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Liu H, van der Heide O, Versteeg E, Froeling M, Fuderer M, Xu F, van den Berg CAT, Sbrizzi A. A three-dimensional Magnetic Resonance Spin Tomography in Time-domain protocol for high-resolution multiparametric quantitative magnetic resonance imaging. NMR IN BIOMEDICINE 2024; 37:e5050. [PMID: 37857335 DOI: 10.1002/nbm.5050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 08/04/2023] [Accepted: 09/11/2023] [Indexed: 10/21/2023]
Abstract
Magnetic Resonance Spin TomogrAphy in Time-domain (MR-STAT) is a multiparametric quantitative MR framework, which allows for simultaneously acquiring quantitative tissue parameters such as T1, T2, and proton density from one single short scan. A typical two-dimensional (2D) MR-STAT acquisition uses a gradient-spoiled, gradient-echo sequence with a slowly varying RF flip-angle train and Cartesian readouts, and the quantitative tissue maps are reconstructed by an iterative, model-based optimization algorithm. In this work, we design a three-dimensional (3D) MR-STAT framework based on previous 2D work, in order to achieve better image signal-to-noise ratio, higher though-plane resolution, and better tissue characterization. Specifically, we design a 7-min, high-resolution 3D MR-STAT sequence, and the corresponding two-step reconstruction algorithm for the large-scale dataset. To reduce the long acquisition time, Cartesian undersampling strategies such as SENSE are adopted in our transient-state quantitative framework. To reduce the computational burden, a data-splitting scheme is designed for decoupling the 3D reconstruction problem into independent 2D reconstructions. The proposed 3D framework is validated by numerical simulations, phantom experiments, and in vivo experiments. High-quality knee quantitative maps with 0.8 × 0.8 × 1.5 mm3 resolution and bilateral lower leg maps with 1.6 mm isotropic resolution can be acquired using the proposed 7-min acquisition sequence and the 3-min-per-slice decoupled reconstruction algorithm. The proposed 3D MR-STAT framework could have wide clinical applications in the future.
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Affiliation(s)
- Hongyan Liu
- Computational Imaging Group for MRI Therapy & Diagnostics, Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Oscar van der Heide
- Computational Imaging Group for MRI Therapy & Diagnostics, Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Edwin Versteeg
- Computational Imaging Group for MRI Therapy & Diagnostics, Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Martijn Froeling
- Department of Radiology, Imaging Division, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Miha Fuderer
- Computational Imaging Group for MRI Therapy & Diagnostics, Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Fei Xu
- Computational Imaging Group for MRI Therapy & Diagnostics, Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Cornelis A T van den Berg
- Computational Imaging Group for MRI Therapy & Diagnostics, Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Alessandro Sbrizzi
- Computational Imaging Group for MRI Therapy & Diagnostics, Department of Radiotherapy, University Medical Center Utrecht, Utrecht, The Netherlands
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2
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Cabini RF, Barzaghi L, Cicolari D, Arosio P, Carrazza S, Figini S, Filibian M, Gazzano A, Krause R, Mariani M, Peviani M, Pichiecchio A, Pizzagalli DU, Lascialfari A. Fast deep learning reconstruction techniques for preclinical magnetic resonance fingerprinting. NMR IN BIOMEDICINE 2024; 37:e5028. [PMID: 37669779 DOI: 10.1002/nbm.5028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 07/05/2023] [Accepted: 07/27/2023] [Indexed: 09/07/2023]
Abstract
We propose a deep learning (DL) model and a hyperparameter optimization strategy to reconstruct T1 and T2 maps acquired with the magnetic resonance fingerprinting (MRF) methodology. We applied two different MRF sequence routines to acquire images of ex vivo rat brain phantoms using a 7-T preclinical scanner. Subsequently, the DL model was trained using experimental data, completely excluding the use of any theoretical MRI signal simulator. The best combination of the DL parameters was implemented by an automatic hyperparameter optimization strategy, whose key aspect is to include all the parameters to the fit, allowing the simultaneous optimization of the neural network architecture, the structure of the DL model, and the supervised learning algorithm. By comparing the reconstruction performances of the DL technique with those achieved from the traditional dictionary-based method on an independent dataset, the DL approach was shown to reduce the mean percentage relative error by a factor of 3 for T1 and by a factor of 2 for T2 , and to improve the computational time by at least a factor of 37. Furthermore, the proposed DL method enables maintaining comparable reconstruction performance, even with a lower number of MRF images and a reduced k-space sampling percentage, with respect to the dictionary-based method. Our results suggest that the proposed DL methodology may offer an improvement in reconstruction accuracy, as well as speeding up MRF for preclinical, and in prospective clinical, investigations.
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Affiliation(s)
- Raffaella Fiamma Cabini
- Department of Mathematics, University of Pavia, Pavia, Italy
- INFN, Istituto Nazionale di Fisica Nucleare, Pavia, Italy
| | - Leonardo Barzaghi
- Department of Mathematics, University of Pavia, Pavia, Italy
- INFN, Istituto Nazionale di Fisica Nucleare, Pavia, Italy
- Advanced Imaging and Artificial Intelligence, Department of Neuroradiology, IRCCS Mondino Foundation, Pavia, Italy
| | - Davide Cicolari
- Department of Physics, University of Pavia, Pavia, Italy
- Department of Physics, University of Milan, Milan, Italy
- INFN, Istituto Nazionale di Fisica Nucleare, Milan, Italy
- Department of Medical Physics, ASST GOM Niguarda, Milan, Italy
| | - Paolo Arosio
- Department of Physics, University of Milan, Milan, Italy
- INFN, Istituto Nazionale di Fisica Nucleare, Milan, Italy
| | - Stefano Carrazza
- Department of Physics, University of Milan, Milan, Italy
- INFN, Istituto Nazionale di Fisica Nucleare, Milan, Italy
| | - Silvia Figini
- INFN, Istituto Nazionale di Fisica Nucleare, Pavia, Italy
- Department of Social and Political Science, University of Pavia, Pavia, Italy
| | - Marta Filibian
- INFN, Istituto Nazionale di Fisica Nucleare, Pavia, Italy
- Centro Grandi Strumenti, University of Pavia, Pavia, Italy
| | - Andrea Gazzano
- Laboratory of Cellular and Molecular Neuropharmacology, Department of Biology and Biotechnology "L. Spallanzani", University of Pavia, Pavia, Italy
| | | | - Manuel Mariani
- Department of Physics, University of Pavia, Pavia, Italy
| | - Marco Peviani
- Laboratory of Cellular and Molecular Neuropharmacology, Department of Biology and Biotechnology "L. Spallanzani", University of Pavia, Pavia, Italy
| | - Anna Pichiecchio
- Advanced Imaging and Artificial Intelligence, Department of Neuroradiology, IRCCS Mondino Foundation, Pavia, Italy
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
| | | | - Alessandro Lascialfari
- INFN, Istituto Nazionale di Fisica Nucleare, Pavia, Italy
- Department of Physics, University of Pavia, Pavia, Italy
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3
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Hu S, Chen Y, Zong X, Lin W, Griswold M, Ma D. Improving motion robustness of 3D MR fingerprinting with a fat navigator. Magn Reson Med 2023; 90:1802-1817. [PMID: 37345703 PMCID: PMC10524525 DOI: 10.1002/mrm.29761] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 05/01/2023] [Accepted: 05/26/2023] [Indexed: 06/23/2023]
Abstract
PURPOSE To develop a 3D MR fingerprinting (MRF) method in combination with fat navigators to improve its motion robustness for neuroimaging. METHODS A rapid fat navigator was developed using the stack-of-spirals acquisition and non-Cartesian spiral GRAPPA. The fat navigator module was implemented in the 3D MRF sequence with high scan efficiency. The developed method was first validated in phantoms and five healthy subjects with intentional head motion. The method was further applied to infants with neonatal opioid withdrawal symptoms. The 3D MRF scans with fat navigators acquired with and without acceleration along the partition-encoding direction were both examined in the study. RESULTS Both phantom and in vivo results demonstrated that the added fat navigator modules did not influence the quantification accuracy in MRF. In combination with non-Cartesian spiral GRAPPA, a rapid fat navigator sampling with whole-brain coverage was achieved in ˜0.5 s at 3T, reducing its sensitivity to potential motion. Based on the motion waveforms extracted from fat navigators, the motion robustness of the 3D MRF was largely improved. With the proposed method, the motion-corrupted MRF datasets yielded T1 and T2 maps with significantly reduced artifacts and high correlations with measurements from the reference motion-free MRF scans. CONCLUSION We developed a 3D MRF method coupled with rapid fat navigators to improve its motion robustness for quantitative neuroimaging. Our results demonstrate that (1) accurate tissue quantification was preserved with the fat navigator modules and (2) the motion robustness for quantitative tissue mapping was largely improved with the developed method.
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Affiliation(s)
- Siyuan Hu
- Department of Biomedical Engineering Cleveland, Ohio, USA
| | - Yong Chen
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA
| | - Xiaopeng Zong
- School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
| | - Weili Lin
- Department of Radiology, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Mark Griswold
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA
| | - Dan Ma
- Department of Biomedical Engineering Cleveland, Ohio, USA
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Bhagavatula S, Cabeen R, Harris NG, Gröhn O, Wright DK, Garner R, Bennett A, Alba C, Martinez A, Ndode-Ekane XE, Andrade P, Paananen T, Ciszek R, Immonen R, Manninen E, Puhakka N, Tohka J, Heiskanen M, Ali I, Shultz SR, Casillas-Espinosa PM, Yamakawa GR, Jones NC, Hudson MR, Silva JC, Braine EL, Brady RD, Santana-Gomez CE, Smith GD, Staba R, O'Brien TJ, Pitkänen A, Duncan D. Image data harmonization tools for the analysis of post-traumatic epilepsy development in preclinical multisite MRI studies. Epilepsy Res 2023; 195:107201. [PMID: 37562146 PMCID: PMC10528111 DOI: 10.1016/j.eplepsyres.2023.107201] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Revised: 07/04/2023] [Accepted: 07/31/2023] [Indexed: 08/12/2023]
Abstract
Preclinical MRI studies have been utilized for the discovery of biomarkers that predict post-traumatic epilepsy (PTE). However, these single site studies often lack statistical power due to limited and homogeneous datasets. Therefore, multisite studies, such as the Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx), are developed to create large, heterogeneous datasets that can lead to more statistically significant results. EpiBioS4Rx collects preclinical data internationally across sites, including the United States, Finland, and Australia. However, in doing so, there are robust normalization and harmonization processes that are required to obtain statistically significant and generalizable results. This work describes the tools and procedures used to harmonize multisite, multimodal preclinical imaging data acquired by EpiBioS4Rx. There were four main harmonization processes that were utilized, including file format harmonization, naming convention harmonization, image coordinate system harmonization, and diffusion tensor imaging (DTI) metrics harmonization. By using Python tools and bash scripts, the file formats, file names, and image coordinate systems are harmonized across all the sites. To harmonize DTI metrics, values are estimated for each voxel in an image to generate a histogram representing the whole image. Then, the Quantitative Imaging Toolkit (QIT) modules are utilized to scale the mode to a value of one and depict the subsequent harmonized histogram. The standardization of file formats, naming conventions, coordinate systems, and DTI metrics are qualitatively assessed. The histograms of the DTI metrics were generated for all the individual rodents per site. For inter-site analysis, an average of the individual scans was calculated to create a histogram that represents each site. In order to ensure the analysis can be run at the level of individual animals, the sham and TBI cohort were analyzed separately, which depicted the same harmonization factor. The results demonstrate that these processes qualitatively standardize the file formats, naming conventions, coordinate systems, and DTI metrics of the data. This assists in the ability to share data across the study, as well as disseminate tools that can help other researchers to strengthen the statistical power of their studies and analyze data more cohesively.
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Affiliation(s)
- Sweta Bhagavatula
- USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA.
| | - Ryan Cabeen
- USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | - Neil G Harris
- Department of Neurology, David Geffen School of Medicine at University of California at Los Angeles, Los Angeles, CA, USA
| | - Olli Gröhn
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - David K Wright
- Departments of Neuroscience and Neurology, Central Clinical School, Alfred Health, Monash University, Melbourne, Victoria, Australia
| | - Rachael Garner
- USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | - Alexis Bennett
- USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | - Celina Alba
- USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | - Aubrey Martinez
- USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | | | - Pedro Andrade
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Tomi Paananen
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Robert Ciszek
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Riikka Immonen
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Eppu Manninen
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Noora Puhakka
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Jussi Tohka
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Mette Heiskanen
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Idrish Ali
- Departments of Neuroscience and Neurology, Central Clinical School, Alfred Health, Monash University, Melbourne, Victoria, Australia
| | - Sandy R Shultz
- Departments of Neuroscience and Neurology, Central Clinical School, Alfred Health, Monash University, Melbourne, Victoria, Australia
| | - Pablo M Casillas-Espinosa
- Departments of Neuroscience and Neurology, Central Clinical School, Alfred Health, Monash University, Melbourne, Victoria, Australia
| | - Glenn R Yamakawa
- Departments of Neuroscience and Neurology, Central Clinical School, Alfred Health, Monash University, Melbourne, Victoria, Australia
| | - Nigel C Jones
- Departments of Neuroscience and Neurology, Central Clinical School, Alfred Health, Monash University, Melbourne, Victoria, Australia
| | - Matthew R Hudson
- Departments of Neuroscience and Neurology, Central Clinical School, Alfred Health, Monash University, Melbourne, Victoria, Australia
| | - Juliana C Silva
- Departments of Neuroscience and Neurology, Central Clinical School, Alfred Health, Monash University, Melbourne, Victoria, Australia
| | - Emma L Braine
- Departments of Neuroscience and Neurology, Central Clinical School, Alfred Health, Monash University, Melbourne, Victoria, Australia
| | - Rhys D Brady
- Departments of Neuroscience and Neurology, Central Clinical School, Alfred Health, Monash University, Melbourne, Victoria, Australia
| | - Cesar E Santana-Gomez
- Department of Neurology, David Geffen School of Medicine at University of California at Los Angeles, Los Angeles, CA, USA
| | - Gregory D Smith
- Department of Neurology, David Geffen School of Medicine at University of California at Los Angeles, Los Angeles, CA, USA
| | - Richard Staba
- Department of Neurology, David Geffen School of Medicine at University of California at Los Angeles, Los Angeles, CA, USA
| | - Terence J O'Brien
- Departments of Neuroscience and Neurology, Central Clinical School, Alfred Health, Monash University, Melbourne, Victoria, Australia
| | - Asla Pitkänen
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Dominique Duncan
- USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
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5
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Gu Y, Wang L, Yang H, Wu Y, Kim K, Zhu Y, Androjna C, Zhu X, Chen Y, Zhong K, Yu X. Three-dimensional high-resolution T 1 and T 2 mapping of whole macaque brain at 9.4 T using magnetic resonance fingerprinting. Magn Reson Med 2022; 87:2901-2913. [PMID: 35129226 DOI: 10.1002/mrm.29181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Revised: 01/10/2022] [Accepted: 01/10/2022] [Indexed: 11/12/2022]
Abstract
PURPOSE Quantitative T1 and T2 mapping in non-human primates with whole-brain coverage is challenged by the requirement of sub-millimeter resolution and the inhomogeneity of the transmit magnetic field (B1 + ) covering a large field of view. The goal of the current study is to develop a magnetic resonance fingerprinting (MRF) method for simultaneous T1 and T2 mapping of the entire macaque brain within feasible scan time. METHODS A three-dimensional (3D) MRF sequence with both inversion- and T2 -preparation modules was developed and evaluated on a 9.4 T preclinical scanner. Data acquisition used a 3D stack-of-spirals trajectory, with undersampling along both the in-plane and the through-plane directions. The effect of B1 + inhomogeneity was accounted for by matching the acquired fingerprint to a dictionary simulated with the B1 + factors measured from a separate scan. In vitro and ex vivo studies were performed to evaluate the accuracy and the undersampling capacity of the MRF method. The application of the MRF method for in vivo, brain-wide T1 and T2 mapping was demonstrated on macaques at 4, 6, and 12 years of age. RESULTS The MRF method enabled highly repeatable T1 and T2 mapping at high spatial resolution (0.35 × 0.35 × 1 mm3 ) with an acceleration factor of 24. In vivo studies showed significant age-related T2 reduction in deep gray nuclei including the globus pallidus, the putamen, and the caudate nucleus. CONCLUSIONS This study demonstrates the first MRF study for brain-wide, multi-parametric quantification in non-human primates with sub-millimeter resolution.
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Affiliation(s)
- Yuning Gu
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Lulu Wang
- High Magnetic Field Laboratory, Chinese Academy of Sciences, Hefei, China.,Anhui Province Key Laboratory of High Field Magnetic Resonance Imaging, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China
| | - Hongyi Yang
- High Magnetic Field Laboratory, Chinese Academy of Sciences, Hefei, China.,Anhui Province Key Laboratory of High Field Magnetic Resonance Imaging, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China.,School of Graduate Studies, Science Island Branch, University of Science and Technology of China, Hefei, China
| | - Yun Wu
- High Magnetic Field Laboratory, Chinese Academy of Sciences, Hefei, China.,Anhui Province Key Laboratory of High Field Magnetic Resonance Imaging, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China
| | - Kihwan Kim
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Yuran Zhu
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Charlie Androjna
- Center for Preclinical Magnetic Resonance Imaging, Cleveland Clinic Foundation, Cleveland, Ohio, USA
| | - Xiaofeng Zhu
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio, USA
| | - Yong Chen
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA
| | - Kai Zhong
- High Magnetic Field Laboratory, Chinese Academy of Sciences, Hefei, China.,Anhui Province Key Laboratory of High Field Magnetic Resonance Imaging, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China.,Biomedical Engineering Department, Peking University, Beijing, China
| | - Xin Yu
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.,Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA
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Wang C, Kim K, Yu X. Rapid In Vivo Quantification of Creatine Kinase Activity by Phosphorous-31 Magnetic Resonance Spectroscopic Fingerprinting ( 31P-MRSF). Methods Mol Biol 2022; 2393:597-609. [PMID: 34837201 DOI: 10.1007/978-1-0716-1803-5_31] [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: 06/13/2023]
Abstract
Creatine kinase (CK) plays an important role in tissue metabolism by providing a buffering mechanism for maintaining a constant supply of adenosine triphosphate (ATP) during metabolic perturbations. Phosphorous-31 magnetic resonance spectroscopy (31P-MRS) employing magnetization transfer techniques is the only noninvasive method for measuring the rate of ATP synthesis via creatine kinase. However, due to the low concentrations of phosphate metabolites, current 31P-MRS methods require long acquisition time to achieve adequate measurement accuracy. In this chapter, we present a new framework of data acquisition and parameter estimation, the 31P magnetic resonance spectroscopic fingerprinting (31P-MRSF) method, for rapid quantification of CK reaction rate constant in the hindlimb of small laboratory animals.
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Affiliation(s)
- Charlie Wang
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
| | - Kihwan Kim
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
| | - Xin Yu
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.
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7
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Tippareddy C, Zhao W, Sunshine JL, Griswold M, Ma D, Badve C. Magnetic resonance fingerprinting: an overview. Eur J Nucl Med Mol Imaging 2021; 48:4189-4200. [PMID: 34037831 DOI: 10.1007/s00259-021-05384-2] [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: 12/21/2020] [Accepted: 04/25/2021] [Indexed: 12/17/2022]
Abstract
Magnetic resonance fingerprinting (MRF) is an evolving quantitative MRI framework consisting of unique data acquisition, processing, visualization, and interpretation steps. MRF is capable of simultaneously producing multiple high-resolution property maps including T1, T2, M0, ADC, and T2* measurements. While a relatively new technology, MRF has undergone rapid development for a variety of clinical applications from brain tumor characterization and epilepsy imaging to characterization of prostate cancer, cardiac imaging, among others. This paper will provide a brief overview of current state of MRF technology including highlights of technical and clinical advances. We will conclude with a brief discussion of the challenges that need to be overcome to establish MRF as a quantitative imaging biomarker.
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Affiliation(s)
- Charit Tippareddy
- Case Western Reserve University School of Medicine, 11100 Euclid Ave., Cleveland, OH, 44106, USA
| | - Walter Zhao
- Case Western Reserve University School of Medicine, 11100 Euclid Ave., Cleveland, OH, 44106, USA
| | - Jeffrey L Sunshine
- Department of Radiology, Case Western Reserve University and University Hospitals Cleveland Medical Center, 11100 Euclid Ave., Cleveland, OH, 44106, USA
| | - Mark Griswold
- Department of Biomedical Engineering, Case Western Reserve University, 11100 Euclid Ave., Cleveland, OH, 44106, USA.,Department of Radiology, Case Western Reserve University and University Hospitals Cleveland Medical Center, 11100 Euclid Ave., Cleveland, OH, 44106, USA
| | - Dan Ma
- Department of Biomedical Engineering, Case Western Reserve University, 11100 Euclid Ave., Cleveland, OH, 44106, USA
| | - Chaitra Badve
- Department of Radiology, Case Western Reserve University and University Hospitals Cleveland Medical Center, 11100 Euclid Ave., Cleveland, OH, 44106, USA.
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8
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Li T, Cui D, Ren G, Hui ES, Cai J. Investigation of the effect of acquisition schemes on time-resolved magnetic resonance fingerprinting. Phys Med Biol 2021; 66. [PMID: 33823496 DOI: 10.1088/1361-6560/abf51f] [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: 10/22/2020] [Accepted: 04/06/2021] [Indexed: 01/27/2023]
Abstract
Purpose.This study aims to investigate the feasibility of different acquisition methods for time-resolved magnetic resonance fingerprinting (TR-MRF) in computer simulation.Methods.An extended cardiac-torso (XCAT) phantom is used to generate abdominal T1, T2, and proton density maps for MRF simulation. The simulated MRF technique consists of an IR-FISP MRF sequence with spiral trajectory acquisition. MRF maps were simulated with different numbers of repetitions from 1 to 15. Three different methods were used to generate TR-MRF maps: (1) continuous acquisition without delay between MRF repetitions; (2) continuous acquisition with 5 s delay between MRF repetitions; (3) triggered acquisition with variable delay between MRF repetitions to allow the next acquisition to start at different respiration phase. After the generation of TR-MRF maps, the image quality indexes including the absolute T1 and T2 values, signal-to-noise-ratio (SNR), tumor-to-liver contrast-to-noise ratio, error in the amplitude of diaphragm motion and tumor volume error were used to evaluate the reconstructed parameter maps. Three volunteers were recruited to test the feasibility of the selected acquisition method.Results.Dynamic MR parametric maps using three different acquisition methods were estimated. The overall and liver T1 value error, liver SNR in T1 and T2 maps, and tumor SNR from T1 maps from triggered method is statistically significantly better than the other two methods (p-value < 0.05). The other image quality indexes have no significant difference between the triggered method and the other two continuous acquisition methods. All image quality indexes exhibit no significant difference between the acquisition methods with 0 s and 5 s delay. The triggered method was successfully performed in three healthy volunteers.Conclusion.TR-MRF technique was investigated using three different acquisition methods in computer simulation where the triggered method showed better performance than the other two methods. The triggered method has been tested successfully in healthy volunteers.
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Affiliation(s)
- Tian Li
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong
| | - Di Cui
- Department of Diagnostic Radiology, The University of Hong Kong, Hong Kong
| | - Ge Ren
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong
| | - Edward S Hui
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong
| | - Jing Cai
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong
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9
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Hectors SJ, Garteiser P, Doblas S, Pagé G, Van Beers BE, Waterton JC, Bane O. MRI Mapping of Renal T 1: Basic Concept. Methods Mol Biol 2021; 2216:157-169. [PMID: 33475999 DOI: 10.1007/978-1-0716-0978-1_9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/19/2023]
Abstract
In renal MRI, measurement of the T1 relaxation time of water molecules may provide a valuable biomarker for a variety of pathological conditions. Due to its sensitivity to the tissue microenvironment, T1 has gained substantial interest for noninvasive imaging of renal pathology, including inflammation and fibrosis. In this chapter, we will discuss the basic concept of T1 mapping and different T1 measurement techniques and we will provide an overview of emerging preclinical applications of T1 for imaging of kidney disease.This chapter is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This introduction chapter is complemented by two separate chapters describing the experimental procedure and data analysis.
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Affiliation(s)
- Stefanie J Hectors
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
| | - Philippe Garteiser
- Laboratory of Imaging Biomarkers, Centre de Recherche sur l'Inflammation, Inserm UMR 1149, Université de Paris, Paris, France
| | - Sabrina Doblas
- Laboratory of Imaging Biomarkers, Centre de Recherche sur l'Inflammation, Inserm UMR 1149, Université de Paris, Paris, France
| | - Gwenaël Pagé
- Laboratory of Imaging Biomarkers, Centre de Recherche sur l'Inflammation, Inserm UMR 1149, Université de Paris, Paris, France
| | - Bernard E Van Beers
- Laboratory of Imaging Biomarkers, Centre de Recherche sur l'Inflammation, Inserm UMR 1149, Université de Paris and AP-HP, Paris, France
| | - John C Waterton
- Division of Informatics Imaging & Data Sciences, Faculty of Biology Medicine & Health, Centre for Imaging Sciences, School of Health Sciences, Manchester Academic Health Sciences Centre, University of Manchester, Manchester, UK
| | - Octavia Bane
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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10
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Marriott A, Bowen C, Rioux J, Brewer K. Simultaneous quantification of SPIO and gadolinium contrast agents using MR fingerprinting. Magn Reson Imaging 2021; 79:121-129. [PMID: 33774098 DOI: 10.1016/j.mri.2021.03.017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Revised: 03/22/2021] [Accepted: 03/22/2021] [Indexed: 11/16/2022]
Abstract
PURPOSE Develop a magnetic resonance fingerprinting (MRF) methodology with R2∗ quantification, intended for use with simultaneous contrast agent concentration mapping, particularly gadolinium (Gd) and iron labelled CD8+ T cells. METHODS Variable-density spiral SSFP MRF was used, modified to allow variable TE, and with an exp.(-TE·R2∗) dictionary modulation. In vitro phantoms containing SPIO labelled cells and/or gadolinium were used to validate parameter maps, probe undersampling capacity, and verify dual quantification capabilities. A C57BL/6 mouse was imaged using MRF to demonstrate acceptable in vivo resolution and signal at 8× undersampling necessary for a 25-min scan. RESULTS Strong agreement was found between conventional and MRF-derived values for R1, R2, and R2∗. Expanded MRF allowed quantification of iron-loaded CD8+ T cells. Results were robust to 8× undersampling and enabled recreation of relaxation profiles for both a Gd agent and iron labelled cells simultaneously. In vivo data demonstrated sufficient SNR in undersampled data for parameter mapping to visualise key features. CONCLUSION MRF can be expanded to include R1, R2, and R2∗ mapping required for simultaneous quantification of gadolinium and SPIO in vitro, allowing for potential implementation of a variety of future in vivo studies using dual MR contrast agents, including molecular imaging of labelled cells.
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Affiliation(s)
- Anna Marriott
- Biomedical Translational Imaging Centre (BIOTIC), Halifax, NS, Canada; Dalhousie University, Halifax, NS, Canada
| | - Chris Bowen
- Biomedical Translational Imaging Centre (BIOTIC), Halifax, NS, Canada; Dalhousie University, Halifax, NS, Canada
| | - James Rioux
- Biomedical Translational Imaging Centre (BIOTIC), Halifax, NS, Canada; Dalhousie University, Halifax, NS, Canada
| | - Kimberly Brewer
- Biomedical Translational Imaging Centre (BIOTIC), Halifax, NS, Canada; Dalhousie University, Halifax, NS, Canada.
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11
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Kim K, Gu Y, Wang CY, Clifford B, Huang S, Liang ZP, Yu X. Quantification of creatine kinase reaction rate in mouse hindlimb using phosphorus-31 magnetic resonance spectroscopic fingerprinting. NMR IN BIOMEDICINE 2021; 34:e4435. [PMID: 33111456 PMCID: PMC8324327 DOI: 10.1002/nbm.4435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2020] [Revised: 09/10/2020] [Accepted: 10/08/2020] [Indexed: 06/11/2023]
Abstract
The goal of this study was to evaluate the accuracy, reproducibility, and efficiency of a 31 P magnetic resonance spectroscopic fingerprinting (31 P-MRSF) method for fast quantification of the forward rate constant of creatine kinase (CK) in mouse hindlimb. The 31 P-MRSF method acquired spectroscopic fingerprints using interleaved acquisition of phosphocreatine (PCr) and γATP with ramped flip angles and a saturation scheme sensitive to chemical exchange between PCr and γATP. Parameter estimation was performed by matching the acquired fingerprints to a dictionary of simulated fingerprints generated from the Bloch-McConnell model. The accuracy of 31 P-MRSF measurements was compared with the magnetization transfer (MT-MRS) method in mouse hindlimb at 9.4 T (n = 8). The reproducibility of 31 P-MRSF was also assessed by repeated measurements. Estimation of the CK rate constant using 31 P-MRSF (0.39 ± 0.03 s-1 ) showed a strong agreement with that using MT-MRS measurements (0.40 ± 0.05 s-1 ). Variations less than 10% were achieved with 2 min acquisition of 31 P-MRSF data. Application of the 31 P-MRSF method to mice subjected to an electrical stimulation protocol detected an increase in CK rate constant in response to stimulation-induced muscle contraction. These results demonstrated the potential of the 31 P-MRSF framework for rapid, accurate, and reproducible quantification of the chemical exchange rate of CK in vivo.
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Affiliation(s)
- Kihwan Kim
- Department of Biomedical Engineering and Case Center for Imaging Research, Case Western Reserve University, Cleveland, Ohio
| | - Yuning Gu
- Department of Biomedical Engineering and Case Center for Imaging Research, Case Western Reserve University, Cleveland, Ohio
| | - Charlie Y. Wang
- Department of Biomedical Engineering and Case Center for Imaging Research, Case Western Reserve University, Cleveland, Ohio
| | - Bryan Clifford
- Department of Electrical and Computer Engineering and Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois
| | - Sherry Huang
- Department of Biomedical Engineering and Case Center for Imaging Research, Case Western Reserve University, Cleveland, Ohio
| | - Zhi-Pei Liang
- Department of Electrical and Computer Engineering and Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois
| | - Xin Yu
- Department of Biomedical Engineering and Case Center for Imaging Research, Case Western Reserve University, Cleveland, Ohio
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12
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MacAskill CJ, Erokwu BO, Markley M, Parsons A, Farr S, Zhang Y, Tran U, Chen Y, Anderson CE, Serai S, Hartung EA, Wessely O, Ma D, Dell KM, Flask CA. Multi-parametric MRI of kidney disease progression for autosomal recessive polycystic kidney disease: mouse model and initial patient results. Pediatr Res 2021; 89:157-162. [PMID: 32283547 PMCID: PMC7554096 DOI: 10.1038/s41390-020-0883-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/16/2020] [Accepted: 02/20/2020] [Indexed: 01/19/2023]
Abstract
BACKGROUND Autosomal recessive polycystic kidney disease (ARPKD) is a rare but potentially lethal genetic disorder typically characterized by diffuse renal microcysts. Clinical trials for patients with ARPKD are not currently possible due to the absence of sensitive measures of ARPKD kidney disease progression and/or therapeutic efficacy. METHODS In this study, animal and human magnetic resonance imaging (MRI) scanners were used to obtain quantitative kidney T1 and T2 relaxation time maps for both excised kidneys from bpk and wild-type (WT) mice as well as for a pediatric patient with ARPKD and a healthy adult volunteer. RESULTS Mean kidney T1 and T2 relaxation times showed significant increases with age (p < 0.05) as well as significant increases in comparison to WT mice (p < 2 × 10-10). Significant or nearly significant linear correlations were observed for mean kidney T1 (p = 0.030) and T2 (p = 0.054) as a function of total kidney volume, respectively. Initial magnetic resonance fingerprinting assessments in a patient with ARPKD showed visible increases in both kidney T1 and T2 in comparison to the healthy volunteer. CONCLUSIONS These preclinical and initial clinical MRI studies suggest that renal T1 and T2 relaxometry may provide an additional outcome measure to assess cystic kidney disease progression in patients with ARPKD. IMPACT A major roadblock for implementing clinical trials in patients with ARPKD is the absence of sensitive measures of ARPKD kidney disease progression and/or therapeutic efficacy. A clinical need exists to develop a safe and sensitive measure for kidney disease progression, and eventually therapeutic efficacy, for patients with ARPKD. Mean kidney T1 and T2 MRI relaxation times showed significant increases with age (p < 0.05) as well as significant increases in comparison to WT mice (p < 2 ×10-10), indicating that T1 and T2 may provide sensitive assessments of cystic changes associated with progressive ARPKD kidney disease. This preclinical and initial clinical study suggests that MRI-based kidney T1 and T2 mapping could be used as a non-invasive assessment of ARPKD kidney disease progression. These non-invasive, quantitative MRI techniques could eventually be used as an outcome measure for clinical trials evaluating novel therapeutics aimed at limiting or preventing ARPKD kidney disease progression.
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Affiliation(s)
| | - Bernadette O Erokwu
- Department of Radiology, Case Western Reserve University, Cleveland, OH, USA
| | - Michael Markley
- Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA
| | - Ashlee Parsons
- Center for Pediatric Nephrology, Cleveland Clinic Children's, Cleveland, OH, USA
| | - Susan Farr
- Department of Radiology, Case Western Reserve University, Cleveland, OH, USA
| | - Yifan Zhang
- Department of Radiology, Case Western Reserve University, Cleveland, OH, USA
| | - Uyen Tran
- Department of Cellular and Molecular Medicine, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA
| | - Yong Chen
- Department of Radiology, Case Western Reserve University, Cleveland, OH, USA
| | - Christian E Anderson
- Department of Radiology, Case Western Reserve University, Cleveland, OH, USA
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
| | - Suraj Serai
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Erum A Hartung
- Department of Pediatrics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Oliver Wessely
- Department of Cellular and Molecular Medicine, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA
| | - Dan Ma
- Department of Radiology, Case Western Reserve University, Cleveland, OH, USA
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
| | - Katherine M Dell
- Center for Pediatric Nephrology, Cleveland Clinic Children's, Cleveland, OH, USA
- Department of Pediatrics, Case Western Reserve University, Cleveland, OH, USA
| | - Chris A Flask
- Department of Radiology, Case Western Reserve University, Cleveland, OH, USA.
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.
- Department of Pediatrics, Case Western Reserve University, Cleveland, OH, USA.
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13
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Ji S, Yang D, Lee J, Choi SH, Kim H, Kang KM. Synthetic MRI: Technologies and Applications in Neuroradiology. J Magn Reson Imaging 2020; 55:1013-1025. [PMID: 33188560 DOI: 10.1002/jmri.27440] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2020] [Revised: 10/29/2020] [Accepted: 10/29/2020] [Indexed: 12/14/2022] Open
Abstract
Synthetic MRI is a technique that synthesizes contrast-weighted images from multicontrast MRI data. There have been advances in synthetic MRI since the technique was introduced. Although a number of synthetic MRI methods have been developed for quantifying one or more relaxometric parameters and for generating multiple contrast-weighted images, this review focuses on several methods that quantify all three relaxometric parameters (T1 , T2 , and proton density) and produce multiple contrast-weighted images. Acquisition, quantification, and image synthesis techniques are discussed for each method. We discuss the image quality and diagnostic accuracy of synthetic MRI methods and their clinical applications in neuroradiology. Based on this analysis, we highlight areas that need to be addressed for synthetic MRI to be widely implemented in the clinic. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 1.
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Affiliation(s)
- Sooyeon Ji
- Electrical and Computer Engineering, Institute of Engineering Research, Seoul National University, Seoul, Republic of Korea
| | - Dongjin Yang
- Department of Radiology, Daegu Fatima Hospital, Daegu, Republic of Korea
| | - Jongho Lee
- Electrical and Computer Engineering, Institute of Engineering Research, Seoul National University, Seoul, Republic of Korea
| | - Seung Hong Choi
- Electrical and Computer Engineering, Institute of Engineering Research, Seoul National University, Seoul, Republic of Korea.,Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea.,Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Hyeonjin Kim
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Koung Mi Kang
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
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14
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Nolte T, Scholten H, Gross-Weege N, Amthor T, Koken P, Doneva M, Schulz V. Confounding factors in breast magnetic resonance fingerprinting: B 1 + , slice profile, and diffusion effects. Magn Reson Med 2020; 85:1865-1880. [PMID: 33118649 DOI: 10.1002/mrm.28545] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Revised: 09/03/2020] [Accepted: 09/14/2020] [Indexed: 11/09/2022]
Abstract
PURPOSE Magnetic resonance fingerprinting (MRF) offers rapid quantitative imaging but may be subject to confounding effects (CE) if these are not included in the model-based reconstruction. This study characterizes the influence of in-plane B 1 + , slice profile and diffusion effects on T1 and T2 estimation in the female breast at 1.5T. METHODS Simulations were used to predict the influence of each CE on the accuracy of MRF and to investigate the influence of electronic noise and spiral aliasing artefacts. The experimentally observed bias in regions of fibroglandular tissue (FGT) and fatty tissue (FT) was analyzed for undersampled spiral breast MRF data of 6 healthy volunteers by performing MRF reconstruction with and without a CE. RESULTS Theoretic analysis predicts T1 under-/T2 overestimation if the nominal flip angles are underestimated and inversely, T1 under-/T2 overestimation if omitting slice profile correction, and T1 under-/T2 underestimation if omitting diffusion in the signal model. Averaged over repeated signal simulations, including spiral aliasing artefacts affected precision more than accuracy. Strong in-plane B 1 + effects occurred in vivo, causing T2 left-right inhomogeneity between both breasts. Their correction decreased the T2 difference from 29 to 5 ms in FGT and from 29 to 9 ms in FT. Slice profile correction affected FGT T2 most strongly, resulting in -22% smaller values. For the employed spoiler gradient strengths, diffusion did not affect the parameter maps, corresponding well with theoretic predictions. CONCLUSION Understanding CEs and their relative significance for an MRF sequence is important when defining an MRF signal model for accurate parameter mapping.
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Affiliation(s)
- Teresa Nolte
- Physics of Molecular Imaging Systems, Experimental Molecular Imaging, RWTH Aachen University, Aachen, Germany
| | - Hannah Scholten
- Department of Diagnostic and Interventional Radiology, University of Würzburg, Würzburg, Germany
| | - Nicolas Gross-Weege
- Physics of Molecular Imaging Systems, Experimental Molecular Imaging, RWTH Aachen University, Aachen, Germany
| | - Thomas Amthor
- Tomographic Imaging Systems, Philips Research Europe, Hamburg, Germany
| | - Peter Koken
- Tomographic Imaging Systems, Philips Research Europe, Hamburg, Germany
| | - Mariya Doneva
- Tomographic Imaging Systems, Philips Research Europe, Hamburg, Germany
| | - Volkmar Schulz
- Physics of Molecular Imaging Systems, Experimental Molecular Imaging, RWTH Aachen University, Aachen, Germany.,Hyperion Hybrid Imaging Systems GmbH, Aachen, Germany.,Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany.,Physics Institute III B, RWTH Aachen University, Aachen, Germany
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15
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Meng Y, Cheung J, Sun PZ. Improved MR fingerprinting for relaxation measurement in the presence of semisolid magnetization transfer. Magn Reson Med 2020; 84:727-737. [PMID: 31898839 PMCID: PMC7180097 DOI: 10.1002/mrm.28159] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2019] [Revised: 12/11/2019] [Accepted: 12/11/2019] [Indexed: 12/16/2022]
Abstract
PURPOSE To characterize and minimize the magnetization transfer (MT) effect in MR fingerprinting (MRF) relaxation measurements with a 2-pool (2P) MT model of multiple tissue types. THEORY AND METHODS Semisolid MT effect in MRF was modeled using 2P Bloch-McConnell equations. The combinations of MT parameters of multiple tissues (white [WM] and gray matter [GM]) were used to build the MRF dictionary. Both 1-pool (1P) and 2P models were simulated to characterize the dependence on MT. Relaxations measured using MRF with spin-echo saturation-recovery (SR) or inversion-recovery preparations were compared with conventional SR-prepared T1 and multiple spin-echo T2 measurements. The simulations results were validated with phantoms and brain tissue samples. RESULTS The MRF signal was different from the 1P and 2P models. 1P MRF produced significantly (P < .05) underestimated T1 in WM (20-30%) and GM (7-10%), while 2P MRF measured consistent T1 and T2 in both WM and GM with conventional measurements (pairwise test P > .1; correlated P < .05). Simulations showed that SR-prepared MRF measuring T1 had much less errors against the variation of the macromolecular fraction. Compared with inversion-recovery preparation, SR-prepared MRF produced higher relaxation correlations (R > 0.9) with conventional measurements in both WM and GM across samples, suggesting that SR-prepared MRF was less sensitive to the compositive effect of multiple MT parameters variations. CONCLUSIONS 2P MRF using a combination of MT parameters for multiple tissue types can measure consistent relaxations with conventional methods. With the 2P models, SR-prepared MRF would provide an option for robust relaxation measurement under heterogeneous MT.
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Affiliation(s)
- Yuguang Meng
- Yerkes Imaging Center, Yerkes National Primate Research Center, Emory University, Atlanta, GA, USA
| | - Jesse Cheung
- Department of Anthropology and Human Biology, Emory University, Atlanta, GA, USA
| | - Phillip Zhe Sun
- Yerkes Imaging Center, Yerkes National Primate Research Center, Emory University, Atlanta, GA, USA
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, USA
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16
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Deruelle T, Kober F, Perles-Barbacaru A, Delzescaux T, Noblet V, Barbier EL, Dojat M. A Multicenter Preclinical MRI Study: Definition of Rat Brain Relaxometry Reference Maps. Front Neuroinform 2020; 14:22. [PMID: 32508614 PMCID: PMC7248563 DOI: 10.3389/fninf.2020.00022] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2019] [Accepted: 04/21/2020] [Indexed: 11/13/2022] Open
Abstract
Similarly to human population imaging, there are several well-founded motivations for animal population imaging, the most notable being the improvement of the validity of statistical results by pooling a sufficient number of animal data provided by different imaging centers. In this paper, we demonstrate the feasibility of such a multicenter animal study, sharing raw data from forty rats and processing pipelines between four imaging centers. As specific use case, we focused on T1 and T2 mapping of the healthy rat brain at 7T. We quantitatively report about the variability observed across two MR data providers and evaluate the influence of image processing steps on the final maps, using three fitting algorithms from three centers. Finally, to derive relaxation times from different brain areas, two multi-atlas segmentation pipelines from different centers were performed on two different platforms. Differences between the two data providers were 2.21% for T1 and 9.52% for T2. Differences between processing pipelines were 1.04% for T1 and 3.33% for T2. These maps, obtained in healthy conditions, may be used in the future as reference when exploring alterations in animal models of pathology.
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Affiliation(s)
- Tristan Deruelle
- INSERM, U1216, Grenoble Institut des Neurosciences, Université Grenoble Alpes, Grenoble, France
| | - Frank Kober
- CNRS, CRMBM, Aix-Marseille Université, Marseille, France
| | | | | | - Vincent Noblet
- CNRS, ICube - IMAGeS, Strasbourg University, Strasbourg, France
| | - Emmanuel L Barbier
- INSERM, U1216, Grenoble Institut des Neurosciences, Université Grenoble Alpes, Grenoble, France
| | - Michel Dojat
- INSERM, U1216, Grenoble Institut des Neurosciences, Université Grenoble Alpes, Grenoble, France
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17
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Faller TL, Trotier AJ, Rousseau AF, Franconi JM, Miraux S, Ribot EJ. 2D multislice MP2RAGE sequence for fast T 1 mapping at 7 T: Application to mouse imaging and MR thermometry. Magn Reson Med 2020; 84:1430-1440. [PMID: 32083341 DOI: 10.1002/mrm.28220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2019] [Revised: 12/24/2019] [Accepted: 01/29/2020] [Indexed: 11/08/2022]
Abstract
PURPOSE To develop a 2D radial multislice MP2RAGE sequence for fast and reliable T1 mapping at 7 T in mice and for MR thermometry. METHODS The 2D-MP2RAGE sequence was performed with the following parameters: TI1 -TI2 -MP2RAGETR = 1000-3000-9000 ms. The multiple dead times within the sequence were used for interleaved multislice acquisition, enabling one to acquire six slices in 9 seconds. The excitation pulse shape, inversion selectivity, and interslice gap were optimized. In vitro comparison with the inversion-recovery sequence was performed. The T1 variations with temperature were measured on tubes with T1 ranging from 800 ms to 2000 ms. The sequence was used to acquire T1 maps continuously during 30 minutes on the brain and abdomen of healthy mice. RESULTS A three-lobe cardinal sine excitation pulse, combined with an inversion slice thickness and an interslice gap of respectively 150% and 50% of the imaging slice thickness, led to a SD and bias of the T1 measurements below 1% and 2%, respectively. A linear dependence of T1 with temperature was measured between 10°C and 60°C. In vivo, less than 1% variation was measured between successive T1 maps in the mouse brain. In the abdomen, no obvious in-plane motion artifacts were observed but respiratory motion in the slice dimension led to 6% T1 underestimation. CONCLUSION The multislice MP2RAGE sequence could be used for fast whole-body T1 mapping and MR thermometry. Its reconstruction method would enable on-the-fly reconstruction.
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Affiliation(s)
- Thibaut L Faller
- Centre de Résonance Magnétique des Systèmes Biologiques, UMR 5536, CNRS/Université de Bordeaux, Bordeaux, France
| | - Aurélien J Trotier
- Centre de Résonance Magnétique des Systèmes Biologiques, UMR 5536, CNRS/Université de Bordeaux, Bordeaux, France
| | - Alice F Rousseau
- Centre de Résonance Magnétique des Systèmes Biologiques, UMR 5536, CNRS/Université de Bordeaux, Bordeaux, France
| | - Jean-Michel Franconi
- Centre de Résonance Magnétique des Systèmes Biologiques, UMR 5536, CNRS/Université de Bordeaux, Bordeaux, France
| | - Sylvain Miraux
- Centre de Résonance Magnétique des Systèmes Biologiques, UMR 5536, CNRS/Université de Bordeaux, Bordeaux, France
| | - Emeline J Ribot
- Centre de Résonance Magnétique des Systèmes Biologiques, UMR 5536, CNRS/Université de Bordeaux, Bordeaux, France
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18
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Anderson CE, Johansen M, Erokwu BO, Hu H, Gu Y, Zhang Y, Kavran M, Vincent J, Drumm ML, Griswold MA, Steinmetz NF, Li M, Clark H, Darrah RJ, Yu X, Brady-Kalnay SM, Flask CA. Dynamic, Simultaneous Concentration Mapping of Multiple MRI Contrast Agents with Dual Contrast - Magnetic Resonance Fingerprinting. Sci Rep 2019; 9:19888. [PMID: 31882792 PMCID: PMC6934650 DOI: 10.1038/s41598-019-56531-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2019] [Accepted: 12/09/2019] [Indexed: 12/31/2022] Open
Abstract
Synchronous assessment of multiple MRI contrast agents in a single scanning session would provide a new "multi-color" imaging capability similar to fluorescence imaging but with high spatiotemporal resolution and unlimited imaging depth. This multi-agent MRI technology would enable a whole new class of basic science and clinical MRI experiments that simultaneously explore multiple physiologic/molecular events in vivo. Unfortunately, conventional MRI acquisition techniques are only capable of detecting and quantifying one paramagnetic MRI contrast agent at a time. Herein, the Dual Contrast - Magnetic Resonance Fingerprinting (DC-MRF) methodology was extended for in vivo application and evaluated by simultaneously and dynamically mapping the intra-tumoral concentration of two MRI contrast agents (Gd-BOPTA and Dy-DOTA-azide) in a mouse glioma model. Co-registered gadolinium and dysprosium concentration maps were generated with sub-millimeter spatial resolution and acquired dynamically with just over 2-minute temporal resolution. Mean tumor Gd and Dy concentration measurements from both single agent and dual agent DC-MRF studies demonstrated significant correlations with ex vivo mass spectrometry elemental analyses. This initial in vivo study demonstrates the potential for DC-MRF to provide a useful dual-agent MRI platform.
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Affiliation(s)
- Christian E Anderson
- Department of Radiology, Case Western Reserve University, Cleveland, OH, USA
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
| | - Mette Johansen
- Department of Molecular Biology and Microbiology, Case Western Reserve University, Cleveland, OH, USA
| | - Bernadette O Erokwu
- Department of Radiology, Case Western Reserve University, Cleveland, OH, USA
| | - He Hu
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
- Department of NanoEngineering, University of California-San Diego, La Jolla, CA, USA
| | - Yuning Gu
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
| | - Yifan Zhang
- Department of Radiology, Case Western Reserve University, Cleveland, OH, USA
| | - Michael Kavran
- Department of Radiology, Case Western Reserve University, Cleveland, OH, USA
| | - Jason Vincent
- Department of Molecular Biology and Microbiology, Case Western Reserve University, Cleveland, OH, USA
| | - Mitchell L Drumm
- Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, OH, USA
- Department of Pediatrics, Case Western Reserve University, Cleveland, OH, USA
| | - Mark A Griswold
- Department of Radiology, Case Western Reserve University, Cleveland, OH, USA
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
| | - Nicole F Steinmetz
- Department of Radiology, Case Western Reserve University, Cleveland, OH, USA
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
- Department of NanoEngineering, University of California-San Diego, La Jolla, CA, USA
- Department of Radiology, University of California-San Diego, La Jolla, CA, USA
- Moores Cancer Center, University of California-San Diego, La Jolla, CA, USA
| | - Ming Li
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA
| | - Heather Clark
- Department of Bioengineering, Northeastern University, Boston, MA, USA
- Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA, USA
- Institute of Systems Bioanalysis and Chemical Imaging, Northeastern University, Boston, MA, USA
| | - Rebecca J Darrah
- Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, OH, USA
- Francis Payne Bolton School of Nursing, Case Western Reserve University, Cleveland, OH, USA
| | - Xin Yu
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
- Department of Physiology and Biophysics, Case Western Reserve University, Cleveland, OH, USA
| | - Susann M Brady-Kalnay
- Department of Molecular Biology and Microbiology, Case Western Reserve University, Cleveland, OH, USA
- Department of Neurosciences, Case Western Reserve University, Cleveland, OH, USA
| | - Chris A Flask
- Department of Radiology, Case Western Reserve University, Cleveland, OH, USA.
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA.
- Department of Pediatrics, Case Western Reserve University, Cleveland, OH, USA.
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19
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Abstract
Advanced neuroimaging techniques are increasingly being implemented in clinical practice as complementary tools to conventional imaging because they can provide crucial functional information about the pathophysiology of a variety of disorders. Therefore, it is important to understand the basic principles underlying them and their role in diagnosis and management. In this review, we will primarily focus on the basic principles and clinical applications of perfusion imaging, diffusion imaging, magnetic resonance spectroscopy, functional MRI, and dual-energy computerized tomography. Our goal is to provide the reader with a basic understanding of these imaging techniques and when they should be used in clinical practice.
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20
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Poorman ME, Martin MN, Ma D, McGivney DF, Gulani V, Griswold MA, Keenan KE. Magnetic resonance fingerprinting Part 1: Potential uses, current challenges, and recommendations. J Magn Reson Imaging 2019; 51:675-692. [PMID: 31264748 DOI: 10.1002/jmri.26836] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2019] [Accepted: 05/31/2019] [Indexed: 12/11/2022] Open
Abstract
Magnetic resonance fingerprinting (MRF) is a powerful quantitative MRI technique capable of acquiring multiple property maps simultaneously in a short timeframe. The MRF framework has been adapted to a wide variety of clinical applications, but faces challenges in technical development, and to date has only demonstrated repeatability and reproducibility in small studies. In this review, we discuss the current implementations of MRF and their use in a clinical setting. Based on this analysis, we highlight areas of need that must be addressed before MRF can be fully adopted into the clinic and make recommendations to the MRF community on standardization and validation strategies of MRF techniques. Level of Evidence: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:675-692.
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Affiliation(s)
- Megan E. Poorman
- Department of PhysicsUniversity of Colorado Boulder Boulder Colorado USA
- Physical Measurement LaboratoryNational Institute of Standards and Technology Boulder Colorado USA
| | - Michele N. Martin
- Physical Measurement LaboratoryNational Institute of Standards and Technology Boulder Colorado USA
| | - Dan Ma
- Department of RadiologyCase Western Reserve University Cleveland Ohio USA
| | - Debra F. McGivney
- Department of RadiologyCase Western Reserve University Cleveland Ohio USA
| | - Vikas Gulani
- Department of RadiologyCase Western Reserve University Cleveland Ohio USA
| | - Mark A. Griswold
- Department of RadiologyCase Western Reserve University Cleveland Ohio USA
| | - Kathryn E. Keenan
- Physical Measurement LaboratoryNational Institute of Standards and Technology Boulder Colorado USA
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21
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Zhao B, Haldar JP, Liao C, Ma D, Jiang Y, Griswold MA, Setsompop K, Wald LL. Optimal Experiment Design for Magnetic Resonance Fingerprinting: Cramér-Rao Bound Meets Spin Dynamics. IEEE TRANSACTIONS ON MEDICAL IMAGING 2019; 38:844-861. [PMID: 30295618 PMCID: PMC6447464 DOI: 10.1109/tmi.2018.2873704] [Citation(s) in RCA: 83] [Impact Index Per Article: 16.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
Magnetic resonance (MR) fingerprinting is a new quantitative imaging paradigm, which simultaneously acquires multiple MR tissue parameter maps in a single experiment. In this paper, we present an estimation-theoretic framework to perform experiment design for MR fingerprinting. Specifically, we describe a discrete-time dynamic system to model spin dynamics, and derive an estimation-theoretic bound, i.e., the Cramér-Rao bound, to characterize the signal-to-noise ratio (SNR) efficiency of an MR fingerprinting experiment. We then formulate an optimal experiment design problem, which determines a sequence of acquisition parameters to encode MR tissue parameters with the maximal SNR efficiency, while respecting the physical constraints and other constraints from the image decoding/reconstruction process. We evaluate the performance of the proposed approach with numerical simulations, phantom experiments, and in vivo experiments. We demonstrate that the optimized experiments substantially reduce data acquisition time and/or improve parameter estimation. For example, the optimized experiments achieve about a factor of two improvement in the accuracy of T2 maps, while keeping similar or slightly better accuracy of T1 maps. Finally, as a remarkable observation, we find that the sequence of optimized acquisition parameters appears to be highly structured rather than randomly/pseudo-randomly varying as is prescribed in the conventional MR fingerprinting experiments.
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Affiliation(s)
- Bo Zhao
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129 USA
- Department of Radiology, Harvard Medical School, Boston, MA 02115 USA
| | - Justin P. Haldar
- Signal and Image Processing Institute and Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, CA 90089 USA
| | - Congyu Liao
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129 USA
- Department of Biomedical Engineering, Zhejiang University, Hangzhou, Zhejiang Province 310027 China
| | - Dan Ma
- Department of Radiology, Case Western Reserve University, Cleveland, OH 44106 USA
| | - Yun Jiang
- Department of Radiology, Case Western Reserve University, Cleveland, OH 44106 USA
| | - Mark A. Griswold
- Department of Radiology, Case Western Reserve University, Cleveland, OH 44106 USA
| | - Kawin Setsompop
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129 USA
- Department of Radiology, Harvard Medical School, Boston, MA, 02115 USA
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
| | - Lawrence L. Wald
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129 USA
- Department of Radiology, Harvard Medical School, Boston, MA, 02115 USA, and also with the Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
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22
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Kara D, Fan M, Hamilton J, Griswold M, Seiberlich N, Brown R. Parameter map error due to normal noise and aliasing artifacts in MR fingerprinting. Magn Reson Med 2019; 81:3108-3123. [PMID: 30671999 DOI: 10.1002/mrm.27638] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2018] [Revised: 10/11/2018] [Accepted: 11/21/2018] [Indexed: 11/10/2022]
Abstract
PURPOSE To introduce a quantitative tool that enables rapid forecasting of T1 and T2 parameter map errors due to normal and aliasing noise as a function of the MR fingerprinting (MRF) sequence, which can be used in sequence optimization. THEORY AND METHODS The variances of normal noise and aliasing artifacts in the collected signal are related to the variances in T1 and T2 maps through derived quality factors. This analytical result is tested against the results of a Monte-Carlo approach for analyzing MRF sequence encoding capability in the presence of aliasing noise, and verified with phantom experiments at 3 T. To further show the utility of our approach, our quality factors are used to find efficient MRF sequences for fewer repetitions. RESULTS Experimental results verify the ability of our quality factors to rapidly assess the efficiency of an MRF sequence in the presence of both normal and aliasing noise. Quality factor assessment of MRF sequences is in agreement with the results of a Monte-Carlo approach. Analysis of MRF parameter map errors from phantom experiments is consistent with the derived quality factors, with T1 (T2 ) data yielding goodness of fit R2 ≥ 0.92 (0.80). In phantom and in vivo experiments, the efficient pulse sequence, determined through quality factor maximization, led to comparable or improved accuracy and precision relative to a longer sequence, demonstrating quality factor utility in MRF sequence design. CONCLUSION The here introduced quality factor framework allows for rapid analysis and optimization of MRF sequence design through T1 and T2 error forecasting.
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Affiliation(s)
- Danielle Kara
- Physics, Case Western Reserve University, Cleveland, Ohio
| | - Mingdong Fan
- Physics, Case Western Reserve University, Cleveland, Ohio
| | - Jesse Hamilton
- Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio
| | - Mark Griswold
- Physics, Case Western Reserve University, Cleveland, Ohio.,Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio.,Radiology, Case Western Reserve University, Cleveland, Ohio
| | - Nicole Seiberlich
- Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio.,Radiology, Case Western Reserve University, Cleveland, Ohio
| | - Robert Brown
- Physics, Case Western Reserve University, Cleveland, Ohio
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23
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Effect of spiral undersampling patterns on FISP MRF parameter maps. Magn Reson Imaging 2019; 62:174-180. [PMID: 30654162 DOI: 10.1016/j.mri.2019.01.011] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2018] [Revised: 01/11/2019] [Accepted: 01/12/2019] [Indexed: 12/18/2022]
Abstract
PURPOSE Artifacts arising from undersampling are not always treatable as incoherent noise for the pattern matching process in Magnetic Resonance Fingerprinting (MRF). To estimate the effect of undersampling artifacts on MRF quantitative results, spiral sampling trajectories and their temporal variation is examined. METHODS The effect of sampling trajectories and their variation during the MRF experiment was assessed by characterizing aliasing artifacts. Temporal rearrangements of sampling trajectories were tested and evaluated in simulations and scans of phantoms and in a volunteer brain. RESULTS Results show that some temporal variations of sampling patterns can lead to spatial biases in MRF parameter maps. Observed effects are consistent with derived performance indicators for different interleaving schemes, leading to substantially improved MRF sampling patterns. CONCLUSION With the help of the presented simulation framework, MRF implementations can be investigated and improved. This was demonstrated for a spiral FISP (Fast imaging with steady-state free precession) MRF implementation, where a significantly improved interleaving scheme was identified, and confirmed by experiment.
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24
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Kooraki S, Assadi M, Gholamrezanezhad A. Hot Topics of Research in Musculoskeletal Imaging. PET Clin 2019; 14:175-182. [DOI: 10.1016/j.cpet.2018.08.014] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
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25
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Koolstra K, Beenakker JWM, Koken P, Webb A, Börnert P. Cartesian MR fingerprinting in the eye at 7T using compressed sensing and matrix completion-based reconstructions. Magn Reson Med 2018; 81:2551-2565. [PMID: 30421448 PMCID: PMC6519255 DOI: 10.1002/mrm.27594] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2018] [Revised: 10/09/2018] [Accepted: 10/12/2018] [Indexed: 12/14/2022]
Abstract
PURPOSE To explore the feasibility of MR Fingerprinting (MRF) to rapidly quantify relaxation times in the human eye at 7T, and to provide a data acquisition and processing framework for future tissue characterization in eye tumor patients. METHODS In this single-element receive coil MRF approach with Cartesian sampling, undersampling is used to shorten scan time and, therefore, to reduce the degree of motion artifacts. For reconstruction, approaches based on compressed sensing (CS) and matrix completion (MC) were used, while their effects on the quality of the MRF parameter maps were studied in simulations and experiments. Average relaxation times in the eye were measured in 6 healthy volunteers. One uveal melanoma patient was included to show the feasibility of MRF in a clinical context. RESULTS Simulation results showed that an MC-based reconstruction enables large undersampling factors and also results in more accurate parameter maps compared with using CS. Experiments in 6 healthy volunteers used a reduction in scan time from 7:02 to 1:16 min, producing images without visible loss of detail in the parameter maps when using the MC-based reconstruction. Relaxation times from 6 healthy volunteers are in agreement with values obtained from fully sampled scans and values in literature, and parameter maps in a uveal melanoma patient show clear difference in relaxation times between tumor and healthy tissue. CONCLUSION Cartesian-based MRF is feasible in the eye at 7T. High undersampling factors can be achieved by means of MC, significantly shortening scan time and increasing patient comfort, while also mitigating the risk of motion artifacts.
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Affiliation(s)
- Kirsten Koolstra
- Radiology, C.J. Gorter Center for High-Field MRI, Leiden University Medical Center, Leiden, The Netherlands
| | - Jan-Willem Maria Beenakker
- Radiology, C.J. Gorter Center for High-Field MRI, Leiden University Medical Center, Leiden, The Netherlands.,Ophthalmology, Leiden University Medical Center, Leiden, The Netherlands
| | | | - Andrew Webb
- Radiology, C.J. Gorter Center for High-Field MRI, Leiden University Medical Center, Leiden, The Netherlands
| | - Peter Börnert
- Radiology, C.J. Gorter Center for High-Field MRI, Leiden University Medical Center, Leiden, The Netherlands.,Philips Research, Hamburg, Germany
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26
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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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27
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Bipin Mehta B, Coppo S, Frances McGivney D, Ian Hamilton J, Chen Y, Jiang Y, Ma D, Seiberlich N, Gulani V, Alan Griswold M. Magnetic resonance fingerprinting: a technical review. Magn Reson Med 2018; 81:25-46. [PMID: 30277265 DOI: 10.1002/mrm.27403] [Citation(s) in RCA: 56] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2017] [Revised: 05/01/2018] [Accepted: 05/21/2018] [Indexed: 01/31/2023]
Abstract
Multiparametric quantitative imaging is gaining increasing interest due to its widespread advantages in clinical applications. Magnetic resonance fingerprinting is a recently introduced approach of fast multiparametric quantitative imaging. In this article, magnetic resonance fingerprinting acquisition, dictionary generation, reconstruction, and validation are reviewed.
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Affiliation(s)
- Bhairav Bipin Mehta
- Department of Radiology, Case Western Reserve Universityand University Hospitals Cleveland Medical Center, Cleveland, Ohio
| | - Simone Coppo
- Department of Radiology, Case Western Reserve Universityand University Hospitals Cleveland Medical Center, Cleveland, Ohio
| | - Debra Frances McGivney
- Department of Radiology, Case Western Reserve Universityand University Hospitals Cleveland Medical Center, Cleveland, Ohio
| | - Jesse Ian Hamilton
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio
| | - Yong Chen
- Department of Radiology, Case Western Reserve Universityand University Hospitals Cleveland Medical Center, Cleveland, Ohio
| | - Yun Jiang
- Department of Radiology, Case Western Reserve Universityand University Hospitals Cleveland Medical Center, Cleveland, Ohio
| | - Dan Ma
- Department of Radiology, Case Western Reserve Universityand University Hospitals Cleveland Medical Center, Cleveland, Ohio
| | - Nicole Seiberlich
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio
| | - Vikas Gulani
- Department of Radiology, Case Western Reserve Universityand University Hospitals Cleveland Medical Center, Cleveland, Ohio.,Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio
| | - Mark Alan Griswold
- Department of Radiology, Case Western Reserve Universityand University Hospitals Cleveland Medical Center, Cleveland, Ohio.,Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio
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28
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Kobayashi Y, Terada Y. Diffusion-weighting Caused by Spoiler Gradients in the Fast Imaging with Steady-state Precession Sequence May Lead to Inaccurate T 2 Measurements in MR Fingerprinting. Magn Reson Med Sci 2018; 18:96-104. [PMID: 29794408 PMCID: PMC6326765 DOI: 10.2463/mrms.tn.2018-0027] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Abstract
Magnetic resonance fingerprinting (MRF) is a promising framework that allows the quantification of multiple magnetic resonance parameters with a single scan. MRF using fast imaging with steady-state precession (MRF-FISP) has robustness to off-resonance artifacts and has many applications in inhomogeneous fields. However, the spoiler gradient used in MRF-FISP is sensitive to diffusion motion, and may lead to quantification errors when the spoiler moment increases. In this study, we examined the effect of the diffusion weighting in MRF-FISP caused by spoiler gradients. The T2 relaxation times were greatly underestimated when large spoiler moments were used. The T2 underestimation was prominent for tissues with large values of T2 and diffusion coefficients. The T2 bias was almost independent of the apparent diffusion coefficient (ADC) and T2 values when the ADC map was measured and incorporated into the matching process. These results reveal that the T2 underestimation resulted from the diffusion weighting caused by the spoiler gradients.
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Gu Y, Wang CY, Anderson CE, Liu Y, Hu H, Johansen ML, Ma D, Jiang Y, Ramos-Estebanez C, Brady-Kalnay S, Griswold MA, Flask CA, Yu X. Fast magnetic resonance fingerprinting for dynamic contrast-enhanced studies in mice. Magn Reson Med 2018; 80:2681-2690. [PMID: 29744935 DOI: 10.1002/mrm.27345] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2017] [Revised: 03/12/2018] [Accepted: 04/13/2018] [Indexed: 12/11/2022]
Abstract
PURPOSE The goal of this study was to develop a fast MR fingerprinting (MRF) method for simultaneous T1 and T2 mapping in DCE-MRI studies in mice. METHODS The MRF sequences based on balanced SSFP and fast imaging with steady-state precession were implemented and evaluated on a 7T preclinical scanner. The readout used a zeroth-moment-compensated variable-density spiral trajectory that fully sampled the entire k-space and the inner 10 × 10 k-space with 48 and 4 interleaves, respectively. In vitro and in vivo studies of mouse brain were performed to evaluate the accuracy of MRF measurements with both fully sampled and undersampled data. The application of MRF to dynamic T1 and T2 mapping in DCE-MRI studies were demonstrated in a mouse model of heterotopic glioblastoma using gadolinium-based and dysprosium-based contrast agents. RESULTS The T1 and T2 measurements in phantom showed strong agreement between the MRF and the conventional methods. The MRF with spiral encoding allowed up to 8-fold undersampling without loss of measurement accuracy. This enabled simultaneous T1 and T2 mapping with 2-minute temporal resolution in DCE-MRI studies. CONCLUSION Magnetic resonance fingerprinting provides the opportunity for dynamic quantification of contrast agent distribution in preclinical tumor models on high-field MRI scanners.
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Affiliation(s)
- Yuning Gu
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio
| | - Charlie Y Wang
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio
| | - Christian E Anderson
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio
| | - Yuchi Liu
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio
| | - He Hu
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio
| | - Mette L Johansen
- Department of Molecular Biology and Microbiology, Case Western Reserve University, Cleveland, Ohio
| | - Dan Ma
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio
| | - Yun Jiang
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio
| | | | - Susann Brady-Kalnay
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio.,Department of Neurosciences, Case Western Reserve University, Cleveland, Ohio
| | - Mark A Griswold
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio.,Department of Radiology, Case Western Reserve University, Cleveland, Ohio
| | - Chris A Flask
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio.,Department of Radiology, Case Western Reserve University, Cleveland, Ohio.,Department of Pediatrics, Case Western Reserve University, Cleveland, Ohio
| | - Xin Yu
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio.,Department of Radiology, Case Western Reserve University, Cleveland, Ohio.,Department of Physiology and Biophysics, Case Western Reserve University, Cleveland, Ohio
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Erokwu BO, Anderson CE, Flask CA, Dell KM. Quantitative magnetic resonance imaging assessments of autosomal recessive polycystic kidney disease progression and response to therapy in an animal model. Pediatr Res 2018. [PMID: 29538364 DOI: 10.1038/pr.2018.24] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
BackgroundAutosomal recessive polycystic kidney disease (ARPKD) is associated with significant mortality and morbidity, and currently, there are no disease-specific treatments available for ARPKD patients. One major limitation in establishing new therapies for ARPKD is a lack of sensitive measures of kidney disease progression. Magnetic resonance imaging (MRI) can provide multiple quantitative assessments of the disease.MethodsWe applied quantitative image analysis of high-resolution (noncontrast) T2-weighted MRI techniques to study cystic kidney disease progression and response to therapy in the PCK rat model of ARPKD.ResultsSerial imaging over a 2-month period demonstrated that renal cystic burden (RCB, %)=[total cyst volume (TCV)/total kidney volume (TKV) × 100], TCV, and, to a lesser extent, TKV detected cystic kidney disease progression, as well as the therapeutic effect of octreotide, a clinically available medication shown previously to slow both kidney and liver disease progression in this model. All three MRI measures correlated significantly with histologic measures of renal cystic area, although the correlation of RCB and TCV was stronger than that of TKV.ConclusionThese preclinical MRI results provide a basis for applying these quantitative MRI techniques in clinical studies, to stage and measure progression in human ARPKD kidney disease.
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Affiliation(s)
| | | | - Chris A Flask
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio
| | - Katherine M Dell
- Department of Pediatrics, Case Western Reserve University, Cleveland, Ohio
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Ma D, Jiang Y, Chen Y, McGivney D, Mehta B, Gulani V, Griswold M. Fast 3D magnetic resonance fingerprinting for a whole-brain coverage. Magn Reson Med 2018; 79:2190-2197. [PMID: 28833436 PMCID: PMC5868964 DOI: 10.1002/mrm.26886] [Citation(s) in RCA: 103] [Impact Index Per Article: 17.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2017] [Revised: 07/19/2017] [Accepted: 08/03/2017] [Indexed: 12/24/2022]
Abstract
PURPOSE The purpose of this study was to accelerate the acquisition and reconstruction time of 3D magnetic resonance fingerprinting scans. METHODS A 3D magnetic resonance fingerprinting scan was accelerated by using a single-shot spiral trajectory with an undersampling factor of 48 in the x-y plane, and an interleaved sampling pattern with an undersampling factor of 3 through plane. Further acceleration came from reducing the waiting time between neighboring partitions. The reconstruction time was accelerated by applying singular value decomposition compression in k-space. Finally, a 3D premeasured B1 map was used to correct for the B1 inhomogeneity. RESULTS The T1 and T2 values of the International Society for Magnetic Resonance in Medicine/National Institute of Standards and Technology MRI phantom showed a good agreement with the standard values, with an average concordance correlation coefficient of 0.99, and coefficient of variation of 7% in the repeatability scans. The results from in vivo scans also showed high image quality in both transverse and coronal views. CONCLUSIONS This study applied a fast acquisition scheme for a fully quantitative 3D magnetic resonance fingerprinting scan with a total acceleration factor of 144 as compared with the Nyquist rate, such that 3D T1 , T2 , and proton density maps can be acquired with whole-brain coverage at clinical resolution in less than 5 min. Magn Reson Med 79:2190-2197, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Dan Ma
- Department of Radiology, Case Western Reserve University, Cleveland, OH
| | - Yun Jiang
- Department of Radiology, Case Western Reserve University, Cleveland, OH
| | - Yong Chen
- Department of Radiology, Case Western Reserve University, Cleveland, OH
| | - Debra McGivney
- Department of Radiology, Case Western Reserve University, Cleveland, OH
| | - Bhairav Mehta
- Department of Radiology, Case Western Reserve University, Cleveland, OH
| | - Vikas Gulani
- Department of Radiology, Case Western Reserve University, Cleveland, OH
| | - Mark Griswold
- Department of Radiology, Case Western Reserve University, Cleveland, OH
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Liao C, Bilgic B, Manhard MK, Zhao B, Cao X, Zhong J, Wald LL, Setsompop K. 3D MR fingerprinting with accelerated stack-of-spirals and hybrid sliding-window and GRAPPA reconstruction. Neuroimage 2017; 162:13-22. [PMID: 28842384 PMCID: PMC6031129 DOI: 10.1016/j.neuroimage.2017.08.030] [Citation(s) in RCA: 78] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2017] [Revised: 07/02/2017] [Accepted: 08/09/2017] [Indexed: 12/13/2022] Open
Abstract
PURPOSE Whole-brain high-resolution quantitative imaging is extremely encoding intensive, and its rapid and robust acquisition remains a challenge. Here we present a 3D MR fingerprinting (MRF) acquisition with a hybrid sliding-window (SW) and GRAPPA reconstruction strategy to obtain high-resolution T1, T2 and proton density (PD) maps with whole brain coverage in a clinically feasible timeframe. METHODS 3D MRF data were acquired using a highly under-sampled stack-of-spirals trajectory with a steady-state precession (FISP) sequence. For data reconstruction, kx-ky under-sampling was mitigated using SW combination along the temporal axis. Non-uniform fast Fourier transform (NUFFT) was then applied to create Cartesian k-space data that are fully-sampled in the in-plane direction, and Cartesian GRAPPA was performed to resolve kz under-sampling to create an alias-free SW dataset. T1, T2 and PD maps were then obtained using dictionary matching. RESULTS Phantom study demonstrated that the proposed 3D-MRF acquisition/reconstruction method is able to produce quantitative maps that are consistent with conventional quantification techniques. Retrospectively under-sampled in vivo acquisition revealed that SW + GRAPPA substantially improves quantification accuracy over the current state-of-the-art accelerated 3D MRF. Prospectively under-sampled in vivo study showed that whole brain T1, T2 and PD maps with 1 mm3 resolution could be obtained in 7.5 min. CONCLUSIONS 3D MRF stack-of-spirals acquisition with hybrid SW + GRAPPA reconstruction may provide a feasible approach for rapid, high-resolution quantitative whole-brain imaging.
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Affiliation(s)
- Congyu Liao
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, Zhejiang, China; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, 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
| | - 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
| | - Bo Zhao
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Xiaozhi Cao
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Jianhui Zhong
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, Zhejiang, China.
| | - Lawrence L Wald
- 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
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Panda A, Mehta BB, Coppo S, Jiang Y, Ma D, Seiberlich N, Griswold MA, Gulani V. Magnetic Resonance Fingerprinting-An Overview. CURRENT OPINION IN BIOMEDICAL ENGINEERING 2017; 3:56-66. [PMID: 29868647 DOI: 10.1016/j.cobme.2017.11.001] [Citation(s) in RCA: 61] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Magnetic Resonance Fingerprinting (MRF) is a new approach to quantitative magnetic resonance imaging that allows simultaneous measurement of multiple tissue properties in a single, time-efficient acquisition. The ability to reproducibly and quantitatively measure tissue properties could enable more objective tissue diagnosis, comparisons of scans acquired at different locations and time points, longitudinal follow-up of individual patients and development of imaging biomarkers. This review provides a general overview of MRF technology, current preclinical and clinical applications and potential future directions. MRF has been initially evaluated in brain, prostate, liver, cardiac, musculoskeletal imaging, and measurement of perfusion and microvascular properties through MR vascular fingerprinting.
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Affiliation(s)
- Ananya Panda
- Department of Radiology, Case Western Reserve University, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Bhairav B Mehta
- Department of Radiology, Case Western Reserve University, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Simone Coppo
- Department of Radiology, Case Western Reserve University, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Yun Jiang
- Department of Biomedical Engineering, Case Western Reserve University, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Dan Ma
- Department of Radiology, Case Western Reserve University, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Nicole Seiberlich
- Department of Radiology, Case Western Reserve University, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA.,Department of Biomedical Engineering, Case Western Reserve University, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Mark A Griswold
- Department of Radiology, Case Western Reserve University, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA.,Department of Biomedical Engineering, Case Western Reserve University, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
| | - Vikas Gulani
- Department of Radiology, Case Western Reserve University, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA.,Department of Biomedical Engineering, Case Western Reserve University, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA
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34
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Cohen O, Rosen MS. Algorithm comparison for schedule optimization in MR fingerprinting. Magn Reson Imaging 2017; 41:15-21. [DOI: 10.1016/j.mri.2017.02.010] [Citation(s) in RCA: 45] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2016] [Revised: 02/15/2017] [Accepted: 02/20/2017] [Indexed: 11/30/2022]
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35
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Cline CC, Chen X, Mailhe B, Wang Q, Pfeuffer J, Nittka M, Griswold MA, Speier P, Nadar MS. AIR-MRF: Accelerated iterative reconstruction for magnetic resonance fingerprinting. Magn Reson Imaging 2017; 41:29-40. [DOI: 10.1016/j.mri.2017.07.007] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2016] [Revised: 07/10/2017] [Accepted: 07/10/2017] [Indexed: 10/19/2022]
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Dual Contrast - Magnetic Resonance Fingerprinting (DC-MRF): A Platform for Simultaneous Quantification of Multiple MRI Contrast Agents. Sci Rep 2017; 7:8431. [PMID: 28814732 PMCID: PMC5559598 DOI: 10.1038/s41598-017-08762-9] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2017] [Accepted: 07/12/2017] [Indexed: 01/21/2023] Open
Abstract
Injectable Magnetic Resonance Imaging (MRI) contrast agents have been widely used to provide critical assessments of disease for both clinical and basic science imaging research studies. The scope of available MRI contrast agents has expanded over the years with the emergence of molecular imaging contrast agents specifically targeted to biological markers. Unfortunately, synergistic application of more than a single molecular contrast agent has been limited by MRI's ability to only dynamically measure a single agent at a time. In this study, a new Dual Contrast - Magnetic Resonance Fingerprinting (DC - MRF) methodology is described that can detect and independently quantify the local concentration of multiple MRI contrast agents following simultaneous administration. This "multi-color" MRI methodology provides the opportunity to monitor multiple molecular species simultaneously and provides a practical, quantitative imaging framework for the eventual clinical translation of molecular imaging contrast agents.
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Anderson CE, Wang CY, Gu Y, Darrah R, Griswold MA, Yu X, Flask CA. Regularly incremented phase encoding - MR fingerprinting (RIPE-MRF) for enhanced motion artifact suppression in preclinical cartesian MR fingerprinting. Magn Reson Med 2017; 79:2176-2182. [PMID: 28796368 DOI: 10.1002/mrm.26865] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2017] [Accepted: 07/19/2017] [Indexed: 12/11/2022]
Abstract
PURPOSE The regularly incremented phase encoding-magnetic resonance fingerprinting (RIPE-MRF) method is introduced to limit the sensitivity of preclinical MRF assessments to pulsatile and respiratory motion artifacts. METHODS As compared to previously reported standard Cartesian-MRF methods (SC-MRF), the proposed RIPE-MRF method uses a modified Cartesian trajectory that varies the acquired phase-encoding line within each dynamic MRF dataset. Phantoms and mice were scanned without gating or triggering on a 7T preclinical MRI scanner using the RIPE-MRF and SC-MRF methods. In vitro phantom longitudinal relaxation time (T1 ) and transverse relaxation time (T2 ) measurements, as well as in vivo liver assessments of artifact-to-noise ratio (ANR) and MRF-based T1 and T2 mean and standard deviation, were compared between the two methods (n = 5). RESULTS RIPE-MRF showed significant ANR reductions in regions of pulsatility (P < 0.005) and respiratory motion (P < 0.0005). RIPE-MRF also exhibited improved precision in T1 and T2 measurements in comparison to the SC-MRF method (P < 0.05). The RIPE-MRF and SC-MRF methods displayed similar mean T1 and T2 estimates (difference in mean values < 10%). CONCLUSION These results show that the RIPE-MRF method can provide effective motion artifact suppression with minimal impact on T1 and T2 accuracy for in vivo small animal MRI studies. Magn Reson Med 79:2176-2182, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Christian E Anderson
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA.,Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Charlie Y Wang
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Yuning Gu
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Rebecca Darrah
- Frances Payne Bolton School of Nursing, Case Western Reserve University, Cleveland, Ohio, USA.,Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, Ohio, USA
| | - Mark A Griswold
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA.,Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Xin Yu
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.,Department of Physiology and Biophysics, Case Western Reserve University, Cleveland, Ohio, USA
| | - Chris A Flask
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA.,Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.,Department of Pediatrics, Case Western Reserve University, Cleveland, Ohio, USA
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Abstract
Modern imaging techniques, particularly functional imaging techniques that interrogate some specific aspect of underlying tumor biology, have enormous potential in neuro-oncology for disease detection, grading, and tumor delineation to guide biopsy and resection; monitoring treatment response; and targeting radiotherapy. This brief review considers the role of magnetic resonance imaging and spectroscopy, and positron emission tomography in these areas and discusses the factors that limit translation of new techniques to the clinic, in particular, the cost and difficulties associated with validation in multicenter clinical trials.
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Affiliation(s)
- Kevin M Brindle
- Kevin M. Brindle, Richard J. Mair, and Alan J. Wright, Cancer Research UK Cambridge Institute, Cambridge; David Y. Lewis, Cancer Research UK Beatson Institute, Glasgow, United Kingdom; José L. Izquierdo-García, Fundación Centro Nacional de Investigaciones Cardiovasculares Carlos III and Centro de Investigación Biomédica en Red Enfermedades Respiratorias, Madrid, Spain
| | - José L Izquierdo-García
- Kevin M. Brindle, Richard J. Mair, and Alan J. Wright, Cancer Research UK Cambridge Institute, Cambridge; David Y. Lewis, Cancer Research UK Beatson Institute, Glasgow, United Kingdom; José L. Izquierdo-García, Fundación Centro Nacional de Investigaciones Cardiovasculares Carlos III and Centro de Investigación Biomédica en Red Enfermedades Respiratorias, Madrid, Spain
| | - David Y Lewis
- Kevin M. Brindle, Richard J. Mair, and Alan J. Wright, Cancer Research UK Cambridge Institute, Cambridge; David Y. Lewis, Cancer Research UK Beatson Institute, Glasgow, United Kingdom; José L. Izquierdo-García, Fundación Centro Nacional de Investigaciones Cardiovasculares Carlos III and Centro de Investigación Biomédica en Red Enfermedades Respiratorias, Madrid, Spain
| | - Richard J Mair
- Kevin M. Brindle, Richard J. Mair, and Alan J. Wright, Cancer Research UK Cambridge Institute, Cambridge; David Y. Lewis, Cancer Research UK Beatson Institute, Glasgow, United Kingdom; José L. Izquierdo-García, Fundación Centro Nacional de Investigaciones Cardiovasculares Carlos III and Centro de Investigación Biomédica en Red Enfermedades Respiratorias, Madrid, Spain
| | - Alan J Wright
- Kevin M. Brindle, Richard J. Mair, and Alan J. Wright, Cancer Research UK Cambridge Institute, Cambridge; David Y. Lewis, Cancer Research UK Beatson Institute, Glasgow, United Kingdom; José L. Izquierdo-García, Fundación Centro Nacional de Investigaciones Cardiovasculares Carlos III and Centro de Investigación Biomédica en Red Enfermedades Respiratorias, Madrid, Spain
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Zhao B, Setsompop K, Adalsteinsson E, Gagoski B, Ye H, Ma D, Jiang Y, Ellen Grant P, Griswold MA, Wald LL. Improved magnetic resonance fingerprinting reconstruction with low-rank and subspace modeling. Magn Reson Med 2017; 79:933-942. [PMID: 28411394 DOI: 10.1002/mrm.26701] [Citation(s) in RCA: 101] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2016] [Revised: 03/14/2017] [Accepted: 03/14/2017] [Indexed: 12/11/2022]
Abstract
PURPOSE This article introduces a constrained imaging method based on low-rank and subspace modeling to improve the accuracy and speed of MR fingerprinting (MRF). THEORY AND METHODS A new model-based imaging method is developed for MRF to reconstruct high-quality time-series images and accurate tissue parameter maps (e.g., T1 , T2 , and spin density maps). Specifically, the proposed method exploits low-rank approximations of MRF time-series images, and further enforces temporal subspace constraints to capture magnetization dynamics. This allows the time-series image reconstruction problem to be formulated as a simple linear least-squares problem, which enables efficient computation. After image reconstruction, tissue parameter maps are estimated via dictionary-based pattern matching, as in the conventional approach. RESULTS The effectiveness of the proposed method was evaluated with in vivo experiments. Compared with the conventional MRF reconstruction, the proposed method reconstructs time-series images with significantly reduced aliasing artifacts and noise contamination. Although the conventional approach exhibits some robustness to these corruptions, the improved time-series image reconstruction in turn provides more accurate tissue parameter maps. The improvement is pronounced especially when the acquisition time becomes short. CONCLUSIONS The proposed method significantly improves the accuracy of MRF, and also reduces data acquisition time. Magn Reson Med 79:933-942, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Bo Zhao
- 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.,Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA.,Harvard-MIT Division of Health Sciences and Technology, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Elfar Adalsteinsson
- Harvard-MIT Division of Health Sciences and Technology, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.,Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Borjan Gagoski
- Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA.,Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Huihui Ye
- Department of Optical Engineering, Zhejiang University, Hangzhou, China
| | - Dan Ma
- Department of Radiology, Case Western Reserve University and University Hospitals of Cleveland, Cleveland, Ohio, USA
| | - Yun Jiang
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - P Ellen Grant
- Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA.,Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Mark A Griswold
- Department of Radiology, Case Western Reserve University and University Hospitals of Cleveland, Cleveland, Ohio, USA.,Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Lawrence L Wald
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA.,Harvard-MIT Division of Health Sciences and Technology, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
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40
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Chiu SC, Lin TM, Lin JM, Chung HW, Ko CW, Büchert M, Bock M. Effects of RF pulse profile and intra-voxel phase dispersion on MR fingerprinting with balanced SSFP readout. Magn Reson Imaging 2017; 41:80-86. [PMID: 28412455 DOI: 10.1016/j.mri.2017.04.002] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2016] [Revised: 04/10/2017] [Accepted: 04/11/2017] [Indexed: 01/29/2023]
Abstract
PURPOSE To investigate possible errors in T1 and T2 quantification via MR fingerprinting with balanced steady-state free precession readout in the presence of intra-voxel phase dispersion and RF pulse profile imperfections, using computer simulations based on Bloch equations. MATERIALS AND METHODS A pulse sequence with TR changing in a Perlin noise pattern and a nearly sinusoidal pattern of flip angle following an initial 180-degree inversion pulse was employed. Gaussian distributions of off-resonance frequency were assumed for intra-voxel phase dispersion effects. Slice profiles of sinc-shaped RF pulses were computed to investigate flip angle profile influences. Following identification of the best fit between the acquisition signals and those established in the dictionary based on known parameters, estimation errors were reported. In vivo experiments were performed at 3T to examine the results. RESULTS Slight intra-voxel phase dispersion with standard deviations from 1 to 3Hz resulted in prominent T2 under-estimations, particularly at large T2 values. T1 and off-resonance frequencies were relatively unaffected. Slice profile imperfections led to under-estimations of T1, which became greater as regional off-resonance frequencies increased, but could be corrected by including slice profile effects in the dictionary. Results from brain imaging experiments in vivo agreed with the simulation results qualitatively. CONCLUSION MR fingerprinting using balanced SSFP readout in the presence of intra-voxel phase dispersion and imperfect slice profile leads to inaccuracies in quantitative estimations of the relaxation times.
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41
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Hong T, Han D, Kim MO, Kim DH. RF slice profile effects in magnetic resonance fingerprinting. Magn Reson Imaging 2017; 41:73-79. [PMID: 28391061 DOI: 10.1016/j.mri.2017.04.001] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2016] [Revised: 04/04/2017] [Accepted: 04/04/2017] [Indexed: 12/19/2022]
Abstract
The radio frequency (RF) slice profile effects on T1 and T2 estimation in magnetic resonance fingerprinting (MRF) are investigated with respect to time-bandwidth product (TBW), flip angle (FA) level and field inhomogeneities. Signal evolutions are generated incorporating the non-ideal slice selective excitation process using Bloch simulation and matched to the original dictionary with and without the non-ideal slice profile taken into account. For validation, phantom and in vivo experiments are performed at 3T. Both simulations and experiments results show that T1 and T2 error from non-ideal slice profile increases with increasing FA level, off-resonance, and low TBW values. Therefore, RF slice profile effects should be compensated for accurate determination of the MR parameters.
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Affiliation(s)
- Taehwa Hong
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Dongyeob Han
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Min-Oh Kim
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Dong-Hyun Kim
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea.
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42
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Ma D, Coppo S, Chen Y, McGivney DF, Jiang Y, Pahwa S, Gulani V, Griswold MA. Slice profile and B 1 corrections in 2D magnetic resonance fingerprinting. Magn Reson Med 2017; 78:1781-1789. [PMID: 28074530 DOI: 10.1002/mrm.26580] [Citation(s) in RCA: 125] [Impact Index Per Article: 17.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2016] [Revised: 11/17/2016] [Accepted: 11/21/2016] [Indexed: 11/12/2022]
Abstract
PURPOSE The goal of this study is to characterize and improve the accuracy of 2D magnetic resonance fingerprinting (MRF) scans in the presence of slice profile (SP) and B1 imperfections, which are two main factors that affect quantitative results in MRF. METHODS The SP and B1 imperfections are characterized and corrected separately. The SP effect is corrected by simulating the radiofrequency pulse in the dictionary, and the B1 is corrected by acquiring a B1 map using the Bloch-Siegert method before each scan. The accuracy, precision, and repeatability of the proposed method are evaluated in phantom studies. The effects of both SP and B1 imperfections are also illustrated and corrected in the in vivo studies. RESULTS The SP and B1 corrections improve the accuracy of the T1 and T2 values, independent of the shape of the radiofrequency pulse. The T1 and T2 values obtained from different excitation patterns become more consistent after corrections, which leads to an improvement of the robustness of the MRF design. CONCLUSION This study demonstrates that MRF is sensitive to both SP and B1 effects, and that corrections can be made to improve the accuracy of MRF with only a 2-s increase in acquisition time. Magn Reson Med 78:1781-1789, 2017. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Dan Ma
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA
| | - Simone Coppo
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA
| | - Yong Chen
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA
| | - Debra F McGivney
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA
| | - Yun Jiang
- Biomedical Engineering Department, Case Western Reserve University, Cleveland, Ohio, USA
| | - Shivani Pahwa
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA
| | - Vikas Gulani
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA
| | - Mark A Griswold
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA
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43
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Pastor G, Jiménez-González M, Plaza-García S, Beraza M, Reese T. Fast T1 and T2 mapping methods: the zoomed U-FLARE sequence compared with EPI and snapshot-FLASH for abdominal imaging at 11.7 Tesla. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2017; 30:299-307. [DOI: 10.1007/s10334-016-0604-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2016] [Revised: 12/07/2016] [Accepted: 12/08/2016] [Indexed: 10/20/2022]
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Pouliot P, Gagnon L, Lam T, Avti PK, Bowen C, Desjardins M, Kakkar AK, Thorin E, Sakadzic S, Boas DA, Lesage F. Magnetic resonance fingerprinting based on realistic vasculature in mice. Neuroimage 2016; 149:436-445. [PMID: 28043909 DOI: 10.1016/j.neuroimage.2016.12.060] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2016] [Revised: 11/20/2016] [Accepted: 12/20/2016] [Indexed: 11/26/2022] Open
Abstract
Magnetic resonance fingerprinting (MRF) was recently proposed as a novel strategy for MR data acquisition and analysis. A variant of MRF called vascular MRF (vMRF) followed, that extracted maps of three parameters of physiological importance: cerebral oxygen saturation (SatO2), mean vessel radius and cerebral blood volume (CBV). However, this estimation was based on idealized 2-dimensional simulations of vascular networks using random cylinders and the empirical Bloch equations convolved with a diffusion kernel. Here we focus on studying the vascular MR fingerprint using real mouse angiograms and physiological values as the substrate for the MR simulations. The MR signal is calculated ab initio with a Monte Carlo approximation, by tracking the accumulated phase from a large number of protons diffusing within the angiogram. We first study the identifiability of parameters in simulations, showing that parameters are fully estimable at realistically high signal-to-noise ratios (SNR) when the same angiogram is used for dictionary generation and parameter estimation, but that large biases in the estimates persist when the angiograms are different. Despite these biases, simulations show that differences in parameters remain estimable. We then applied this methodology to data acquired using the GESFIDE sequence with SPIONs injected into 9 young wild type and 9 old atherosclerotic mice. Both the pre injection signal and the ratio of post-to-pre injection signals were modeled, using 5-dimensional dictionaries. The vMRF methodology extracted significant differences in SatO2, mean vessel radius and CBV between the two groups, consistent across brain regions and dictionaries. Further validation work is essential before vMRF can gain wider application.
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Affiliation(s)
- Philippe Pouliot
- Department of Electrical Engineering, Ecole Polytechnique Montreal, Montreal, QC, Canada; Research Centre, Montreal Heart Institute, Montreal, Canada.
| | - Louis Gagnon
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, MA, United States
| | - Tina Lam
- Department of Chemistry, McGill University, Montreal, QC, Canada
| | - Pramod K Avti
- Research Centre, Montreal Heart Institute, Montreal, Canada
| | - Chris Bowen
- Department of Diagnostic Radiology, Dalhousie University, Halifax, NS, Canada
| | - Michèle Desjardins
- Department of Electrical Engineering, Ecole Polytechnique Montreal, Montreal, QC, Canada
| | - Ashok K Kakkar
- Department of Chemistry, McGill University, Montreal, QC, Canada
| | - Eric Thorin
- Dept. of Surgery, Faculty of Medicine, University of Montreal, QC, Canada; Research Centre, Montreal Heart Institute, Montreal, Canada
| | - Sava Sakadzic
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, MA, United States
| | - David A Boas
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, MA, United States
| | - Frédéric Lesage
- Department of Electrical Engineering, Ecole Polytechnique Montreal, Montreal, QC, Canada; Research Centre, Montreal Heart Institute, Montreal, Canada
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45
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Rieger B, Zimmer F, Zapp J, Weingärtner S, Schad LR. Magnetic resonance fingerprinting using echo-planar imaging: Joint quantification of T1
and
T2∗ relaxation times. Magn Reson Med 2016; 78:1724-1733. [DOI: 10.1002/mrm.26561] [Citation(s) in RCA: 47] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2016] [Revised: 10/17/2016] [Accepted: 11/02/2016] [Indexed: 12/16/2022]
Affiliation(s)
- Benedikt Rieger
- Computer Assisted Clinical Medicine; University Medical Center Mannheim, Heidelberg University; Mannheim Germany
| | - Fabian Zimmer
- Computer Assisted Clinical Medicine; University Medical Center Mannheim, Heidelberg University; Mannheim Germany
| | - Jascha Zapp
- Computer Assisted Clinical Medicine; University Medical Center Mannheim, Heidelberg University; Mannheim Germany
| | - Sebastian Weingärtner
- Computer Assisted Clinical Medicine; University Medical Center Mannheim, Heidelberg University; Mannheim Germany
- Electrical and Computer Engineering; University of Minnesota; Minneapolis Minnesota United States
- Center for Magnetic Resonance Research; University of Minnesota; Minneapolis Minnesota United States
| | - Lothar R. Schad
- Computer Assisted Clinical Medicine; University Medical Center Mannheim, Heidelberg University; Mannheim Germany
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46
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Chen Y, Li W, Jiang K, Wang CY, Yu X. Rapid T2 mapping of mouse heart using the carr-purcell-meiboom-gill sequence and compressed sensing reconstruction. J Magn Reson Imaging 2016; 44:375-82. [PMID: 26854752 DOI: 10.1002/jmri.25175] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2015] [Accepted: 01/19/2016] [Indexed: 01/29/2023] Open
Abstract
PURPOSE To develop and prove preliminary validation of a fast in vivo T2 mapping technique for mouse heart. MATERIALS AND METHODS Magnetic resonance imaging (MRI) experiments were performed on a 7T animal scanner. The standard Carr-Purcell-Meiboom-Gill (CPMG) sequence was modified to minimize the effect of stimulated echoes for accurate T2 quantification. The acquisition was further accelerated with the compressed sensing approach. The accuracy of the proposed method was first validated with both phantom experiments and numerical simulations. In vivo T2 measurement was performed on seven mice in a manganese-enhanced MRI study. RESULTS In phantom studies, T2 values obtained with the modified CPMG sequence are in good agreement with the standard spin-echo method (P > 0.05). Numerical simulations further demonstrated that with the application of the compressed sensing approach, fast T2 quantification with a spatial resolution of 2.3 mm can be achieved at a high temporal resolution of 1 minute per slice. With the proposed technique, an average T2 value of 25 msec was observed for mouse heart at 7T and this number decreased significantly after manganese infusion (P < 0.001). CONCLUSION A rapid T2 mapping technique was developed and assessed, which allows accurate T2 quantification of mouse heart at a temporal resolution of 1 minute per slice. J. Magn. Reson. Imaging 2016;44:375-382.
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Affiliation(s)
- Yong Chen
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Wen Li
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Kai Jiang
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Charlie Y Wang
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Xin Yu
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA.,Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA.,Department of Physiology and Biophysics, Case Western Reserve University, Cleveland, Ohio, USA.,Case Center for Imaging Research, Case Western Reserve University, Cleveland, Ohio, USA
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47
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Chen Y, Jiang Y, Pahwa S, Ma D, Lu L, Twieg MD, Wright KL, Seiberlich N, Griswold MA, Gulani V. MR Fingerprinting for Rapid Quantitative Abdominal Imaging. Radiology 2016; 279:278-86. [PMID: 26794935 DOI: 10.1148/radiol.2016152037] [Citation(s) in RCA: 154] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
PURPOSE To develop a magnetic resonance (MR) "fingerprinting" technique for quantitative abdominal imaging. MATERIALS AND METHODS This HIPAA-compliant study had institutional review board approval, and informed consent was obtained from all subjects. To achieve accurate quantification in the presence of marked B0 and B1 field inhomogeneities, the MR fingerprinting framework was extended by using a two-dimensional fast imaging with steady-state free precession, or FISP, acquisition and a Bloch-Siegert B1 mapping method. The accuracy of the proposed technique was validated by using agarose phantoms. Quantitative measurements were performed in eight asymptomatic subjects and in six patients with 20 focal liver lesions. A two-tailed Student t test was used to compare the T1 and T2 results in metastatic adenocarcinoma with those in surrounding liver parenchyma and healthy subjects. RESULTS Phantom experiments showed good agreement with standard methods in T1 and T2 after B1 correction. In vivo studies demonstrated that quantitative T1, T2, and B1 maps can be acquired within a breath hold of approximately 19 seconds. T1 and T2 measurements were compatible with those in the literature. Representative values included the following: liver, 745 msec ± 65 (standard deviation) and 31 msec ± 6; renal medulla, 1702 msec ± 205 and 60 msec ± 21; renal cortex, 1314 msec ± 77 and 47 msec ± 10; spleen, 1232 msec ± 92 and 60 msec ± 19; skeletal muscle, 1100 msec ± 59 and 44 msec ± 9; and fat, 253 msec ± 42 and 77 msec ± 16, respectively. T1 and T2 in metastatic adenocarcinoma were 1673 msec ± 331 and 43 msec ± 13, respectively, significantly different from surrounding liver parenchyma relaxation times of 840 msec ± 113 and 28 msec ± 3 (P < .0001 and P < .01) and those in hepatic parenchyma in healthy volunteers (745 msec ± 65 and 31 msec ± 6, P < .0001 and P = .021, respectively). CONCLUSION A rapid technique for quantitative abdominal imaging was developed that allows simultaneous quantification of multiple tissue properties within one 19-second breath hold, with measurements comparable to those in published literature.
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Affiliation(s)
- Yong Chen
- From the Departments of Radiology (Y.C., S.P., D.M., L.L., K.L.W., M.A.G., V.G.), Biomedical Engineering (Y.J., N.S., M.A.G.), and Electrical Engineering and Computer Science (M.D.T.), Case Western Reserve University/University Hospitals Case Medical Center, 11100 Euclid Ave, Bolwell Building, Room B120, Cleveland, OH 44106
| | - Yun Jiang
- From the Departments of Radiology (Y.C., S.P., D.M., L.L., K.L.W., M.A.G., V.G.), Biomedical Engineering (Y.J., N.S., M.A.G.), and Electrical Engineering and Computer Science (M.D.T.), Case Western Reserve University/University Hospitals Case Medical Center, 11100 Euclid Ave, Bolwell Building, Room B120, Cleveland, OH 44106
| | - Shivani Pahwa
- From the Departments of Radiology (Y.C., S.P., D.M., L.L., K.L.W., M.A.G., V.G.), Biomedical Engineering (Y.J., N.S., M.A.G.), and Electrical Engineering and Computer Science (M.D.T.), Case Western Reserve University/University Hospitals Case Medical Center, 11100 Euclid Ave, Bolwell Building, Room B120, Cleveland, OH 44106
| | - Dan Ma
- From the Departments of Radiology (Y.C., S.P., D.M., L.L., K.L.W., M.A.G., V.G.), Biomedical Engineering (Y.J., N.S., M.A.G.), and Electrical Engineering and Computer Science (M.D.T.), Case Western Reserve University/University Hospitals Case Medical Center, 11100 Euclid Ave, Bolwell Building, Room B120, Cleveland, OH 44106
| | - Lan Lu
- From the Departments of Radiology (Y.C., S.P., D.M., L.L., K.L.W., M.A.G., V.G.), Biomedical Engineering (Y.J., N.S., M.A.G.), and Electrical Engineering and Computer Science (M.D.T.), Case Western Reserve University/University Hospitals Case Medical Center, 11100 Euclid Ave, Bolwell Building, Room B120, Cleveland, OH 44106
| | - Michael D Twieg
- From the Departments of Radiology (Y.C., S.P., D.M., L.L., K.L.W., M.A.G., V.G.), Biomedical Engineering (Y.J., N.S., M.A.G.), and Electrical Engineering and Computer Science (M.D.T.), Case Western Reserve University/University Hospitals Case Medical Center, 11100 Euclid Ave, Bolwell Building, Room B120, Cleveland, OH 44106
| | - Katherine L Wright
- From the Departments of Radiology (Y.C., S.P., D.M., L.L., K.L.W., M.A.G., V.G.), Biomedical Engineering (Y.J., N.S., M.A.G.), and Electrical Engineering and Computer Science (M.D.T.), Case Western Reserve University/University Hospitals Case Medical Center, 11100 Euclid Ave, Bolwell Building, Room B120, Cleveland, OH 44106
| | - Nicole Seiberlich
- From the Departments of Radiology (Y.C., S.P., D.M., L.L., K.L.W., M.A.G., V.G.), Biomedical Engineering (Y.J., N.S., M.A.G.), and Electrical Engineering and Computer Science (M.D.T.), Case Western Reserve University/University Hospitals Case Medical Center, 11100 Euclid Ave, Bolwell Building, Room B120, Cleveland, OH 44106
| | - Mark A Griswold
- From the Departments of Radiology (Y.C., S.P., D.M., L.L., K.L.W., M.A.G., V.G.), Biomedical Engineering (Y.J., N.S., M.A.G.), and Electrical Engineering and Computer Science (M.D.T.), Case Western Reserve University/University Hospitals Case Medical Center, 11100 Euclid Ave, Bolwell Building, Room B120, Cleveland, OH 44106
| | - Vikas Gulani
- From the Departments of Radiology (Y.C., S.P., D.M., L.L., K.L.W., M.A.G., V.G.), Biomedical Engineering (Y.J., N.S., M.A.G.), and Electrical Engineering and Computer Science (M.D.T.), Case Western Reserve University/University Hospitals Case Medical Center, 11100 Euclid Ave, Bolwell Building, Room B120, Cleveland, OH 44106
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Buonincontri G, Sawiak SJ. MR fingerprinting with simultaneous B1 estimation. Magn Reson Med 2015; 76:1127-35. [PMID: 26509746 PMCID: PMC5061105 DOI: 10.1002/mrm.26009] [Citation(s) in RCA: 100] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2015] [Revised: 09/14/2015] [Accepted: 09/14/2015] [Indexed: 12/12/2022]
Abstract
PURPOSE MR fingerprinting (MRF) can be used for quantitative estimation of physical parameters in MRI. Here, we extend the method to incorporate B1 estimation. METHODS The acquisition is based on steady state free precession MR fingerprinting with a Cartesian trajectory. To increase the sensitivity to the B1 profile, abrupt changes in flip angle were introduced in the sequence. Slice profile and B1 effects were included in the dictionary and the results from two- and three-dimensional (3D) acquisitions were compared. Acceleration was demonstrated using retrospective undersampling in the phase encode directions of 3D data exploiting redundancy between MRF frames at the edges of k-space. RESULTS Without B1 estimation, T2 and B1 were inaccurate by more than 20%. Abrupt changes in flip angle improved B1 maps. T1 and T2 values obtained with the new MRF methods agree with classical spin echo measurements and are independent of the B1 field profile. When using view sharing reconstruction, results remained accurate (error <10%) when sampling under 10% of k-space from the 3D data. CONCLUSION The methods demonstrated here can successfully measure T1, T2, and B1. Errors due to slice profile can be substantially reduced by including its effect in the dictionary or acquiring data in 3D. Magn Reson Med 76:1127-1135, 2016. © 2015 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
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Affiliation(s)
- Guido Buonincontri
- Istituto Nazionale di Fisica Nucleare (INFN), sezione di Pisa, Largo B. Pontecorvo, Pisa (PI), Italy.
| | - Stephen J Sawiak
- Wolfson Brain Imaging Centre, Department of Clinical Neurosciences, University of Cambridge, Addenbrooke's Hospital, Hills Road, Cambridge, United Kingdom
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