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Khodanovich M, Svetlik M, Naumova A, Kamaeva D, Usova A, Kudabaeva M, Anan’ina T, Wasserlauf I, Pashkevich V, Moshkina M, Obukhovskaya V, Kataeva N, Levina A, Tumentceva Y, Yarnykh V. Age-Related Decline in Brain Myelination: Quantitative Macromolecular Proton Fraction Mapping, T2-FLAIR Hyperintensity Volume, and Anti-Myelin Antibodies Seven Years Apart. Biomedicines 2023; 12:61. [PMID: 38255168 PMCID: PMC10812983 DOI: 10.3390/biomedicines12010061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 12/09/2023] [Accepted: 12/21/2023] [Indexed: 01/24/2024] Open
Abstract
Age-related myelination decrease is considered one of the likely mechanisms of cognitive decline. The present preliminary study is based on the longitudinal assessment of global and regional myelination of the normal adult human brain using fast macromolecular fraction (MPF) mapping. Additional markers were age-related changes in white matter (WM) hyperintensities on FLAIR-MRI and the levels of anti-myelin autoantibodies in serum. Eleven healthy subjects (33-60 years in the first study) were scanned twice, seven years apart. An age-related decrease in MPF was found in global WM, grey matter (GM), and mixed WM-GM, as well as in 48 out of 82 examined WM and GM regions. The greatest decrease in MPF was observed for the frontal WM (2-5%), genu of the corpus callosum (CC) (4.0%), and caudate nucleus (5.9%). The age-related decrease in MPF significantly correlated with an increase in the level of antibodies against myelin basic protein (MBP) in serum (r = 0.69 and r = 0.63 for global WM and mixed WM-GM, correspondingly). The volume of FLAIR hyperintensities increased with age but did not correlate with MPF changes and the levels of anti-myelin antibodies. MPF mapping showed high sensitivity to age-related changes in brain myelination, providing the feasibility of this method in clinics.
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Affiliation(s)
- Marina Khodanovich
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (M.S.); (A.N.); (M.K.); (T.A.); (I.W.); (N.K.); (A.L.); (Y.T.)
| | - Mikhail Svetlik
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (M.S.); (A.N.); (M.K.); (T.A.); (I.W.); (N.K.); (A.L.); (Y.T.)
| | - Anna Naumova
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (M.S.); (A.N.); (M.K.); (T.A.); (I.W.); (N.K.); (A.L.); (Y.T.)
- Department of Radiology, University of Washington, 850 Republican Street, Seattle, WA 98109, USA
| | - Daria Kamaeva
- Laboratory of Molecular Genetics and Biochemistry, Mental Health Research Institute, Tomsk National Research Medical Center of the Russian Academy of Sciences, Tomsk 634014, Russia;
| | - Anna Usova
- Cancer Research Institute, Tomsk National Research Medical Center of the Russian Academy of Sciences, 12/1 Savinykh St., Tomsk 634009, Russia;
| | - Marina Kudabaeva
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (M.S.); (A.N.); (M.K.); (T.A.); (I.W.); (N.K.); (A.L.); (Y.T.)
| | - Tatyana Anan’ina
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (M.S.); (A.N.); (M.K.); (T.A.); (I.W.); (N.K.); (A.L.); (Y.T.)
| | - Irina Wasserlauf
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (M.S.); (A.N.); (M.K.); (T.A.); (I.W.); (N.K.); (A.L.); (Y.T.)
| | - Valentina Pashkevich
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (M.S.); (A.N.); (M.K.); (T.A.); (I.W.); (N.K.); (A.L.); (Y.T.)
| | - Marina Moshkina
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (M.S.); (A.N.); (M.K.); (T.A.); (I.W.); (N.K.); (A.L.); (Y.T.)
| | - Victoria Obukhovskaya
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (M.S.); (A.N.); (M.K.); (T.A.); (I.W.); (N.K.); (A.L.); (Y.T.)
- Department of Fundamental Psychology and Behavioral Medicine, Siberian State Medical University, 2 Moskovskiy Trakt, Tomsk 634050, Russia
| | - Nadezhda Kataeva
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (M.S.); (A.N.); (M.K.); (T.A.); (I.W.); (N.K.); (A.L.); (Y.T.)
- Department of Neurology and Neurosurgery, Siberian State Medical University, 2 Moskovskiy Trakt, Tomsk 634050, Russia
| | - Anastasia Levina
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (M.S.); (A.N.); (M.K.); (T.A.); (I.W.); (N.K.); (A.L.); (Y.T.)
- Medica Diagnostic and Treatment Center, 86 Sovetskaya st., Tomsk 634510, Russia
| | - Yana Tumentceva
- Laboratory of Neurobiology, Research Institute of Biology and Biophysics, Tomsk State University, 36 Lenina Ave., Tomsk 634050, Russia; (M.S.); (A.N.); (M.K.); (T.A.); (I.W.); (N.K.); (A.L.); (Y.T.)
| | - Vasily Yarnykh
- Department of Radiology, University of Washington, 850 Republican Street, Seattle, WA 98109, USA
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Soustelle L, Troalen T, Hertanu A, Ranjeva JP, Guye M, Varma G, Alsop DC, Duhamel G, Girard OM. Quantitative magnetization transfer MRI unbiased by on-resonance saturation and dipolar order contributions. Magn Reson Med 2023. [PMID: 37154400 DOI: 10.1002/mrm.29678] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 03/22/2023] [Accepted: 04/01/2023] [Indexed: 05/10/2023]
Abstract
PURPOSE To demonstrate the bias in quantitative MT (qMT) measures introduced by the presence of dipolar order and on-resonance saturation (ONRS) effects using magnetization transfer (MT) spoiled gradient-recalled (SPGR) acquisitions, and propose changes to the acquisition and analysis strategies to remove these biases. METHODS The proposed framework consists of SPGR sequences prepared with simultaneous dual-offset frequency-saturation pulses to cancel out dipolar order and associated relaxation (T1D ) effects in Z-spectrum acquisitions, and a matched quantitative MT (qMT) mathematical model that includes ONRS effects of readout pulses. Variable flip angle and MT data were fitted jointly to simultaneously estimate qMT parameters (macromolecular proton fraction [MPF], T2,f , T2,b , R, and free pool T1 ). This framework is compared with standard qMT and investigated in terms of reproducibility, and then further developed to follow a joint single-point qMT methodology for combined estimation of MPF and T1 . RESULTS Bland-Altman analyses demonstrated a systematic underestimation of MPF (-2.5% and -1.3%, on average, in white and gray matter, respectively) and overestimation of T1 (47.1 ms and 38.6 ms, on average, in white and gray matter, respectively) if both ONRS and dipolar order effects are ignored. Reproducibility of the proposed framework is excellent (ΔMPF = -0.03% and ΔT1 = -19.0 ms). The single-point methodology yielded consistent MPF and T1 values with respective maximum relative average bias of -0.15% and -3.5 ms found in white matter. CONCLUSION The influence of acquisition strategy and matched mathematical model with regard to ONRS and dipolar order effects in qMT-SPGR frameworks has been investigated. The proposed framework holds promise for improved accuracy with reproducibility.
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Affiliation(s)
- Lucas Soustelle
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | | | - Andreea Hertanu
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - Jean-Philippe Ranjeva
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - Maxime Guye
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - Gopal Varma
- Division of MR Research, Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - David C Alsop
- Division of MR Research, Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Guillaume Duhamel
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - Olivier M Girard
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France
- APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
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Hertanu A, Soustelle L, Buron J, Le Priellec J, Cayre M, Le Troter A, Prevost VH, Ranjeva JP, Varma G, Alsop DC, Durbec P, Girard OM, Duhamel G. Inhomogeneous Magnetization Transfer (ihMT) imaging in the acute cuprizone mouse model of demyelination/remyelination. Neuroimage 2023; 265:119785. [PMID: 36464096 DOI: 10.1016/j.neuroimage.2022.119785] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2022] [Revised: 10/31/2022] [Accepted: 12/01/2022] [Indexed: 12/05/2022] Open
Abstract
BACKGROUND To investigate the association of ihMT (inhom signals with the demyelination and remyelination phases of the acute cuprizone mouse model in comparison with histology, and to assess the extent of tissue damage and repair from MRI data. METHODS Acute demyelination by feeding 0.2% cuprizone for five weeks, followed by a four-week remyelination period was applied on genetically modified plp-GFP mice. Animals were scanned at different time points of the demyelination and remyelination phases of the cuprizone model using a multimodal MRI protocol, including ihMT T1D-filters, MPF (Macromolecular Proton Fraction) and R1 (longitudinal relaxation rate). For histology, plp-GFP (proteolipid protein - Green Fluorescent Protein) microscopy and LFB (Luxol Fast Blue) staining were employed as references for the myelin content. Comparison of MRI with histology was performed in the medial corpus callosum (mCC) and cerebral cortex (CTX) at two brain levels whereas ROI-wise and voxel-based analyses of the MRI metrics allowed investigating in vivo the spatial extent of myelin alterations. RESULTS IhMT high-pass T1D-filters, targeted toward long T1D components, showed significant temporal variations in the mCC consistent with the effects induced by the cuprizone toxin. In addition, the corresponding signals correlated strongly and significantly with the myelin content assessed by GFP fluorescence and LFB staining over the demyelination and the remyelination phases. The signal of the band-pass T1D-filter, which isolates short T1D components, showed changes over time that were poorly correlated with histology, hence suggesting a sensitivity to pathological processes possibly not related to myelin. Although MPF was also highly correlated to histology, ihMT high-pass T1D-filters showed better capability to characterize the spatial-temporal patterns during the demyelination and remyelination phases of the acute cuprizone model (e.g., rostro-caudal gradient of demyelination in the mCC previously described in the literature). CONCLUSIONS IhMT sequences selective for long T1D components are specific and sensitive in vivo markers of demyelination and remyelination and have successfully captured the spatially heterogeneous pattern of the demyelination and remyelination mechanisms in the cuprizone model. Interestingly, differences in signal variations between the ihMT high-pass and band-pass T1D-filter, suggest a sensitivity of the ihMT sequences targeted to short T1Ds to alterations other than those of myelin. Future studies will need to further address these differences by examining more closely the origin of the short T1D components and the variation of each T1D component in pathology.
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Weiss Y, Huber E, Ferjan Ramírez N, Corrigan NM, Yarnykh VL, Kuhl PK. Language input in late infancy scaffolds emergent literacy skills and predicts reading related white matter development. Front Hum Neurosci 2022; 16:922552. [PMID: 36457757 PMCID: PMC9705348 DOI: 10.3389/fnhum.2022.922552] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Accepted: 10/26/2022] [Indexed: 11/17/2022] Open
Abstract
Longitudinal studies provide the unique opportunity to test whether early language provides a scaffolding for the acquisition of the ability to read. This study tests the hypothesis that parental language input during the first 2 years of life predicts emergent literacy skills at 5 years of age, and that white matter development observed early in the 3rd year (at 26 months) may help to account for these effects. We collected naturalistic recordings of parent and child language at 6, 10, 14, 18, and 24 months using the Language ENvironment Analysis system (LENA) in a group of typically developing infants. We then examined the relationship between language measures during infancy and follow-up measures of reading related skills at age 5 years, in the same group of participants (N = 53). A subset of these children also completed diffusion and quantitative MRI scans at age 2 years (N = 20). Within this subgroup, diffusion tractography was used to identify white matter pathways that are considered critical to language and reading development, namely, the arcuate fasciculus (AF), superior and inferior longitudinal fasciculi, and inferior occipital-frontal fasciculus. Quantitative macromolecular proton fraction (MPF) mapping was used to characterize myelin density within these separately defined regions of interest. The longitudinal data were then used to test correlations between early language input and output, white matter measures at age 2 years, and pre-literacy skills at age 5 years. Parental language input, child speech output, and parent-child conversational turns correlated with pre-literacy skills, as well as myelin density estimates within the left arcuate and superior longitudinal fasciculus. Mediation analyses indicated that the left AF accounted for longitudinal relationships between infant home language measures and 5-year letter identification and letter-sound knowledge, suggesting that the left AF myelination at 2 years may serve as a mechanism by which early language experience supports emergent literacy.
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Affiliation(s)
- Yael Weiss
- Institute for Learning and Brain Sciences, University of Washington, Seattle, WA, United States
- Department of Speech and Hearing Sciences, University of Washington, Seattle, WA, United States
| | - Elizabeth Huber
- Institute for Learning and Brain Sciences, University of Washington, Seattle, WA, United States
- Department of Speech and Hearing Sciences, University of Washington, Seattle, WA, United States
| | - Naja Ferjan Ramírez
- Institute for Learning and Brain Sciences, University of Washington, Seattle, WA, United States
- Department of Linguistics, University of Washington, Seattle, WA, United States
| | - Neva M. Corrigan
- Institute for Learning and Brain Sciences, University of Washington, Seattle, WA, United States
- Department of Speech and Hearing Sciences, University of Washington, Seattle, WA, United States
| | - Vasily L. Yarnykh
- Department of Radiology, University of Washington, Seattle, WA, United States
| | - Patricia K. Kuhl
- Institute for Learning and Brain Sciences, University of Washington, Seattle, WA, United States
- Department of Speech and Hearing Sciences, University of Washington, Seattle, WA, United States
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Corrigan NM, Yarnykh VL, Huber E, Zhao TC, Kuhl PK. Brain myelination at 7 months of age predicts later language development. Neuroimage 2022; 263:119641. [PMID: 36170763 PMCID: PMC10038938 DOI: 10.1016/j.neuroimage.2022.119641] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Revised: 08/24/2022] [Accepted: 09/19/2022] [Indexed: 11/17/2022] Open
Abstract
Between 6 and 12 months of age there are dramatic changes in infants' processing of language. The neurostructural underpinnings of these changes are virtually unknown. The objectives of this study were to (1) examine changes in brain myelination during this developmental period and (2) examine the relationship between myelination during this period and later language development. Macromolecular proton fraction (MPF) was used as a marker of myelination. Whole-brain MPF maps were obtained with 1.25 mm3 isotropic spatial resolution from typically developing children at 7 and 11 months of age. Effective myelin density was calculated from MPF based on a linear relationship known from the literature. Voxel-based analyses were used to identify longitudinal changes in myelin density and to calculate correlations between myelin density at these ages and later language development. Increases in myelin density were more predominant in white matter than in gray matter. A strong predictive relationship was found between myelin density at 7 months of age, language production at 24 and 30 months of age, and rate of language growth. No relationships were found between myelin density at 11 months, or change in myelin density between 7 and 11 months of age, and later language measures. Our findings suggest that critical changes in brain structure may precede periods of pronounced change in early language skills.
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Affiliation(s)
- Neva M Corrigan
- Institute for Learning & Brain Sciences, University of Washington, Seattle, WA 98195, USA; Department of Speech and Hearing Sciences, University of Washington, Seattle, WA 98195, USA.
| | - Vasily L Yarnykh
- Department of Radiology, University of Washington, Seattle, WA 98195, USA
| | - Elizabeth Huber
- Institute for Learning & Brain Sciences, University of Washington, Seattle, WA 98195, USA; Department of Speech and Hearing Sciences, University of Washington, Seattle, WA 98195, USA
| | - T Christina Zhao
- Institute for Learning & Brain Sciences, University of Washington, Seattle, WA 98195, USA; Department of Speech and Hearing Sciences, University of Washington, Seattle, WA 98195, USA
| | - Patricia K Kuhl
- Institute for Learning & Brain Sciences, University of Washington, Seattle, WA 98195, USA; Department of Speech and Hearing Sciences, University of Washington, Seattle, WA 98195, USA
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Kisel AA, Naumova AV, Yarnykh VL. Macromolecular Proton Fraction as a Myelin Biomarker: Principles, Validation, and Applications. Front Neurosci 2022; 16:819912. [PMID: 35221905 PMCID: PMC8863973 DOI: 10.3389/fnins.2022.819912] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Accepted: 01/17/2022] [Indexed: 12/16/2022] Open
Abstract
Macromolecular proton fraction (MPF) is a quantitative MRI parameter describing the magnetization transfer (MT) effect and defined as a relative amount of protons bound to biological macromolecules with restricted molecular motion, which participate in magnetic cross-relaxation with water protons. MPF attracted significant interest during past decade as a biomarker of myelin. The purpose of this mini review is to provide a brief but comprehensive summary of MPF mapping methods, histological validation studies, and MPF applications in neuroscience. Technically, MPF maps can be obtained using a variety of quantitative MT methods. Some of them enable clinically reasonable scan time and resolution. Recent studies demonstrated the feasibility of MPF mapping using standard clinical MRI pulse sequences, thus substantially enhancing the method availability. A number of studies in animal models demonstrated strong correlations between MPF and histological markers of myelin with a minor influence of potential confounders. Histological studies validated the capability of MPF to monitor both demyelination and re-myelination. Clinical applications of MPF have been mainly focused on multiple sclerosis where this method provided new insights into both white and gray matter pathology. Besides, several studies used MPF to investigate myelin role in other neurological and psychiatric conditions. Another promising area of MPF applications is the brain development studies. MPF demonstrated the capabilities to quantitatively characterize the earliest stage of myelination during prenatal brain maturation and protracted myelin development in adolescence. In summary, MPF mapping provides a technically mature and comprehensively validated myelin imaging technology for various preclinical and clinical neuroscience applications.
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Affiliation(s)
- Alena A. Kisel
- Department of Radiology, University of Washington, Seattle, WA, United States
- Laboratory of Neurobiology, Tomsk State University, Tomsk, Russia
| | - Anna V. Naumova
- Department of Radiology, University of Washington, Seattle, WA, United States
| | - Vasily L. Yarnykh
- Department of Radiology, University of Washington, Seattle, WA, United States
- Laboratory of Neurobiology, Tomsk State University, Tomsk, Russia
- *Correspondence: Vasily L. Yarnykh,
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Yarnykh VL, Korostyshevskaya AM, Savelov AA, Isaeva YO, Gornostaeva AM, Tulupov AA, Sagdeev RZ. Macromolecular proton fraction mapping in magnetic resonance imaging: physicochemical principles and biomedical applications. Russ Chem Bull 2022. [DOI: 10.1007/s11172-021-3343-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Hertanu A, Soustelle L, Buron J, Le Priellec J, Cayre M, Le Troter A, Varma G, Alsop DC, Durbec P, Girard OM, Duhamel G. T 1D -weighted ihMT imaging - Part II. Investigating the long- and short-T 1D components correlation with myelin content. Comparison with R 1 and the macromolecular proton fraction. Magn Reson Med 2022; 87:2329-2346. [PMID: 35001427 DOI: 10.1002/mrm.29140] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 10/29/2021] [Accepted: 12/12/2021] [Indexed: 12/22/2022]
Abstract
PURPOSE To investigate the long- and short-T1D components correlation with myelin content using inhomogeneous magnetization transfer (ihMT) high-pass and band-pass T1D -filters and to compare ihMT, R1 , and the macromolecular proton fraction (MPF) for myelin specific imaging. METHODS The 3D ihMT rapid gradient echo (ihMTRAGE) sequences with increasing switching times (Δt) were used to derive ihMT high-pass T1D -filters with increasing T1D cutoff values and an ihMT band-pass T1D -filter for components in the 100 µs to 1 ms range. 3D spoiled gradient echo quantitative MT (SPGR-qMT) protocols were used to derive R1 and MPF maps. The specificity of R1 , MPF, and ihMT T1D -filters was evaluated by comparison with two histological reference techniques for myelin imaging. RESULTS The higher contribution of long-T1D s as compared to the short components as Δt got longer led to an increase in the specificity to myelination. In contrast, focusing on the signal originating from a narrow range of short-T1D s (< 1 ms) as isolated by the band-pass T1D -filter led to lower specificity. In addition, the significantly lower r2 correlation coefficient of the band-pass T1D -filter suggests that the origin of short-T1D components is mostly associated with non-myelin protons. Also, the important contribution of short-T1D s to the estimated MPF, explains its low specificity to myelination as compared to the ihMT high-pass T1D -filters. CONCLUSION Long-T1D components imaging by means of ihMT high-pass T1D -filters is proposed as an MRI biomarker for myelin content. Future studies should enable the investigation of the sensitivity of ihMT T1D -filters for demyelinating processes.
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Affiliation(s)
- Andreea Hertanu
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France.,APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - Lucas Soustelle
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France.,APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - Julie Buron
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France.,APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France.,Aix Marseille Univ, CNRS, IBDM, Marseille, France
| | | | - Myriam Cayre
- Aix Marseille Univ, CNRS, IBDM, Marseille, France
| | - Arnaud Le Troter
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France.,APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - Gopal Varma
- Division of MR Research, Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - David C Alsop
- Division of MR Research, Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | | | - Olivier M Girard
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France.,APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - Guillaume Duhamel
- Aix Marseille Univ, CNRS, CRMBM, Marseille, France.,APHM, Hôpital Universitaire Timone, CEMEREM, Marseille, France
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Yarnykh VL. Data-Driven Retrospective Correction of B 1 Field Inhomogeneity in Fast Macromolecular Proton Fraction and R 1 Mapping. IEEE Trans Med Imaging 2021; 40:3473-3484. [PMID: 34110989 PMCID: PMC8711232 DOI: 10.1109/tmi.2021.3088258] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
Correction of B1 field non-uniformity is critical for many quantitative MRI methods including variable flip angle (VFA) T1 mapping and single-point macromolecular proton fraction (MPF) mapping. The latter method showed promising results as a fast and robust quantitative myelin imaging approach and involves VFA-based R1=1/T1 map reconstruction as an intermediate processing step. The need for B1 correction restricts applications of the above methods, since B1 mapping sequences increase the examination time and are not commonly available in clinics. A new algorithm was developed to enable retrospective data-driven simultaneous B1 correction in VFA R1 and single-point MPF mapping. The principle of the algorithm is based on different mathematical dependences of B1 -related errors in R1 and MPF allowing extraction of a surrogate B1 field map from uncorrected R1 and MPF maps. To validate the method, whole-brain R1 and MPF maps with isotropic 1.25 mm3 resolution were obtained on a 3 T MRI scanner from 11 volunteers. Mean parameter values in segmented brain tissues were compared between three reconstruction options including the absence of correction, actual B1 correction, and surrogate B1 correction. Surrogate B1 maps closely reproduced actual patterns of B1 inhomogeneity. Without correction, B1 non-uniformity caused highly significant biases in R1 and MPF ( ). Surrogate B1 field correction reduced the biases in both R1 and MPF to a non-significant level ( 0.1 ≤ P ≤ 0.8 ). The described algorithm obviates the use of dedicated B1 mapping sequences in fast single-point MPF mapping and provides an alternative solution for correction of B1 non-uniformities in VFA R1 mapping.
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Khodanovich MY, Gubskiy IL, Kudabaeva MS, Namestnikova DD, Kisel AA, Anan’ina TV, Tumentceva YA, Mustafina LR, Yarnykh VL. Long-term monitoring of chronic demyelination and remyelination in a rat ischemic stroke model using macromolecular proton fraction mapping. J Cereb Blood Flow Metab 2021; 41:2856-2869. [PMID: 34107787 PMCID: PMC8756474 DOI: 10.1177/0271678x211020860] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 04/24/2021] [Accepted: 04/26/2021] [Indexed: 12/23/2022]
Abstract
Remyelination is a key process enabling post-stroke brain tissue recovery and plasticity. This study aimed to explore the feasibility of demyelination and remyelination monitoring in experimental stroke from the acute to chronic stage using an emerging myelin imaging biomarker, macromolecular proton fraction (MPF). After stroke induction by transient middle cerebral artery occlusion, rats underwent repeated MRI examinations during 85 days after surgery with histological endpoints for the animal subgroups on the 7th, 21st, 56th, and 85th days. MPF maps revealed two sub-regions within the infarct characterized by distinct temporal profiles exhibiting either a persistent decrease by 30%-40% or a transient decrease followed by return to nearly normal values after one month of observation. Myelin histology confirmed that these sub-regions had nearly similar extent of demyelination in the sub-acute phase and then demonstrated either chronic demyelination or remyelination. The remyelination zones also exhibited active axonal regrowth, reconstitution of compact fiber bundles, and proliferation of neuronal and oligodendroglial precursors. The demyelination zones showed more extensive astrogliosis from the 21st day endpoint. Both sub-regions had substantially depleted neuronal population over all endpoints. These results histologically validate MPF mapping as a novel approach for quantitative assessment of myelin damage and repair in ischemic stroke.
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Affiliation(s)
| | - Ilya L Gubskiy
- Research Institute of Cerebrovascular Pathology and Stroke, Pirogov Russian Medical University, Moscow, Russian Federation
| | - Marina S Kudabaeva
- Laboratory of Neurobiology, Tomsk State University, Tomsk, Russian Federation
| | - Darya D Namestnikova
- Research Institute of Cerebrovascular Pathology and Stroke, Pirogov Russian Medical University, Moscow, Russian Federation
| | - Alena A Kisel
- Laboratory of Neurobiology, Tomsk State University, Tomsk, Russian Federation
- Department of Radiology, University of Washington, Seattle, USA
| | - Tatyana V Anan’ina
- Laboratory of Neurobiology, Tomsk State University, Tomsk, Russian Federation
| | - Yana A Tumentceva
- Laboratory of Neurobiology, Tomsk State University, Tomsk, Russian Federation
| | - Lilia R Mustafina
- Department of histology, embriology, and cytology, Siberian State Medical University, Tomsk, Russian Federation
| | - Vasily L Yarnykh
- Laboratory of Neurobiology, Tomsk State University, Tomsk, Russian Federation
- Department of Radiology, University of Washington, Seattle, USA
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11
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Smirnova LP, Yarnykh VL, Parshukova DA, Kornetova EG, Semke AV, Usova AV, Pishchelko AO, Khodanovich MY, Ivanova SA. Global hypomyelination of the brain white and gray matter in schizophrenia: quantitative imaging using macromolecular proton fraction. Transl Psychiatry 2021; 11:365. [PMID: 34226491 DOI: 10.1038/s41398-021-01475-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/24/2020] [Revised: 05/08/2021] [Accepted: 05/17/2021] [Indexed: 02/06/2023] Open
Abstract
Myelin deficiency is commonly recognized as an important pathological feature of brain tissues in schizophrenia (SZ). In this pilot study, global myelin content abnormalities in white matter (WM) and gray matter (GM) of SZ patients were non-invasively investigated using a novel clinically-targeted quantitative myelin imaging technique, fast macromolecular proton fraction (MPF) mapping. MPF maps were obtained from 23 healthy subjects and 31 SZ patients using a clinical 1.5T magnetic resonance imaging (MRI) scanner. Mean MPF in WM and GM was compared between the healthy control subjects and SZ patients with positive and negative leading symptoms using the multivariate analysis of covariance. The SZ patients had significantly reduced MPF in GM (p < 0.001) and WM (p = 0.02) with the corresponding relative decrease of 5% and 3%, respectively. The effect sizes for the myelin content loss in SZ relative to the control group were 1.0 and 1.5 for WM and GM, respectively. The SZ patients with leading negative symptoms had significantly lower MPF in GM (p < 0.001) and WM (p = 0.003) as compared to the controls and showed a significant MPF decrease in WM (p = 0.03) relative to the patients with leading positive symptoms. MPF in WM significantly negatively correlated with the disease duration in SZ patients (Pearson's r = -0.51; p = 0.004). This study demonstrates that chronic SZ is characterized by global microscopic brain hypomyelination of both WM and GM, which is associated with the disease duration and negative symptoms. Myelin deficiency in SZ can be detected and quantified by the fast MPF mapping method.
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12
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Corrigan NM, Yarnykh VL, Hippe DS, Owen JP, Huber E, Zhao TC, Kuhl PK. Myelin development in cerebral gray and white matter during adolescence and late childhood. Neuroimage 2020; 227:117678. [PMID: 33359342 PMCID: PMC8214999 DOI: 10.1016/j.neuroimage.2020.117678] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Revised: 12/14/2020] [Accepted: 12/15/2020] [Indexed: 01/07/2023] Open
Abstract
Myelin development during adolescence is becoming an area of growing interest in view of its potential relationship to cognition, behavior, and learning. While recent investigations suggest that both white matter (WM) and gray matter (GM) undergo protracted myelination during adolescence, quantitative relations between myelin development in WM and GM have not been previously studied. We quantitatively characterized the dependence of cortical GM, WM, and subcortical myelin density across the brain on age, gender, and puberty status during adolescence with the use of a novel macromolecular proton fraction (MPF) mapping method. Whole-brain MPF maps from a cross-sectional sample of 146 adolescents (age range 9–17 years) were collected. Myelin density was calculated from MPF values in GM and WM of all brain lobes, as well as in subcortical structures. In general, myelination of cortical GM was widespread and more significantly correlated with age than that of WM. Myelination of GM in the parietal lobe was found to have a significantly stronger age dependence than that of GM in the frontal, occipital, temporal and insular lobes. Myelination of WM in the temporal lobe had the strongest association with age as compared to WM in other lobes. Myelin density was found to be higher in males as compared to females when averaged across all cortical lobes, as well as in a bilateral subcortical region. Puberty stage was significantly correlated with myelin density in several cortical areas and in the subcortical GM. These findings point to significant differences in the trajectories of myelination of GM and WM across brain regions and suggest that cortical GM myelination plays a dominant role during adolescent development.
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Affiliation(s)
- Neva M Corrigan
- Institute for Learning & Brain Sciences, University of Washington, Box 357988, Portage Bay Building, Seattle WA 98195, United States.
| | - Vasily L Yarnykh
- Department of Radiology, University of Washington, Seattle WA 98195, United States
| | - Daniel S Hippe
- Department of Radiology, University of Washington, Seattle WA 98195, United States
| | - Julia P Owen
- Department of Radiology, University of Washington, Seattle WA 98195, United States
| | - Elizabeth Huber
- Institute for Learning & Brain Sciences, University of Washington, Box 357988, Portage Bay Building, Seattle WA 98195, United States
| | - T Christina Zhao
- Institute for Learning & Brain Sciences, University of Washington, Box 357988, Portage Bay Building, Seattle WA 98195, United States
| | - Patricia K Kuhl
- Institute for Learning & Brain Sciences, University of Washington, Box 357988, Portage Bay Building, Seattle WA 98195, United States
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13
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Cooper G, Hirsch S, Scheel M, Brandt AU, Paul F, Finke C, Boehm-Sturm P, Hetzer S. Quantitative Multi-Parameter Mapping Optimized for the Clinical Routine. Front Neurosci 2020; 14:611194. [PMID: 33364921 PMCID: PMC7750476 DOI: 10.3389/fnins.2020.611194] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Accepted: 11/16/2020] [Indexed: 12/12/2022] Open
Abstract
Using quantitative multi-parameter mapping (MPM), studies can investigate clinically relevant microstructural changes with high reliability over time and across subjects and sites. However, long acquisition times (20 min for the standard 1-mm isotropic protocol) limit its translational potential. This study aimed to evaluate the sensitivity gain of a fast 1.6-mm isotropic MPM protocol including post-processing optimized for longitudinal clinical studies. 6 healthy volunteers (35±7 years old; 3 female) were scanned at 3T to acquire the following whole-brain MPM maps with 1.6 mm isotropic resolution: proton density (PD), magnetization transfer saturation (MT), longitudinal relaxation rate (R1), and transverse relaxation rate (R2*). MPM maps were generated using two RF transmit field (B1+) correction methods: (1) using an acquired B1+ map and (2) using a data-driven approach. Maps were generated with and without Gibb's ringing correction. The intra-/inter-subject coefficient of variation (CoV) of all maps in the gray and white matter, as well as in all anatomical regions of a fine-grained brain atlas, were compared between the different post-processing methods using Student's t-test. The intra-subject stability of the 1.6-mm MPM protocol is 2–3 times higher than for the standard 1-mm sequence and can be achieved in less than half the scan duration. Intra-subject variability for all four maps in white matter ranged from 1.2–5.3% and in gray matter from 1.8 to 9.2%. Bias-field correction using an acquired B1+ map significantly improved intra-subject variability of PD and R1 in the gray (42%) and white matter (54%) and correcting the raw images for the effect of Gibb's ringing further improved intra-subject variability in all maps in the gray (11%) and white matter (10%). Combining Gibb's ringing correction and bias field correction using acquired B1+ maps provides excellent stability of the 7-min MPM sequence with 1.6 mm resolution suitable for the clinical routine.
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Affiliation(s)
- Graham Cooper
- Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany.,NeuroCure Clinical Research Center, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health Berlin, Berlin, Germany.,Einstein Center for Neurosciences Berlin, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.,Department of Experimental Neurology and Center for Stroke Research Berlin, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Sebastian Hirsch
- Berlin Center for Advanced Neuroimaging, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health Berlin, Berlin, Germany.,Bernstein Center for Computational Neuroscience, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Michael Scheel
- NeuroCure Clinical Research Center, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health Berlin, Berlin, Germany.,Department of Neuroradiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health Berlin, Berlin, Germany
| | - Alexander U Brandt
- NeuroCure Clinical Research Center, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health Berlin, Berlin, Germany.,Department of Neurology, University of California, Irvine, Irvine, CA, United States
| | - Friedemann Paul
- Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Berlin, Germany.,NeuroCure Clinical Research Center, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health Berlin, Berlin, Germany.,Einstein Center for Neurosciences Berlin, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.,Department of Neurology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health Berlin, Berlin, Germany
| | - Carsten Finke
- Einstein Center for Neurosciences Berlin, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.,Department of Neurology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health Berlin, Berlin, Germany.,Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Philipp Boehm-Sturm
- Department of Experimental Neurology and Center for Stroke Research Berlin, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.,NeuroCure Cluster of Excellence and Charité Core Facility 7T Experimental MRIs, Charité Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health Berlin, Berlin, Germany
| | - Stefan Hetzer
- Berlin Center for Advanced Neuroimaging, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health Berlin, Berlin, Germany.,Bernstein Center for Computational Neuroscience, Humboldt-Universität zu Berlin, Berlin, Germany
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14
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Soustelle L, Antal MC, Lamy J, Harsan LA, Loureiro de Sousa P. Determination of optimal parameters for 3D single-point macromolecular proton fraction mapping at 7T in healthy and demyelinated mouse brain. Magn Reson Med 2020; 85:369-379. [PMID: 32767495 DOI: 10.1002/mrm.28397] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Revised: 06/05/2020] [Accepted: 06/05/2020] [Indexed: 12/19/2022]
Abstract
PURPOSE To determine optimal constrained tissue parameters and off-resonance sequence parameters for single-point macromolecular proton fraction (SP-MPF) mapping based on a comprehensive quantitative magnetization transfer (qMT) protocol in healthy and demyelinated living mice at 7T. METHODS Using 3D spoiled gradient echo-based sequences, a comprehensive qMT protocol is performed by sampling the Z-spectrum of mice brains, in vivo. Provided additional T1 , B 1 + and B0 maps allow for the estimation of qMT tissue parameters, among which three will be constrained, namely the longitudinal and transverse relaxation characteristics of the free pool (R1,f T2,f ), the cross-relaxation rate (R) and the bound pool transverse relaxation time (T2,r ). Different sets of constrained parameters are investigated to reduce the bias between the SP-MPF and its reference based on the comprehensive protocol. RESULTS Based on a whole-brain histogram analysis about the constrained parameters, the optimal experimental parameters that minimize the global bias between reference and SP-MPF maps consist of a 600° and 6 kHz off-resonance irradiation pulse. Following a Bland-Altman analysis over regions of interest, optimal constrained parameters were R1,f T2,f = 0.0129, R = 26.5 s-1 , and T2,r = 9.1 µs, yielding an overall MPF bias of 10-4 (limits of agreement [-0.0068;0.0070]) and a relative variation of 0.64% ± 5.95% between the reference and the optimal single-point method across all mice. CONCLUSION The necessity of estimating animal model- and field-dependent constrained parameters was demonstrated. The single-point MPF method can be reliably applied at 7T, as part of routine preclinical in vivo imaging protocol in mice.
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Affiliation(s)
- Lucas Soustelle
- ICube, Université de Strasbourg, CNRS, Strasbourg, France.,Aix Marseille University, CNRS, CRMBM, Marseille, France
| | | | - Julien Lamy
- ICube, Université de Strasbourg, CNRS, Strasbourg, France
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15
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Anisimov NV, Pavlova OS, Pirogov YA, Yarnykh VL. Three-dimensional fast single-point macromolecular proton fraction mapping of the human brain at 0.5 Tesla. Quant Imaging Med Surg 2020; 10:1441-1449. [PMID: 32676363 DOI: 10.21037/qims-19-1057] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Fast single-point macromolecular proton fraction (MPF) mapping is a recent magnetic resonance imaging (MRI) method enabling quantitative assessment of myelin content in neural tissues. To date, the reported technical implementations of MPF mapping utilized high-field MRI equipment (1.5 T or higher), while low-field applications might pose challenges due to signal-to-noise ratio (SNR) limitations and short T1 . This study aimed to evaluate the feasibility of MPF mapping of the human brain at 0.5 T. The three-dimensional MPF mapping protocol was implemented according to the single-point synthetic-reference method, which includes three spoiled gradient-echo sequences providing proton density, T1 , and magnetization transfer contrast weightings. Whole-brain MPF maps were obtained from three healthy volunteers with spatial resolution of 1.5×1.5×2 mm3 and the total scan time of 19 minutes. MPF values were measured in a series of white and gray matter structures and compared with literature data for 3 T magnetic field. MPF maps enabled high contrast between white and gray matter with notable insensitivity to paramagnetic effects in iron-rich structures, such as globus pallidus, substantia nigra, and dentate nucleus. MPF values at 0.5 T appeared in close agreement with those at 3 T. This study demonstrates the feasibility of fast MPF mapping with low-field MRI equipment and the independence of brain MPF values of magnetic field. The presented results confirm the utility of MPF as an absolute scale for MRI-based myelin content measurements across a wide range of magnetic field strengths and extend the applicability of fast MPF mapping to inexpensive low-field MRI hardware.
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Affiliation(s)
- Nikolay V Anisimov
- Faculty of Fundamental Medicine, Lomonosov Moscow State University, 117192, Moscow, Lomonosovsky Prospekt, 31-5, Russian Federation
| | - Olga S Pavlova
- Faculty of Fundamental Medicine, Lomonosov Moscow State University, 117192, Moscow, Lomonosovsky Prospekt, 31-5, Russian Federation.,Faculty of Physics, Lomonosov Moscow State University, 119991, Moscow, GSP-1, Leninskie Gory, 1-2, Russian Federation
| | - Yury A Pirogov
- Faculty of Physics, Lomonosov Moscow State University, 119991, Moscow, GSP-1, Leninskie Gory, 1-2, Russian Federation.,Institute for Physical and Chemical Fundamentals of Artificial Intelligence, Lomonosov Moscow State University, 119991, Moscow, GSP-1, Leninskie Gory, 1-11, Russian Federation
| | - Vasily L Yarnykh
- Department of Radiology, University of Washington, Seattle, WA 98109, USA.,Research Institute of Biology and Biophysics, Tomsk State University, 634050, Tomsk, Russian Federation
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16
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Boudreau M. Editorial for "Scan-Rescan Repeatability and Impact of B 0 and B 1 Field Nonuniformity Corrections in Single-Point Whole-Brain Macromolecular Proton Fraction Mapping". J Magn Reson Imaging 2020; 52:954-955. [PMID: 32045068 DOI: 10.1002/jmri.27088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2020] [Accepted: 01/27/2020] [Indexed: 11/07/2022] Open
Affiliation(s)
- Mathieu Boudreau
- Montreal Heart Institute, Université de Montreal, Montreal, Quebec, Canada.,NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Quebec, Canada
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