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Lancione M, Cencini M, Scaffei E, Cipriano E, Buonincontri G, Schulte RF, Pirkl CM, Buchignani B, Pasquariello R, Canapicchi R, Battini R, Biagi L, Tosetti M. Magnetic resonance fingerprinting-based myelin water fraction mapping for the assessment of white matter maturation and integrity in typical development and leukodystrophies. NMR IN BIOMEDICINE 2024; 37:e5114. [PMID: 38390667 DOI: 10.1002/nbm.5114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 01/10/2024] [Accepted: 01/11/2024] [Indexed: 02/24/2024]
Abstract
A quantitative biomarker for myelination, such as myelin water fraction (MWF), would boost the understanding of normative and pathological neurodevelopment, improving patients' diagnosis and follow-up. We quantified the fraction of a rapidly relaxing pool identified as MW using multicomponent three-dimensional (3D) magnetic resonance fingerprinting (MRF) to evaluate white matter (WM) maturation in typically developing (TD) children and alterations in leukodystrophies (LDs). We acquired DTI and 3D MRF-based R1, R2 and MWF data of 15 TD children and 17 LD patients (9 months-12.5 years old) at 1.5 T. We computed normative maturation curves in corpus callosum and corona radiata and performed WM tract profile analysis, comparing MWF with R1, R2 and fractional anisotropy (FA). Normative maturation curves demonstrated a steep increase for all tissue parameters in the first 3 years of age, followed by slower growth for MWF while R1, R2R2 and FA reached a plateau. Unlike FA, MWF values were similar for regions of interest (ROIs) with different degrees of axonal packing, suggesting independence from fiber bundle macro-organization and higher myelin specificity. Tract profile analysis indicated a specific spatial pattern of myelination in the major fiber bundles, consistent across subjects. LD were better distinguished from TD by MWF rather than FA, showing reduced MWF with respect to age-matched controls in both ROI-based and tract analysis. In conclusion, MRF-based MWF provides myelin-specific WM maturation curves and is sensitive to alteration due to LDs, suggesting its potential as a biomarker for WM disorders. As MRF allows fast simultaneous acquisition of relaxometry and MWF, it can represent a valuable diagnostic tool to study and follow up developmental WM disorders in children.
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Affiliation(s)
| | - Matteo Cencini
- Pisa Division, National Institute for Nuclear Physics (INFN), Pisa, Italy
| | | | - Emilio Cipriano
- IRCCS Stella Maris Foundation, Pisa, Italy
- Department of Physics, University of Pisa, Pisa, Italy
| | | | | | | | | | | | | | - Roberta Battini
- IRCCS Stella Maris Foundation, Pisa, Italy
- Department of Clinical and Experimental Medicine, Università di Pisa, Pisa, Italy
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Radunsky D, Solomon C, Stern N, Blumenfeld-Katzir T, Filo S, Mezer A, Karsa A, Shmueli K, Soustelle L, Duhamel G, Girard OM, Kepler G, Shrot S, Hoffmann C, Ben-Eliezer N. A comprehensive protocol for quantitative magnetic resonance imaging of the brain at 3 Tesla. PLoS One 2024; 19:e0297244. [PMID: 38820354 PMCID: PMC11142522 DOI: 10.1371/journal.pone.0297244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2023] [Accepted: 01/01/2024] [Indexed: 06/02/2024] Open
Abstract
Quantitative MRI (qMRI) has been shown to be clinically useful for numerous applications in the brain and body. The development of rapid, accurate, and reproducible qMRI techniques offers access to new multiparametric data, which can provide a comprehensive view of tissue pathology. This work introduces a multiparametric qMRI protocol along with full postprocessing pipelines, optimized for brain imaging at 3 Tesla and using state-of-the-art qMRI tools. The total scan time is under 50 minutes and includes eight pulse-sequences, which produce range of quantitative maps including T1, T2, and T2* relaxation times, magnetic susceptibility, water and macromolecular tissue fractions, mean diffusivity and fractional anisotropy, magnetization transfer ratio (MTR), and inhomogeneous MTR. Practical tips and limitations of using the protocol are also provided and discussed. Application of the protocol is presented on a cohort of 28 healthy volunteers and 12 brain regions-of-interest (ROIs). Quantitative values agreed with previously reported values. Statistical analysis revealed low variability of qMRI parameters across subjects, which, compared to intra-ROI variability, was x4.1 ± 0.9 times higher on average. Significant and positive linear relationship was found between right and left hemispheres' values for all parameters and ROIs with Pearson correlation coefficients of r>0.89 (P<0.001), and mean slope of 0.95 ± 0.04. Finally, scan-rescan stability demonstrated high reproducibility of the measured parameters across ROIs and volunteers, with close-to-zero mean difference and without correlation between the mean and difference values (across map types, mean P value was 0.48 ± 0.27). The entire quantitative data and postprocessing scripts described in the manuscript are publicly available under dedicated GitHub and Figshare repositories. The quantitative maps produced by the presented protocol can promote longitudinal and multi-center studies, and improve the biological interpretability of qMRI by integrating multiple metrics that can reveal information, which is not apparent when examined using only a single contrast mechanism.
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Affiliation(s)
- Dvir Radunsky
- Department of Biomedical Engineering, Tel-Aviv University, Tel Aviv, Israel
| | - Chen Solomon
- Department of Biomedical Engineering, Tel-Aviv University, Tel Aviv, Israel
| | - Neta Stern
- Department of Biomedical Engineering, Tel-Aviv University, Tel Aviv, Israel
| | | | - Shir Filo
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Aviv Mezer
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Anita Karsa
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Karin Shmueli
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | | | | | | | - Gal Kepler
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
- School of Neurobiology, Biochemistry and Biophysics, Faculty of Life Science, Tel Aviv University, Tel Aviv, Israel
| | - Shai Shrot
- Sackler School of Medicine, Tel-Aviv University, Tel-Aviv, Israel
- Department of Diagnostic Imaging, Sheba Medical Center, Ramat-Gan, Israel
| | - Chen Hoffmann
- Sackler School of Medicine, Tel-Aviv University, Tel-Aviv, Israel
- Department of Diagnostic Imaging, Sheba Medical Center, Ramat-Gan, Israel
| | - Noam Ben-Eliezer
- Department of Biomedical Engineering, Tel-Aviv University, Tel Aviv, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
- Center for Advanced Imaging Innovation and Research (CAI2R), New-York University Langone Medical Center, New York, NY, United States of America
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3
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Lapidaire W, Clayden JD, Fewtrell MS, Clark CA. Increased white matter fibre dispersion and lower IQ scores in adults born preterm. Hum Brain Mapp 2024; 45:e26545. [PMID: 38070181 PMCID: PMC10789207 DOI: 10.1002/hbm.26545] [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: 08/22/2023] [Revised: 11/08/2023] [Accepted: 11/13/2023] [Indexed: 01/16/2024] Open
Abstract
Preterm birth has been associated with altered microstructural properties of the white matter and lower cognitive ability in childhood and adulthood. Due to methodological limitations of the diffusion tensor model, it is not clear whether alterations in myelination or variation in fibre orientation are driving these differences. Novel models applied to multi-shell diffusion imaging have been used to disentangle these effects, but to date this has not been used to study the preterm brain in adulthood. This study investigated whether novel advanced diffusion MRI metrics such as microscopic anisotropy and orientation dispersion are altered in adults born preterm, and whether this was associated with cognitive performance. Seventy-two preterm born participants (<37 weeks gestational age) were recruited from a 1982-1984 cohort (33 males, mean age 33.5 ± 1.0 years). Seventy-two term born (>37 weeks gestational age) controls (34 males, mean age 30.9 ± 4.0 years) were recruited from the general population. Tensor FA was calculated with FSL, while microscopic FA and orientation dispersion entropy (ODE) were estimated using the Spherical Mean Technique (SMT). Estimated Full Scale IQ (FSIQ), Verbal Comprehension Index (VCI) and Perceptual Reasoning Index (PRI) were obtained from the WASI-II (abbreviated) IQ test. Voxel-wise comparisons using FSL's tract-based spatial statistics were performed to test between-group differences in diffusion MRI metrics as well as within-group associations of diffusion MRI metrics and IQ outcomes. The preterm group had significantly lower FSIQ, VCI and PRI scores. Preterm subjects demonstrated widespread decreases in ODE reflecting increased fibre dispersion, but no differences in microscopic FA. Tensor FA was increased in a small area in the anterior corona radiata. Lower FA values in the preterm population were associated with lower FSIQ and PRI scores. An increase in fibre dispersion in white matter and lower IQ scores after preterm birth exist in adulthood. Advanced diffusion MRI metrics such as the orientation dispersion entropy can be used to monitor white matter alterations across the lifespan in preterm born individuals. Although not significantly different between preterm and term groups, tensor FA values in the preterm group were associated with cognitive outcome.
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Affiliation(s)
- Winok Lapidaire
- UCL Great Ormond Street Institute of Child HealthUniversity College LondonLondonUK
- Oxford Cardiovascular Clinical Research Facility, Division of Cardiovascular Medicine, Radcliffe Department of MedicineUniversity of Oxford, John Radcliffe HospitalOxfordUK
| | - Jonathan D. Clayden
- UCL Great Ormond Street Institute of Child HealthUniversity College LondonLondonUK
| | - Mary S. Fewtrell
- UCL Great Ormond Street Institute of Child HealthUniversity College LondonLondonUK
| | - Christopher A. Clark
- UCL Great Ormond Street Institute of Child HealthUniversity College LondonLondonUK
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4
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McNaughton R, Pieper C, Sakai O, Rollins JV, Zhang X, Kennedy DN, Frazier JA, Douglass L, Heeren T, Fry RC, O'Shea TM, Kuban KK, Jara H. Quantitative MRI Characterization of the Extremely Preterm Brain at Adolescence: Atypical versus Neurotypical Developmental Pathways. Radiology 2022; 304:419-428. [PMID: 35471112 PMCID: PMC9340244 DOI: 10.1148/radiol.210385] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Revised: 01/27/2022] [Accepted: 02/17/2022] [Indexed: 12/16/2022]
Abstract
Background Extremely preterm (EP) birth is associated with higher risks of perinatal white matter (WM) injury, potentially causing abnormal neurologic and neurocognitive outcomes. MRI biomarkers distinguishing individuals with and without neurologic disorder guide research on EP birth antecedents, clinical correlates, and prognoses. Purpose To compare multiparametric quantitative MRI (qMRI) parameters of EP-born adolescents with autism spectrum disorder, cerebral palsy, epilepsy, or cognitive impairment (ie, atypically developing) with those without (ie, neurotypically developing), characterizing sex-stratified brain development. Materials and Methods This prospective multicenter study included individuals aged 14-16 years born EP (Extremely Low Gestational Age Newborns-Environmental Influences on Child Health Outcomes Study, or ELGAN-ECHO). Participants underwent 3.0-T MRI evaluation from 2017 to 2019. qMRI outcomes were compared for atypically versus neurotypically developing adolescents and for girls versus boys. Sex-stratified multiple regression models were used to examine associations between spatial entropy density (SEd) and T1, T2, and cerebrospinal fluid (CSF)-normalized proton density (nPD), and between CSF volume and T2. Interaction terms modeled differences in slopes between atypically versus neurotypically developing adolescents. Results A total of 368 adolescents were classified as 116 atypically (66 boys) and 252 neurotypically developing (125 boys) participants. Atypically versus neurotypically developing girls had lower nPD (mean, 557 10 × percent unit [pu] ± 46 [SD] vs 573 10 × pu ± 43; P = .04), while atypically versus neurotypically developing boys had longer T1 (814 msec ± 57 vs 789 msec ± 82; P = .01). Atypically developing girls versus boys had lower nPD and shorter T2 (eg, in WM, 557 10 × pu ± 46 vs 580 10 × pu ± 39 for nPD [P = .006] and 86 msec ± 3 vs 88 msec ± 4 for T2 [P = .003]). Atypically versus neurotypically developing boys had a more moderate negative association between T1 and SEd (slope, -32.0 msec per kB/cm3 [95% CI: -49.8, -14.2] vs -62.3 msec per kB/cm3 [95% CI: -79.7, -45.0]; P = .03). Conclusion Atypically developing participants showed sexual dimorphisms in the cerebrospinal fluid-normalized proton density (nPD) and T2 of both white matter (WM) and gray matter. Atypically versus neurotypically developing girls had lower WM nPD, while atypically versus neurotypically developing boys had longer WM T1 and more moderate T1 associations with microstructural organization in WM. © RSNA, 2022 Online supplemental material is available for this article.
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Affiliation(s)
- Ryan McNaughton
- From the Departments of Mechanical Engineering (R.M., X.Z.) and
Biomedical Engineering (H.J.), Boston University College of Engineering, Boston,
Mass; Department of Radiology, Boston University School of Medicine, 670 Albany
St, Boston, MA 02118 (C.P., O.S., H.J.); Department of Pediatrics, University of
North Carolina School of Medicine, Chapel Hill, NC (J.V.R., T.M.O.); Department
of Psychiatry, University of Massachusetts Medical School, Worcester, Mass
(D.N.K., J.A.F.); Department of Pediatrics, Boston University School of
Medicine, Boston, Mass (L.D.); Department of Biostatistics, Boston University
School of Public Health, Boston, Mass (T.H.); and Department of Environmental
Sciences & Engineering, University of North Carolina Gillings School of
Global Public Health, Chapel Hill, NC (R.C.F.)
| | - Chris Pieper
- From the Departments of Mechanical Engineering (R.M., X.Z.) and
Biomedical Engineering (H.J.), Boston University College of Engineering, Boston,
Mass; Department of Radiology, Boston University School of Medicine, 670 Albany
St, Boston, MA 02118 (C.P., O.S., H.J.); Department of Pediatrics, University of
North Carolina School of Medicine, Chapel Hill, NC (J.V.R., T.M.O.); Department
of Psychiatry, University of Massachusetts Medical School, Worcester, Mass
(D.N.K., J.A.F.); Department of Pediatrics, Boston University School of
Medicine, Boston, Mass (L.D.); Department of Biostatistics, Boston University
School of Public Health, Boston, Mass (T.H.); and Department of Environmental
Sciences & Engineering, University of North Carolina Gillings School of
Global Public Health, Chapel Hill, NC (R.C.F.)
| | - Osamu Sakai
- From the Departments of Mechanical Engineering (R.M., X.Z.) and
Biomedical Engineering (H.J.), Boston University College of Engineering, Boston,
Mass; Department of Radiology, Boston University School of Medicine, 670 Albany
St, Boston, MA 02118 (C.P., O.S., H.J.); Department of Pediatrics, University of
North Carolina School of Medicine, Chapel Hill, NC (J.V.R., T.M.O.); Department
of Psychiatry, University of Massachusetts Medical School, Worcester, Mass
(D.N.K., J.A.F.); Department of Pediatrics, Boston University School of
Medicine, Boston, Mass (L.D.); Department of Biostatistics, Boston University
School of Public Health, Boston, Mass (T.H.); and Department of Environmental
Sciences & Engineering, University of North Carolina Gillings School of
Global Public Health, Chapel Hill, NC (R.C.F.)
| | - Julie V. Rollins
- From the Departments of Mechanical Engineering (R.M., X.Z.) and
Biomedical Engineering (H.J.), Boston University College of Engineering, Boston,
Mass; Department of Radiology, Boston University School of Medicine, 670 Albany
St, Boston, MA 02118 (C.P., O.S., H.J.); Department of Pediatrics, University of
North Carolina School of Medicine, Chapel Hill, NC (J.V.R., T.M.O.); Department
of Psychiatry, University of Massachusetts Medical School, Worcester, Mass
(D.N.K., J.A.F.); Department of Pediatrics, Boston University School of
Medicine, Boston, Mass (L.D.); Department of Biostatistics, Boston University
School of Public Health, Boston, Mass (T.H.); and Department of Environmental
Sciences & Engineering, University of North Carolina Gillings School of
Global Public Health, Chapel Hill, NC (R.C.F.)
| | - Xin Zhang
- From the Departments of Mechanical Engineering (R.M., X.Z.) and
Biomedical Engineering (H.J.), Boston University College of Engineering, Boston,
Mass; Department of Radiology, Boston University School of Medicine, 670 Albany
St, Boston, MA 02118 (C.P., O.S., H.J.); Department of Pediatrics, University of
North Carolina School of Medicine, Chapel Hill, NC (J.V.R., T.M.O.); Department
of Psychiatry, University of Massachusetts Medical School, Worcester, Mass
(D.N.K., J.A.F.); Department of Pediatrics, Boston University School of
Medicine, Boston, Mass (L.D.); Department of Biostatistics, Boston University
School of Public Health, Boston, Mass (T.H.); and Department of Environmental
Sciences & Engineering, University of North Carolina Gillings School of
Global Public Health, Chapel Hill, NC (R.C.F.)
| | - David N. Kennedy
- From the Departments of Mechanical Engineering (R.M., X.Z.) and
Biomedical Engineering (H.J.), Boston University College of Engineering, Boston,
Mass; Department of Radiology, Boston University School of Medicine, 670 Albany
St, Boston, MA 02118 (C.P., O.S., H.J.); Department of Pediatrics, University of
North Carolina School of Medicine, Chapel Hill, NC (J.V.R., T.M.O.); Department
of Psychiatry, University of Massachusetts Medical School, Worcester, Mass
(D.N.K., J.A.F.); Department of Pediatrics, Boston University School of
Medicine, Boston, Mass (L.D.); Department of Biostatistics, Boston University
School of Public Health, Boston, Mass (T.H.); and Department of Environmental
Sciences & Engineering, University of North Carolina Gillings School of
Global Public Health, Chapel Hill, NC (R.C.F.)
| | - Jean A. Frazier
- From the Departments of Mechanical Engineering (R.M., X.Z.) and
Biomedical Engineering (H.J.), Boston University College of Engineering, Boston,
Mass; Department of Radiology, Boston University School of Medicine, 670 Albany
St, Boston, MA 02118 (C.P., O.S., H.J.); Department of Pediatrics, University of
North Carolina School of Medicine, Chapel Hill, NC (J.V.R., T.M.O.); Department
of Psychiatry, University of Massachusetts Medical School, Worcester, Mass
(D.N.K., J.A.F.); Department of Pediatrics, Boston University School of
Medicine, Boston, Mass (L.D.); Department of Biostatistics, Boston University
School of Public Health, Boston, Mass (T.H.); and Department of Environmental
Sciences & Engineering, University of North Carolina Gillings School of
Global Public Health, Chapel Hill, NC (R.C.F.)
| | - Laurie Douglass
- From the Departments of Mechanical Engineering (R.M., X.Z.) and
Biomedical Engineering (H.J.), Boston University College of Engineering, Boston,
Mass; Department of Radiology, Boston University School of Medicine, 670 Albany
St, Boston, MA 02118 (C.P., O.S., H.J.); Department of Pediatrics, University of
North Carolina School of Medicine, Chapel Hill, NC (J.V.R., T.M.O.); Department
of Psychiatry, University of Massachusetts Medical School, Worcester, Mass
(D.N.K., J.A.F.); Department of Pediatrics, Boston University School of
Medicine, Boston, Mass (L.D.); Department of Biostatistics, Boston University
School of Public Health, Boston, Mass (T.H.); and Department of Environmental
Sciences & Engineering, University of North Carolina Gillings School of
Global Public Health, Chapel Hill, NC (R.C.F.)
| | - Timothy Heeren
- From the Departments of Mechanical Engineering (R.M., X.Z.) and
Biomedical Engineering (H.J.), Boston University College of Engineering, Boston,
Mass; Department of Radiology, Boston University School of Medicine, 670 Albany
St, Boston, MA 02118 (C.P., O.S., H.J.); Department of Pediatrics, University of
North Carolina School of Medicine, Chapel Hill, NC (J.V.R., T.M.O.); Department
of Psychiatry, University of Massachusetts Medical School, Worcester, Mass
(D.N.K., J.A.F.); Department of Pediatrics, Boston University School of
Medicine, Boston, Mass (L.D.); Department of Biostatistics, Boston University
School of Public Health, Boston, Mass (T.H.); and Department of Environmental
Sciences & Engineering, University of North Carolina Gillings School of
Global Public Health, Chapel Hill, NC (R.C.F.)
| | - Rebecca C. Fry
- From the Departments of Mechanical Engineering (R.M., X.Z.) and
Biomedical Engineering (H.J.), Boston University College of Engineering, Boston,
Mass; Department of Radiology, Boston University School of Medicine, 670 Albany
St, Boston, MA 02118 (C.P., O.S., H.J.); Department of Pediatrics, University of
North Carolina School of Medicine, Chapel Hill, NC (J.V.R., T.M.O.); Department
of Psychiatry, University of Massachusetts Medical School, Worcester, Mass
(D.N.K., J.A.F.); Department of Pediatrics, Boston University School of
Medicine, Boston, Mass (L.D.); Department of Biostatistics, Boston University
School of Public Health, Boston, Mass (T.H.); and Department of Environmental
Sciences & Engineering, University of North Carolina Gillings School of
Global Public Health, Chapel Hill, NC (R.C.F.)
| | - T. Michael O'Shea
- From the Departments of Mechanical Engineering (R.M., X.Z.) and
Biomedical Engineering (H.J.), Boston University College of Engineering, Boston,
Mass; Department of Radiology, Boston University School of Medicine, 670 Albany
St, Boston, MA 02118 (C.P., O.S., H.J.); Department of Pediatrics, University of
North Carolina School of Medicine, Chapel Hill, NC (J.V.R., T.M.O.); Department
of Psychiatry, University of Massachusetts Medical School, Worcester, Mass
(D.N.K., J.A.F.); Department of Pediatrics, Boston University School of
Medicine, Boston, Mass (L.D.); Department of Biostatistics, Boston University
School of Public Health, Boston, Mass (T.H.); and Department of Environmental
Sciences & Engineering, University of North Carolina Gillings School of
Global Public Health, Chapel Hill, NC (R.C.F.)
| | - Karl K. Kuban
- From the Departments of Mechanical Engineering (R.M., X.Z.) and
Biomedical Engineering (H.J.), Boston University College of Engineering, Boston,
Mass; Department of Radiology, Boston University School of Medicine, 670 Albany
St, Boston, MA 02118 (C.P., O.S., H.J.); Department of Pediatrics, University of
North Carolina School of Medicine, Chapel Hill, NC (J.V.R., T.M.O.); Department
of Psychiatry, University of Massachusetts Medical School, Worcester, Mass
(D.N.K., J.A.F.); Department of Pediatrics, Boston University School of
Medicine, Boston, Mass (L.D.); Department of Biostatistics, Boston University
School of Public Health, Boston, Mass (T.H.); and Department of Environmental
Sciences & Engineering, University of North Carolina Gillings School of
Global Public Health, Chapel Hill, NC (R.C.F.)
| | - Hernán Jara
- From the Departments of Mechanical Engineering (R.M., X.Z.) and
Biomedical Engineering (H.J.), Boston University College of Engineering, Boston,
Mass; Department of Radiology, Boston University School of Medicine, 670 Albany
St, Boston, MA 02118 (C.P., O.S., H.J.); Department of Pediatrics, University of
North Carolina School of Medicine, Chapel Hill, NC (J.V.R., T.M.O.); Department
of Psychiatry, University of Massachusetts Medical School, Worcester, Mass
(D.N.K., J.A.F.); Department of Pediatrics, Boston University School of
Medicine, Boston, Mass (L.D.); Department of Biostatistics, Boston University
School of Public Health, Boston, Mass (T.H.); and Department of Environmental
Sciences & Engineering, University of North Carolina Gillings School of
Global Public Health, Chapel Hill, NC (R.C.F.)
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5
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Thompson DK, Yang JYM, Chen J, Kelly CE, Adamson CL, Alexander B, Gilchrist C, Matthews LG, Lee KJ, Hunt RW, Cheong JLY, Spencer-Smith M, Neil JJ, Seal ML, Inder TE, Doyle LW, Anderson PJ. Brain White Matter Development Over the First 13 Years in Very Preterm and Typically Developing Children Based on the T 1-w/ T 2-w Ratio. Neurology 2022; 98:e924-e937. [PMID: 34937788 PMCID: PMC8901175 DOI: 10.1212/wnl.0000000000013250] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Accepted: 12/13/2021] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES To investigate brain regional white matter development in full-term (FT) and very preterm (VP) children at term equivalent and 7 and 13 years of age based on the ratio of T 1- and T 2-weighted MRI (T 1-w/T 2-w), including (1) whether longitudinal changes differ between birth groups or sexes, (2) associations with perinatal risk factors in VP children, and (3) relationships with neurodevelopmental outcomes at 13 years. METHODS Prospective longitudinal cohort study of VP (born <30 weeks' gestation or <1,250 g) and FT infants born between 2001 and 2004 and followed up at term equivalent and 7 and 13 years of age, including MRI studies and neurodevelopmental assessments. T 1-w/T 2-w images were parcellated into 48 white matter regions of interest. RESULTS Of 224 VP participants and 76 FT participants, 197 VP and 55 FT participants had useable T 1-w/T 2-w data from at least one timepoint. T 1-w/T 2-w values increased between term equivalent and 13 years of age, with little evidence that longitudinal changes varied between birth groups or sexes. VP birth, neonatal brain abnormalities, being small for gestational age, and postnatal infection were associated with reduced regional T 1-w/T 2-w values in childhood and adolescence. Increased T 1-w/T 2-w values across the white matter at 13 years were associated with better motor and working memory function for all children. Within the FT group only, larger increases in T 1-w/T 2-w values from term equivalent to 7 years were associated with poorer attention and executive function, and higher T 1-w/T 2-w values at 7 years were associated with poorer mathematics performance. DISCUSSION VP birth and multiple known perinatal risk factors are associated with long-term reductions in the T 1-w/T 2-w ratio in white matter regions in childhood and adolescence, which may relate to alterations in microstructure and myelin content. Increased T 1-w/T 2-w ratio at 13 years appeared to be associated with better motor and working memory function and there appeared to be developmental differences between VP and FT children in the associations for attention, executive functioning, and mathematics performance.
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Affiliation(s)
- Deanne K Thompson
- From the Victorian Infant Brain Study (VIBeS) (D.T., C.K.), Developmental Imaging (J. Chen, C.L.A., M.S.), and Clinical Epidemiology and Biostatistics Unit (K.J.L.), Murdoch Children's Research Institute; Department of Neurosurgery (J.Y.-M.Y., B.A.) and Neonatal Medicine (R.H.), The Royal Children's Hospital, Parkville; Neurodevelopment in Health and Disease Program (C.G.), School of Health and Biomedical Sciences, RMIT University, Bundoora; Turner Institute for Brain and Mental Health (L.M., M.S.-S., P.A.), Monash University, Clayton; Neonatal Services (J. Cheong), The Royal Women's Hospital, Parkville, Melbourne, Australia; Department of Pediatric Neurology (J.N.), Washington University School of Medicine, St. Louis, MO; Department of Pediatric Newborn Medicine (T.I.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Department of Obstetrics and Gynaecology (L.D.), The University of Melbourne, Parkville, Australia.
| | - Joseph Y M Yang
- From the Victorian Infant Brain Study (VIBeS) (D.T., C.K.), Developmental Imaging (J. Chen, C.L.A., M.S.), and Clinical Epidemiology and Biostatistics Unit (K.J.L.), Murdoch Children's Research Institute; Department of Neurosurgery (J.Y.-M.Y., B.A.) and Neonatal Medicine (R.H.), The Royal Children's Hospital, Parkville; Neurodevelopment in Health and Disease Program (C.G.), School of Health and Biomedical Sciences, RMIT University, Bundoora; Turner Institute for Brain and Mental Health (L.M., M.S.-S., P.A.), Monash University, Clayton; Neonatal Services (J. Cheong), The Royal Women's Hospital, Parkville, Melbourne, Australia; Department of Pediatric Neurology (J.N.), Washington University School of Medicine, St. Louis, MO; Department of Pediatric Newborn Medicine (T.I.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Department of Obstetrics and Gynaecology (L.D.), The University of Melbourne, Parkville, Australia
| | - Jian Chen
- From the Victorian Infant Brain Study (VIBeS) (D.T., C.K.), Developmental Imaging (J. Chen, C.L.A., M.S.), and Clinical Epidemiology and Biostatistics Unit (K.J.L.), Murdoch Children's Research Institute; Department of Neurosurgery (J.Y.-M.Y., B.A.) and Neonatal Medicine (R.H.), The Royal Children's Hospital, Parkville; Neurodevelopment in Health and Disease Program (C.G.), School of Health and Biomedical Sciences, RMIT University, Bundoora; Turner Institute for Brain and Mental Health (L.M., M.S.-S., P.A.), Monash University, Clayton; Neonatal Services (J. Cheong), The Royal Women's Hospital, Parkville, Melbourne, Australia; Department of Pediatric Neurology (J.N.), Washington University School of Medicine, St. Louis, MO; Department of Pediatric Newborn Medicine (T.I.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Department of Obstetrics and Gynaecology (L.D.), The University of Melbourne, Parkville, Australia
| | - Claire E Kelly
- From the Victorian Infant Brain Study (VIBeS) (D.T., C.K.), Developmental Imaging (J. Chen, C.L.A., M.S.), and Clinical Epidemiology and Biostatistics Unit (K.J.L.), Murdoch Children's Research Institute; Department of Neurosurgery (J.Y.-M.Y., B.A.) and Neonatal Medicine (R.H.), The Royal Children's Hospital, Parkville; Neurodevelopment in Health and Disease Program (C.G.), School of Health and Biomedical Sciences, RMIT University, Bundoora; Turner Institute for Brain and Mental Health (L.M., M.S.-S., P.A.), Monash University, Clayton; Neonatal Services (J. Cheong), The Royal Women's Hospital, Parkville, Melbourne, Australia; Department of Pediatric Neurology (J.N.), Washington University School of Medicine, St. Louis, MO; Department of Pediatric Newborn Medicine (T.I.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Department of Obstetrics and Gynaecology (L.D.), The University of Melbourne, Parkville, Australia
| | - Christopher L Adamson
- From the Victorian Infant Brain Study (VIBeS) (D.T., C.K.), Developmental Imaging (J. Chen, C.L.A., M.S.), and Clinical Epidemiology and Biostatistics Unit (K.J.L.), Murdoch Children's Research Institute; Department of Neurosurgery (J.Y.-M.Y., B.A.) and Neonatal Medicine (R.H.), The Royal Children's Hospital, Parkville; Neurodevelopment in Health and Disease Program (C.G.), School of Health and Biomedical Sciences, RMIT University, Bundoora; Turner Institute for Brain and Mental Health (L.M., M.S.-S., P.A.), Monash University, Clayton; Neonatal Services (J. Cheong), The Royal Women's Hospital, Parkville, Melbourne, Australia; Department of Pediatric Neurology (J.N.), Washington University School of Medicine, St. Louis, MO; Department of Pediatric Newborn Medicine (T.I.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Department of Obstetrics and Gynaecology (L.D.), The University of Melbourne, Parkville, Australia
| | - Bonnie Alexander
- From the Victorian Infant Brain Study (VIBeS) (D.T., C.K.), Developmental Imaging (J. Chen, C.L.A., M.S.), and Clinical Epidemiology and Biostatistics Unit (K.J.L.), Murdoch Children's Research Institute; Department of Neurosurgery (J.Y.-M.Y., B.A.) and Neonatal Medicine (R.H.), The Royal Children's Hospital, Parkville; Neurodevelopment in Health and Disease Program (C.G.), School of Health and Biomedical Sciences, RMIT University, Bundoora; Turner Institute for Brain and Mental Health (L.M., M.S.-S., P.A.), Monash University, Clayton; Neonatal Services (J. Cheong), The Royal Women's Hospital, Parkville, Melbourne, Australia; Department of Pediatric Neurology (J.N.), Washington University School of Medicine, St. Louis, MO; Department of Pediatric Newborn Medicine (T.I.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Department of Obstetrics and Gynaecology (L.D.), The University of Melbourne, Parkville, Australia
| | - Courtney Gilchrist
- From the Victorian Infant Brain Study (VIBeS) (D.T., C.K.), Developmental Imaging (J. Chen, C.L.A., M.S.), and Clinical Epidemiology and Biostatistics Unit (K.J.L.), Murdoch Children's Research Institute; Department of Neurosurgery (J.Y.-M.Y., B.A.) and Neonatal Medicine (R.H.), The Royal Children's Hospital, Parkville; Neurodevelopment in Health and Disease Program (C.G.), School of Health and Biomedical Sciences, RMIT University, Bundoora; Turner Institute for Brain and Mental Health (L.M., M.S.-S., P.A.), Monash University, Clayton; Neonatal Services (J. Cheong), The Royal Women's Hospital, Parkville, Melbourne, Australia; Department of Pediatric Neurology (J.N.), Washington University School of Medicine, St. Louis, MO; Department of Pediatric Newborn Medicine (T.I.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Department of Obstetrics and Gynaecology (L.D.), The University of Melbourne, Parkville, Australia
| | - Lillian G Matthews
- From the Victorian Infant Brain Study (VIBeS) (D.T., C.K.), Developmental Imaging (J. Chen, C.L.A., M.S.), and Clinical Epidemiology and Biostatistics Unit (K.J.L.), Murdoch Children's Research Institute; Department of Neurosurgery (J.Y.-M.Y., B.A.) and Neonatal Medicine (R.H.), The Royal Children's Hospital, Parkville; Neurodevelopment in Health and Disease Program (C.G.), School of Health and Biomedical Sciences, RMIT University, Bundoora; Turner Institute for Brain and Mental Health (L.M., M.S.-S., P.A.), Monash University, Clayton; Neonatal Services (J. Cheong), The Royal Women's Hospital, Parkville, Melbourne, Australia; Department of Pediatric Neurology (J.N.), Washington University School of Medicine, St. Louis, MO; Department of Pediatric Newborn Medicine (T.I.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Department of Obstetrics and Gynaecology (L.D.), The University of Melbourne, Parkville, Australia
| | - Katherine J Lee
- From the Victorian Infant Brain Study (VIBeS) (D.T., C.K.), Developmental Imaging (J. Chen, C.L.A., M.S.), and Clinical Epidemiology and Biostatistics Unit (K.J.L.), Murdoch Children's Research Institute; Department of Neurosurgery (J.Y.-M.Y., B.A.) and Neonatal Medicine (R.H.), The Royal Children's Hospital, Parkville; Neurodevelopment in Health and Disease Program (C.G.), School of Health and Biomedical Sciences, RMIT University, Bundoora; Turner Institute for Brain and Mental Health (L.M., M.S.-S., P.A.), Monash University, Clayton; Neonatal Services (J. Cheong), The Royal Women's Hospital, Parkville, Melbourne, Australia; Department of Pediatric Neurology (J.N.), Washington University School of Medicine, St. Louis, MO; Department of Pediatric Newborn Medicine (T.I.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Department of Obstetrics and Gynaecology (L.D.), The University of Melbourne, Parkville, Australia
| | - Rodney W Hunt
- From the Victorian Infant Brain Study (VIBeS) (D.T., C.K.), Developmental Imaging (J. Chen, C.L.A., M.S.), and Clinical Epidemiology and Biostatistics Unit (K.J.L.), Murdoch Children's Research Institute; Department of Neurosurgery (J.Y.-M.Y., B.A.) and Neonatal Medicine (R.H.), The Royal Children's Hospital, Parkville; Neurodevelopment in Health and Disease Program (C.G.), School of Health and Biomedical Sciences, RMIT University, Bundoora; Turner Institute for Brain and Mental Health (L.M., M.S.-S., P.A.), Monash University, Clayton; Neonatal Services (J. Cheong), The Royal Women's Hospital, Parkville, Melbourne, Australia; Department of Pediatric Neurology (J.N.), Washington University School of Medicine, St. Louis, MO; Department of Pediatric Newborn Medicine (T.I.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Department of Obstetrics and Gynaecology (L.D.), The University of Melbourne, Parkville, Australia
| | - Jeanie L Y Cheong
- From the Victorian Infant Brain Study (VIBeS) (D.T., C.K.), Developmental Imaging (J. Chen, C.L.A., M.S.), and Clinical Epidemiology and Biostatistics Unit (K.J.L.), Murdoch Children's Research Institute; Department of Neurosurgery (J.Y.-M.Y., B.A.) and Neonatal Medicine (R.H.), The Royal Children's Hospital, Parkville; Neurodevelopment in Health and Disease Program (C.G.), School of Health and Biomedical Sciences, RMIT University, Bundoora; Turner Institute for Brain and Mental Health (L.M., M.S.-S., P.A.), Monash University, Clayton; Neonatal Services (J. Cheong), The Royal Women's Hospital, Parkville, Melbourne, Australia; Department of Pediatric Neurology (J.N.), Washington University School of Medicine, St. Louis, MO; Department of Pediatric Newborn Medicine (T.I.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Department of Obstetrics and Gynaecology (L.D.), The University of Melbourne, Parkville, Australia
| | - Megan Spencer-Smith
- From the Victorian Infant Brain Study (VIBeS) (D.T., C.K.), Developmental Imaging (J. Chen, C.L.A., M.S.), and Clinical Epidemiology and Biostatistics Unit (K.J.L.), Murdoch Children's Research Institute; Department of Neurosurgery (J.Y.-M.Y., B.A.) and Neonatal Medicine (R.H.), The Royal Children's Hospital, Parkville; Neurodevelopment in Health and Disease Program (C.G.), School of Health and Biomedical Sciences, RMIT University, Bundoora; Turner Institute for Brain and Mental Health (L.M., M.S.-S., P.A.), Monash University, Clayton; Neonatal Services (J. Cheong), The Royal Women's Hospital, Parkville, Melbourne, Australia; Department of Pediatric Neurology (J.N.), Washington University School of Medicine, St. Louis, MO; Department of Pediatric Newborn Medicine (T.I.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Department of Obstetrics and Gynaecology (L.D.), The University of Melbourne, Parkville, Australia
| | - Jeffrey J Neil
- From the Victorian Infant Brain Study (VIBeS) (D.T., C.K.), Developmental Imaging (J. Chen, C.L.A., M.S.), and Clinical Epidemiology and Biostatistics Unit (K.J.L.), Murdoch Children's Research Institute; Department of Neurosurgery (J.Y.-M.Y., B.A.) and Neonatal Medicine (R.H.), The Royal Children's Hospital, Parkville; Neurodevelopment in Health and Disease Program (C.G.), School of Health and Biomedical Sciences, RMIT University, Bundoora; Turner Institute for Brain and Mental Health (L.M., M.S.-S., P.A.), Monash University, Clayton; Neonatal Services (J. Cheong), The Royal Women's Hospital, Parkville, Melbourne, Australia; Department of Pediatric Neurology (J.N.), Washington University School of Medicine, St. Louis, MO; Department of Pediatric Newborn Medicine (T.I.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Department of Obstetrics and Gynaecology (L.D.), The University of Melbourne, Parkville, Australia
| | - Marc L Seal
- From the Victorian Infant Brain Study (VIBeS) (D.T., C.K.), Developmental Imaging (J. Chen, C.L.A., M.S.), and Clinical Epidemiology and Biostatistics Unit (K.J.L.), Murdoch Children's Research Institute; Department of Neurosurgery (J.Y.-M.Y., B.A.) and Neonatal Medicine (R.H.), The Royal Children's Hospital, Parkville; Neurodevelopment in Health and Disease Program (C.G.), School of Health and Biomedical Sciences, RMIT University, Bundoora; Turner Institute for Brain and Mental Health (L.M., M.S.-S., P.A.), Monash University, Clayton; Neonatal Services (J. Cheong), The Royal Women's Hospital, Parkville, Melbourne, Australia; Department of Pediatric Neurology (J.N.), Washington University School of Medicine, St. Louis, MO; Department of Pediatric Newborn Medicine (T.I.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Department of Obstetrics and Gynaecology (L.D.), The University of Melbourne, Parkville, Australia
| | - Terrie E Inder
- From the Victorian Infant Brain Study (VIBeS) (D.T., C.K.), Developmental Imaging (J. Chen, C.L.A., M.S.), and Clinical Epidemiology and Biostatistics Unit (K.J.L.), Murdoch Children's Research Institute; Department of Neurosurgery (J.Y.-M.Y., B.A.) and Neonatal Medicine (R.H.), The Royal Children's Hospital, Parkville; Neurodevelopment in Health and Disease Program (C.G.), School of Health and Biomedical Sciences, RMIT University, Bundoora; Turner Institute for Brain and Mental Health (L.M., M.S.-S., P.A.), Monash University, Clayton; Neonatal Services (J. Cheong), The Royal Women's Hospital, Parkville, Melbourne, Australia; Department of Pediatric Neurology (J.N.), Washington University School of Medicine, St. Louis, MO; Department of Pediatric Newborn Medicine (T.I.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Department of Obstetrics and Gynaecology (L.D.), The University of Melbourne, Parkville, Australia
| | - Lex W Doyle
- From the Victorian Infant Brain Study (VIBeS) (D.T., C.K.), Developmental Imaging (J. Chen, C.L.A., M.S.), and Clinical Epidemiology and Biostatistics Unit (K.J.L.), Murdoch Children's Research Institute; Department of Neurosurgery (J.Y.-M.Y., B.A.) and Neonatal Medicine (R.H.), The Royal Children's Hospital, Parkville; Neurodevelopment in Health and Disease Program (C.G.), School of Health and Biomedical Sciences, RMIT University, Bundoora; Turner Institute for Brain and Mental Health (L.M., M.S.-S., P.A.), Monash University, Clayton; Neonatal Services (J. Cheong), The Royal Women's Hospital, Parkville, Melbourne, Australia; Department of Pediatric Neurology (J.N.), Washington University School of Medicine, St. Louis, MO; Department of Pediatric Newborn Medicine (T.I.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Department of Obstetrics and Gynaecology (L.D.), The University of Melbourne, Parkville, Australia
| | - Peter J Anderson
- From the Victorian Infant Brain Study (VIBeS) (D.T., C.K.), Developmental Imaging (J. Chen, C.L.A., M.S.), and Clinical Epidemiology and Biostatistics Unit (K.J.L.), Murdoch Children's Research Institute; Department of Neurosurgery (J.Y.-M.Y., B.A.) and Neonatal Medicine (R.H.), The Royal Children's Hospital, Parkville; Neurodevelopment in Health and Disease Program (C.G.), School of Health and Biomedical Sciences, RMIT University, Bundoora; Turner Institute for Brain and Mental Health (L.M., M.S.-S., P.A.), Monash University, Clayton; Neonatal Services (J. Cheong), The Royal Women's Hospital, Parkville, Melbourne, Australia; Department of Pediatric Neurology (J.N.), Washington University School of Medicine, St. Louis, MO; Department of Pediatric Newborn Medicine (T.I.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; and Department of Obstetrics and Gynaecology (L.D.), The University of Melbourne, Parkville, Australia
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6
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Bruckert L, Travis KE, Mezer AA, Ben-Shachar M, Feldman HM. Associations of Reading Efficiency with White Matter Properties of the Cerebellar Peduncles in Children. THE CEREBELLUM 2021; 19:771-777. [PMID: 32642932 DOI: 10.1007/s12311-020-01162-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
Reading in children has been associated with microstructural properties of the cerebellar peduncles, the white matter pathways connecting the cerebellum to the cerebrum. In this study, we used two independent neuroimaging modalities to assess which features of the cerebellar peduncles would be associated with reading. Twenty-three 8-year-old children were evaluated on word reading efficiency and imaged using diffusion MRI (dMRI) and quantitative T1 relaxometry (qT1). We segmented the superior (SCP), middle, and inferior cerebellar peduncles and extracted two metrics: fractional anisotropy (FA) from dMRI and R1 from qT1. Tract-FA was significantly correlated with tract-R1 in left and right SCPs (left: rP(21) = .63, right: rP(21) = .76, p ≤ .001) suggesting that FA of these peduncles, at least in part, indexed myelin content. Tract-FA and tract R1 were not correlated in the other cerebellar peduncles. Reading efficiency negatively correlated with tract-FA of the left (rP(21) = - .43, p = .040) and right SCP (rP(21) = - .37, p = .079). Reading efficiency did not correlate with tract-R1 in the SCPs. The negative association of reading efficiency with tract-FA and the lack of association of reading efficiency with tract-R1 implicate properties other than myelin content as relevant to the information flow between the cerebellum and the cerebrum for individual differences in reading skills in children.
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Affiliation(s)
- Lisa Bruckert
- Developmental-Behavioral Pediatrics, Stanford School of Medicine, Stanford, CA, USA
| | - Katherine E Travis
- Developmental-Behavioral Pediatrics, Stanford School of Medicine, Stanford, CA, USA
| | - Aviv A Mezer
- Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Michal Ben-Shachar
- Department of English Literature and Linguistics, Bar Ilan University, Ramat Gan, Israel.,The Gonda Multidisciplinary Brain Research Center, Bar Ilan University, Ramat Gan, Israel
| | - Heidi M Feldman
- Developmental-Behavioral Pediatrics, Stanford School of Medicine, Stanford, CA, USA. .,Medical School Office Building, 1265 Welch Road, Room X163, Stanford, CA, 94305, USA.
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7
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Huber E, Mezer A, Yeatman JD. Neurobiological underpinnings of rapid white matter plasticity during intensive reading instruction. Neuroimage 2021; 243:118453. [PMID: 34358657 DOI: 10.1016/j.neuroimage.2021.118453] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Revised: 07/24/2021] [Accepted: 08/03/2021] [Indexed: 01/18/2023] Open
Abstract
Diffusion MRI is a powerful tool for imaging brain structure, but it is challenging to discern the biological underpinnings of plasticity inferred from these and other non-invasive MR measurements. Biophysical modeling of the diffusion signal aims to render a more biologically rich image of tissue microstructure, but the application of these models comes with important caveats. A separate approach for gaining biological specificity has been to seek converging evidence from multi-modal datasets. Here we use metrics derived from diffusion kurtosis imaging (DKI) and the white matter tract integrity (WMTI) model along with quantitative MRI measurements of T1 relaxation to characterize changes throughout the white matter during an 8-week, intensive reading intervention (160 total hours of instruction). Behavioral measures, multi-shell diffusion MRI data, and quantitative T1 data were collected at regular intervals during the intervention in a group of 33 children with reading difficulties (7-12 years old), and over the same period in an age-matched non-intervention control group. Throughout the white matter, mean 'extra-axonal' diffusivity was inversely related to intervention time. In contrast, model estimated axonal water fraction (AWF), overall diffusion kurtosis, and T1 relaxation time showed no significant change over the intervention period. Both diffusion and quantitative T1 based metrics were correlated with pre-intervention reading performance, albeit with distinct anatomical distributions. These results are consistent with the view that rapid changes in diffusion properties reflect phenomena other than widespread changes in myelin density. We discuss this result in light of recent work highlighting non-axonal factors in experience-dependent plasticity and learning.
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Affiliation(s)
- Elizabeth Huber
- Institute for Learning and Brain Sciences and Department of Speech and Hearing Sciences, University of Washington, Seattle, WA 98195, USA.
| | - Aviv Mezer
- Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Jason D Yeatman
- Graduate School of Education, Stanford University, Stanford, CA 94305, USA; Division of Developmental-Behavioral Pediatrics, Stanford University School of Medicine, Stanford, CA 95305, USA
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8
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Speech rate association with cerebellar white-matter diffusivity in adults with persistent developmental stuttering. Brain Struct Funct 2021; 226:801-816. [PMID: 33538875 DOI: 10.1007/s00429-020-02210-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Accepted: 12/22/2020] [Indexed: 10/22/2022]
Abstract
Speech rate is a basic characteristic of language production, which affects the speaker's intelligibility and communication efficiency. Various speech disorders, including persistent developmental stuttering, present altered speech rate. Specifically, adults who stutter (AWS) typically exhibit a slower speech rate compared to fluent speakers. Evidence from imaging studies suggests that the cerebellum contributes to the paced production of speech. People who stutter show structural and functional abnormalities in the cerebellum. However, the involvement of the cerebellar pathways in controlling speech rate remains unexplored. Here, we assess the association of the cerebellar peduncles with speech rate in AWS and control speakers. Diffusion MRI and speech-rate data were collected in 42 participants (23 AWS, 19 controls). We used deterministic tractography with Automatic Fiber segmentation and Quantification (AFQ) to identify the superior, middle, and inferior cerebellar peduncles (SCP, MCP, ICP) bilaterally, and quantified fractional anisotropy (FA) and mean diffusivity (MD) along each tract. No significant differences were observed between AWS and controls in the diffusivity values of the cerebellar peduncles. However, AWS demonstrated a significant negative association between speech rate and FA within the left ICP, a major cerebellar pathway that transmits sensory feedback signals from the olivary nucleus into the cerebellum. The involvement of the ICP in controlling speech production in AWS is compatible with the view that stuttering stems from hyperactive speech monitoring, where even minor deviations from the speech plan are considered as errors. In conclusion, our findings suggest a plausible neural mechanism for speech rate reduction observed in AWS.
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9
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Erramuzpe A, Schurr R, Yeatman JD, Gotlib IH, Sacchet MD, Travis KE, Feldman HM, Mezer AA. A Comparison of Quantitative R1 and Cortical Thickness in Identifying Age, Lifespan Dynamics, and Disease States of the Human Cortex. Cereb Cortex 2021; 31:1211-1226. [PMID: 33095854 PMCID: PMC8485079 DOI: 10.1093/cercor/bhaa288] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 08/25/2020] [Accepted: 09/03/2020] [Indexed: 07/22/2023] Open
Abstract
Brain development and aging are complex processes that unfold in multiple brain regions simultaneously. Recently, models of brain age prediction have aroused great interest, as these models can potentially help to understand neurological diseases and elucidate basic neurobiological mechanisms. We test whether quantitative magnetic resonance imaging can contribute to such age prediction models. Using R1, the longitudinal rate of relaxation, we explore lifespan dynamics in cortical gray matter. We compare R1 with cortical thickness, a well-established biomarker of brain development and aging. Using 160 healthy individuals (6-81 years old), we found that R1 and cortical thickness predicted age similarly, but the regions contributing to the prediction differed. Next, we characterized R1 development and aging dynamics. Compared with anterior regions, in posterior regions we found an earlier R1 peak but a steeper postpeak decline. We replicate these findings: firstly, we tested a subset (N = 10) of the original dataset for whom we had additional scans at a lower resolution; and second, we verified the results on an independent dataset (N = 34). Finally, we compared the age prediction models on a subset of 10 patients with multiple sclerosis. The patients are predicted older than their chronological age using R1 but not with cortical thickness.
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Affiliation(s)
| | - R Schurr
- The Hebrew University of Jerusalem, The Edmond and Lily Safra Center for Brain Sciences, Jerusalem, Israel
| | - J D Yeatman
- Graduate School of Education, Stanford University, Stanford, CA, USA
- Division of Developmental-Behavioral Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - I H Gotlib
- Psychology, Stanford University, Stanford, CA, USA
| | - M D Sacchet
- Harvard Medical School, Center for Depression, Anxiety, and Stress Research, McLean Hospital, Belmont, MA, USA
| | - K E Travis
- Pediatrics, Stanford University, Stanford, CA, USA
| | - H M Feldman
- Development and Behavior Unit, Stanford University, Stanford, CA, USA
| | - A A Mezer
- The Hebrew University of Jerusalem, The Edmond and Lily Safra Center for Brain Sciences, Jerusalem, Israel
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10
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Menegaux A, Hedderich DM, Bäuml JG, Manoliu A, Daamen M, Berg RC, Preibisch C, Zimmer C, Boecker H, Bartmann P, Wolke D, Sorg C, Stämpfli P. Reduced apparent fiber density in the white matter of premature-born adults. Sci Rep 2020; 10:17214. [PMID: 33057208 PMCID: PMC7560721 DOI: 10.1038/s41598-020-73717-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Accepted: 09/21/2020] [Indexed: 12/13/2022] Open
Abstract
Premature-born adults exhibit lasting white matter alterations as demonstrated by widespread reduction in fractional anisotropy (FA) based on diffusion-weighted imaging (DWI). FA reduction, however, is non-specific for microscopic underpinnings such as aberrant myelination or fiber density (FD). Using recent advances in DWI, we tested the hypothesis of reduced FD in premature-born adults and investigated its link with the degree of prematurity and cognition. 73 premature- and 89 mature-born adults aged 25-27 years underwent single-shell DWI, from which a FD measure was derived using convex optimization modeling for microstructure informed tractography (COMMIT). Premature-born adults exhibited lower FD in numerous tracts including the corpus callosum and corona radiata compared to mature-born adults. These FD alterations were associated with both the degree of prematurity, as assessed via gestational age and birth weight, as well as with reduced cognition as measured by full-scale IQ. Finally, lower FD overlapped with lower FA, suggesting lower FD underlie unspecific FA reductions. Results provide evidence that premature birth leads to lower FD in adulthood which links with lower full-scale IQ. Data suggest that lower FD partly underpins FA reductions of premature birth but that other processes such as hypomyelination might also take place.
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Affiliation(s)
- Aurore Menegaux
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany. .,TUM Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany.
| | - Dennis M Hedderich
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany.,TUM Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Josef G Bäuml
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany.,TUM Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Andrei Manoliu
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Zurich, Switzerland.,Wellcome Centre for Human Neuroimaging, University College London, London, UK.,Centre for Computational Psychiatry and Ageing Research, Max Planck University College London, London, UK
| | - Marcel Daamen
- Functional Neuroimaging Group, Department of Radiology, University Hospital Bonn, Bonn, Germany.,Department of Neonatology, University Hospital Bonn, Bonn, Germany
| | - Ronja C Berg
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany.,TUM Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Christine Preibisch
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany.,TUM Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Claus Zimmer
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany.,TUM Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Henning Boecker
- Functional Neuroimaging Group, Department of Radiology, University Hospital Bonn, Bonn, Germany
| | - Peter Bartmann
- Department of Neonatology, University Hospital Bonn, Bonn, Germany
| | - Dieter Wolke
- Department of Psychology, University of Warwick, Coventry, UK.,Warwick Medical School, University of Warwick, Coventry, UK
| | - Christian Sorg
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany.,TUM Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany.,Department of Psychiatry, School of Medicine, Technical University of Munich, Munich, Germany
| | - Philipp Stämpfli
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Zurich, Switzerland.,MR-Center of the Department of Psychiatry, Psychotherapy, and Psychosomatics and the Department of Child and Adolescent Psychiatry, Psychiatric Hospital of the University of Zurich, University of Zurich, Zurich, Switzerland
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11
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Dubner SE, Dodson CK, Marchman VA, Ben-Shachar M, Feldman HM, Travis KE. White matter microstructure and cognitive outcomes in relation to neonatal inflammation in 6-year-old children born preterm. NEUROIMAGE-CLINICAL 2019; 23:101832. [PMID: 31075555 PMCID: PMC6603335 DOI: 10.1016/j.nicl.2019.101832] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/05/2019] [Revised: 04/03/2019] [Accepted: 04/18/2019] [Indexed: 12/15/2022]
Abstract
BACKGROUND Cognitive outcomes in preterm (PT) children have been associated with microstructural properties of white matter. PT children who experienced neonatal inflammatory conditions have poorer cognitive outcomes than those who did not. The goal of this study was to contrast white matter microstructure and cognitive outcomes after preterm birth in relation to the presence or absence of severe inflammatory conditions in the neonatal period. METHODS PT children (n = 35), born at gestational age 22-32 weeks, were classified as either PT+ (n = 12) based on a neonatal history of inflammatory conditions, including bronchopulmonary dysplasia, necrotizing enterocolitis or culture positive sepsis, or PT- (n = 23) based on the absence of the three inflammatory conditions. Full term (FT) children (n = 43) served as controls. Participants underwent diffusion MRI and cognitive testing (intelligence, reading, and executive function) at age 6 years. The corpus callosum was segmented into 7 regions using deterministic tractography and based on the cortical projection zones of the callosal fibers. Mean fractional anisotropy (FA) and mean diffusivity (MD) were calculated for each segment. General linear models with planned contrasts assessed group differences in FA, MD and cognitive outcomes. Pearson correlations assessed associations of white matter metrics and cognitive outcome measures. RESULTS FA was significantly lower and MD was significantly higher in PT+ compared to PT- or FT groups in multiple callosal segments, even after adjusting for gestational age. Executive function scores, but not intelligence or reading scores, were less favorable in PT+ than in PT- groups. Among the entire sample, occipital FA was significantly correlated with IQ (r = 0.25, p < 0.05), reading (r = 0.32, p < 0.01), and executive function (r = -0.28, p < 0.05) measures. Anterior frontal FA and superior parietal FA were significantly correlated with executive function (r = -0.25, r = 0.23, respectively, p < 0.05). CONCLUSIONS We observed differences in the white matter microstructure of the corpus callosum and in the cognitive skills of 6-year-old PT children based on their history of neonatal inflammation. Neonatal inflammation is one medical factor that may contribute to variation in long-term neurobiological and neuropsychological outcomes in PT samples.
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Affiliation(s)
- Sarah E Dubner
- Division of Developmental-Behavioral Pediatrics, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Cory K Dodson
- Division of Developmental-Behavioral Pediatrics, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | | | - Michal Ben-Shachar
- The Gonda Multidisciplinary Brain Research Center, Bar Ilan University, Ramat Gan, Israel; Department of English Literature and Linguistics, Bar Ilan University, Ramat Gan, Israel
| | - Heidi M Feldman
- Division of Developmental-Behavioral Pediatrics, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA
| | - Katherine E Travis
- Division of Developmental-Behavioral Pediatrics, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA.
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