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Bontempi P, Marangoni S, Cazzoletti L, Bajrami A, Giometto B, Farace P, Rozzanigo U. Very-long T2-weighted imaging of the non-lesional brain tissue in multiple sclerosis patients. NMR IN BIOMEDICINE 2024:e5235. [PMID: 39086258 DOI: 10.1002/nbm.5235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Revised: 07/15/2024] [Accepted: 07/21/2024] [Indexed: 08/02/2024]
Abstract
The purpose of this study is to demonstrate that T2-weighted imaging with very long echo time (TE > 300 ms) can provide relevant information in neurodegenerative/inflammatory disorder. Twenty patients affected by relapsing-remitting multiple sclerosis with stable disease course underwent 1.5 T 3D FLAIR, 3D T1-weighted, and a multi-echo sequence with 32 echoes (TE = 10-320 ms). Focal lesions (FL) were identified on FLAIR. T1-images were processed to segment deep gray matter (dGM), white matter (WM), FL sub-volumes with T1 hypo-intensity (T1FL), and dGM volumes (atrophy). Clinical-radiological parameters included Expanded Disability Status Scale (EDSS), disease duration, patient age, T1FL, and dGM atrophy. Correlation analysis was performed between the mean signal intensity (SI) computed on the non-lesional dGM and WM at different TE versus the clinical-radiological parameters. Multivariable linear regressions were fitted to the data to assess the association between the dependent variable EDSS and the independent variables obtained by T1FL lesion load and the mean SI of dGM and WM at the different TE. A clear trend is observed, with a systematic strengthening of the significance of the correlation at longer TE for all the relationships with the clinical-radiological parameters, becoming significant (p < 0.05) for EDSS, T1FL volumes, and dGM atrophy. Multivariable linear regressions show that at shorter TE, the SI of the T2-weighted sequences is not relevant for describing the EDSS variability while the T1FL volumes are relevant, and vice versa, at very-long TEs (around 300 ms); the SI of the T2-weighted sequences significantly (p < 0.05) describes the EDSS variability. By very long TE, the SI primarily originates from water with a T2 longer than 250 ms and/or free water, which may be arising from the perivascular space (PVS). Very-long T2-weighting might detect dilated PVS and represent an unexplored MR approach in neurofluid imaging of neurodegenerative/inflammatory diseases.
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Affiliation(s)
- Pietro Bontempi
- Department of Engineering for Innovation Medicine, University of Verona, Verona, Italy
| | | | - Lucia Cazzoletti
- Unit of Epidemiology and Medical Statistics, Department of Diagnostics and Public Health, University of Verona, Verona, Italy
| | | | | | - Paolo Farace
- Medical Physics Department, Hospital of Trento, Trento, Italy
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Bontempi P, Rozzanigo U, Marangoni S, Fogazzi E, Ravanelli D, Cazzoletti L, Giometto B, Farace P. Non-lesional white matter in relapsing-remitting multiple sclerosis assessed by multicomponent T2 relaxation. Brain Behav 2023; 13:e3334. [PMID: 38041516 PMCID: PMC10726908 DOI: 10.1002/brb3.3334] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 10/31/2023] [Accepted: 11/02/2023] [Indexed: 12/03/2023] Open
Abstract
INTRODUCTION The purpose of the study is to investigate, by T2 relaxation, non-lesional white matter (WM) in relapsing-remitting (RR) multiple sclerosis (MS). METHODS Twenty stable RR MS patients underwent 1.5T Magnetic Resonance Imaging (MRI) with 3D Fluid-Attenuated Inversion-Recovery (FLAIR), 3D-T1-weighted, and T2-relaxation multi-echo sequences. The Lesion Segmentation Tool processed FLAIR images to identify focal lesions (FLs), whereas T1 images were segmented to identify WM and FL sub-volumes with T1 hypo-intensity. Non-lesional WM was obtained as the segmented WM, excluding FL volumes. The multi-echo sequence allowed decomposition into myelin water, intra-extracellular water, and free water (Fw), which were evaluated on the segmented non-lesional WM. Correlation analysis was performed between the non-lesional WM relaxation parameters and Expanded Disability Status Scale (EDSS), disease duration, patient age, and T1 hypo-intense FL volumes. RESULTS The T1 hypo-intense FL volumes correlated with EDSS. On the non-lesional WM, the median Fw correlated with EDSS, disease duration, age, and T1 hypo-intense FL volumes. Bivariate EDSS correlation of FL volumes and WM T2-relaxation parameters did not improve significance. CONCLUSION T2 relaxation allowed identifying subtle WM alterations, which significantly correlated with EDSS, disease duration, and age but do not seem to be EDSS-predictors independent from FL sub-volumes in stable RR patients. Particularly, the increase in the Fw component is suggestive of an uninvestigated prodromal phenomenon in brain degeneration.
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Affiliation(s)
- Pietro Bontempi
- Department of Engineering for Innovation MedicineUniversity of VeronaVeronaItaly
| | - Umberto Rozzanigo
- Neuro‐radiology Unit, Hospital of TrentoAzienda Provinciale per i Servizi Sanitari (APSS)TrentoItaly
| | - Sabrina Marangoni
- Neurology Unit, Hospital of TrentoAzienda Provinciale per i Servizi Sanitari (APSS)TrentoItaly
| | - Elena Fogazzi
- Physics departmentUniversity of TrentoPovoTrentoItaly
| | - Daniele Ravanelli
- Medical Physics Department, Hospital of TrentoAzienda Provinciale per i Servizi Sanitari (APSS)TrentoItaly
| | - Lucia Cazzoletti
- Unit of Epidemiology and Medical Statistics, Department of Diagnostics and Public HealthUniversity of VeronaVeronaItaly
| | - Bruno Giometto
- Neurology Unit, Hospital of TrentoAzienda Provinciale per i Servizi Sanitari (APSS)TrentoItaly
| | - Paolo Farace
- Medical Physics Department, Hospital of TrentoAzienda Provinciale per i Servizi Sanitari (APSS)TrentoItaly
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Nagtegaal MA, Hermann I, Weingärtner S, Martinez-Heras E, Solana E, Llufriu S, Gass A, Poot DHJ, van Osch MJP, Vos FM, de Bresser J. White matter changes measured by multi-component MR Fingerprinting in multiple sclerosis. Neuroimage Clin 2023; 40:103528. [PMID: 37837891 PMCID: PMC10589890 DOI: 10.1016/j.nicl.2023.103528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 09/11/2023] [Accepted: 10/09/2023] [Indexed: 10/16/2023]
Abstract
T2-hyperintense lesions are the key imaging marker of multiple sclerosis (MS). Previous studies have shown that the white matter surrounding such lesions is often also affected by MS. Our aim was to develop a new method to visualize and quantify the extent of white matter tissue changes in MS based on relaxometry properties. We applied a fast, multi-parametric quantitative MRI approach and used a multi-component MR Fingerprinting (MC-MRF) analysis. We assessed the differences in the MRF component representing prolongedrelaxation time between patients with MS and controls and studied the relation between this component's volume and structural white matter damage identified on FLAIR MRI scans in patients with MS. A total of 48 MS patients at two different sites and 12 healthy controls were scanned with FLAIR and MRF-EPI MRI scans. MRF scans were analyzed with a joint-sparsity multi-component analysis to obtain magnetization fraction maps of different components, representing tissues such as myelin water, white matter, gray matter and cerebrospinal fluid. In the MS patients, an additional component was identified with increased transverse relaxation times compared to the white matter, likely representing changes in free water content. Patients with MS had a higher volume of the long- component in the white matter of the brain compared to healthy controls (B (95%-CI) = 0.004 (0.0006-0.008), p = 0.02). Furthermore, this MRF component had a moderate correlation (correlation coefficient R 0.47) with visible structural white matter changes on the FLAIR scans. Also, the component was found to be more extensive compared to structural white matter changes in 73% of MS patients. In conclusion, our MRF acquisition and analysis captured white matter tissue changes in MS patients compared to controls. In patients these tissue changes were more extensive compared to visually detectable white matter changes on FLAIR scans. Our method provides a novel way to quantify the extent of white matter changes in MS patients, which is underestimated using only conventional clinical MRI scans.
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Affiliation(s)
- Martijn A Nagtegaal
- Department of Imaging Physics, Delft University of Technology, Delft, the Netherlands; C.J. Gorter MRI Center, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands.
| | - Ingo Hermann
- Department of Imaging Physics, Delft University of Technology, Delft, the Netherlands; Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Sebastian Weingärtner
- Department of Imaging Physics, Delft University of Technology, Delft, the Netherlands
| | - Eloy Martinez-Heras
- Neuroimmunology and Multiple Sclerosis Unit and Laboratory of Advanced Imaging in Neuroimmunological Diseases (ImaginEM). Hospital Clinic Barcelona, Institut d'Investigacions Biomediques August Pi i Sunyer (IDIBAPS) and Universitat de Barcelona, Barcelona, Spain
| | - Elisabeth Solana
- Neuroimmunology and Multiple Sclerosis Unit and Laboratory of Advanced Imaging in Neuroimmunological Diseases (ImaginEM). Hospital Clinic Barcelona, Institut d'Investigacions Biomediques August Pi i Sunyer (IDIBAPS) and Universitat de Barcelona, Barcelona, Spain
| | - Sara Llufriu
- Neuroimmunology and Multiple Sclerosis Unit and Laboratory of Advanced Imaging in Neuroimmunological Diseases (ImaginEM). Hospital Clinic Barcelona, Institut d'Investigacions Biomediques August Pi i Sunyer (IDIBAPS) and Universitat de Barcelona, Barcelona, Spain
| | - Achim Gass
- Department of Neurology, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Dirk H J Poot
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands
| | - Matthias J P van Osch
- C.J. Gorter MRI Center, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Frans M Vos
- Department of Imaging Physics, Delft University of Technology, Delft, the Netherlands; Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands
| | - Jeroen de Bresser
- Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
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Zhou L, Li Y, Sweeney EM, Wang XH, Kuceyeski A, Chiang GC, Ivanidze J, Wang Y, Gauthier SA, de Leon MJ, Nguyen TD. Association of brain tissue cerebrospinal fluid fraction with age in healthy cognitively normal adults. Front Aging Neurosci 2023; 15:1162001. [PMID: 37396667 PMCID: PMC10312090 DOI: 10.3389/fnagi.2023.1162001] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 05/31/2023] [Indexed: 07/04/2023] Open
Abstract
Background and purpose Our objective was to apply multi-compartment T2 relaxometry in cognitively normal individuals aged 20-80 years to study the effect of aging on the parenchymal CSF fraction (CSFF), a potential measure of the subvoxel CSF space. Materials and methods A total of 60 volunteers (age range, 22-80 years) were enrolled. Voxel-wise maps of short-T2 myelin water fraction (MWF), intermediate-T2 intra/extra-cellular water fraction (IEWF), and long-T2 CSFF were obtained using fast acquisition with spiral trajectory and adiabatic T2prep (FAST-T2) sequence and three-pool non-linear least squares fitting. Multiple linear regression analyses were performed to study the association between age and regional MWF, IEWF, and CSFF measurements, adjusting for sex and region of interest (ROI) volume. ROIs include the cerebral white matter (WM), cerebral cortex, and subcortical deep gray matter (GM). In each model, a quadratic term for age was tested using an ANOVA test. A Spearman's correlation between the normalized lateral ventricle volume, a measure of organ-level CSF space, and the regional CSFF, a measure of tissue-level CSF space, was computed. Results Regression analyses showed that there was a statistically significant quadratic relationship with age for CSFF in the cortex (p = 0.018), MWF in the cerebral WM (p = 0.033), deep GM (p = 0.017) and cortex (p = 0.029); and IEWF in the deep GM (p = 0.033). There was a statistically highly significant positive linear relationship between age and regional CSFF in the cerebral WM (p < 0.001) and deep GM (p < 0.001). In addition, there was a statistically significant negative linear association between IEWF and age in the cerebral WM (p = 0.017) and cortex (p < 0.001). In the univariate correlation analysis, the normalized lateral ventricle volume correlated with the regional CSFF measurement in the cerebral WM (ρ = 0.64, p < 0.001), cortex (ρ = 0.62, p < 0.001), and deep GM (ρ = 0.66, p < 0.001). Conclusion Our cross-sectional data demonstrate that brain tissue water in different compartments shows complex age-dependent patterns. Parenchymal CSFF, a measure of subvoxel CSF-like water in the brain tissue, is quadratically associated with age in the cerebral cortex and linearly associated with age in the cerebral deep GM and WM.
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Affiliation(s)
- Liangdong Zhou
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Yi Li
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Elizabeth M. Sweeney
- Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Department of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, PA, United States
| | - Xiuyuan H. Wang
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Amy Kuceyeski
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
- Department of Statistics and Data Science, Cornell University, Ithaca, NY, United States
| | - Gloria C. Chiang
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Jana Ivanidze
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Yi Wang
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, United States
| | - Susan A. Gauthier
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Mony J. de Leon
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Thanh D. Nguyen
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
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Stellingwerff MD, Pouwels PJW, Roosendaal SD, Barkhof F, van der Knaap MS. Quantitative MRI in leukodystrophies. Neuroimage Clin 2023; 38:103427. [PMID: 37150021 PMCID: PMC10193020 DOI: 10.1016/j.nicl.2023.103427] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 04/27/2023] [Accepted: 04/28/2023] [Indexed: 05/09/2023]
Abstract
Leukodystrophies constitute a large and heterogeneous group of genetic diseases primarily affecting the white matter of the central nervous system. Different disorders target different white matter structural components. Leukodystrophies are most often progressive and fatal. In recent years, novel therapies are emerging and for an increasing number of leukodystrophies trials are being developed. Objective and quantitative metrics are needed to serve as outcome measures in trials. Quantitative MRI yields information on microstructural properties, such as myelin or axonal content and condition, and on the chemical composition of white matter, in a noninvasive fashion. By providing information on white matter microstructural involvement, quantitative MRI may contribute to the evaluation and monitoring of leukodystrophies. Many distinct MR techniques are available at different stages of development. While some are already clinically applicable, others are less far developed and have only or mainly been applied in healthy subjects. In this review, we explore the background, current status, potential and challenges of available quantitative MR techniques in the context of leukodystrophies.
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Affiliation(s)
- Menno D Stellingwerff
- Amsterdam UMC Location Vrije Universiteit Amsterdam, Child Neurology, Emma Children's Hospital, and Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Petra J W Pouwels
- Amsterdam UMC Location Vrije Universiteit Amsterdam, Department of Radiology and Nuclear Medicine, and Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Stefan D Roosendaal
- Amsterdam UMC Location University of Amsterdam, Department of Radiology, Meibergdreef 9, Amsterdam, the Netherlands
| | - Frederik Barkhof
- Amsterdam UMC Location Vrije Universiteit Amsterdam, Department of Radiology and Nuclear Medicine, and Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands; University College London, Institutes of Neurology and Healthcare Engineering, London, UK
| | - Marjo S van der Knaap
- Amsterdam UMC Location Vrije Universiteit Amsterdam, Child Neurology, Emma Children's Hospital, and Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands; Vrije Universiteit Amsterdam, Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, De Boelelaan 1105, Amsterdam, the Netherlands.
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6
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Edwards EM, Stanley JA, Daugherty AM, Lynn J, Borich MR, Fritz NE. Associations between myelin water imaging and measures of fall risk and functional mobility in multiple sclerosis. J Neuroimaging 2023; 33:94-101. [PMID: 36266780 DOI: 10.1111/jon.13064] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 09/26/2022] [Accepted: 10/08/2022] [Indexed: 02/01/2023] Open
Abstract
BACKGROUND AND PURPOSE Myelin water fraction (MWF) deficits as measured by myelin water imaging (MWI) have been related to worse motor function in persons with multiple sclerosis (PwMS). However, it is unknown if measures from MWI metrics in motor areas relate to fall risk measures in PwMS. The objective of this study was to examine the relationship between MWI measures in motor areas to performance on clinical measures of fall risk and disability in PwMS. METHODS Sixteen individuals with relapsing-remitting MS participated (1 male, 15 female; age 47.1 years [12.3]; Expanded Disability Status Scale 4.0 [range 0-6.5]) and completed measures of walking and fall risk (Timed 25 Foot Walk [T25FW] and Timed Up and Go). MWF and the geometric mean of the intra-/extracellular water T2 (geomT2IEW ) values reflecting myelin content and contribution of large-diameter axons/density, respectively, were assessed in three motor-related regions. RESULTS The geomT2IEW of the corticospinal tract (r = -.599; p = .018) and superior cerebellar peduncles (r = -.613; p = .015) demonstrated significant inverse relationships with T25FW, suggesting that decreased geomT2IEW was related to slower walking. Though not significant, MWF in the corticospinal tract and superior cerebellar peduncles also demonstrated fair relationships with the T25FW, suggesting that worse performance on the T25FW was associated with lower MWF values. CONCLUSIONS MWI of key motor regions was associated with walking performance in PwMS. Further MWI studies are needed to identify relationships between pathology and clinical function in PwMS to guide targeted rehabilitation therapies aimed at preventing falls.
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Affiliation(s)
- Erin M Edwards
- Translational Neuroscience Program, Wayne State University, Detroit, Michigan, USA.,Neuroimaging and Neurorehabilitation Laboratory, Wayne State University, Detroit, Michigan, USA
| | - Jeffrey A Stanley
- Translational Neuroscience Program, Wayne State University, Detroit, Michigan, USA.,Department of Psychiatry and Behavioral Neurosciences, Wayne State University, Detroit, Michigan, USA
| | - Ana M Daugherty
- Department of Psychology, Wayne State University, Detroit, Michigan, USA.,Institute of Gerontology, Wayne State University, Detroit, Michigan, USA
| | - Jonathan Lynn
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University, Detroit, Michigan, USA
| | - Michael R Borich
- Division of Physical Therapy, Department of Rehabilitation Medicine, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Nora E Fritz
- Translational Neuroscience Program, Wayne State University, Detroit, Michigan, USA.,Neuroimaging and Neurorehabilitation Laboratory, Wayne State University, Detroit, Michigan, USA.,Department of Health Care Sciences, Wayne State University, Detroit, Michigan, USA.,Department of Neurology, Wayne State University, Detroit, Michigan, USA
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7
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Fischi-Gomez E, Girard G, Koch PJ, Yu T, Pizzolato M, Brügger J, Piredda GF, Hilbert T, Cadic-Melchior AG, Beanato E, Park CH, Morishita T, Wessel MJ, Schiavi S, Daducci A, Kober T, Canales-Rodríguez EJ, Hummel FC, Thiran JP. Variability and reproducibility of multi-echo T2 relaxometry: Insights from multi-site, multi-session and multi-subject MRI acquisitions. FRONTIERS IN RADIOLOGY 2022; 2:930666. [PMID: 37492668 PMCID: PMC10365099 DOI: 10.3389/fradi.2022.930666] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Accepted: 06/30/2022] [Indexed: 07/27/2023]
Abstract
Quantitative magnetic resonance imaging (qMRI) can increase the specificity and sensitivity of conventional weighted MRI to underlying pathology by comparing meaningful physical or chemical parameters, measured in physical units, with normative values acquired in a healthy population. This study focuses on multi-echo T2 relaxometry, a qMRI technique that probes the complex tissue microstructure by differentiating compartment-specific T2 relaxation times. However, estimation methods are still limited by their sensitivity to the underlying noise. Moreover, estimating the model's parameters is challenging because the resulting inverse problem is ill-posed, requiring advanced numerical regularization techniques. As a result, the estimates from distinct regularization strategies are different. In this work, we aimed to investigate the variability and reproducibility of different techniques for estimating the transverse relaxation time of the intra- and extra-cellular space (T2IE) in gray (GM) and white matter (WM) tissue in a clinical setting, using a multi-site, multi-session, and multi-run T2 relaxometry dataset. To this end, we evaluated three different techniques for estimating the T2 spectra (two regularized non-negative least squares methods and a machine learning approach). Two independent analyses were performed to study the effect of using raw and denoised data. For both the GM and WM regions, and the raw and denoised data, our results suggest that the principal source of variance is the inter-subject variability, showing a higher coefficient of variation (CoV) than those estimated for the inter-site, inter-session, and inter-run, respectively. For all reconstruction methods studied, the CoV ranged between 0.32 and 1.64%. Interestingly, the inter-session variability was close to the inter-scanner variability with no statistical differences, suggesting that T2IE is a robust parameter that could be employed in multi-site neuroimaging studies. Furthermore, the three tested methods showed consistent results and similar intra-class correlation (ICC), with values superior to 0.7 for most regions. Results from raw data were slightly more reproducible than those from denoised data. The regularized non-negative least squares method based on the L-curve technique produced the best results, with ICC values ranging from 0.72 to 0.92.
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Affiliation(s)
- Elda Fischi-Gomez
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Translational Machine Learning Lab, Department of Radiology, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
| | - Gabriel Girard
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
- Department of Radiology, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
| | - Philipp J. Koch
- Defitech Chair for Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, Sion, Switzerland
- Department of Neurology, University of Lübeck, Lübeck, Germany
- Center of Brain, Behavior and Metabolism (CBBM), University of Lübeck, Lübeck, Germany
| | - Thomas Yu
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
| | - Marco Pizzolato
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Julia Brügger
- Defitech Chair for Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, Sion, Switzerland
| | - Gian Franco Piredda
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Department of Radiology, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
| | - Tom Hilbert
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Department of Radiology, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
| | - Andéol G. Cadic-Melchior
- Defitech Chair for Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, Sion, Switzerland
| | - Elena Beanato
- Defitech Chair for Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, Sion, Switzerland
| | - Chang-Hyun Park
- Defitech Chair for Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, Sion, Switzerland
| | - Takuya Morishita
- Defitech Chair for Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, Sion, Switzerland
| | - Maximilian J. Wessel
- Defitech Chair for Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, Sion, Switzerland
- Department of Neurology, University Hospital and Julius-Maximilians-University, Wuerzburg, Germany
| | - Simona Schiavi
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
- Diffusion Imaging and Connectivity Estimation (DICE) Lab, Department of Computer Science, University of Verona, Verona, Italy
| | - Alessandro Daducci
- Diffusion Imaging and Connectivity Estimation (DICE) Lab, Department of Computer Science, University of Verona, Verona, Italy
| | - Tobias Kober
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Department of Radiology, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
| | - Erick J. Canales-Rodríguez
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Friedhelm C. Hummel
- Defitech Chair for Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (NIX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Clinique Romande de Réadaptation, Sion, Switzerland
- Clinical Neuroscience, University Hospital of Geneva (HUG), Geneva, Switzerland
| | - Jean-Philippe Thiran
- Signal Processing Laboratory 5 (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- CIBM Center for Biomedical Imaging, Lausanne, Switzerland
- Department of Radiology, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
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8
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Song JE, Kim DH. Improved Multi-Echo Gradient-Echo-Based Myelin Water Fraction Mapping Using Dimensionality Reduction. IEEE TRANSACTIONS ON MEDICAL IMAGING 2022; 41:27-38. [PMID: 34357864 DOI: 10.1109/tmi.2021.3102977] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Multi-echo gradient-echo (mGRE)-based myelin water fraction (MWF) mapping is a promising myelin water imaging (MWI) modality but is vulnerable to noise and artifact corruption. The linear dimensionality reduction (LDR) method has recently shown improvements with regard to these challenges. However, the magnitude value based low rank operators have been shown to misestimate the MWF for regions with [Formula: see text] anisotropy. This paper presents a nonlinear dimensionality reduction (NLDR) method to estimate the MWF map better by encouraging nonlinear low dimensionality of mGRE signal sources. Specifically, we implemented a fully connected deep autoencoder to extract the low-dimensional features of complex-valued signals and incorporated a sparse regularization to separate the anomaly sources that do not reside in the low-dimensional manifold. Simulations and in vivo experiments were performed to evaluate the accuracy of the MWF map under various situations. The proposed NLDR-based MWF improves the accuracy of the MWF map over the conventional nonlinear least-squares method and the LDR-based MWF and maintains robustness against noise and artifact corruption.
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9
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Tackley G, Kong Y, Minne R, Messina S, Winkler A, Cavey A, Everett R, DeLuca GC, Weir A, Craner M, Tracey I, Palace J, Stagg CJ, Emir U. An In-vivo 1H-MRS short-echo time technique at 7T: Quantification of metabolites in chronic multiple sclerosis and neuromyelitis optica brain lesions and normal appearing brain tissue. Neuroimage 2021; 238:118225. [PMID: 34062267 PMCID: PMC7611458 DOI: 10.1016/j.neuroimage.2021.118225] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Revised: 03/09/2021] [Accepted: 05/29/2021] [Indexed: 11/05/2022] Open
Abstract
Magnetic Resonance Spectroscopy (MRS) allows for the non-invasive quantification of neurochemicals and has the potential to differentiate between the pathologically distinct diseases, multiple sclerosis (MS) and AQP4Ab-positive neuromyelitis optica spectrum disorder (AQP4Ab-NMOSD). In this study we characterised the metabolite profiles of brain lesions in 11 MS and 4 AQP4Ab-NMOSD patients using an optimised MRS methodology at ultra-high field strength (7T) incorporating correction for T2 water relaxation differences between lesioned and normal tissue. MS metabolite results were in keeping with the existing literature: total N-acetylaspartate (NAA) was lower in lesions compared to normal appearing brain white matter (NAWM) with reciprocal findings for myo-Inositol. An unexpected subtlety revealed by our technique was that total NAA differences were likely driven by NAA-glutamate (NAAG), a ubiquitous CNS molecule with functions quite distinct from NAA though commonly quantified together with NAA in MRS studies as total NAA. Surprisingly, AQP4Ab-NMOSD showed no significant differences for total NAA, NAA, NAAG or myo-Inositol between lesion and NAWM sites, nor were there any differences between MS and AQP4Ab-NMOSD for a priori hypotheses. Post-hoc testing revealed a significant correlation between NAWM Ins:NAA and disability (as measured by EDSS) for disease groups combined, driven by the AP4Ab-NMOSD group. Utilising an optimised MRS methodology, our study highlights some under-explored subtleties in MRS profiles, such as the absence of myo-Inositol concentration differences in AQP4Ab-NMOSD brain lesions versus NAWM and the potential influence of NAAG differences between lesions and normal appearing white matter in MS.
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Affiliation(s)
- George Tackley
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, United Kingdom; Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, CF24 4HQ, United Kingdom.
| | - Yazhuo Kong
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, United Kingdom; CAS Key Laboratory of Behavioural Science, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Rachel Minne
- School of Health Sciences, Purdue University, 550 Stadium Mall Drive, West Lafayette, IN 47907, (765) 494-1419, United States
| | - Silvia Messina
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, United Kingdom
| | - Anderson Winkler
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, United Kingdom; National Institute of Mental Health (NIMH), National Institutes of Health (NIH), Bethesda, MD, United States
| | - Ana Cavey
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, United Kingdom
| | - Rosie Everett
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, United Kingdom
| | - Gabriele C DeLuca
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, United Kingdom
| | - Andrew Weir
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, United Kingdom
| | - Matthew Craner
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, United Kingdom
| | - Irene Tracey
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, United Kingdom
| | - Jacqueline Palace
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, United Kingdom
| | - Charlotte J Stagg
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, United Kingdom; MRC Brain Network Dynamics Unit, University of Oxford, Oxford, OX1 3TH, United Kingdom
| | - Uzay Emir
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, United Kingdom; School of Health Sciences, Purdue University, 550 Stadium Mall Drive, West Lafayette, IN 47907, (765) 494-1419, United States; Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, United States
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10
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Age- and gender-related differences in brain tissue microstructure revealed by multi-component T 2 relaxometry. Neurobiol Aging 2021; 106:68-79. [PMID: 34252873 DOI: 10.1016/j.neurobiolaging.2021.06.002] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Revised: 05/30/2021] [Accepted: 06/01/2021] [Indexed: 12/19/2022]
Abstract
In spite of extensive work, inconsistent findings and lack of specificity in most neuroimaging techniques used to examine age- and gender-related patterns in brain tissue microstructure indicate the need for additional research. Here, we performed the largest Multi-component T2 relaxometry cross-sectional study to date in healthy adults (N = 145, 18-60 years). Five quantitative microstructure parameters derived from various segments of the estimated T2 spectra were evaluated, allowing a more specific interpretation of results in terms of tissue microstructure. We found similar age-related myelin water fraction (MWF) patterns in men and women but we also observed differential male related results including increased MWF content in a few white matter tracts, a faster decline with age of the intra- and extra-cellular water fraction and its T2 relaxation time (i.e. steeper age related negative slopes) and a faster increase in the free and quasi-free water fraction, spanning the whole grey matter. Such results point to a sexual dimorphism in brain tissue microstructure and suggest a lesser vulnerability to age-related changes in women.
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11
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Dvorak AV, Swift-LaPointe T, Vavasour IM, Lee LE, Abel S, Russell-Schulz B, Graf C, Wurl A, Liu H, Laule C, Li DKB, Traboulsee A, Tam R, Boyd LA, MacKay AL, Kolind SH. An atlas for human brain myelin content throughout the adult life span. Sci Rep 2021; 11:269. [PMID: 33431990 PMCID: PMC7801525 DOI: 10.1038/s41598-020-79540-3] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Accepted: 12/09/2020] [Indexed: 12/11/2022] Open
Abstract
Myelin water imaging is a quantitative neuroimaging technique that provides the myelin water fraction (MWF), a metric highly specific to myelin content, and the intra-/extra-cellular T2 (IET2), which is related to water and iron content. We coupled high-resolution data from 100 adults with gold-standard methodology to create an optimized anatomical brain template and accompanying MWF and IET2 atlases. We then used the MWF atlas to characterize how myelin content relates to demographic factors. In most brain regions, myelin content followed a quadratic pattern of increase during the third decade of life, plateau at a maximum around the fifth decade, then decrease during later decades. The ranking of mean myelin content between brain regions remained consistent across age groups. These openly available normative atlases can facilitate evaluation of myelin imaging results on an individual basis and elucidate the distribution of myelin content between brain regions and in the context of aging.
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Affiliation(s)
- Adam V Dvorak
- Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada. .,International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, BC, Canada.
| | | | - Irene M Vavasour
- Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada.,Radiology, University of British Columbia, Vancouver, BC, Canada
| | - Lisa Eunyoung Lee
- Medicine (Neurology), University of British Columbia, Vancouver, BC, Canada
| | - Shawna Abel
- Medicine (Neurology), University of British Columbia, Vancouver, BC, Canada
| | | | - Carina Graf
- Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada.,International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, BC, Canada
| | - Anika Wurl
- Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
| | - Hanwen Liu
- Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada.,International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, BC, Canada
| | - Cornelia Laule
- Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada.,International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, BC, Canada.,Radiology, University of British Columbia, Vancouver, BC, Canada.,Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
| | - David K B Li
- Radiology, University of British Columbia, Vancouver, BC, Canada.,Medicine (Neurology), University of British Columbia, Vancouver, BC, Canada
| | - Anthony Traboulsee
- Medicine (Neurology), University of British Columbia, Vancouver, BC, Canada
| | - Roger Tam
- Radiology, University of British Columbia, Vancouver, BC, Canada.,Biomedical Engineering, University of British Columbia, Vancouver, BC, Canada
| | - Lara A Boyd
- Department of Physical Therapy, University of British Columbia, Vancouver, BC, Canada
| | - Alex L MacKay
- Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada.,Radiology, University of British Columbia, Vancouver, BC, Canada
| | - Shannon H Kolind
- Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada.,International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, BC, Canada.,Radiology, University of British Columbia, Vancouver, BC, Canada.,Medicine (Neurology), University of British Columbia, Vancouver, BC, Canada
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12
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Wiggermann V, Vavasour IM, Kolind SH, MacKay AL, Helms G, Rauscher A. Non-negative least squares computation for in vivo myelin mapping using simulated multi-echo spin-echo T 2 decay data. NMR IN BIOMEDICINE 2020; 33:e4277. [PMID: 32124505 DOI: 10.1002/nbm.4277] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2019] [Revised: 01/20/2020] [Accepted: 01/26/2020] [Indexed: 06/10/2023]
Abstract
Multi-compartment T2 mapping has gained particular relevance for the study of myelin water in the brain. As a facilitator of rapid saltatory axonal signal transmission, myelin is a cornerstone indicator of white matter development and function. Regularized non-negative least squares fitting of multi-echo T2 data has been widely employed for the computation of the myelin water fraction (MWF), and the obtained MWF maps have been histopathologically validated. MWF measurements depend upon the quality of the data acquisition, B1+ homogeneity and a range of fitting parameters. In this special issue article, we discuss the relevance of these factors for the accurate computation of multi-compartment T2 and MWF maps. We generated multi-echo spin-echo T2 decay curves following the Carr-Purcell-Meiboom-Gill approach for various myelin concentrations and myelin T2 scenarios by simulating the evolution of the magnetization vector between echoes based on the Bloch equations. We demonstrated that noise and imperfect refocusing flip angles yield systematic underestimations in MWF and intra-/extracellular water geometric mean T2 (gmT2 ). MWF estimates were more stable than myelin water gmT2 time across different settings of the T2 analysis. We observed that the lower limit of the T2 distribution grid should be slightly shorter than TE1 . Both TE1 and the acquisition echo spacing also have to be sufficiently short to capture the rapidly decaying myelin water T2 signal. Among all parameters of interest, the estimated MWF and intra-/extracellular water gmT2 differed by approximately 0.13-4 percentage points and 3-4 ms, respectively, from the true values, with larger deviations observed in the presence of greater B1+ inhomogeneities and at lower signal-to-noise ratio. Tailoring acquisition strategies may allow us to better characterize the T2 distribution, including the myelin water, in vivo.
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Affiliation(s)
- V Wiggermann
- Department of Physics and Astronomy, University of British Columbia, Vancouver, Canada
- Department of Pediatrics, University of British Columbia, Vancouver, Canada
- UBC MRI Research Center, University of British Columbia, Vancouver, Canada
| | - I M Vavasour
- UBC MRI Research Center, University of British Columbia, Vancouver, Canada
- Department of Radiology, University of British Columbia, Vancouver, Canada
| | - S H Kolind
- Department of Physics and Astronomy, University of British Columbia, Vancouver, Canada
- UBC MRI Research Center, University of British Columbia, Vancouver, Canada
- Department of Radiology, University of British Columbia, Vancouver, Canada
- Department of Medicine (Division Neurology), University of British Columbia, Vancouver, Canada
| | - A L MacKay
- Department of Physics and Astronomy, University of British Columbia, Vancouver, Canada
- UBC MRI Research Center, University of British Columbia, Vancouver, Canada
- Department of Radiology, University of British Columbia, Vancouver, Canada
| | - G Helms
- Department of Clinical Sciences Lund (IKVL), Medical Radiation Physics, Lund University, Lund, Sweden
| | - A Rauscher
- Department of Physics and Astronomy, University of British Columbia, Vancouver, Canada
- Department of Pediatrics, University of British Columbia, Vancouver, Canada
- UBC MRI Research Center, University of British Columbia, Vancouver, Canada
- Department of Radiology, University of British Columbia, Vancouver, Canada
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13
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Nagtegaal M, Koken P, Amthor T, de Bresser J, Mädler B, Vos F, Doneva M. Myelin water imaging from multi-echo T2 MR relaxometry data using a joint sparsity constraint. Neuroimage 2020; 219:117014. [DOI: 10.1016/j.neuroimage.2020.117014] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Revised: 05/29/2020] [Accepted: 05/30/2020] [Indexed: 11/24/2022] Open
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14
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Piredda GF, Hilbert T, Thiran JP, Kober T. Probing myelin content of the human brain with MRI: A review. Magn Reson Med 2020; 85:627-652. [PMID: 32936494 DOI: 10.1002/mrm.28509] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Revised: 08/12/2020] [Accepted: 08/17/2020] [Indexed: 12/11/2022]
Abstract
Rapid and efficient transmission of electric signals among neurons of vertebrates is ensured by myelin-insulating sheaths surrounding axons. Human cognition, sensation, and motor functions rely on the integrity of these layers, and demyelinating diseases often entail serious cognitive and physical impairments. Magnetic resonance imaging radically transformed the way these disorders are monitored, offering an irreplaceable tool to noninvasively examine the brain structure. Several advanced techniques based on MRI have been developed to provide myelin-specific contrasts and a quantitative estimation of myelin density in vivo. Here, the vast offer of acquisition strategies developed to date for this task is reviewed. Advantages and pitfalls of the different approaches are compared and discussed.
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Affiliation(s)
- Gian Franco Piredda
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland.,Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Tom Hilbert
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland.,Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Jean-Philippe Thiran
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland.,Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,LTS5, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
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15
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Piredda GF, Hilbert T, Canales-Rodríguez EJ, Pizzolato M, von Deuster C, Meuli R, Pfeuffer J, Daducci A, Thiran JP, Kober T. Fast and high-resolution myelin water imaging: Accelerating multi-echo GRASE with CAIPIRINHA. Magn Reson Med 2020; 85:209-222. [PMID: 32720406 DOI: 10.1002/mrm.28427] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Revised: 06/17/2020] [Accepted: 06/23/2020] [Indexed: 02/06/2023]
Abstract
PURPOSE Although several MRI methods have been explored to achieve in vivo myelin quantification, imaging the whole brain in clinically acceptable times and sufficiently high resolution remains challenging. To address this problem, this work investigates the acceleration of multi-echo T2 acquisitions based on the multi-echo gradient and spin echo (GRASE) sequence using CAIPIRINHA undersampling and adapted k-space reordering patterns. METHODS A prototype multi-echo GRASE sequence supporting CAIPIRINHA parallel imaging was implemented. Multi-echo T2 data were acquired from 12 volunteers using the implemented sequence (1.6 × 1.6 × 1.6 mm3 , 84 slices, acquisition time [TA] = 10:30 min) and a multi-echo spin echo (MESE) sequence as reference (1.6 × 1.6 × 3.2 mm3 , single-slice, TA = 5:41 min). Myelin water fraction (MWF) maps derived from both acquisitions were compared via correlation and Bland-Altman analyses. In addition, scan-rescan datasets were acquired to evaluate the repeatability of the derived maps. RESULTS Resulting maps from the MESE and multi-echo GRASE sequences were found to be correlated (r = 0.83). The Bland-Altman analysis revealed a mean bias of -0.2% (P = .24) with the limits of agreement ranging from -3.7% to 3.3%. The Pearson's correlation coefficient among MWF values obtained from the scan-rescan datasets was found to be 0.95 and the mean bias equal to 0.11% (P = .32), indicating good repeatability of the retrieved maps. CONCLUSION By combining a 3D multi-echo GRASE sequence with CAIPIRINHA sampling, whole-brain MWF maps were obtained in 10:30 min with 1.6 mm isotropic resolution. The good correlation with conventional MESE-based maps demonstrates that the implemented sequence may be a promising alternative to time-consuming MESE acquisitions.
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Affiliation(s)
- Gian Franco Piredda
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tom Hilbert
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Erick Jorge Canales-Rodríguez
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- FIDMAG Germanes Hospitalàries, Sant Boi de Llobregat, Barcelona, Spain
| | - Marco Pizzolato
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Constantin von Deuster
- Siemens Healthcare AG, Zurich, Switzerland
- SCMI, Swiss Center for Musculoskeletal Imaging, Zurich, Switzerland
| | - Reto Meuli
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Josef Pfeuffer
- Application Development, Siemens Healthcare GmbH, Erlangen, Germany
| | | | - Jean-Philippe Thiran
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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16
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Jung S, Lee H, Ryu K, Song JE, Park M, Moon WJ, Kim DH. Artificial neural network for multi-echo gradient echo-based myelin water fraction estimation. Magn Reson Med 2020; 85:380-389. [PMID: 32686208 DOI: 10.1002/mrm.28407] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2020] [Revised: 06/09/2020] [Accepted: 06/09/2020] [Indexed: 02/01/2023]
Abstract
PURPOSE To demonstrate robust myelin water fraction (MWF) mapping using an artificial neural network (ANN) with multi-echo gradient-echo (GRE) signal. METHODS Multi-echo gradient-echo signals simulated with a three-pool exponential model were used to generate the training data set for the ANN, which was designed to yield the MWF. We investigated the performance of our proposed ANN for various conditions using both numerical simulations and in vivo data. Simulations were conducted with various SNRs to investigate the performance of the ANN. In vivo data with high spatial resolutions were applied in the analyses, and results were compared with MWFs derived by the nonlinear least-squares algorithm using a complex three-pool exponential model. RESULTS The network results for the simulations show high accuracies against noise compared with nonlinear least-squares MWFs: RMS-error value of 5.46 for the nonlinear least-squares MWF and 3.56 for the ANN MWF at an SNR of 150 (relative gain = 34.80%). These effects were also found in the in vivo data, with reduced SDs in the region-of-interest analyses. These effects of the ANN demonstrate the feasibility of acquiring high-resolution myelin water images. CONCLUSION The simulation results and in vivo data suggest that the ANN facilitates more robust MWF mapping in multi-echo gradient-echo sequences compared with the conventional nonlinear least-squares method.
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Affiliation(s)
- Soozy Jung
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Hongpyo Lee
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Kanghyun Ryu
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Jae Eun Song
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Mina Park
- Department of Radiology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Won-Jin Moon
- Department of Radiology, Konkuk University Medical Center, Konkuk University School of Medicine, Seoul, Republic of Korea
| | - Dong-Hyun Kim
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
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17
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Xiang B, Wen J, Lu HC, Schmidt RE, Yablonskiy DA, Cross AH. In vivo evolution of biopsy-proven inflammatory demyelination quantified by R2t* mapping. Ann Clin Transl Neurol 2020; 7:1055-1060. [PMID: 32367692 PMCID: PMC7317639 DOI: 10.1002/acn3.51052] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Revised: 03/22/2020] [Accepted: 04/10/2020] [Indexed: 11/09/2022] Open
Abstract
A 35‐year‐old man with an enhancing tumefactive brain lesion underwent biopsy, revealing inflammatory demyelination. We used quantitative Gradient‐Recalled‐Echo (qGRE) MRI to visualize and measure tissue damage in the lesion. Two weeks after biopsy, qGRE showed significant R2t* reduction in the left optic radiation and surrounding tissue, consistent with the histopathological and clinical findings. qGRE was repeated 6 and 14 months later, demonstrating partially recovered optic radiation R2t*, in concert with improvement of the hemianopia to ultimately involve only the lower right visual quadrant. These results support qGRE metrics as in vivo biomarkers for tissue damage and longitudinal monitoring of demyelinating disease.
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Affiliation(s)
- Biao Xiang
- Department of Radiology, Washington University, St. Louis, Missouri, 63110
| | - Jie Wen
- Department of Radiology, Washington University, St. Louis, Missouri, 63110
| | - Hsiang-Chih Lu
- Department of Pathology & Immunology, Washington University, St. Louis, Missouri, 63110
| | - Robert E Schmidt
- Department of Pathology & Immunology, Washington University, St. Louis, Missouri, 63110
| | | | - Anne H Cross
- Department of Neurology, Washington University, St. Louis, Missouri, 63110
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18
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Faizy TD, Thaler C, Broocks G, Flottmann F, Leischner H, Kniep H, Nawabi J, Schön G, Stellmann JP, Kemmling A, Reddy R, Heit JJ, Fiehler J, Kumar D, Hanning U. The Myelin Water Fraction Serves as a Marker for Age-Related Myelin Alterations in the Cerebral White Matter - A Multiparametric MRI Aging Study. Front Neurosci 2020; 14:136. [PMID: 32153358 PMCID: PMC7050496 DOI: 10.3389/fnins.2020.00136] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2019] [Accepted: 02/03/2020] [Indexed: 12/13/2022] Open
Abstract
Quantitative MRI modalities, such as diffusion tensor imaging (DTI) or magnetization transfer imaging (MTI) are sensitive to the neuronal effects of aging of the cerebral white matter (WM), but lack the specificity for myelin content. Myelin water imaging (MWI) is highly specific for myelin and may be more sensitive for the detection of changes in myelin content inside the cerebral WM microstructure. In this multiparametric imaging study, we evaluated the performance of myelin water fraction (MWF) estimates as a marker for myelin alterations during normal-aging. Multiparametric MRI data derived from DTI, MTI and a novel, recently-proposed MWF-map processing and reconstruction algorithm were acquired from 54 healthy subjects (aged 18-79 years) and region-based multivariate regression analysis was performed. MWFs significantly decreased with age in most WM regions (except corticospinal tract) and changes of MWFs were associated with changes of radial diffusivity, indicating either substantial alterations or preservation of myelin content in these regions. Decreases of fractional anisotropy and magnetization transfer ratio were associated with lower MWFs in commissural fiber tracts only. Mean diffusivity had no regional effects on MWF. We conclude that MWF estimates are sensitive for the assessment of age-related myelin alterations in the cerebral WM of normal-aging brains.
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Affiliation(s)
- Tobias D Faizy
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Christian Thaler
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Gabriel Broocks
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Fabian Flottmann
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Hannes Leischner
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Helge Kniep
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jawed Nawabi
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Gerhard Schön
- Institute of Applied Biometrics and Epidemiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jan-Patrick Stellmann
- Institute of Neuroimmunology and Multiple Sclerosis, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.,Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - André Kemmling
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Muenster, Münster, Germany
| | - Ravinder Reddy
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
| | - Jeremy J Heit
- Department of Radiology, Stanford University School of Medicine, Palo Alto, CA, United States
| | - Jens Fiehler
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Dushyant Kumar
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.,Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
| | - Uta Hanning
- Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
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19
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Dvorak AV, Wiggermann V, Gilbert G, Vavasour IM, MacMillan EL, Barlow L, Wiley N, Kozlowski P, MacKay AL, Rauscher A, Kolind SH. Multi-spin echo T 2 relaxation imaging with compressed sensing (METRICS) for rapid myelin water imaging. Magn Reson Med 2020; 84:1264-1279. [PMID: 32065474 DOI: 10.1002/mrm.28199] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Revised: 12/20/2019] [Accepted: 01/13/2020] [Indexed: 12/11/2022]
Abstract
PURPOSE Myelin water imaging (MWI) provides a valuable biomarker for myelin, but clinical application has been restricted by long acquisition times. Accelerating the standard multi-echo T2 acquisition with gradient echoes (GRASE) or by 2D multi-slice data collection results in image blurring, contrast changes, and other issues. Compressed sensing (CS) can vastly accelerate conventional MRI. In this work, we assessed the use of CS for in vivo human MWI, using a 3D multi spin-echo sequence. METHODS We implemented multi-echo T2 relaxation imaging with compressed sensing (METRICS) and METRICS with partial Fourier acceleration (METRICS-PF). Scan-rescan data were acquired from 12 healthy controls for assessment of repeatability. MWI data were acquired for METRICS in 9 m:58 s and for METRICS-PF in 7 m:25 s, both with 1.5 × 2 × 3 mm3 voxels, 56 echoes, 7 ms ΔTE, and 240 × 240 × 170 mm3 FOV. METRICS was compared with a novel multi-echo spin-echo gold-standard (MSE-GS) MWI acquisition, acquired for a single additional subject in 2 h:2 m:40 s. RESULTS METRICS/METRICS-PF myelin water fraction had mean: repeatability coefficient 1.5/1.1, coefficient of variation 6.2/4.5%, and intra-class correlation coefficient 0.79/0.84. Repeatability metrics comparing METRICS with METRICS-PF were similar, and both sequences agreed with reference values from literature. METRICS images and quantitative maps showed excellent qualitative agreement with those of MSE-GS. CONCLUSION METRICS and METRICS-PF provided highly repeatable MWI data without the inherent disadvantages of GRASE or 2D multi-slice acquisition. CS acceleration allows MWI data to be acquired rapidly with larger FOV, higher estimated SNR, more isotropic voxels and more echoes than with previous techniques. The approach introduced here generalizes to any multi-component T2 mapping application.
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Affiliation(s)
- Adam V Dvorak
- Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, British Columbia, Canada
| | - Vanessa Wiggermann
- Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Pediatrics, University of British Columbia, Vancouver, British Columbia, Canada.,UBC MRI Research Centre, University of British Columbia, Vancouver, British Columbia, Canada
| | | | - Irene M Vavasour
- Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Erin L MacMillan
- UBC MRI Research Centre, University of British Columbia, Vancouver, British Columbia, Canada.,MR Clinical Science, Philips Canada, Markham, Ontario, Canada.,Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Laura Barlow
- UBC MRI Research Centre, University of British Columbia, Vancouver, British Columbia, Canada
| | - Neale Wiley
- UBC MRI Research Centre, University of British Columbia, Vancouver, British Columbia, Canada
| | - Piotr Kozlowski
- International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, British Columbia, Canada.,UBC MRI Research Centre, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Alex L MacKay
- Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,UBC MRI Research Centre, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Alexander Rauscher
- Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Pediatrics, University of British Columbia, Vancouver, British Columbia, Canada.,UBC MRI Research Centre, University of British Columbia, Vancouver, British Columbia, Canada
| | - Shannon H Kolind
- Department of Physics and Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, British Columbia, Canada.,UBC MRI Research Centre, University of British Columbia, Vancouver, British Columbia, Canada.,Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,Division of Neurology, Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada
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20
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Zimmermann M, Oros-Peusquens AM, Iordanishvili E, Shin S, Yun SD, Abbas Z, Shah NJ. Multi-Exponential Relaxometry Using l 1 -Regularized Iterative NNLS (MERLIN) With Application to Myelin Water Fraction Imaging. IEEE TRANSACTIONS ON MEDICAL IMAGING 2019; 38:2676-2686. [PMID: 30990178 DOI: 10.1109/tmi.2019.2910386] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
A new parameter estimation algorithm, MERLIN, is presented for accurate and robust multi-exponential relaxometry using magnetic resonance imaging, a tool that can provide valuable insight into the tissue microstructure of the brain. Multi-exponential relaxometry is used to analyze the myelin water fraction and can help to detect related diseases. However, the underlying problem is ill-conditioned, and as such, is extremely sensitive to noise and measurement imperfections, which can lead to less precise and more biased parameter estimates. MERLIN is a fully automated, multi-voxel approach that incorporates state-of-the-art l1 -regularization to enforce sparsity and spatial consistency of the estimated distributions. The proposed method is validated in simulations and in vivo experiments, using a multi-echo gradient-echo (MEGE) sequence at 3 T. MERLIN is compared to the conventional single-voxel l2 -regularized NNLS (rNNLS) and a multi-voxel extension with spatial priors (rNNLS + SP), where it consistently showed lower root mean squared errors of up to 70 percent for all parameters of interest in these simulations.
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21
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Imaging the multiple sclerosis lesion: insights into pathogenesis, progression and repair. Curr Opin Neurol 2019; 32:338-345. [DOI: 10.1097/wco.0000000000000698] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
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22
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Ali TS, Tourell MC, Hugo HJ, Pyke C, Yang S, Lloyd T, Thompson EW, Momot KI. Transverse relaxation-based assessment of mammographic density and breast tissue composition by single-sided portable NMR. Magn Reson Med 2019; 82:1199-1213. [PMID: 31034648 DOI: 10.1002/mrm.27781] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2018] [Revised: 04/02/2019] [Accepted: 04/02/2019] [Indexed: 02/06/2023]
Abstract
PURPOSE Elevated mammographic density (MD) is an independent risk factor for breast cancer (BC) as well as a source of masking in X-ray mammography. High-frequency longitudinal monitoring of MD could also be beneficial in hormonal BC prevention, where early MD changes herald the treatment's success. We present a novel approach to quantification of MD in breast tissue using single-sided portable NMR. Its development was motivated by the low cost of portable-NMR instrumentation, the suitability for measurements in vivo, and the absence of ionizing radiation. METHODS Five breast slices were obtained from three patients undergoing prophylactic mastectomy or breast reduction surgery. Carr-Purcell-Meiboom-Gill (CPMG) relaxation curves were measured from (1) regions of high and low MD (HMD and LMD, respectively) in the full breast slices; (2) the same regions excised from the full slices; and (3) excised samples after H2 O-D2 O replacement. T2 distributions were reconstructed from the CPMG decays using inverse Laplace transform. RESULTS Two major peaks, identified as fat and water, were consistently observed in the T2 distributions of HMD regions. The LMD T2 distributions were dominated by the fat peak. The relative areas of the two peaks exhibited statistically significant (P < .005) differences between HMD and LMD regions, enabling their classification as HMD or LMD. The relative-area distributions exhibited no statistically significant differences between full slices and excised samples. CONCLUSION T2 -based portable-NMR analysis is a novel approach to MD quantification. The ability to quantify tissue composition, combined with the low cost of instrumentation, make this approach promising for clinical applications.
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Affiliation(s)
- Tonima S Ali
- School of Chemistry, Physics and Mechanical Engineering, Queensland University of Technology (QUT), Brisbane, Australia.,Institute of Health and Biomedical Innovation, Queensland University of Technology (QUT), Brisbane, Australia
| | - Monique C Tourell
- School of Chemistry, Physics and Mechanical Engineering, Queensland University of Technology (QUT), Brisbane, Australia.,Institute of Health and Biomedical Innovation, Queensland University of Technology (QUT), Brisbane, Australia
| | - Honor J Hugo
- Institute of Health and Biomedical Innovation, Queensland University of Technology (QUT), Brisbane, Australia.,School of Biomedical Sciences, Faculty of Health, Queensland University of Technology (QUT), Brisbane, Australia.,Translational Research Institute, Woolloongabba, Australia
| | - Chris Pyke
- Department of Surgery, Mater Hospital, University of Queensland, St Lucia, Australia
| | - Samuel Yang
- Department of Plastic and Reconstructive Surgery, Greenslopes Private Hospital, Brisbane, Australia
| | - Thomas Lloyd
- Division of Radiology, Princess Alexandra Hospital, Woolloongabba, Australia
| | - Erik W Thompson
- Institute of Health and Biomedical Innovation, Queensland University of Technology (QUT), Brisbane, Australia.,School of Biomedical Sciences, Faculty of Health, Queensland University of Technology (QUT), Brisbane, Australia.,Translational Research Institute, Woolloongabba, Australia.,University of Melbourne Department of Surgery, St Vincent's Hospital, Melbourne, Australia
| | - Konstantin I Momot
- School of Chemistry, Physics and Mechanical Engineering, Queensland University of Technology (QUT), Brisbane, Australia.,Institute of Health and Biomedical Innovation, Queensland University of Technology (QUT), Brisbane, Australia
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Burlina AP, Lachmann RH, Manara R, Cazzorla C, Celato A, van Spronsen FJ, Burlina A. The neurological and psychological phenotype of adult patients with early-treated phenylketonuria: A systematic review. J Inherit Metab Dis 2019; 42:209-219. [PMID: 30690773 DOI: 10.1002/jimd.12065] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/10/2018] [Accepted: 01/21/2019] [Indexed: 11/11/2022]
Abstract
Newborn screening for phenylketonuria (PKU) and early introduction of dietary therapy has been remarkably successful in preventing the severe neurological features of PKU, including mental retardation and epilepsy. However, concerns remain that long-term outcome is still suboptimal, particularly in adult patients who are no longer on strict phenylalanine-restricted diets. With our systematic literature review we aimed to describe the neurological phenotype of adults with early-treated phenylketonuria (ETPKU). The literature search covered the period from 1 January 1990 up to 16 April 2018, using the NLM MEDLINE controlled vocabulary. Of the 643 records initially identified, 83 were included in the analysis. The most commonly reported neurological signs were tremor and hyperreflexia. The overall quality of life (QoL) of ETPKU adults was good or comparable to control populations, and there was no evidence for a significant incidence of psychiatric disease or social difficulties. Neuroimaging revealed that brain abnormalities are present in ETPKU adults, but their clinical significance remains unclear. Generally, intelligence quotient (IQ) appears normal but specific deficits in neuropsychological and social functioning were reported in early-treated adults compared with healthy individuals. However, accurately defining the prevalence of these deficits is complicated by the lack of standardized neuropsychological tests. Future research should employ standardized neurological, neuropsychological, and neuroimaging protocols, and consider other techniques such as advanced imaging analyses and the recently validated PKU-specific QoL questionnaire, to precisely define the nature of the impairments within the adult ETPKU population and how these relate to metabolic control throughout life.
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Affiliation(s)
| | - Robin H Lachmann
- Charles Dent Metabolic Unit, National Hospital for Neurology and Neurosurgery, London, UK
| | - Renzo Manara
- Department of Medicine and Surgery, University of Salerno, Salerno, Italy
| | - Chiara Cazzorla
- Division of Inborn Metabolic Diseases, Department of Paediatrics, University Hospital, Padua, Italy
| | - Andrea Celato
- Division of Inborn Metabolic Diseases, Department of Paediatrics, University Hospital, Padua, Italy
| | - Francjan J van Spronsen
- Division of Metabolic Diseases, Beatrix Children's Hospital, University Medical Center of Groningen, University of Groningen, Groningen, The Netherlands
| | - Alberto Burlina
- Division of Inborn Metabolic Diseases, Department of Paediatrics, University Hospital, Padua, Italy
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Alonso-Ortiz E, Levesque IR, Pike GB. Impact of magnetic susceptibility anisotropy at 3 T and 7 T on T2*-based myelin water fraction imaging. Neuroimage 2018; 182:370-378. [DOI: 10.1016/j.neuroimage.2017.09.040] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2017] [Revised: 08/14/2017] [Accepted: 09/20/2017] [Indexed: 10/18/2022] Open
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25
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Laule C, Moore GW. Myelin water imaging to detect demyelination and remyelination and its validation in pathology. Brain Pathol 2018; 28:750-764. [PMID: 30375119 PMCID: PMC8028667 DOI: 10.1111/bpa.12645] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2018] [Accepted: 07/09/2018] [Indexed: 12/11/2022] Open
Abstract
Damage to myelin is a key feature of multiple sclerosis (MS) pathology. Magnetic resonance imaging (MRI) has revolutionized our ability to detect and monitor MS pathology in vivo. Proton density, T1 and T2 can provide qualitative contrast weightings that yield superb in vivo visualization of central nervous system tissue and have proved invaluable as diagnostic and patient management tools in MS. However, standard clinical MR methods are not specific to the types of tissue damage they visualize, and they cannot detect subtle abnormalities in tissue that appears otherwise normal on conventional MRIs. Myelin water imaging is an MR method that provides in vivo measurement of myelin. Histological validation work in both human brain and spinal cord tissue demonstrates a strong correlation between myelin water and staining for myelin, validating myelin water as a marker for myelin. Myelin water varies throughout the brain and spinal cord in healthy controls, and shows good intra- and inter-site reproducibility. MS plaques show variably decreased myelin water fraction, with older lesions demonstrating the greatest myelin loss. Longitudinal study of myelin water can provide insights into the dynamics of demyelination and remyelination in plaques. Normal appearing brain and spinal cord tissues show reduced myelin water, an abnormality which becomes progressively more evident over a timescale of years. Diffusely abnormal white matter, which is evident in 20%-25% of MS patients, also shows reduced myelin water both in vivo and postmortem, and appears to originate from a primary lipid abnormality with relative preservation of myelin proteins. Active research is ongoing in the quest to refine our ability to image myelin and its perturbations in MS and other disorders of the myelin sheath.
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Affiliation(s)
- Cornelia Laule
- RadiologyUniversity of British ColumbiaVancouverBCCanada
- Pathology & Laboratory MedicineUniversity of British ColumbiaVancouverBCCanada
- Physics & AstronomyUniversity of British ColumbiaVancouverBCCanada
- International Collaboration on Repair Discoveries (ICORD)University of British ColumbiaVancouverBCCanada
| | - G.R. Wayne Moore
- Pathology & Laboratory MedicineUniversity of British ColumbiaVancouverBCCanada
- International Collaboration on Repair Discoveries (ICORD)University of British ColumbiaVancouverBCCanada
- Medicine (Neurology)University of British ColumbiaVancouverBCCanada
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26
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Using 3D spatial correlations to improve the noise robustness of multi component analysis of 3D multi echo quantitative T2 relaxometry data. Neuroimage 2018; 178:583-601. [PMID: 29763672 DOI: 10.1016/j.neuroimage.2018.05.026] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2018] [Revised: 05/07/2018] [Accepted: 05/08/2018] [Indexed: 12/18/2022] Open
Abstract
PURPOSE We present a computationally feasible and iterative multi-voxel spatially regularized algorithm for myelin water fraction (MWF) reconstruction. This method utilizes 3D spatial correlations present in anatomical/pathological tissues and underlying B1+-inhomogeneity or flip angle inhomogeneity to enhance the noise robustness of the reconstruction while intrinsically accounting for stimulated echo contributions using T2-distribution data alone. METHODS Simulated data and in vivo data acquired using 3D non-selective multi-echo spin echo (3DNS-MESE) were used to compare the reconstruction quality of the proposed approach against those of the popular algorithm (the method by Prasloski et al.) and our previously proposed 2D multi-slice spatial regularization spatial regularization approach. We also investigated whether the inter-sequence correlations and agreements improved as a result of the proposed approach. MWF-quantifications from two sequences, 3DNS-MESE vs 3DNS-gradient and spin echo (3DNS-GRASE), were compared for both reconstruction approaches to assess correlations and agreements between inter-sequence MWF-value pairs. MWF values from whole-brain data of six volunteers and two multiple sclerosis patients are being reported as well. RESULTS In comparison with competing approaches such as Prasloski's method or our previously proposed 2D multi-slice spatial regularization method, the proposed method showed better agreements with simulated truths using regression analyses and Bland-Altman analyses. For 3DNS-MESE data, MWF-maps reconstructed using the proposed algorithm provided better depictions of white matter structures in subcortical areas adjoining gray matter which agreed more closely with corresponding contrasts on T2-weighted images than MWF-maps reconstructed with the method by Prasloski et al. We also achieved a higher level of correlations and agreements between inter-sequence (3DNS-MESE vs 3DNS-GRASE) MWF-value pairs. CONCLUSION The proposed algorithm provides more noise-robust fits to T2-decay data and improves MWF-quantifications in white matter structures especially in the sub-cortical white matter and major white matter tract regions.
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27
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Cohen-Adad J. Microstructural imaging in the spinal cord and validation strategies. Neuroimage 2018; 182:169-183. [PMID: 29635029 DOI: 10.1016/j.neuroimage.2018.04.009] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2017] [Revised: 03/02/2018] [Accepted: 04/06/2018] [Indexed: 12/13/2022] Open
Abstract
In vivo histology using magnetic resonance imaging (MRI) is a newly emerging research field that aims to non-invasively characterize tissue microstructure. The implications of in vivo histology are many, from discovering novel biomarkers to studying human development, to providing tools for disease diagnosis and monitoring the effects of novel treatments on tissue. This review focuses on quantitative MRI (qMRI) techniques that are used to map spinal cord microstructure. Opening with a rationale for non-invasive imaging of the spinal cord, this article continues with a brief overview of the existing MRI techniques for axon and myelin imaging, followed by the specific challenges and potential solutions for acquiring and processing such data. The final part of this review focuses on histological validation, with suggested tissue preparation, acquisition and processing protocols for large-scale microscopy.
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Affiliation(s)
- J Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada; Functional Neuroimaging Unit, CRIUGM, Université de Montréal, Montreal, QC, Canada.
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28
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Does MD. Inferring brain tissue composition and microstructure via MR relaxometry. Neuroimage 2018; 182:136-148. [PMID: 29305163 DOI: 10.1016/j.neuroimage.2017.12.087] [Citation(s) in RCA: 72] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2017] [Revised: 12/25/2017] [Accepted: 12/27/2017] [Indexed: 11/28/2022] Open
Abstract
MRI relaxometry is sensitive to a variety of tissue characteristics in a complex manner, which makes it both attractive and challenging for characterizing tissue. This article reviews the most common water proton relaxometry measures, T1, T2, and T2*, and reports on their development and current potential to probe the composition and microstructure of brain tissue. The development of these relaxometry measures is challenged by the need for suitably accurate tissue models, as well as robust acquisition and analysis methodologies. MRI relaxometry has been established as a tool for characterizing neural tissue, particular with respect to myelination, and the potential for further development exists.
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Affiliation(s)
- Mark D Does
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA; Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Electrical Engineering, Vanderbilt University, Nashville, TN, USA.
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29
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Characterization of brain tumours with spin–spin relaxation: pilot case study reveals unique T 2 distribution profiles of glioblastoma, oligodendroglioma and meningioma. J Neurol 2017; 264:2205-2214. [DOI: 10.1007/s00415-017-8609-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2017] [Revised: 08/28/2017] [Accepted: 08/31/2017] [Indexed: 11/26/2022]
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30
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Alonso-Ortiz E, Levesque IR, Pike GB. Multi-gradient-echo myelin water fraction imaging: Comparison to the multi-echo-spin-echo technique. Magn Reson Med 2017; 79:1439-1446. [DOI: 10.1002/mrm.26809] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2016] [Revised: 05/06/2017] [Accepted: 05/31/2017] [Indexed: 12/19/2022]
Affiliation(s)
- Eva Alonso-Ortiz
- Department of Medical Physics; The Ottawa Hospital Cancer Centre; Ottawa Canada
| | - Ives R. Levesque
- Medical Physics Unit, McGill University; Montreal Canada
- Department of Oncology; McGill University; Montreal Canada
- Research Institute of the McGill University Health Centre; McGill University; Montreal Canada
| | - G. Bruce Pike
- Medical Physics Unit, McGill University; Montreal Canada
- McConnell Brain Imaging Centre, McGill University; Montreal Canada
- Department of Radiology and Hotchkiss Brain Institute; University of Calgary; Calgary Canada
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31
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Abstract
Myelin is critical for healthy brain function. An accurate in vivo measure of myelin content has important implications for understanding brain plasticity and neurodegenerative diseases. Myelin water imaging is a magnetic resonance imaging method which can be used to visualize myelination in the brain and spinal cord in vivo. This review presents an overview of myelin water imaging data acquisition and analysis, post-mortem validation work, findings in both animal and human studies and a brief discussion about other MR techniques purported to provide in vivo myelin content. Multi-echo T2 relaxation approaches continue to undergo development and whole-brain imaging time now takes less than 10 minutes; the standard analysis method for this type of data acquisition is a non-negative least squares approach. Alternate methods including the multi-flip angle gradient echo mcDESPOT are also being used for myelin water imaging. Histological validation studies in animal and human brain and spinal cord tissue demonstrate high specificity of myelin water imaging for myelin. Potential confounding factors for in vivo myelin water fraction measurement include the presence of myelin debris and magnetization exchange processes. Myelin water imaging has successfully been used to study animal models of injury, applied in healthy human controls and can be used to assess damage and injury in conditions such as multiple sclerosis, neuromyelitis optica, schizophrenia, phenylketonuria, neurofibromatosis, niemann pick’s disease, stroke and concussion. Other quantitative magnetic resonance approaches that are sensitive to, but not specific for, myelin exist including magnetization transfer, diffusion tensor imaging and T1 weighted imaging.
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Affiliation(s)
- Alex L MacKay
- Department of Radiology, University of British Columbia, Vancouver, Canada.,Department of Physics and Astronomy, University of British Columbia, Vancouver, Canada
| | - Cornelia Laule
- Department of Radiology, University of British Columbia, Vancouver, Canada.,Department of Pathology & Laboratory Medicine, University of British Columbia, Vancouver, Canada.,International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, Canada
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32
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Alonso-Ortiz E, Levesque IR, Paquin R, Pike GB. Field inhomogeneity correction for gradient echo myelin water fraction imaging. Magn Reson Med 2016; 78:49-57. [DOI: 10.1002/mrm.26334] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2016] [Revised: 06/06/2016] [Accepted: 06/16/2016] [Indexed: 12/20/2022]
Affiliation(s)
- Eva Alonso-Ortiz
- Medical Physics Unit, McGill University, 3801 University Street, Montreal, QC, H3A 2B4, Canada.,McConnell Brain Imaging Centre, McGill University, 3801 University Street, Montreal, QC, H3A 2B4, Canada
| | - Ives R Levesque
- Medical Physics Unit, McGill University, 3801 University Street, Montreal, QC, H3A 2B4, Canada.,Department of Oncology, McGill University, 3801 University Street, Montreal, QC, H3A 2B4, Canada.,Research Institute of the McGill University Health Centre, McGill University, 3801 University Street, Montreal, QC, H3A 2B4, Canada
| | | | - G Bruce Pike
- Medical Physics Unit, McGill University, 3801 University Street, Montreal, QC, H3A 2B4, Canada.,McConnell Brain Imaging Centre, McGill University, 3801 University Street, Montreal, QC, H3A 2B4, Canada.,Department of Radiology and Hotchkiss Brain Institute, University of Calgary, 3330 Hospital Drive NW, Calgary, AB, T2N 4N1, Canada
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33
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Heterogeneity of Multiple Sclerosis Lesions in Multislice Myelin Water Imaging. PLoS One 2016; 11:e0151496. [PMID: 26990645 PMCID: PMC4798764 DOI: 10.1371/journal.pone.0151496] [Citation(s) in RCA: 53] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2015] [Accepted: 02/29/2016] [Indexed: 11/19/2022] Open
Abstract
Purpose To assess neuroprotection and remyelination in Multiple Sclerosis (MS), we applied a more robust myelin water imaging (MWI) processing technique, including spatial priors into image reconstruction, which allows for lower SNR, less averages and shorter acquisition times. We sought to evaluate this technique in MS-patients and healthy controls (HC). Materials and Methods Seventeen MS-patients and 14 age-matched HCs received a 3T Magnetic Resonance Imaging (MRI) examination including MWI (8 slices, 12 minutes acquisition time), T2w and T1mprage pre and post gadolinium (GD) administration. Black holes (BH), contrast enhancing lesions (CEL) and T2 lesions were marked and registered to MWI. Additionally, regions of interest (ROI) were defined in the frontal, parietal and occipital normal appearing white matter (NAWM)/white matter (WM), the corticospinal tract (CST), the splenium (SCC) and genu (GCC) of the corpus callosum in patients and HCs. Mean values of myelin water fraction (MWF) were determined for each ROI. Results Significant differences (p≤0.05) of the MWF were found in all three different MS-lesion types (BH, CEL, T2 lesions), compared to the WM of HCs. The mean MWF values among the different lesion types were significantly differing from each other. Comparing MS-patients vs. HCs, we found a significant (p≤0.05) difference of the MWF in all measured ROIs except of GCC and SCC. The mean reduction of MWF in the NAWM of MS-patients compared to HCs was 37%. No age, sex, disability score and disease duration dependency was found for the NAWM MWF. Conclusion MWF measures were in line with previous studies and lesions were clearly visible in MWI. MWI allows for quantitative assessment of NAWM and lesions in MS, which could be used as an additional sensitive imaging endpoint for larger MS studies. Measurements of the MWF also differ between patients and healthy controls.
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Nguyen TD, Deh K, Monohan E, Pandya S, Spincemaille P, Raj A, Wang Y, Gauthier SA. Feasibility and reproducibility of whole brain myelin water mapping in 4 minutes using fast acquisition with spiral trajectory and adiabatic T2prep (FAST-T2) at 3T. Magn Reson Med 2015; 76:456-65. [PMID: 26331978 DOI: 10.1002/mrm.25877] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2015] [Revised: 06/17/2015] [Accepted: 07/07/2015] [Indexed: 11/12/2022]
Abstract
PURPOSE To develop and measure the reproducibility of 4-min whole brain myelin water fraction (MWF) mapping using fast acquisition with spiral trajectory and T2prep (FAST-T2) sequence at 3T. METHODS Experiments were performed on phantoms, 13 volunteers, and 16 patients with multiple sclerosis. MWF maps were extracted using a spatially constrained non-linear algorithm. The proposed adiabatic modified BIR-4 (mBIR-4) T2prep was compared with the conventional composite T2prep (COMP). The effect of reducing the number of echo times (TEs) from 15 to 6 (reducing scan time from 10 to 4 min) was evaluated. Reproducibility was assessed using correlation analysis, coefficient of variation (COV), and Bland-Altman plots. RESULTS Compared with COMP, mBIR-4 provided more accurate T2 in phantoms and better MWF maps in human brains. Reducing the number of TEs had a negligible effect on MWF map quality, with a regional MWF difference of <0.8%. Regional MWFs obtained by repeated scans showed excellent correlation (R = 0.99), low COV (1.3%-2.4%), and negligible bias within ±1% limits of agreement. On a voxel-wise basis, the agreement remained strong (correlation R = 0.89 ± 0.03, bias = 0.01% ± 0.29%, limits of agreement = [-3.35% ± 0.73%, 3.33% ± 0.61%]). CONCLUSION Whole brain MWF mapping with adiabatic FAST-T2 is feasible in 4 min and provides good intrasite reproducibility. Magn Reson Med 76:456-465, 2016. © 2015 Wiley Periodicals, Inc.
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Affiliation(s)
- Thanh D Nguyen
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Kofi Deh
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Elizabeth Monohan
- Department of Neurology and Neuroscience, Weill Cornell Medical College, New York, New York, USA
| | - Sneha Pandya
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Pascal Spincemaille
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Ashish Raj
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Yi Wang
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Susan A Gauthier
- Department of Neurology and Neuroscience, Weill Cornell Medical College, New York, New York, USA
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Ali TS, Bjarnason TA, Senger DL, Dunn JF, Joseph JT, Mitchell JR. QuantitativeT2: interactive quantitative T2 MRI witnessed in mouse glioblastoma. J Med Imaging (Bellingham) 2015. [PMID: 26213695 DOI: 10.1117/1.jmi.2.3.036002] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
The aim of this study was to establish an advanced analytical platform for complex in vivo pathologies. We have developed a software program, QuantitativeT2, for voxel-based real-time quantitative T2 magnetic resonance imaging. We analyzed murine brain tumors to confirm feasibility of our method for neurological conditions. Anesthetized mice (with invasive gliomas, and controls) were imaged on a 9.4 Tesla scanner using a Carr-Purcell-Meiboom-Gill sequence. The multiecho T2 decays from axial brain slices were analyzed using QuantitativeT2. T2 distribution histograms demonstrated substantial characteristic differences between normal and pathological brain tissues. Voxel-based quantitative maps of tissue water fraction (WF) and geometric mean T2 (gmT2) revealed the heterogeneous alterations to water compartmentalization caused by pathology. The numeric distribution of WF and gmT2 indicated the extent of tumor infiltration. Relative evaluations between in vivo scans and ex vivo histology indicated that the T2s between 30 and 150 ms were related to cellular density and the integrity of the extracellular matrix. Overall, QuantitativeT2 has demonstrated significant advancements in qT2 analysis with real-time operation. It is interactive with an intuitive workflow; can analyze data from many MR manufacturers; and is released as open-source code to encourage examination, improvement, and expansion of this method.
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Affiliation(s)
- Tonima Sumya Ali
- Queensland University of Technology , Science and Engineering Faculty, Department of Biomedical Engineering and Medical Physics, 2 George Street, Brisbane, QLD 4000, Australia
| | - Thorarin Albert Bjarnason
- Diagnostic Imaging Services , Interior Health, 101-3330 Richter Street, Kelowna V1W 4V5, Canada ; University of British Columbia , Department of Radiology, 2329 W Mall, Vancouver V6T 1Z4, Canada ; University of British Columbia Okanagan , 3333 University Way, Kelowna V1V 1V7, Canada
| | - Donna L Senger
- University of Calgary , Faculty of Medicine, Department of Oncology, 2500 University Drive, Calgary T2N 1N4, Canada
| | - Jeff F Dunn
- University of Calgary , Faculty of Medicine, Hotchkiss Brain Institute, 3330 Hospital Drive, Calgary T2N 4N1, Canada ; University of Calgary , Faculty of Medicine, Department of Radiology, 2500 University Drive, Calgary T2N 1N4, Canada
| | - Jeffery T Joseph
- Foothills Medical Centre , Department of Pathology, 1403 29 Street, Calgary T2N 2T9, Canada
| | - Joseph Ross Mitchell
- Mayo Clinic College of Medicine , Department of Radiology, 200 1st Street, Rochester, Minnesota 55905, United States
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Billiet T, Vandenbulcke M, Mädler B, Peeters R, Dhollander T, Zhang H, Deprez S, Van den Bergh BR, Sunaert S, Emsell L. Age-related microstructural differences quantified using myelin water imaging and advanced diffusion MRI. Neurobiol Aging 2015; 36:2107-21. [PMID: 25840837 DOI: 10.1016/j.neurobiolaging.2015.02.029] [Citation(s) in RCA: 148] [Impact Index Per Article: 16.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2014] [Revised: 02/26/2015] [Accepted: 02/28/2015] [Indexed: 10/23/2022]
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Characterizing the microstructural basis of "unidentified bright objects" in neurofibromatosis type 1: A combined in vivo multicomponent T2 relaxation and multi-shell diffusion MRI analysis. NEUROIMAGE-CLINICAL 2014; 4:649-58. [PMID: 24936416 PMCID: PMC4053637 DOI: 10.1016/j.nicl.2014.04.005] [Citation(s) in RCA: 77] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/30/2014] [Revised: 03/14/2014] [Accepted: 04/08/2014] [Indexed: 01/23/2023]
Abstract
Introduction The histopathological basis of “unidentified bright objects” (UBOs) (hyperintense regions seen on T2-weighted magnetic resonance (MR) brain scans in neurofibromatosis-1 (NF1)) remains unclear. New in vivo MRI-based techniques (multi-exponential T2 relaxation (MET2) and diffusion MR imaging (dMRI)) provide measures relating to microstructural change. We combined these methods and present previously unreported data on in vivo UBO microstructure in NF1. Methods 3-Tesla dMRI data were acquired on 17 NF1 patients, covering 30 white matter UBOs. Diffusion tensor, kurtosis and neurite orientation and dispersion density imaging parameters were calculated within UBO sites and in contralateral normal appearing white matter (cNAWM). Analysis of MET2 parameters was performed on 24 UBO–cNAWM pairs. Results No significant alterations in the myelin water fraction and intra- and extracellular (IE) water fraction were found. Mean T2 time of IE water was significantly higher in UBOs. UBOs furthermore showed increased axial, radial and mean diffusivity, and decreased fractional anisotropy, mean kurtosis and neurite density index compared to cNAWM. Neurite orientation dispersion and isotropic fluid fraction were unaltered. Conclusion Our results suggest that demyelination and axonal degeneration are unlikely to be present in UBOs, which appear to be mainly caused by a shift towards a higher T2-value of the intra- and extracellular water pool. This may arise from altered microstructural compartmentalization, and an increase in ‘extracellular-like’, intracellular water, possibly due to intramyelinic edema. These findings confirm the added value of combining dMRI and MET2 to characterize the microstructural basis of T2 hyperintensities in vivo. We examine MRI white matter T2-weighted hyperintense lesions, “UBOs” in NF1. Myelin water and intra- and extracellular water fractions are unchanged in UBOs. Diffusivity is higher, while mean kurtosis and neurite density are lower in UBOs. The combined measures suggest that UBOs may arise from intramyelinic edema. Combining diffusion MRI and multi-exponential T2 relaxation has added value.
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Zhang J, Kolind SH, Laule C, MacKay AL. Comparison of myelin water fraction from multiecho T2decay curve and steady-state methods. Magn Reson Med 2014; 73:223-32. [DOI: 10.1002/mrm.25125] [Citation(s) in RCA: 66] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2013] [Revised: 11/29/2013] [Accepted: 12/18/2013] [Indexed: 12/24/2022]
Affiliation(s)
- Jing Zhang
- UBC MRI Research Centre, Department of Radiology; University of British Columbia; Vancouver BC Canada
| | - Shannon H. Kolind
- Division of Neurology, Department of Medicine; University of British Columbia; Vancouver BC Canada
| | - Cornelia Laule
- UBC MRI Research Centre, Department of Radiology; University of British Columbia; Vancouver BC Canada
- Department of Pathology & Laboratory Medicine; University of British Columbia; Vancouver BC Canada
| | - Alex L. MacKay
- UBC MRI Research Centre, Department of Radiology; University of British Columbia; Vancouver BC Canada
- Department of Physics and Astronomy; University of British Columbia; Vancouver BC Canada
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Matthews PM, Comley R. Advances in the molecular imaging of multiple sclerosis. Expert Rev Clin Immunol 2014; 5:765-77. [DOI: 10.1586/eci.09.66] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
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40
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Thiessen JD, Zhang Y, Zhang H, Wang L, Buist R, Del Bigio MR, Kong J, Li XM, Martin M. Quantitative MRI and ultrastructural examination of the cuprizone mouse model of demyelination. NMR IN BIOMEDICINE 2013; 26:1562-1581. [PMID: 23943390 DOI: 10.1002/nbm.2992] [Citation(s) in RCA: 113] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2012] [Revised: 05/23/2013] [Accepted: 05/24/2013] [Indexed: 06/02/2023]
Abstract
The cuprizone mouse model of demyelination was used to investigate the influence that white matter changes have on different magnetic resonance imaging results. In vivo T2 -weighted and magnetization transfer images (MTIs) were acquired weekly in control (n = 5) and cuprizone-fed (n = 5) mice, with significant increases in signal intensity in T2 -weighted images (p < 0.001) and lower magnetization transfer ratio (p < 0.001) in the corpus callosum of the cuprizone-fed mice starting at 3 weeks and peaking at 4 and 5 weeks, respectively. Diffusion tensor imaging (DTI), quantitative MTI (qMTI), and T1/T2 measurements were used to analyze freshly excised tissue after 6 weeks of cuprizone administration. In multicomponent T2 analysis with 10 ms echo spacing, there was no visible myelin water component associated with the short T2 value. Quantitative MTI metrics showed significant differences in the corpus callosum and external capsule of the cuprizone-fed mice, similar to previous studies of multiple sclerosis in humans and animal models of demyelination. Fractional anisotropy was significantly lower and mean, axial, and radial diffusivity were significantly higher in the cuprizone-fed mice. Cellular distributions measured in electron micrographs of the corpus callosum correlated strongly to several different quantitative MRI metrics. The largest Spearman correlation coefficient varied depending on cellular type: T1 versus the myelinated axon fraction (ρ = -0.90), the bound pool fraction (ƒ) versus the myelin sheath fraction (ρ = 0.93), and axial diffusivity versus the non-myelinated cell fraction (ρ = 0.92). Using Pearson's correlation coefficient, ƒ was strongly correlated to the myelin sheath fraction (r = 0.98) with a linear equation predicting myelin content (5.37ƒ - 0.25). Of the calculated MRI metrics, ƒ was the strongest indicator of myelin content, while longitudinal relaxation rates and diffusivity measurements were the strongest indicators of changes in tissue structure.
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Affiliation(s)
- Jonathan D Thiessen
- Department of Physics and Astronomy, University of Manitoba, Winnipeg, MB, Canada; Department of Radiology, University of Manitoba, Winnipeg, MB, Canada
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Guo J, Ji Q, Reddick WE. Multi-slice myelin water imaging for practical clinical applications at 3.0 T. Magn Reson Med 2013; 70:813-22. [PMID: 23132434 PMCID: PMC3568216 DOI: 10.1002/mrm.24527] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2012] [Revised: 09/18/2012] [Accepted: 09/21/2012] [Indexed: 12/19/2022]
Abstract
Myelin water imaging is a promising, noninvasive technique for evaluating white matter diseases such as multiple sclerosis and other leukoencephalopathies (LE), and monitoring myelination in early childhood. Unfortunately, poor image quality and a long acquisition time are major obstacles to practical clinical applications. In this study, a novel postprocessing method with an efficient multi-slice acquisition scheme, called T2 spectrum analysis using a weighted regularized non-negative least squares algorithm and nonlocal mean filter (T2SPARC), is presented to overcome these obstacles and achieve a shorter acquisition time, higher image quality, and large volume coverage. In vivo results from healthy volunteers and a patient with LE showed that the T2SPARC method can generate robust and high-quality myelin water fraction maps of 10 slices within 11 min. This method also yields some useful byproducts such as intra- and extracellular water fraction and long T2 tissue water fraction maps, which can quantify lesions in different brain diseases.
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Affiliation(s)
- Junyu Guo
- Department of Radiological Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
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Smith SA, Pekar JJ, van Zijl PCM. Advanced MRI strategies for assessing spinal cord injury. HANDBOOK OF CLINICAL NEUROLOGY 2013. [PMID: 23098708 DOI: 10.1016/b978-0-444-52137-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Advanced magnetic resonance (MR) approaches permit the noninvasive quantification of macromolecular, functional, and physiological properties of biological tissues. In this chapter, we review the application of advanced MR techniques to the spinal cord. Macromolecular properties of the spinal cord can be studied using magnetization transfer (MT) MR, diffusion tensor imaging (DTI), Q-space diffusion spectroscopy, and selective detection of myelin water. The functional and metabolic status of the spinal cord can be studied using functional MRI (fMRI), perfusion imaging, and magnetic resonance spectroscopy (MRS). Finally, we consider the outlook for advanced MR studies in persons in whom metal hardware has been implanted to stabilize the cord. In spite of the spinal cord's diminutive size, its location deep within the body, and constant motion, recent work shows that the spinal cord can be studied using these advanced MR approaches.
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Affiliation(s)
- Seth A Smith
- Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA
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Harkins KD, Valentine WM, Gochberg DF, Does MD. In-vivo multi-exponential T2, magnetization transfer and quantitative histology in a rat model of intramyelinic edema. NEUROIMAGE-CLINICAL 2013; 2:810-7. [PMID: 24179832 PMCID: PMC3777678 DOI: 10.1016/j.nicl.2013.06.007] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/13/2013] [Revised: 06/10/2013] [Accepted: 06/12/2013] [Indexed: 11/26/2022]
Abstract
Two MRI methods, multi-exponential analysis of transverse relaxation (MET2) and quantitative magnetization transfer (qMT), were used along with quantitative evaluation of histology in a study of intra-myelinic edema in rat spinal white matter. The results showed a strong linear correlation between a distinct long-T2 signal from MET2 analysis and the edema water volume fraction as measured by histology, although this analysis overestimated the edema water content by ≈ 100% relative to quantitative histological measurements. This overestimation was reasoned to result from the effects of inter-compartmental water exchange on observed transverse relaxation. Commonly studied MRI markers for myelin, the myelin water fraction (from MET2 analysis) and the macromolecular pool size ratio (from qMT analysis) produced results that could not be explained purely by changes in myelin content. The results demonstrate the potential for MET2 analysis as well as the limits of putative myelin markers for characterizing white matter abnormalities involving intra-myelinic edema. We studied a rat model of intra-myelinic edema induced by hexachlorophene ingestion. We used multi-exponential T2 (MET2) and quantitative magnetization transfer MRI. Histology was quantitatively evaluated to measure edema volume and myelin content. MET2 provides a measure that correlates but overestimates with edema volume fraction. MET2 measure of edema is affected by microscopic water dynamics.
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Bjarnason TA, Laule C, Bluman J, Kozlowski P. Temporal phase correction of multiple echo T2 magnetic resonance images. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2013; 231:22-31. [PMID: 23563572 PMCID: PMC5478376 DOI: 10.1016/j.jmr.2013.02.019] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2012] [Revised: 02/14/2013] [Accepted: 02/18/2013] [Indexed: 05/24/2023]
Abstract
Typically, magnetic resonance imaging (MRI) analysis is performed on magnitude data, and multiple echo T2 data consist of numerous images of the same slice taken with different echo spacing, giving voxel-wise temporal sampling of the noise as the signals decay according to T2 relaxation. Magnitude T2 decay data has Rician distributed noise which is characterized by a change in the noise distribution from Gaussian, through a transitional region, to Rayleigh as the signal to noise ratio decreases with increasing echo time. Non-Gaussian noise distributions may produce errors in the commonly applied non-negative least squares (NNLS) algorithm that is used to assess multiple echo decays for compartmentalized water environments through the creation of T2 distributions. Typically, Gaussian noise is sought by performing spatial-based phase correction on the MRI data however, these methods cannot capitalize on the temporal information available from multiple echo T2 acquisitions. Here we describe a temporal phase correction (TPC) algorithm that utilizes the temporal noise information available in multiple echo T2 acquisitions to put the relevant decay information in the Real portion of the decay data and leave only noise in the Imaginary portion. We apply this TPC algorithm to create real-valued multiple echo T2 data from human subjects measured at 1.5 T. We show that applying TPC causes changes in the T2 distribution estimates; notably the possible resolution of separate extracellular and intracellular water environments, and the disappearance of the commonly labeled cerebrospinal fluid peak, which might be an artefact observed in many previously published multiple echo T2 analyses.
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Kolind S, Sharma R, Knight S, Johansen-Berg H, Talbot K, Turner MR. Myelin imaging in amyotrophic and primary lateral sclerosis. Amyotroph Lateral Scler Frontotemporal Degener 2013; 14:562-73. [PMID: 23678852 PMCID: PMC3837681 DOI: 10.3109/21678421.2013.794843] [Citation(s) in RCA: 54] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Primary lateral sclerosis (PLS) has been regarded as a rare, extreme form of amyotrophic lateral sclerosis (ALS). Like ALS, it is a clinical diagnosis without established biomarkers. We sought to explore loss of cerebral myelin in relation to clinical features, including cognitive impairment, in cases of both ALS and PLS. A novel MRI sequence (mcDESPOT) sensitive to water pools within myelin and intra- and extra-cellular spaces was applied to 23 ALS patients, seven PLS patients and 12 healthy controls, with interval follow-up in 15 ALS and four PLS patients. Results demonstrated that PLS patients were distinguished by widespread cerebral myelin water fraction reductions, independent of disease duration and clinical upper motor neuron burden. ALS patients showed a significant increase in intra- and extra-cellular water, indirectly linked to neuroinflammatory activity. Limited measures of cognitive impairment in the ALS group were associated with myelin changes within the anterior corpus callosum and frontal lobe projections. Longitudinal changes were only significant in the PLS group. In conclusion, in this exploratory study, myelin imaging has potential to distinguish PLS from ALS, and may have value as a marker of extramotor involvement. PLS may be a more active cerebral pathological process than its rate of clinical deterioration suggests.
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Affiliation(s)
- Shannon Kolind
- Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), University of Oxford
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What causes the hyperintense T2-weighting and increased short T2 signal in the corticospinal tract? Magn Reson Imaging 2013; 31:329-35. [DOI: 10.1016/j.mri.2012.07.003] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2012] [Revised: 06/30/2012] [Accepted: 07/08/2012] [Indexed: 11/23/2022]
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47
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Tonkova V, Arhelger V, Schenk J, Neeb H. Rapid myelin water content mapping on clinical MR systems. Z Med Phys 2012; 22:133-42. [DOI: 10.1016/j.zemedi.2011.09.005] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2011] [Revised: 09/18/2011] [Accepted: 09/19/2011] [Indexed: 10/15/2022]
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Smith SA, Pekar JJ, van Zijl PCM. Advanced MRI strategies for assessing spinal cord injury. HANDBOOK OF CLINICAL NEUROLOGY 2012; 109:85-101. [PMID: 23098708 DOI: 10.1016/b978-0-444-52137-8.00006-1] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Advanced magnetic resonance (MR) approaches permit the noninvasive quantification of macromolecular, functional, and physiological properties of biological tissues. In this chapter, we review the application of advanced MR techniques to the spinal cord. Macromolecular properties of the spinal cord can be studied using magnetization transfer (MT) MR, diffusion tensor imaging (DTI), Q-space diffusion spectroscopy, and selective detection of myelin water. The functional and metabolic status of the spinal cord can be studied using functional MRI (fMRI), perfusion imaging, and magnetic resonance spectroscopy (MRS). Finally, we consider the outlook for advanced MR studies in persons in whom metal hardware has been implanted to stabilize the cord. In spite of the spinal cord's diminutive size, its location deep within the body, and constant motion, recent work shows that the spinal cord can be studied using these advanced MR approaches.
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Affiliation(s)
- Seth A Smith
- Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA
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Reddick WE, Conklin HM. Impact of acute lymphoblastic leukemia therapy on attention and working memory in children. Expert Rev Hematol 2011; 3:655-9. [PMID: 21091140 DOI: 10.1586/ehm.10.65] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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50
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Shah NJ, Ermer V, Oros-Peusquens AM. Measuring the absolute water content of the brain using quantitative MRI. Methods Mol Biol 2011; 711:29-64. [PMID: 21279597 DOI: 10.1007/978-1-61737-992-5_3] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
Abstract
Methods for quantitative imaging of the brain are presented and compared. Highly precise and accurate mapping of the absolute water content and distribution, as presented here, requires a significant number of corrections and also involves mapping of other MR parameters. Here, either T(1) and T(2)(*) or T(2) is mapped, and several corrections involving the measurement of temperature, transmit and receive B(1) inhomogeneities and signal extrapolation to zero TE are applied. Information about the water content of the whole brain can be acquired in clinically acceptable measurement times (10 or 20 min). Since water content is highly regulated in the healthy brain, pathological changes can be easily identified and their evolution or correlation with other manifestations of the disease investigated. In addition to voxel-based total water content, information about the different environments of water can be gleaned from qMRI. The myelin water fraction can be extracted from the fit of very high-SNR multiple-echo T(2) decay curves with a superposition of a large number of exponentials. Diseases involving de- or dysmyelination can be investigated and lead to novel observations regarding the water compartmentalisation in tissue, despite the limited spatial coverage. In conclusion, quantitative MRI is emerging as an unparalleled tool for the study of the normal and diseased brain, replacing the customary time-space environment of the sequential mixed-contrast MRI with a multi-NMR-parametric space in which tissue microscopy is increasingly revealed.
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Affiliation(s)
- Nadim Joni Shah
- Institute of Neuroscience and Medicine (INM-4), Research Centre Juelich, Juelich, Germany.
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