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Samsonov AA, Yarnykh VL. Accurate actual flip angle imaging (AFI) in the presence of fat. Magn Reson Med 2024; 91:2345-2357. [PMID: 38193249 PMCID: PMC10997465 DOI: 10.1002/mrm.30000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 11/30/2023] [Accepted: 12/19/2023] [Indexed: 01/10/2024]
Abstract
PURPOSE To investigate the effect of incomplete fat spoiling on the accuracy of B1 mapping with actual flip angle imaging (AFI) and to propose a method to minimize the errors using the chemical shift properties of fat. THEORY AND METHODS Diffusion-based dephasing is the main spoiling mechanism exploited in AFI. However, a very low diffusion in fat may make the spoiling insufficient, leading to ghosts in the B1 maps. As the errors retain the chemical-shift signature of fat, their impact can be minimized using chemical-shift-based fat signal removal from AFI acquisition modified to include multi-echo readout. The source of the errors and the proposed correction were studied in simulations and phantom and in-vivo imaging experiments. RESULTS Our results support that AFI artifacts are caused by the incomplete fat spoiling present in clinically attractive short TR acquisition regimes. The correction eliminated the ghosting and significantly improved the B1 mapping accuracy as well as the accuracy of R1 mapping performed with AFI-derived B1 maps. CONCLUSIONS The incomplete fat signal spoiling may be a source of AFI B1 mapping errors, especially in subjects with high fat content. Achieving complete fat spoiling requires longer TR, which is undesirable in clinical applications. The proposed approach based on fat signal removal can reduce errors without significant prolongation of the AFI pulse sequence. We propose that, when attaining complete fat spoiling is not feasible, AFI mapping should be performed in a multi-echo regime with appropriate fat separation or suppression to minimize these errors.
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Affiliation(s)
- Alexey A Samsonov
- Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Vasily L Yarnykh
- Department of Radiology, University of Washington, Seattle, Washington, USA
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2
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Kisel AA, Naumova AV, Yarnykh VL. Macromolecular Proton Fraction as a Myelin Biomarker: Principles, Validation, and Applications. Front Neurosci 2022; 16:819912. [PMID: 35221905 PMCID: PMC8863973 DOI: 10.3389/fnins.2022.819912] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Accepted: 01/17/2022] [Indexed: 12/16/2022] Open
Abstract
Macromolecular proton fraction (MPF) is a quantitative MRI parameter describing the magnetization transfer (MT) effect and defined as a relative amount of protons bound to biological macromolecules with restricted molecular motion, which participate in magnetic cross-relaxation with water protons. MPF attracted significant interest during past decade as a biomarker of myelin. The purpose of this mini review is to provide a brief but comprehensive summary of MPF mapping methods, histological validation studies, and MPF applications in neuroscience. Technically, MPF maps can be obtained using a variety of quantitative MT methods. Some of them enable clinically reasonable scan time and resolution. Recent studies demonstrated the feasibility of MPF mapping using standard clinical MRI pulse sequences, thus substantially enhancing the method availability. A number of studies in animal models demonstrated strong correlations between MPF and histological markers of myelin with a minor influence of potential confounders. Histological studies validated the capability of MPF to monitor both demyelination and re-myelination. Clinical applications of MPF have been mainly focused on multiple sclerosis where this method provided new insights into both white and gray matter pathology. Besides, several studies used MPF to investigate myelin role in other neurological and psychiatric conditions. Another promising area of MPF applications is the brain development studies. MPF demonstrated the capabilities to quantitatively characterize the earliest stage of myelination during prenatal brain maturation and protracted myelin development in adolescence. In summary, MPF mapping provides a technically mature and comprehensively validated myelin imaging technology for various preclinical and clinical neuroscience applications.
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Affiliation(s)
- Alena A. Kisel
- Department of Radiology, University of Washington, Seattle, WA, United States
- Laboratory of Neurobiology, Tomsk State University, Tomsk, Russia
| | - Anna V. Naumova
- Department of Radiology, University of Washington, Seattle, WA, United States
| | - Vasily L. Yarnykh
- Department of Radiology, University of Washington, Seattle, WA, United States
- Laboratory of Neurobiology, Tomsk State University, Tomsk, Russia
- *Correspondence: Vasily L. Yarnykh,
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3
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Yarnykh VL. Data-Driven Retrospective Correction of B 1 Field Inhomogeneity in Fast Macromolecular Proton Fraction and R 1 Mapping. IEEE TRANSACTIONS ON MEDICAL IMAGING 2021; 40:3473-3484. [PMID: 34110989 PMCID: PMC8711232 DOI: 10.1109/tmi.2021.3088258] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
Correction of B1 field non-uniformity is critical for many quantitative MRI methods including variable flip angle (VFA) T1 mapping and single-point macromolecular proton fraction (MPF) mapping. The latter method showed promising results as a fast and robust quantitative myelin imaging approach and involves VFA-based R1=1/T1 map reconstruction as an intermediate processing step. The need for B1 correction restricts applications of the above methods, since B1 mapping sequences increase the examination time and are not commonly available in clinics. A new algorithm was developed to enable retrospective data-driven simultaneous B1 correction in VFA R1 and single-point MPF mapping. The principle of the algorithm is based on different mathematical dependences of B1 -related errors in R1 and MPF allowing extraction of a surrogate B1 field map from uncorrected R1 and MPF maps. To validate the method, whole-brain R1 and MPF maps with isotropic 1.25 mm3 resolution were obtained on a 3 T MRI scanner from 11 volunteers. Mean parameter values in segmented brain tissues were compared between three reconstruction options including the absence of correction, actual B1 correction, and surrogate B1 correction. Surrogate B1 maps closely reproduced actual patterns of B1 inhomogeneity. Without correction, B1 non-uniformity caused highly significant biases in R1 and MPF ( ). Surrogate B1 field correction reduced the biases in both R1 and MPF to a non-significant level ( 0.1 ≤ P ≤ 0.8 ). The described algorithm obviates the use of dedicated B1 mapping sequences in fast single-point MPF mapping and provides an alternative solution for correction of B1 non-uniformities in VFA R1 mapping.
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Bosticardo S, Schiavi S, Schaedelin S, Lu PJ, Barakovic M, Weigel M, Kappos L, Kuhle J, Daducci A, Granziera C. Microstructure-Weighted Connectomics in Multiple Sclerosis. Brain Connect 2021; 12:6-17. [PMID: 34210167 PMCID: PMC8867108 DOI: 10.1089/brain.2021.0047] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022] Open
Abstract
Introduction: Graph theory has been applied to study the pathophysiology of multiple sclerosis (MS) since it provides global and focal measures of brain network properties that are affected by MS. Typically, the connection strength and, consequently, the network properties are computed by counting the number of streamlines (NOS) connecting couples of gray matter regions. However, recent studies have shown that this method is not quantitative. Methods: We evaluated diffusion-based microstructural measures extracted from three different models to assess the network properties in a group of 66 MS patients and 64 healthy subjects. Besides, we assessed their correlation with patients' disability and with a biological measure of neuroaxonal damage. Results: Graph metrics extracted from connectomes weighted by intra-axonal microstructural components were the most sensitive to MS pathology and the most related to clinical disability. In contrast, measures of network segregation extracted from the connectomes weighted by maps describing extracellular diffusivity were the most related to serum concentration of neurofilament light chain. Network properties assessed with NOS were neither sensitive to MS pathology nor correlated with clinical and pathological measures of disease impact in MS patients. Conclusion: Using tractometry-derived graph measures in MS patients, we identified a set of metrics based on microstructural components that are highly sensitive to the disease and that provide sensitive correlates of clinical and biological deterioration in MS patients.
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Affiliation(s)
- Sara Bosticardo
- Diffusion Imaging and Connectivity Estimation (DICE) Lab, Department of Computer Science, University of Verona, Verona, Italy
| | - Simona Schiavi
- Diffusion Imaging and Connectivity Estimation (DICE) Lab, Department of Computer Science, University of Verona, Verona, Italy
| | - Sabine Schaedelin
- Neurology Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Po-Jui Lu
- Translational Imaging in Neurology (ThINk), Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience (RC2NB) Basel, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Muhamed Barakovic
- Translational Imaging in Neurology (ThINk), Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience (RC2NB) Basel, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Matthias Weigel
- Translational Imaging in Neurology (ThINk), Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience (RC2NB) Basel, University Hospital Basel and University of Basel, Basel, Switzerland
- Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
| | - Ludwig Kappos
- Translational Imaging in Neurology (ThINk), Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience (RC2NB) Basel, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Jens Kuhle
- Neurology Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk), Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience (RC2NB) Basel, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Alessandro Daducci
- Diffusion Imaging and Connectivity Estimation (DICE) Lab, Department of Computer Science, University of Verona, Verona, Italy
| | - Cristina Granziera
- Neurology Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Translational Imaging in Neurology (ThINk), Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience (RC2NB) Basel, University Hospital Basel and University of Basel, Basel, Switzerland
- Address correspondence to: Cristina Granziera, Translational Imaging in Neurology (ThINk), Department of Biomedical Engineering, University Hospital Basel and University of Basel, Gewerbestrasse 16, 4123 Allschwil, BL, Switzerland
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Global hypomyelination of the brain white and gray matter in schizophrenia: quantitative imaging using macromolecular proton fraction. Transl Psychiatry 2021; 11:365. [PMID: 34226491 PMCID: PMC8257619 DOI: 10.1038/s41398-021-01475-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/24/2020] [Revised: 05/08/2021] [Accepted: 05/17/2021] [Indexed: 02/06/2023] Open
Abstract
Myelin deficiency is commonly recognized as an important pathological feature of brain tissues in schizophrenia (SZ). In this pilot study, global myelin content abnormalities in white matter (WM) and gray matter (GM) of SZ patients were non-invasively investigated using a novel clinically-targeted quantitative myelin imaging technique, fast macromolecular proton fraction (MPF) mapping. MPF maps were obtained from 23 healthy subjects and 31 SZ patients using a clinical 1.5T magnetic resonance imaging (MRI) scanner. Mean MPF in WM and GM was compared between the healthy control subjects and SZ patients with positive and negative leading symptoms using the multivariate analysis of covariance. The SZ patients had significantly reduced MPF in GM (p < 0.001) and WM (p = 0.02) with the corresponding relative decrease of 5% and 3%, respectively. The effect sizes for the myelin content loss in SZ relative to the control group were 1.0 and 1.5 for WM and GM, respectively. The SZ patients with leading negative symptoms had significantly lower MPF in GM (p < 0.001) and WM (p = 0.003) as compared to the controls and showed a significant MPF decrease in WM (p = 0.03) relative to the patients with leading positive symptoms. MPF in WM significantly negatively correlated with the disease duration in SZ patients (Pearson's r = -0.51; p = 0.004). This study demonstrates that chronic SZ is characterized by global microscopic brain hypomyelination of both WM and GM, which is associated with the disease duration and negative symptoms. Myelin deficiency in SZ can be detected and quantified by the fast MPF mapping method.
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Soustelle L, Antal MC, Lamy J, Harsan LA, Loureiro de Sousa P. Determination of optimal parameters for 3D single-point macromolecular proton fraction mapping at 7T in healthy and demyelinated mouse brain. Magn Reson Med 2020; 85:369-379. [PMID: 32767495 DOI: 10.1002/mrm.28397] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Revised: 06/05/2020] [Accepted: 06/05/2020] [Indexed: 12/19/2022]
Abstract
PURPOSE To determine optimal constrained tissue parameters and off-resonance sequence parameters for single-point macromolecular proton fraction (SP-MPF) mapping based on a comprehensive quantitative magnetization transfer (qMT) protocol in healthy and demyelinated living mice at 7T. METHODS Using 3D spoiled gradient echo-based sequences, a comprehensive qMT protocol is performed by sampling the Z-spectrum of mice brains, in vivo. Provided additional T1 , B 1 + and B0 maps allow for the estimation of qMT tissue parameters, among which three will be constrained, namely the longitudinal and transverse relaxation characteristics of the free pool (R1,f T2,f ), the cross-relaxation rate (R) and the bound pool transverse relaxation time (T2,r ). Different sets of constrained parameters are investigated to reduce the bias between the SP-MPF and its reference based on the comprehensive protocol. RESULTS Based on a whole-brain histogram analysis about the constrained parameters, the optimal experimental parameters that minimize the global bias between reference and SP-MPF maps consist of a 600° and 6 kHz off-resonance irradiation pulse. Following a Bland-Altman analysis over regions of interest, optimal constrained parameters were R1,f T2,f = 0.0129, R = 26.5 s-1 , and T2,r = 9.1 µs, yielding an overall MPF bias of 10-4 (limits of agreement [-0.0068;0.0070]) and a relative variation of 0.64% ± 5.95% between the reference and the optimal single-point method across all mice. CONCLUSION The necessity of estimating animal model- and field-dependent constrained parameters was demonstrated. The single-point MPF method can be reliably applied at 7T, as part of routine preclinical in vivo imaging protocol in mice.
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Affiliation(s)
- Lucas Soustelle
- ICube, Université de Strasbourg, CNRS, Strasbourg, France.,Aix Marseille University, CNRS, CRMBM, Marseille, France
| | | | - Julien Lamy
- ICube, Université de Strasbourg, CNRS, Strasbourg, France
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Anisimov NV, Pavlova OS, Pirogov YA, Yarnykh VL. Three-dimensional fast single-point macromolecular proton fraction mapping of the human brain at 0.5 Tesla. Quant Imaging Med Surg 2020; 10:1441-1449. [PMID: 32676363 DOI: 10.21037/qims-19-1057] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Fast single-point macromolecular proton fraction (MPF) mapping is a recent magnetic resonance imaging (MRI) method enabling quantitative assessment of myelin content in neural tissues. To date, the reported technical implementations of MPF mapping utilized high-field MRI equipment (1.5 T or higher), while low-field applications might pose challenges due to signal-to-noise ratio (SNR) limitations and short T1 . This study aimed to evaluate the feasibility of MPF mapping of the human brain at 0.5 T. The three-dimensional MPF mapping protocol was implemented according to the single-point synthetic-reference method, which includes three spoiled gradient-echo sequences providing proton density, T1 , and magnetization transfer contrast weightings. Whole-brain MPF maps were obtained from three healthy volunteers with spatial resolution of 1.5×1.5×2 mm3 and the total scan time of 19 minutes. MPF values were measured in a series of white and gray matter structures and compared with literature data for 3 T magnetic field. MPF maps enabled high contrast between white and gray matter with notable insensitivity to paramagnetic effects in iron-rich structures, such as globus pallidus, substantia nigra, and dentate nucleus. MPF values at 0.5 T appeared in close agreement with those at 3 T. This study demonstrates the feasibility of fast MPF mapping with low-field MRI equipment and the independence of brain MPF values of magnetic field. The presented results confirm the utility of MPF as an absolute scale for MRI-based myelin content measurements across a wide range of magnetic field strengths and extend the applicability of fast MPF mapping to inexpensive low-field MRI hardware.
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Affiliation(s)
- Nikolay V Anisimov
- Faculty of Fundamental Medicine, Lomonosov Moscow State University, 117192, Moscow, Lomonosovsky Prospekt, 31-5, Russian Federation
| | - Olga S Pavlova
- Faculty of Fundamental Medicine, Lomonosov Moscow State University, 117192, Moscow, Lomonosovsky Prospekt, 31-5, Russian Federation.,Faculty of Physics, Lomonosov Moscow State University, 119991, Moscow, GSP-1, Leninskie Gory, 1-2, Russian Federation
| | - Yury A Pirogov
- Faculty of Physics, Lomonosov Moscow State University, 119991, Moscow, GSP-1, Leninskie Gory, 1-2, Russian Federation.,Institute for Physical and Chemical Fundamentals of Artificial Intelligence, Lomonosov Moscow State University, 119991, Moscow, GSP-1, Leninskie Gory, 1-11, Russian Federation
| | - Vasily L Yarnykh
- Department of Radiology, University of Washington, Seattle, WA 98109, USA.,Research Institute of Biology and Biophysics, Tomsk State University, 634050, Tomsk, Russian Federation
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8
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Paquola C, Bethlehem RAI, Seidlitz J, Wagstyl K, Romero-Garcia R, Whitaker KJ, Vos de Wael R, Williams GB, Vértes PE, Margulies DS, Bernhardt B, Bullmore ET. Shifts in myeloarchitecture characterise adolescent development of cortical gradients. eLife 2019; 8:e50482. [PMID: 31724948 PMCID: PMC6855802 DOI: 10.7554/elife.50482] [Citation(s) in RCA: 60] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2019] [Accepted: 11/02/2019] [Indexed: 11/21/2022] Open
Abstract
We studied an accelerated longitudinal cohort of adolescents and young adults (n = 234, two time points) to investigate dynamic reconfigurations in myeloarchitecture. Intracortical profiles were generated using magnetization transfer (MT) data, a myelin-sensitive magnetic resonance imaging contrast. Mixed-effect models of depth specific intracortical profiles demonstrated two separate processes i) overall increases in MT, and ii) flattening of the MT profile related to enhanced signal in mid-to-deeper layers, especially in heteromodal and unimodal association cortices. This development was independent of morphological changes. Enhanced MT in mid-to-deeper layers was found to spatially co-localise specifically with gene expression markers of oligodendrocytes. Interregional covariance analysis revealed that these intracortical changes contributed to a gradual differentiation of higher-order from lower-order systems. Depth-dependent trajectories of intracortical myeloarchitectural development contribute to the maturation of structural hierarchies in the human neocortex, providing a model for adolescent development that bridges microstructural and macroscopic scales of brain organisation.
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Affiliation(s)
- Casey Paquola
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and HospitalMcGill UniversityMontrealCanada
| | - Richard AI Bethlehem
- Department of PsychiatryUniversity of CambridgeCambridgeUnited Kingdom
- Autism Research Centre, Department of PsychiatryUniversity of CambridgeCambridgeUnited Kingdom
| | - Jakob Seidlitz
- Department of PsychiatryUniversity of CambridgeCambridgeUnited Kingdom
- Developmental Neurogenomics UnitNational Institute of Mental HealthBethesdaUnited States
| | - Konrad Wagstyl
- Department of PsychiatryUniversity of CambridgeCambridgeUnited Kingdom
| | | | - Kirstie J Whitaker
- Department of PsychiatryUniversity of CambridgeCambridgeUnited Kingdom
- The Alan Turing InstituteLondonUnited Kingdom
| | - Reinder Vos de Wael
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and HospitalMcGill UniversityMontrealCanada
| | - Guy B Williams
- Department of Clinical Neurosciences, Wolfson Brain Imaging CentreUniversity of CambridgeCambridgeUnited Kingdom
| | | | - Petra E Vértes
- Department of PsychiatryUniversity of CambridgeCambridgeUnited Kingdom
- The Alan Turing InstituteLondonUnited Kingdom
| | - Daniel S Margulies
- FrontlabInstitut du Cerveau et de la Moelle épinière, UPMC UMRS 1127, Inserm U 1127, CNRS UMR 7225ParisFrance
| | - Boris Bernhardt
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and HospitalMcGill UniversityMontrealCanada
| | - Edward T Bullmore
- Department of PsychiatryUniversity of CambridgeCambridgeUnited Kingdom
- Department of Clinical Neurosciences, Wolfson Brain Imaging CentreUniversity of CambridgeCambridgeUnited Kingdom
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Khodanovich M, Pishchelko A, Glazacheva V, Pan E, Akulov A, Svetlik M, Tyumentseva Y, Anan'ina T, Yarnykh V. Quantitative Imaging of White and Gray Matter Remyelination in the Cuprizone Demyelination Model Using the Macromolecular Proton Fraction. Cells 2019; 8:cells8101204. [PMID: 31590363 PMCID: PMC6830095 DOI: 10.3390/cells8101204] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2019] [Revised: 10/01/2019] [Accepted: 10/01/2019] [Indexed: 02/07/2023] Open
Abstract
Macromolecular proton fraction (MPF) has been established as a quantitative clinically-targeted MRI myelin biomarker based on recent demyelination studies. This study aimed to assess the capability of MPF to quantify remyelination using the murine cuprizone-induced reversible demyelination model. MPF was measured in vivo using the fast single-point method in three animal groups (control, cuprizone-induced demyelination, and remyelination after cuprizone withdrawal) and compared to quantitative immunohistochemistry for myelin basic protein (MBP), myelinating oligodendrocytes (CNP-positive cells), and oligodendrocyte precursor cells (OPC, NG2-positive cells) in the corpus callosum, caudate putamen, hippocampus, and cortex. In the demyelination group, MPF, MBP-stained area, and oligodendrocyte count were significantly reduced, while OPC count was significantly increased as compared to both control and remyelination groups in all anatomic structures (p < 0.05). All variables were similar in the control and remyelination groups. MPF and MBP-stained area strongly correlated in each anatomic structure (Pearson’s correlation coefficients, r = 0.80–0.90, p < 0.001). MPF and MBP correlated positively with oligodendrocyte count (r = 0.70–0.84, p < 0.01 for MPF; r = 0.81–0.92, p < 0.001 for MBP) and negatively with OPC count (r = −0.69–−0.77, p < 0.01 for MPF; r = −0.72–−0.89, p < 0.01 for MBP). This study provides immunohistological validation of fast MPF mapping as a non-invasive tool for quantitative assessment of de- and remyelination in white and gray matter and indicates the feasibility of using MPF as a surrogate marker of reparative processes in demyelinating diseases.
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Affiliation(s)
- Marina Khodanovich
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, Tomsk 634050, Russia.
| | - Anna Pishchelko
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, Tomsk 634050, Russia.
| | - Valentina Glazacheva
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, Tomsk 634050, Russia.
| | - Edgar Pan
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, Tomsk 634050, Russia.
| | - Andrey Akulov
- Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk 630090, Russia.
| | - Mikhail Svetlik
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, Tomsk 634050, Russia.
| | - Yana Tyumentseva
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, Tomsk 634050, Russia.
| | - Tatyana Anan'ina
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, Tomsk 634050, Russia.
| | - Vasily Yarnykh
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, Tomsk 634050, Russia.
- Department of Radiology, University of Washington, Seattle, WA 98109, USA.
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10
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Deshmane A, McGivney DF, Ma D, Jiang Y, Badve C, Gulani V, Seiberlich N, Griswold MA. Partial volume mapping using magnetic resonance fingerprinting. NMR IN BIOMEDICINE 2019; 32:e4082. [PMID: 30821878 DOI: 10.1002/nbm.4082] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/17/2018] [Revised: 01/21/2019] [Accepted: 01/23/2019] [Indexed: 06/09/2023]
Abstract
Magnetic resonance fingerprinting (MRF) is a quantitative imaging technique that maps multiple tissue properties through pseudorandom signal excitation and dictionary-based reconstruction. The aim of this study is to estimate and validate partial volumes from MRF signal evolutions (PV-MRF), and to characterize possible sources of error. Partial volume model inversion (pseudoinverse) and dictionary-matching approaches to calculate brain tissue fractions (cerebrospinal fluid, gray matter, white matter) were compared in a numerical phantom and seven healthy subjects scanned at 3 T. Results were validated by comparison with ground truth in simulations and ROI analysis in vivo. Simulations investigated tissue fraction errors arising from noise, undersampling artifacts, and model errors. An expanded partial volume model was investigated in a brain tumor patient. PV-MRF with dictionary matching is robust to noise, and estimated tissue fractions are sensitive to model errors. A 6% error in pure tissue T1 resulted in average absolute tissue fraction error of 4% or less. A partial volume model within these accuracy limits could be semi-automatically constructed in vivo using k-means clustering of MRF-mapped relaxation times. Dictionary-based PV-MRF robustly identifies pure white matter, gray matter and cerebrospinal fluid, and partial volumes in subcortical structures. PV-MRF could also estimate partial volumes of solid tumor and peritumoral edema. We conclude that PV-MRF can attribute subtle changes in relaxation times to altered tissue composition, allowing for quantification of specific tissues which occupy a fraction of a voxel.
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Affiliation(s)
- Anagha Deshmane
- Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
| | | | - Dan Ma
- Radiology, Case Western Reserve University, Cleveland, OH, USA
| | - Yun Jiang
- Radiology, Case Western Reserve University, Cleveland, OH, USA
| | - Chaitra Badve
- Radiology, Case Western Reserve University, Cleveland, OH, USA
- Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA
| | - Vikas Gulani
- Radiology, Case Western Reserve University, Cleveland, OH, USA
- Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA
- Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
| | - Nicole Seiberlich
- Radiology, Case Western Reserve University, Cleveland, OH, USA
- Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
| | - Mark A Griswold
- Radiology, Case Western Reserve University, Cleveland, OH, USA
- Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
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11
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Sled JG. Modelling and interpretation of magnetization transfer imaging in the brain. Neuroimage 2017; 182:128-135. [PMID: 29208570 DOI: 10.1016/j.neuroimage.2017.11.065] [Citation(s) in RCA: 78] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2017] [Revised: 11/19/2017] [Accepted: 11/29/2017] [Indexed: 01/09/2023] Open
Abstract
Magnetization transfer contrast has yielded insight into brain tissue microstructure changes across the lifespan and in a range of disorders. This progress has been aided by the development of quantitative magnetization transfer imaging techniques able to extract intrinsic properties of the tissue that are independent of the specifics of the data acquisition. While the tissue properties extracted by these techniques do not map directly onto specific cellular structures or pathological processes, a growing body of work from animal models and histopathological correlations aids the in vivo interpretation of magnetization transfer properties of tissue. This review examines the biophysical models that have been developed to describe magnetization transfer contrast in tissue as well as the experimental evidence for the biological interpretation of magnetization transfer data in health and disease.
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Affiliation(s)
- John G Sled
- Hospital for Sick Children, Mouse Imaging Centre, Toronto, Ontario, Canada; Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.
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12
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Hagiwara A, Hori M, Yokoyama K, Nakazawa M, Ueda R, Horita M, Andica C, Abe O, Aoki S. Analysis of White Matter Damage in Patients with Multiple Sclerosis via a Novel In Vivo MR Method for Measuring Myelin, Axons, and G-Ratio. AJNR Am J Neuroradiol 2017; 38:1934-1940. [PMID: 28775058 PMCID: PMC7963610 DOI: 10.3174/ajnr.a5312] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2017] [Accepted: 05/24/2017] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Myelin and axon volume fractions can now be estimated via MR imaging in vivo, as can the g-ratio, which equals the ratio of the inner to the outer diameter of a nerve fiber. The purpose of this study was to evaluate WM damage in patients with MS via this novel MR imaging technique. MATERIALS AND METHODS Twenty patients with relapsing-remitting MS with a combined total of 149 chronic plaques were analyzed. Myelin volume fraction was calculated based on simultaneous tissue relaxometry. Intracellular and CSF compartment volume fractions were quantified via neurite orientation dispersion and density imaging. Axon volume fraction and g-ratio were calculated by combining these measurements. Myelin and axon volume fractions and g-ratio were measured in plaques, periplaque WM, and normal-appearing WM. RESULTS All metrics differed significantly across the 3 groups (P < .001, except P = .027 for g-ratio between periplaque WM and normal-appearing WM). Those in plaques differed most from those in normal-appearing WM. The percentage changes in plaque and periplaque WM metrics relative to normal-appearing WM were significantly larger in absolute value for myelin volume fraction than for axon volume fraction and g-ratio (P < .001, except P = .033 in periplaque WM relative to normal-appearing WM for comparison between myelin and axon volume fraction). CONCLUSIONS In this in vivo MR imaging study, the myelin of WM was more damaged than axons in plaques and periplaque WM of patients with MS. Myelin and axon volume fractions and g-ratio may potentially be useful for evaluating WM damage in patients with MS.
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Affiliation(s)
- A Hagiwara
- From the Departments of Radiology (A.H., M. Hori., M.N., R.U., M. Horita, C.A., S.A.)
- Department of Radiology (A.H., O.A.), Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - M Hori
- From the Departments of Radiology (A.H., M. Hori., M.N., R.U., M. Horita, C.A., S.A.)
| | - K Yokoyama
- Neurology (K.Y.), Juntendo University School of Medicine, Tokyo, Japan
| | - M Nakazawa
- From the Departments of Radiology (A.H., M. Hori., M.N., R.U., M. Horita, C.A., S.A.)
| | - R Ueda
- From the Departments of Radiology (A.H., M. Hori., M.N., R.U., M. Horita, C.A., S.A.)
- Department of Radiological Sciences (R.U.), Graduate School of Human Health Sciences, Tokyo Metropolitan University, Tokyo, Japan
| | - M Horita
- From the Departments of Radiology (A.H., M. Hori., M.N., R.U., M. Horita, C.A., S.A.)
| | - C Andica
- From the Departments of Radiology (A.H., M. Hori., M.N., R.U., M. Horita, C.A., S.A.)
| | - O Abe
- Department of Radiology (A.H., O.A.), Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - S Aoki
- From the Departments of Radiology (A.H., M. Hori., M.N., R.U., M. Horita, C.A., S.A.)
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13
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Liu F, Velikina JV, Block WF, Kijowski R, Samsonov AA. Fast Realistic MRI Simulations Based on Generalized Multi-Pool Exchange Tissue Model. IEEE TRANSACTIONS ON MEDICAL IMAGING 2017; 36:527-537. [PMID: 28113746 PMCID: PMC5322984 DOI: 10.1109/tmi.2016.2620961] [Citation(s) in RCA: 59] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
We present MRiLab, a new comprehensive simulator for large-scale realistic MRI simulations on a regular PC equipped with a modern graphical processing unit (GPU). MRiLab combines realistic tissue modeling with numerical virtualization of an MRI system and scanning experiment to enable assessment of a broad range of MRI approaches including advanced quantitative MRI methods inferring microstructure on a sub-voxel level. A flexible representation of tissue microstructure is achieved in MRiLab by employing the generalized tissue model with multiple exchanging water and macromolecular proton pools rather than a system of independent proton isochromats typically used in previous simulators. The computational power needed for simulation of the biologically relevant tissue models in large 3D objects is gained using parallelized execution on GPU. Three simulated and one actual MRI experiments were performed to demonstrate the ability of the new simulator to accommodate a wide variety of voxel composition scenarios and demonstrate detrimental effects of simplified treatment of tissue micro-organization adapted in previous simulators. GPU execution allowed ∼ 200× improvement in computational speed over standard CPU. As a cross-platform, open-source, extensible environment for customizing virtual MRI experiments, MRiLab streamlines the development of new MRI methods, especially those aiming to infer quantitatively tissue composition and microstructure.
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14
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Pasternak O, Kubicki M, Shenton ME. In vivo imaging of neuroinflammation in schizophrenia. Schizophr Res 2016; 173:200-212. [PMID: 26048294 PMCID: PMC4668243 DOI: 10.1016/j.schres.2015.05.034] [Citation(s) in RCA: 95] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2015] [Revised: 05/18/2015] [Accepted: 05/20/2015] [Indexed: 12/18/2022]
Abstract
In recent years evidence has accumulated to suggest that neuroinflammation might be an early pathology of schizophrenia that later leads to neurodegeneration, yet the exact role in the etiology, as well as the source of neuroinflammation, are still not known. The hypothesis of neuroinflammation involvement in schizophrenia is quickly gaining popularity, and thus it is imperative that we have reliable and reproducible tools and measures that are both sensitive, and, most importantly, specific to neuroinflammation. The development and use of appropriate human in vivo imaging methods can help in our understanding of the location and extent of neuroinflammation in different stages of the disorder, its natural time-course, and its relation to neurodegeneration. Thus far, there is little in vivo evidence derived from neuroimaging methods. This is likely the case because the methods that are specific and sensitive to neuroinflammation are relatively new or only just being developed. This paper provides a methodological review of both existing and emerging positron emission tomography and magnetic resonance imaging techniques that identify and characterize neuroinflammation. We describe \how these methods have been used in schizophrenia research. We also outline the shortcomings of existing methods, and we highlight promising future techniques that will likely improve state-of-the-art neuroimaging as a more refined approach for investigating neuroinflammation in schizophrenia.
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Affiliation(s)
- Ofer Pasternak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02215, USA; Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02215, USA; Department of Applied Mathematics, Tel Aviv University, Tel Aviv 69978, Israel.
| | - Marek Kubicki
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02215, USA; Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02215, USA; Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02215, USA
| | - Martha E Shenton
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02215, USA; Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02215, USA; VA Boston Healthcare System, Brockton, MA, USA
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15
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Liu F, Chaudhary R, Block WF, Samsonov A, Kijowski R. Multicomponent T2 analysis of articular cartilage with synovial fluid partial volume correction. J Magn Reson Imaging 2016; 43:1140-7. [PMID: 26435385 PMCID: PMC4878387 DOI: 10.1002/jmri.25061] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2015] [Accepted: 09/18/2015] [Indexed: 12/20/2022] Open
Abstract
PURPOSE To investigate the use of a three-pool model to account for the confounding effects of synovial fluid on multicomponent T2 analysis of articular cartilage using Multicomponent Driven Equilibrium Single Shot Observation of T1 and T2 (mcDESPOT). MATERIALS AND METHODS mcDESPOT was performed on the knee of eight asymptomatic volunteers and eight patients with osteoarthritis at 3.0T with multicomponent T2 maps created using the two-pool model and a three-pool model containing a nonexchanging synovial fluid water pool. The fraction of the fast-relaxing water component (FF ) and the T2 relaxation times for the fast-relaxing (T2F ) and slow-relaxing (T2S ) water components were measured in the superficial and deep layers of patellar cartilage using the two-pool and three-pool models in asymptomatic volunteers and patients with osteoarthritis and were compared using Wilcoxon signed rank tests. RESULTS Within the superficial layer of patellar cartilage, FF was 22.5% and 25.6% for asymptomatic volunteers and 21.3% and 22.8% for patients with osteoarthritis when using the two-pool and three-pool models, respectively, while T2S was 73.9 msec and 62.0 msec for asymptomatic volunteers and 72.0 msec and 63.1 msec for patients with osteoarthritis when using the two-pool and three-pool models, respectively. For both asymptomatic volunteers and patients with osteoarthritis, the two-pool model provided significantly (P < 0.05) lower FF and higher T2S than the three-pool model, likely due to the effects of synovial fluid partial volume averaging. CONCLUSION The effects of partial volume averaging between superficial cartilage and synovial fluid may result in biased multicomponent T2 measurements that can be corrected using an mcDESPOT three-pool model containing a nonexchanging synovial fluid water pool.
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Affiliation(s)
- Fang Liu
- Department of Medical Physics, University of Wisconsin - Madison, Madison, Wisconsin, USA
| | - Rajeev Chaudhary
- Department of Biomedical Engineering, University of Wisconsin - Madison, Madison, Wisconsin, USA
| | - Walter F. Block
- Department of Medical Physics, University of Wisconsin - Madison, Madison, Wisconsin, USA
- Department of Biomedical Engineering, University of Wisconsin - Madison, Madison, Wisconsin, USA
| | - Alexey Samsonov
- Department of Radiology, University of Wisconsin - Madison, Madison, Wisconsin, USA
| | - Richard Kijowski
- Department of Radiology, University of Wisconsin - Madison, Madison, Wisconsin, USA
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16
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Smith AK, Dortch RD, Dethrage LM, Lyttle BD, Kang H, Welch EB, Smith SA. Incorporating dixon multi-echo fat water separation for novel quantitative magnetization transfer of the human optic nerve in vivo. Magn Reson Med 2016; 77:707-716. [PMID: 27037720 DOI: 10.1002/mrm.26164] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2015] [Revised: 01/08/2016] [Accepted: 01/23/2016] [Indexed: 12/21/2022]
Abstract
PURPOSE The optic nerve (ON) represents the sole pathway between the eyes and brain; consequently, diseases of the ON can have dramatic effects on vision. However, quantitative magnetization transfer (qMT) applications in the ON have been limited to ex vivo studies, in part because of the fatty connective tissue that surrounds the ON, confounding the magnetization transfer (MT) experiment. Therefore, the aim of this study was to implement a multi-echo Dixon fat-water separation approach to remove the fat component from MT images. METHODS MT measurements were taken in a single slice of the ON and frontal lobe using a three-echo Dixon readout, and the water and out-of-phase images were applied to a two-pool model in ON tissue and brain white matter to evaluate the effectiveness of using Dixon fat-water separation to remove fatty tissue from MT images. RESULTS White matter data showed no significant differences between image types; however, there was a significant increase (p < 0.05) in variation in the out-of-phase images in the ON relative to the water images. CONCLUSIONS The results of this study demonstrate that Dixon fat-water separation can be robustly used for accurate MT quantification of anatomies susceptible to partial volume effects resulting from fat. Magn Reson Med 77:707-716, 2017. © 2016 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Alex K Smith
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA.,Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, Tennessee, USA
| | - Richard D Dortch
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA.,Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, Tennessee, USA.,Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, Tennessee, USA
| | - Lindsey M Dethrage
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, Tennessee, USA
| | - Bailey D Lyttle
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, Tennessee, USA
| | - Hakmook Kang
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, Tennessee, USA.,Department of Biostatistics, Vanderbilt University, Nashville, Tennessee, USA.,Center for Quantitative Sciences, Vanderbilt University, Nashville, Tennessee, USA
| | - E Brian Welch
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA.,Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, Tennessee, USA.,Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, Tennessee, USA
| | - Seth A Smith
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA.,Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, Tennessee, USA.,Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, Tennessee, USA.,Department of Ophthalmology and Visual Sciences, Vanderbilt University, Nashville, Tennessee, USA
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17
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Liu F, Block WF, Kijowski R, Samsonov A. Rapid multicomponent relaxometry in steady state with correction of magnetization transfer effects. Magn Reson Med 2016; 75:1423-33. [PMID: 25959974 PMCID: PMC4637271 DOI: 10.1002/mrm.25672] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2014] [Revised: 01/26/2015] [Accepted: 02/06/2015] [Indexed: 11/07/2022]
Abstract
PURPOSE To study the effects of magnetization transfer (MT) on multicomponent T2 parameters obtained using mcDESPOT in macromolecule-rich tissues and to propose a new method called mcRISE to correct MT-induced biases. METHODS The two-pool mcDESPOT model was modified by the addition of an exchanging macromolecule proton pool to model the MT effect in cartilage. The mcRISE acquisition scheme was developed to provide sensitivity to all pools. An incremental fitting was applied to estimate MT and relaxometry parameters with minimized coupling. The interaction between MT and relaxometry parameters, efficacy of MT correction, and feasibility of mcRISE in vivo were investigated in simulations and in healthy volunteers. RESULTS The MT effect caused significant errors in multicomponent T1/T2 values and in fast-relaxing water fraction fF , which is consistent with previous experimental observations. fF increased significantly with macromolecule content if MT was ignored. mcRISE resulted in a multifold reduction of MT biases and yielded decoupled multicomponent T1/T2 relaxometry and quantitative MT parameters. CONCLUSION mcRISE is an efficient approach for correcting MT biases in multicomponent relaxometry based on steady state sequences. Improved specificity of mcRISE may help to elucidate the sources of the previously described high sensitivity of noncorrected mcDESPOT parameters to disease-related changes in cartilage and the brain.
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Affiliation(s)
- Fang Liu
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Walter F Block
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Richard Kijowski
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Alexey Samsonov
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
- Department of Radiology, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
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