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Faulkner ME, Gong Z, Guo A, Laporte JP, Bae J, Bouhrara M. Harnessing myelin water fraction as an imaging biomarker of human cerebral aging, neurodegenerative diseases, and risk factors influencing myelination: A review. J Neurochem 2024. [PMID: 38973579 DOI: 10.1111/jnc.16170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2024] [Revised: 06/12/2024] [Accepted: 06/19/2024] [Indexed: 07/09/2024]
Abstract
Myelin water fraction (MWF) imaging has emerged as a promising magnetic resonance imaging (MRI) biomarker for investigating brain function and composition. This comprehensive review synthesizes the current state of knowledge on MWF as a biomarker of human cerebral aging, neurodegenerative diseases, and risk factors influencing myelination. The databases used include Web of Science, Scopus, Science Direct, and PubMed. We begin with a brief discussion of the theoretical foundations of MWF imaging, including its basis in MR physics and the mathematical modeling underlying its calculation, with an overview of the most adopted MRI methods of MWF imaging. Next, we delve into the clinical and research applications that have been explored to date, highlighting its advantages and limitations. Finally, we explore the potential of MWF to serve as a predictive biomarker for neurological disorders and identify future research directions for optimizing MWF imaging protocols and interpreting MWF in various contexts. By harnessing the power of MWF imaging, we may gain new insights into brain health and disease across the human lifespan, ultimately informing novel diagnostic and therapeutic strategies.
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Affiliation(s)
- Mary E Faulkner
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - Zhaoyuan Gong
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - Alex Guo
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - John P Laporte
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - Jonghyun Bae
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - Mustapha Bouhrara
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
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Kawaguchi S, Kan H, Uchida Y, Kasai H, Hiwatashi A, Ueki Y. Anisotropy of the R1/T2* value dependent on white matter fiber orientation with respect to the B0 field. Magn Reson Imaging 2024; 109:83-90. [PMID: 38387713 DOI: 10.1016/j.mri.2024.02.010] [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: 12/26/2023] [Revised: 02/19/2024] [Accepted: 02/19/2024] [Indexed: 02/24/2024]
Abstract
The R1 (1/T1) map divided by the T2* map (R1/T2* map) draws attention as a high-resolution myelin-related map. However, both R1 and R2* (1/T2*) values demonstrate anisotropy dependent on the white matter (WM) fiber orientation with respect to the static magnetic (B0) field. Therefore, this study primarily aimed to investigate the comprehensive impact of these angular-dependent anisotropies on the R1/T2* value. This study enrolled 10 healthy human volunteers (age = 25 ± 1.3) on the 3.0 T MRI system. For R1/T2* map calculation, whole brain R1 and T2* maps were repeatedly obtained in three head tilt positions by magnetization-prepared two rapid gradient echoes and multiple spoiled gradient echo sequences, respectively. Afterward, all maps were spatially normalized and registered to the Johns Hopkins University WM atlas. R1/T2*, R1, and R2* values were binned for fiber orientation related to the B0 field, which was estimated from diffusion-weighted echo-planar imaging data with 3° intervals, to investigate angular-dependent anisotropies in vivo. A larger change in the R1/T2* value in the global WM region as a function of fiber orientation with respect to the B0 field was observed compared to the R1 and R2* values alone. The minimum R1/T2* value at the near magic-angle range was 18.86% lower than the maximum value at the perpendicular angle range. Furthermore, R1/T2* values in the corpus callosum tract and the right and left cingulum cingulate gyrus tracts changed among the three head tilt positions due to fiber orientation changes. In conclusion, the R1/T2* value demonstrates distinctive and complicated angular-dependent anisotropy indicating the trends of both R1 and R2* values and may provide supplemental information for detecting slight changes in the microstructure of myelin and axons.
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Affiliation(s)
| | - Hirohito Kan
- Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Japan; Department of Radiology, Nagoya City University Graduate School of Medical Sciences, Japan.
| | - Yuto Uchida
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Neurology, Nagoya City University Graduate School of Medical Sciences, Japan
| | - Harumasa Kasai
- Department of Radiology, Nagoya City University Hospital, Japan
| | - Akio Hiwatashi
- Department of Radiology, Nagoya City University Graduate School of Medical Sciences, Japan
| | - Yoshino Ueki
- Department of Rehabilitation Medicine, Nagoya City University Graduate School of Medical Sciences, Japan
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Chen L, Shin HG, van Zijl PC, Li X. Exploiting gradient-echo frequency evolution: Probing white matter microstructure and extracting bulk susceptibility-induced frequency for quantitative susceptibility mapping. Magn Reson Med 2024; 91:1676-1693. [PMID: 38102838 PMCID: PMC10880384 DOI: 10.1002/mrm.29958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2023] [Revised: 10/08/2023] [Accepted: 11/17/2023] [Indexed: 12/17/2023]
Abstract
PURPOSE This work is to investigate the microstructure-induced frequency shift in white matter (WM) with crossing fibers and to separate the microstructure-related frequency shift from the bulk susceptibility-induced frequency shift by model fitting the gradient-echo (GRE) frequency evolution for potentially more accurate quantitative susceptibility mapping (QSM). METHODS A hollow-cylinder fiber model (HCFM) with two fiber populations was developed to investigate GRE frequency evolutions in WM voxels with microstructural orientation dispersion. The simulated and experimentally measured TE-dependent local frequency shift was then fitted to a simplified frequency evolution model to obtain a microstructure-related frequency difference parameter (∆ f $$ \Delta f $$ ) and a TE-independent bulk susceptibility-induced frequency shift (C f $$ {C}_f $$ ). The obtainedC f $$ {C}_f $$ was then used for QSM reconstruction. Reconstruction performances were evaluated using a numerical head phantom and in vivo data and then compared to other multi-echo combination methods. RESULTS GRE frequency evolutions and∆ f $$ \Delta f $$ -based tissue parameters in both parallel and crossing fibers determined from our simulations were comparable to those observed in vivo. The TE-dependent frequency fitting method outperformed other multi-echo combination methods in estimatingC f $$ {C}_f $$ in simulations. The fitted∆ f $$ \Delta f $$ ,C f $$ {C}_f $$ , and QSM could be improved further by navigator-based B0 fluctuation correction. CONCLUSION A HCFM with two fiber populations can be used to characterize microstructure-induced frequency shifts in WM regions with crossing fibers. HCFM-based TE-dependent frequency fitting provides tissue contrast related to microstructure (∆ f $$ \Delta f $$ ) and in addition may help improve the quantification accuracy ofC f $$ {C}_f $$ and the corresponding QSM.
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Affiliation(s)
- Lin Chen
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, United States
- Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, Maryland, United States
| | - Hyeong-Geol Shin
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, United States
- Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, Maryland, United States
| | - Peter C.M. van Zijl
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, United States
- Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, Maryland, United States
| | - Xu Li
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, United States
- Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, Maryland, United States
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Schäper J, Bieri O. Myelin water imaging at 0.55 T using a multigradient-echo sequence. Magn Reson Med 2024; 91:1043-1056. [PMID: 38010053 DOI: 10.1002/mrm.29949] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 10/19/2023] [Accepted: 11/12/2023] [Indexed: 11/29/2023]
Abstract
PURPOSE To investigate the prospects of a multigradient-echo (mGRE) acquisition for in vivo myelin water imaging at 0.55 T. METHODS Scans were performed on the brain of four healthy volunteers at 0.55 and 3 T, using a 3D mGRE sequence. The myelin water fraction (MWF) was calculated for both field strengths using a nonnegative least squares (NNLS) algorithm, implemented in the qMRLab suite. The quality of these maps as well as single-voxel fits were compared visually for 0.55 and 3 T. RESULTS The obtained MWF values at 0.55 T are consistent with previously reported ones at higher field strengths. The MWF maps are a considerable improvement over the ones at 3 T. Example fits show that 0.55 T data is better described by an exponential model than 3 T data, making the assumed multi-exponential model of the NNLS algorithm more accurate. CONCLUSION This first assessment shows that mGRE myelin water imaging at 0.55 T is feasible and has the potential to yield better results than at higher fields.
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Affiliation(s)
- Jessica Schäper
- Department of Biomedical Engineering, University of Basel, Basel, Switzerland
- Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
| | - Oliver Bieri
- Department of Biomedical Engineering, University of Basel, Basel, Switzerland
- Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
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Shaterian Mohammadi H, Moazamian D, Athertya JS, Shin SH, Lo J, Suprana A, Malhi BS, Ma Y. Quantitative myelin water imaging using short TR adiabatic inversion recovery prepared echo-planar imaging (STAIR-EPI) sequence. FRONTIERS IN RADIOLOGY 2023; 3:1263491. [PMID: 37840897 PMCID: PMC10568074 DOI: 10.3389/fradi.2023.1263491] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Accepted: 09/18/2023] [Indexed: 10/17/2023]
Abstract
Introduction Numerous techniques for myelin water imaging (MWI) have been devised to specifically assess alterations in myelin. The biomarker employed to measure changes in myelin content is known as the myelin water fraction (MWF). The short TR adiabatic inversion recovery (STAIR) sequence has recently been identified as a highly effective method for calculating MWF. The purpose of this study is to develop a new clinical transitional myelin water imaging (MWI) technique that combines STAIR preparation and echo-planar imaging (EPI) (STAIR-EPI) sequence for data acquisition. Methods Myelin water (MW) in the brain has shorter T1 and T2 relaxation times than intracellular and extracellular water. In the proposed STAIR-EPI sequence, a short TR (e.g., ≤300 ms) together with an optimized inversion time enable robust long T1 water suppression with a wide range of T1 values [i.e., (600, 2,000) ms]. The EPI allows fast data acquisition of the remaining MW signals. Seven healthy volunteers and seven patients with multiple sclerosis (MS) were recruited and scanned in this study. The apparent myelin water fraction (aMWF), defined as the signal ratio of MW to total water, was measured in the lesions and normal-appearing white matter (NAWM) in MS patients and compared with those measured in the normal white matter (NWM) in healthy volunteers. Results As seen in the STAIR-EPI images acquired from MS patients, the MS lesions show lower signal intensities than NAWM do. The aMWF measurements for both MS lesions (3.6 ± 1.3%) and NAWM (8.6 ± 1.2%) in MS patients are significantly lower than NWM (10 ± 1.3%) in healthy volunteers (P < 0.001). Discussion The proposed STAIR-EPI technique, which can be implemented in MRI scanners from all vendors, is able to detect myelin loss in both MS lesions and NAWM in MS patients.
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Affiliation(s)
| | | | | | | | | | | | | | - Yajun Ma
- Department of Radiology, University of California San Diego, San Diego, CA, United States
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Ma YJ, Jang H, Lombardi AF, Corey-Bloom J, Bydder GM. Myelin water imaging using a short-TR adiabatic inversion-recovery (STAIR) sequence. Magn Reson Med 2022; 88:1156-1169. [PMID: 35613378 PMCID: PMC9867567 DOI: 10.1002/mrm.29287] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 03/21/2022] [Accepted: 04/13/2022] [Indexed: 01/26/2023]
Abstract
PURPOSE To develop a new myelin water imaging (MWI) technique using a short-TR adiabatic inversion-recovery (STAIR) sequence on a clinical 3T MR scanner. METHODS Myelin water (MW) in the brain has both a much shorter T1 and a much shorter T2 * than intracellular/extracellular water. A STAIR sequence with a short TR was designed to efficiently suppress long T1 signals from intracellular/extracellular water, and therefore allow selective imaging of MW, which has a much shorter T1 . Numerical simulation and phantom studies were performed to investigate the effectiveness of long T1 signal suppression. TheT2 * in white matter (WM) was measured with STAIR and compared with T2 * measured with a conventional gradient recall echo in in vivo study. Four healthy volunteers and 4 patients with multiple sclerosis were recruited for qualitative and quantitative MWI. Apparent MW fraction was generated to compare MW in normal WM in volunteers to MW in lesions in patients with multiple sclerosis. RESULTS Both simulation and phantom studies showed that when TR was sufficiently short (eg, 250 ms), the STAIR sequence effectively suppressed long T1 signals from tissues with a broad range of T1 s using a single TR/TI combination. The volunteer study showed a short T2 * of 9.5 ± 1.7 ms in WM, which is similar to reported values for MW. Lesions in patients with multiple sclerosis showed a significantly lower apparent MW fraction (4.5% ± 1.0%) compared with that of normal WM (9.2% ± 1.5%) in healthy volunteers (p < 0.05). CONCLUSIONS The STAIR sequence provides selective MWI in brain and can quantify reductions in MW content in patients with multiple sclerosis.
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Affiliation(s)
- Ya-Jun Ma
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Hyungseok Jang
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Alecio F. Lombardi
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Jody Corey-Bloom
- Department of Neurosciences, University of California San Diego, San Diego, CA, USA
| | - Graeme M. Bydder
- Department of Radiology, University of California San Diego, San Diego, CA, USA
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Lee JH, Yi J, Kim JH, Ryu K, Han D, Kim S, Lee S, Kim DY, Kim DH. Accelerated 3D myelin water imaging using joint spatio-temporal reconstruction. Med Phys 2022; 49:5929-5942. [PMID: 35678751 DOI: 10.1002/mp.15788] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Revised: 03/31/2022] [Accepted: 05/26/2022] [Indexed: 11/08/2022] Open
Abstract
PURPOSE To enable acceleration in 3D multi-echo gradient echo (mGRE) acquisition for myelin water imaging (MWI) by combining joint parallel imaging (JPI) and joint deep learning (JDL). METHODS We implemented a multistep reconstruction process using both advanced parallel imaging and deep learning network which can utilize joint spatiotemporal components between the multi-echo images to further accelerate 3D mGRE acquisition for MWI. In the first step, JPI was performed to estimate missing k-space lines. Next, JDL was implemented to reduce residual artifacts and produce high-fidelity reconstruction by using variable splitting optimization consisting of spatiotemporal denoiser block, data consistency block, and weighted average block. The proposed method was evaluated for MWI with 2D Cartesian uniform under-sampling for each echo, enabling scan times of up to approximately 2 min for 2 mm × 2 mm × 2 mm $2\ {\rm mm} \times 2\ {\rm mm} \times 2\ {\rm mm}$ 3D coverage. RESULTS The proposed method showed acceptable MWI quality with improved quantitative values compared to both JPI and JDL methods individually. The improved performance of the proposed method was demonstrated by the low normalized mean-square error and high-frequency error norm values of the reconstruction with high similarity to the fully sampled MWI. CONCLUSION Joint spatiotemporal reconstruction approach by combining JPI and JDL can achieve high acceleration factors for 3D mGRE-based MWI.
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Affiliation(s)
- Jae-Hun Lee
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Jaeuk Yi
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Jun-Hyeong Kim
- 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.,Department of Radiology, Stanford University, Stanford, California, USA
| | - Dongyeob Han
- Siemens Healthineers Ltd, Seoul, Republic of Korea
| | - Sewook Kim
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Seul Lee
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea
| | - Deog Young Kim
- Department of Research Institute of Rehabilitation Medicine, Yonsei University College 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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Kiely M, Triebswetter C, Cortina LE, Gong Z, Alsameen MH, Spencer RG, Bouhrara M. Insights into human cerebral white matter maturation and degeneration across the adult lifespan. Neuroimage 2022; 247:118727. [PMID: 34813969 PMCID: PMC8792239 DOI: 10.1016/j.neuroimage.2021.118727] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Revised: 10/15/2021] [Accepted: 11/12/2021] [Indexed: 01/01/2023] Open
Abstract
White matter (WM) microstructural properties change across the adult lifespan and with neuronal diseases. Understanding microstructural changes due to aging is paramount to distinguish them from neuropathological changes. Conducted on a large cohort of 147 cognitively unimpaired subjects, spanning a wide age range of 21 to 94 years, our study evaluated sex- and age-related differences in WM microstructure. Specifically, we used diffusion tensor imaging (DTI) magnetic resonance imaging (MRI) indices, sensitive measures of myelin and axonal density in WM, and myelin water fraction (MWF), a measure of the fraction of the signal of water trapped within the myelin sheets, to probe these differences. Furthermore, we examined regional correlations between MWF and DTI indices to evaluate whether the DTI metrics provide information complementary to MWF. While sexual dimorphism was, overall, nonsignificant, we observed region-dependent differences in MWF, that is, myelin content, and axonal density with age and found that both exhibit nonlinear, but distinct, associations with age. Furthermore, DTI indices were moderately correlated with MWF, indicating their good sensitivity to myelin content as well as to other constituents of WM tissue such as axonal density. The microstructural differences captured by our MRI metrics, along with their weak to moderate associations with MWF, strongly indicate the potential value of combining these outcome measures in a multiparametric approach. Furthermore, our results support the last-in-first-out and the gain-predicts-loss hypotheses of WM maturation and degeneration. Indeed, our results indicate that the posterior WM regions are spared from neurodegeneration as compared to anterior regions, while WM myelination follows a temporally symmetric time course across the adult life span.
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Affiliation(s)
- Matthew Kiely
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224 MD, USA
| | - Curtis Triebswetter
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224 MD, USA
| | - Luis E Cortina
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224 MD, USA
| | - Zhaoyuan Gong
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224 MD, USA
| | - Maryam H Alsameen
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224 MD, USA
| | - Richard G Spencer
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224 MD, USA
| | - Mustapha Bouhrara
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224 MD, USA.
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Lim SH, Lee J, Jung S, Kim B, Rhee HY, Oh SH, Park S, Cho AR, Ryu CW, Jahng GH. Myelin-Weighted Imaging Presents Reduced Apparent Myelin Water in Patients with Alzheimer’s Disease. Diagnostics (Basel) 2022; 12:diagnostics12020446. [PMID: 35204537 PMCID: PMC8871299 DOI: 10.3390/diagnostics12020446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 01/27/2022] [Accepted: 02/06/2022] [Indexed: 02/04/2023] Open
Abstract
The purpose of this study was to investigate myelin loss in both AD and mild cognitive impairment (MCI) patients with a new myelin water mapping technique within reasonable scan time and evaluate the clinical relevance of the apparent myelin water fraction (MWF) values by assessing the relationship between decreases in myelin water and the degree of memory decline or aging. Twenty-nine individuals were assigned to the cognitively normal (CN) elderly group, 32 participants were assigned to the MCI group, and 31 patients were assigned to the AD group. A 3D visualization of the short transverse relaxation time component (ViSTa)-gradient and spin-echo (GraSE) sequence was developed to map apparent MWF. Then, the MWF values were compared between the three participant groups and was evaluated the relationship with the degree of memory loss. The AD group showed a reduced apparent MWF compared to the CN and MCI groups. The largest AUC (area under the curve) value was in the corpus callosum and used to classify the CN and AD groups using the apparent MWF. The ViSTa-GraSE sequence can be a useful tool to map the MWF in a reasonable scan time. Combining the MWF in the corpus callosum with the detection of atrophy in the hippocampus can be valuable for group classification.
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Affiliation(s)
- Seung-Hyun Lim
- Department of Radiology, Kyung Hee University Hospital at Gangdong, 892 Dongnam-ro, Gangdong-gu, Seoul 05278, Korea; (S.-H.L.); (B.K.); (C.-W.R.)
| | - Jiyoon Lee
- Department of Biomedical Engineering, Undergraduate School, College of Electronics and Information, Kyung Hee University, 1732 Deogyeong-daero, Giheung-gu, Yongin-si 17104, Korea; (J.L.); (S.J.)
| | - Sumin Jung
- Department of Biomedical Engineering, Undergraduate School, College of Electronics and Information, Kyung Hee University, 1732 Deogyeong-daero, Giheung-gu, Yongin-si 17104, Korea; (J.L.); (S.J.)
| | - Bokyung Kim
- Department of Radiology, Kyung Hee University Hospital at Gangdong, 892 Dongnam-ro, Gangdong-gu, Seoul 05278, Korea; (S.-H.L.); (B.K.); (C.-W.R.)
| | - Hak Young Rhee
- Department of Neurology, Kyung Hee University Hospital at Gangdong, 892 Dongnam-ro, Gangdong-gu, Seoul 05278, Korea;
- Department of Medicine, College of Medicine, Kyung Hee University, 26 Kyung Hee Dae-ro, Dongdaemun-gu, Seoul 02447, Korea; (S.P.); (A.R.C.)
| | - Se-Hong Oh
- Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin 17035, Korea;
| | - Soonchan Park
- Department of Medicine, College of Medicine, Kyung Hee University, 26 Kyung Hee Dae-ro, Dongdaemun-gu, Seoul 02447, Korea; (S.P.); (A.R.C.)
| | - Ah Rang Cho
- Department of Medicine, College of Medicine, Kyung Hee University, 26 Kyung Hee Dae-ro, Dongdaemun-gu, Seoul 02447, Korea; (S.P.); (A.R.C.)
- Department of Psychiatry, Kyung Hee University Hospital at Gangdong, 892 Dongnam-ro, Gangdong-gu, Seoul 05278, Korea
| | - Chang-Woo Ryu
- Department of Radiology, Kyung Hee University Hospital at Gangdong, 892 Dongnam-ro, Gangdong-gu, Seoul 05278, Korea; (S.-H.L.); (B.K.); (C.-W.R.)
- Department of Medicine, College of Medicine, Kyung Hee University, 26 Kyung Hee Dae-ro, Dongdaemun-gu, Seoul 02447, Korea; (S.P.); (A.R.C.)
| | - Geon-Ho Jahng
- Department of Radiology, Kyung Hee University Hospital at Gangdong, 892 Dongnam-ro, Gangdong-gu, Seoul 05278, Korea; (S.-H.L.); (B.K.); (C.-W.R.)
- Department of Medicine, College of Medicine, Kyung Hee University, 26 Kyung Hee Dae-ro, Dongdaemun-gu, Seoul 02447, Korea; (S.P.); (A.R.C.)
- Correspondence: ; Tel.: +82-2-440-6187; Fax: +82-2-440-6932
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10
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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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11
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Mohammadi S, Callaghan MF. Towards in vivo g-ratio mapping using MRI: Unifying myelin and diffusion imaging. J Neurosci Methods 2021; 348:108990. [PMID: 33129894 PMCID: PMC7840525 DOI: 10.1016/j.jneumeth.2020.108990] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 09/21/2020] [Accepted: 10/20/2020] [Indexed: 12/19/2022]
Abstract
BACKGROUND The g-ratio, quantifying the comparative thickness of the myelin sheath encasing an axon, is a geometrical invariant that has high functional relevance because of its importance in determining neuronal conduction velocity. Advances in MRI data acquisition and signal modelling have put in vivo mapping of the g-ratio, across the entire white matter, within our reach. This capacity would greatly increase our knowledge of the nervous system: how it functions, and how it is impacted by disease. NEW METHOD This is the second review on the topic of g-ratio mapping using MRI. RESULTS This review summarizes the most recent developments in the field, while also providing methodological background pertinent to aggregate g-ratio weighted mapping, and discussing pitfalls associated with these approaches. COMPARISON WITH EXISTING METHODS Using simulations based on recently published data, this review reveals caveats to the state-of-the-art calibration methods that have been used for in vivo g-ratio mapping. It highlights the need to estimate both the slope and offset of the relationship between these MRI-based markers and the true myelin volume fraction if we are really to achieve the goal of precise, high sensitivity g-ratio mapping in vivo. Other challenges discussed in this review further evidence the need for gold standard measurements of human brain tissue from ex vivo histology. CONCLUSIONS We conclude that the quest to find the most appropriate MRI biomarkers to enable in vivo g-ratio mapping is ongoing, with the full potential of many novel techniques yet to be investigated.
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Affiliation(s)
- Siawoosh Mohammadi
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany; Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| | - Martina F Callaghan
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, UK
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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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Whitaker ST, Nataraj G, Nielsen JF, Fessler JA. Myelin water fraction estimation using small-tip fast recovery MRI. Magn Reson Med 2020; 84:1977-1990. [PMID: 32281179 PMCID: PMC7478173 DOI: 10.1002/mrm.28259] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2019] [Revised: 02/05/2020] [Accepted: 02/26/2020] [Indexed: 11/09/2022]
Abstract
PURPOSE To demonstrate the feasibility of an optimized set of small-tip fast recovery (STFR) MRI scans for rapidly estimating myelin water fraction (MWF) in the brain. METHODS We optimized a set of STFR scans to minimize the Cramér-Rao Lower Bound of MWF estimates. We evaluated the RMSE of MWF estimates from the optimized scans in simulation. We compared STFR-based MWF estimates (both modeling exchange and not modeling exchange) to multi-echo spin echo (MESE)-based estimates. We used the optimized scans to acquire in vivo data from which a MWF map was estimated. We computed the STFR-based MWF estimates using PERK, a recently developed kernel regression technique, and the MESE-based MWF estimates using both regularized non-negative least squares (NNLS) and PERK. RESULTS In simulation, the optimized STFR scans led to estimates of MWF with low RMSE across a range of tissue parameters and across white matter and gray matter. The STFR-based MWF estimates that modeled exchange compared well to MESE-based MWF estimates in simulation. When the optimized scans were tested in vivo, the MWF map that was estimated using a 3-compartment model with exchange was closer to the MESE-based MWF map. CONCLUSIONS The optimized STFR scans appear to be well suited for estimating MWF in simulation and in vivo when we model exchange in training. In this case, the STFR-based MWF estimates are close to the MESE-based estimates.
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Affiliation(s)
- Steven T. Whitaker
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, Michigan, USA
| | - Gopal Nataraj
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Jon-Fredrik Nielsen
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA
| | - Jeffrey A. Fessler
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, Michigan, USA
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14
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Lanzman BA, Huang Y, Lee EH, Iv M, Moseley ME, Holdsworth SJ, Yeom KW. Simultaneous time of flight-MRA and T2* imaging for cerebrovascular MRI. Neuroradiology 2020; 63:243-251. [PMID: 32945913 DOI: 10.1007/s00234-020-02499-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2020] [Accepted: 07/13/2020] [Indexed: 11/25/2022]
Abstract
PURPOSE 3D multi-echo gradient-recalled echo (ME-GRE) can simultaneously generate time-of-flight magnetic resonance angiography (pTOF) in addition to T2*-based susceptibility-weighted images (SWI). We assessed the clinical performance of pTOF generated from a 3D ME-GRE acquisition compared with conventional TOF-MRA (cTOF). METHODS Eighty consecutive children were retrospectively identified who obtained 3D ME-GRE alongside cTOF. Two blinded readers independently assessed pTOF derived from 3D ME-GRE and compared them with cTOF. A 5-point Likert scale was used to rank lesion conspicuity and to assess for diagnostic confidence. RESULTS Across 80 pediatric neurovascular pathologies, a similar number of lesions were reported on pTOF and cTOF (43-40%, respectively, p > 0.05). Rating of lesion conspicuity was higher with cTOF (4.5 ± 1.0) as compared with pTOF (4.0 ± 0.7), but this was not significantly different (p = 0.06). Diagnostic confidence was rated higher with cTOF (4.8 ± 0.5) than that of pTOF (3.7 ± 0.6; p < 0.001). Overall, the inter-rater agreement between two readers for lesion count on pTOF was classified as almost perfect (κ = 0.98, 96% CI 0.8-1.0). CONCLUSIONS In this study, TOF-MRA simultaneously generated in addition to SWI from 3D MR-GRE can serve as a diagnostic adjunct, particularly for proximal vessel disease and when conventional TOF-MRA images are absent.
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Affiliation(s)
- Bryan A Lanzman
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Yuhao Huang
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
| | - Edward H Lee
- Department of Radiology, Stanford University, Stanford, CA, USA.,Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Michael Iv
- Department of Radiology, Stanford University, Stanford, CA, USA
| | | | - Samantha J Holdsworth
- Mātai Medical Research Institute, Gisborne-Tairāwhiti, Gisborne, New Zealand.,Department of Anatomy and Medical Imaging & Centre for Brain Research, The University of Auckland, Auckland, New Zealand
| | - Kristen W Yeom
- Department of Radiology, Stanford University, Stanford, CA, USA. .,Lucile Packard Children's Hospital, Palo Alto, CA, USA.
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15
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Foxley S, Wildenberg G, Sampathkumar V, Karczmar GS, Brugarolas P, Kasthuri N. Sensitivity to myelin using model-free analysis of the water resonance line-shape in postmortem mouse brain. Magn Reson Med 2020; 85:667-677. [PMID: 32783262 DOI: 10.1002/mrm.28440] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Revised: 06/17/2020] [Accepted: 06/30/2020] [Indexed: 12/18/2022]
Abstract
PURPOSE Dysmyelinating diseases are characterized by abnormal myelin formation and function. Such microstructural abnormalities in myelin have been demonstrated to produce measurable effects on the MR signal. This work examines these effects on measurements of voxel-wise, high-resolution water spectra acquired using a 3D echo-planar spectroscopic imaging (EPSI) pulse sequence from both postmortem fixed control mouse brains and a dysmyelination mouse brain model. METHODS Perfusion fixed, resected control (n = 5) and shiverer (n = 4) mouse brains were imaged using 3D-EPSI with 100 µm isotropic resolution. The free induction decay (FID) was sampled every 2.74 ms over 192 echoes, for a total sampling duration of 526.08 ms. Voxel-wise FIDs were Fourier transformed to produce water spectra with 1.9 Hz resolution. Spectral asymmetry was computed and compared between the two tissue types. RESULTS The water resonance is more asymmetrically broadened in the white matter of control mouse brain compared with dysmyelinated white matter. In control brain, this is modulated by and consistent with previously reported orientationally dependent effects of white matter relative to B0 . Similar sensitivity to orientation is observed in dysmyelinated white matter as well; however, the magnitude of the resonance asymmetry is much lower across all directions. CONCLUSION Results demonstrate that components of the spectra are specifically differentially affected by myelin concentration. This suggests that water proton spectra may be sensitive to the presence of myelin, and as such, could serve as a MRI-based biomarker of dysmyelinating disease, free of mathematical models.
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Affiliation(s)
- Sean Foxley
- Department of Radiology, University of Chicago, Chicago, Illinois, USA
| | - Gregg Wildenberg
- Department of Neurobiology, University of Chicago, Chicago, Illinois, USA
| | | | | | - Pedro Brugarolas
- Department of Radiology, Harvard Medical School, Boston, Maryland, USA.,Gordon Center for Medical Imaging, Massachusetts General Hospital, Boston, Maryland, USA
| | - Narayanan Kasthuri
- Department of Neurobiology, University of Chicago, Chicago, Illinois, USA
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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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Song JE, Shin J, Lee H, Lee HJ, Moon WJ, Kim DH. Blind Source Separation for Myelin Water Fraction Mapping Using Multi-Echo Gradient Echo Imaging. IEEE TRANSACTIONS ON MEDICAL IMAGING 2020; 39:2235-2245. [PMID: 31976881 DOI: 10.1109/tmi.2020.2967068] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
In conventional gradient-echo myelin water imaging (GRE-MWI), myelin water fraction (MWF) is estimated by fitting the multi-echo gradient recalled echo (mGRE) signal to a pre-assumed numerical model (e.g., multi-component exponential curves or three component exponential curves). However, in mGRE, imaging artifacts (e.g., voxel spread function and physiological noise) and noise render the signal to deviate from the numerical model, leading to misfit of the model parameters. Here, as an alternative to the model-based GRE-MWI, a blind source separation (BSS) technique for the separation of multi-exponential mGRE signal is proposed. Among the various BSS techniques, a modified robust principal component analysis (rPCA) is presented to separate signal sources by enforcing the data-driven properties such as "low rankness" and "sparsity." Considering the signal evolution of T2∗ relaxation (i.e., non-negative exponential decay), low rankness of exponential decay was enforced by nonnegative matrix factorization (NMF) and hankelization. This method provides the separation of slow-decaying, fast-decaying exponential components and artifact components from mGRE images. After the separation, MWF map is reconstructed as the ratio of the fast-decaying component to the total decaying components. The proposed method was demonstrated in numerical simulations and in vivo scans. The method provided a robust estimation of MWF in the presence of statistical noise and imaging artifacts.
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18
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Soellradl M, Lesch A, Strasser J, Pirpamer L, Stollberger R, Ropele S, Langkammer C. Assessment and correction of macroscopic field variations in 2D spoiled gradient-echo sequences. Magn Reson Med 2019; 84:620-633. [PMID: 31868260 PMCID: PMC7216950 DOI: 10.1002/mrm.28139] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2019] [Revised: 11/04/2019] [Accepted: 11/29/2019] [Indexed: 01/13/2023]
Abstract
Purpose To model and correct the dephasing effects in the gradient‐echo signal for arbitrary RF excitation pulses with large flip angles in the presence of macroscopic field variations. Methods The dephasing of the spoiled 2D gradient‐echo signal was modeled using a numerical solution of the Bloch equations to calculate the magnitude and phase of the transverse magnetization across the slice profile. Additionally, regional variations of the transmit RF field and slice profile scaling due to macroscopic field gradients were included. Simulations, phantom, and in vivo measurements at 3 T were conducted for R2∗ and myelin water fraction (MWF) mapping. Results The influence of macroscopic field gradients on R2∗ and myelin water fraction estimation can be substantially reduced by applying the proposed model. Moreover, it was shown that the dephasing over time for flip angles of 60° or greater also depends on the polarity of the slice‐selection gradient because of phase variation along the slice profile. Conclusion Substantial improvements in R2∗ accuracy and myelin water fraction mapping coverage can be achieved using the proposed model if higher flip angles are required. In this context, we demonstrated that the phase along the slice profile and the polarity of the slice‐selection gradient are essential for proper modeling of the gradient‐echo signal in the presence of macroscopic field variations.
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Affiliation(s)
- Martin Soellradl
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Andreas Lesch
- Institute of Medical Engineering, Graz University of Technology, Graz, Austria
| | | | - Lukas Pirpamer
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Rudolf Stollberger
- Institute of Medical Engineering, Graz University of Technology, Graz, Austria
| | - Stefan Ropele
- Department of Neurology, Medical University of Graz, Graz, Austria
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19
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Chen Q, She H, Du YP. Improved quantification of myelin water fraction using joint sparsity of T2* distribution. J Magn Reson Imaging 2019; 52:146-158. [DOI: 10.1002/jmri.27013] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2019] [Revised: 11/20/2019] [Accepted: 11/20/2019] [Indexed: 12/23/2022] Open
Affiliation(s)
- Quan Chen
- Institute for Medical Imaging Technology, School of Biomedical EngineeringShanghai Jiao Tong University Shanghai China
| | - Huajun She
- Institute for Medical Imaging Technology, School of Biomedical EngineeringShanghai Jiao Tong University Shanghai China
| | - Yiping P. Du
- Institute for Medical Imaging Technology, School of Biomedical EngineeringShanghai Jiao Tong University Shanghai China
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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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Drenthen GS, Backes WH, Aldenkamp AP, Op 't Veld GJ, Jansen JFA. A new analysis approach for T 2 relaxometry myelin water quantification: Orthogonal Matching Pursuit. Magn Reson Med 2018; 81:3292-3303. [PMID: 30444019 PMCID: PMC6587563 DOI: 10.1002/mrm.27600] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2018] [Revised: 10/09/2018] [Accepted: 10/18/2018] [Indexed: 12/19/2022]
Abstract
Purpose In vivo myelin quantification can provide valuable noninvasive information on neuronal maturation and development, as well as insights into neurological disorders. Multiexponential analysis of multiecho T2 relaxation is a powerful and widely applied method for the quantification of the myelin water fraction (MWF). In recent literature, the MWF is most commonly estimated using a regularized nonnegative least squares algorithm. Methods The orthogonal matching pursuit algorithm is proposed as an alternative method for the estimation of the MWF. The orthogonal matching pursuit is a greedy sparse reconstruction algorithm with a low computation complexity. For validation, both methods are compared to a ground truth using numerical simulations and a phantom model using comparable computation times. The numerical simulations were used to measure the theoretical errors, as well as the effects of varying the SNR, strength of the regularization, and resolution of the basis set. Additionally, a phantom model was used to estimate the performance of the 2 methods while including errors occurring due to the MR measurement. Lastly, 4 healthy subjects were scanned to evaluate the in vivo performance. Results The results in simulations and phantoms demonstrate that the MWFs determined with the orthogonal matching pursuit are 1.7 times more accurate as compared to the nonnegative least squares, with a comparable precision. The remaining bias of the MWF is shown to be related to the regularization of the nonnegative least squares algorithm and the Rician noise present in magnitude MR images. Conclusion The orthogonal matching pursuit algorithm provides a more accurate alternative for T2 relaxometry myelin water quantification.
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Affiliation(s)
- Gerhard S Drenthen
- School for Mental Health and Neuroscience, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, the Netherlands.,Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, the Netherlands.,Department of Electrical Engineering, Eindhoven University of Technology, De Rondom 70, Eindhoven, the Netherlands
| | - Walter H Backes
- School for Mental Health and Neuroscience, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, the Netherlands.,Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, the Netherlands
| | - Albert P Aldenkamp
- School for Mental Health and Neuroscience, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, the Netherlands.,Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, the Netherlands.,Department of Behavioral Sciences, Epilepsy Center Kempenhaeghe, Sterkselseweg 65, Heeze, the Netherlands
| | - Giel J Op 't Veld
- School of Computer and Communication Sciences, École Polytechnique Fédérale de Lausanne, Station 14, Lausanne, Switzerland
| | - Jacobus F A Jansen
- School for Mental Health and Neuroscience, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, the Netherlands.,Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, the Netherlands.,Department of Electrical Engineering, Eindhoven University of Technology, De Rondom 70, Eindhoven, the Netherlands
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22
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West KL, Kelm ND, Carson RP, Gochberg DF, Ess KC, Does MD. Myelin volume fraction imaging with MRI. Neuroimage 2018; 182:511-521. [PMID: 28025129 PMCID: PMC5481512 DOI: 10.1016/j.neuroimage.2016.12.067] [Citation(s) in RCA: 50] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2016] [Revised: 11/23/2016] [Accepted: 12/22/2016] [Indexed: 11/20/2022] Open
Abstract
MRI is a valuable tool to assess myelin during development and demyelinating disease processes. While multiexponential T2 and quantitative magnetization transfer measures correlate with myelin content, neither provides the total myelin volume fraction. In many cases correlative measures are adequate; but to assess microstructure of myelin, (e.g. calculate the g-ratio using MRI), an accurate measure of myelin volume fraction is imperative. Using a volumetric model of white matter, we relate MRI measures of myelin to absolute measures of myelin volume fraction and compare them to quantitative histology. We assess our approach in control mice along with two models of hypomyelination and one model of hypermyelination and find strong agreement between MRI and histology amongst models. This work investigates the sensitivities of MRI myelin measures to changes in axon geometry and displays promise for estimating g-ratio from MRI.
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Affiliation(s)
- Kathryn L West
- Department of Biomedical Engineering, Vanderbilt University, USA; Vanderbilt University Institute of Imaging Science, Vanderbilt University, USA
| | - Nathaniel D Kelm
- Department of Biomedical Engineering, Vanderbilt University, USA; Vanderbilt University Institute of Imaging Science, Vanderbilt University, USA
| | - Robert P Carson
- Department of Pediatrics, Vanderbilt University School of Medicine, USA; Department of Neurology, Vanderbilt University School of Medicine, USA
| | - Daniel F Gochberg
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, USA; Department of Radiology and Radiological Sciences, Vanderbilt University School of Medicine, USA
| | - Kevin C Ess
- Department of Pediatrics, Vanderbilt University School of Medicine, USA; Department of Neurology, Vanderbilt University School of Medicine, USA
| | - Mark D Does
- Department of Biomedical Engineering, Vanderbilt University, USA; Vanderbilt University Institute of Imaging Science, Vanderbilt University, USA; Department of Radiology and Radiological Sciences, Vanderbilt University School of Medicine, USA; Department of Electrical Engineering, Vanderbilt University, USA.
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Neeb H, Schenk J. Multivariate prediction of multiple sclerosis using robust quantitative MR-based image metrics. Z Med Phys 2018; 29:262-271. [PMID: 30442457 DOI: 10.1016/j.zemedi.2018.10.004] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2018] [Revised: 08/25/2018] [Accepted: 10/14/2018] [Indexed: 02/02/2023]
Abstract
OBJECTIVES The current work investigates the performance of different multivariate supervised machine learning models to predict the presence or absence of multiple sclerosis (MS) based on features derived from quantitative MRI acquisitions. The performance of these models was evaluated for images which are significantly degraded due to subject motion, a problem which is often observed in clinical routine diagnostics. Finally, the difference between a true multivariate analysis and the corresponding univariate analysis based on single parameters alone was addressed. MATERIALS AND METHODS 52 MS patients and 45 healthy controls where scanned on a 3T system. The datasets showed variable degrees of motion-associated artefacts. For each dataset, the average of T1, T2*, total and myelin bound water content was determined in white and grey matter. Based on these parameters, different multivariate models were trained and their cross-validated performance to predict the presence of MS was evaluated. Furthermore, the univariate distributions of each quantitative parameter were employed to define optimised cut-offs that differentiate MS patients from healthy controls. RESULTS For data not affected by motion, 83.7% of all subjects were correctly classified using a crossvalidated multivariate model. Inclusion of data with significant artefacts reduces the rate of correct classification to 74.5%. T1 in grey and myelin water content in white matter where the most discriminating variables in the multivariate analysis. In contrast, the total water content in white matter and the ratio of white and grey matter total water content each resulted in 77% correct classifications in a univariate regression analysis. CONCLUSION The results demonstrate that even simple quantitative MRI-based measures allow for an automated prediction of the presence/absence of multiple sclerosis with good specificity. Importantly, even highly degraded datasets due to motion-artefacts could be correctly classified, especially when pooling features derived from grey and white matter. Finally, the advantage of a multivariate over a univariate analysis of quantitative MR data was shown.
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Affiliation(s)
- Heiko Neeb
- Multimodal Imaging Physics Group, University of Applied Sciences Koblenz, RheinAhrCampus Remagen, 53424 Remagen, Germany; Institute for Medical Engineering and Information Processing - MTI Mittelrhein, University of Koblenz, 56070 Koblenz, Germany.
| | - Jochen Schenk
- Radiologisches Institut Hohenzollernstrasse, 56068 Koblenz, Germany
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24
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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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Lee H, Nam Y, Kim D. Echo time‐range effects on gradient‐echo based myelin water fraction mapping at 3T. Magn Reson Med 2018; 81:2799-2807. [DOI: 10.1002/mrm.27564] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2018] [Revised: 09/15/2018] [Accepted: 09/19/2018] [Indexed: 12/19/2022]
Affiliation(s)
- Hongpyo Lee
- Department of Electrical and Electronic Engineering Yonsei University Seoul Korea
| | - Yoonho Nam
- Department of Radiology Seoul St. Mary’s Hospital, College of Medicine, the Catholic University of Korea Seoul Korea
| | - Dong‐Hyun Kim
- Department of Electrical and Electronic Engineering Yonsei University Seoul Korea
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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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Bouhrara M, Reiter DA, Maring MC, Bonny JM, Spencer RG. Use of the NESMA Filter to Improve Myelin Water Fraction Mapping with Brain MRI. J Neuroimaging 2018; 28:640-649. [PMID: 29999204 DOI: 10.1111/jon.12537] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2018] [Revised: 05/31/2018] [Accepted: 06/19/2018] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND AND PURPOSE Myelin water fraction (MWF) mapping permits direct visualization of myelination patterns in the developing brain and in pathology. MWF is conventionally measured through multiexponential T2 analysis which is very sensitive to noise, leading to inaccuracies in derived MWF estimates. Although noise reduction filters may be applied during postprocessing, conventional filtering can introduce bias and obscure small structures and edges. Advanced nonblurring filters, while effective, exhibit a high level of complexity and the requirement for supervised implementation for optimal performance. The purpose of this paper is to demonstrate the ability of the recently introduced nonlocal estimation of multispectral magnitudes (NESMA) filter to greatly improve the determination of MWF parameter estimates from gradient and spin echo (GRASE) imaging data. METHODS We evaluated the performance of the NESMA filter for MWF mapping from clinical GRASE imaging data of the human brain, and compared the results to those calculated from unfiltered images. Numerical and in vivo analyses of the brains of three subjects, representing different ages, were conducted. RESULTS Our results demonstrated the potential of the NESMA filter to permit high-quality in vivo MWF mapping. Indeed, NESMA permits substantial reduction of random variation in derived MWF estimates while preserving accuracy and detail. CONCLUSIONS In vivo estimation of MWF in the human brain from GRASE imaging data was markedly improved through use of the NESMA filter. The use of NESMA may contribute to the goal of high-quality MWF mapping in clinically feasible imaging times.
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Affiliation(s)
- Mustapha Bouhrara
- Laboratory of Clinical Investigation, National Institute on Aging, NIH, Baltimore, MD
| | - David A Reiter
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA
| | - Michael C Maring
- Laboratory of Clinical Investigation, National Institute on Aging, NIH, Baltimore, MD
| | | | - Richard G Spencer
- Laboratory of Clinical Investigation, National Institute on Aging, NIH, Baltimore, MD
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Lee H, Nam Y, Lee HJ, Hsu JJ, Henry RG, Kim DH. Improved three-dimensional multi-echo gradient echo based myelin water fraction mapping with phase related artifact correction. Neuroimage 2018; 169:1-10. [DOI: 10.1016/j.neuroimage.2017.11.058] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2017] [Revised: 11/21/2017] [Accepted: 11/25/2017] [Indexed: 12/17/2022] Open
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Lee D, Lee J, Lee J, Nam Y. Single-scan z-shim method for reducing susceptibility artifacts in gradient echo myelin water imaging. Magn Reson Med 2018; 80:1101-1109. [DOI: 10.1002/mrm.27127] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2017] [Revised: 01/14/2018] [Accepted: 01/21/2018] [Indexed: 11/11/2022]
Affiliation(s)
- Doohee Lee
- Department of Electrical and Computer Engineering; Seoul National University; Seoul Korea
| | - Jingu Lee
- Department of Electrical and Computer Engineering; Seoul National University; Seoul Korea
| | - Jongho Lee
- Department of Electrical and Computer Engineering; Seoul National University; Seoul Korea
| | - Yoonho Nam
- Department of Radiology; Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea; Seoul Korea
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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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Lee J, Nam Y, Choi JY, Kim EY, Oh SH, Kim DH. Mechanisms of T 2 * anisotropy and gradient echo myelin water imaging. NMR IN BIOMEDICINE 2017; 30:e3513. [PMID: 27060968 DOI: 10.1002/nbm.3513] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2015] [Revised: 01/26/2016] [Accepted: 02/17/2016] [Indexed: 06/05/2023]
Abstract
In MRI, structurally aligned molecular or micro-organization (e.g. axonal fibers) can be a source of substantial signal variations that depend on the structural orientation and the applied magnetic field. This signal anisotropy gives us a unique opportunity to explore information that exists at a resolution several orders of magnitude smaller than that of typical MRI. In this review, one of the signal anisotropies, T2 * anisotropy in white matter, and a related imaging method, gradient echo myelin water imaging (GRE-MWI), are explored. The T2 * anisotropy has been attributed to isotropic and anisotropic magnetic susceptibility of myelin and compartmentalized microstructure of white matter fibers (i.e. axonal, myelin, and extracellular space). The susceptibility and microstructure create magnetic frequency shifts that change with the relative orientation of the fiber and the main magnetic field, generating the T2 * anisotropy. The resulting multi-component magnitude decay and nonlinear phase evolution have been utilized for GRE-MWI, assisting in resolving the signal fraction of the multiple compartments in white matter. The GRE-MWI method has been further improved by signal compensation techniques including physiological noise compensation schemes. The T2 * anisotropy and GRE-MWI provide microstructural information on a voxel (e.g. fiber orientation and tissue composition), and may serve as sensitive biomarkers for microstructural changes in the brain. Copyright © 2016 John Wiley & Sons, Ltd.
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Affiliation(s)
- Jongho Lee
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea
| | - Yoonho Nam
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Joon Yul Choi
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea
| | - Eung Yeop Kim
- Department of Radiology, Gachon University Gil Medical Center, Incheon, Korea
| | - Se-Hong Oh
- Imaging Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Dong-Hyun Kim
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Korea
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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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Bouhrara M, Spencer RG. Rapid simultaneous high-resolution mapping of myelin water fraction and relaxation times in human brain using BMC-mcDESPOT. Neuroimage 2016; 147:800-811. [PMID: 27729276 DOI: 10.1016/j.neuroimage.2016.09.064] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2016] [Revised: 08/21/2016] [Accepted: 09/26/2016] [Indexed: 10/20/2022] Open
Abstract
A number of central nervous system (CNS) diseases exhibit changes in myelin content and magnetic resonance longitudinal, T1, and transverse, T2, relaxation times, which therefore represent important biomarkers of CNS pathology. Among the methods applied for measurement of myelin water fraction (MWF) and relaxation times, the multicomponent driven equilibrium single pulse observation of T1 and T2 (mcDESPOT) approach is of particular interest. mcDESPOT permits whole brain mapping of multicomponent T1 and T2, with data acquisition accomplished within a clinically realistic acquisition time. Unfortunately, previous studies have indicated the limited performance of mcDESPOT in the setting of the modest signal-to-noise range of high-resolution mapping, required for the depiction of small structures and to reduce partial volume effects. Recently, we showed that a new Bayesian Monte Carlo (BMC) analysis substantially improved determination of MWF from mcDESPOT imaging data. However, our previous study was limited in that it did not discuss determination of relaxation times. Here, we extend the BMC analysis to the simultaneous determination of whole-brain MWF and relaxation times using the two-component mcDESPOT signal model. Simulation analyses and in-vivo human brain studies indicate the overall greater performance of this approach compared to the stochastic region contraction (SRC) algorithm, conventionally used to derive parameter estimates from mcDESPOT data. SRC estimates of the transverse relaxation time of the long T2 fraction, T2,l, and the longitudinal relaxation time of the short T1 fraction, T1,s, clustered towards the lower and upper parameter search space limits, respectively, indicating failure of the fitting procedure. We demonstrate that this effect is absent in the BMC analysis. Our results also showed improved parameter estimation for BMC as compared to SRC for high-resolution mapping. Overall we find that the combination of BMC analysis and mcDESPOT, BMC-mcDESPOT, shows excellent performance for accurate high-resolution whole-brain mapping of MWF and bi-component transverse and longitudinal relaxation times within a clinically realistic acquisition time.
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Affiliation(s)
- Mustapha Bouhrara
- Magnetic Resonance Imaging and Spectroscopy Section, Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Intramural Research Program, BRC 04B-116, 251 Bayview Boulevard, Baltimore, MD 21224, USA.
| | - Richard G Spencer
- Magnetic Resonance Imaging and Spectroscopy Section, Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Intramural Research Program, BRC 04B-116, 251 Bayview Boulevard, Baltimore, MD 21224, USA.
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34
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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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35
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Bouhrara M, Spencer RG. Improved determination of the myelin water fraction in human brain using magnetic resonance imaging through Bayesian analysis of mcDESPOT. Neuroimage 2016; 127:456-471. [PMID: 26499810 PMCID: PMC4854306 DOI: 10.1016/j.neuroimage.2015.10.034] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2015] [Revised: 09/26/2015] [Accepted: 10/14/2015] [Indexed: 10/22/2022] Open
Abstract
Myelin water fraction (MWF) mapping with magnetic resonance imaging has led to the ability to directly observe myelination and demyelination in both the developing brain and in disease. Multicomponent driven equilibrium single pulse observation of T1 and T2 (mcDESPOT) has been proposed as a rapid approach for multicomponent relaxometry and has been applied to map MWF in the human brain. However, even for the simplest two-pool signal model consisting of myelin-associated and non-myelin-associated water, the dimensionality of the parameter space for obtaining MWF estimates remains high. This renders parameter estimation difficult, especially at low-to-moderate signal-to-noise ratios (SNRs), due to the presence of local minima and the flatness of the fit residual energy surface used for parameter determination using conventional nonlinear least squares (NLLS)-based algorithms. In this study, we introduce three Bayesian approaches for analysis of the mcDESPOT signal model to determine MWF. Given the high-dimensional nature of the mcDESPOT signal model, and, therefore the high-dimensional marginalizations over nuisance parameters needed to derive the posterior probability distribution of the MWF, the Bayesian analyses introduced here use different approaches to reduce the dimensionality of the parameter space. The first approach uses normalization by average signal amplitude, and assumes that noise can be accurately estimated from signal-free regions of the image. The second approach likewise uses average amplitude normalization, but incorporates a full treatment of noise as an unknown variable through marginalization. The third approach does not use amplitude normalization and incorporates marginalization over both noise and signal amplitude. Through extensive Monte Carlo numerical simulations and analysis of in vivo human brain datasets exhibiting a range of SNR and spatial resolution, we demonstrated markedly improved accuracy and precision in the estimation of MWF using these Bayesian methods as compared to the stochastic region contraction (SRC) implementation of NLLS.
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Affiliation(s)
- Mustapha Bouhrara
- Magnetic Resonance Imaging and Spectroscopy Section, Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA.
| | - Richard G Spencer
- Magnetic Resonance Imaging and Spectroscopy Section, Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA.
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Akhondi-Asl A, Afacan O, Balasubramanian M, Mulkern RV, Warfield SK. Fast myelin water fraction estimation using 2D multislice CPMG. Magn Reson Med 2015; 76:1301-13. [PMID: 26536382 DOI: 10.1002/mrm.26034] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2015] [Revised: 09/22/2015] [Accepted: 10/15/2015] [Indexed: 11/09/2022]
Abstract
PURPOSE T2 relaxometry based on multiexponential fitting to a single slice multiecho sequence has been the most common MRI technique for myelin water fraction mapping, where the short T2 is associated with myelin water. However, very long acquisition times and physically unrealistic models for T2 distribution are limitations of this approach. We present a novel framework for myelin imaging which substantially increases the imaging speed and myelin water fraction estimation accuracy. METHOD We used the 2D multislice Carr-Purcell-Meiboom-Gill sequence to increase the volume coverage. To compensate for nonideal slice profiles, we numerically solved the Bloch equations for a range of T2 and B1 inhomogeneity scales to construct the bases for the estimation of the T2 distribution. We used a finite mixture of continuous parametric distributions to describe the complete T2 spectrum and used the constrained variable projection optimization algorithm to estimate myelin water fraction. To validate our model, synthetic, phantom, and in vivo brain experiments were conducted. RESULTS Using the Bloch equations, we can model the slice profile and construct the forward model of the T2 curve. Our method estimated myelin water fraction with smaller error than the nonnegative least squares algorithm. CONCLUSIONS The proposed framework can be used for reliable whole brain myelin imaging with a resolution of 2×2×4 mm3 in ≈17 min. Magn Reson Med 76:1301-1313, 2016. © 2015 Wiley Periodicals, Inc.
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Affiliation(s)
- Alireza Akhondi-Asl
- Computational Radiology Laboratory, Department of Radiology, Children's Hospital, Boston, Massachusetts, USA.
| | - Onur Afacan
- Computational Radiology Laboratory, Department of Radiology, Children's Hospital, Boston, Massachusetts, USA
| | - Mukund Balasubramanian
- Computational Radiology Laboratory, Department of Radiology, Children's Hospital, Boston, Massachusetts, USA
| | - Robert V Mulkern
- Computational Radiology Laboratory, Department of Radiology, Children's Hospital, Boston, Massachusetts, USA
| | - Simon K Warfield
- Computational Radiology Laboratory, Department of Radiology, Children's Hospital, Boston, Massachusetts, USA
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Nam Y, Lee J, Hwang D, Kim DH. Improved estimation of myelin water fraction using complex model fitting. Neuroimage 2015; 116:214-21. [PMID: 25858448 DOI: 10.1016/j.neuroimage.2015.03.081] [Citation(s) in RCA: 81] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2015] [Revised: 02/28/2015] [Accepted: 03/17/2015] [Indexed: 01/20/2023] Open
Abstract
In gradient echo (GRE) imaging, three compartment water modeling (myelin water, axonal water and extracellular water) in white matter has been demonstrated to show different frequency shifts that depend on the relative orientation of fibers and the B0 field. This finding suggests that in GRE-based myelin water imaging, a signal model may need to incorporate frequency offset terms and become a complex-valued model. In the current study, three different signal models and fitting approaches (a magnitude model fitted to magnitude data, a complex model fitted to magnitude data, and a complex model fitted to complex data) were investigated to address the reliability of each model in the estimation of the myelin water signal. For the complex model fitted to complex data, a new fitting approach that does not require background phase removal was proposed. When the three models were compared, the results from the new complex model fitting showed the most stable parameter estimation.
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Affiliation(s)
- Yoonho Nam
- Department of Electrical and Electronic Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 120-749, Republic of Korea; Department of Electrical and Computer Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 151-744, Republic of Korea
| | - Jongho Lee
- Department of Electrical and Computer Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 151-744, Republic of Korea.
| | - Dosik Hwang
- Department of Electrical and Electronic Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 120-749, Republic of Korea
| | - Dong-Hyun Kim
- Department of Electrical and Electronic Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 120-749, Republic of Korea.
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Marchand A, Hitti E, Monge F, Saint-Jalmes H, Guillin R, Duvauferrier R, Gambarota G. MRI quantification of diffusion and perfusion in bone marrow by intravoxel incoherent motion (IVIM) and non-negative least square (NNLS) analysis. Magn Reson Imaging 2014; 32:1091-6. [DOI: 10.1016/j.mri.2014.07.009] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2013] [Revised: 05/24/2014] [Accepted: 07/25/2014] [Indexed: 01/21/2023]
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Kim D, Lee HM, Oh SH, Lee J. Probing signal phase in direct visualization of short transverse relaxation time component (ViSTa). Magn Reson Med 2014; 74:499-505. [PMID: 25154599 DOI: 10.1002/mrm.25416] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2014] [Revised: 07/03/2014] [Accepted: 07/28/2014] [Indexed: 11/08/2022]
Abstract
PURPOSE To demonstrate the phase evolutions of direct visualization of short transverse relaxation time component (ViSTa) matches with those of myelin water. METHOD Myelin water imaging (MWI) measures short transverse signals and has been suggested as a biomarker for myelin. Recently, a new approach, ViSTa, has been proposed to acquire short T2* signals by suppressing long T1 signals. This method does not require any ill-conditioned data processing and therefore provides high-quality images. In this study, the phase of the ViSTa signal was compared with the phase of myelin water simulated by the magnetic susceptibility model of hollow cylinder. RESULTS The phase evolutions of the ViSTa signal were similar to the simulated myelin water phase evolutions. When fiber orientation was perpendicular relative to the main magnetic field, both the ViSTa and the simulated myelin water phase showed large positive frequency shifts, whereas the gradient echo phase showed a slightly negative frequency shift. Additionally, the myelin water phase map generated using diffusion tensor imaging (DTI) information revealed a good match with the ViSTa phase image. CONCLUSION The results of this study support the origin of ViSTa signal as myelin water. ViSTa phase may potentially provide sensitivity to demyelination.
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Affiliation(s)
- Daeun Kim
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Signal and Image Processing Institute, Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, California, USA
| | - Hyo Min Lee
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Se-Hong Oh
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Imaging Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Jongho Lee
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Department of Electrical and Computer Engineering, School of Engineering, Seoul National University, Seoul, Korea
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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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Alonso-Ortiz E, Levesque IR, Pike GB. MRI-based myelin water imaging: A technical review. Magn Reson Med 2014; 73:70-81. [PMID: 24604728 DOI: 10.1002/mrm.25198] [Citation(s) in RCA: 195] [Impact Index Per Article: 19.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2013] [Revised: 02/11/2014] [Accepted: 02/12/2014] [Indexed: 12/19/2022]
Abstract
Multiexponential T2 relaxation time measurement in the central nervous system shows a component that originates from water trapped between the lipid bilayers of myelin. This myelin water component is of significant interest as it provides a myelin-specific MRI signal of value in assessing myelin changes in cerebral white matter in vivo. In this article, the various acquisition and analysis strategies proposed to date for myelin water imaging are reviewed and research conducted into their validity and clinical applicability is presented. Comparisons between the imaging methods are made with a discussion regarding potential difficulties and model limitations.
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Affiliation(s)
- Eva Alonso-Ortiz
- Medical Physics Unit, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, 3801 University Street, room WB 321, Montreal, Quebec, Canada, H3A 2B4
| | - Ives R Levesque
- Department of Oncology, McGill University and Research Institute of the MUHC, 1650 Cedar Avenue, room L5-212.3, Montreal, Quebec, Canada, H3A 2G4
| | - G Bruce Pike
- Department of Radiology and Hotchkiss Brain Institute, University of Calgary, 3330 Hospital Drive NW, Calgary, Alberta, Canada, T2N 4N1
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Oh SH, Bilello M, Schindler M, Markowitz CE, Detre JA, Lee J. Direct visualization of short transverse relaxation time component (ViSTa). Neuroimage 2013; 83:485-92. [PMID: 23796545 DOI: 10.1016/j.neuroimage.2013.06.047] [Citation(s) in RCA: 66] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2013] [Revised: 05/14/2013] [Accepted: 06/13/2013] [Indexed: 10/26/2022] Open
Abstract
White matter of the brain has been demonstrated to have multiple relaxation components. Among them, the short transverse relaxation time component (T2<40 ms; T2⁎<25 ms at 3 T) has been suggested to originate from myelin water whereas long transverse relaxation time components have been associated with axonal and/or interstitial water. In myelin water imaging, T2 or T2⁎ signal decay is measured to estimate myelin water fraction based on T2 or T2⁎ differences among the water components. This method has been demonstrated to be sensitive to demyelination in the brain but suffers from low SNR and image artifacts originating from ill-conditioned multi-exponential fitting. In this study, a novel approach that selectively acquires short transverse relaxation time signal is proposed. The method utilizes a double inversion RF pair to suppress a range of long T1 signal. This suppression leaves short T2⁎ signal, which has been suggested to have short T1, as the primary source of the image. The experimental results confirm that after suppression of long T1 signals, the image is dominated by short T2⁎ in the range of myelin water, allowing us to directly visualize the short transverse relaxation time component in the brain. Compared to conventional myelin water imaging, this new method of direct visualization of short relaxation time component (ViSTa) provides high quality images. When applied to multiple sclerosis patients, chronic lesions show significantly reduced signal intensity in ViSTa images suggesting sensitivity to demyelination.
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Affiliation(s)
- Se-Hong Oh
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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Borich M, MacKay A, Vavasour I, Rauscher A, Boyd L. Evaluation of white matter myelin water fraction in chronic stroke. Neuroimage Clin 2013; 2:569-80. [PMID: 24179808 PMCID: PMC3777839 DOI: 10.1016/j.nicl.2013.04.006] [Citation(s) in RCA: 61] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2013] [Revised: 04/11/2013] [Accepted: 04/11/2013] [Indexed: 12/15/2022]
Abstract
Multi-component T2 relaxation imaging (MCRI) provides specific in vivo measurement of myelin water content and tissue water environments through myelin water fraction (MWF), intra/extra-cellular water fraction (I/EWF) and intra/extracellular and global geometric mean T2 (GMT2) times. Quantitative MCRI assessment of tissue water environments has provided new insights into the progression and underlying white matter pathology in neural disorders such as multiple sclerosis. It has not previously been applied to investigate changes in white matter in the stroke-affected brain. Thus, the purposes of this study were to 1) use MCRI to index myelin water content and tissue water environments in the brain after stroke 2) evaluate relationships between MWF and diffusion behavior indexed by diffusion tensor imaging-based metrics and 3) examine the relationship between white matter status (MWF and fractional anisotropy) and motor behavior in the chronic phase of stroke recovery. Twenty individuals with ischemic stroke and 12 matched healthy controls participated. Excellent to good test/re-test and inter-rater reliability was observed for region of interest-based voxelwise MWF data. Reduced MWF was observed in whole-cerebrum white matter (p < 0.001) and in the ipsilesional (p = 0.017) and contralesional (p = 0.037) posterior limb of internal capsule (PLIC) after stroke compared to whole-cerebrum and bilateral PLIC MWF in healthy controls. The stroke group also demonstrated increased I/EWF, I/E GMT2 and global GMT2 times for whole-cerebrum white matter. Measures of diffusion behavior were also significantly different in the stroke group across each region investigated (p < 0.001). MWF was not significantly correlated with specific tensor-based measures of diffusion in the PLIC for either group. Fractional anisotropy in the ipsilesional PLIC correlated with motor behavior in chronic stroke. These results provide novel insights into tissue-specific changes within white matter after stroke that may have important applications for the understanding of the neuropathology of stroke.
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Affiliation(s)
- M.R. Borich
- Department of Physical Therapy, University of British Columbia, Canada
| | - A.L. MacKay
- Department of Radiology, University of British Columbia, Canada
- Department of Physics and Astronomy, University of British Columbia, Canada
| | - I.M. Vavasour
- Department of Radiology, University of British Columbia, Canada
| | - A. Rauscher
- Department of Radiology, University of British Columbia, Canada
- UBC MRI Research Centre, University of British Columbia, Canada
- Brain Research Centre, University of British Columbia, Canada
| | - L.A. Boyd
- Department of Physical Therapy, University of British Columbia, Canada
- Brain Research Centre, University of British Columbia, Canada
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Meyers SM, Vavasour IM, Mädler B, Harris T, Fu E, Li DK, Traboulsee AL, MacKay AL, Laule C. Multicenter measurements of myelin water fraction and geometric mean T2: Intra- and intersite reproducibility. J Magn Reson Imaging 2013; 38:1445-53. [DOI: 10.1002/jmri.24106] [Citation(s) in RCA: 56] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2012] [Accepted: 02/11/2013] [Indexed: 11/10/2022] Open
Affiliation(s)
- Sandra M. Meyers
- Physics and Astronomy; University of British Columbia; Vancouver BC Canada
| | | | | | - Trudy Harris
- UBC MRI Research Centre; University of British Columbia; Vancouver BC Canada
| | - Eric Fu
- Centre for Health Evaluation and Outcome Sciences; St Paul's Hospital; BC Canada
| | - David K.B. Li
- Radiology; University of British Columbia; Vancouver BC Canada
- UBC MRI Research Centre; University of British Columbia; Vancouver BC Canada
- Medicine, 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
- UBC MRI Research Centre; University of British Columbia; Vancouver BC Canada
| | - Cornelia Laule
- Radiology; University of British Columbia; Vancouver BC Canada
- UBC MRI Research Centre; University of British Columbia; Vancouver BC Canada
- Pathology and Laboratory Medicine; University of British Columbia; Vancouver BC Canada
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Kwon OI, Woo EJ, Du YP, Hwang D. A tissue-relaxation-dependent neighboring method for robust mapping of the myelin water fraction. Neuroimage 2013; 74:12-21. [PMID: 23384527 DOI: 10.1016/j.neuroimage.2013.01.064] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2012] [Revised: 01/17/2013] [Accepted: 01/23/2013] [Indexed: 10/27/2022] Open
Abstract
Quantitative assessment of the myelin content in white matter (WM) using MRI has become a useful tool for investigating myelin-related diseases, such as multiple sclerosis (MS). Myelin water fraction (MWF) maps can be estimated pixel-by-pixel by a determination of the T₂ or T₂* spectrum from signal decay measurements at each individual image pixel. However, detection of parameters from the measured decay curve, assuming a combination of smooth multi-exponential curves, results in a nonlinear and seriously ill-posed problem. In this paper, we propose a new method to obtain a stable MWF map robust to the presence of noise while sustaining sufficient resolution, which uses weighted combinations of measured decay signals in a spatially independent neighborhood to combine tissues with similar relaxation parameters. To determine optimal weighting factors, we define a spatially independent neighborhood for each pixel and a distance with respect to decay rates that effectively includes pixels with similar decay characteristics, and which therefore have similar relaxation parameters. We recover the MWF values by using optimally weighted decay curves. We use numerical simulations and in vitro and in vivo experimental brain data scanned with a multi-gradient-echo sequence to demonstrate the feasibility of our proposed algorithm and to highlight its advantages compared to the conventional method.
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Affiliation(s)
- Oh In Kwon
- Department of Mathematics, Konkuk University, Republic of Korea
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Multicentre absolute myelin water content mapping: Development of a whole brain atlas and application to low-grade multiple sclerosis. NEUROIMAGE-CLINICAL 2012; 1:121-30. [PMID: 24179745 PMCID: PMC3757724 DOI: 10.1016/j.nicl.2012.09.013] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/21/2012] [Revised: 09/27/2012] [Accepted: 09/28/2012] [Indexed: 01/24/2023]
Abstract
The current study investigates the whole brain myelin water content distribution applying a new approach that allows for the simultaneous mapping of total and relative myelin water content, T 1 and T 2* with full brain coverage and high resolution (1 × 1 × 2 mm(3)). The data was collected at two different sites in healthy controls to validate the independence of a specific setup. In addition, a group of patients with known white matter affections was investigated to compare two measures of myelin, i.e. relative and absolute myelin water content. Based on the first dataset, a quantitative myelin water content atlas was created which served as a control set for the other two datasets. Both control groups measured at different institutions yielded consistent results. However, distinct regions of reduced myelin water content were observed for the patient dataset, both on an individual basis and in a group-wise comparison. The comparison between the absolute and relative measurement of myelin water content in MS patients showed that the relative measurement, which is employed by many researchers, overestimates both disease volume and the corresponding reduction of myelin water content in white matter lesions. However, for normal appearing white matter, no difference between both approaches was detected. The results obtained in the current study demonstrate that absolute myelin water content can reliably be determined in a multicentre environment using standard MR sequences. The optimised protocol allows for a measurement of four quantitative parameters with full brain coverage in only 10 min. This might expedite a more widespread future use of quantitative MRI methods for clinical research and diagnosis.
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