to-maximum slope, and maximum slope with normalization on maximum signal and the arterial input function (SMN1, SMN2). The parameters were compared with ADC using multiparametric machine-learning models to determine classification accuracy. A Wilcoxon test was used for the hypothesis test and the Spearman coefficient for correlation. RESULTS There were significant differences (P < 0.05) for all 7 DCE-derived parameters between the normal peripheral zone versus PIRADS 4 or 5 lesions and the biopsy-positive versus biopsy-negative lesions. Multiparametric analysis showed better performance when combining ADC + DCE as input (accuracy/sensitivity/specificity, 97%/93%/100%) relative to ADC alone (accuracy/sensitivity/specificity, 94%/95%/95%) and to DCE alone (accuracy/sensitivity/specificity, 78%/79%/77%) in differentiating the normal peripheral zone from PIRADS lesions, biopsy-positive versus biopsy-negative lesions (accuracy/sensitivity/specificity, 68%/33%/81%), and Gleason 6 versus ≥7 prostate cancer (accuracy/sensitivity/specificity, 69%/60%/72%). CONCLUSIONS Descriptive perfusion characteristics derived from high-resolution DCE-MRI using model-free computations show significant differences between normal and cancerous tissue but do not reach the accuracy achieved with solely ADC-based classification. Combining ADC with DCE-based input features improved classification accuracy for PIRADS lesions, discrimination of biopsy-positive versus biopsy-negative lesions, and differentiation between Gleason 6 versus Gleason ≥7 lesions.
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Affiliation(s)
- Hanns C. Breit
- Department of Radiology, University Hospital Basel, Basel, Switzerland
| | | | - David J. Winkel
- Department of Radiology, University Hospital Basel, Basel, Switzerland
| | | | - Carl G. Glessgen
- Department of Radiology, University Hospital Basel, Basel, Switzerland
| | - Helge Seifert
- Department of Radiology, University Hospital Basel, Basel, Switzerland
| | | | - Daniel T. Boll
- Department of Radiology, University Hospital Basel, Basel, Switzerland
| | - Tobias J. Heye
- Department of Radiology, University Hospital Basel, Basel, Switzerland
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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: 32] [Impact Index Per Article: 8.0] [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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20
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Harder FN, Budjan J, Nickel MD, Grimm R, Pietsch H, Schoenberg SO, Jost G, Attenberger UI. Intraindividual Comparison of Compressed Sensing-Accelerated Cartesian and Radial Arterial Phase Imaging of the Liver in an Experimental Tumor Model. Invest Radiol 2021; 56:433-441. [PMID: 33813577 DOI: 10.1097/rli.0000000000000767] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
OBJECTIVES The aim of this study was to intraindividually compare the performance of 2 compressed sensing (CS)-accelerated magnetic resonance imaging (MRI) sequences, 1 featuring Cartesian (compressed sensing volumetric interpolated breath-hold examination [CS-VIBE]) and the other radial (golden-angle radial sparse parallel [GRASP]) k-space sampling in continuous dynamic imaging during hepatic vascular phases, using extracellular and hepatocyte-specific contrast agents. MATERIALS AND METHODS Seven New Zealand white rabbits, with induced VX2 liver tumors (median number of lesions, 2 ± 0.83; range, 1-3), received 2 continuously acquired T1-weighted prototype CS-accelerated MRI sequences (CS-VIBE and GRASP) with high spatial (0.8 × 0.8 × 1.5 mm) and temporal resolution (3.5 seconds) in randomized order on 2 separate days using a 1.5-T scanner. In all animals, imaging was performed using first gadobutrol at a dose of 0.1 mmol/kg and, then 45 minutes later, gadoxetic acid at a dose of 0.025 mmol/kg.The following qualitative parameters were assessed using 3- and 5-point Likert scales (3 and 5 being the highest scores respectively): image quality (IQ), arterial and venous vessel delineation, tumor enhancement, motion artifacts, and sequence-specific artifacts. Furthermore, the following quantitative parameters were obtained: relative peak signal enhancement, time to peak, mean transit time, and plasma flow ratios. Paired sampled t tests and Wilcoxon signed rank tests were used for intraindividual comparison. Image analysis was performed by 2 radiologists. RESULTS Six of 7 animals underwent the full imaging protocol and obtained data were analyzed statistically. Overall IQ was rated moderate to excellent, not differing significantly between the 2 sequences.Gadobutrol-enhanced CS-VIBE examinations revealed the highest mean Likert scale values in terms of vessel delineation and tumor enhancement (arterial 4.4 [4-5], venous 4.3 [3-5], and tumor 2.9 [2-3]). Significantly, more sequence-specific artifacts were seen in GRASP examinations (P = 0.008-0.031). However, these artifacts did not impair IQ. Excellent Likert scale ratings were found for motion artifacts in both sequences. In both sequences, a maximum of 4 hepatic arterial dominant phases were obtained. Regarding the relative peak signal enhancement, CS-VIBE and GRASP showed similar results. The relative peak signal enhancement values did not differ significantly between the 2 sequences in the aorta, the hepatic artery, or the inferior vena cava (P = 0.063-0.536). However, significantly higher values were noted for CS-VIBE in gadoxetic acid-enhanced examinations in the portal vein (P = 0.031) and regarding the tumor enhancement (P = 0.005). Time to peak and mean transit time or plasma flow ratios did not differ significantly between the sequences. CONCLUSIONS Both CS-VIBE and GRASP provide excellent results in dynamic liver MRI using extracellular and hepatocyte-specific contrast agents, in terms of IQ, peak signal intensity, and presence of artifacts.
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Affiliation(s)
- Felix N Harder
- From the Department of Diagnostic and Interventional Radiology, School of Medicine, Technical University of Munich, Munich
| | | | | | | | | | - Stefan O Schoenberg
- Department of Clinical Radiology and Nuclear Medicine, University Medical Center Mannheim, Medical Faculty Mannheim-Heidelberg University, Mannheim
| | - Gregor Jost
- MR and CT Contrast Media Research, Bayer AG, Berlin
| | - Ulrike I Attenberger
- Department of Diagnostic and Interventional Radiology, University of Bonn, Bonn, Germany
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21
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Freedman JN, Gurney-Champion OJ, Nill S, Shiarli AM, Bainbridge HE, Mandeville HC, Koh DM, McDonald F, Kachelrieß M, Oelfke U, Wetscherek A. Rapid 4D-MRI reconstruction using a deep radial convolutional neural network: Dracula. Radiother Oncol 2021; 159:209-217. [PMID: 33812914 PMCID: PMC8216429 DOI: 10.1016/j.radonc.2021.03.034] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 03/07/2021] [Accepted: 03/26/2021] [Indexed: 11/16/2022]
Abstract
BACKGROUND AND PURPOSE 4D and midposition MRI could inform plan adaptation in lung and abdominal MR-guided radiotherapy. We present deep learning-based solutions to overcome long 4D-MRI reconstruction times while maintaining high image quality and short scan times. METHODS Two 3D U-net deep convolutional neural networks were trained to accelerate the 4D joint MoCo-HDTV reconstruction. For the first network, gridded and joint MoCo-HDTV-reconstructed 4D-MRI were used as input and target data, respectively, whereas the second network was trained to directly calculate the midposition image. For both networks, input and target data had dimensions of 256 × 256 voxels (2D) and 16 respiratory phases. Deep learning-based MRI were verified against joint MoCo-HDTV-reconstructed MRI using the structural similarity index (SSIM) and the naturalness image quality evaluator (NIQE). Moreover, two experienced observers contoured the gross tumour volume and scored the images in a blinded study. RESULTS For 12 subjects, previously unseen by the networks, high-quality 4D and midposition MRI (1.25 × 1.25 × 3.3 mm3) were each reconstructed from gridded images in only 28 seconds per subject. Excellent agreement was found between deep-learning-based and joint MoCo-HDTV-reconstructed MRI (average SSIM ≥ 0.96, NIQE scores 7.94 and 5.66). Deep-learning-based 4D-MRI were clinically acceptable for target and organ-at-risk delineation. Tumour positions agreed within 0.7 mm on midposition images. CONCLUSION Our results suggest that the joint MoCo-HDTV and midposition algorithms can each be approximated by a deep convolutional neural network. This rapid reconstruction of 4D and midposition MRI facilitates online treatment adaptation in thoracic or abdominal MR-guided radiotherapy.
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Affiliation(s)
- Joshua N Freedman
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom.
| | - Oliver J Gurney-Champion
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom; Department of Radiology and Nuclear Medicine, Cancer Center Amsterdam, Amsterdam UMC, University of Amsterdam, The Netherlands.
| | - Simeon Nill
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom.
| | - Anna-Maria Shiarli
- Department of Radiotherapy, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom.
| | - Hannah E Bainbridge
- Department of Radiotherapy, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom; Department of Radiotherapy, Portsmouth Hospitals University NHS Trust, Queen Alexandra Hospital, United Kingdom.
| | - Henry C Mandeville
- Department of Radiotherapy, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom.
| | - Dow-Mu Koh
- Department of Radiology, The Royal Marsden NHS Foundation Trust, London, United Kingdom.
| | - Fiona McDonald
- Department of Radiotherapy, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom.
| | - Marc Kachelrieß
- Division of X-Ray Imaging and CT, German Cancer Research Center (DKFZ), Heidelberg, Germany.
| | - Uwe Oelfke
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom.
| | - Andreas Wetscherek
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom.
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22
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Tian Y, Lim Y, Zhao Z, Byrd D, Narayanan S, Nayak KS. Aliasing artifact reduction in spiral real-time MRI. Magn Reson Med 2021; 86:916-925. [PMID: 33728700 DOI: 10.1002/mrm.28746] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Revised: 01/09/2021] [Accepted: 02/02/2021] [Indexed: 12/17/2022]
Abstract
PURPOSE To mitigate a common artifact in spiral real-time MRI, caused by aliasing of signal outside the desired FOV. This artifact frequently occurs in midsagittal speech real-time MRI. METHODS Simulations were performed to determine the likely origin of the artifact. Two methods to mitigate the artifact are proposed. The first approach, denoted as "large FOV" (LF), keeps an FOV that is large enough to include the artifact signal source during reconstruction. The second approach, denoted as "estimation-subtraction" (ES), estimates the artifact signal source before subtracting a synthetic signal representing that source in multicoil k-space raw data. Twenty-five midsagittal speech-production real-time MRI data sets were used to evaluate both of the proposed methods. Reconstructions without and with corrections were evaluated by two expert readers using a 5-level Likert scale assessing artifact severity. Reconstruction time was also compared. RESULTS The origin of the artifact was found to be a combination of gradient nonlinearity and imperfect anti-aliasing in spiral sampling. The LF and ES methods were both able to substantially reduce the artifact, with an averaged qualitative score improvement of 1.25 and 1.35 Likert levels for LF correction and ES correction, respectively. Average reconstruction time without correction, with LF correction, and with ES correction were 160.69 ± 1.56, 526.43 ± 5.17, and 171.47 ± 1.71 ms/frame. CONCLUSION Both proposed methods were able to reduce the spiral aliasing artifacts, with the ES-reduction method being more effective and more time efficient.
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Affiliation(s)
- Ye Tian
- Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, California, USA
| | - Yongwan Lim
- Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, California, USA
| | - Ziwei Zhao
- Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, California, USA
| | - Dani Byrd
- Department of Linguistics, Dornsife College of Letters, Arts and Sciences, University of Southern California, Los Angeles, California, USA
| | - Shrikanth Narayanan
- Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, California, USA.,Department of Linguistics, Dornsife College of Letters, Arts and Sciences, University of Southern California, Los Angeles, California, USA
| | - Krishna S Nayak
- Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, California, USA
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23
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Solomon E, Rigie DS, Vahle T, Paška J, Bollenbeck J, Sodickson DK, Boada FE, Block KT, Chandarana H. Free-breathing radial imaging using a pilot-tone radiofrequency transmitter for detection of respiratory motion. Magn Reson Med 2020; 85:2672-2685. [PMID: 33306216 DOI: 10.1002/mrm.28616] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Revised: 10/14/2020] [Accepted: 11/05/2020] [Indexed: 12/21/2022]
Abstract
PURPOSE To describe an approach for detection of respiratory signals using a transmitted radiofrequency (RF) reference signal called Pilot-Tone (PT) and to use the PT signal for creation of motion-resolved images based on 3D stack-of-stars imaging under free-breathing conditions. METHODS This work explores the use of a reference RF signal generated by a small RF transmitter, placed outside the MR bore. The reference signal is received in parallel to the MR signal during each readout. Because the received PT amplitude is modulated by the subject's breathing pattern, a respiratory signal can be obtained by detecting the strength of the received PT signal over time. The breathing-induced PT signal modulation can then be used for reconstructing motion-resolved images from free-breathing scans. The PT approach was tested in volunteers using a radial stack-of-stars 3D gradient echo (GRE) sequence with golden-angle acquisition. RESULTS Respiratory signals derived from the proposed PT method were compared to signals from a respiratory cushion sensor and k-space-center-based self-navigation under different breathing conditions. Moreover, the accuracy was assessed using a modified acquisition scheme replacing the golden-angle scheme by a zero-angle acquisition. Incorporating the PT signal into eXtra-Dimensional (XD) motion-resolved reconstruction led to improved image quality and clearer anatomical depiction of the lung and liver compared to k-space-center signal and motion-averaged reconstruction, when binned into 6, 8, and 10 motion states. CONCLUSION PT is a novel concept for tracking respiratory motion. Its small dimension (8 cm), high sampling rate, and minimal interaction with the imaging scan offers great potential for resolving respiratory motion.
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Affiliation(s)
- Eddy Solomon
- Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
| | - David S Rigie
- Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
| | | | - Jan Paška
- Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
| | | | - Daniel K Sodickson
- Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
| | - Fernando E Boada
- Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
| | - Kai Tobias Block
- Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA.,Siemens Healthcare GmbH, Erlangen, Germany
| | - Hersh Chandarana
- Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA
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24
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Kennedy P, Bane O, Hectors SJ, Fischman A, Schiano T, Lewis S, Taouli B. Noninvasive imaging assessment of portal hypertension. Abdom Radiol (NY) 2020; 45:3473-3495. [PMID: 32926209 PMCID: PMC10124623 DOI: 10.1007/s00261-020-02729-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Revised: 08/16/2020] [Accepted: 08/30/2020] [Indexed: 02/07/2023]
Abstract
Portal hypertension (PH) is a spectrum of complications of chronic liver disease (CLD) and cirrhosis, with manifestations including ascites, gastroesophageal varices, splenomegaly, hypersplenism, hepatic hydrothorax, hepatorenal syndrome, hepatopulmonary syndrome and portopulmonary hypertension. PH can vary in severity and is diagnosed via invasive hepatic venous pressure gradient measurement (HVPG), which is considered the reference standard. Accurate diagnosis of PH and assessment of severity are highly relevant as patients with clinically significant portal hypertension (CSPH) are at higher risk for developing acute variceal bleeding and mortality. In this review, we discuss current and upcoming noninvasive imaging methods for diagnosis and assessment of severity of PH.
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25
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Buzan MT, Wetscherek A, Rank CM, Kreuter M, Heussel CP, Kachelrieß M, Dinkel J. Delayed contrast dynamics as marker of regional impairment in pulmonary fibrosis using 5D MRI - a pilot study. Br J Radiol 2020; 93:20190121. [PMID: 32584606 DOI: 10.1259/bjr.20190121] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
OBJECTIVE To analyse delayed contrast dynamics of fibrotic lesions in interstitial lung disease (ILD) using five dimensional (5D) MRI and to correlate contrast dynamics with disease severity. METHODS 20 patients (mean age: 71 years; M:F, 13:7), with chronic fibrosing ILD: n = 12 idiopathic pulmonary fibrosis (IPF) and n = 8 non-IPF, underwent thin-section multislice CT as part of the standard diagnostic workup and additionally MRI of the lung. 2 min after contrast injection, a radial gradient echo sequence with golden-angle spacing was acquired during 5 min of free-breathing, followed by 5D image reconstruction. Disease was categorized as severe or non-severe according to CT morphological regional severity. For each patient, 10 lesions were analysed. RESULTS IPF lesions showed later peak enhancement compared to non-IPF (severe: p = 0.01, non-severe: p = 0.003). Severe lesions showed later peak enhancement compared to non-severe lesions, in non-IPF (p = 0.04), but not in IPF (p = 0.35). There was a tendency towards higher accumulation and washout rates in IPF compared to non-IPF in non-severe disease. Severe lesions had lower washout rate than non-severe ones in both IPF (p = 0.003) and non-IPF (p = 0.005). Continuous contrast agent accumulation, without washout, was found only in IPF lesions. CONCLUSIONS Contrast agent dynamics are influenced by type and severity of pulmonary fibrosis, which might enable a more thorough characterisation of disease burden. The regional impairment is of particular interest in the context of antifibrotic treatments and was characterised using a non-invasive, non-irradiating, free-breathing method. ADVANCES IN KNOWLEDGE Delayed contrast enhancement patterns allow the assessment of regional lung impairment which could represent different disease stages or phenotypes in ILD.
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Affiliation(s)
- Maria Ta Buzan
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at Heidelberg University Hospital, Heidelberg, Germany.,Department of Pneumology, Iuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca, Romania.,Translational Lung Research Center Heidelberg (TLRC), Member of the German Center for Lung Research (DZL), Heidelberg, Germany.,Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - Andreas Wetscherek
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Joint Department of Physics at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Christopher M Rank
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Michael Kreuter
- Translational Lung Research Center Heidelberg (TLRC), Member of the German Center for Lung Research (DZL), Heidelberg, Germany.,Center for Rare and Interstitial Lung Diseases, Pneumology and respiratory critical care medicine, Thoraxklinik, Heidelberg University Hospital, Heidelberg, Germany
| | - Claus Peter Heussel
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at Heidelberg University Hospital, Heidelberg, Germany.,Translational Lung Research Center Heidelberg (TLRC), Member of the German Center for Lung Research (DZL), Heidelberg, Germany.,Center for Rare and Interstitial Lung Diseases, Pneumology and respiratory critical care medicine, Thoraxklinik, Heidelberg University Hospital, Heidelberg, Germany
| | - Marc Kachelrieß
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Julien Dinkel
- Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at Heidelberg University Hospital, Heidelberg, Germany.,Institute for Clinical Radiology, Ludwig-Maximilians-University Hospital Munich, Munich, Germany.,Comprehensive Pneumology Center Munich (CPC-M), Member of the German Center for Lung Research (DZL), Munich, Germany
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26
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Demerath T, Blackham K, Anastasopoulos C, Block K, Stieltjes B, Schubert T. Golden-Angle Radial Sparse Parallel (GRASP) MRI differentiates head & neck paragangliomas from schwannomas. Magn Reson Imaging 2020; 70:73-80. [DOI: 10.1016/j.mri.2020.04.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2020] [Revised: 03/30/2020] [Accepted: 04/10/2020] [Indexed: 11/24/2022]
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Feng L, Tyagi N, Otazo R. MRSIGMA: Magnetic Resonance SIGnature MAtching for real-time volumetric imaging. Magn Reson Med 2020; 84:1280-1292. [PMID: 32086858 DOI: 10.1002/mrm.28200] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2019] [Revised: 12/13/2019] [Accepted: 01/16/2020] [Indexed: 12/25/2022]
Abstract
PURPOSE To propose a real-time 3D MRI technique called MR SIGnature MAtching (MRSIGMA) for high-resolution volumetric imaging and motion tracking with very low imaging latency. METHODS MRSIGMA consists of two steps: (1) offline learning of a database of possible 3D motion states and corresponding motion signature ranges and (2) online matching of new motion signatures acquired in real time with prelearned motion states. Specifically, the offline learning step (non-real-time) reconstructs motion-resolved 4D images representing different motion states and assigns a unique motion range to each state. The online matching step (real-time) acquires motion signatures only and selects one of the prelearned 3D motion states for each newly acquired signature, which generates 3D images efficiently in real time. The MRSIGMA technique was evaluated on 15 golden-angle stack-of-stars liver data sets, and the performance of respiratory motion tracking with the online-generated real-time 3D MRI was compared with the corresponding 2D projections acquired in real time. RESULTS The total latency of generating each 3D image during online matching was about 300 ms, including acquisition of the motion signature data (~138 ms) and corresponding matching process (~150 ms). Linear correlation assessment suggested excellent correlation (R2 = 0.948) between motion displacement measured from the online-generated real-time 3D images and the 2D real-time projections. CONCLUSION This proof-of-concept study demonstrates the feasibility of MRSIGMA for high-resolution real-time volumetric imaging, which shifts the acquisition and reconstruction burden to an offline learning step and leaves fast online matching for online imaging with very low imaging latency. The MRSIGMA technique can potentially be used for real-time motion tracking in MRI-guided radiation therapy.
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Affiliation(s)
- Li Feng
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.,Biomedical Engineering and Imaging Institute, Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Neelam Tyagi
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Ricardo Otazo
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.,Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
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28
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Chen L, Zeng X, Ji B, Liu D, Wang J, Zhang J, Feng L. Improving dynamic contrast-enhanced MRI of the lung using motion-weighted sparse reconstruction: Initial experiences in patients. Magn Reson Imaging 2020; 68:36-44. [PMID: 32001328 DOI: 10.1016/j.mri.2020.01.013] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2019] [Revised: 01/17/2020] [Accepted: 01/26/2020] [Indexed: 12/14/2022]
Abstract
PURPOSE The purpose of this study was to evaluate the performance of motion-weighted Golden-angle RAdial Sparse Parallel MRI (motion-weighted GRASP) for free-breathing dynamic contrast-enhanced MRI (DCE-MRI) of the lung. METHODS Motion-weighted GRASP incorporates a soft-gating motion compensation algorithm into standard GRASP reconstruction, so that motion-corrupted motion k-space (e.g., k-space acquired in inspiratory phases) contributes less to the final reconstructed images. Lung MR data from 20 patients (mean age = 57.9 ± 13.5) with known pulmonary lesions were retrospectively collected for this study. Each subject underwent a free-breathing DCE-MR scan using a fat-statured T1-weighted stack-of-stars golden-angle radial sequence and a post-contrast breath-hold MR scan using a Cartesian volumetric-interpolated imaging sequence (BH-VIBE). Each radial dataset was reconstructed using GRASP without motion compensation and motion-weighted GRASP. All MR images were visually evaluated by two experienced radiologists blinded to reconstruction and acquisition schemes independently. In addition, the influence of motion-weighted reconstruction on dynamic contrast-enhancement patterns was also investigated. RESULTS For image quality assessment, motion-weighted GRASP received significantly higher visual scores than GRASP (P < 0.05) for overall image quality (3.68 vs. 3.39), lesion conspicuity (3.54 vs. 3.18) and overall artifact level (3.53 vs. 3.15). There was no significant difference (P > 0.05) between the breath-hold BH-VIBE and motion-weighted GRASP images. For assessment of temporal fidelity, motion-weighted GRASP maintained a good agreement with respect to GRASP. CONCLUSION Motion-weighted GRASP achieved better reconstruction performance in free-breathing DCE-MRI of the lung compared to standard GRASP, and it may enable improved assessment of pulmonary lesions.
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Affiliation(s)
- Lihua Chen
- Department of Radiology, PLA 904 Hospital, Wuxi, Jiangsu, China
| | - Xianchun Zeng
- Department of Radiology, Guizhou Provincial People's Hospital, Guizhou, China
| | - Bing Ji
- Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Daihong Liu
- Department of Radiology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, China; Key Laboratory for Biorheological Science and Technology of Ministry of Education (Chongqing University), Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, China
| | - Jian Wang
- Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China.
| | - Jiuquan Zhang
- Department of Radiology, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, China; Key Laboratory for Biorheological Science and Technology of Ministry of Education (Chongqing University), Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, China.
| | - Li Feng
- Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, USA
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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: 62] [Impact Index Per Article: 10.3] [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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30
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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: 41] [Impact Index Per Article: 6.8] [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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Mandava S, Keerthivasan MB, Martin DR, Altbach MI, Bilgin A. Radial streak artifact reduction using phased array beamforming. Magn Reson Med 2019; 81:3915-3923. [PMID: 30756432 PMCID: PMC10188278 DOI: 10.1002/mrm.27689] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2018] [Revised: 01/21/2019] [Accepted: 01/22/2019] [Indexed: 11/07/2022]
Abstract
PURPOSE A new method for streak artifact reduction in radial MRI based on phased array filtering. THEORY Radial imaging in applications that require large fields-of-view can be susceptible to streaking artifacts due to gradient nonlinearities. Coil removal methods prune the coils contributing the most to streaking artifacts at the expense of signal loss. Phased array beamforming is a form of spatial filtering used to suppress unwanted signals. The proposed method uses interference covariance generated from the streaking artifact samples which are manually extracted with phased array beamforming to suppress streaking in the images. METHODS The performance of the proposed method was evaluated on abdomen radial fast spin echo images acquired on a 1.5T Siemens scanner and compared with previously proposed methods. RESULTS Our results demonstrate that the proposed method can effectively suppress streaking artifacts without any noticeable loss in signal levels. Coil removal methods can suppress streaks as well but they may incur significant signal loss due to coil pruning. Quantitative metrics also demonstrate the superiority of the proposed method over earlier methods. CONCLUSION The use of interference covariance with phased array beamforming can help reduce streaking artifacts.
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Affiliation(s)
- Sagar Mandava
- Department of Electrical and Computer Engineering, University of Arizona, Tucson, Arizona.,Department of Medical Imaging, University of Arizona, Tucson, Arizona
| | - Mahesh B Keerthivasan
- Department of Electrical and Computer Engineering, University of Arizona, Tucson, Arizona.,Department of Medical Imaging, University of Arizona, Tucson, Arizona
| | - Diego R Martin
- Department of Medical Imaging, University of Arizona, Tucson, Arizona
| | - Maria I Altbach
- Department of Medical Imaging, University of Arizona, Tucson, Arizona.,Department of Biomedical Engineering, University of Arizona, Tucson, Arizona
| | - Ali Bilgin
- Department of Electrical and Computer Engineering, University of Arizona, Tucson, Arizona.,Department of Medical Imaging, University of Arizona, Tucson, Arizona.,Department of Biomedical Engineering, University of Arizona, Tucson, Arizona
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Zhou R, Yang Y, Mathew RC, Mugler JP, Weller DS, Kramer CM, Ahmed AH, Jacob M, Salerno M. Free-breathing cine imaging with motion-corrected reconstruction at 3T using SPiral Acquisition with Respiratory correction and Cardiac Self-gating (SPARCS). Magn Reson Med 2019; 82:706-720. [PMID: 31006916 DOI: 10.1002/mrm.27763] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2018] [Revised: 03/12/2019] [Accepted: 03/15/2019] [Indexed: 12/28/2022]
Abstract
PURPOSE To develop a continuous-acquisition cardiac self-gated spiral pulse sequence and a respiratory motion-compensated reconstruction strategy for free-breathing cine imaging. METHODS Cine data were acquired continuously on a 3T scanner for 8 seconds per slice without ECG gating or breath-holding, using a golden-angle gradient echo spiral pulse sequence. Cardiac motion information was extracted by applying principal component analysis on the gridded 8 × 8 k-space center data. Respiratory motion was corrected by rigid registration on each heartbeat. Images were reconstructed using a low-rank and sparse (L+S) technique. This strategy was evaluated in 37 healthy subjects and 8 subjects undergoing clinical cardiac MR studies. Image quality was scored (1-5 scale) in a blinded fashion by 2 experienced cardiologists. In 13 subjects with whole-heart coverage, left ventricular ejection fraction (LVEF) from SPiral Acquisition with Respiratory correction and Cardiac Self-gating (SPARCS) was compared to that from a standard ECG-gated breath-hold balanced steady-state free precession (bSSFP) cine sequence. RESULTS The self-gated signal was successfully extracted in all cases and demonstrated close agreement with the acquired ECG signal (mean bias, -0.22 ms). The mean image score across all subjects was 4.0 for reconstruction using the L+S model. There was good agreement between the LVEF derived from SPARCS and the gold-standard bSSFP technique. CONCLUSION SPARCS successfully images cardiac function without the need for ECG gating or breath-holding. With an 8-second data acquisition per slice, whole-heart cine images with clinically acceptable spatial and temporal resolution and image quality can be acquired in <90 seconds of free-breathing acquisition.
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Affiliation(s)
- Ruixi Zhou
- Department of Biomedical Engineering, University of Virginia Health System, Charlottesville, Virginia
| | - Yang Yang
- Department of Medicine, Cardiovascular Division, University of Virginia Health System, Charlottesville, Virginia.,Translational and Molecular Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Roshin C Mathew
- Department of Medicine, Cardiovascular Division, University of Virginia Health System, Charlottesville, Virginia.,Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, Virginia
| | - John P Mugler
- Department of Biomedical Engineering, University of Virginia Health System, Charlottesville, Virginia.,Department of Medicine, Cardiovascular Division, University of Virginia Health System, Charlottesville, Virginia.,Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, Virginia
| | - Daniel S Weller
- Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, Virginia
| | - Christopher M Kramer
- Department of Medicine, Cardiovascular Division, University of Virginia Health System, Charlottesville, Virginia.,Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, Virginia
| | - Abdul Haseeb Ahmed
- Department of Electrical and Computer Engineering, University of Iowa, Iowa City, Iowa
| | - Mathews Jacob
- Department of Electrical and Computer Engineering, University of Iowa, Iowa City, Iowa
| | - Michael Salerno
- Department of Biomedical Engineering, University of Virginia Health System, Charlottesville, Virginia.,Department of Medicine, Cardiovascular Division, University of Virginia Health System, Charlottesville, Virginia.,Radiology and Medical Imaging, University of Virginia Health System, Charlottesville, Virginia
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Chitiboi T, Muckley M, Dane B, Huang C, Feng L, Chandarana H. Pancreas deformation in the presence of tumors using feature tracking from free-breathing XD-GRASP MRI. J Magn Reson Imaging 2019; 50:1633-1640. [PMID: 30854767 DOI: 10.1002/jmri.26714] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2018] [Revised: 02/24/2019] [Accepted: 02/25/2019] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND Quantifying the biomechanical properties of pancreatic tumors could potentially help with assessment of tumor aggressiveness, prognosis, and prediction of therapy response. PURPOSE To quantify respiratory-induced deformation in the pancreas and pancreatic lesions using XD-GRASP (eXtra-Dimensional Golden-angle RAdial Sparse Parallel), MRI. STUDY TYPE Retrospective study where patients undergoing clinically indicated abdominal MRI which included free-breathing radial T1 -weighted (T1 W) imaging were studied. SUBJECTS Thirty-two patients (12 male and 20 female) including nine with pancreatic lesions constituted our study cohort. FIELD STRENGTH/SEQUENCE 3.0 T with T1 WI contrast-enhanced gradient echo radial free-breathing acquisition. ASSESSMENT Using the XD-GRASP imaging technique, the acquired free-breathing radial data were sorted and binned into 10 consecutive respiratory motion states that were jointly reconstructed. 3D deformation fields along the respiratory dimension were computed using an optical flow method and were analyzed in the pancreas. STATISTICAL TESTS The Wilcoxon signed-rank test was used to assess the difference in average displacement across pancreatic regions, while the Wilcoxon rank-sum test was used for displacement differences between patients with and without tumors. The interclass correlation coefficient (ICC) was computed to assess consistency between observers for each image quality measure. RESULTS There was a significantly larger displacement in the pancreatic tail compared with the head (8.2 ± 3.7 mm > 5.8 ± 2.4 mm; P < 0.001) and body regions (8.2 ± 3.7 mm > 6.6 ± 2.9 mm; P < 0.001). Furthermore, there was reduced normalized average displacement in patients with pancreatic lesions compared with subjects without lesions (0.33 ± 0.1 < 0.69 ± 0.26, P < 0.001 for the head; 0.30 ± 0.1 < 0.84 ± 0.31, P < 0.001 for the body; and 0.44 ± 0.31 < 1.08 ± 0.53, P < 0.001 for the tail, respectively). DATA CONCLUSION Free-breathing respiratory motion-sorted XD-GRASP MRI has the potential to noninvasively characterize the biomechanical properties of the pancreas by quantifying breathing-induced mechanical displacement. LEVEL OF EVIDENCE 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:1633-1640.
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Affiliation(s)
- Teodora Chitiboi
- 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.,Siemens Healthineers, Princeton, New Jersey, USA
| | - Matthew Muckley
- 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
| | - Bari Dane
- 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
| | - Li Feng
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, 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
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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: 2.2] [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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Zhang J, Feng L, Otazo R, Kim SG. Rapid dynamic contrast-enhanced MRI for small animals at 7T using 3D ultra-short echo time and golden-angle radial sparse parallel MRI. Magn Reson Med 2019; 81:140-152. [PMID: 30058079 PMCID: PMC6258350 DOI: 10.1002/mrm.27357] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2018] [Revised: 04/02/2018] [Accepted: 04/22/2018] [Indexed: 01/18/2023]
Abstract
PURPOSE To develop a rapid dynamic contrast-enhanced MRI method with high spatial and temporal resolution for small-animal imaging at 7 Tesla. METHODS An ultra-short echo time (UTE) pulse sequence using a 3D golden-angle radial sampling was implemented to achieve isotropic spatial resolution with flexible temporal resolution. Continuously acquired radial spokes were grouped into subsets for image reconstruction using a multicoil compressed sensing approach (Golden-angle RAdial Sparse Parallel; GRASP). The proposed 3D-UTE-GRASP method with high temporal and spatial resolutions was tested using 7 mice with GL261 intracranial glioma models. RESULTS Iterative reconstruction with different temporal resolutions and regularization factors λ showed that, in all cases, the cost function decreased to less than 2.5% of its starting value within 20 iterations. The difference between the time-intensity curves of 3D-UTE-GRASP and nonuniform fast Fourier transform (NUFFT) images was minimal when λ was 1% of the maximum signal intensity of the initial NUFFT images. The 3D isotropic images were used to generate pharmacokinetic parameter maps to show the detailed images of the tumor characteristics in 3D and also to show longitudinal changes during tumor growth. CONCLUSION This feasibility study demonstrated that the proposed 3D-UTE-GRASP method can be used for effective measurement of the 3D spatial heterogeneity of tumor pharmacokinetic parameters.
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Affiliation(s)
- Jin Zhang
- Center for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAIR), Department of Radiology, New York University School of Medicine, New York, NY, United States
| | - Li Feng
- Center for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAIR), Department of Radiology, New York University School of Medicine, New York, NY, United States
| | - Ricardo Otazo
- Center for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAIR), Department of Radiology, New York University School of Medicine, New York, NY, United States
| | - Sungheon Gene Kim
- Center for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAIR), Department of Radiology, New York University School of Medicine, New York, NY, United States
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Feng L, Delacoste J, Smith D, Weissbrot J, Flagg E, Moore WH, Girvin F, Raad R, Bhattacharji P, Stoffel D, Piccini D, Stuber M, Sodickson DK, Otazo R, Chandarana H. Simultaneous Evaluation of Lung Anatomy and Ventilation Using 4D Respiratory-Motion-Resolved Ultrashort Echo Time Sparse MRI. J Magn Reson Imaging 2018; 49:411-422. [PMID: 30252989 DOI: 10.1002/jmri.26245] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2018] [Accepted: 06/14/2018] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Computed tomography (CT) and spirometry are the current standard methods for assessing lung anatomy and pulmonary ventilation, respectively. However, CT provides limited ventilation information and spirometry only provides global measures of lung ventilation. Thus, a method that can enable simultaneous examination of lung anatomy and ventilation is of clinical interest. PURPOSE To develop and test a 4D respiratory-resolved sparse lung MRI (XD-UTE: eXtra-Dimensional Ultrashort TE imaging) approach for simultaneous evaluation of lung anatomy and pulmonary ventilation. STUDY TYPE Prospective. POPULATION In all, 23 subjects (11 volunteers and 12 patients, mean age = 63.6 ± 8.4). FIELD STRENGTH/SEQUENCE 3T MR; a prototype 3D golden-angle radial UTE sequence, a Cartesian breath-hold volumetric-interpolated examination (BH-VIBE) sequence. ASSESSMENT All subjects were scanned using the 3D golden-angle radial UTE sequence during normal breathing. Ten subjects underwent an additional scan during alternating normal and deep breathing. Respiratory-motion-resolved sparse reconstruction was performed for all the acquired data to generate dynamic normal-breathing or deep-breathing image series. For comparison, BH-VIBE was performed in 12 subjects. Lung images were visually scored by three experienced chest radiologists and were analyzed by two observers who segmented the left and right lung to derive ventilation parameters in comparison with spirometry. STATISTICAL TESTS Nonparametric paired two-tailed Wilcoxon signed-rank test; intraclass correlation coefficient, Pearson correlation coefficient. RESULTS XD-UTE achieved significantly improved image quality compared both with Cartesian BH-VIBE and radial reconstruction without motion compensation (P < 0.05). The global ventilation parameters (a sum of the left and right lung measures) were in good correlation with spirometry in the same subjects (correlation coefficient = 0.724). There were excellent correlations between the results obtained by two observers (intraclass correlation coefficient ranged from 0.8855-0.9995). DATA CONCLUSION Simultaneous evaluation of lung anatomy and ventilation using XD-UTE is demonstrated, which have shown good potential for improved diagnosis and management of patients with heterogeneous lung diseases. LEVEL OF EVIDENCE 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:411-422.
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Affiliation(s)
- Li Feng
- Center for Advanced Imaging Innovation and Research (CAIR), and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA.,Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Jean Delacoste
- Department of Radiology, University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - David Smith
- Center for Advanced Imaging Innovation and Research (CAIR), and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - Joseph Weissbrot
- Center for Advanced Imaging Innovation and Research (CAIR), and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - Eric Flagg
- Center for Advanced Imaging Innovation and Research (CAIR), and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - William H Moore
- Center for Advanced Imaging Innovation and Research (CAIR), and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - Francis Girvin
- Center for Advanced Imaging Innovation and Research (CAIR), and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - Roy Raad
- Center for Advanced Imaging Innovation and Research (CAIR), and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - Priya Bhattacharji
- Center for Advanced Imaging Innovation and Research (CAIR), and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - David Stoffel
- Center for Advanced Imaging Innovation and Research (CAIR), and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA
| | - Davide Piccini
- Department of Radiology, University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.,Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
| | - Matthias Stuber
- Department of Radiology, University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.,Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Daniel K Sodickson
- Center for Advanced Imaging Innovation and Research (CAIR), 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 (CAIR), and Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA.,Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Hersh Chandarana
- Center for Advanced Imaging Innovation and Research (CAIR), 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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Zhou Z, Han F, Yoshida T, Nguyen KL, Finn JP, Hu P. Improved 4D cardiac functional assessment for pediatric patients using motion-weighted image reconstruction. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2018; 31:747-756. [PMID: 30043124 DOI: 10.1007/s10334-018-0694-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2018] [Revised: 07/06/2018] [Accepted: 07/08/2018] [Indexed: 01/07/2023]
Abstract
OBJECTIVE Our aim was to develop and evaluate a motion-weighted reconstruction technique for improved cardiac function assessment in 4D magnetic resonance imaging (MRI). MATERIALS AND METHODS A flat-topped, two-sided Gaussian kernel was used to weigh k-space data in each target cardiac phase and adjacent two temporal phases during the proposed phase-by-phase reconstruction algorithm. The proposed method (Strategy 3) was used to reconstruct 18 cardiac phases based on data acquired using a previously proposed technique [4D multiphase steady-state imaging with contrast enhancement (MUSIC) technique and its self-gated extension using rotating Cartesian k-space (ROCK-MUSIC) from 12 pediatric patients. As a comparison, the same data set was reconstructed into nine phases using a phase-by-phase method (Strategy 1), 18 phases using view sharing (Strategy 4), and 18 phases using a temporal regularized method (Strategy 2). Regional image sharpness and left ventricle volumetric measurements were used to compare the four reconstructions quantitatively. RESULTS Strategies 1 and 4 generated significantly sharper images of static structures (P ≤ 0.018) than Strategies 2 and 3 but significantly more blurry (P ≤ 0.021) images of the heart. Left ventricular volumetric measurements from the nine-phase reconstruction (Strategy 1) correlated moderately (r < 0.8) with the 2D cine, whereas the remaining three techniques had a higher correlation (r > 0.9). The computational burden of Strategy 2 was six times that of Strategy 3. CONCLUSION The proposed method of motion-weighted reconstruction improves temporal resolution in 4D cardiac imaging with a clinically practical workflow.
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Affiliation(s)
- Ziwu Zhou
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Department of Bioengineering, University of California, Los Angeles, CA, USA
| | - Fei Han
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Department of Bioengineering, University of California, Los Angeles, CA, USA
| | - Takegawa Yoshida
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | - Kim-Lien Nguyen
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Division of Cardiology, VA Greater Los Angeles Healthcare System, Los Angeles, CA, USA
| | - John Paul Finn
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Biomedical Physics Inter-Departmental Graduate Program, University of California, Los Angeles, CA, USA
| | - Peng Hu
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
- Biomedical Physics Inter-Departmental Graduate Program, University of California, Los Angeles, CA, USA.
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, 300 UCLA Medical Plaza Suite B119, Los Angeles, CA, 90095, USA.
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Chen L, Liu D, Zhang J, Xie B, Zhou X, Grimm R, Huang X, Wang J, Feng L. Free-breathing dynamic contrast-enhanced MRI for assessment of pulmonary lesions using golden-angle radial sparse parallel imaging. J Magn Reson Imaging 2018; 48:459-468. [PMID: 29437281 DOI: 10.1002/jmri.25977] [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: 12/01/2017] [Accepted: 01/30/2018] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has been shown to be a promising technique for assessing lung lesions. However, DCE-MRI often suffers from motion artifacts and insufficient imaging speed. Therefore, highly accelerated free-breathing DCE-MRI is of clinical interest for lung exams. PURPOSE To test the performance of rapid free-breathing DCE-MRI for simultaneous qualitative and quantitative assessment of pulmonary lesions using Golden-angle RAdial Sparse Parallel (GRASP) imaging. STUDY TYPE Prospective. POPULATION Twenty-six patients (17 males, mean age = 55.1 ± 14.4) with known pulmonary lesions. FIELD STRENGTH/SEQUENCE 3T MR scanner; a prototype fat-saturated, T1 -weighted stack-of-stars golden-angle radial sequence for data acquisition and a Cartesian breath-hold volumetric-interpolated examination (BH-VIBE) sequence for comparison. ASSESSMENT After a dual-mode GRASP reconstruction, one with 3-second temporal resolution (3s-GRASP) and the other with 15-second temporal resolution (15s-GRASP), all GRASP and BH-VIBE images were pooled together for blind assessment by two experienced radiologists, who independently scored the overall image quality, lesion delineation, overall artifact level, and diagnostic confidence of each case. Perfusion analysis was performed for the 3s-GRASP images using a Tofts model to generate the volume transfer coefficient (Ktrans ) and interstitial volume (Ve ). STATISTICAL TESTS Nonparametric paired two-tailed Wilcoxon signed-rank test; Cohen's kappa; unpaired Student's t-test. RESULTS 15s-GRASP achieved comparable image quality with conventional BH-VIBE (P > 0.05), except for the higher overall artifact level in the precontrast phase (P = 0.018). The Ktrans and Ve in inflammation were higher than those in malignant lesions (Ktrans : 0.78 ± 0.52 min-1 vs. 0.37 ± 0.22 min-1 , P = 0.020; Ve : 0.36 ± 0.16 vs. 0.26 ± 0.1, P = 0.177). Also, the Ktrans and Ve in malignant lesions were also higher than those in benign lesions (Ktrans : 0.37 ± 0.22 min-1 vs. 0.04 ± 0.04 min-1 , P = 0.001; Ve : 0.26 ± 0.12 vs. 0.10 ± 0.00, P = 0.063). DATA CONCLUSION This feasibility study demonstrated the performance of high spatiotemporal resolution free-breathing DCE-MRI of the lung using GRASP for qualitative and quantitative assessment of pulmonary lesions. LEVEL OF EVIDENCE 2 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2018;48:459-468.
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Affiliation(s)
- Lihua Chen
- Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China.,Department of Radiology, PLA 101st Hospital, Wuxi Jiangsu, China
| | - Daihong Liu
- Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Jiuquan Zhang
- Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Bing Xie
- Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Xiaoyue Zhou
- MR Collaboration, North East Asia, Siemens Healthcare, Shanghai, China
| | | | - Xuequan Huang
- Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - Jian Wang
- Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), Chongqing, China
| | - 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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