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3D Echo Planar Time-resolved Imaging (3D-EPTI) for ultrafast multi-parametric quantitative MRI. Neuroimage 2022; 250:118963. [PMID: 35122969 PMCID: PMC8920906 DOI: 10.1016/j.neuroimage.2022.118963] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Revised: 12/09/2021] [Accepted: 02/01/2022] [Indexed: 12/11/2022] Open
Abstract
Multi-parametric quantitative MRI has shown great potential to improve the sensitivity and specificity of clinical diagnosis and to enhance our understanding of complex brain processes, but suffers from long scan time especially at high spatial resolution. To address this longstanding challenge, we introduce a novel approach termed 3D Echo Planar Time-resolved Imaging (3D-EPTI), which significantly increases the acceleration capacity of MRI sampling, and provides high acquisition efficiency for multi-parametric MRI. This is achieved by exploiting the spatiotemporal correlation of MRI data at multiple timescales through new encoding strategies within and between efficient continuous readouts. Specifically, an optimized spatiotemporal CAIPI encoding within the readouts combined with a radial-block sampling strategy across the readouts enables an acceleration rate of 800 fold in the k-t space. A subspace reconstruction was employed to resolve thousands of high-quality multi-contrast images. We have demonstrated the ability of 3D-EPTI to provide robust and repeatable whole-brain simultaneous T1, T2, T2*, PD and B1+ mapping at high isotropic resolution within minutes (e.g., 1-mm isotropic resolution in 3 minutes), and to enable submillimeter multi-parametric imaging to study detailed brain structures.
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Byanju R, Klein S, Cristobal-Huerta A, Hernandez-Tamames JA, Poot DH. Time efficiency analysis for undersampled quantitative MRI acquisitions. Med Image Anal 2022; 78:102390. [DOI: 10.1016/j.media.2022.102390] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Revised: 11/12/2021] [Accepted: 02/10/2022] [Indexed: 10/19/2022]
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Arefeen Y, Beker O, Cho J, Yu H, Adalsteinsson E, Bilgic B. Scan-specific artifact reduction in k-space (SPARK) neural networks synergize with physics-based reconstruction to accelerate MRI. Magn Reson Med 2022; 87:764-780. [PMID: 34601751 PMCID: PMC8627503 DOI: 10.1002/mrm.29036] [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: 07/07/2021] [Revised: 09/19/2021] [Accepted: 09/20/2021] [Indexed: 02/03/2023]
Abstract
PURPOSE To develop a scan-specific model that estimates and corrects k-space errors made when reconstructing accelerated MRI data. METHODS Scan-specific artifact reduction in k-space (SPARK) trains a convolutional-neural-network to estimate and correct k-space errors made by an input reconstruction technique by back-propagating from the mean-squared-error loss between an auto-calibration signal (ACS) and the input technique's reconstructed ACS. First, SPARK is applied to generalized autocalibrating partially parallel acquisitions (GRAPPA) and demonstrates improved robustness over other scan-specific models, such as robust artificial-neural-networks for k-space interpolation (RAKI) and residual-RAKI. Subsequent experiments demonstrate that SPARK synergizes with residual-RAKI to improve reconstruction performance. SPARK also improves reconstruction quality when applied to advanced acquisition and reconstruction techniques like 2D virtual coil (VC-) GRAPPA, 2D LORAKS, 3D GRAPPA without an integrated ACS region, and 2D/3D wave-encoded imaging. RESULTS SPARK yields SSIM improvement and 1.5 - 2× root mean squared error (RMSE) reduction when applied to GRAPPA and improves robustness to ACS size for various acceleration rates in comparison to other scan-specific techniques. When applied to advanced reconstruction techniques such as residual-RAKI, 2D VC-GRAPPA and LORAKS, SPARK achieves up to 20% RMSE improvement. SPARK with 3D GRAPPA also improves RMSE performance by ~2×, SSIM performance, and perceived image quality without a fully sampled ACS region. Finally, SPARK synergizes with non-Cartesian, 2D and 3D wave-encoding imaging by reducing RMSE between 20% and 25% and providing qualitative improvements. CONCLUSION SPARK synergizes with physics-based acquisition and reconstruction techniques to improve accelerated MRI by training scan-specific models to estimate and correct reconstruction errors in k-space.
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Affiliation(s)
- Yamin Arefeen
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Onur Beker
- Computer and Communication Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Jaejin Cho
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | - Heng Yu
- Department of Automation, Tsinghua University, Beijing, China
| | - Elfar Adalsteinsson
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
- Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
- Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
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Lima da Cruz GJ, Velasco C, Lavin B, Jaubert O, Botnar RM, Prieto C. Myocardial T1, T2, T2*, and fat fraction quantification via low-rank motion-corrected cardiac MR fingerprinting. Magn Reson Med 2022; 87:2757-2774. [PMID: 35081260 PMCID: PMC9306903 DOI: 10.1002/mrm.29171] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Revised: 12/06/2021] [Accepted: 01/05/2022] [Indexed: 12/11/2022]
Abstract
Purpose Develop a novel 2D cardiac MR fingerprinting (MRF) approach to enable simultaneous T1, T2, T2*, and fat fraction (FF) myocardial tissue characterization in a single breath‐hold scan. Methods Simultaneous, co‐registered, multi‐parametric mapping of T1, T2, and FF has been recently achieved with cardiac MRF. Here, we further incorporate T2* quantification within this approach, enabling simultaneous T1, T2, T2*, and FF myocardial tissue characterization in a single breath‐hold scan. T2* quantification is achieved with an eight‐echo readout that requires a long cardiac acquisition window. A novel low‐rank motion‐corrected (LRMC) reconstruction is exploited to correct for cardiac motion within the long acquisition window. The proposed T1/T2/T2*/FF cardiac MRF was evaluated in phantom and in 10 healthy subjects in comparison to conventional mapping techniques. Results The proposed approach achieved high quality parametric mapping of T1, T2, T2*, and FF with corresponding normalized RMS error (RMSE) T1 = 5.9%, T2 = 9.6% (T2 values <100 ms), T2* = 3.3% (T2* values <100 ms), and FF = 0.8% observed in phantom scans. In vivo, the proposed approach produced higher left‐ventricular myocardial T1 values than MOLLI (1148 vs 1056 ms), lower T2 values than T2‐GraSE (42.8 vs 50.6 ms), lower T2* values than eight‐echo gradient echo (GRE) (35.0 vs 39.4 ms), and higher FF values than six‐echo GRE (0.8 vs 0.3 %) reference techniques. The proposed approach achieved considerable reduction in motion artifacts compared to cardiac MRF without motion correction, improved spatial uniformity, and statistically higher apparent precision relative to conventional mapping for all parameters. Conclusion The proposed cardiac MRF approach enables simultaneous, co‐registered mapping of T1, T2, T2*, and FF in a single breath‐hold for comprehensive myocardial tissue characterization, achieving higher apparent precision than conventional methods.
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Affiliation(s)
- Gastao José Lima da Cruz
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Carlos Velasco
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Begoña Lavin
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.,Department of Biochemistry and Molecular Biology, School of Chemistry, Complutense University, Madrid, Spain
| | - Olivier Jaubert
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Rene Michael Botnar
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.,Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Claudia Prieto
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.,Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile
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Keerthivasan MB, Galons JP, Johnson K, Umapathy L, Martin DR, Bilgin A, Altbach MI. Abdominal T2-Weighted Imaging and T2 Mapping Using a Variable Flip Angle Radial Turbo Spin-Echo Technique. J Magn Reson Imaging 2022; 55:289-300. [PMID: 34254382 PMCID: PMC8678192 DOI: 10.1002/jmri.27825] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Revised: 06/22/2021] [Accepted: 06/23/2021] [Indexed: 01/03/2023] Open
Abstract
BACKGROUND T2 mapping is of great interest in abdominal imaging but current methods are limited by low resolution, slice coverage, motion sensitivity, or lengthy acquisitions. PURPOSE Develop a radial turbo spin-echo technique with refocusing variable flip angles (RADTSE-VFA) for high spatiotemporal T2 mapping and efficient slice coverage within a breath-hold and compare to the constant flip angle counterpart (RADTSE-CFA). STUDY TYPE Prospective technical efficacy. SUBJECTS Testing performed on agarose phantoms and 12 patients. Focal liver lesion classification tested on malignant (N = 24) and benign (N = 11) lesions. FIELD STRENGTH/SEQUENCE 1.5 T/RADTSE-VFA, RADTSE-CFA. ASSESSMENT A constrained objective function was used to optimize the refocusing flip angles. Phantom and/or in vivo data were used to assess relative contrast, T2 estimation, specific absorption rate (SAR), and focal liver lesion classification. STATISTICAL TESTS: t-Tests or Mann-Whitney Rank Sum tests were used. RESULTS Phantom data did not show significant differences in mean relative contrast (P = 0.10) and T2 accuracy (P = 0.99) between RADTSE-VFA and RADTSE-CFA. Adding noise caused T2 overestimation predominantly for RADTSE-CFA and low T2 values. In vivo results did not show significant differences in mean spleen-to-liver (P = 0.62) and kidney-to-liver (P = 0.49) relative contrast between RADTSE-VFA and RADTSE-CFA. Mean T2 values were not significantly different between the two techniques for spleen (T2VFA = 109.2 ± 12.3 msec; T2CFA = 110.7 ± 11.1 msec; P = 0.78) and kidney-medulla (T2VFA = 113.0 ± 8.7 msec; T2CFA = 114.0 ± 8.6 msec; P = 0.79). Liver T2 was significantly higher for RADTSE-CFA (T2VFA = 52.6 ± 6.6 msec; T2CFA = 60.4 ± 8.0 msec) consistent with T2 overestimation in the phantom study. Focal liver lesion classification had comparable T2 distributions for RADTSE-VFA and RADTSE-CFA for malignancies (P = 1.0) and benign lesions (P = 0.39). RADTSE-VFA had significantly lower SAR than RADTSE-CFA increasing slice coverage by 1.5. DATA CONCLUSION RADTSE-VFA provided noise-robust T2 estimation compared to the constant flip angle counterpart while generating T2-weighted images with comparable contrast. The VFA scheme minimized SAR improving slice efficiency for breath-hold imaging. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY STAGE: 1.
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Affiliation(s)
- Mahesh B Keerthivasan
- Medical Imaging, University of Arizona, Tucson, Arizona
- Electrical and Computer Engineering, University of Arizona, Tucson, Arizona
| | | | - Kevin Johnson
- Medical Imaging, University of Arizona, Tucson, Arizona
| | - Lavanya Umapathy
- Medical Imaging, University of Arizona, Tucson, Arizona
- Electrical and Computer Engineering, University of Arizona, Tucson, Arizona
| | - Diego R Martin
- Medical Imaging, University of Arizona, Tucson, Arizona
- Electrical and Computer Engineering, University of Arizona, Tucson, Arizona
| | - Ali Bilgin
- Medical Imaging, University of Arizona, Tucson, Arizona
- Electrical and Computer Engineering, University of Arizona, Tucson, Arizona
- Biomedical Engineering, University of Arizona, Tucson, Arizona
| | - Maria I Altbach
- Medical Imaging, University of Arizona, Tucson, Arizona
- Biomedical Engineering, University of Arizona, Tucson, Arizona
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Sprenger T, Kits A, Norbeck O, van Niekerk A, Berglund J, Rydén H, Avventi E, Skare S. NeuroMix-A single-scan brain exam. Magn Reson Med 2021; 87:2178-2193. [PMID: 34904751 DOI: 10.1002/mrm.29120] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Revised: 11/23/2021] [Accepted: 11/24/2021] [Indexed: 01/15/2023]
Abstract
PURPOSE Implement a fast, motion-robust pulse sequence that acquires T1 -weighted, T2 -weighted, T2 * -weighted, T2 fluid-attenuated inversion recovery, and DWI data in one run with only one prescription and one prescan. METHODS A software framework was developed that configures and runs several sequences in one main sequence. Based on that framework, the NeuroMix sequence was implemented, containing motion robust single-shot sequences using EPI and fast spin echo (FSE) readouts (without EPI distortions). Optional multi-shot sequences that provide better contrast, higher resolution, or isotropic resolution could also be run within the NeuroMix sequence. An optimized acquisition order was implemented that minimizes times where no data is acquired. RESULTS NeuroMix is customizable and takes between 1:20 and 4 min for a full brain scan. A comparison with the predecessor EPIMix revealed significant improvements for T2 -weighted and T2 fluid-attenuated inversion recovery, while taking only 8 s longer for a similar configuration. The optional contrasts were less motion robust but offered a significant increase in quality, detail, and contrast. Initial clinical scans on 1 pediatric and 1 adult patient showed encouraging image quality. CONCLUSION The single-shot FSE readouts for T2 -weighted and T2 fluid-attenuated inversion recovery and the optional multishot FSE and 3D-EPI contrasts significantly increased diagnostic value compared with EPIMix, allowing NeuroMix to be considered as a standalone brain MRI application.
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Affiliation(s)
- Tim Sprenger
- MR Applied Science Laboratory Europe, GE Healthcare, Stockholm, Sweden.,Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Annika Kits
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Ola Norbeck
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Adam van Niekerk
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Johan Berglund
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Henric Rydén
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Enrico Avventi
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Stefan Skare
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
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Wang F, Dong Z, Wald LL, Polimeni JR, Setsompop K. Simultaneous pure T 2 and varying T 2'-weighted BOLD fMRI using Echo Planar Time-resolved Imaging for mapping cortical-depth dependent responses. Neuroimage 2021; 245:118641. [PMID: 34655771 PMCID: PMC8820652 DOI: 10.1016/j.neuroimage.2021.118641] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Revised: 10/06/2021] [Accepted: 10/07/2021] [Indexed: 12/12/2022] Open
Abstract
Spin-echo (SE) BOLD fMRI has high microvascular specificity, and thus provides a more reliable means to localize neural activity compared to conventional gradient-echo BOLD fMRI. However, the most common SE BOLD acquisition method, SE-EPI, is known to suffer from T2′ contrast contamination with undesirable draining vein bias. To address this, in this study, we extended a recently developed distortion/blurring-free multi-shot EPI technique, Echo-Planar Time-resolved Imaging (EPTI), to cortical-depth dependent SE-fMRI at 7T to test whether it could provide purer SE BOLD contrast with minimal T2′ contamination for improved neuronal specificity. From the same acquisition, the time-resolved feature of EPTI also provides a series of asymmetric SE (ASE) images with varying T2′ weightings, and enables extraction of data equivalent to conventional SE EPI with different echo train lengths (ETLs). This allows us to systematically examine how T2′-contribution affects different SE acquisition strategies using a single dataset. A low-rank spatiotemporal subspace reconstruction was implemented for the SE-EPTI acquisition, which incorporates corrections for both shot-to-shot phase variations and dynamic B0 drifts. SE-EPTI was used in a visual task fMRI experiment to demonstrate that i) the pure SE image provided by EPTI results in the highest microvascular specificity; ii) the ASE EPTI series, with a graded introduction of T2′ weightings at time points farther away from the pure SE, show a gradual sensitivity increase along with increasing draining vein bias; iii) the longer ETL seen in conventional SE EPI acquisitions will induce more draining vein bias. Consistent results were observed across multiple subjects, demonstrating the robustness of the proposed technique for SE-BOLD fMRI with high specificity.
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Affiliation(s)
- Fuyixue Wang
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA.
| | - Zijing Dong
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Electrical Engineering and Computer Science, MIT, Cambridge, MA, USA
| | - Lawrence L Wald
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Jonathan R Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Kawin Setsompop
- Department of Radiology, Stanford University, Stanford, USA; Department of Electrical Engineering, Stanford University, Stanford, USA
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58
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Accuracy and repeatability of QRAPMASTER and MRF-vFA. Magn Reson Imaging 2021; 83:196-207. [PMID: 34506911 DOI: 10.1016/j.mri.2021.09.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Revised: 09/03/2021] [Accepted: 09/05/2021] [Indexed: 11/23/2022]
Abstract
Our purpose is to evaluate bias and repeatability of the quantitative MRI sequences QRAPMASTER, based on steady-state imaging, and variable Flip Angle MRF (MRF-VFA), based on the transient response. Both techniques are assessed with a standardized phantom and five volunteers on 1.5 T and 3 T clinical scanners. All scans were repeated eight times in consecutive weeks. In the phantom, the mean bias±95% confidence interval for T1 values with QRAPMASTER was 10 ± 10% on 1.5 T and 4 ± 13% on 3.0 T. The mean bias for T1 values with MRF-vFA was 21 ± 17% on 1.5 T and 9 ± 9% on 3.0 T. For T2 values the mean bias with QRAPMASTER was 12 ± 3% on 1.5 T and 23 ± 1% on 3.0 T. For T2 values the mean bias with MRF-vFA was 17 ± 1% on 1.5 T and 19 ± 2% on 3.0 T. QRAPMASTER estimated lower T1 and T2 values than MRF-vFA. Repeatability was good with low coefficients of variation (CoV). Mean CoV ± 95% confidence interval for T1 were 3.2 ± 0.4% on 1.5 T and 4.5 ± 0.8% on 3.0 T with QRAPMASTER and 2.7% ± 0.2% on 1.5 T and 2.5 ± 0.2% on 3.0 T with MRF-vFA. For T2 were 3.3 ± 1.9% on 1.5 T and 3.2 ± 0.6% on 3.0 T with QRAPMASTER and 2.0 ± 0.4% on 1.5 T and 5.7 ± 1.0% on 3.0 T with MRF-vFA. The in-vivo T1 and T2 are in the range of values previously reported by other authors. The in-vivo mean CoV ± 95% confidence interval in gray matter were for T1 1.7 ± 0.2% using QRAPMASTER and 0.7 ± 0.5% using MRF-vFA and for T2 were 0.9 ± 0.4% using QRAPMASTER and 2.4 ± 0.5% using MRF-vFA. In white matter were for T1 0.9 ± 0.3% using QRAPMASTER and 1.3 ± 1.1% using MRF-vFA and for T2 were 0.7 ± 0.4% using QRAPMASTER and 2.4 ± 0.4% using MRF-vFA. A GLM analysis showed that the variations in T1 and T2 mainly depend on the field strength and the subject, but not on the follow-up repetition in different days. This confirms the high repeatability of QRAPMASTER and MRF-vFA. In summary, QRAPMASTER and MRF-vFA on both systems were highly repeatable with moderate accuracy, providing results comparable to standard references. While repeatability was similar for both methods, QRAPMASTER was more accurate. QRAPMASTER is a tested commercial product but MRF-vFA is 4.77 times faster, which would ease the inclusion of quantitative relaxometry.
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Mickevicius NJ, Kim JP, Zhao J, Morris ZS, Hurst NJ, Glide-Hurst CK. Toward magnetic resonance fingerprinting for low-field MR-guided radiation therapy. Med Phys 2021; 48:6930-6940. [PMID: 34487357 DOI: 10.1002/mp.15202] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 08/17/2021] [Accepted: 08/25/2021] [Indexed: 12/14/2022] Open
Abstract
PURPOSE The acquisition of multiparametric quantitative magnetic resonance imaging (qMRI) is becoming increasingly important for functional characterization of cancer prior to- and throughout the course of radiation therapy. The feasibility of a qMRI method known as magnetic resonance fingerprinting (MRF) for rapid T1 and T2 mapping was assessed on a low-field MR-linac system. METHODS A three-dimensional MRF sequence was implemented on a 0.35T MR-guided radiotherapy system. MRF-derived measurements of T1 and T2 were compared to those obtained with gold standard single spin echo methods, and the impacts of the radiofrequency field homogeneity and scan times ranging between 6 and 48 min were analyzed by acquiring between 1 and 8 spokes per time point in a standard quantitative system phantom. The short-term repeatability of MRF was assessed over three measurements taken over a 10-h period. To evaluate transferability, MRF measurements were acquired on two additional MR-guided radiotherapy systems. Preliminary human volunteer studies were performed. RESULTS The phantom benchmarking studies showed that MRF is capable of mapping T1 and T2 values within 8% and 10% of gold standard measures, respectively, at 0.35T. The coefficient of variation of T1 and T2 estimates over three repeated scans was < 5% over a broad range of relaxation times. The T1 and T2 times derived using a single-spoke MRF acquisition across three scanners were near unity and mean percent errors in T1 and T2 estimates using the same phantom were < 3%. The mean percent differences in T1 and T2 as a result of truncating the scan time to 6 min over the large range of relaxation times in the system phantom were 0.65% and 4.05%, respectively. CONCLUSIONS The technical feasibility and accuracy of MRF on a low-field MR-guided radiation therapy device has been demonstrated. MRF can be used to measure accurate T1 and T2 maps in three dimensions from a brief 6-min scan, offering strong potential for efficient and reproducible qMRI for future clinical trials in functional plan adaptation and tumor/normal tissue response assessment.
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Affiliation(s)
- Nikolai J Mickevicius
- Department of Human Oncology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Joshua P Kim
- Department of Radiation Oncology, Henry Ford Cancer Institute, Detroit, Michigan, USA
| | - Jiwei Zhao
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Zachary S Morris
- Department of Human Oncology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Newton J Hurst
- Department of Human Oncology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Carri K Glide-Hurst
- Department of Human Oncology, University of Wisconsin-Madison, Madison, Wisconsin, USA
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Engel M, Kasper L, Wilm B, Dietrich B, Patzig F, Vionnet L, Pruessmann KP. Mono-planar T-Hex: Speed and flexibility for high-resolution 3D imaging. Magn Reson Med 2021; 87:272-280. [PMID: 34398985 PMCID: PMC9292510 DOI: 10.1002/mrm.28979] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2021] [Revised: 07/06/2021] [Accepted: 07/31/2021] [Indexed: 11/23/2022]
Abstract
Purpose The aim of this work is the reconciliation of high spatial and temporal resolution for MRI. For this purpose, a novel sampling strategy for 3D encoding is proposed, which provides flexible k‐space segmentation along with uniform sampling density and benign filtering effects related to signal decay. Methods For time‐critical MRI applications such as functional MRI (fMRI), 3D k‐space is usually sampled by stacking together 2D trajectories such as echo planar imaging (EPI) or spiral readouts, where each shot covers one k‐space plane. For very high temporal and medium to low spatial resolution, tilted hexagonal sampling (T‐Hex) was recently proposed, which allows the acquisition of a larger k‐space volume per excitation than can be covered with a planar readout. Here, T‐Hex is described in a modified version where it instead acquires a smaller k‐space volume per shot for use with medium temporal and high spatial resolution. Results Mono‐planar T‐Hex sampling provides flexibility in the choice of speed, signal‐to‐noise ratio (SNR), and contrast for rapid MRI acquisitions. For use with a conventional gradient system, it offers the greatest benefit in a regime of high in‐plane resolution <1 mm. The sampling scheme is combined with spirals for high sampling speed as well as with more conventional EPI trajectories. Conclusion Mono‐planar T‐Hex sampling combines fast 3D encoding with SNR efficiency and favorable depiction characteristics regarding noise amplification and filtering effects from T2∗ decay, thereby providing flexibility in the choice of imaging parameters. It is attractive both for high‐resolution time series such as fMRI and for applications that require rapid anatomical imaging.
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Affiliation(s)
- Maria Engel
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Lars Kasper
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland.,Translational Neuromodeling Unit, IBT, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Bertram Wilm
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Benjamin Dietrich
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Franz Patzig
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Laetitia Vionnet
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Klaas P Pruessmann
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
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61
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Manhard MK, Stockmann J, Liao C, Park D, Han S, Fair M, van den Boomen M, Polimeni J, Bilgic B, Setsompop K. A multi-inversion multi-echo spin and gradient echo echo planar imaging sequence with low image distortion for rapid quantitative parameter mapping and synthetic image contrasts. Magn Reson Med 2021; 86:866-880. [PMID: 33764563 PMCID: PMC8793364 DOI: 10.1002/mrm.28761] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Revised: 02/02/2021] [Accepted: 02/12/2021] [Indexed: 02/06/2023]
Abstract
PURPOSE Brain imaging exams typically take 10-20 min and involve multiple sequential acquisitions. A low-distortion whole-brain echo planar imaging (EPI)-based approach was developed to efficiently encode multiple contrasts in one acquisition, allowing for calculation of quantitative parameter maps and synthetic contrast-weighted images. METHODS Inversion prepared spin- and gradient-echo EPI was developed with slice-order shuffling across measurements for efficient acquisition with T1 , T2 , and T 2 ∗ weighting. A dictionary-matching approach was used to fit the images to quantitative parameter maps, which in turn were used to create synthetic weighted images with typical clinical contrasts. Dynamic slice-optimized multi-coil shimming with a B0 shim array was used to reduce B0 inhomogeneity and, therefore, image distortion by >50%. Multi-shot EPI was also implemented to minimize distortion and blurring while enabling high in-plane resolution. A low-rank reconstruction approach was used to mitigate errors from shot-to-shot phase variation. RESULTS The slice-optimized shimming approach was combined with in-plane parallel-imaging acceleration of 4× to enable single-shot EPI with more than eight-fold distortion reduction. The proposed sequence efficiently obtained 40 contrasts across the whole-brain in just over 1 min at 1.2 × 1.2 × 3 mm resolution. The multi-shot variant of the sequence achieved higher in-plane resolution of 1 × 1 × 4 mm with good image quality in 4 min. Derived quantitative maps showed comparable values to conventional mapping methods. CONCLUSION The approach allows fast whole-brain imaging with quantitative parameter maps and synthetic weighted contrasts. The slice-optimized multi-coil shimming and multi-shot reconstruction approaches result in minimal EPI distortion, giving the sequence the potential to be used in rapid screening applications.
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Affiliation(s)
- Mary Kate Manhard
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Jason Stockmann
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Congyu Liao
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Daniel Park
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - Sohyun Han
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon, Korea, Republic of
| | - Merlin Fair
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Maaike van den Boomen
- Department of Radiology, Harvard Medical School, Boston, MA, USA
- Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Jon Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
- Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, USA
| | - Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Kawin Setsompop
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
- Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, USA
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Feng L, Liu F, Soultanidis G, Liu C, Benkert T, Block KT, Fayad ZA, Yang Y. Magnetization-prepared GRASP MRI for rapid 3D T1 mapping and fat/water-separated T1 mapping. Magn Reson Med 2021; 86:97-114. [PMID: 33580909 PMCID: PMC8197608 DOI: 10.1002/mrm.28679] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Revised: 12/18/2020] [Accepted: 12/22/2020] [Indexed: 12/22/2022]
Abstract
PURPOSE This study aimed to (i) develop Magnetization-Prepared Golden-angle RAdial Sparse Parallel (MP-GRASP) MRI using a stack-of-stars trajectory for rapid free-breathing T1 mapping and (ii) extend MP-GRASP to multi-echo acquisition (MP-Dixon-GRASP) for fat/water-separated (water-specific) T1 mapping. METHODS An adiabatic non-selective 180° inversion-recovery pulse was added to a gradient-echo-based golden-angle stack-of-stars sequence for magnetization-prepared 3D single-echo or 3D multi-echo acquisition. In combination with subspace-based GRASP-Pro reconstruction, the sequence allows for standard T1 mapping (MP-GRASP) or fat/water-separated T1 mapping (MP-Dixon-GRASP), respectively. The accuracy of T1 mapping using MP-GRASP was evaluated in a phantom and volunteers (brain and liver) against clinically accepted reference methods. The repeatability of T1 estimation was also assessed in the phantom and volunteers. The performance of MP-Dixon-GRASP for water-specific T1 mapping was evaluated in a fat/water phantom and volunteers (brain and liver). RESULTS ROI-based mean T1 values are correlated between the references and MP-GRASP in the phantom (R2 = 1.0), brain (R2 = 0.96), and liver (R2 = 0.73). MP-GRASP achieved good repeatability of T1 estimation in the phantom (R2 = 1.0), brain (R2 = 0.99), and liver (R2 = 0.82). Water-specific T1 is different from in-phase and out-of-phase composite T1 (composite T1 when fat and water signal are mixed in phase or out of phase) both in the phantom and volunteers. CONCLUSION This work demonstrated the initial performance of MP-GRASP and MP-Dixon-GRASP MRI for rapid 3D T1 mapping and 3D fat/water-separated T1 mapping in the brain (without motion) and in the liver (during free breathing). With fat/water-separated T1 estimation, MP-Dixon-GRASP could be potentially useful for imaging patients with fatty-liver diseases.
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Affiliation(s)
- Li Feng
- Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Fang Liu
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Georgios Soultanidis
- Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Chenyu Liu
- Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Thomas Benkert
- MR Application Development, Siemens Healthcare GmbH, Erlangen, Germany
| | - Kai Tobias Block
- MR Application Development, Siemens Healthcare GmbH, Erlangen, Germany
- Center for Advanced Imaging Innovation and Research (CAIR), New York University School of Medicine, New York, NY, USA
| | - Zahi A. Fayad
- Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Yang Yang
- Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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Qi H, Cruz G, Botnar R, Prieto C. Synergistic multi-contrast cardiac magnetic resonance image reconstruction. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2021; 379:20200197. [PMID: 33966456 DOI: 10.1098/rsta.2020.0197] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Cardiac magnetic resonance imaging (CMR) is an important tool for the non-invasive diagnosis of a variety of cardiovascular diseases. Parametric mapping with multi-contrast CMR is able to quantify tissue alterations in myocardial disease and promises to improve patient care. However, magnetic resonance imaging is an inherently slow imaging modality, resulting in long acquisition times for parametric mapping which acquires a series of cardiac images with different contrasts for signal fitting or dictionary matching. Furthermore, extra efforts to deal with respiratory and cardiac motion by triggering and gating further increase the scan time. Several techniques have been developed to speed up CMR acquisitions, which usually acquire less data than that required by the Nyquist-Shannon sampling theorem, followed by regularized reconstruction to mitigate undersampling artefacts. Recent advances in CMR parametric mapping speed up CMR by synergistically exploiting spatial-temporal and contrast redundancies. In this article, we will review the recent developments in multi-contrast CMR image reconstruction for parametric mapping with special focus on low-rank and model-based reconstructions. Deep learning-based multi-contrast reconstruction has recently been proposed in other magnetic resonance applications. These developments will be covered to introduce the general methodology. Current technical limitations and potential future directions are discussed. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 1'.
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Affiliation(s)
- Haikun Qi
- School of Biomedical Engineering and Imaging Sciences, King's College London, 3rd Floor, Lambeth Wing, St Thomas' Hospital, London SE1 7EH, UK
| | - Gastao Cruz
- School of Biomedical Engineering and Imaging Sciences, King's College London, 3rd Floor, Lambeth Wing, St Thomas' Hospital, London SE1 7EH, UK
| | - René Botnar
- School of Biomedical Engineering and Imaging Sciences, King's College London, 3rd Floor, Lambeth Wing, St Thomas' Hospital, London SE1 7EH, UK
- Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Claudia Prieto
- School of Biomedical Engineering and Imaging Sciences, King's College London, 3rd Floor, Lambeth Wing, St Thomas' Hospital, London SE1 7EH, UK
- Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile
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Wang X, Tan Z, Scholand N, Roeloffs V, Uecker M. Physics-based reconstruction methods for magnetic resonance imaging. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2021; 379:20200196. [PMID: 33966457 PMCID: PMC8107652 DOI: 10.1098/rsta.2020.0196] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 02/01/2021] [Indexed: 05/03/2023]
Abstract
Conventional magnetic resonance imaging (MRI) is hampered by long scan times and only qualitative image contrasts that prohibit a direct comparison between different systems. To address these limitations, model-based reconstructions explicitly model the physical laws that govern the MRI signal generation. By formulating image reconstruction as an inverse problem, quantitative maps of the underlying physical parameters can then be extracted directly from efficiently acquired k-space signals without intermediate image reconstruction-addressing both shortcomings of conventional MRI at the same time. This review will discuss basic concepts of model-based reconstructions and report on our experience in developing several model-based methods over the last decade using selected examples that are provided complete with data and code. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 1'.
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Affiliation(s)
- Xiaoqing Wang
- Institute for Diagnostic and Interventional Radiology, University Medical Center Göttingen, Göttingen, Germany
- Partner Site Göttingen, German Centre for Cardiovascular Research (DZHK), Göttingen, Germany
| | - Zhengguo Tan
- Institute for Diagnostic and Interventional Radiology, University Medical Center Göttingen, Göttingen, Germany
- Partner Site Göttingen, German Centre for Cardiovascular Research (DZHK), Göttingen, Germany
| | - Nick Scholand
- Institute for Diagnostic and Interventional Radiology, University Medical Center Göttingen, Göttingen, Germany
- Partner Site Göttingen, German Centre for Cardiovascular Research (DZHK), Göttingen, Germany
| | - Volkert Roeloffs
- Institute for Diagnostic and Interventional Radiology, University Medical Center Göttingen, Göttingen, Germany
| | - Martin Uecker
- Institute for Diagnostic and Interventional Radiology, University Medical Center Göttingen, Göttingen, Germany
- Partner Site Göttingen, German Centre for Cardiovascular Research (DZHK), Göttingen, Germany
- Cluster of Excellence ‘Multiscale Bioimaging: from Molecular Machines to Networks of Excitable Cells’ (MBExC), University of Göttingen, Göttingen, Germany
- Campus Institute Data Science (CIDAS), University of Göttingen, Göttingen, Germany
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Kratzer FJ, Flassbeck S, Schmitter S, Wilferth T, Magill AW, Knowles BR, Platt T, Bachert P, Ladd ME, Nagel AM. 3D sodium ( 23 Na) magnetic resonance fingerprinting for time-efficient relaxometric mapping. Magn Reson Med 2021; 86:2412-2425. [PMID: 34061397 DOI: 10.1002/mrm.28873] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Revised: 04/16/2021] [Accepted: 05/08/2021] [Indexed: 11/07/2022]
Abstract
PURPOSE To develop a framework for 3D sodium (23 Na) MR fingerprinting (MRF), based on irreducible spherical tensor operators with tailored flip angle (FA) pattern and time-efficient data acquisition for simultaneous quantification of T1 , T 2 l ∗ , T 2 s ∗ , and T 2 ∗ in addition to ΔB0 . METHODS 23 Na-MRF was implemented in a 3D sequence and irreducible spherical tensor operators were exploited in the simulations. Furthermore, the Cramér Rao lower bound was used to optimize the flip angle pattern. A combination of single and double echo readouts was implemented to increase the readout efficiency. A study was conducted to compare results in a multicompartment phantom acquired with MRF and reference methods. Finally, the relaxation times in the human brain were measured in four healthy volunteers. RESULTS Phantom experiments revealed a mean difference of 1.0% between relaxation times acquired with MRF and results determined with the reference methods. Simultaneous quantification of the longitudinal and transverse relaxation times in the human brain was possible within 32 min using 3D 23 Na-MRF with a nominal resolution of (5 mm)3 . In vivo measurements in four volunteers yielded average relaxation times of: T1,brain = (35.0 ± 3.2) ms, T 2 l , brain ∗ = (29.3 ± 3.8) ms and T 2 s , brain ∗ = (5.5 ± 1.3) ms in brain tissue, whereas T1,CSF = (61.9 ± 2.8) ms and T 2 , CSF ∗ = (46.3 ± 4.5) ms was found in cerebrospinal fluid. CONCLUSION The feasibility of in vivo 3D relaxometric sodium mapping within roughly ½ h is demonstrated using MRF in the human brain, moving sodium relaxometric mapping toward clinically relevant measurement times.
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Affiliation(s)
- Fabian J Kratzer
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Faculty of Physics and Astronomy, Ruprecht-Karls University Heidelberg, Heidelberg, Germany
| | - Sebastian Flassbeck
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Center for Biomedical Imaging, Department of Radiology, New York University, New York, New York, USA
- Center for Advanced Imaging Innovation and Research, New York University, New York, New York, USA
| | - Sebastian Schmitter
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Berlin, Germany
| | - Tobias Wilferth
- Institute of Radiology, Friedrich-Alexander University Erlangen-Nürnberg (FAU), University Hospital Erlangen, Erlangen, Germany
| | - Arthur W Magill
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Benjamin R Knowles
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Tanja Platt
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Peter Bachert
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Faculty of Physics and Astronomy, Ruprecht-Karls University Heidelberg, Heidelberg, Germany
| | - Mark E Ladd
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Faculty of Physics and Astronomy, Ruprecht-Karls University Heidelberg, Heidelberg, Germany
- Faculty of Medicine, Ruprecht-Karls University Heidelberg, Heidelberg, Germany
| | - Armin M Nagel
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Institute of Radiology, Friedrich-Alexander University Erlangen-Nürnberg (FAU), University Hospital Erlangen, Erlangen, Germany
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Cao X, Wang K, Liao C, Zhang Z, Srinivasan Iyer S, Chen Z, Lo WC, Liu H, He H, Setsompop K, Zhong J, Bilgic B. Efficient T 2 mapping with blip-up/down EPI and gSlider-SMS (T 2 -BUDA-gSlider). Magn Reson Med 2021; 86:2064-2075. [PMID: 34046924 DOI: 10.1002/mrm.28872] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2020] [Revised: 05/10/2021] [Accepted: 05/10/2021] [Indexed: 12/22/2022]
Abstract
PURPOSE To rapidly obtain high isotropic-resolution T2 maps with whole-brain coverage and high geometric fidelity. METHODS A T2 blip-up/down EPI acquisition with generalized slice-dithered enhanced resolution (T2 -BUDA-gSlider) is proposed. A RF-encoded multi-slab spin-echo (SE) EPI acquisition with multiple TEs was developed to obtain high SNR efficiency with reduced TR. This was combined with an interleaved 2-shot EPI acquisition using blip-up/down phase encoding. An estimated field map was incorporated into the joint multi-shot EPI reconstruction with a structured low rank constraint to achieve distortion-free and robust reconstruction for each slab without navigation. A Bloch simulated subspace model was integrated into gSlider reconstruction and used for T2 quantification. RESULTS In vivo results demonstrated that the T2 values estimated by the proposed method were consistent with gold standard spin-echo acquisition. Compared to the reference 3D fast spin echo (FSE) images, distortion caused by off-resonance and eddy current effects were effectively mitigated. CONCLUSION BUDA-gSlider SE-EPI acquisition and gSlider-subspace joint reconstruction enabled distortion-free whole-brain T2 mapping in 2 min at ~1 mm3 isotropic resolution, which could bring significant benefits to related clinical and neuroscience applications.
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Affiliation(s)
- Xiaozhi Cao
- Center for Brain Imaging Science and Technology, Department of Biomedical Engineering, Zhejiang University, Hangzhou, Zhejiang, China.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Charlestown, Massachusetts, USA
| | - Kang Wang
- Department of Neurology, the First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Congyu Liao
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Charlestown, Massachusetts, USA
| | - Zijing Zhang
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,State Key Laboratory of Modern Optical Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, Zhejiang, China
| | - Siddharth Srinivasan Iyer
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Zhifeng Chen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Charlestown, Massachusetts, USA.,School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, Guangdong, China
| | - Wei-Ching Lo
- Siemens Medical Solutions, Boston, Massachusetts, USA
| | - Huafeng Liu
- State Key Laboratory of Modern Optical Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, Zhejiang, China
| | - Hongjian He
- Center for Brain Imaging Science and Technology, Department of Biomedical Engineering, Zhejiang University, Hangzhou, Zhejiang, China
| | - Kawin Setsompop
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Charlestown, Massachusetts, USA.,Harvard-MIT Department of Health Sciences and Technology, Cambridge, Massachusetts, USA
| | - Jianhui Zhong
- Center for Brain Imaging Science and Technology, Department of Biomedical Engineering, Zhejiang University, Hangzhou, Zhejiang, China.,Department of Imaging Sciences, University of Rochester, Rochester, New York, USA
| | - Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Charlestown, Massachusetts, USA.,Harvard-MIT Department of Health Sciences and Technology, Cambridge, Massachusetts, USA
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Bydder M, Ali F, Ghodrati V, Hu P, Yao J, Ellingson BM. Minimizing echo and repetition times in magnetic resonance imaging using a double half-echo k-space acquisition and low-rank reconstruction. NMR IN BIOMEDICINE 2021; 34:e4458. [PMID: 33300182 PMCID: PMC7935763 DOI: 10.1002/nbm.4458] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Accepted: 11/17/2020] [Indexed: 06/12/2023]
Abstract
Sampling k-space asymmetrically (ie, partial Fourier sampling) in the readout direction is a common way to reduce the echo time (TE) during magnetic resonance image acquisitions. This technique requires overlap around the center of k-space to provide a calibration region for reconstruction, which limits the minimum fractional echo to ~60% before artifacts are observed. The present study describes a method for reconstructing images from exact half echoes using two separate acquisitions with reversed readout polarity, effectively providing a full line of k-space without additional data around central k-space. This approach can benefit sequences or applications that prioritize short TE, short inter-echo spacing or short repetition time. An example of the latter is demonstrated to reduce banding artifacts in balanced steady-state free precession.
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Affiliation(s)
- Mark Bydder
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Fadil Ali
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Vahid Ghodrati
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Peng Hu
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Jingwen Yao
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
- Department of Bioengineering, Samueli School of Engineering, University of California Los Angeles, Los Angeles, California, USA
| | - Benjamin M Ellingson
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
- Department of Bioengineering, Samueli School of Engineering, University of California Los Angeles, Los Angeles, California, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
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Wang X, Rosenzweig S, Scholand N, Holme HCM, Uecker M. Model-based reconstruction for simultaneous multi-slice T1 mapping using single-shot inversion-recovery radial FLASH. Magn Reson Med 2021; 85:1258-1271. [PMID: 32936487 PMCID: PMC10409492 DOI: 10.1002/mrm.28497] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Revised: 08/03/2020] [Accepted: 08/04/2020] [Indexed: 01/17/2023]
Abstract
PURPOSE To develop a single-shot multi-slice T 1 mapping method by combing simultaneous multi-slice (SMS) excitations, single-shot inversion-recovery (IR) radial fast low-angle shot (FLASH), and a nonlinear model-based reconstruction method. METHODS SMS excitations are combined with a single-shot IR radial FLASH sequence for data acquisition. A previously developed single-slice calibrationless model-based reconstruction is extended to SMS, formulating the estimation of parameter maps and coil sensitivities from all slices as a single nonlinear inverse problem. Joint-sparsity constraints are further applied to the parameter maps to improve T 1 precision. Validations of the proposed method are performed for a phantom and for the human brain and liver in 6 healthy adult subjects. RESULTS Phantom results confirm good T 1 accuracy and precision of the simultaneously acquired multi-slice T 1 maps in comparison to single-slice references. In vivo human brain studies demonstrate the better performance of SMS acquisitions compared to the conventional spoke-interleaved multi-slice acquisition using model-based reconstruction. Aside from good accuracy and precision, the results of 6 healthy subjects in both brain and abdominal studies confirm good repeatability between scan and re-scans. The proposed method can simultaneously acquire T 1 maps for 5 slices of a human brain ( 0.75 × 0.75 × 5 mm 3 ) or 3 slices of the abdomen ( 1.25 × 1.25 × 6 mm 3 ) within 4 seconds. CONCLUSIONS The IR SMS radial FLASH acquisition together with a nonlinear model-based reconstruction enable rapid high-resolution multi-slice T 1 mapping with good accuracy, precision, and repeatability.
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Affiliation(s)
- Xiaoqing Wang
- Institute for Diagnostic and Interventional Radiology of the University Medical Center Göttingen, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Göttingen, Germany
| | - Sebastian Rosenzweig
- Institute for Diagnostic and Interventional Radiology of the University Medical Center Göttingen, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Göttingen, Germany
| | - Nick Scholand
- Institute for Diagnostic and Interventional Radiology of the University Medical Center Göttingen, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Göttingen, Germany
| | - H. Christian M. Holme
- Institute for Diagnostic and Interventional Radiology of the University Medical Center Göttingen, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Göttingen, Germany
| | - Martin Uecker
- Institute for Diagnostic and Interventional Radiology of the University Medical Center Göttingen, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Göttingen, Germany
- Cluster of Excellence “Multiscale Bioimaging: from Molecular Machines to Networks of Excitable Cells” (MBExC), University of Göttingen, Germany
- Campus Institute Data Science (CIDAS), University of Göttingen, Germany
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Zhang C, Klein S, Cristobal-Huerta A, Hernandez-Tamames JA, Poot DHJ. APIR4EMC: Autocalibrated parallel imaging reconstruction for extended multi-contrast imaging. Magn Reson Imaging 2021; 78:80-89. [PMID: 33592248 DOI: 10.1016/j.mri.2021.02.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Revised: 01/11/2021] [Accepted: 02/03/2021] [Indexed: 11/26/2022]
Abstract
PURPOSE To improve image quality of multi-contrast imaging with the proposed Autocalibrated Parallel Imaging Reconstruction for Extended Multi-Contrast Imaging (APIR4EMC). METHODS APIR4EMC reconstructs multi-contrast images in an autocalibrated parallel imaging reconstruction framework by adding contrasts as virtual coils. Compensation of signal evolution along the echo train of different contrasts is performed to improve signal prediction for missing samples. As a proof of concept, we performed prospectively accelerated phantom and in-vivo brain acquisitions with T1, T1-fat saturated (Fatsat), T2, PD, and FLAIR contrasts. The k-space sampling patterns of these acquisitions were jointly optimized. Images were jointly reconstructed with the proposed APIR4EMC method as well as individually with GRAPPA. Root mean square error (RMSE) to fully sampled reference images and g-factor maps were computed for both methods in the phantom experiment. Visual evaluation was performed in the in-vivo experiment. RESULTS Compared to GRAPPA, APIR4EMC reduced artifacts and improved SNR of the reconstructed images in the phantom acquisitions. Quantitatively, APIR4EMC substantially reduced noise amplification (g-factor) as well as RMSE compared to GRAPPA. Signal evolution compensation reduced artifacts. In the in-vivo experiments, 1 mm3 isotropic 3D images with contrasts of T1, T1-Fatsat, T2, PD, and FLAIR were acquired in as little as 7.5 min with the acceleration factor of 9. Reconstruction quality was consistent with the phantom results. CONCLUSION Compared to single contrast reconstruction with GRAPPA, APIR4EMC reduces artifacts and noise amplification in accelerated multi-contrast imaging.
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Affiliation(s)
- Chaoping Zhang
- Department of Medical Informatics, Erasmus MC, Rotterdam, the Netherlands; Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands.
| | - Stefan Klein
- Department of Medical Informatics, Erasmus MC, Rotterdam, the Netherlands; Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands
| | | | | | - Dirk H J Poot
- Department of Medical Informatics, Erasmus MC, Rotterdam, the Netherlands; Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands
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Mandava S, Keerthivasan MB, Martin DR, Altbach MI, Bilgin A. Improving subspace constrained radial fast spin echo MRI using block matching driven non-local low rank regularization. Phys Med Biol 2021; 66:04NT03. [PMID: 33333497 PMCID: PMC8321599 DOI: 10.1088/1361-6560/abd4b8] [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] [Indexed: 11/12/2022]
Abstract
Subspace-constrained reconstruction methods restrict the relaxation signals (of size M) in the scene to a pre-determined subspace (of size K≪M) and allow multi-contrast imaging and parameter mapping from accelerated acquisitions. However, these constraints yield poor image quality at some imaging contrasts, which can impact the parameter mapping performance. Additional regularization such as the use of joint-sparse (JS) or locally-low-rank (LLR) constraints can help improve the recovery of these images but are not sufficient when operating at high acceleration rates. We propose a method, non-local rank 3D (NLR3D), that is built on block matching and transform domain low rank constraints to allow high quality recovery of subspace-coefficient images (SCI) and subsequent multi-contrast imaging and parameter mapping. The performance of NLR3D was evaluated using Monte-Carlo (MC) simulations and compared against the JS and LLR methods. In vivo T 2 mapping results are presented on brain and knee datasets. MC results demonstrate improved bias, variance, and MSE behavior in both the multi-contrast images and parameter maps when compared to the JS and LLR methods. In vivo brain and knee results at moderate and high acceleration rates demonstrate improved recovery of high SNR early TE images as well as parameter maps. No significant difference was found in the T2 values measured in ROIs between the NLR3D reconstructions and the reference images (Wilcoxon signed rank test). The proposed method, NLR3D, enables recovery of high-quality SCI and, consequently, the associated multi-contrast images and parameter maps.
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Affiliation(s)
- Sagar Mandava
- Department of Electrical and Computer Engineering, University of Arizona, Tucson, Arizona, USA
- Department of Medical Imaging, University of Arizona, Tucson, Arizona, USA
| | - Mahesh B. Keerthivasan
- Department of Electrical and Computer Engineering, University of Arizona, Tucson, Arizona, USA
- Department of Medical Imaging, University of Arizona, Tucson, Arizona, USA
| | - Diego R. Martin
- Department of Medical Imaging, University of Arizona, Tucson, Arizona, USA
| | - Maria I. Altbach
- Department of Medical Imaging, University of Arizona, Tucson, Arizona, USA
- Department of Biomedical Engineering, University of Arizona, Tucson, Arizona, USA
| | - Ali Bilgin
- Department of Electrical and Computer Engineering, University of Arizona, Tucson, Arizona, USA
- Department of Medical Imaging, University of Arizona, Tucson, Arizona, USA
- Department of Biomedical Engineering, University of Arizona, Tucson, Arizona, USA
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Zhou Z, Chen S, Balu N, Chu B, Zhao X, Sun J, Mossa-Basha M, Hatsukami T, Börnert P, Yuan C. Neural network enhanced 3D turbo spin echo for MR intracranial vessel wall imaging. Magn Reson Imaging 2021; 78:7-17. [PMID: 33548457 DOI: 10.1016/j.mri.2021.01.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Revised: 12/28/2020] [Accepted: 01/31/2021] [Indexed: 11/17/2022]
Abstract
PURPOSE To improve the signal-to-noise ratio (SNR) and image sharpness for whole brain isotropic 0.5 mm three-dimensional (3D) T1 weighted (T1w) turbo spin echo (TSE) intracranial vessel wall imaging (IVWI) at 3 T. METHODS The variable flip angle (VFA) method enables useful optimization across scan efficiency, SNR and relaxation induced point spread function (PSF) for TSE imaging. A convolutional neural network (CNN) was developed to retrospectively enhance the acquired TSE image with PSF blurring. The previously developed VFA method to increase SNR at the expense of blur can be combined with the presented PSF correction to yield long echo train length (ETL) scan while the acquired image remains high SNR and sharp. The overall approach can enable an optimized solution for accelerated whole brain high-resolution 3D T1w TSE IVWI. Its performance was evaluated on healthy volunteers and patients. RESULTS The PSF blurred image acquired by a long ETL scan can be enhanced by CNN to restore similar sharpness as a short ETL scan, which outperforms the traditional linear PSF enhancement approach. For accelerated whole brain IVWI on volunteers, the optimized isotropic 0.5 mm 3D T1w TSE sequence with CNN based PSF enhancement provides sufficient flow suppression and improved image quality. Preliminary results on patients further demonstrated its improved delineation for intracranial vessel wall and plaque morphology. CONCLUSION The CNN enhanced VFA TSE imaging enables an overall image quality improvement for high-resolution 3D T1w IVWI, and may provide a better tradeoff across scan efficiency, SNR and PSF for 3D TSE acquisitions.
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Affiliation(s)
- Zechen Zhou
- Philips Research North America, Cambridge, MA 02141, United States.
| | - Shuo Chen
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Niranjan Balu
- Department of Radiology, University of Washington, Seattle, WA 98195, United States
| | - Baocheng Chu
- Department of Radiology, University of Washington, Seattle, WA 98195, United States
| | - Xihai Zhao
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Jie Sun
- Department of Radiology, University of Washington, Seattle, WA 98195, United States
| | - Mahmud Mossa-Basha
- Department of Radiology, University of Washington, Seattle, WA 98195, United States
| | - Thomas Hatsukami
- Department of Surgery, Division of Vascular Surgery, University of Washington, Seattle, WA 98104, United States
| | | | - Chun Yuan
- Department of Radiology, University of Washington, Seattle, WA 98195, United States
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Mickevicius NJ, Paulson ES. On the use of low-dimensional temporal subspace constraints to reduce reconstruction time and improve image quality of accelerated 4D-MRI. Radiother Oncol 2021; 158:215-223. [PMID: 33412207 DOI: 10.1016/j.radonc.2020.12.032] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2020] [Revised: 12/18/2020] [Accepted: 12/20/2020] [Indexed: 11/29/2022]
Abstract
BACKGROUND AND PURPOSE The purpose of this work is to investigate the use of low-dimensional temporal subspace constraints for 4D-MRI reconstruction from accelerated data in the context of MR-guided online adaptive radiation therapy (MRgOART). MATERIALS AND METHODS Subspace basis functions are derived directly from the accelerated golden angle radial stack-of-stars 4D-MRI data. The reconstruction times, image quality, and motion estimates are investigated as a function of the number of subspace coefficients and compared with a conventional frame-by-frame reconstruction. These experiments were performed in five patients with four 4D-MRI scans per patient on a 1.5T MR-Linac. RESULTS If two or three subspace coefficients are used, the iterative reconstruction time is reduced by 32% and 18%, respectively, compared to conventional parallel imaging with compressed sensing reconstructions. No significant difference was found between motion estimates made with the subspace-constrained reconstructions (p > 0.08). Qualitative improvements in image quality included reduction in apparent noise and reductions in streaking artifacts from the radial k-space coverage. CONCLUSION Incorporating subspace constraints for accelerated 4D-MRI reconstruction reduces noise and residual undersampling artifacts in the images while reducing computation time, making it a strong candidate for use in clinical MRgOART workflows.
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Affiliation(s)
| | - Eric S Paulson
- Department of Radiation Oncology, Medical College of Wisconsin, United States; Department of Radiology, Medical College of Wisconsin, United States; Department of Biophysics, Medical College of Wisconsin, United States
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Darçot E, Yerly J, Hilbert T, Colotti R, Najdenovska E, Kober T, Stuber M, van Heeswijk RB. Compressed sensing with signal averaging for improved sensitivity and motion artifact reduction in fluorine-19 MRI. NMR IN BIOMEDICINE 2021; 34:e4418. [PMID: 33002268 DOI: 10.1002/nbm.4418] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/26/2019] [Revised: 09/09/2020] [Accepted: 09/11/2020] [Indexed: 06/11/2023]
Abstract
Fluorine-19 (19 F) MRI of injected perfluorocarbon emulsions (PFCs) allows for the non-invasive quantification of inflammation and cell tracking, but suffers from a low signal-to-noise ratio and extended scan time. To address this limitation, we tested the hypotheses that a 19 F MRI pulse sequence that combines a specific undersampling regime with signal averaging has both increased sensitivity and robustness against motion artifacts compared with a non-averaged fully sampled pulse sequence, when both datasets are reconstructed with compressed sensing. As a proof of principle, numerical simulations and phantom experiments were performed on selected variable ranges to characterize the point spread function of undersampling patterns, as well as the vulnerability to noise of undersampling and reconstruction parameters with paired numbers of x signal averages and acceleration factor x (NAx-AFx). The numerical simulations demonstrated that a probability density function that uses 25% of the samples to fully sample the k-space central area allowed for an optimal balance between limited blurring and artifact incoherence. At all investigated noise levels, the Dice similarity coefficient (DSC) strongly depended on the regularization parameters and acceleration factor. In phantoms, the motion robustness of an NA8-AF8 undersampling pattern versus NA1-AF1 was evaluated with simulated and real motion patterns. Differences were assessed with the DSC, which was consistently higher for the NA8-AF8 compared with the NA1-AF1 strategy, for both simulated and real cyclic motion patterns (P < 0.001). Both strategies were validated in vivo in mice (n = 2) injected with perfluoropolyether. Here, the images displayed a sharper delineation of the liver with the NA8-AF8 strategy than with the NA1-AF1 strategy. In conclusion, we validated the hypotheses that in 19 F MRI the combination of undersampling and averaging improves both the sensitivity and the robustness against motion artifacts.
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Affiliation(s)
- Emeline Darçot
- Department of Radiology, University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Jérôme Yerly
- Department of Radiology, University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Lausanne and Geneva, Switzerland
| | - Tom Hilbert
- Department of Radiology, University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Advanced Clinical Imaging Technology (HC CMEA SUI DI PI), Siemens Healthcare AG, Lausanne, Switzerland
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Roberto Colotti
- Department of Radiology, University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Elena Najdenovska
- Department of Radiology, University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Lausanne and Geneva, Switzerland
| | - Tobias Kober
- Department of Radiology, University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Advanced Clinical Imaging Technology (HC CMEA SUI DI PI), Siemens Healthcare AG, Lausanne, Switzerland
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Matthias Stuber
- Department of Radiology, University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Lausanne and Geneva, Switzerland
| | - Ruud B van Heeswijk
- Department of Radiology, University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Lausanne and Geneva, Switzerland
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Zibetti MVW, Helou ES, Sharafi A, Regatte RR. Fast multicomponent 3D-T 1ρ relaxometry. NMR IN BIOMEDICINE 2020; 33:e4318. [PMID: 32359000 PMCID: PMC7606711 DOI: 10.1002/nbm.4318] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/03/2019] [Revised: 03/10/2020] [Accepted: 04/05/2020] [Indexed: 05/06/2023]
Abstract
NMR relaxometry can provide information about the relaxation of the magnetization in different tissues, increasing our understanding of molecular dynamics and biochemical composition in biological systems. In general, tissues have complex and heterogeneous structures composed of multiple pools. As a result, bulk magnetization returns to its original state with different relaxation times, in a multicomponent relaxation. Recovering the distribution of relaxation times in each voxel is a difficult inverse problem; it is usually unstable and requires long acquisition time, especially on clinical scanners. MRI can also be viewed as an inverse problem, especially when compressed sensing (CS) is used. The solution of these two inverse problems, CS and relaxometry, can be obtained very efficiently in a synergistically combined manner, leading to a more stable multicomponent relaxometry obtained with short scan times. In this paper, we will discuss the details of this technique from the viewpoint of inverse problems.
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Affiliation(s)
- Marcelo V W Zibetti
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, US
| | - Elias S Helou
- Institute of Mathematical Sciences and Computation, University of São Paulo, São Carlos, SP, Brazil
| | - Azadeh Sharafi
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, US
| | - Ravinder R Regatte
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, US
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Zi R, Zhu D, Qin Q. Quantitative T 2 mapping using accelerated 3D stack-of-spiral gradient echo readout. Magn Reson Imaging 2020; 73:138-147. [PMID: 32860871 PMCID: PMC7571618 DOI: 10.1016/j.mri.2020.08.007] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Accepted: 08/18/2020] [Indexed: 12/15/2022]
Abstract
PURPOSE To develop a rapid T2 mapping protocol using optimized spiral acquisition, accelerated reconstruction, and model fitting. MATERIALS AND METHODS A T2-prepared stack-of-spiral gradient echo (GRE) pulse sequence was applied. A model-based approach joined with compressed sensing was compared with the two methods applied separately for accelerated reconstruction and T2 mapping. A 2-parameter-weighted fitting method was compared with 2- or 3-parameter models for accurate T2 estimation under the influences of noise and B1 inhomogeneity. The performance was evaluated using both digital phantoms and healthy volunteers. Mitigating partial voluming with cerebrospinal fluid (CSF) was also tested. RESULTS Simulations demonstrates that the 2-parameter-weighted fitting approach was robust to a large range of B1 scales and SNR levels. With an in-plane acceleration factor of 5, the model-based compressed sensing-incorporated method yielded around 8% normalized errors compared to references. The T2 estimation with and without CSF nulling was consistent with literature values. CONCLUSION This work demonstrated the feasibility of a T2 quantification technique with 3D high-resolution and whole-brain coverage in 2-3 min. The proposed iterative reconstruction method, which utilized the model consistency, data consistency and spatial sparsity jointly, provided reasonable T2 estimation. The technique also allowed mitigation of CSF partial volume effect.
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Affiliation(s)
- Ruoxun Zi
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Dan Zhu
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Qin Qin
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA.
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Chaudhari AS, Kogan F, Pedoia V, Majumdar S, Gold GE, Hargreaves BA. Rapid Knee MRI Acquisition and Analysis Techniques for Imaging Osteoarthritis. J Magn Reson Imaging 2020; 52:1321-1339. [PMID: 31755191 PMCID: PMC7925938 DOI: 10.1002/jmri.26991] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Revised: 10/22/2019] [Accepted: 10/22/2019] [Indexed: 12/16/2022] Open
Abstract
Osteoarthritis (OA) of the knee is a major source of disability that has no known treatment or cure. Morphological and compositional MRI is commonly used for assessing the bone and soft tissues in the knee to enhance the understanding of OA pathophysiology. However, it is challenging to extend these imaging methods and their subsequent analysis techniques to study large population cohorts due to slow and inefficient imaging acquisition and postprocessing tools. This can create a bottleneck in assessing early OA changes and evaluating the responses of novel therapeutics. The purpose of this review article is to highlight recent developments in tools for enhancing the efficiency of knee MRI methods useful to study OA. Advances in efficient MRI data acquisition and reconstruction tools for morphological and compositional imaging, efficient automated image analysis tools, and hardware improvements to further drive efficient imaging are discussed in this review. For each topic, we discuss the current challenges as well as potential future opportunities to alleviate these challenges. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 3.
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Affiliation(s)
| | - Feliks Kogan
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Valentina Pedoia
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- Center of Digital Health Innovation (CDHI), University of California San Francisco, San Francisco, California, USA
| | - Sharmila Majumdar
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
- Center of Digital Health Innovation (CDHI), University of California San Francisco, San Francisco, California, USA
| | - Garry E. Gold
- Department of Radiology, Stanford University, Stanford, California, USA
- Department of Orthopaedic Surgery, Stanford University, Stanford, California, USA
- Department of Bioengineering, Stanford University, Stanford, California, USA
| | - Brian A. Hargreaves
- Department of Radiology, Stanford University, Stanford, California, USA
- Department of Bioengineering, Stanford University, Stanford, California, USA
- Department of Electrical Engineering, Stanford University, Stanford, California, USA
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van der Heide O, Sbrizzi A, van den Berg CAT. Accelerated MR-STAT Reconstructions Using Sparse Hessian Approximations. IEEE TRANSACTIONS ON MEDICAL IMAGING 2020; 39:3737-3748. [PMID: 32746119 DOI: 10.1109/tmi.2020.3003893] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
MR-STAT is a quantitative magnetic resonance imaging framework for obtaining multi-parametric quantitative tissue parameter maps using data from single short scans. A large-scale optimization problem is solved in which spatial localization of signal and estimation of tissue parameters are performed simultaneously by directly fitting a Bloch-based volumetric signal model to measured time-domain data. In previous work, a highly parallelized, matrix-free Gauss-Newton reconstruction algorithm was presented that can solve the large-scale optimization problem for high-resolution scans. The main computational bottleneck in this matrix-free method is solving a linear system involving (an approximation to) the Hessian matrix at each iteration. In the current work, we analyze the structure of the Hessian matrix in relation to the dynamics of the spin system and derive conditions under which the (approximate) Hessian admits a sparse structure. In the case of Cartesian sampling patterns with smooth RF trains we demonstrate how exploiting this sparsity can reduce MR-STAT reconstruction times by approximately an order of magnitude.
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Fu Z, Mandava S, Keerthivasan MB, Li Z, Johnson K, Martin DR, Altbach MI, Bilgin A. A multi-scale residual network for accelerated radial MR parameter mapping. Magn Reson Imaging 2020; 73:152-162. [PMID: 32882339 PMCID: PMC7580302 DOI: 10.1016/j.mri.2020.08.013] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Revised: 07/17/2020] [Accepted: 08/20/2020] [Indexed: 01/04/2023]
Abstract
A deep learning MR parameter mapping framework which combines accelerated radial data acquisition with a multi-scale residual network (MS-ResNet) for image reconstruction is proposed. The proposed supervised learning strategy uses input image patches from multi-contrast images with radial undersampling artifacts and target image patches from artifact-free multi-contrast images. Subspace filtering is used during pre-processing to denoise input patches. For each anatomy and relaxation parameter, an individual network is trained. in vivo T1 mapping results are obtained on brain and abdomen datasets and in vivo T2 mapping results are obtained on brain and knee datasets. Quantitative results for the T2 mapping of the knee show that MS-ResNet trained using either fully sampled or undersampled data outperforms conventional model-based compressed sensing methods. This is significant because obtaining fully sampled training data is not possible in many applications. in vivo brain and abdomen results for T1 mapping and in vivo brain results for T2 mapping demonstrate that MS-ResNet yields contrast-weighted images and parameter maps that are comparable to those achieved by model-based iterative methods while offering two orders of magnitude reduction in reconstruction times. The proposed approach enables recovery of high-quality contrast-weighted images and parameter maps from highly accelerated radial data acquisitions. The rapid image reconstructions enabled by the proposed approach makes it a good candidate for routine clinical use.
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Affiliation(s)
- Zhiyang Fu
- Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ, USA; Department of Medical Imaging, University of Arizona, Tucson, AZ, USA
| | - Sagar Mandava
- Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ, USA; Department of Medical Imaging, University of Arizona, Tucson, AZ, USA
| | - Mahesh B Keerthivasan
- Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ, USA; Department of Medical Imaging, University of Arizona, Tucson, AZ, USA
| | - Zhitao Li
- Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ, USA; Department of Medical Imaging, University of Arizona, Tucson, AZ, USA
| | - Kevin Johnson
- Department of Medical Imaging, University of Arizona, Tucson, AZ, USA
| | - Diego R Martin
- Department of Medical Imaging, University of Arizona, Tucson, AZ, USA
| | - Maria I Altbach
- Department of Medical Imaging, University of Arizona, Tucson, AZ, USA; Department of Biomedical Engineering, University of Arizona, Tucson, AZ, USA
| | - Ali Bilgin
- Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ, USA; Department of Medical Imaging, University of Arizona, Tucson, AZ, USA; Department of Biomedical Engineering, University of Arizona, Tucson, AZ, USA.
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Ma S, Wang N, Fan Z, Kaisey M, Sicotte NL, Christodoulou AG, Li D. Three-dimensional whole-brain simultaneous T1, T2, and T1ρ quantification using MR Multitasking: Method and initial clinical experience in tissue characterization of multiple sclerosis. Magn Reson Med 2020; 85:1938-1952. [PMID: 33107126 DOI: 10.1002/mrm.28553] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Revised: 09/22/2020] [Accepted: 09/23/2020] [Indexed: 02/06/2023]
Abstract
PURPOSE To develop a 3D whole-brain simultaneous T1/T2/T1ρ quantification method with MR Multitasking that provides high quality, co-registered multiparametric maps in 9 min. METHODS MR Multitasking conceptualizes T1/T2/T1ρ relaxations as different time dimensions, simultaneously resolving all three dimensions with a low-rank tensor image model. The proposed method was validated on a phantom and in healthy volunteers, comparing quantitative measurements against corresponding reference methods and evaluating the scan-rescan repeatability. Initial clinical validation was performed in age-matched relapsing-remitting multiple sclerosis (RRMS) patients to examine the feasibility of quantitative tissue characterization and to compare with the healthy control cohort. The feasibility of synthesizing six contrast-weighted images was also examined. RESULTS Our framework produced high quality, co-registered T1/T2/T1ρ maps that closely resemble the reference maps. Multitasking T1/T2/T1ρ measurements showed substantial agreement with reference measurements on the phantom and in healthy controls. Bland-Altman analysis indicated good in vivo repeatability of all three parameters. In RRMS patients, lesions were conspicuously delineated on all three maps and on four synthetic weighted images (T2-weighted, T2-FLAIR, double inversion recovery, and a novel "T1ρ-FLAIR" contrast). T1 and T2 showed significant differences for normal appearing white matter between patients and controls, while T1ρ showed significant differences for normal appearing white matter, cortical gray matter, and deep gray matter. The combination of three parameters significantly improved the differentiation between RRMS patients and healthy controls, compared to using any single parameter alone. CONCLUSION MR Multitasking simultaneously quantifies whole-brain T1/T2/T1ρ and is clinically promising for quantitative tissue characterization of neurological diseases, such as MS.
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Affiliation(s)
- Sen Ma
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.,Department of Bioengineering, University of California, Los Angeles, California, USA
| | - Nan Wang
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.,Department of Bioengineering, University of California, Los Angeles, California, USA
| | - Zhaoyang Fan
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.,Department of Bioengineering, University of California, Los Angeles, California, USA
| | - Marwa Kaisey
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Nancy L Sicotte
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Anthony G Christodoulou
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.,Department of Bioengineering, University of California, Los Angeles, California, USA
| | - Debiao Li
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.,Department of Bioengineering, University of California, Los Angeles, California, USA
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Liu X, Gómez PA, Solana AB, Wiesinger F, Menzel MI, Menze BH. Silent 3D MR sequence for quantitative and multicontrast T1 and proton density imaging. Phys Med Biol 2020; 65:185010. [PMID: 32663809 DOI: 10.1088/1361-6560/aba5e8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
This study aims to develop a silent, fast and 3D method for T1 and proton density (PD) mapping, while generating time series of T1-weighted (T1w) images with bias-field correction. Undersampled T1w images at different effective inversion times (TIs) were acquired using the inversion recovery prepared RUFIS sequence with an interleaved k-space trajectory. Unaliased images were reconstructed by constraining the signal evolution to a temporal subspace which was learned from the signal model. Parameter maps were obtained by fitting the data to the signal model, and bias-field correction was conducted on T1w images. Accuracy and repeatability of the method was accessed in repeated experiments with phantom and volunteers. For the phantom study, T1 values obtained by the proposed method were highly consistent with values from the gold standard method, R2 = 0.9976. Coefficients of variation (CVs) ranged from 0.09% to 0.83%. For the volunteer study, T1 values from gray and white matter regions were consistent with literature values, and peaks of gray and white matter can be clearly delineated on whole-brain T1 histograms. CVs ranged from 0.01% to 2.30%. The acoustic noise measured at the scanner isocenter was 2.6 dBA higher compared to the in-bore background. Rapid and with low acoustic noise, the proposed method is shown to produce accurate T1 and PD maps with high repeatability by reconstructing sparsely sampled T1w images at different TIs using temporal subspace. Our approach can greatly enhance patient comfort during examination and therefore increase the acceptance of the procedure.
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Affiliation(s)
- Xin Liu
- Technical University Munich, Garching, Germany. GE Global Research Europe, Munich, Germany
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Rapid golden-angle diffusion-weighted propeller MRI for simultaneous assessment of ADC and IVIM. Neuroimage 2020; 223:117327. [PMID: 32882379 PMCID: PMC7792631 DOI: 10.1016/j.neuroimage.2020.117327] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Revised: 08/22/2020] [Accepted: 08/24/2020] [Indexed: 11/24/2022] Open
Abstract
Purpose: Golden-angle single-shot PROPLLER (GA-SS-PROP) is proposed to accelerate the PROPELLER acquisition for distortion-free diffusion-weighted (DW) imaging. Acceleration is achieved by acquiring one-shot per b-value and several b-values can be acquired along a diffusion direction, where the DW signal follows a bi-exponential decay (i.e. IVIM). Sparse reconstruction is used to reconstruct full resolution DW images. Consequently, apparent diffusion coefficient (ADC) map and IVIM maps (i.e., perfusion fraction (f) and the perfusion-free diffusion coefficient (D)) are obtained simultaneously. The performance of GA-SS-PROP was demonstrated with simulation and human experiments. Methods: A realistic numerical phantom of high-quality diffusion images of the brain was developed. The error of the reconstructed DW images and quantitative maps were compared to the ground truth. The pulse sequence was developed to acquire human brain data. For comparison, fully sampled PROPELLER and conventional single-shot echo planar imaging (SS-EPI) acquisitions were performed. Results: GA-SS-PROP was 5 times faster than conventional PROPELLER acquisition with comparable image quality. The simulation demonstrated that sparse reconstruction is effective in restoring contrast and resolution. The human experiments demonstrated that GA-SS-PROP achieved superior image fidelity compared to SS-EPI for the same acquisition time and same in-plane resolution (1 × 1 mm2). Conclusion: GA-SS-PROP offers fast, high-resolution and distortion-free DW images. The generated quantitative maps (f, D and ADC) can provide valuable information on tissue perfusion and diffusion properties simultaneously, which are desirable in many applications, especially in oncology. As a turbo spin-echo based technique, it can be applied in most challenging regions where SS-EPI is problematic.
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82
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Wyatt CR, Barbara TM, Guimaraes AR. T 1ρ magnetic resonance fingerprinting. NMR IN BIOMEDICINE 2020; 33:e4284. [PMID: 32125050 PMCID: PMC8818303 DOI: 10.1002/nbm.4284] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Revised: 02/03/2020] [Accepted: 02/05/2020] [Indexed: 05/15/2023]
Abstract
T1ρ relaxation imaging is a quantitative imaging technique that has been used to assess cartilage integrity, liver fibrosis, tumors, cardiac infarction, and Alzheimer's disease. T1 , T2 , and T1ρ relaxation time constants have each demonstrated different degrees of sensitivity to several markers of fibrosis and inflammation, allowing for a potential multi-parametric approach to tissue quantification. Traditional magnetic resonance fingerprinting (MRF) has been shown to provide quick, quantitative mapping of T1 and T2 relaxation time constants. In this study, T1ρ relaxation is added to the MRF framework using spin lock preparations. An MRF sequence involving an RF-spoiled sequence with TR , flip angle, T1ρ , and T2 preparation variation is described. The sequence is then calibrated against conventional T1 , T2 , and T1ρ relaxation mapping techniques in agar phantoms and the abdomens of four healthy volunteers. Strong intraclass correlation coefficients (ICC > 0.9) were found between conventional and MRF sequences in phantoms and also in healthy volunteers (ICC > 0.8). The highest ICC correlation values were seen in T1 , followed by T1ρ and then T2 . In this study, T1ρ relaxation has been incorporated into the MRF framework by using spin lock preparations, while still fitting for T1 and T2 relaxation time constants. The acquisition of these parameters within a single breath hold in the abdomen alleviates the issues of movement between breath holds in conventional techniques.
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Affiliation(s)
- Cory R. Wyatt
- Advanced Imaging Research Center, Oregon Health & Sciences University, Portland, OR 97239
- Department of Diagnostic Radiology, Oregon Health & Sciences University, Portland, OR 97239
| | - Thomas M. Barbara
- Advanced Imaging Research Center, Oregon Health & Sciences University, Portland, OR 97239
| | - Alexander R. Guimaraes
- Advanced Imaging Research Center, Oregon Health & Sciences University, Portland, OR 97239
- Department of Diagnostic Radiology, Oregon Health & Sciences University, Portland, OR 97239
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83
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Dong Z, Wang F, Reese TG, Bilgic B, Setsompop K. Echo planar time-resolved imaging with subspace reconstruction and optimized spatiotemporal encoding. Magn Reson Med 2020; 84:2442-2455. [PMID: 32333478 DOI: 10.1002/mrm.28295] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2019] [Revised: 03/01/2020] [Accepted: 03/31/2020] [Indexed: 12/17/2022]
Abstract
PURPOSE To develop new encoding and reconstruction techniques for fast multi-contrast/quantitative imaging. METHODS The recently proposed Echo Planar Time-resolved Imaging (EPTI) technique can achieve fast distortion- and blurring-free multi-contrast/quantitative imaging. In this work, a subspace reconstruction framework is developed to improve the reconstruction accuracy of EPTI at high encoding accelerations. The number of unknowns in the reconstruction is significantly reduced by modeling the temporal signal evolutions using low-rank subspace. As part of the proposed reconstruction approach, a B0 -update algorithm and a shot-to-shot B0 variation correction method are developed to enable the reconstruction of high-resolution tissue phase images and to mitigate artifacts from shot-to-shot phase variations. Moreover, the EPTI concept is extended to 3D k-space for 3D GE-EPTI, where a new "temporal-variant" of CAIPI encoding is proposed to further improve performance. RESULTS The effectiveness of the proposed subspace reconstruction was demonstrated first in 2D GESE EPTI, where the reconstruction achieved higher accuracy when compared to conventional B0 -informed GRAPPA. For 3D GE-EPTI, a retrospective undersampling experiment demonstrates that the new temporal-variant CAIPI encoding can achieve up to 72× acceleration with close to 2× reduction in reconstruction error when compared to conventional spatiotemporal-CAIPI encoding. In a prospective undersampling experiment, high-quality whole-brain T 2 ∗ and tissue phase maps at 1 mm isotropic resolution were acquired in 52 seconds at 3T using 3D GE-EPTI with temporal-variant CAIPI encoding. CONCLUSION The proposed subspace reconstruction and optimized temporal-variant CAIPI encoding can further improve the performance of EPTI for fast quantitative mapping.
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Affiliation(s)
- Zijing Dong
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Electrical Engineering and Computer Science, MIT, Cambridge, Massachusetts, USA
| | - Fuyixue Wang
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Harvard-MIT Health Sciences and Technology, MIT, Cambridge, Massachusetts, USA
| | - Timothy G Reese
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Kawin Setsompop
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Harvard-MIT Health Sciences and Technology, MIT, Cambridge, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
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84
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Roeloffs V, Uecker M, Frahm J. Joint T1 and T2 Mapping With Tiny Dictionaries and Subspace-Constrained Reconstruction. IEEE TRANSACTIONS ON MEDICAL IMAGING 2020; 39:1008-1014. [PMID: 31484113 DOI: 10.1109/tmi.2019.2939130] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
A novel method is developed that adaptively generates tiny dictionaries for joint T1-T2 mapping in magnetic resonance imaging. This work breaks the bond between dictionary size and representation accuracy (i) by approximating the Bloch-response manifold by piece-wise linear functions and (ii) by adaptively refining the sampling grid depending on the locally-linear approximation error. Data acquisition is accomplished with use of an 2D radially sampled Inversion-Recovery Hybrid-State Free Precession sequence. Adaptive dictionaries are generated with different error tolerances and compared to a heuristically designed dictionary. Based on simulation results, tiny dictionaries were used for T1-T2 mapping in phantom and in vivo studies. Reconstruction and parameter mapping were performed entirely in subspace. All experiments demonstrated excellent agreement between the proposed mapping technique and template matching using heuristic dictionaries. Adaptive dictionaries in combination with manifold projection allow to reduce the necessary dictionary sizes by one to two orders of magnitude.
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85
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Milshteyn E, Reed GD, Gordon JW, von Morze C, Cao P, Tang S, Leynes AP, Larson PEZ, Vigneron DB. Simultaneous T 1 and T 2 mapping of hyperpolarized 13C compounds using the bSSFP sequence. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2020; 312:106691. [PMID: 32058912 PMCID: PMC7227792 DOI: 10.1016/j.jmr.2020.106691] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/09/2019] [Revised: 01/29/2020] [Accepted: 01/30/2020] [Indexed: 06/10/2023]
Abstract
As in conventional 1H MRI, T1 and T2 relaxation times of hyperpolarized (HP) 13C nuclei can provide important biomedical information. Two new approaches were developed for simultaneous T1 and T2 mapping of HP 13C probes based on balanced steady state free precession (bSSFP) acquisitions: a method based on sequential T1 and T2 mapping modules, and a model-based joint T1/T2 approach analogous to MR fingerprinting. These new methods were tested in simulations, HP 13C phantoms, and in vivo in normal Sprague-Dawley rats. Non-localized T1 values, low flip angle EPI T1 maps, bSSFP T2 maps, and Bloch-Siegert B1 maps were also acquired for comparison. T1 and T2 maps acquired using both approaches were in good agreement with both literature values and data from comparative acquisitions. Multiple HP 13C compounds were successfully mapped, with their relaxation time parameters measured within heart, liver, kidneys, and vasculature in one acquisition for the first time.
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Affiliation(s)
- Eugene Milshteyn
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA.
| | | | - Jeremy W Gordon
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Cornelius von Morze
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Peng Cao
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Shuyu Tang
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Andrew P Leynes
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Peder E Z Larson
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Daniel B Vigneron
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
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86
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Song JE, Shin J, Lee H, Choi YS, Song HT, Kim DH. Dynamic hyperpolarized 13 C MR spectroscopic imaging using SPICE in mouse kidney at 9.4 T. NMR IN BIOMEDICINE 2020; 33:e4230. [PMID: 31856426 DOI: 10.1002/nbm.4230] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/23/2019] [Revised: 10/29/2019] [Accepted: 11/04/2019] [Indexed: 05/16/2023]
Abstract
This study aims to investigate the feasibility of dynamic hyperpolarized 13 C MR spectroscopic imaging (MRSI) using the SPectroscopic Imaging by exploiting spatiospectral CorrElation (SPICE) technique and an estimation of the spatially resolved conversion constant rate (kpl ). An acquisition scheme comprising a single training dataset and several imaging datasets was proposed considering hyperpolarized 13 C circumstances. The feasibility and advantage of the scheme were investigated in two parts: (a) consistency of spectral basis over time and (b) accuracy of the estimated kpl . The simulations and in vivo experiments support accurate kpl estimation with consistent spectral bases. The proposed method was implemented in an enzyme phantom and via in vivo experiments. In the enzyme phantom experiments, spatially resolved homogeneous kpl maps were observed. In the in vivo experiments, normal diet (ND) mice and high-fat diet (HFD) mice had kpl (s-1 ) values of medullar (ND: 0.0119 ± 0.0022, HFD: 0.0195 ± 0.0005) and cortical (ND: 0.0148 ±0.0023, HFD: 0.0224 ±0.0054) regions which were higher than vascular (ND: 0.0087 ±0.0013, HFD: 0.0132 ±0.0050) regions. In particular, the kpl value in the medullar region exhibited a significant difference between the two diet groups. In summary, the feasibility of using modified SPICE for dynamic hyperpolarized 13 C MRSI was demonstrated via simulations and in vivo experiments. The consistency of spectral bases over time and the accuracy of the estimated kpl values validate the proposed acquisition scheme, which comprises only a single training dataset. The proposed method improved the spatial resolution of dynamic hyperpolarized 13 C MRSI, which could be used for kpl estimation using high signal-to-noise ratio spectral bases.
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Affiliation(s)
- Jae Eun Song
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea
| | - Jaewook Shin
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea
| | - Hansol Lee
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea
| | - Young-Suk Choi
- Department of Radiology and Research Institute of Radiological Science, College of Medicine, Yonsei University, Seoul, South Korea
| | - Ho-Taek Song
- Department of Radiology and Research Institute of Radiological Science, College of Medicine, Yonsei University, Seoul, South Korea
| | - Dong-Hyun Kim
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, South Korea
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87
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Jaubert O, Cruz G, Bustin A, Schneider T, Koken P, Doneva M, Rueckert D, Botnar RM, Prieto C. Free-running cardiac magnetic resonance fingerprinting: Joint T1/T2 map and Cine imaging. Magn Reson Imaging 2020; 68:173-182. [PMID: 32061964 PMCID: PMC7677167 DOI: 10.1016/j.mri.2020.02.005] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Revised: 01/21/2020] [Accepted: 02/09/2020] [Indexed: 12/15/2022]
Abstract
PURPOSE To develop and evaluate a novel non-ECG triggered 2D magnetic resonance fingerprinting (MRF) sequence allowing for simultaneous myocardial T1 and T2 mapping and cardiac Cine imaging. METHODS Cardiac MRF (cMRF) has been recently proposed to provide joint T1/T2 myocardial mapping by triggering the acquisition to mid-diastole and relying on a subject-dependent dictionary of MR signal evolutions to generate the maps. In this work, we propose a novel "free-running" (non-ECG triggered) cMRF framework for simultaneous myocardial T1 and T2 mapping and cardiac Cine imaging in a single scan. Free-running cMRF is based on a transient state bSSFP acquisition with tiny golden angle radial readouts, varying flip angle and multiple adiabatic inversion pulses. The acquired data is retrospectively gated into several cardiac phases, which are reconstructed with an approach that combines parallel imaging, low rank modelling and patch-based high-order tensor regularization. Free-running cMRF was evaluated in a standardized phantom and ten healthy subjects. Comparison with reference spin-echo, MOLLI, SASHA, T2-GRASE and Cine was performed. RESULTS T1 and T2 values obtained with the proposed approach were in good agreement with reference phantom values (ICC(A,1) > 0.99). Reported values for myocardium septum T1 were 1043 ± 48 ms, 1150 ± 100 ms and 1160 ± 79 ms for MOLLI, SASHA and free-running cMRF respectively and for T2 of 51.7 ± 4.1 ms and 44.6 ± 4.1 ms for T2-GRASE and free-running cMRF respectively. Good agreement was observed between free-running cMRF and conventional Cine 2D ejection fraction (bias = -0.83%). CONCLUSION The proposed free-running cardiac MRF approach allows for simultaneous assessment of myocardial T1 and T2 and Cine imaging in a single scan.
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Affiliation(s)
- O Jaubert
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
| | - G Cruz
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - A Bustin
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - T Schneider
- Philips Healthcare, Guilford, United Kingdom
| | - P Koken
- Philips Research Europe, Hamburg, Germany
| | - M Doneva
- Philips Research Europe, Hamburg, Germany
| | - D Rueckert
- Department of Computing, Imperial College London, London, United Kingdom
| | - R M Botnar
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - C Prieto
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom; Escuela de Ingeniería, Pontificia Universidad Católica de Chile, Santiago, Chile
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88
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Tamir JI, Ong F, Anand S, Karasan E, Wang K, Lustig M. Computational MRI with Physics-based Constraints: Application to Multi-contrast and Quantitative Imaging. IEEE SIGNAL PROCESSING MAGAZINE 2020; 37:94-104. [PMID: 33746469 PMCID: PMC7977016 DOI: 10.1109/msp.2019.2940062] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/17/2023]
Abstract
Compressed sensing takes advantage of low-dimensional signal structure to reduce sampling requirements far below the Nyquist rate. In magnetic resonance imaging (MRI), this often takes the form of sparsity through wavelet transform, finite differences, and low rank extensions. Though powerful, these image priors are phenomenological in nature and do not account for the mechanism behind the image formation. On the other hand, MRI signal dynamics are governed by physical laws, which can be explicitly modeled and used as priors for reconstruction. These explicit and implicit signal priors can be synergistically combined in an inverse problem framework to recover sharp, multi-contrast images from highly accelerated scans. Furthermore, the physics-based constraints provide a recipe for recovering quantitative, bio-physical parameters from the data. This article introduces physics-based modeling constraints in MRI and shows how they can be used in conjunction with compressed sensing for image reconstruction and quantitative imaging. We describe model-based quantitative MRI, as well as its linear subspace approximation. We also discuss approaches to selecting user-controllable scan parameters given knowledge of the physical model. We present several MRI applications that take advantage of this framework for the purpose of multi-contrast imaging and quantitative mapping.
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Affiliation(s)
- Jonathan I Tamir
- Department of Electrical Engineering and Computer Sciences, University of California
| | - Frank Ong
- Department of Electrical Engineering, Stanford University
| | - Suma Anand
- Department of Electrical Engineering and Computer Sciences, University of California
| | - Ekin Karasan
- Department of Electrical Engineering and Computer Sciences, University of California
| | - Ke Wang
- Department of Electrical Engineering and Computer Sciences, University of California
| | - Michael Lustig
- Department of Electrical Engineering and Computer Sciences, University of California
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89
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Ma S, Nguyen CT, Han F, Wang N, Deng Z, Binesh N, Moser FG, Christodoulou AG, Li D. Three-dimensional simultaneous brain T 1 , T 2 , and ADC mapping with MR Multitasking. Magn Reson Med 2019; 84:72-88. [PMID: 31765496 DOI: 10.1002/mrm.28092] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2019] [Revised: 10/01/2019] [Accepted: 10/31/2019] [Indexed: 02/06/2023]
Abstract
PURPOSE To develop a simultaneous T1 , T2 , and ADC mapping method that provides co-registered, distortion-free images and enables multiparametric quantification of 3D brain coverage in a clinically feasible scan time with the MR Multitasking framework. METHODS The T1 /T2 /diffusion weighting was generated by a series of T2 preparations and diffusion preparations. The underlying multidimensional image containing 3 spatial dimensions, 1 T1 weighting dimension, 1 T2 -preparation duration dimension, 1 b-value dimension, and 1 diffusion direction dimension was modeled as a 5-way low-rank tensor. A separate real-time low-rank model incorporating time-resolved phase correction was also used to compensate for both inter-shot and intra-shot phase inconsistency induced by physiological motion. The proposed method was validated on both phantom and 16 healthy subjects. The quantification of T1 /T2 /ADC was evaluated for each case. Three post-surgery brain tumor patients were scanned for demonstration of clinical feasibility. RESULTS Multitasking T1 /T2 /ADC maps were perfectly co-registered and free from image distortion. Phantom studies showed substantial quantitative agreement ( R 2 = 0.999 ) with reference protocols for T1 /T2 /ADC. In vivo studies showed nonsignificant T1 (P = .248), T2 (P = .97), ADC (P = .328) differences among the frontal, parietal, and occipital regions. Although Multitasking showed significant differences of T1 (P = .03), T2 (P < .001), and ADC (P = .001) biases against the references, the mean bias estimates were small (ΔT1 % < 5%, ΔT2 % < 7%, ΔADC% < 5%), with all intraclass correlation coefficients greater than 0.82 indicating "excellent" agreement. Patient studies showed that Multitasking T1 /T2 /ADC maps were consistent with the clinical qualitative images. CONCLUSION The Multitasking approach simultaneously quantifies T1 /T2 /ADC with substantial agreement with the references and is promising for clinical applications.
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Affiliation(s)
- Sen Ma
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, California.,Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | - Christopher T Nguyen
- Cardiovascular Research Center, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts
| | - Fei Han
- Siemens Healthcare, Los Angeles, California
| | - Nan Wang
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, California.,Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | - Zixin Deng
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California
| | - Nader Binesh
- S. Mark Taper Foundation Imaging Center, Cedars-Sinai Medical Center, Los Angeles, California
| | - Franklin G Moser
- Department of Neurosurgery, Cedars-Sinai Medical Center, Los Angeles, California
| | | | - Debiao Li
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, California.,Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California
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90
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Zhou Z, Yuan C, Börnert P. Self-calibrating wave-encoded 3D turbo spin echo imaging using subspace model based autofocusing. Magn Reson Med 2019; 83:1250-1262. [PMID: 31628767 DOI: 10.1002/mrm.28007] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2019] [Revised: 08/02/2019] [Accepted: 08/31/2019] [Indexed: 12/22/2022]
Abstract
PURPOSE To develop a self-calibrating approach for the estimation of wave point spread function (PSF) and coil sensitivities from the subsampled wave-encoded k-space, and evaluate its performance for wave-encoded 3D turbo spin echo (TSE) imaging. METHODS A low rank subspace parametric model was demonstrated in simulation to improve the representation for practical wave encoding k-space trajectories with aperiodicity, and an autofocus metric for the entire imaging volume was used to calibrate the wave PSF in a 2-stage manner from coarse to refined estimation. The coil sensitivities can be extracted from the shifted central region of wave PSF corrected subsampled k-space, and further used with wave PSF for wave-encoded parallel imaging (PI) reconstruction. The wave encoding gradients were integrated into the 3D TSE sequence considering eddy current reduction aspects and maintaining of the Carr-Purcell-Meiboom-Gill condition. Phantom and in vivo brain experiments were performed to evaluate the accuracy of wave PSF self-calibration and to compare the PI reconstruction performance between wave and Cartesian encoding scheme. RESULTS The self-calibrated wave PSF, estimated from different k-space undersampling patterns can robustly correct the wave encoding induced image artifacts given sufficient central autocalibration data. The self-calibrating wave-encoded PI reconstruction has demonstrated its improved performance in reduced aliasing artifacts and noise amplification in comparison to the Cartesian-encoded PI reconstruction results for 3D TSE imaging. CONCLUSION The proposed self-calibrating wave-encoded method allows robust calibration of wave PSF and coil sensitivities from the subsampled k-space, and improves the overall image quality for accelerated 3D TSE imaging.
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Affiliation(s)
- Zechen Zhou
- Philips Research North America, Cambridge, Massachusetts
| | - Chun Yuan
- Department of Radiology, University of Washington, Seattle, Washington
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91
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Wang X, Kohler F, Unterberg-Buchwald C, Lotz J, Frahm J, Uecker M. Model-based myocardial T1 mapping with sparsity constraints using single-shot inversion-recovery radial FLASH cardiovascular magnetic resonance. J Cardiovasc Magn Reson 2019; 21:60. [PMID: 31533736 PMCID: PMC6751613 DOI: 10.1186/s12968-019-0570-3] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2018] [Accepted: 07/31/2019] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND This study develops a model-based myocardial T1 mapping technique with sparsity constraints which employs a single-shot inversion-recovery (IR) radial fast low angle shot (FLASH) cardiovascular magnetic resonance (CMR) acquisition. The method should offer high resolution, accuracy, precision and reproducibility. METHODS The proposed reconstruction estimates myocardial parameter maps directly from undersampled k-space which is continuously measured by IR radial FLASH with a 4 s breathhold and retrospectively sorted based on a cardiac trigger signal. Joint sparsity constraints are imposed on the parameter maps to further improve T1 precision. Validations involved studies of an experimental phantom and 8 healthy adult subjects. RESULTS In comparison to an IR spin-echo reference method, phantom experiments with T1 values ranging from 300 to 1500 ms revealed good accuracy and precision at simulated heart rates between 40 and 100 bpm. In vivo T1 maps achieved better precision and qualitatively better preservation of image features for the proposed method than a real-time CMR approach followed by pixelwise fitting. Apart from good inter-observer reproducibility (0.6% of the mean), in vivo results confirmed good intra-subject reproducibility (1.05% of the mean for intra-scan and 1.17, 1.51% of the means for the two inter-scans, respectively) of the proposed method. CONCLUSION Model-based reconstructions with sparsity constraints allow for single-shot myocardial T1 maps with high spatial resolution, accuracy, precision and reproducibility within a 4 s breathhold. Clinical trials are warranted.
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Affiliation(s)
- Xiaoqing Wang
- Department of Diagnostic and Interventional Radiology, University Medical Center Göttingen, Robert-Koch-Str. 40, 37075 Göttingen, Germany
- DZHK (German Centre for Cardiovascular Research), partner site Göttingen, Berlin, Germany
| | - Florian Kohler
- Department of Diagnostic and Interventional Radiology, University Medical Center Göttingen, Robert-Koch-Str. 40, 37075 Göttingen, Germany
- DZHK (German Centre for Cardiovascular Research), partner site Göttingen, Berlin, Germany
| | - Christina Unterberg-Buchwald
- Department of Diagnostic and Interventional Radiology, University Medical Center Göttingen, Robert-Koch-Str. 40, 37075 Göttingen, Germany
- DZHK (German Centre for Cardiovascular Research), partner site Göttingen, Berlin, Germany
| | - Joachim Lotz
- Department of Diagnostic and Interventional Radiology, University Medical Center Göttingen, Robert-Koch-Str. 40, 37075 Göttingen, Germany
- DZHK (German Centre for Cardiovascular Research), partner site Göttingen, Berlin, Germany
| | - Jens Frahm
- DZHK (German Centre for Cardiovascular Research), partner site Göttingen, Berlin, Germany
- Biomedizinische NMR, Max-Planck-Institut für biophysikalische Chemie, Am Fassberg 11, 37077 Göttingen, Germany
| | - Martin Uecker
- Department of Diagnostic and Interventional Radiology, University Medical Center Göttingen, Robert-Koch-Str. 40, 37075 Göttingen, Germany
- DZHK (German Centre for Cardiovascular Research), partner site Göttingen, Berlin, Germany
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92
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Feng L, Wen Q, Huang C, Tong A, Liu F, Chandarana H. GRASP-Pro: imProving GRASP DCE-MRI through self-calibrating subspace-modeling and contrast phase automation. Magn Reson Med 2019; 83:94-108. [PMID: 31400028 DOI: 10.1002/mrm.27903] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2019] [Accepted: 06/25/2019] [Indexed: 12/19/2022]
Abstract
PURPOSE To propose a highly accelerated, high-resolution dynamic contrast-enhanced MRI (DCE-MRI) technique called GRASP-Pro (golden-angle radial sparse parallel imaging with imProved performance) through a joint sparsity and self-calibrating subspace constraint with automated selection of contrast phases. METHODS GRASP-Pro reconstruction enforces a combination of an explicit low-rank subspace-constraint and a temporal sparsity constraint. The temporal basis used to construct the subspace is learned from an intermediate reconstruction step using the low-resolution portion of radial k-space, which eliminates the need for generating the basis using auxiliary data or a physical signal model. A convolutional neural network was trained to generate the contrast enhancement curve in the artery, from which clinically relevant contrast phases are automatically selected for evaluation. The performance of GRASP-Pro was demonstrated for high spatiotemporal resolution DCE-MRI of the prostate and was compared against standard GRASP in terms of overall image quality, image sharpness, and residual streaks and/or noise level. RESULTS Compared to GRASP, GRASP-Pro reconstructed dynamic images with enhanced sharpness, less residual streaks and/or noise, and finer delineation of the prostate without prolonging reconstruction time. The image quality improvement reached statistical significance (P < 0.05) in all the assessment categories. The neural network successfully generated contrast enhancement curves in the artery, and corresponding peak enhancement indexes correlated well with that from the manual selection. CONCLUSION GRASP-Pro is a promising method for rapid and continuous DCE-MRI. It enables superior reconstruction performance over standard GRASP and allows reliable generation of artery enhancement curve to guide the selection of desired contrast phases for improving the efficiency of GRASP MRI workflow.
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Affiliation(s)
- Li Feng
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Qiuting Wen
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, Indiana
| | - Chenchan Huang
- Department of Radiology, New York University School of Medicine, New York, New York
| | - Angela Tong
- Department of Radiology, New York University School of Medicine, New York, New York
| | - Fang Liu
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin
| | - Hersh Chandarana
- Department of Radiology, New York University School of Medicine, New York, New York.,Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, New York, New York
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93
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Keerthivasan MB, Saranathan M, Johnson K, Fu Z, Weinkauf CC, Martin DR, Bilgin A, Altbach MI. An efficient 3D stack-of-stars turbo spin echo pulse sequence for simultaneous T2-weighted imaging and T2 mapping. Magn Reson Med 2019; 82:326-341. [PMID: 30883879 DOI: 10.1002/mrm.27737] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2018] [Revised: 02/01/2019] [Accepted: 02/21/2019] [Indexed: 01/16/2023]
Abstract
PURPOSE To design a pulse sequence for efficient 3D T2-weighted imaging and T2 mapping. METHODS A stack-of-stars turbo spin echo pulse sequence with variable refocusing flip angles and a flexible pseudorandom view ordering is proposed for simultaneous T2-weighted imaging and T2 mapping. An analytical framework is introduced for the selection of refocusing flip angles to maximize relative tissue contrast while minimizing T2 estimation errors and maintaining low specific absorption rate. Images at different echo times are generated using a subspace constrained iterative reconstruction algorithm. T2 maps are obtained by modeling the signal evolution using the extended phase graph model. The technique is evaluated using phantoms and demonstrated in vivo for brain, knee, and carotid imaging. RESULTS Numerical simulations demonstrate an improved point spread function with the proposed pseudorandom view ordering compared to golden angle view ordering. Phantom experiments show that T2 values estimated from the stack-of-stars turbo spin echo pulse sequence with variable refocusing flip angles have good concordance with spin echo reference values. In vivo results show the proposed pulse sequence can generate qualitatively comparable T2-weighted images as conventional Cartesian 3D SPACE in addition to simultaneously generating 3D T2 maps. CONCLUSION The proposed stack-of-stars turbo spin echo pulse sequence with pseudorandom view ordering and variable refocusing flip angles allows high resolution isotropic T2 mapping in clinically acceptable scan times. The optimization framework for the selection of refocusing flip angles improves T2 estimation accuracy while generating T2-weighted contrast comparable to conventional Cartesian imaging.
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Affiliation(s)
- Mahesh Bharath Keerthivasan
- Medical Imaging, University of Arizona, Tucson, Arizona.,Electrical and Computer Engineering, University of Arizona, Tucson, Arizona
| | - Manojkumar Saranathan
- Medical Imaging, University of Arizona, Tucson, Arizona.,Electrical and Computer Engineering, University of Arizona, Tucson, Arizona.,Biomedical Engineering, University of Arizona, Tucson, Arizona
| | - Kevin Johnson
- Medical Imaging, University of Arizona, Tucson, Arizona
| | - Zhiyang Fu
- Medical Imaging, University of Arizona, Tucson, Arizona.,Electrical and Computer Engineering, University of Arizona, Tucson, Arizona
| | | | | | - Ali Bilgin
- Medical Imaging, University of Arizona, Tucson, Arizona.,Electrical and Computer Engineering, University of Arizona, Tucson, Arizona.,Biomedical Engineering, University of Arizona, Tucson, Arizona
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94
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Senel LK, Kilic T, Gungor A, Kopanoglu E, Guven HE, Saritas EU, Koc A, Cukur T. Statistically Segregated k-Space Sampling for Accelerating Multiple-Acquisition MRI. IEEE TRANSACTIONS ON MEDICAL IMAGING 2019; 38:1701-1714. [PMID: 30640604 DOI: 10.1109/tmi.2019.2892378] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
A central limitation of multiple-acquisition magnetic resonance imaging (MRI) is the degradation in scan efficiency as the number of distinct datasets grows. Sparse recovery techniques can alleviate this limitation via randomly undersampled acquisitions. A frequent sampling strategy is to prescribe for each acquisition a different random pattern drawn from a common sampling density. However, naive random patterns often contain gaps or clusters across the acquisition dimension that, in turn, can degrade reconstruction quality or reduce scan efficiency. To address this problem, a statistically segregated sampling method is proposed for multiple-acquisition MRI. This method generates multiple patterns sequentially while adaptively modifying the sampling density to minimize k-space overlap across patterns. As a result, it improves incoherence across acquisitions while still maintaining similar sampling density across the radial dimension of k-space. Comprehensive simulations and in vivo results are presented for phase-cycled balanced steady-state free precession and multi-echo [Formula: see text]-weighted imaging. Segregated sampling achieves significantly improved quality in both Fourier and compressed-sensing reconstructions of multiple-acquisition datasets.
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95
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Gómez PA, Molina-Romero M, Buonincontri G, Menzel MI, Menze BH. Designing contrasts for rapid, simultaneous parameter quantification and flow visualization with quantitative transient-state imaging. Sci Rep 2019; 9:8468. [PMID: 31186480 PMCID: PMC6560213 DOI: 10.1038/s41598-019-44832-w] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2018] [Accepted: 05/22/2019] [Indexed: 02/01/2023] Open
Abstract
Magnetic resonance imaging (MRI) has evolved into an outstandingly versatile diagnostic modality, as it has the ability to non-invasively produce detailed information on a tissue's structure and function. Complementary data is normally obtained in separate measurements, either as contrast-weighted images, which are fast and simple to acquire, or as quantitative parametric maps, which offer an absolute quantification of underlying biophysical effects, such as relaxation times or flow. Here, we demonstrate how to acquire and reconstruct data in a transient-state with a dual purpose: 1 - to generate contrast-weighted images that can be adjusted to emphasise clinically relevant image biomarkers; exemplified with signal modulation according to flow to obtain angiography information, and 2 - to simultaneously infer multiple quantitative parameters with a single, highly accelerated acquisition. This is achieved by introducing three novel elements: a model that accounts for flowing blood, a method for sequence design using smooth flip angle excitation patterns that incorporates both parameter encoding and signal contrast, and the reconstruction of temporally resolved contrast-weighted images. From these images we simultaneously obtain angiography projections and multiple quantitative maps. By doing so, we increase the amount of clinically relevant data without adding measurement time, creating new dimensions for biomarker exploration and adding value to MR examinations for patients and clinicians alike.
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96
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Wang F, Dong Z, Reese TG, Bilgic B, Manhard MK, Chen J, Polimeni JR, Wald LL, Setsompop K. Echo planar time-resolved imaging (EPTI). Magn Reson Med 2019; 81:3599-3615. [PMID: 30714198 PMCID: PMC6435385 DOI: 10.1002/mrm.27673] [Citation(s) in RCA: 62] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2018] [Revised: 12/06/2018] [Accepted: 01/06/2019] [Indexed: 01/15/2023]
Abstract
PURPOSE To develop an efficient distortion- and blurring-free multi-shot EPI technique for time-resolved multiple-contrast and/or quantitative imaging. METHODS EPI is a commonly used sequence but suffers from geometric distortions and blurring. Here, we introduce a new multi-shot EPI technique termed echo planar time-resolved imaging (EPTI), which has the ability to rapidly acquire distortion- and blurring-free multi-contrast data set. The EPTI approach performs encoding in ky -t space and uses a new highly accelerated spatio-temporal CAIPI sampling trajectory to take advantage of signal correlation along these dimensions. Through this acquisition and a B0 -informed parallel imaging reconstruction, hundreds of "time-resolved" distortion- and blurring-free images at different TEs across the EPI readout window can be created at sub-millisecond temporal increments using a small number of EPTI shots. Moreover, a method for self-estimation and correction of shot-to-shot B0 variations was developed. Simultaneous multi-slice acquisition was also incorporated to further improve the acquisition efficiency. RESULTS We evaluated EPTI under varying simulated acceleration factors, B0 -inhomogeneity, and shot-to-shot B0 variations to demonstrate its ability to provide distortion- and blurring-free images at multiple TEs. Two variants of EPTI were demonstrated in vivo at 3T: (1) a combined gradient- and spin-echo EPTI for quantitative mapping of T2 , T2* , proton density, and susceptibility at 1.1 × 1.1 × 3 mm3 whole-brain in 28 s (0.8 s/slice), and (2) a gradient-echo EPTI, for multi-echo and quantitative T2* fMRI at 2 × 2 × 3 mm3 whole-brain at a 3.3 s temporal resolution. CONCLUSION EPTI is a new approach for multi-contrast and/or quantitative imaging that can provide fast acquisition of distortion- and blurring-free images at multiple TEs.
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Affiliation(s)
- Fuyixue Wang
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
- Harvard-MIT Health Sciences and Technology, MIT, Cambridge, Massachusetts
| | - Zijing Dong
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
- Department of Electrical Engineering and Computer Science, MIT, Cambridge, Massachusetts
| | - Timothy G. Reese
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
| | - Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
- Department of Radiology, Harvard Medical School, Boston, Massachusetts
| | - Mary Katherine Manhard
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
| | - Jingyuan Chen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
| | - Jonathan R. Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
- Harvard-MIT Health Sciences and Technology, MIT, Cambridge, Massachusetts
- Department of Radiology, Harvard Medical School, Boston, Massachusetts
| | - Lawrence L. Wald
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
- Harvard-MIT Health Sciences and Technology, MIT, Cambridge, Massachusetts
- Department of Radiology, Harvard Medical School, Boston, Massachusetts
| | - Kawin Setsompop
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts
- Harvard-MIT Health Sciences and Technology, MIT, Cambridge, Massachusetts
- Department of Radiology, Harvard Medical School, Boston, Massachusetts
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97
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Bustin A, Lima da Cruz G, Jaubert O, Lopez K, Botnar RM, Prieto C. High-dimensionality undersampled patch-based reconstruction (HD-PROST) for accelerated multi-contrast MRI. Magn Reson Med 2019; 81:3705-3719. [PMID: 30834594 PMCID: PMC6646908 DOI: 10.1002/mrm.27694] [Citation(s) in RCA: 67] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2018] [Revised: 01/23/2019] [Accepted: 01/23/2019] [Indexed: 12/14/2022]
Abstract
PURPOSE To develop a new high-dimensionality undersampled patch-based reconstruction (HD-PROST) for highly accelerated 2D and 3D multi-contrast MRI. METHODS HD-PROST jointly reconstructs multi-contrast MR images by exploiting the highly redundant information, on a local and non-local scale, and the strong correlation shared between the multiple contrast images. This is achieved by enforcing multi-dimensional low-rank in the undersampled images. 2D magnetic resonance fingerprinting (MRF) phantom and in vivo brain acquisitions were performed to evaluate the performance of HD-PROST for highly accelerated simultaneous T1 and T2 mapping. Additional in vivo experiments for reconstructing multiple undersampled 3D magnetization transfer (MT)-weighted images were conducted to illustrate the impact of HD-PROST for high-resolution multi-contrast 3D imaging. RESULTS In the 2D MRF phantom study, HD-PROST provided accurate and precise estimation of the T1 and T2 values in comparison to gold standard spin echo acquisitions. HD-PROST achieved good quality maps for the in vivo 2D MRF experiments in comparison to conventional low-rank inversion reconstruction. T1 and T2 values of white matter and gray matter were in good agreement with those reported in the literature for MRF acquisitions with reduced number of time point images (500 time point images, ~2.5 s scan time). For in vivo MT-weighted 3D acquisitions (6 different contrasts), HD-PROST achieved similar image quality than the fully sampled reference image for an undersampling factor of 6.5-fold. CONCLUSION HD-PROST enables multi-contrast 2D and 3D MR images in a short acquisition time without compromising image quality. Ultimately, this technique may increase the potential of conventional parameter mapping.
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Affiliation(s)
- Aurélien Bustin
- Department of Biomedical Engineering, School of Imaging Sciences & Biomedical EngineeringKing’s College London, King’s Health PartnersLondonUnited Kingdom
| | - Gastão Lima da Cruz
- Department of Biomedical Engineering, School of Imaging Sciences & Biomedical EngineeringKing’s College London, King’s Health PartnersLondonUnited Kingdom
| | - Olivier Jaubert
- Department of Biomedical Engineering, School of Imaging Sciences & Biomedical EngineeringKing’s College London, King’s Health PartnersLondonUnited Kingdom
| | - Karina Lopez
- Department of Biomedical Engineering, School of Imaging Sciences & Biomedical EngineeringKing’s College London, King’s Health PartnersLondonUnited Kingdom
| | - René M. Botnar
- Department of Biomedical Engineering, School of Imaging Sciences & Biomedical EngineeringKing’s College London, King’s Health PartnersLondonUnited Kingdom
- Escuela de IngenieríaPontificia Universidad Católica de ChileSantiagoChile
| | - Claudia Prieto
- Department of Biomedical Engineering, School of Imaging Sciences & Biomedical EngineeringKing’s College London, King’s Health PartnersLondonUnited Kingdom
- Escuela de IngenieríaPontificia Universidad Católica de ChileSantiagoChile
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98
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Tamir JI, Taviani V, Alley MT, Perkins B, Hart L, Obrien K, Wishah F, Sandberg JK, Anderson MJ, Turek JS, Willke TL, Lustig M, Vasanawala SS. Targeted rapid knee MRI exam using T 2 shuffling. J Magn Reson Imaging 2019; 49:e195-e204. [PMID: 30637847 PMCID: PMC6551292 DOI: 10.1002/jmri.26600] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2018] [Revised: 11/18/2018] [Accepted: 11/19/2018] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND MRI is commonly used to evaluate pediatric musculoskeletal pathologies, but same-day/near-term scheduling and short exams remain challenges. PURPOSE To investigate the feasibility of a targeted rapid pediatric knee MRI exam, with the goal of reducing cost and enabling same-day MRI access. STUDY TYPE A cost effectiveness study done prospectively. SUBJECTS Forty-seven pediatric patients. FIELD STRENGTH/SEQUENCE 3T. The 10-minute protocol was based on T2 Shuffling, a four-dimensional acquisition and reconstruction of images with variable T2 contrast, and a T1 2D fast spin-echo (FSE) sequence. A distributed, compressed sensing-based reconstruction was implemented on a four-node high-performance compute cluster and integrated into the clinical workflow. ASSESSMENT In an Institutional Review Board-approved study with informed consent/assent, we implemented a targeted pediatric knee MRI exam for assessing pediatric knee pain. Pediatric patients were subselected for the exam based on insurance plan and clinical indication. Over a 2-year period, 47 subjects were recruited for the study and 49 MRIs were ordered. Date and time information was recorded for MRI referral, registration, and completion. Image quality was assessed from 0 (nondiagnostic) to 5 (outstanding) by two readers, and consensus was subsequently reached. STATISTICAL TESTS A Wilcoxon rank-sum test assessed the null hypothesis that the targeted exam times compared with conventional knee exam times were unchanged. RESULTS Of the 49 cases, 20 were completed on the same day as exam referral. Median time from registration to exam completion was 18.7 minutes. Median reconstruction time for T2 Shuffling was reduced from 18.9 minutes to 95 seconds using the distributed implementation. Technical fees charged for the targeted exam were one-third that of the routine clinical knee exam. No subject had to return for additional imaging. DATA CONCLUSION The targeted knee MRI exam is feasible and reduces the imaging time, cost, and barrier to same-day MRI access for pediatric patients. LEVEL OF EVIDENCE 2 Technical Efficacy: Stage 6 J. Magn. Reson. Imaging 2019.
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Affiliation(s)
- Jonathan I. Tamir
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California, USA
| | - Valentina Taviani
- Global Applied Science Laboratory, GE Healthcare, Menlo Park, California, USA
| | - Marcus T. Alley
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Becki Perkins
- Department of Radiology, Lucile Packard Children’s Hospital, Stanford, California, USA
| | - Lori Hart
- Department of Radiology, Lucile Packard Children’s Hospital, Stanford, California, USA
| | - Kendall Obrien
- Department of Radiology, Lucile Packard Children’s Hospital, Stanford, California, USA
| | - Fidaa Wishah
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Jesse K Sandberg
- Department of Radiology, Stanford University, Stanford, California, USA
| | | | - Javier S. Turek
- Brain-Inspired Computing Lab, Intel Labs, Hillsboro, Oregon, USA
| | | | - Michael Lustig
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California, USA
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99
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Balachandrasekaran A, Mani M, Jacob M. Calibration-Free B0 Correction of EPI Data Using Structured Low Rank Matrix Recovery. IEEE TRANSACTIONS ON MEDICAL IMAGING 2019; 38:979-990. [PMID: 30334785 PMCID: PMC7840148 DOI: 10.1109/tmi.2018.2876423] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
We introduce a structured low rank algorithm for the calibration-free compensation of field inhomogeneity artifacts in echo planar imaging (EPI) MRI data. We acquire the data using two EPI readouts that differ in echo-time. Using time segmentation, we reformulate the field inhomogeneity compensation problem as the recovery of an image time series from highly undersampled Fourier measurements. The temporal profile at each pixel is modeled as a single exponential, which is exploited to fill in the missing entries. We show that the exponential behavior at each pixel, along with the spatial smoothness of the exponential parameters, can be exploited to derive a 3-D annihilation relation in the Fourier domain. This relation translates to a low rank property on a structured multi-fold Toeplitz matrix, whose entries correspond to the measured k-space samples. We introduce a fast two-step algorithm for the completion of the Toeplitz matrix from the available samples. In the first step, we estimate the null space vectors of the Toeplitz matrix using only its fully sampled rows. The null space is then used to estimate the signal subspace, which facilitates the efficient recovery of the time series of images. We finally demonstrate the proposed approach on spherical MR phantom data and human data and show that the artifacts are significantly reduced.
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Affiliation(s)
- Arvind Balachandrasekaran
- Arvind Balachandrasekaran, Mathews Jacob are with the Department of Electrical and Computer Engineering and Merry Mani is with the Department of Radiology, University of Iowa, Iowa City, IA, 52245, USA
| | - Merry Mani
- Arvind Balachandrasekaran, Mathews Jacob are with the Department of Electrical and Computer Engineering and Merry Mani is with the Department of Radiology, University of Iowa, Iowa City, IA, 52245, USA
| | - Mathews Jacob
- Arvind Balachandrasekaran, Mathews Jacob are with the Department of Electrical and Computer Engineering and Merry Mani is with the Department of Radiology, University of Iowa, Iowa City, IA, 52245, USA
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100
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Lima da Cruz G, Bustin A, Jaubert O, Schneider T, Botnar RM, Prieto C. Sparsity and locally low rank regularization for MR fingerprinting. Magn Reson Med 2019; 81:3530-3543. [PMID: 30720209 PMCID: PMC6492150 DOI: 10.1002/mrm.27665] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2018] [Revised: 12/03/2018] [Accepted: 12/29/2018] [Indexed: 12/22/2022]
Abstract
Purpose Develop a sparse and locally low rank (LLR) regularized reconstruction to accelerate MR fingerprinting (MRF). Methods Recent works have introduced low rank reconstructions to MRF, based on temporal compression operators learned from the MRF dictionary. In other MR applications, LLR regularization has been introduced to exploit temporal redundancy in local regions of the image. Here, we propose to include spatial sparsity and LLR regularization terms in the MRF reconstruction. This approach, so called SLLR‐MRF, further reduces aliasing in the time‐point images and enables higher acceleration factors. The proposed approach was evaluated in simulations, T1/T2 phantom acquisition, and in vivo brain acquisitions in 5 healthy subjects with different undersampling factors. Acceleration was also used in vivo to enable acquisitions with higher in‐plane spatial resolution in comparable scan time. Results Simulations, phantom, and in vivo results show that low rank MRF reconstructions with high acceleration factors (<875 time‐point images, 1 radial spoke per time‐point) have residual aliasing artifacts that propagate into the parametric maps. The artifacts are reduced with the proposed SLLR‐MRF resulting in considerable improvements in precision, without changes in accuracy. In vivo results show improved parametric maps for the proposed SLLR‐MRF, potentially enabling MRF acquisitions with 1 radial spoke per time‐point in approximately 2.6 s (~600 time‐point images) for 2 × 2 mm and 9.6 s (1750 time‐point images) for 1 × 1 mm in‐plane resolution. Conclusion The proposed SLLR‐MRF reconstruction further improves parametric map quality compared with low rank MRF, enabling shorter scan times and/or increased spatial resolution.
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Affiliation(s)
- Gastão Lima da Cruz
- King's College London, School of Biomedical Engineering and Imaging Sciences, London, United Kingdom
| | - Aurélien Bustin
- King's College London, School of Biomedical Engineering and Imaging Sciences, London, United Kingdom
| | - Oliver Jaubert
- King's College London, School of Biomedical Engineering and Imaging Sciences, London, United Kingdom
| | | | - René M Botnar
- King's College London, School of Biomedical Engineering and Imaging Sciences, London, United Kingdom.,Pontificia Universidad Católica de Chile, Escuela de Ingeniería, Santiago, Chile
| | - Claudia Prieto
- King's College London, School of Biomedical Engineering and Imaging Sciences, London, United Kingdom
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