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Liao C, Cao X, Iyer SS, Schauman S, Zhou Z, Yan X, Chen Q, Li Z, Wang N, Gong T, Wu Z, He H, Zhong J, Yang Y, Kerr A, Grill-Spector K, Setsompop K. High-resolution myelin-water fraction and quantitative relaxation mapping using 3D ViSTa-MR fingerprinting. Magn Reson Med 2024; 91:2278-2293. [PMID: 38156945 PMCID: PMC10997479 DOI: 10.1002/mrm.29990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 12/11/2023] [Accepted: 12/11/2023] [Indexed: 01/03/2024]
Abstract
PURPOSE This study aims to develop a high-resolution whole-brain multi-parametric quantitative MRI approach for simultaneous mapping of myelin-water fraction (MWF), T1, T2, and proton-density (PD), all within a clinically feasible scan time. METHODS We developed 3D visualization of short transverse relaxation time component (ViSTa)-MRF, which combined ViSTa technique with MR fingerprinting (MRF), to achieve high-fidelity whole-brain MWF and T1/T2/PD mapping on a clinical 3T scanner. To achieve fast acquisition and memory-efficient reconstruction, the ViSTa-MRF sequence leverages an optimized 3D tiny-golden-angle-shuffling spiral-projection acquisition and joint spatial-temporal subspace reconstruction with optimized preconditioning algorithm. With the proposed ViSTa-MRF approach, high-fidelity direct MWF mapping was achieved without a need for multicompartment fitting that could introduce bias and/or noise from additional assumptions or priors. RESULTS The in vivo results demonstrate the effectiveness of the proposed acquisition and reconstruction framework to provide fast multi-parametric mapping with high SNR and good quality. The in vivo results of 1 mm- and 0.66 mm-isotropic resolution datasets indicate that the MWF values measured by the proposed method are consistent with standard ViSTa results that are 30× slower with lower SNR. Furthermore, we applied the proposed method to enable 5-min whole-brain 1 mm-iso assessment of MWF and T1/T2/PD mappings for infant brain development and for post-mortem brain samples. CONCLUSIONS In this work, we have developed a 3D ViSTa-MRF technique that enables the acquisition of whole-brain MWF, quantitative T1, T2, and PD maps at 1 and 0.66 mm isotropic resolution in 5 and 15 min, respectively. This advancement allows for quantitative investigations of myelination changes in the brain.
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Affiliation(s)
- Congyu Liao
- Department of Radiology, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Xiaozhi Cao
- Department of Radiology, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Siddharth Srinivasan Iyer
- Department of Radiology, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Sophie Schauman
- Department of Radiology, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Zihan Zhou
- Department of Radiology, Stanford University, Stanford, CA, USA
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Xiaoqian Yan
- Department of Psychology, Stanford University, Stanford, CA, USA
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Quan Chen
- Department of Radiology, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Zhitao Li
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Nan Wang
- Department of Radiology, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Ting Gong
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Zhe Wu
- Techna Institute, University Health Network, Toronto, ON, Canada
| | - Hongjian He
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
- School of Physics, Zhejiang University, Hangzhou, Zhejiang, China
| | - Jianhui Zhong
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
- Department of Imaging Sciences, University of Rochester, Rochester, NY, USA
| | - Yang Yang
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Adam Kerr
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
- Stanford Center for Cognitive and Neurobiological Imaging, Stanford University, Stanford, CA, USA
| | | | - Kawin Setsompop
- Department of Radiology, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
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Liao C, Cao X, Srinivasan Iyer S, Schauman S, Zhou Z, Yan X, Chen Q, Li Z, Wang N, Gong T, Wu Z, He H, Zhong J, Yang Y, Kerr A, Grill-Spector K, Setsompop K. High-resolution myelin-water fraction and quantitative relaxation mapping using 3D ViSTa-MR fingerprinting. ARXIV 2023:arXiv:2312.13523v1. [PMID: 38196746 PMCID: PMC10775347] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 01/11/2024]
Abstract
Purpose This study aims to develop a high-resolution whole-brain multi-parametric quantitative MRI approach for simultaneous mapping of myelin-water fraction (MWF), T1, T2, and proton-density (PD), all within a clinically feasible scan time. Methods We developed 3D ViSTa-MRF, which combined Visualization of Short Transverse relaxation time component (ViSTa) technique with MR Fingerprinting (MRF), to achieve high-fidelity whole-brain MWF and T1/T2/PD mapping on a clinical 3T scanner. To achieve fast acquisition and memory-efficient reconstruction, the ViSTa-MRF sequence leverages an optimized 3D tiny-golden-angle-shuffling spiral-projection acquisition and joint spatial-temporal subspace reconstruction with optimized preconditioning algorithm. With the proposed ViSTa-MRF approach, high-fidelity direct MWF mapping was achieved without a need for multi-compartment fitting that could introduce bias and/or noise from additional assumptions or priors. Results The in-vivo results demonstrate the effectiveness of the proposed acquisition and reconstruction framework to provide fast multi-parametric mapping with high SNR and good quality. The in-vivo results of 1mm- and 0.66mm-iso datasets indicate that the MWF values measured by the proposed method are consistent with standard ViSTa results that are 30x slower with lower SNR. Furthermore, we applied the proposed method to enable 5-minute whole-brain 1mm-iso assessment of MWF and T1/T2/PD mappings for infant brain development and for post-mortem brain samples. Conclusions In this work, we have developed a 3D ViSTa-MRF technique that enables the acquisition of whole-brain MWF, quantitative T1, T2, and PD maps at 1mm and 0.66mm isotropic resolution in 5 and 15 minutes, respectively. This advancement allows for quantitative investigations of myelination changes in the brain.
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Affiliation(s)
- Congyu Liao
- Department of Radiology, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Xiaozhi Cao
- Department of Radiology, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Siddharth Srinivasan Iyer
- Department of Radiology, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Sophie Schauman
- Department of Radiology, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Zihan Zhou
- Department of Radiology, Stanford University, Stanford, CA, USA
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Xiaoqian Yan
- Department of Psychology, Stanford University, Stanford, CA, USA
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Quan Chen
- Department of Radiology, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Zhitao Li
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Nan Wang
- Department of Radiology, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Ting Gong
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Zhe Wu
- Techna Institute, University Health Network, Toronto, ON, Canada
| | - Hongjian He
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
- School of Physics, Zhejiang University, Hangzhou, Zhejiang, China
| | - Jianhui Zhong
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
- Department of Imaging Sciences, University of Rochester, Rochester, NY, USA
| | - Yang Yang
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| | - Adam Kerr
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
- Stanford Center for Cognitive and Neurobiological Imaging, Stanford University, Stanford, CA, USA
| | | | - Kawin Setsompop
- Department of Radiology, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
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Daval-Frérot G, Massire A, Mailhe B, Nadar M, Vignaud A, Ciuciu P. Iterative static field map estimation for off-resonance correction in non-Cartesian susceptibility weighted imaging. Magn Reson Med 2022; 88:1592-1607. [PMID: 35735217 PMCID: PMC9545844 DOI: 10.1002/mrm.29297] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Revised: 04/01/2022] [Accepted: 04/19/2022] [Indexed: 11/21/2022]
Abstract
Purpose Patient‐induced inhomogeneities in the magnetic field cause distortions and blurring during acquisitions with long readouts such as in susceptibility‐weighted imaging (SWI). Most correction methods require collecting an additional ΔB0 field map to remove these artifacts. Theory The static ΔB0 field map can be approximated with an acceptable error directly from a single echo acquisition in SWI. The main component of the observed phase is linearly related to ΔB0 and the echo time (TE), and the relative impact of non‐ ΔB0 terms becomes insignificant with TE >20 ms at 3 T for a well‐tuned system. Methods The main step is to combine and unfold the multi‐channel phase maps wrapped many times, and several competing algorithms are compared for this purpose. Four in vivo brain data sets collected using the recently proposed 3D spreading projection algorithm for rapid k‐space sampling (SPARKLING) readouts are used to assess the proposed method. Results The estimated 3D field maps generated with a 0.6 mm isotropic spatial resolution provide overall similar off‐resonance corrections compared to reference corrections based on an external ΔB0 acquisitions, and even improved for 2 of 4 individuals. Although a small estimation error is expected, no aftermath was observed in the proposed corrections, whereas degradations were observed in the references. Conclusion A static ΔB0 field map estimation method was proposed to take advantage of acquisitions with long echo times, and outperformed the reference technique based on an external field map. The difference can be attributed to an inherent robustness to mismatches between volumes and external ΔB0 maps, and diverse other sources investigated. Click here for author‐reader discussions
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Affiliation(s)
- Guillaume Daval-Frérot
- Siemens Healthcare SAS, Saint-Denis, France.,CEA, NeuroSpin, CNRS, Université Paris-Saclay, Gif-sur-Yvette, France.,Inria, Palaiseau, France
| | | | - Boris Mailhe
- Siemens Healthineers, Digital Technology & Innovation, Princeton, New Jersey, USA
| | - Mariappan Nadar
- Siemens Healthineers, Digital Technology & Innovation, Princeton, New Jersey, USA
| | - Alexandre Vignaud
- CEA, NeuroSpin, CNRS, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Philippe Ciuciu
- CEA, NeuroSpin, CNRS, Université Paris-Saclay, Gif-sur-Yvette, France.,Inria, Palaiseau, France
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Cao X, Liao C, Iyer SS, Wang Z, Zhou Z, Dai E, Liberman G, Dong Z, Gong T, He H, Zhong J, Bilgic B, Setsompop K. Optimized multi-axis spiral projection MR fingerprinting with subspace reconstruction for rapid whole-brain high-isotropic-resolution quantitative imaging. Magn Reson Med 2022; 88:133-150. [PMID: 35199877 DOI: 10.1002/mrm.29194] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Revised: 12/16/2021] [Accepted: 01/21/2022] [Indexed: 11/07/2022]
Abstract
PURPOSE To improve image quality and accelerate the acquisition of 3D MR fingerprinting (MRF). METHODS Building on the multi-axis spiral-projection MRF technique, a subspace reconstruction with locally low-rank constraint and a modified spiral-projection spatiotemporal encoding scheme called tiny golden-angle shuffling were implemented for rapid whole-brain high-resolution quantitative mapping. Reconstruction parameters such as the locally low-rank regularization parameter and the subspace rank were tuned using retrospective in vivo data and simulated examinations. B0 inhomogeneity correction using multifrequency interpolation was incorporated into the subspace reconstruction to further improve the image quality by mitigating blurring caused by off-resonance effect. RESULTS The proposed MRF acquisition and reconstruction framework yields high-quality 1-mm isotropic whole-brain quantitative maps in 2 min at better quality compared with 6-min acquisitions of prior approaches. The proposed method was validated to not induce bias in T1 and T2 mapping. High-quality whole-brain MRF data were also obtained at 0.66-mm isotropic resolution in 4 min using the proposed technique, where the increased resolution was shown to improve visualization of subtle brain structures. CONCLUSIONS The proposed tiny golden-angle shuffling, MRF with optimized spiral-projection trajectory and subspace reconstruction enables high-resolution quantitative mapping in ultrafast acquisition time.
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Affiliation(s)
- Xiaozhi Cao
- Department of Radiology, Stanford University, Stanford, California, USA.,Department of Electrical Engineering, Stanford University, Stanford, California, USA
| | - Congyu Liao
- Department of Radiology, Stanford University, Stanford, California, USA.,Department of Electrical Engineering, Stanford University, Stanford, California, USA
| | - Siddharth Srinivasan Iyer
- Department of Radiology, Stanford University, Stanford, California, USA.,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
| | - Zhixing Wang
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
| | - Zihan Zhou
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, China
| | - Erpeng Dai
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Gilad Liberman
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Zijing Dong
- 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
| | - Ting Gong
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, China
| | - Hongjian He
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, China
| | - Jianhui Zhong
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, 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, Cambridge, Massachusetts, USA.,Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Kawin Setsompop
- Department of Radiology, Stanford University, Stanford, California, USA.,Department of Electrical Engineering, Stanford University, Stanford, California, USA
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Feasibility study of 2D Dixon-Magnetic Resonance Fingerprinting (MRF) of breast cancer. Eur J Radiol Open 2022; 9:100453. [DOI: 10.1016/j.ejro.2022.100453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2022] [Revised: 10/31/2022] [Accepted: 11/05/2022] [Indexed: 11/17/2022] Open
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Coronado R, Cruz G, Castillo-Passi C, Tejos C, Uribe S, Prieto C, Irarrazaval P. A Spatial Off-Resonance Correction in Spirals for Magnetic Resonance Fingerprinting. IEEE TRANSACTIONS ON MEDICAL IMAGING 2021; 40:3832-3842. [PMID: 34310296 DOI: 10.1109/tmi.2021.3100293] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
In MR Fingerprinting (MRF), balanced Steady-State Free Precession (bSSFP) has advantages over unbalanced SSFP because it retains the spin history achieving a higher signal-to-noise ratio (SNR) and scan efficiency. However, bSSFP-MRF is not frequently used because it is sensitive to off-resonance, producing artifacts and blurring, and affecting the parametric map quality. Here we propose a novel Spatial Off-resonance Correction (SOC) approach for reducing these artifacts in bSSFP-MRF with spiral trajectories. SOC-MRF uses each pixel's Point Spread Function to create system matrices that encode both off-resonance and gridding effects. We iteratively compute the inverse of these matrices to reduce the artifacts. We evaluated the proposed method using brain simulations and actual MRF acquisitions of a standardized T1/T2 phantom and five healthy subjects. The results show that the off-resonance distortions in T1/T2 maps were considerably reduced using SOC-MRF. For T2, the Normalized Root Mean Square Error (NRMSE) was reduced from 17.3 to 8.3% (simulations) and from 35.1 to 14.9% (phantom). For T1, the NRMS was reduced from 14.7 to 7.7% (simulations) and from 17.7 to 6.7% (phantom). For in-vivo, the mean and standard deviation in different ROI in white and gray matter were significantly improved. For example, SOC-MRF estimated an average T2 for white matter of 77ms (the ground truth was 74ms) versus 50 ms of MRF. For the same example the standard deviation was reduced from 18 ms to 6ms. The corrections achieved with the proposed SOC-MRF may expand the potential applications of bSSFP-MRF, taking advantage of its better SNR property.
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Wang L, Hong Z. Multi-Dimensional Spiral CT Scan Assisted Recurrence Monitoring After Esophageal Cancer Surgery. JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS 2021. [DOI: 10.1166/jmihi.2021.3698] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
Esophageal cancer is a kind of malignant tumor, which is more common in clinic, and its etiology is more complicated. Many patients are in the middle and late stage when they are found. Patients with esophageal cancer are accompanied by dysphagia, which leads to malnutrition, which
has a serious impact on the normal life of the patients. In the results of this paper, the coincidence rate of the observation group was 95.00%, the missed diagnosis rate was 5.00%, the misdiagnosis rate was 0, the diagnosis time was (12.68 ± 2.09)% in the min, control group, the coincidence
rate was 50.005%, the missed diagnosis rate was 30.005%, the misdiagnosis rate was 20.00, and the diagnosis time was 19.55 ±2.48 min, (P < 0.05). Therefore, CT examination has more advantages in the diagnosis of patients with esophageal cancer to ensure that patients receive
treatment in time. It can improve the cure probability. Clinically, if patients feel discomfort in the esophagus, medical staff usually carry out X-ray examination to grasp the patient’s condition and etiology. Therefore, X-ray examination is widely used in clinic and is the main diagnostic
method of esophageal cancer. Therefore, the application of CT in the diagnosis of esophageal cancer can not only improve the diagnostic accuracy, but also reduce the examination time, and has the value of application and promotion in the clinical diagnosis of esophageal cancer.
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Affiliation(s)
- Lei Wang
- Department of Cardiothoracic Surgery, Tongde Hospital of Zhejiang Province, Hangzhou Zhejiang, 310012, China
| | - Zhipeng Hong
- Department of Thoracic Surgery, The First Affiliated Hospital of Kunming Medical University, Kunming Yunnan, 650032, China
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McGivney DF, Boyacioğlu R, Jiang Y, Poorman ME, Seiberlich N, Gulani V, Keenan KE, Griswold MA, Ma D. Magnetic resonance fingerprinting review part 2: Technique and directions. J Magn Reson Imaging 2020; 51:993-1007. [PMID: 31347226 PMCID: PMC6980890 DOI: 10.1002/jmri.26877] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2019] [Revised: 07/05/2019] [Accepted: 07/05/2019] [Indexed: 12/12/2022] Open
Abstract
Magnetic resonance fingerprinting (MRF) is a general framework to quantify multiple MR-sensitive tissue properties with a single acquisition. There have been numerous advances in MRF in the years since its inception. In this work we highlight some of the recent technical developments in MRF, focusing on sequence optimization, modifications for reconstruction and pattern matching, new methods for partial volume analysis, and applications of machine and deep learning. Level of Evidence: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:993-1007.
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Affiliation(s)
- Debra F. McGivney
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA
| | - Rasim Boyacioğlu
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA
| | - Yun Jiang
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Megan E. Poorman
- Department of Physics, University of Colorado Boulder, Boulder, Colorado, USA
- Physical Measurement Laboratory, National Institute of Standards and Technology, Boulder, Colorado, USA
| | - Nicole Seiberlich
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Vikas Gulani
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Kathryn E. Keenan
- Physical Measurement Laboratory, National Institute of Standards and Technology, Boulder, Colorado, USA
| | - Mark A. Griswold
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA
| | - Dan Ma
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA
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Nolte T, Gross‐Weege N, Doneva M, Koken P, Elevelt A, Truhn D, Kuhl C, Schulz V. Spiral blurring correction with water–fat separation for magnetic resonance fingerprinting in the breast. Magn Reson Med 2019; 83:1192-1207. [DOI: 10.1002/mrm.27994] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2019] [Revised: 08/23/2019] [Accepted: 08/23/2019] [Indexed: 12/12/2022]
Affiliation(s)
- Teresa Nolte
- Physics of Molecular Imaging Systems Experimental Molecular Imaging RWTH Aachen University Aachen Germany
| | - Nicolas Gross‐Weege
- Physics of Molecular Imaging Systems Experimental Molecular Imaging RWTH Aachen University Aachen Germany
| | - Mariya Doneva
- Tomographic Imaging Systems Philips Research Europe Hamburg Germany
| | - Peter Koken
- Tomographic Imaging Systems Philips Research Europe Hamburg Germany
| | - Aaldert Elevelt
- Oncology Solutions Philips Research Europe Eindhoven The Netherlands
| | - Daniel Truhn
- Clinic for Diagnostic and Interventional Radiology University Hospital Aachen Aachen Germany
| | - Christiane Kuhl
- Clinic for Diagnostic and Interventional Radiology University Hospital Aachen Aachen Germany
| | - Volkmar Schulz
- Physics of Molecular Imaging Systems Experimental Molecular Imaging RWTH Aachen University Aachen Germany
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MR fingerprinting with simultaneous T 1, T 2, and fat signal fraction estimation with integrated B 0 correction reduces bias in water T 1 and T 2 estimates. Magn Reson Imaging 2019; 60:7-19. [PMID: 30910696 DOI: 10.1016/j.mri.2019.03.017] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Revised: 03/15/2019] [Accepted: 03/19/2019] [Indexed: 12/26/2022]
Abstract
PURPOSE MR fingerprinting (MRF) sequences permit efficient T1 and T2 estimation in cranial and extracranial regions, but these areas may include substantial fat signals that bias T1 and T2 estimates. MRI fat signal fraction estimation is also a topic of active research in itself, but may be complicated by B0 heterogeneity and blurring during spiral k-space acquisitions, which are commonly used for MRF. An MRF method is proposed that separates fat and water signals, estimates water T1 and T2, and accounts for B0 effects with spiral blurring correction, in a single sequence. THEORY AND METHODS A k-space-based fat-water separation method is further extended to unbalanced steady-state free precession MRF with swept echo time. Repeated application of this k-space fat-water separation to demodulated forms of the measured data allows a B0 map and correction to be approximated. The method is compared with MRF without fat separation across a broad range of fat signal fractions (FSFs), water T1s and T2s, and under heterogeneous static fields in simulations, phantoms, and in vivo. RESULTS The proposed method's FSF estimates had a concordance correlation coefficient of 0.990 with conventional measurements, and reduced biases in the T1 and T2 estimates due to fat signal relative to other MRF sequences by several hundred ms. The B0 correction improved the FSF, T1, and T2 estimation compared to those estimates without correction. CONCLUSION The proposed method improves MRF water T1 and T2 estimation in the presence of fat and provides accurate FSF estimation with inline B0 correction.
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11
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Cencini M, Biagi L, Kaggie JD, Schulte RF, Tosetti M, Buonincontri G. Magnetic resonance fingerprinting with dictionary-based fat and water separation (DBFW MRF): A multi-component approach. Magn Reson Med 2018; 81:3032-3045. [PMID: 30578569 PMCID: PMC6590362 DOI: 10.1002/mrm.27628] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2018] [Revised: 10/04/2018] [Accepted: 11/14/2018] [Indexed: 12/20/2022]
Abstract
Purpose To obtain a fast and robust fat‐water separation with simultaneous estimation of water T1, fat T1, and fat fraction maps. Methods We modified an MR fingerprinting (MRF) framework to use a single dictionary combination of a water and fat dictionary. A variable TE acquisition pattern with maximum TE = 4.8 ms was used to increase the fat–water separability. Radiofrequency (RF) spoiling was used to reduce the size of the dictionary by reducing T2 sensitivity. The technique was compared both in vitro and in vivo to an MRF method that incorporated 3‐point Dixon (DIXON MRF), as well as Cartesian IDEAL with different acquisition parameters. Results The proposed dictionary‐based fat–water separation technique (DBFW MRF) successfully provided fat fraction, water, and fat T1, B0, and B1+ maps both in vitro and in vivo. The fat fraction and water T1 values obtained with DBFW MRF show excellent agreement with DIXON MRF as well as with the reference values obtained using a Cartesian IDEAL with a long TR (concordance correlation coefficient: 0.97/0.99 for fat fraction–water T1). Whereas fat fraction values with Cartesian IDEAL were degraded in the presence of T1 saturation, MRF methods successfully estimated and accounted for T1 in the fat fraction estimates. Conclusion The DBFW MRF technique can successfully provide T1 and fat fraction quantification in under 20 s per slice, intrinsically correcting T1 biases typical of fast Dixon techniques. These features could improve the diagnostic quality and use of images in presence of fat.
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Affiliation(s)
- Matteo Cencini
- Department of Physics, University of Pisa, Pisa, Italy.,IMAGO7 Foundation, Pisa, Italy
| | - Laura Biagi
- IMAGO7 Foundation, Pisa, Italy.,IRCCS Stella Maris Scientific Institute, Pisa, Italy
| | - Joshua D Kaggie
- Department of Radiology, University of Cambridge, Cambridge, United Kingdom
| | | | - Michela Tosetti
- IMAGO7 Foundation, Pisa, Italy.,IRCCS Stella Maris Scientific Institute, Pisa, Italy
| | - Guido Buonincontri
- IMAGO7 Foundation, Pisa, Italy.,Istituto Nazionale di Fisica Nucleare (INFN), Pisa, Italy
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Chen Y, Panda A, Pahwa S, Hamilton JI, Dastmalchian S, McGivney DF, Ma D, Batesole J, Seiberlich N, Griswold MA, Plecha D, Gulani V. Three-dimensional MR Fingerprinting for Quantitative Breast Imaging. Radiology 2018; 290:33-40. [PMID: 30375925 DOI: 10.1148/radiol.2018180836] [Citation(s) in RCA: 51] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Purpose To develop a fast three-dimensional method for simultaneous T1 and T2 quantification for breast imaging by using MR fingerprinting. Materials and Methods In this prospective study, variable flip angles and magnetization preparation modules were applied to acquire MR fingerprinting data for each partition of a three-dimensional data set. A fast postprocessing method was implemented by using singular value decomposition. The proposed technique was first validated in phantoms and then applied to 15 healthy female participants (mean age, 24.2 years ± 5.1 [standard deviation]; range, 18-35 years) and 14 female participants with breast cancer (mean age, 55.4 years ± 8.8; range, 39-66 years) between March 2016 and April 2018. The sensitivity of the method to B1 field inhomogeneity was also evaluated by using the Bloch-Siegert method. Results Phantom results showed that accurate and volumetric T1 and T2 quantification was achieved by using the proposed technique. The acquisition time for three-dimensional quantitative maps with a spatial resolution of 1.6 × 1.6 × 3 mm3 was approximately 6 minutes. For healthy participants, averaged T1 and T2 relaxation times for fibroglandular tissues at 3.0 T were 1256 msec ± 171 and 46 msec ± 7, respectively. Compared with normal breast tissues, higher T2 relaxation time (68 msec ± 13) was observed in invasive ductal carcinoma (P < .001), whereas no statistical difference was found in T1 relaxation time (1183 msec ± 256; P = .37). Conclusion A method was developed for breast imaging by using the MR fingerprinting technique, which allows simultaneous and volumetric quantification of T1 and T2 relaxation times for breast tissues. © RSNA, 2018 Online supplemental material is available for this article.
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Affiliation(s)
- Yong Chen
- From the Departments of Radiology (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., N.S., M.A.G., D.P., V.G.) and Biomedical Engineering (J.I.H., N.S., M.A.G., V.G.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106; and Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., M.A.G., D.P., V.G.)
| | - Ananya Panda
- From the Departments of Radiology (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., N.S., M.A.G., D.P., V.G.) and Biomedical Engineering (J.I.H., N.S., M.A.G., V.G.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106; and Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., M.A.G., D.P., V.G.)
| | - Shivani Pahwa
- From the Departments of Radiology (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., N.S., M.A.G., D.P., V.G.) and Biomedical Engineering (J.I.H., N.S., M.A.G., V.G.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106; and Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., M.A.G., D.P., V.G.)
| | - Jesse I Hamilton
- From the Departments of Radiology (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., N.S., M.A.G., D.P., V.G.) and Biomedical Engineering (J.I.H., N.S., M.A.G., V.G.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106; and Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., M.A.G., D.P., V.G.)
| | - Sara Dastmalchian
- From the Departments of Radiology (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., N.S., M.A.G., D.P., V.G.) and Biomedical Engineering (J.I.H., N.S., M.A.G., V.G.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106; and Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., M.A.G., D.P., V.G.)
| | - Debra F McGivney
- From the Departments of Radiology (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., N.S., M.A.G., D.P., V.G.) and Biomedical Engineering (J.I.H., N.S., M.A.G., V.G.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106; and Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., M.A.G., D.P., V.G.)
| | - Dan Ma
- From the Departments of Radiology (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., N.S., M.A.G., D.P., V.G.) and Biomedical Engineering (J.I.H., N.S., M.A.G., V.G.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106; and Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., M.A.G., D.P., V.G.)
| | - Joshua Batesole
- From the Departments of Radiology (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., N.S., M.A.G., D.P., V.G.) and Biomedical Engineering (J.I.H., N.S., M.A.G., V.G.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106; and Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., M.A.G., D.P., V.G.)
| | - Nicole Seiberlich
- From the Departments of Radiology (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., N.S., M.A.G., D.P., V.G.) and Biomedical Engineering (J.I.H., N.S., M.A.G., V.G.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106; and Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., M.A.G., D.P., V.G.)
| | - Mark A Griswold
- From the Departments of Radiology (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., N.S., M.A.G., D.P., V.G.) and Biomedical Engineering (J.I.H., N.S., M.A.G., V.G.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106; and Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., M.A.G., D.P., V.G.)
| | - Donna Plecha
- From the Departments of Radiology (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., N.S., M.A.G., D.P., V.G.) and Biomedical Engineering (J.I.H., N.S., M.A.G., V.G.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106; and Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., M.A.G., D.P., V.G.)
| | - Vikas Gulani
- From the Departments of Radiology (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., N.S., M.A.G., D.P., V.G.) and Biomedical Engineering (J.I.H., N.S., M.A.G., V.G.), Case Western Reserve University, 11100 Euclid Ave, Cleveland, OH 44106; and Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio (Y.C., A.P., S.P., S.D., D.F.M., D.M., J.B., M.A.G., D.P., V.G.)
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Körzdörfer G, Jiang Y, Speier P, Pang J, Ma D, Pfeuffer J, Hensel B, Gulani V, Griswold M, Nittka M. Magnetic resonance field fingerprinting. Magn Reson Med 2018; 81:2347-2359. [PMID: 30320925 DOI: 10.1002/mrm.27558] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2018] [Revised: 09/12/2018] [Accepted: 09/14/2018] [Indexed: 12/17/2022]
Abstract
PURPOSE To develop and evaluate the magnetic resonance field fingerprinting method that simultaneously generates T1 , T2 , B0 , and B 1 + maps from a single continuous measurement. METHODS An encoding pattern was designed to integrate true fast imaging with steady-state precession (TrueFISP), fast imaging with steady-state precession (FISP), and fast low-angle shot (FLASH) sequence segments with varying flip angles, radio frequency (RF) phases, TEs, and gradient moments in a continuous acquisition. A multistep matching process was introduced that includes steps for integrated spiral deblurring and the correction of intravoxel phase dispersion. The method was evaluated in phantoms as well as in vivo studies in brain and lower abdomen. RESULTS Simultaneous measurement of T1 , T2 , B0 , and B 1 + is achieved with T1 and T2 subsequently being less afflicted by B0 and B 1 + variations. Phantom results demonstrate the stability of generated parameter maps. Higher undersampling factors and spatial resolution can be achieved with the proposed method as compared with solely FISP-based magnetic resonance fingerprinting. High-resolution B0 maps can potentially be further used as diagnostic information. CONCLUSION The proposed magnetic resonance field fingerprinting method can estimate T1 , T2 , B0 , and B 1 + maps accurately in phantoms, in the brain, and in the lower abdomen.
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Affiliation(s)
- Gregor Körzdörfer
- Siemens Healthcare GmbH, Erlangen, Germany.,Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Yun Jiang
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio
| | | | - Jianing Pang
- Siemens Medical Solutions USA, Chicago, Illinois
| | - Dan Ma
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio
| | | | - Bernhard Hensel
- Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Vikas Gulani
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio.,Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio
| | - Mark Griswold
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio.,Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio
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