1
|
Serio B, Hettwer MD, Wiersch L, Bignardi G, Sacher J, Weis S, Eickhoff SB, Valk SL. Sex differences in functional cortical organization reflect differences in network topology rather than cortical morphometry. Nat Commun 2024; 15:7714. [PMID: 39231965 PMCID: PMC11375086 DOI: 10.1038/s41467-024-51942-1] [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: 12/06/2023] [Accepted: 08/21/2024] [Indexed: 09/06/2024] Open
Abstract
Differences in brain size between the sexes are consistently reported. However, the consequences of this anatomical difference on sex differences in intrinsic brain function remain unclear. In the current study, we investigate whether sex differences in intrinsic cortical functional organization may be associated with differences in cortical morphometry, namely different measures of brain size, microstructure, and the geodesic distance of connectivity profiles. For this, we compute a low dimensional representation of functional cortical organization, the sensory-association axis, and identify widespread sex differences. Contrary to our expectations, sex differences in functional organization do not appear to be systematically associated with differences in total surface area, microstructural organization, or geodesic distance, despite these morphometric properties being per se associated with functional organization and differing between sexes. Instead, functional sex differences in the sensory-association axis are associated with differences in functional connectivity profiles and network topology. Collectively, our findings suggest that sex differences in functional cortical organization extend beyond sex differences in cortical morphometry.
Collapse
Affiliation(s)
- Bianca Serio
- Institute of Neuroscience and Medicine, Brain & Behavior (INM-7), Research Centre Jülich, Jülich, Germany.
- Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany.
- Max Planck School of Cognition, Leipzig, Germany.
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| | - Meike D Hettwer
- Institute of Neuroscience and Medicine, Brain & Behavior (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany
- Max Planck School of Cognition, Leipzig, Germany
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Lisa Wiersch
- Institute of Neuroscience and Medicine, Brain & Behavior (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany
- Brain-Based Predictive Modeling Lab, Feinstein Institutes for Medical Research, Glen Oaks, New York, NY, USA
| | - Giacomo Bignardi
- Max Planck School of Cognition, Leipzig, Germany
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Julia Sacher
- Max Planck School of Cognition, Leipzig, Germany
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Leipzig Center for Female Health & Gender Medicine, Medical Faculty, University Clinic Leipzig, Leipzig, Germany
- Clinic for Cognitive Neurology, University Medical Center Leipzig, Leipzig, Germany
| | - Susanne Weis
- Institute of Neuroscience and Medicine, Brain & Behavior (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine, Brain & Behavior (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany
- Max Planck School of Cognition, Leipzig, Germany
| | - Sofie L Valk
- Institute of Neuroscience and Medicine, Brain & Behavior (INM-7), Research Centre Jülich, Jülich, Germany.
- Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany.
- Max Planck School of Cognition, Leipzig, Germany.
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| |
Collapse
|
2
|
Mendez Colmenares A, Thomas ML, Anderson C, Arciniegas DB, Calhoun V, Choi IY, Kramer AF, Li K, Lee J, Lee P, Burzynska AZ. Testing the structural disconnection hypothesis: Myelin content correlates with memory in healthy aging. Neurobiol Aging 2024; 141:21-33. [PMID: 38810596 PMCID: PMC11290458 DOI: 10.1016/j.neurobiolaging.2024.05.013] [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: 03/12/2024] [Revised: 05/07/2024] [Accepted: 05/21/2024] [Indexed: 05/31/2024]
Abstract
INTRODUCTION The "structural disconnection" hypothesis of cognitive aging suggests that deterioration of white matter (WM), especially myelin, results in cognitive decline, yet in vivo evidence is inconclusive. METHODS We examined age differences in WM microstructure using Myelin Water Imaging and Diffusion Tensor Imaging in 141 healthy participants (age 20-79). We used the Virginia Cognitive Aging Project and the NIH Toolbox® to generate composites for memory, processing speed, and executive function. RESULTS Voxel-wise analyses showed that lower myelin water fraction (MWF), predominantly in prefrontal WM, genu of the corpus callosum, and posterior limb of the internal capsule was associated with reduced memory performance after controlling for age, sex, and education. In structural equation modeling, MWF in the prefrontal white matter and genu of the corpus callosum significantly mediated the effect of age on memory, whereas fractional anisotropy (FA) did not. DISCUSSION Our findings support the disconnection hypothesis, showing that myelin decline contributes to age-related memory loss and opens avenues for interventions targeting myelin health.
Collapse
Affiliation(s)
- Andrea Mendez Colmenares
- The BRAiN lab, Department of Human Development and Family Studies/Molecular, Cellular and Integrative Neurosciences, Colorado State University, Behavioral Sciences Building, 303, 410 W Pitkin St, Fort Collins, CO 80523, USA
| | - Michael L Thomas
- Department of Psychology, Colorado State University, Behavioral Sciences Building, 303, 410 W Pitkin, St, Fort Collins, CO 80523, USA
| | - Charles Anderson
- Department of Computer Science, Colorado State University, 456 University Ave #444, Fort Collins, CO 80521, USA
| | - David B Arciniegas
- Marcus Institute for Brain Health, University of Colorado Anschutz Medical Campus, 12348 E Montview Blvd, Aurora, CO 80045, USA
| | - Vince Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory, 55 Park Pl NE, Atlanta, GA 30303, USA
| | - In-Young Choi
- Department of Neurology, Department of Radiology, Hoglund Biomedical Imaging Center, University of Kansas Medical Center, 3805 Eaton St, Kansas City, KS 66103, USA
| | - Arthur F Kramer
- Beckman Institute for Advanced Science and Technology at the University of Illinois, 405 N Mathews Ave, Urbana, IL 61801, USA; Center for Cognitive & Brain Health, Northeastern University, Address: 360 Huntington Ave, Boston, MA 02115, USA
| | - Kaigang Li
- Department of Health and Exercise Science, Colorado State University, 951 W Plum St, Fort Collins, CO 80521, USA
| | - Jongho Lee
- Department of Electrical and Computer Engineering, Seoul National University, 232 Gongneung-ro, Nowon-gu, Seoul 01811, South Korea
| | - Phil Lee
- Department of Radiology, Hoglund Biomedical Imaging Center, University of Kansas Medical Center, 3805 Eaton St, Kansas City, KS 66103, USA
| | - Agnieszka Z Burzynska
- The BRAiN lab, Department of Human Development and Family Studies/Molecular, Cellular and Integrative Neurosciences, Colorado State University, Behavioral Sciences Building, 303, 410 W Pitkin St, Fort Collins, CO 80523, USA.
| |
Collapse
|
3
|
Jossinger S, Yablonski M, Amir O, Ben-Shachar M. The Contributions of the Cerebellar Peduncles and the Frontal Aslant Tract in Mediating Speech Fluency. NEUROBIOLOGY OF LANGUAGE (CAMBRIDGE, MASS.) 2024; 5:676-700. [PMID: 39175785 PMCID: PMC11338307 DOI: 10.1162/nol_a_00098] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 12/23/2022] [Indexed: 08/24/2024]
Abstract
Fluent speech production is a complex task that spans multiple processes, from conceptual framing and lexical access, through phonological encoding, to articulatory control. For the most part, imaging studies portraying the neural correlates of speech fluency tend to examine clinical populations sustaining speech impairments and focus on either lexical access or articulatory control, but not both. Here, we evaluated the contribution of the cerebellar peduncles to speech fluency by measuring the different components of the process in a sample of 45 neurotypical adults. Participants underwent an unstructured interview to assess their natural speaking rate and articulation rate, and completed timed semantic and phonemic fluency tasks to assess their verbal fluency. Diffusion magnetic resonance imaging with probabilistic tractography was used to segment the bilateral cerebellar peduncles (CPs) and frontal aslant tract (FAT), previously associated with speech production in clinical populations. Our results demonstrate distinct patterns of white matter associations with different fluency components. Specifically, verbal fluency is associated with the right superior CP, whereas speaking rate is associated with the right middle CP and bilateral FAT. No association is found with articulation rate in these pathways, in contrast to previous findings in persons who stutter. Our findings support the contribution of the cerebellum to aspects of speech production that go beyond articulatory control, such as lexical access, pragmatic or syntactic generation. Further, we demonstrate that distinct cerebellar pathways dissociate different components of speech fluency in neurotypical speakers.
Collapse
Affiliation(s)
- Sivan Jossinger
- The Gonda Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat-Gan, Israel
| | - Maya Yablonski
- The Gonda Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat-Gan, Israel
| | - Ofer Amir
- Department of Communication Disorders, Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel
| | - Michal Ben-Shachar
- The Gonda Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat-Gan, Israel
- The Department of English Literature and Linguistics, Bar-Ilan University, Ramat-Gan, Israel
| |
Collapse
|
4
|
Faulkner ME, Gong Z, Guo A, Laporte JP, Bae J, Bouhrara M. Harnessing myelin water fraction as an imaging biomarker of human cerebral aging, neurodegenerative diseases, and risk factors influencing myelination: A review. J Neurochem 2024. [PMID: 38973579 DOI: 10.1111/jnc.16170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2024] [Revised: 06/12/2024] [Accepted: 06/19/2024] [Indexed: 07/09/2024]
Abstract
Myelin water fraction (MWF) imaging has emerged as a promising magnetic resonance imaging (MRI) biomarker for investigating brain function and composition. This comprehensive review synthesizes the current state of knowledge on MWF as a biomarker of human cerebral aging, neurodegenerative diseases, and risk factors influencing myelination. The databases used include Web of Science, Scopus, Science Direct, and PubMed. We begin with a brief discussion of the theoretical foundations of MWF imaging, including its basis in MR physics and the mathematical modeling underlying its calculation, with an overview of the most adopted MRI methods of MWF imaging. Next, we delve into the clinical and research applications that have been explored to date, highlighting its advantages and limitations. Finally, we explore the potential of MWF to serve as a predictive biomarker for neurological disorders and identify future research directions for optimizing MWF imaging protocols and interpreting MWF in various contexts. By harnessing the power of MWF imaging, we may gain new insights into brain health and disease across the human lifespan, ultimately informing novel diagnostic and therapeutic strategies.
Collapse
Affiliation(s)
- Mary E Faulkner
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - Zhaoyuan Gong
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - Alex Guo
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - John P Laporte
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - Jonghyun Bae
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| | - Mustapha Bouhrara
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, Maryland, USA
| |
Collapse
|
5
|
Schmidbauer VU, Yildirim MS, Dovjak GO, Goeral K, Buchmayer J, Weber M, Kienast P, Diogo MC, Prayer F, Stuempflen M, Kittinger J, Malik J, Nowak NM, Klebermass-Schrehof K, Fuiko R, Berger A, Prayer D, Kasprian G, Giordano V. Quantitative Magnetic Resonance Imaging for Neurodevelopmental Outcome Prediction in Neonates Born Extremely Premature-An Exploratory Study. Clin Neuroradiol 2024; 34:421-429. [PMID: 38289377 PMCID: PMC11129968 DOI: 10.1007/s00062-023-01378-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Accepted: 12/26/2023] [Indexed: 05/29/2024]
Abstract
PURPOSE Neonates born at < 28 weeks of gestation are at risk for neurodevelopmental delay. The aim of this study was to identify quantitative MR-based metrics for the prediction of neurodevelopmental outcomes in extremely preterm neonates. METHODS T1-/T2-relaxation times (T1R/T2R), ADC, and fractional anisotropy (FA) of the left/right posterior limb of the internal capsule (PLIC) and the brainstem were determined at term-equivalent ages in a sample of extremely preterm infants (n = 33). Scores for cognitive, language, and motor outcomes were collected at one year corrected-age. Pearson's correlation analyses detected relationships between quantitative measures and outcome data. Stepwise regression procedures identified imaging metrics to estimate neurodevelopmental outcomes. RESULTS Cognitive outcomes correlated significantly with T2R (r = 0.412; p = 0.017) and ADC (r = -0.401; p = 0.021) (medulla oblongata). Furthermore, there were significant correlations between motor outcomes and T1R (pontine tegmentum (r = 0.346; p = 0.049), midbrain (r = 0.415; p = 0.016), right PLIC (r = 0.513; p = 0.002), and left PLIC (r = 0.504; p = 0.003)); T2R (right PLIC (r = 0.405; p = 0.019)); ADC (medulla oblongata (r = -0.408; p = 0.018) and pontine tegmentum (r = -0.414; p = 0.017)); and FA (pontine tegmentum (r = -0.352; p = 0.045)). T2R/ADC (medulla oblongata) (cognitive outcomes (R2 = 0.296; p = 0.037)) and T1R (right PLIC)/ADC (medulla oblongata) (motor outcomes (R2 = 0.405; p = 0.009)) revealed predictive potential for neurodevelopmental outcomes. CONCLUSION There are relationships between relaxometry‑/DTI-based metrics determined by neuroimaging near term and neurodevelopmental outcomes collected at one year of age. Both modalities bear prognostic potential for the prediction of cognitive and motor outcomes. Thus, quantitative MRI at term-equivalent ages represents a promising approach with which to estimate neurologic development in extremely preterm infants.
Collapse
Affiliation(s)
- Victor U Schmidbauer
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria.
| | - Mehmet S Yildirim
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Gregor O Dovjak
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Katharina Goeral
- Comprehensive Center for Pediatrics, Department of Pediatrics and Adolescent Medicine, Division of Neonatology, Pediatric Intensive Care and Neuropediatrics, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Julia Buchmayer
- Comprehensive Center for Pediatrics, Department of Pediatrics and Adolescent Medicine, Division of Neonatology, Pediatric Intensive Care and Neuropediatrics, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Michael Weber
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Patric Kienast
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Mariana C Diogo
- Department of Neuroradiology, Hospital Garcia de Orta, Av. Torrado da Silva, 2805-267 Almada, Portugal
| | - Florian Prayer
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Marlene Stuempflen
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Jakob Kittinger
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Jakob Malik
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Nikolaus M Nowak
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Katrin Klebermass-Schrehof
- Comprehensive Center for Pediatrics, Department of Pediatrics and Adolescent Medicine, Division of Neonatology, Pediatric Intensive Care and Neuropediatrics, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Renate Fuiko
- Comprehensive Center for Pediatrics, Department of Pediatrics and Adolescent Medicine, Division of Neonatology, Pediatric Intensive Care and Neuropediatrics, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Angelika Berger
- Comprehensive Center for Pediatrics, Department of Pediatrics and Adolescent Medicine, Division of Neonatology, Pediatric Intensive Care and Neuropediatrics, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Daniela Prayer
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Gregor Kasprian
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Vito Giordano
- Comprehensive Center for Pediatrics, Department of Pediatrics and Adolescent Medicine, Division of Neonatology, Pediatric Intensive Care and Neuropediatrics, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| |
Collapse
|
6
|
Kitano S, Kanazawa Y, Harada M, Taniguchi Y, Hayashi H, Matsumoto Y, Ito K, Bito Y, Haga A. Conversion map from quantitative parameter mapping to myelin water fraction: comparison with R 1·R 2* and myelin water fraction in white matter. MAGMA (NEW YORK, N.Y.) 2024:10.1007/s10334-024-01155-w. [PMID: 38581455 DOI: 10.1007/s10334-024-01155-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Revised: 02/28/2024] [Accepted: 02/29/2024] [Indexed: 04/08/2024]
Abstract
OBJECTIVE To clarify the relationship between myelin water fraction (MWF) and R1⋅R2* and to develop a method to calculate MWF directly from parameters derived from QPM, i.e., MWF converted from QPM (MWFQPM). MATERIALS AND METHODS Subjects were 12 healthy volunteers. On a 3 T MR scanner, dataset was acquired using spoiled gradient-echo sequence for QPM. MWF and R1⋅R2* maps were derived from the multi-gradient-echo (mGRE) dataset. Volume-of-interest (VOI) analysis using the JHU-white matter (WM) atlas was performed. All the data in the 48 WM regions measured VOI were plotted, and quadratic polynomial approximations of each region were derived from the relationship between R1·R2* and the two-pool model-MWF. The R1·R2* map was converted to MWFQPM map. MWF atlas template was generated using converted to MWF from R1·R2* per WM region. RESULTS The mean MWF and R1·R2* values for the 48 WM regions were 11.96 ± 6.63%, and 19.94 ± 4.59 s-2, respectively. A non-linear relationship in 48 regions of the WM between MWF and R1·R2* values was observed by quadratic polynomial approximation (R2 ≥ 0.963, P < 0.0001). DISCUSSION MWFQPM map improved image quality compared to the mGRE-MWF map. Myelin water atlas template derived from MWFQPM may be generated with combined multiple WM regions.
Collapse
Affiliation(s)
- Shun Kitano
- Graduate of Health Science, Tokushima University, 3-18-15 Kuramoto-cho, Tokushima, Tokushima, 770-8503, Japan
- Clinical Radiology Service, Kyoto University Hospital, Kyoto, 606-8507, Japan
| | - Yuki Kanazawa
- Graduate School of Biomedical Sciences, Tokushima University, 3-18-15 Kuramoto-cho, Tokushima, Tokushima, 770-8503, Japan.
| | - Masafumi Harada
- Graduate School of Biomedical Sciences, Tokushima University, 3-18-15 Kuramoto-cho, Tokushima, Tokushima, 770-8503, Japan
| | - Yo Taniguchi
- FUJIFILM Healthcare Corporation, 2-1 Shintoyofuta, Kashiwa, Chiba, 277-0804, Japan
| | - Hiroaki Hayashi
- College of Medical, Pharmaceutical and Health Sciences, Kanazawa University, 5-11-80 Kodatsuno, Kanazawa, Ishikawa, 920-0942, Japan
| | - Yuki Matsumoto
- Graduate School of Biomedical Sciences, Tokushima University, 3-18-15 Kuramoto-cho, Tokushima, Tokushima, 770-8503, Japan
| | - Kosuke Ito
- FUJIFILM Healthcare Corporation, 2-1 Shintoyofuta, Kashiwa, Chiba, 277-0804, Japan
| | - Yoshitaka Bito
- FUJIFILM Healthcare Corporation, 2-1 Shintoyofuta, Kashiwa, Chiba, 277-0804, Japan
| | - Akihiro Haga
- Graduate School of Biomedical Sciences, Tokushima University, 3-18-15 Kuramoto-cho, Tokushima, Tokushima, 770-8503, Japan
| |
Collapse
|
7
|
Jørgensen KN, Nerland S, Slapø NB, Norbom LB, Mørch-Johnsen L, Wortinger LA, Barth C, Andreou D, Maximov II, Geier OM, Andreassen OA, Jönsson EG, Agartz I. Assessing regional intracortical myelination in schizophrenia spectrum and bipolar disorders using the optimized T1w/T2w-ratio. Psychol Med 2024:1-11. [PMID: 38563302 DOI: 10.1017/s0033291724000503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
BACKGROUND Dysmyelination could be part of the pathophysiology of schizophrenia spectrum (SCZ) and bipolar disorders (BPD), yet few studies have examined myelination of the cerebral cortex. The ratio of T1- and T2-weighted magnetic resonance images (MRI) correlates with intracortical myelin. We investigated the T1w/T2w-ratio and its age trajectories in patients and healthy controls (CTR) and explored associations with antipsychotic medication use and psychotic symptoms. METHODS Patients with SCZ (n = 64; mean age = 30.4 years, s.d. = 9.8), BPD (n = 91; mean age 31.0 years, s.d. = 10.2), and CTR (n = 155; mean age = 31.9 years, s.d. = 9.1) who participated in the TOP study (NORMENT, University of Oslo, Norway) were clinically assessed and scanned using a General Electric 3 T MRI system. T1w/T2w-ratio images were computed using an optimized pipeline with intensity normalization and field inhomogeneity correction. Vertex-wise regression models were used to compare groups and examine group × age interactions. In regions showing significant differences, we explored associations with antipsychotic medication use and psychotic symptoms. RESULTS No main effect of diagnosis was found. However, age slopes of the T1w/T2w-ratio differed significantly between SCZ and CTR, predominantly in frontal and temporal lobe regions: Lower T1w/T2w-ratio values with higher age were found in CTR, but not in SCZ. Follow-up analyses revealed a more positive age slope in patients who were using antipsychotics and patients using higher chlorpromazine-equivalent doses. CONCLUSIONS While we found no evidence of reduced intracortical myelin in SCZ or BPD relative to CTR, different regional age trajectories in SCZ may suggest a promyelinating effect of antipsychotic medication.
Collapse
Affiliation(s)
- Kjetil Nordbø Jørgensen
- The Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychiatry, Telemark Hospital, Skien, Norway
| | - Stener Nerland
- The Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - Nora Berz Slapø
- The Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Linn B Norbom
- The Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- Department of Psychology, PROMENTA Research Center, University of Oslo, Oslo, Norway
| | - Lynn Mørch-Johnsen
- The Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychiatry & Department of Clinical Research, Østfold Hospital, Grålum, Norway
| | - Laura Anne Wortinger
- The Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - Claudia Barth
- The Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
| | - Dimitrios Andreou
- The Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet, Stockholm, Sweden & Stockholm Health Care Services, Stockholm Region, Stockholm, Sweden
| | - Ivan I Maximov
- Department of Psychology, University of Oslo, Oslo, Norway
- The Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Department of Health and Functioning, Western Norway University of Applied Sciences, Bergen, Norway
| | - Oliver M Geier
- Department of Physics and Computational Radiology, Division of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Ole A Andreassen
- The Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- The Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Erik G Jönsson
- The Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet, Stockholm, Sweden & Stockholm Health Care Services, Stockholm Region, Stockholm, Sweden
| | - Ingrid Agartz
- The Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet, Stockholm, Sweden & Stockholm Health Care Services, Stockholm Region, Stockholm, Sweden
| |
Collapse
|
8
|
Wiltgen T, Voon C, Van Leemput K, Wiestler B, Mühlau M. Intensity scaling of conventional brain magnetic resonance images avoiding cerebral reference regions: A systematic review. PLoS One 2024; 19:e0298642. [PMID: 38483873 PMCID: PMC10939249 DOI: 10.1371/journal.pone.0298642] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Accepted: 01/26/2024] [Indexed: 03/17/2024] Open
Abstract
BACKGROUND Conventional brain magnetic resonance imaging (MRI) produces image intensities that have an arbitrary scale, hampering quantification. Intensity scaling aims to overcome this shortfall. As neurodegenerative and inflammatory disorders may affect all brain compartments, reference regions within the brain may be misleading. Here we summarize approaches for intensity scaling of conventional T1-weighted (w) and T2w brain MRI avoiding reference regions within the brain. METHODS Literature was searched in the databases of Scopus, PubMed, and Web of Science. We included only studies that avoided reference regions within the brain for intensity scaling and provided validating evidence, which we divided into four categories: 1) comparative variance reduction, 2) comparative correlation with clinical parameters, 3) relation to quantitative imaging, or 4) relation to histology. RESULTS Of the 3825 studies screened, 24 fulfilled the inclusion criteria. Three studies used scaled T1w images, 2 scaled T2w images, and 21 T1w/T2w-ratio calculation (with double counts). A robust reduction in variance was reported. Twenty studies investigated the relation of scaled intensities to different types of quantitative imaging. Statistically significant correlations with clinical or demographic data were reported in 8 studies. Four studies reporting the relation to histology gave no clear picture of the main signal driver of conventional T1w and T2w MRI sequences. CONCLUSIONS T1w/T2w-ratio calculation was applied most often. Variance reduction and correlations with other measures suggest a biologically meaningful signal harmonization. However, there are open methodological questions and uncertainty on its biological underpinning. Validation evidence on other scaling methods is even sparser.
Collapse
Affiliation(s)
- Tun Wiltgen
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Cuici Voon
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| | - Koen Van Leemput
- Department of Neuroscience and Biomedical Engineering, Aalto University Helsinki, Espoo, Finland
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Benedikt Wiestler
- Department of Neuroradiology, School of Medicine, Technical University of Munich, Munich, Germany
| | - Mark Mühlau
- Department of Neurology, School of Medicine, Technical University of Munich, Munich, Germany
- TUM-Neuroimaging Center, School of Medicine, Technical University of Munich, Munich, Germany
| |
Collapse
|
9
|
Boaventura M, Sastre-Garriga J, Rimkus CDM, Rovira À, Pareto D. T1/T2-weighted ratio: A feasible MRI biomarker in multiple sclerosis. Mult Scler 2024; 30:283-291. [PMID: 38389172 DOI: 10.1177/13524585241233448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/24/2024]
Abstract
T1/T2-weighted ratio is a novel magnetic resonance imaging (MRI) biomarker based on conventional sequences, related to microstructural integrity and with increasing use in multiple sclerosis (MS) research. Different from other advanced MRI techniques, this method has the advantage of being based on routinely acquired MRI sequences, a feature that enables analysis of retrospective cohorts with considerable clinical value. This article provides an overview of this method, describing the previous cross-sectional and longitudinal findings in the main MS clinical phenotypes and in different brain tissues: focal white matter (WM) lesions, normal-appearing white matter (NAWM), cortical gray matter (GM), and deep normal-appearing gray matter (NAGM). We also discuss the clinical associations, possible reasons for conflicting results, correlations with other MRI-based measures, and histopathological associations. We highlight the limitations of the biomarker itself and the methodology of each study. Finally, we update the reader on its potential use as an imaging biomarker in research.
Collapse
Affiliation(s)
| | - Jaume Sastre-Garriga
- Department of Neurology-Neuroimmunology, Multiple Sclerosis Centre of Catalonia (Cemcat), Barcelona, Spain
| | | | - Àlex Rovira
- Section of Neuroradiology. Department of Radiology (IDI). Vall d'Hebron University Hospital, Barcelona, Spain
| | - Deborah Pareto
- Section of Neuroradiology. Department of Radiology (IDI). Vall d'Hebron University Hospital, Barcelona, Spain
| |
Collapse
|
10
|
Tremblay SA, Alasmar Z, Pirhadi A, Carbonell F, Iturria-Medina Y, Gauthier CJ, Steele CJ. MVComp toolbox: MultiVariate Comparisons of brain MRI features accounting for common information across metrics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.27.582381. [PMID: 38463982 PMCID: PMC10925263 DOI: 10.1101/2024.02.27.582381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Multivariate approaches have recently gained in popularity to address the physiological unspecificity of neuroimaging metrics and to better characterize the complexity of biological processes underlying behavior. However, commonly used approaches are biased by the intrinsic associations between variables, or they are computationally expensive and may be more complicated to implement than standard univariate approaches. Here, we propose using the Mahalanobis distance (D2), an individual-level measure of deviation relative to a reference distribution that accounts for covariance between metrics. To facilitate its use, we introduce an open-source python-based tool for computing D2 relative to a reference group or within a single individual: the MultiVariate Comparison (MVComp) toolbox. The toolbox allows different levels of analysis (i.e., group- or subject-level), resolutions (e.g., voxel-wise, ROI-wise) and dimensions considered (e.g., combining MRI metrics or WM tracts). Several example cases are presented to showcase the wide range of possible applications of MVComp and to demonstrate the functionality of the toolbox. The D2 framework was applied to the assessment of white matter (WM) microstructure at 1) the group-level, where D2 can be computed between a subject and a reference group to yield an individualized measure of deviation. We observed that clustering applied to D2 in the corpus callosum yields parcellations that highly resemble known topography based on neuroanatomy, suggesting that D2 provides an integrative index that meaningfully reflects the underlying microstructure. 2) At the subject level, D2 was computed between voxels to obtain a measure of (dis)similarity. The loadings of each MRI metric (i.e., its relative contribution to D2) were then extracted in voxels of interest to showcase a useful option of the MVComp toolbox. These relative contributions can provide important insights into the physiological underpinnings of differences observed. Integrative multivariate models are crucial to expand our understanding of the complex brain-behavior relationships and the multiple factors underlying disease development and progression. Our toolbox facilitates the implementation of a useful multivariate method, making it more widely accessible.
Collapse
Affiliation(s)
- Stefanie A Tremblay
- Department of Physics, Concordia University, Montreal, Canada
- School of Health, Concordia University, Montreal, Canada
- EPIC Centre, Montreal Heart Institute, Montreal, Canada
| | - Zaki Alasmar
- School of Health, Concordia University, Montreal, Canada
- Department of Psychology, Concordia University, Montreal, Canada
| | - Amir Pirhadi
- Department of Electrical Engineering, Concordia University, Montreal, Canada
- ViTAA medical solutions, Montreal, Canada
| | | | - Yasser Iturria-Medina
- Neurology and Neurosurgery Department, Montreal Neurological Institute, McGill University, Montreal, Canada
- McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, Canada
- Ludmer Center for NeuroInformatics and Mental Health, Montreal, Canada
| | - Claudine J Gauthier
- Department of Physics, Concordia University, Montreal, Canada
- School of Health, Concordia University, Montreal, Canada
- EPIC Centre, Montreal Heart Institute, Montreal, Canada
| | - Christopher J Steele
- School of Health, Concordia University, Montreal, Canada
- Department of Psychology, Concordia University, Montreal, Canada
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| |
Collapse
|
11
|
Caffarra S, Kanopka K, Kruper J, Richie-Halford A, Roy E, Rokem A, Yeatman JD. Development of the Alpha Rhythm Is Linked to Visual White Matter Pathways and Visual Detection Performance. J Neurosci 2024; 44:e0684232023. [PMID: 38124006 PMCID: PMC11059423 DOI: 10.1523/jneurosci.0684-23.2023] [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: 04/14/2023] [Revised: 11/21/2023] [Accepted: 11/29/2023] [Indexed: 12/23/2023] Open
Abstract
Alpha is the strongest electrophysiological rhythm in awake humans at rest. Despite its predominance in the EEG signal, large variations can be observed in alpha properties during development, with an increase in alpha frequency over childhood and adulthood. Here, we tested the hypothesis that these changes in alpha rhythm are related to the maturation of visual white matter pathways. We capitalized on a large diffusion MRI (dMRI)-EEG dataset (dMRI n = 2,747, EEG n = 2,561) of children and adolescents of either sex (age range, 5-21 years old) and showed that maturation of the optic radiation specifically accounts for developmental changes of alpha frequency. Behavioral analyses also confirmed that variations of alpha frequency are related to maturational changes in visual perception. The present findings demonstrate the close link between developmental variations in white matter tissue properties, electrophysiological responses, and behavior.
Collapse
Affiliation(s)
- Sendy Caffarra
- Division of Developmental-Behavioral Pediatrics, Stanford University School of Medicine, Stanford 94305, California
- Stanford University Graduate School of Education, Stanford 94305, California
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena 41125, Italy
| | - Klint Kanopka
- Stanford University Graduate School of Education, Stanford 94305, California
| | - John Kruper
- Department of Psychology, University of Washington, Seattle 91905, Washington
- eScience Institute, University of Washington, Seattle 98195-1570, Washington
| | - Adam Richie-Halford
- Division of Developmental-Behavioral Pediatrics, Stanford University School of Medicine, Stanford 94305, California
- Stanford University Graduate School of Education, Stanford 94305, California
| | - Ethan Roy
- Stanford University Graduate School of Education, Stanford 94305, California
| | - Ariel Rokem
- Department of Psychology, University of Washington, Seattle 91905, Washington
- eScience Institute, University of Washington, Seattle 98195-1570, Washington
| | - Jason D Yeatman
- Division of Developmental-Behavioral Pediatrics, Stanford University School of Medicine, Stanford 94305, California
- Stanford University Graduate School of Education, Stanford 94305, California
| |
Collapse
|
12
|
Dipnall LM, Yang JYM, Chen J, Fuelscher I, Craig JM, Silk TJ. Childhood development of brain white matter myelin: a longitudinal T1w/T2w-ratio study. Brain Struct Funct 2024; 229:151-159. [PMID: 37982844 PMCID: PMC10827845 DOI: 10.1007/s00429-023-02718-8] [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: 06/25/2023] [Accepted: 09/27/2023] [Indexed: 11/21/2023]
Abstract
Myelination of human brain white matter (WM) continues into adulthood following birth, facilitating connection within and between brain networks. In vivo MRI studies using diffusion weighted imaging (DWI) suggest microstructural properties of brain WM increase over childhood and adolescence. Although DWI metrics, such as fractional anisotropy (FA), could reflect axonal myelination, they are not specific to myelin and could also represent other elements of WM microstructure, for example, fibre architecture, axon diameter and cell swelling. Little work exists specifically examining myelin development. The T1w/T2w ratio approach offers an alternative non-invasive method of estimating brain myelin. The approach uses MRI scans that are routinely part of clinical imaging and only require short acquisition times. Using T1w/T2w ratio maps from three waves of the Neuroimaging of the Children's Attention Project (NICAP) [N = 95 (208 scans); 44% female; ages 9.5-14.20 years] we aimed to investigate the developmental trajectories of brain white matter myelin in children as they enter adolescence. We also aimed to investigate whether longitudinal changes in myelination of brain WM differs between biological sex. Longitudinal regression modelling suggested non-linear increases in WM myelin brain wide. A positive parabolic, or U-shaped developmental trajectory was seen across 69 of 71 WM tracts modelled. At a corrected level, no significant effect for sex was found. These findings build on previous brain development research by suggesting that increases in brain WM microstructure from childhood to adolescence could be attributed to increases in myelin.
Collapse
Affiliation(s)
- Lillian M Dipnall
- School of Psychology and Centre for Social and Early Emotional Development (SEED), Deakin University, Geelong, Australia.
| | - Joseph Y M Yang
- Neuroscience Advanced Clinical Imaging Service (NACIS), Department of Neurosurgery, Royal Children's Hospital, Melbourne, VIC, Australia
- Murdoch Children's Research Institute, Melbourne, VIC, Australia
- Department of Paediatrics, University of Melbourne, Melbourne, VIC, Australia
| | - Jian Chen
- Murdoch Children's Research Institute, Melbourne, VIC, Australia
| | - Ian Fuelscher
- School of Psychology and Centre for Social and Early Emotional Development (SEED), Deakin University, Geelong, Australia
| | - Jeffrey M Craig
- School of Medicine and the Institute for Mental and Physical Health and Clinical Translation (IMPACT), Deakin University, Geelong, Australia
- Murdoch Children's Research Institute, Melbourne, VIC, Australia
- Department of Paediatrics, University of Melbourne, Melbourne, VIC, Australia
| | - Timothy J Silk
- School of Psychology and Centre for Social and Early Emotional Development (SEED), Deakin University, Geelong, Australia
- Murdoch Children's Research Institute, Melbourne, VIC, Australia
| |
Collapse
|
13
|
Lynch KM, Cabeen RP, Toga AW. Spatiotemporal patterns of cortical microstructural maturation in children and adolescents with diffusion MRI. Hum Brain Mapp 2024; 45:e26528. [PMID: 37994234 PMCID: PMC10789199 DOI: 10.1002/hbm.26528] [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: 07/06/2023] [Revised: 10/10/2023] [Accepted: 10/19/2023] [Indexed: 11/24/2023] Open
Abstract
Neocortical maturation is a dynamic process that proceeds in a hierarchical manner; however, the spatiotemporal organization of cortical microstructure with diffusion MRI has yet to be fully defined. This study characterized cortical microstructural maturation using diffusion MRI (fwe-diffusion tensor imaging [DTI] and neurite orientation dispersion and density imaging [NODDI] multicompartment modeling) in a cohort of 637 children and adolescents between 8 and 21 years of age. We found spatially heterogeneous developmental patterns broadly demarcated into functional domains where NODDI metrics increased, and fwe-DTI metrics decreased with age. By applying nonlinear growth models in a vertex-wise analysis, we observed a general posterior-to-anterior pattern of maturation, where the fwe-DTI measures mean diffusivity and radial diffusivity reached peak maturation earlier than the NODDI metrics neurite density index. Using non-negative matrix factorization, we found occipito-parietal cortical regions that correspond to lower order sensory domains mature earlier than fronto-temporal higher order association domains. Our findings corroborate previous histological and neuroimaging studies that show spatially varying patterns of cortical maturation that may reflect unique developmental processes of cytoarchitectonically determined regional patterns of change.
Collapse
Affiliation(s)
- Kirsten M. Lynch
- Laboratory of Neuro Imaging (LONI)USC Mark and Mary Stevens Institute for Neuroimaging and Informatics, USC Keck School of MedicineLos AngelesCaliforniaUSA
| | - Ryan P. Cabeen
- Laboratory of Neuro Imaging (LONI)USC Mark and Mary Stevens Institute for Neuroimaging and Informatics, USC Keck School of MedicineLos AngelesCaliforniaUSA
| | - Arthur W. Toga
- Laboratory of Neuro Imaging (LONI)USC Mark and Mary Stevens Institute for Neuroimaging and Informatics, USC Keck School of MedicineLos AngelesCaliforniaUSA
| |
Collapse
|
14
|
Serio B, Hettwer MD, Wiersch L, Bignardi G, Sacher J, Weis S, Eickhoff SB, Valk SL. Sex differences in intrinsic functional cortical organization reflect differences in network topology rather than cortical morphometry. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.23.568437. [PMID: 38045320 PMCID: PMC10690290 DOI: 10.1101/2023.11.23.568437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
Brain size robustly differs between sexes. However, the consequences of this anatomical dimorphism on sex differences in intrinsic brain function remain unclear. We investigated the extent to which sex differences in intrinsic cortical functional organization may be explained by differences in cortical morphometry, namely brain size, microstructure, and the geodesic distances of connectivity profiles. For this, we computed a low dimensional representation of functional cortical organization, the sensory-association axis, and identified widespread sex differences. Contrary to our expectations, observed sex differences in functional organization were not fundamentally associated with differences in brain size, microstructural organization, or geodesic distances, despite these morphometric properties being per se associated with functional organization and differing between sexes. Instead, functional sex differences in the sensory-association axis were associated with differences in functional connectivity profiles and network topology. Collectively, our findings suggest that sex differences in functional cortical organization extend beyond sex differences in cortical morphometry.
Collapse
Affiliation(s)
- Bianca Serio
- Max Planck School of Cognition, Leipzig, Germany
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Institute of Neuroscience and Medicine, Brain & Behavior (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany
| | - Meike D. Hettwer
- Max Planck School of Cognition, Leipzig, Germany
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Institute of Neuroscience and Medicine, Brain & Behavior (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany
| | - Lisa Wiersch
- Institute of Neuroscience and Medicine, Brain & Behavior (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany
| | - Giacomo Bignardi
- Max Planck School of Cognition, Leipzig, Germany
- Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
| | - Julia Sacher
- Max Planck School of Cognition, Leipzig, Germany
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Clinic for Cognitive Neurology, University Medical Center Leipzig, Leipzig, Germany
| | - Susanne Weis
- Institute of Neuroscience and Medicine, Brain & Behavior (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany
| | - Simon B. Eickhoff
- Max Planck School of Cognition, Leipzig, Germany
- Institute of Neuroscience and Medicine, Brain & Behavior (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany
| | - Sofie L. Valk
- Max Planck School of Cognition, Leipzig, Germany
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Institute of Neuroscience and Medicine, Brain & Behavior (INM-7), Research Centre Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany
| |
Collapse
|
15
|
Denis C, Dabbs K, Nair VA, Mathis J, Almane DN, Lakshmanan A, Nencka A, Birn RM, Conant L, Humphries C, Felton E, Raghavan M, DeYoe EA, Binder JR, Hermann B, Prabhakaran V, Bendlin BB, Meyerand ME, Boly M, Struck AF. T1-/T2-weighted ratio reveals no alterations to gray matter myelination in temporal lobe epilepsy. Ann Clin Transl Neurol 2023; 10:2149-2154. [PMID: 37872734 PMCID: PMC10647008 DOI: 10.1002/acn3.51653] [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: 02/04/2022] [Revised: 05/29/2022] [Accepted: 06/09/2022] [Indexed: 10/25/2023] Open
Abstract
Short-range functional connectivity in the limbic network is increased in patients with temporal lobe epilepsy (TLE), and recent studies have shown that cortical myelin content correlates with fMRI connectivity. We thus hypothesized that myelin may increase progressively in the epileptic network. We compared T1w/T2w gray matter myelin maps between TLE patients and age-matched controls and assessed relationships between myelin and aging. While both TLE patients and healthy controls exhibited increased T1w/T2w intensity with age, we found no evidence for significant group-level aberrations in overall myelin content or myelin changes through time in TLE.
Collapse
Affiliation(s)
- Colin Denis
- Department of NeurologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Kevin Dabbs
- Department of NeurologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Veena A. Nair
- Department of RadiologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Jedidiah Mathis
- Department of RadiologyMedical College of WisconsinMilwaukeeWisconsinUSA
| | - Dace N. Almane
- Department of NeurologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | | | - Andrew Nencka
- Department of RadiologyMedical College of WisconsinMilwaukeeWisconsinUSA
| | - Rasmus M. Birn
- Department of RadiologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
- Department of PsychiatryUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Lisa Conant
- Department of NeurologyMedical College of WisconsinMilwaukeeWisconsinUSA
| | - Colin Humphries
- Department of NeurologyMedical College of WisconsinMilwaukeeWisconsinUSA
| | - Elizabeth Felton
- Department of NeurologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Manoj Raghavan
- Department of NeurologyMedical College of WisconsinMilwaukeeWisconsinUSA
| | - Edgar A. DeYoe
- Department of RadiologyMedical College of WisconsinMilwaukeeWisconsinUSA
- Department of BiophysicsMedical College of WisconsinMilwaukeeWisconsinUSA
| | - Jeffrey R. Binder
- Department of NeurologyMedical College of WisconsinMilwaukeeWisconsinUSA
- Department of BiophysicsMedical College of WisconsinMilwaukeeWisconsinUSA
| | - Bruce Hermann
- Department of NeurologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Vivek Prabhakaran
- Department of RadiologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Barbara B. Bendlin
- Department of MedicineUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Mary E. Meyerand
- Department of Medical PhysicsUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
- Department of Biomedical EngineeringUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Mélanie Boly
- Department of NeurologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
- Department of PsychiatryUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Aaron F. Struck
- Department of NeurologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
- William S. Middleton Veterans Administration HospitalMadisonWisconsinUSA
| |
Collapse
|
16
|
Ford A, Ammar Z, Li L, Shultz S. Lateralization of major white matter tracts during infancy is time-varying and tract-specific. Cereb Cortex 2023; 33:10221-10233. [PMID: 37595203 PMCID: PMC10545441 DOI: 10.1093/cercor/bhad277] [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: 03/24/2023] [Revised: 07/08/2023] [Accepted: 07/10/2023] [Indexed: 08/20/2023] Open
Abstract
Lateralization patterns are a major structural feature of brain white matter and have been investigated as a neural architecture that indicates and supports the specialization of cognitive processing and observed behaviors, e.g. language skills. Many neurodevelopmental disorders have been associated with atypical lateralization, reinforcing the need for careful measurement and study of this structural characteristic. Unfortunately, there is little consensus on the direction and magnitude of lateralization in major white matter tracts during the first months and years of life-the period of most rapid postnatal brain growth and cognitive maturation. In addition, no studies have examined white matter lateralization in a longitudinal pediatric sample-preventing confirmation of if and how white matter lateralization changes over time. Using a densely sampled longitudinal data set from neurotypical infants aged 0-6 months, we aim to (i) chart trajectories of white matter lateralization in 9 major tracts and (ii) link variable findings from cross-sectional studies of white matter lateralization in early infancy. We show that patterns of lateralization are time-varying and tract-specific and that differences in lateralization results during this period may reflect the dynamic nature of lateralization through development, which can be missed in cross-sectional studies.
Collapse
Affiliation(s)
- Aiden Ford
- Neuroscience Program, Emory University, Atlanta, GA 30322, United States
- Marcus Autism Center, Children’s Healthcare of Atlanta, Atlanta, GA 30329, United States
| | - Zeena Ammar
- Neuroscience Program, Emory University, Atlanta, GA 30322, United States
- Marcus Autism Center, Children’s Healthcare of Atlanta, Atlanta, GA 30329, United States
| | - Longchuan Li
- Marcus Autism Center, Children’s Healthcare of Atlanta, Atlanta, GA 30329, United States
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA 30322, United States
| | - Sarah Shultz
- Neuroscience Program, Emory University, Atlanta, GA 30322, United States
- Marcus Autism Center, Children’s Healthcare of Atlanta, Atlanta, GA 30329, United States
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA 30322, United States
| |
Collapse
|
17
|
Fritz FJ, Mordhorst L, Ashtarayeh M, Periquito J, Pohlmann A, Morawski M, Jaeger C, Niendorf T, Pine KJ, Callaghan MF, Weiskopf N, Mohammadi S. Fiber-orientation independent component of R 2* obtained from single-orientation MRI measurements in simulations and a post-mortem human optic chiasm. Front Neurosci 2023; 17:1133086. [PMID: 37694109 PMCID: PMC10491021 DOI: 10.3389/fnins.2023.1133086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Accepted: 08/04/2023] [Indexed: 09/12/2023] Open
Abstract
The effective transverse relaxation rate (R2*) is sensitive to the microstructure of the human brain like the g-ratio which characterises the relative myelination of axons. However, the fibre-orientation dependence of R2* degrades its reproducibility and any microstructural derivative measure. To estimate its orientation-independent part (R2,iso*) from single multi-echo gradient-recalled-echo (meGRE) measurements at arbitrary orientations, a second-order polynomial in time model (hereafter M2) can be used. Its linear time-dependent parameter, β1, can be biophysically related to R2,iso* when neglecting the myelin water (MW) signal in the hollow cylinder fibre model (HCFM). Here, we examined the performance of M2 using experimental and simulated data with variable g-ratio and fibre dispersion. We found that the fitted β1 can estimate R2,iso* using meGRE with long maximum-echo time (TEmax ≈ 54 ms), but not accurately captures its microscopic dependence on the g-ratio (error 84%). We proposed a new heuristic expression for β1 that reduced the error to 12% for ex vivo compartmental R2 values. Using the new expression, we could estimate an MW fraction of 0.14 for fibres with negligible dispersion in a fixed human optic chiasm for the ex vivo compartmental R2 values but not for the in vivo values. M2 and the HCFM-based simulations failed to explain the measured R2*-orientation-dependence around the magic angle for a typical in vivo meGRE protocol (with TEmax ≈ 18 ms). In conclusion, further validation and the development of movement-robust in vivo meGRE protocols with TEmax ≈ 54 ms are required before M2 can be used to estimate R2,iso* in subjects.
Collapse
Affiliation(s)
- Francisco J. Fritz
- Department of Systems Neurosciences, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Laurin Mordhorst
- Department of Systems Neurosciences, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Mohammad Ashtarayeh
- Department of Systems Neurosciences, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Joao Periquito
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Andreas Pohlmann
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Markus Morawski
- Paul Flechsig Institute – Center for Neuropathology and Brain Research, University of Leipzig, Leipzig, Germany
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Carsten Jaeger
- Paul Flechsig Institute – Center for Neuropathology and Brain Research, University of Leipzig, Leipzig, Germany
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Thoralf Niendorf
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Kerrin J. Pine
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Martina F. Callaghan
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany
| | - Siawoosh Mohammadi
- Department of Systems Neurosciences, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Max Planck Research Group MR Physics, Max Planck Institute for Human Development, Berlin, Germany
| |
Collapse
|
18
|
Grotheer M, Bloom D, Kruper J, Richie-Halford A, Zika S, Aguilera González VA, Yeatman JD, Grill-Spector K, Rokem A. Human white matter myelinates faster in utero than ex utero. Proc Natl Acad Sci U S A 2023; 120:e2303491120. [PMID: 37549280 PMCID: PMC10438384 DOI: 10.1073/pnas.2303491120] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 06/27/2023] [Indexed: 08/09/2023] Open
Abstract
The formation of myelin, the fatty sheath that insulates nerve fibers, is critical for healthy brain function. A fundamental open question is what impact being born has on myelin growth. To address this, we evaluated a large (n = 300) cross-sectional sample of newborns from the Developing Human Connectome Project (dHCP). First, we developed software for the automated identification of 20 white matter bundles in individual newborns that is well suited for large samples. Next, we fit linear models that quantify how T1w/T2w (a myelin-sensitive imaging contrast) changes over time at each point along the bundles. We found faster growth of T1w/T2w along the lengths of all bundles before birth than right after birth. Further, in a separate longitudinal sample of preterm infants (N = 34), we found lower T1w/T2w than in full-term peers measured at the same age. By applying the linear models fit on the cross-section sample to the longitudinal sample of preterm infants, we find that their delay in T1w/T2w growth is well explained by the amount of time they spent developing in utero and ex utero. These results suggest that white matter myelinates faster in utero than ex utero. The reduced rate of myelin growth after birth, in turn, explains lower myelin content in individuals born preterm and could account for long-term cognitive, neurological, and developmental consequences of preterm birth. We hypothesize that closely matching the environment of infants born preterm to what they would have experienced in the womb may reduce delays in myelin growth and hence improve developmental outcomes.
Collapse
Affiliation(s)
- Mareike Grotheer
- Department of Psychology, Philipps-Universität Marburg, Marburg35039, Germany
- Center for Mind, Brain and Behavior, Philipps-Universität Marburg and Justus-Liebig-Universität Giessen, Marburg35039, Germany
| | - David Bloom
- Department of Psychology, University of Washington, Seattle, WA98105
- eScience Institute, University of Washington, Seattle, WA98105
| | - John Kruper
- Department of Psychology, University of Washington, Seattle, WA98105
- eScience Institute, University of Washington, Seattle, WA98105
| | - Adam Richie-Halford
- Department of Psychology, University of Washington, Seattle, WA98105
- eScience Institute, University of Washington, Seattle, WA98105
| | - Stephanie Zika
- Department of Psychology, Philipps-Universität Marburg, Marburg35039, Germany
- Center for Mind, Brain and Behavior, Philipps-Universität Marburg and Justus-Liebig-Universität Giessen, Marburg35039, Germany
| | - Vicente A. Aguilera González
- Department of Psychology, Philipps-Universität Marburg, Marburg35039, Germany
- Center for Mind, Brain and Behavior, Philipps-Universität Marburg and Justus-Liebig-Universität Giessen, Marburg35039, Germany
| | - Jason D. Yeatman
- Department of Psychology, Stanford University, Stanford, CA94305
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA94305
- Graduate School of Education, Stanford University, Stanford, CA94305
- Division of Developmental-Behavioral Pediatrics, Stanford University School of Medicine, Stanford, CA94305
| | - Kalanit Grill-Spector
- Department of Psychology, Stanford University, Stanford, CA94305
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA94305
| | - Ariel Rokem
- Department of Psychology, University of Washington, Seattle, WA98105
- eScience Institute, University of Washington, Seattle, WA98105
| |
Collapse
|
19
|
Endt S, Engel M, Naldi E, Assereto R, Molendowska M, Mueller L, Mayrink Verdun C, Pirkl CM, Palombo M, Jones DK, Menzel MI. In Vivo Myelin Water Quantification Using Diffusion-Relaxation Correlation MRI: A Comparison of 1D and 2D Methods. APPLIED MAGNETIC RESONANCE 2023; 54:1571-1588. [PMID: 38037641 PMCID: PMC10682074 DOI: 10.1007/s00723-023-01584-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 07/18/2023] [Accepted: 07/25/2023] [Indexed: 12/02/2023]
Abstract
Multidimensional Magnetic Resonance Imaging (MRI) is a versatile tool for microstructure mapping. We use a diffusion weighted inversion recovery spin echo (DW-IR-SE) sequence with spiral readouts at ultra-strong gradients to acquire a rich diffusion-relaxation data set with sensitivity to myelin water. We reconstruct 1D and 2D spectra with a two-step convex optimization approach and investigate a variety of multidimensional MRI methods, including 1D multi-component relaxometry, 1D multi-component diffusometry, 2D relaxation correlation imaging, and 2D diffusion-relaxation correlation spectroscopic imaging (DR-CSI), in terms of their potential to quantify tissue microstructure, including the myelin water fraction (MWF). We observe a distinct spectral peak that we attribute to myelin water in multi-component T1 relaxometry, T1-T2 correlation, T1-D correlation, and T2-D correlation imaging. Due to lower achievable echo times compared to diffusometry, MWF maps from relaxometry have higher quality. Whilst 1D multi-component T1 data allows much faster myelin mapping, 2D approaches could offer unique insights into tissue microstructure and especially myelin diffusion.
Collapse
Affiliation(s)
- Sebastian Endt
- Technical University of Munich, Munich, Germany
- AImotion Bavaria, Technische Hochschule Ingolstadt, Ingolstadt, Germany
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
| | - Maria Engel
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
| | - Emanuele Naldi
- Technische Universität Braunschweig, Braunschweig, Germany
| | | | - Malwina Molendowska
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
- Medical Radiation Physics, Lund University, Lund, Sweden
| | - Lars Mueller
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
- Biomedical Imaging Science Department, Leeds Institute of Cardiovascular and Metabolic Medicine (LICAMM), University of Leeds, Leeds, United Kingdom
| | - Claudio Mayrink Verdun
- Technical University of Munich, Munich, Germany
- Munich Center for Machine Learning, Munich, Germany
| | | | - Marco Palombo
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
| | - Derek K. Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, United Kingdom
| | - Marion I. Menzel
- Technical University of Munich, Munich, Germany
- AImotion Bavaria, Technische Hochschule Ingolstadt, Ingolstadt, Germany
- GE HealthCare, Munich, Germany
| |
Collapse
|
20
|
Voldsbekk I, Kjelkenes R, Dahl A, Holm MC, Lund MJ, Kaufmann T, Tamnes CK, Andreassen OA, Westlye LT, Alnæs D. Delineating disorder-general and disorder-specific dimensions of psychopathology from functional brain networks in a developmental clinical sample. Dev Cogn Neurosci 2023; 62:101271. [PMID: 37348146 PMCID: PMC10439505 DOI: 10.1016/j.dcn.2023.101271] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 06/09/2023] [Accepted: 06/18/2023] [Indexed: 06/24/2023] Open
Abstract
The interplay between functional brain network maturation and psychopathology during development remains elusive. To establish the structure of psychopathology and its neurobiological mechanisms, mapping of both shared and unique functional connectivity patterns across developmental clinical populations is needed. We investigated shared associations between resting-state functional connectivity and psychopathology in children and adolescents aged 5-21 (n = 1689). Specifically, we used partial least squares (PLS) to identify latent variables (LV) between connectivity and both symptom scores and diagnostic information. We also investigated associations between connectivity and each diagnosis specifically, controlling for other diagnosis categories. PLS identified five significant LVs between connectivity and symptoms, mapping onto the psychopathology hierarchy. The first LV resembled a general psychopathology factor, followed by dimensions of internalising- externalising, neurodevelopment, somatic complaints, and thought problems. Another PLS with diagnostic data revealed one significant LV, resembling a cross-diagnostic case-control pattern. The diagnosis-specific PLS identified a unique connectivity pattern for autism spectrum disorder (ASD). All LVs were associated with distinct patterns of functional connectivity. These dimensions largely replicated in an independent sample (n = 420) from the same dataset, as well as to an independent cohort (n = 3504). This suggests that covariance in developmental functional brain networks supports transdiagnostic dimensions of psychopathology.
Collapse
Affiliation(s)
- Irene Voldsbekk
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, & Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway; Department of Psychology, University of Oslo, Oslo, Norway.
| | - Rikka Kjelkenes
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, & Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway; Department of Psychology, University of Oslo, Oslo, Norway
| | - Andreas Dahl
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, & Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway; Department of Psychology, University of Oslo, Oslo, Norway
| | - Madelene C Holm
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, & Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway; Department of Psychology, University of Oslo, Oslo, Norway
| | - Martina J Lund
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, & Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Tobias Kaufmann
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, & Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway; Department of Psychiatry and Psychotherapy, University of Tübingen, Germany
| | - Christian K Tamnes
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, & Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway; Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway; PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, & Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, & Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Lars T Westlye
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, & Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway; Department of Psychology, University of Oslo, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, & Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Dag Alnæs
- Norwegian Centre for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo, & Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway; Kristiania University College, Oslo, Norway
| |
Collapse
|
21
|
Boroshok AL, McDermott CL, Fotiadis P, Park AT, Tooley UA, Gataviņš MM, Tisdall MD, Bassett DS, Mackey AP. Individual differences in T1w/T2w ratio development during childhood. Dev Cogn Neurosci 2023; 62:101270. [PMID: 37348147 PMCID: PMC10439503 DOI: 10.1016/j.dcn.2023.101270] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 05/12/2023] [Accepted: 06/15/2023] [Indexed: 06/24/2023] Open
Abstract
Myelination is a key developmental process that promotes rapid and efficient information transfer. Myelin also stabilizes existing brain networks and thus may constrain neuroplasticity, defined here as the brain's potential to change in response to experiences rather than the canonical definition as the process of change. Characterizing individual differences in neuroplasticity may shed light on mechanisms by which early experiences shape learning, brain and body development, and response to interventions. The T1-weighted/T2-weighted (T1w/T2w) MRI signal ratio is a proxy measure of cortical microstructure and thus neuroplasticity. Here, in pre-registered analyses, we investigated individual differences in T1w/T2w ratios in children (ages 4-10, n = 157). T1w/T2w ratios were positively associated with age within early-developing sensorimotor and attention regions. We also tested whether socioeconomic status, cognition (crystallized knowledge or fluid reasoning), and biological age (as measured with molar eruption) were related to T1w/T2w signal but found no significant effects. Associations among T1w/T2w ratios, early experiences, and cognition may emerge later in adolescence and may not be strong enough to detect in moderate sample sizes.
Collapse
Affiliation(s)
- Austin L Boroshok
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA.
| | | | - Panagiotis Fotiadis
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA
| | - Anne T Park
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA
| | - Ursula A Tooley
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA; Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA; Department of Psychiatry, Washington University in St. Louis, USA; Department of Neurology, Washington University in St. Louis, USA
| | - Mārtiņš M Gataviņš
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA
| | - M Dylan Tisdall
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Dani S Bassett
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA; Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA; Department of Electrical & Systems Engineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA; Department of Physics & Astronomy, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, USA; Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Santa Fe Institute, Santa Fe, NM, USA
| | - Allyson P Mackey
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA; Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA
| |
Collapse
|
22
|
Figley CR, Figley TD, Wong K, Uddin MN, Dalvit Carvalho da Silva R, Kornelsen J. Periventricular and juxtacortical characterization of UManitoba-JHU functionally defined human white matter atlas networks. Front Hum Neurosci 2023; 17:1196624. [PMID: 37484918 PMCID: PMC10357038 DOI: 10.3389/fnhum.2023.1196624] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Accepted: 06/22/2023] [Indexed: 07/25/2023] Open
Abstract
Background The open-access UManitoba-JHU functionally defined human white matter (WM) atlas contains specific WM pathways and general WM regions underlying 12 functional brain networks in ICBM152 template space. However, it is not known whether any of these WM networks are disproportionately co-localized with periventricular and/or juxtacortical WM (PVWM and JCWM), which could potentially impact their ability to infer network-specific effects in future studies-particularly in patient populations expected to have disproportionate PVWM and/or JCWM damage. Methods The current study therefore identified intersecting regions of PVWM and JCWM (defined as WM within 5 mm of the ventricular and cortical boundaries) and: (1) the ICBM152 global WM mask, and (2) all 12 UManitoba-JHU WM networks. Dice Similarity Coefficient (DSC), Jaccard Similarity Coefficient (JSC), and proportion of volume (POV) values between PVWM (and JCWM) and each functionally defined WM network were then compared to corresponding values between PVWM (and JCWM) and global WM. Results Between the 12 WM networks and PVWM, 8 had lower DSC, JSC, and POV; 1 had lower DSC and JSC, but higher POV; and 3 had higher DSC, JSC, and POV compared to global WM. For JCWM, all 12 WM networks had lower DSC, JSC, and POV compared to global WM. Conclusion The majority of UManitoba-JHU functionally defined WM networks exhibited lower than average spatial similarity with PVWM, and all exhibited lower than average spatial similarity with JCWM. This suggests that they can be used to explore network-specific WM changes, even in patient populations with known predispositions toward PVWM and/or JCWM damage.
Collapse
Affiliation(s)
- Chase R. Figley
- Department of Radiology, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg, MB, Canada
- Department of Physiology and Pathophysiology, University of Manitoba, Winnipeg, MB, Canada
| | - Teresa D. Figley
- Department of Radiology, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg, MB, Canada
| | - Kaihim Wong
- Department of Radiology, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg, MB, Canada
| | - Md Nasir Uddin
- Department of Radiology, University of Manitoba, Winnipeg, MB, Canada
- Department of Neurology, University of Rochester, Rochester, NY, United States
- Department of Biomedical Engineering, University of Rochester, Rochester, NY, United States
| | - Rodrigo Dalvit Carvalho da Silva
- Department of Radiology, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg, MB, Canada
| | - Jennifer Kornelsen
- Department of Radiology, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg, MB, Canada
- Department of Physiology and Pathophysiology, University of Manitoba, Winnipeg, MB, Canada
| |
Collapse
|
23
|
Oh J, Crockett RA, Hsu CL, Dao E, Tam R, Liu-Ambrose T. Resistance Training Maintains White Matter and Physical Function in Older Women with Cerebral Small Vessel Disease: An Exploratory Analysis of a Randomized Controlled Trial. J Alzheimers Dis Rep 2023; 7:627-639. [PMID: 37483319 PMCID: PMC10357123 DOI: 10.3233/adr-220113] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Accepted: 05/17/2023] [Indexed: 07/25/2023] Open
Abstract
Background As the aging population grows, there is an increasing need to develop accessible interventions against risk factors for cognitive impairment and dementia, such as cerebral small vessel disease (CSVD). The progression of white matter hyperintensities (WMHs), a key hallmark of CSVD, can be slowed by resistance training (RT). We hypothesize RT preserves white matter integrity and that this preservation is associated with improved cognitive and physical function. Objective To determine if RT preserves regional white matter integrity and if any changes are associated with cognitive and physical outcomes. Methods Using magnetic resonance imaging data from a 12-month randomized controlled trial, we compared the effects of a twice-weekly 60-minute RT intervention versus active control on T1-weighted over T2-weighted ratio (T1w/T2w; a non-invasive proxy measure of white matter integrity) in a subset of study participants (N = 21 females, mean age = 69.7 years). We also examined the association between changes in T1w/T2w with two key outcomes of the parent study: (1) selective attention and conflict resolution, and (2) peak muscle power. Results Compared with an active control group, RT increased T1w/T2w in the external capsule (p = 0.024) and posterior thalamic radiations (p = 0.013) to a greater degree. Increased T1w/T2w in the external capsule was associated with an increase in peak muscle power (p = 0.043) in the RT group. Conclusion By maintaining white matter integrity, RT may be a promising intervention to counteract the pathological changes that accompany CSVD, while improving functional outcomes such as muscle power.
Collapse
Affiliation(s)
- Jean Oh
- Aging, Mobility, and Cognitive Health Laboratory, University of British Columbia, Vancouver, Canada
| | - Rachel A. Crockett
- Aging, Mobility, and Cognitive Health Laboratory, University of British Columbia, Vancouver, Canada
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
- Djavad Mowafaghian Centre for Brain Health, Vancouver Coastal Health Research Institute, University of British Columbia, Vancouver, Canada
- Department of Physical Therapy, University of British Columbia, Vancouver, Canada
- Centre for SMART Aging at Vancouver Coastal Health, Vancouver Coastal Health Research Institute, Vancouver, Canada
| | - Chun-Liang Hsu
- Aging, Mobility, and Cognitive Health Laboratory, University of British Columbia, Vancouver, Canada
- Department of Rehabilitation Sciences, Hong Kong Polytechnic University, Hung Hom, Hong Kong
- Djavad Mowafaghian Centre for Brain Health, Vancouver Coastal Health Research Institute, University of British Columbia, Vancouver, Canada
- Department of Physical Therapy, University of British Columbia, Vancouver, Canada
- Centre for SMART Aging at Vancouver Coastal Health, Vancouver Coastal Health Research Institute, Vancouver, Canada
| | - Elizabeth Dao
- Djavad Mowafaghian Centre for Brain Health, Vancouver Coastal Health Research Institute, University of British Columbia, Vancouver, Canada
- Department of Radiology, University of British Columbia, Vancouver, Canada
- Centre for SMART Aging at Vancouver Coastal Health, Vancouver Coastal Health Research Institute, Vancouver, Canada
| | - Roger Tam
- Djavad Mowafaghian Centre for Brain Health, Vancouver Coastal Health Research Institute, University of British Columbia, Vancouver, Canada
- School of Biomedical Engineering, University of British Columbia, Vancouver, Canada
- Department of Radiology, University of British Columbia, Vancouver, Canada
- Centre for SMART Aging at Vancouver Coastal Health, Vancouver Coastal Health Research Institute, Vancouver, Canada
| | - Teresa Liu-Ambrose
- Aging, Mobility, and Cognitive Health Laboratory, University of British Columbia, Vancouver, Canada
- Djavad Mowafaghian Centre for Brain Health, Vancouver Coastal Health Research Institute, University of British Columbia, Vancouver, Canada
- Department of Physical Therapy, University of British Columbia, Vancouver, Canada
- Centre for SMART Aging at Vancouver Coastal Health, Vancouver Coastal Health Research Institute, Vancouver, Canada
| |
Collapse
|
24
|
Filimonova E, Ovsiannikov K, Zaitsev B, Rzaev J. T1w/T2w ratio is associated with the brush sign and perfusion delay in watershed regions in patients with moyamoya angiopathy. Clin Neurol Neurosurg 2023; 231:107821. [PMID: 37302378 DOI: 10.1016/j.clineuro.2023.107821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 05/24/2023] [Accepted: 06/04/2023] [Indexed: 06/13/2023]
Abstract
BACKGROUND It has been shown recently using the T1w/T2w mapping technique that white matter microstructural integrity impairments exist in watershed regions patients with moyamoya angiopathy (MMA). We hypothesized that these changes could be associated with the prominence of other neuroimaging markers of chronic brain ischemia, such as perfusion delay and the brush sign. METHODS Thirteen adult patients with MMA (24 affected hemispheres) were evaluated using brain MRI and CT perfusion. The T1w/T2w signal intensity ratio, which reflects white matter integrity, was calculated in watershed regions (centrum semiovale and middle frontal gyrus). Brush sign prominence was evaluated with susceptibility-weighted MRI. Additionally, brain perfusion parameters such as cerebral blood flow (CBF), cerebral blood volume (CBF), and mean transit time (MTT) were assessed. Correlations between white matter integrity and perfusion changes in watershed regions, as well as the prominence of the brush sign, were evaluated. RESULTS Statistically significant negative correlations between the prominence of the brush sign and the T1w/T2w ratio values from the centrum semiovale and middle frontal white matter were found (R = -0.62 to 0.71, adjusted p < 0.05). Furthermore, there was a positive correlation between the T1w/T2w ratio values and the MTT values from the centrum semiovale (R = 0.65, adjusted p < 0.05). CONCLUSIONS We revealed that T1w/T2w ratio changes are associated with the prominence of the brush sign as well as white matter hypoperfusion in watershed regions in patients with MMA. This could be explained by chronic ischemia due to venous congestion in the deep medullary vein territory.
Collapse
Affiliation(s)
- E Filimonova
- Federal Center of Neurosurgery Novosibirsk, Nemirovich-Danchenko Str. 132/1, Novosibirsk 630087, Russia; Novosibirsk State Medical University, Krasny Prospect St. 52, Novosibirsk 630091, Russia.
| | - K Ovsiannikov
- Federal Center of Neurosurgery Novosibirsk, Nemirovich-Danchenko Str. 132/1, Novosibirsk 630087, Russia; Department of Neuroscience, Institute of Medicine and Psychology, Novosibirsk State University, Pirogov Str. 1, Novosibirsk 630090, Russia
| | - B Zaitsev
- Federal Center of Neurosurgery Novosibirsk, Nemirovich-Danchenko Str. 132/1, Novosibirsk 630087, Russia
| | - J Rzaev
- Federal Center of Neurosurgery Novosibirsk, Nemirovich-Danchenko Str. 132/1, Novosibirsk 630087, Russia; Novosibirsk State Medical University, Krasny Prospect St. 52, Novosibirsk 630091, Russia; Department of Neuroscience, Institute of Medicine and Psychology, Novosibirsk State University, Pirogov Str. 1, Novosibirsk 630090, Russia
| |
Collapse
|
25
|
Rocca MA, Margoni M, Battaglini M, Eshaghi A, Iliff J, Pagani E, Preziosa P, Storelli L, Taoka T, Valsasina P, Filippi M. Emerging Perspectives on MRI Application in Multiple Sclerosis: Moving from Pathophysiology to Clinical Practice. Radiology 2023; 307:e221512. [PMID: 37278626 PMCID: PMC10315528 DOI: 10.1148/radiol.221512] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 11/28/2022] [Accepted: 01/17/2023] [Indexed: 06/07/2023]
Abstract
MRI plays a central role in the diagnosis of multiple sclerosis (MS) and in the monitoring of disease course and treatment response. Advanced MRI techniques have shed light on MS biology and facilitated the search for neuroimaging markers that may be applicable in clinical practice. MRI has led to improvements in the accuracy of MS diagnosis and a deeper understanding of disease progression. This has also resulted in a plethora of potential MRI markers, the importance and validity of which remain to be proven. Here, five recent emerging perspectives arising from the use of MRI in MS, from pathophysiology to clinical application, will be discussed. These are the feasibility of noninvasive MRI-based approaches to measure glymphatic function and its impairment; T1-weighted to T2-weighted intensity ratio to quantify myelin content; classification of MS phenotypes based on their MRI features rather than on their clinical features; clinical relevance of gray matter atrophy versus white matter atrophy; and time-varying versus static resting-state functional connectivity in evaluating brain functional organization. These topics are critically discussed, which may guide future applications in the field.
Collapse
Affiliation(s)
- Maria Assunta Rocca
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Monica Margoni
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Marco Battaglini
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Arman Eshaghi
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Jeffrey Iliff
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Elisabetta Pagani
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Paolo Preziosa
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Loredana Storelli
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Toshiaki Taoka
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Paola Valsasina
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Massimo Filippi
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| |
Collapse
|
26
|
Morris SR, Vavasour IM, Smolina A, MacMillan EL, Gilbert G, Lam M, Kozlowski P, Michal CA, Manning A, MacKay AL, Laule C. Myelin biomarkers in the healthy adult brain: Correlation, reproducibility, and the effect of fiber orientation. Magn Reson Med 2023; 89:1809-1824. [PMID: 36511247 DOI: 10.1002/mrm.29552] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 10/17/2022] [Accepted: 11/18/2022] [Indexed: 12/15/2022]
Abstract
PURPOSE We investigated the correlation, reproducibility, and effect of white matter fiber orientation for three myelin-sensitive MRI techniques: magnetization transfer ratio (MTR), inhomogeneous magnetization transfer ratio (ihMTR), and gradient and spin echo-derived myelin water fraction (MWF). METHODS We measured the three metrics in 17 white and three deep grey matter regions in 17 healthy adults at 3 T. RESULTS We found a strong correlation between ihMTR and MTR (r = 0.70, p < 0.001) and ihMTR and MWF (r = 0.79, p < 0.001), and a weaker correlation between MTR and MWF (r = 0.54, p < 0.001). The dynamic range in white matter was greatest for MWF (2.0%-27.5%), followed by MTR (14.4%-23.2%) and then ihMTR (1.2%-5.4%). The average scan-rescan coefficient of variation for white matter regions was 0.6% MTR, 0.3% ihMTR, and 0.7% MWF in metric units; however, when adjusted by the dynamic range, these became 6.3%, 6.1% and 2.8%, respectively. All three metrics varied with fiber direction: MWF and ihMTR were lower in white matter fibers perpendicular to B0 by 6% and 1%, respectively, compared with those parallel, whereas MTR was lower by 0.5% at about 40°, with the highest values at 90°. However, separating the apparent orientation dependence by white matter region revealed large dissimilarities in the trends, suggesting that real differences in myelination between regions are confounding the apparent orientation dependence measured using this method. CONCLUSION The strong correlation between ihMTR and MWF suggests that these techniques are measuring the same myelination; however, the larger dynamic range of MWF may provide more power to detect small differences in myelin.
Collapse
Affiliation(s)
- Sarah R Morris
- Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,Physics & Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, British Columbia, Canada
| | - Irene M Vavasour
- Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, British Columbia, Canada.,UBC MRI Research Center, University of British Columbia, Vancouver, British Columbia, Canada
| | - Anastasia Smolina
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.,The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Erin L MacMillan
- Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,UBC MRI Research Center, University of British Columbia, Vancouver, British Columbia, Canada.,MR Clinical Science, Philips Healthcare Canada, Mississauga, Ontario, Canada
| | - Guillaume Gilbert
- MR Clinical Science, Philips Healthcare Canada, Mississauga, Ontario, Canada
| | - Michelle Lam
- Physics & Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,UBC MRI Research Center, University of British Columbia, Vancouver, British Columbia, Canada
| | - Piotr Kozlowski
- Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,Physics & Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, British Columbia, Canada.,UBC MRI Research Center, University of British Columbia, Vancouver, British Columbia, Canada
| | - Carl A Michal
- Physics & Astronomy, University of British Columbia, Vancouver, British Columbia, Canada
| | - Alan Manning
- Physics & Astronomy, University of British Columbia, Vancouver, British Columbia, Canada
| | - Alex L MacKay
- Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,Physics & Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,UBC MRI Research Center, University of British Columbia, Vancouver, British Columbia, Canada
| | - Cornelia Laule
- Radiology, University of British Columbia, Vancouver, British Columbia, Canada.,Physics & Astronomy, University of British Columbia, Vancouver, British Columbia, Canada.,International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, British Columbia, Canada.,UBC MRI Research Center, University of British Columbia, Vancouver, British Columbia, Canada.,Pathology & Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada
| |
Collapse
|
27
|
Laporte JP, Faulkner ME, Gong Z, Palchamy E, Akhonda MA, Bouhrara M. Investigation of the association between central arterial stiffness and aggregate g-ratio in cognitively unimpaired adults. Front Neurol 2023; 14:1170457. [PMID: 37181577 PMCID: PMC10167487 DOI: 10.3389/fneur.2023.1170457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Accepted: 04/03/2023] [Indexed: 05/16/2023] Open
Abstract
Stiffness of the large arteries has been shown to impact cerebral white matter (WM) microstructure in both younger and older adults. However, no study has yet demonstrated an association between arterial stiffness and aggregate g-ratio, a specific magnetic resonance imaging (MRI) measure of axonal myelination that is highly correlated with neuronal signal conduction speed. In a cohort of 38 well-documented cognitively unimpaired adults spanning a wide age range, we investigated the association between central arterial stiffness, measured using pulse wave velocity (PWV), and aggregate g-ratio, measured using our recent advanced quantitative MRI methodology, in several cerebral WM structures. After adjusting for age, sex, smoking status, and systolic blood pressure, our results indicate that higher PWV values, that is, elevated arterial stiffness, were associated with lower aggregate g-ratio values, that is, lower microstructural integrity of WM. Compared to other brain regions, these associations were stronger and highly significant in the splenium of the corpus callosum and the internal capsules, which have been consistently documented as very sensitive to elevated arterial stiffness. Moreover, our detailed analysis indicates that these associations were mainly driven by differences in myelination, measured using myelin volume fraction, rather than axonal density, measured using axonal volume fraction. Our findings suggest that arterial stiffness is associated with myelin degeneration, and encourages further longitudinal studies in larger study cohorts. Controlling arterial stiffness may represent a therapeutic target in maintaining the health of WM tissue in cerebral normative aging.
Collapse
Affiliation(s)
| | | | | | | | | | - Mustapha Bouhrara
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States
| |
Collapse
|
28
|
Kilpatrick L, Zhang K, Dong T, Gee G, Beltran-Sanchez H, Wang M, Labus J, Naliboff B, Mayer E, Gupta A. Mediating role of obesity on the association between disadvantaged neighborhoods and intracortical myelination. RESEARCH SQUARE 2023:rs.3.rs-2592087. [PMID: 36993600 PMCID: PMC10055549 DOI: 10.21203/rs.3.rs-2592087/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
We investigated the relationship between neighborhood disadvantage (area deprivation index [ADI]) and intracortical myelination (T1-weighted/T2-weighted ratio at deep to superficial cortical levels), and the potential mediating role of the body mass index (BMI) and perceived stress in 92 adults. Worse ADI was correlated with increased BMI and perceived stress (p's<.05). Non-rotated partial least squares analysis revealed associations between worse ADI and decreased myelination in middle/deep cortex in supramarginal, temporal, and primary motor regions and increased myelination in superficial cortex in medial prefrontal and cingulate regions (p<.001); thus, neighborhood disadvantage may influence the flexibility of information processing involved in reward, emotion regulation, and cognition. Structural equation modelling revealed increased BMI as partially mediating the relationship between worse ADI and observed myelination increases (p=.02). Further, trans-fatty acid intake was correlated with observed myelination increases (p=.03), suggesting the importance of dietary quality. These data further suggest ramifications of neighborhood disadvantage on brain health.
Collapse
Affiliation(s)
| | | | - Tien Dong
- University of California Los Angeles
| | | | | | - May Wang
- University of California Los Angeles
| | | | | | | | | |
Collapse
|
29
|
Bero J, Li Y, Kumar A, Humphries C, Nag S, Lee H, Ahn WY, Hahn S, Constable RT, Kim H, Lee D. Coordinated anatomical and functional variability in the human brain during adolescence. Hum Brain Mapp 2023; 44:1767-1778. [PMID: 36479851 PMCID: PMC9921246 DOI: 10.1002/hbm.26173] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2022] [Revised: 10/26/2022] [Accepted: 11/25/2022] [Indexed: 12/13/2022] Open
Abstract
Adolescence represents a time of unparalleled brain development. In particular, developmental changes in morphometric and cytoarchitectural features are accompanied by maturation in the functional connectivity (FC). Here, we examined how three facets of the brain, including myelination, cortical thickness (CT), and resting-state FC, interact in children between the ages of 10 and 15. We investigated the pattern of coordination in these measures by computing correlation matrices for each measure as well as meta-correlations among them both at the regional and network levels. The results revealed consistently higher meta-correlations among myelin, CT, and FC in the sensory-motor cortical areas than in the association cortical areas. We also found that these meta-correlations were stable and little affected by age-related changes in each measure. In addition, regional variations in the meta-correlations were consistent with the previously identified gradient in the FC and therefore reflected the hierarchy of cortical information processing, and this relationship persists in the adult brain. These results demonstrate that heterogeneity in FC among multiple cortical areas are closely coordinated with the development of cortical myelination and thickness during adolescence.
Collapse
Affiliation(s)
- John Bero
- Neurogazer, Inc.BaltimoreMarylandUSA
| | - Yang Li
- Neurogazer, Inc.BaltimoreMarylandUSA
| | | | | | | | | | - Woo Young Ahn
- Department of PsychologySeoul National UniversitySeoulKorea
| | - Sowon Hahn
- Department of PsychologySeoul National UniversitySeoulKorea
| | - Robert Todd Constable
- Department of Diagnostic Radiology and NeurosurgeryYale School of MedicineNew HavenConnecticutUSA
| | - Hackjin Kim
- Department of PsychologyKorea UniversitySeoulKorea
| | - Daeyeol Lee
- Neurogazer, Inc.BaltimoreMarylandUSA
- The Zanvyl Krieger Mind/Brain Institute, Johns Hopkins UniversityBaltimoreMarylandUSA
- Department of NeuroscienceJohns Hopkins UniversityBaltimoreMarylandUSA
- Department of Psychological and Brain SciencesJohns Hopkins UniversityBaltimoreMarylandUSA
- Kavli Neuroscience Discovery Institute, Johns Hopkins UniversityBaltimoreMarylandUSA
| |
Collapse
|
30
|
Malakshan SR, Daneshvarfard F, Abrishami Moghaddam H. A correlational study between microstructural, macrostructural and functional age-related changes in the human visual cortex. PLoS One 2023; 18:e0266206. [PMID: 36662780 PMCID: PMC9858032 DOI: 10.1371/journal.pone.0266206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 12/27/2022] [Indexed: 01/21/2023] Open
Abstract
Age-related changes in the human brain can be investigated from either structural or functional perspectives. Analysis of structural and functional age-related changes throughout the lifespan may help to understand the normal brain development process and monitor the structural and functional pathology of the brain. This study, combining dedicated electroencephalography (EEG) and magnetic resonance imaging (MRI) approaches in adults (20-78 years), highlights the complex relationship between micro/macrostructural properties and the functional responses to visual stimuli. Here, we aimed to relate age-related changes of the latency of visual evoked potentials (VEPs) to micro/macrostructural indexes and find any correlation between micro/macrostructural features, as well. We studied age-related structural changes in the brain, by using the MRI and diffusion-weighted imaging (DWI) as preferred imaging methods for extracting brain macrostructural parameters such as the cortical thickness, surface area, folding and curvature index, gray matter volume, and microstructural parameters such as mean diffusivity (MD), radial diffusivity (RD) and axial diffusivity (AD). All the mentioned features were significantly correlated with age in V1 and V2 regions of the visual cortex. Furthermore, we highlighted, negative correlations between structural features extracted from T1-weighted images and DWI. The latency and amplitude of the three dominants peaks (C1, P1, N1) of the VEP were considered as the brain functional features to be examined for correlation with age and structural features of the corresponding age. We observed significant correlations between mean C1 latency and GM volume averaged in V1 and V2. In hierarchical regression analysis, the structural index did not contribute to significant variance in the C1 latency after regressing out the effect of age. However, the age explained significant variance in the model after regressing out the effect of structural feature.
Collapse
Affiliation(s)
- Sahar Rahimi Malakshan
- Faculty of Electrical Engineering, Department of Biomedical Engineering, K.N. Toosi University of Technology, Tehran, Iran
| | - Farveh Daneshvarfard
- Faculty of Electrical Engineering, Department of Biomedical Engineering, K.N. Toosi University of Technology, Tehran, Iran
- INSERM U1105, Université de Picardie, CURS, Amiens, France
| | - Hamid Abrishami Moghaddam
- Faculty of Electrical Engineering, Department of Biomedical Engineering, K.N. Toosi University of Technology, Tehran, Iran
| |
Collapse
|
31
|
Mapping myelin in white matter with T1-weighted/T2-weighted maps: discrepancy with histology and other myelin MRI measures. Brain Struct Funct 2023; 228:525-535. [PMID: 36692695 PMCID: PMC9944377 DOI: 10.1007/s00429-022-02600-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 11/18/2022] [Indexed: 01/25/2023]
Abstract
The ratio of T1-weighted/T2-weighted magnetic resonance images (T1w/T2w MRI) has been successfully applied at the cortical level since 2011 and is now one of the most used myelin mapping methods. However, no reports have explored the histological validity of T1w/T2w myelin mapping in white matter. Here we compare T1w/T2w with ex vivo postmortem histology and in vivo MRI methods, namely quantitative susceptibility mapping (QSM) and multi-echo T2 myelin water fraction (MWF) mapping techniques. We report a discrepancy between T1w/T2w myelin maps of the human corpus callosum and the histology and analyse the putative causes behind such discrepancy. T1w/T2w does not positively correlate with Luxol Fast Blue (LFB)-Optical Density but shows a weak to moderate, yet significant, negative correlation. On the contrary, MWF is strongly and positively correlated with LFB, whereas T1w/T2w and MWF maps are weakly negatively correlated. The discrepancy between T1w/T2w MRI maps, MWF and histological myelin maps suggests caution in using T1w/T2w as a white matter mapping method at the callosal level. While T1w/T2w imaging may correlate with myelin content at the cortical level, it is not a specific method to map myelin density in white matter.
Collapse
|
32
|
Strain JF, Cooley SA, Tomov D, Boerwinkle A, Ances BM. Abnormal Magnetic Resonance Image Signature in Virologically Stable HIV Individuals. J Infect Dis 2022; 226:2161-2169. [PMID: 36281565 DOI: 10.1093/infdis/jiac418] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 10/11/2022] [Accepted: 10/20/2022] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND With implementation of combination antiretroviral therapy (cART), changes to brain integrity in people with HIV (PWH) are subtle compared to those observed in the pre-cART era. T1-weighted/T2-weighted (T1w/T2w) ratio has been proposed as a measure of cortical myelin. This study examines T1w/T2w values between virologically controlled PWH and persons without HIV (PWoH). METHODS Virologically well-controlled PWH (n = 164) and PWoH (n = 120) were compared on global and regional T1w/T2w values. T1w/T2w values were associated with HIV disease variables (nadir and current CD4 T-cell count, and CNS penetration effectiveness of cART regimen) in PWH, and as a function of age for both PWoH and PWH. RESULTS PWH had reduced global and regional T1w/T2w values compared to PWoH in the posterior cingulate cortex, caudal anterior cingulate cortex, and insula. T1w/T2w values did not correlate with HIV variables except for a negative relationship with CNS penetration effectiveness. Greater cardiovascular disease risk and older age were associated with lower T1w/T2w values only for PWH. CONCLUSIONS T1w/T2w values obtained from commonly acquired MRI protocols differentiates virologically well-controlled PWH from PWoH. Changes in T1w/T2w ratio do not correlate with typical HIV measures. Future studies are needed to determine the biological mechanisms underlying this measure.
Collapse
Affiliation(s)
- Jeremy F Strain
- Department of Neurology, Washington University, St Louis, Missouri, USA
| | - Sarah A Cooley
- Department of Neurology, Washington University, St Louis, Missouri, USA
| | - Dimitre Tomov
- Department of Neurology, Washington University, St Louis, Missouri, USA
| | - Anna Boerwinkle
- Department of Neurology, Washington University, St Louis, Missouri, USA
| | - Beau M Ances
- Department of Neurology, Washington University, St Louis, Missouri, USA
| |
Collapse
|
33
|
Sui YV, Masurkar AV, Rusinek H, Reisberg B, Lazar M. Cortical myelin profile variations in healthy aging brain: A T1w/T2w ratio study. Neuroimage 2022; 264:119743. [PMID: 36368498 PMCID: PMC9904172 DOI: 10.1016/j.neuroimage.2022.119743] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Revised: 10/31/2022] [Accepted: 11/07/2022] [Indexed: 11/09/2022] Open
Abstract
Demyelination is observed in both healthy aging and age-related neurodegenerative disorders. While the significance of myelin within the cortex is well acknowledged, studies focused on intracortical demyelination and depth-specific structural alterations in normal aging are lacking. Using the recently available Human Connectome Project Aging dataset, we investigated intracortical myelin in a normal aging population using the T1w/T2w ratio. To capture the fine changes across cortical depths, we employed a surface-based approach by constructing cortical profiles traveling perpendicularly through the cortical ribbon and sampling T1w/T2w values. The curvatures of T1w/T2w cortical profiles may be influenced by differences in local myeloarchitecture and other tissue properties, which are known to vary across cortical regions. To quantify the shape of these profiles, we parametrized the level of curvature using a nonlinearity index (NLI) that measures the deviation of the profile from a straight line. We showed that NLI exhibited a steep decline in aging that was independent of local cortical thinning. Further examination of the profiles revealed that lower T1w/T2w near the gray-white matter boundary and superficial cortical depths were major contributors to the apparent NLI variations with age. These findings suggest that demyelination and changes in other T1w/T2w related tissue properties in normal aging may be depth-specific and highlight the potential of NLI as a unique marker of microstructural alterations within the cerebral cortex.
Collapse
Affiliation(s)
- Yu Veronica Sui
- Department of Radiology, NYU Grossman School of Medicine, 660 1st Ave, rm440, New York, NY 10016, USA,Corresponding author. (Y.V. Sui)
| | - Arjun V. Masurkar
- Department of Neurology, Center for Cognitive Neurology, NYU Grossman School of Medicine, New York, NY, USA,Department of Neuroscience and Physiology, NYU Grossman School of Medicine, New York, NY, USA,Neuroscience Institute, NYU Grossman School of Medicine, New York, NY, USA
| | - Henry Rusinek
- Department of Radiology, NYU Grossman School of Medicine, 660 1st Ave, rm440, New York, NY 10016, USA,Department of Psychiatry, NYU Grossman School of Medicine, New York, NY, USA
| | - Barry Reisberg
- Department of Psychiatry, NYU Grossman School of Medicine, New York, NY, USA
| | - Mariana Lazar
- Department of Radiology, NYU Grossman School of Medicine, 660 1st Ave, rm440, New York, NY 10016, USA
| |
Collapse
|
34
|
Ponticorvo S, Manara R, Russillo MC, Andreozzi V, Forino L, Erro R, Picillo M, Amboni M, Cuoco S, Di Salle G, Di Salle F, Barone P, Esposito F, Pellecchia MT. Combined regional T1w/T2w ratio and voxel-based morphometry in multiple system atrophy: A follow-up study. Front Neurol 2022; 13:1017311. [PMID: 36341112 PMCID: PMC9626981 DOI: 10.3389/fneur.2022.1017311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 09/29/2022] [Indexed: 11/13/2022] Open
Abstract
Several MRI techniques have become available to support the early diagnosis of multiple system atrophy (MSA), but few longitudinal studies on both MSA variants have been performed, and there are no established MRI markers of disease progression. We aimed to characterize longitudinal brain changes in 26 patients with MSA (14 MSA-P and 12 MSA-C) over a 1-year follow-up period in terms of local tissue density and T1w/T2w ratio in a-priori regions, namely, bilateral putamen, cerebellar gray matter (GM), white matter (WM), and substantia nigra (SN). A significant GM density decrease was found in cerebellum and left putamen in the entire group (10.7 and 33.1% variation, respectively) and both MSA subtypes (MSA-C: 15.4 and 33.0% variation; MSA-P: 7.7 and 33.2%) and in right putamen in the entire group (19.8% variation) and patients with MSA-C (20.9% variation). A WM density decrease was found in the entire group (9.3% variation) and both subtypes in cerebellum-brainstem (MSA-C: 18.0% variation; MSA-P: 5% variation). The T1w/T2w ratio increase was found in the cerebellar and left putamen GM (6.6 and 24.9% variation), while a significant T1w/T2w ratio decrease was detected in SN in the entire MSA group (31% variation). We found a more progressive atrophy of the cerebellum in MSA-C with a similar progression of putaminal atrophy in the two variants. T1w/T2w ratio can be further studied as a potential marker of disease progression, possibly reflecting decreased neuronal density or iron accumulation.
Collapse
Affiliation(s)
- Sara Ponticorvo
- Neuroscience Section, Department of Medicine, Surgery and Dentistry, Scuola Medica Salernitana, University of Salerno, Salerno, Italy
- *Correspondence: Sara Ponticorvo ;
| | - Renzo Manara
- Neuroradiology Unit, Department of Neurosciences, University of Padua, Padua, Italy
| | - Maria Claudia Russillo
- Neuroscience Section, Department of Medicine, Surgery and Dentistry, Scuola Medica Salernitana, University of Salerno, Salerno, Italy
| | - Valentina Andreozzi
- Neuroscience Section, Department of Medicine, Surgery and Dentistry, Scuola Medica Salernitana, University of Salerno, Salerno, Italy
| | - Lorenzo Forino
- Neuroscience Section, Department of Medicine, Surgery and Dentistry, Scuola Medica Salernitana, University of Salerno, Salerno, Italy
| | - Roberto Erro
- Neuroscience Section, Department of Medicine, Surgery and Dentistry, Scuola Medica Salernitana, University of Salerno, Salerno, Italy
| | - Marina Picillo
- Neuroscience Section, Department of Medicine, Surgery and Dentistry, Scuola Medica Salernitana, University of Salerno, Salerno, Italy
| | - Marianna Amboni
- Neuroscience Section, Department of Medicine, Surgery and Dentistry, Scuola Medica Salernitana, University of Salerno, Salerno, Italy
| | - Sofia Cuoco
- Neuroscience Section, Department of Medicine, Surgery and Dentistry, Scuola Medica Salernitana, University of Salerno, Salerno, Italy
| | | | - Francesco Di Salle
- Neuroscience Section, Department of Medicine, Surgery and Dentistry, Scuola Medica Salernitana, University of Salerno, Salerno, Italy
| | - Paolo Barone
- Neuroscience Section, Department of Medicine, Surgery and Dentistry, Scuola Medica Salernitana, University of Salerno, Salerno, Italy
| | - Fabrizio Esposito
- Department of Advanced Medical and Surgical Sciences, University of Campania “Luigi Vanvitelli”, Naples, Italy
| | - Maria Teresa Pellecchia
- Neuroscience Section, Department of Medicine, Surgery and Dentistry, Scuola Medica Salernitana, University of Salerno, Salerno, Italy
| |
Collapse
|
35
|
Parsons N, Ugon J, Morgan K, Shelyag S, Hocking A, Chan SY, Poudel G, Domìnguez D JF, Caeyenberghs K. Structural-Functional Connectivity Bandwidth of the Human Brain. Neuroimage 2022; 263:119659. [PMID: 36191756 DOI: 10.1016/j.neuroimage.2022.119659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 09/25/2022] [Accepted: 09/29/2022] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND The human brain is a complex network that seamlessly manifests behaviour and cognition. This network comprises neurons that directly, or indirectly mediate communication between brain regions. Here, we show how multilayer/multiplex network analysis provides a suitable framework to uncover the throughput of structural connectivity (SC) to mediate information transfer-giving rise to functional connectivity (FC). METHOD We implemented a novel method to reconcile SC and FC using diffusion and resting-state functional MRI connectivity data from 484 subjects (272 females, 212 males; age = 29.15 ± 3.47) from the Human Connectome Project. First, we counted the number of direct and indirect structural paths that mediate FC. FC nodes with indirect SC paths were then weighted according to their least restrictive SC path. We refer to this as SC-FC Bandwidth. We then mapped paths with the highest SC-FC Bandwidth across 7 canonical resting-state networks. FINDINGS We found that most pairs of FC nodes were connected by SC paths of length two and three (SC paths of length >5 were virtually non-existent). Direct SC-FC connections accounted for only 10% of all SC-FC connections. The majority of FC nodes without a direct SC path were mediated by a proportion of two (44%) or three SC path lengths (39%). Only a small proportion of FC nodes were mediated by SC path lengths of four (5%). We found high-bandwidth direct SC-FC connections show dense intra- and sparse inter-network connectivity, with a bilateral, anteroposterior distribution. High bandwidth SC-FC triangles have a right superomedial distribution within the somatomotor network. High-bandwidth SC-FC quads have a superoposterior distribution within the default mode network. CONCLUSION Our method allows the measurement of indirect SC-FC using undirected, weighted graphs derived from multimodal MRI data in order to map the location and throughput of SC to mediate FC. An extension of this work may be to explore how SC-FC Bandwidth changes over time, relates to cognition/behavior, and if this measure reflects a marker of neurological injury or psychiatric disorders.
Collapse
Affiliation(s)
- Nicholas Parsons
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Melbourne, VIC, Australia.
| | - Julien Ugon
- School of Information Technology, Faculty of Science Engineering & Built Environment, Deakin University, Melbourne, VIC, Australia
| | - Kerri Morgan
- School of Information Technology, Faculty of Science Engineering & Built Environment, Deakin University, Melbourne, VIC, Australia
| | - Sergiy Shelyag
- School of Information Technology, Faculty of Science Engineering & Built Environment, Deakin University, Melbourne, VIC, Australia
| | - Alex Hocking
- School of Information Technology, Faculty of Science Engineering & Built Environment, Deakin University, Melbourne, VIC, Australia
| | - Su Yuan Chan
- School of Information Technology, Faculty of Science Engineering & Built Environment, Deakin University, Melbourne, VIC, Australia
| | - Govinda Poudel
- School of Information Technology, Faculty of Science Engineering & Built Environment, Deakin University, Melbourne, VIC, Australia
| | - Juan F Domìnguez D
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Melbourne, VIC, Australia
| | - Karen Caeyenberghs
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Melbourne, VIC, Australia; Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, VIC, Australia
| |
Collapse
|
36
|
Huang H, Ma X, Yue X, Kang S, Li Y, Rao Y, Feng Y, Wu J, Long W, Chen Y, Lyu W, Tan X, Qiu S. White Matter Characteristics of Damage Along Fiber Tracts in Patients with Type 2 Diabetes Mellitus. Clin Neuroradiol 2022; 33:327-341. [DOI: 10.1007/s00062-022-01213-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Accepted: 08/06/2022] [Indexed: 11/03/2022]
Abstract
Abstract
Purpose
The white matter (WM) of the brain of type 2 diabetes mellitus (T2DM) patients is susceptible to neurodegenerative processes, but the specific types and positions of microstructural lesions along the fiber tracts remain unclear.
Methods
In this study 61 T2DM patients and 61 healthy controls were recruited and underwent diffusion spectrum imaging (DSI). The results were reconstructed with diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI). WM microstructural abnormalities were identified using tract-based spatial statistics (TBSS). Pointwise WM tract differences were detected through automatic fiber quantification (AFQ). The relationships between WM tract abnormalities and clinical characteristics were explored with partial correlation analysis.
Results
TBSS revealed widespread WM lesions in T2DM patients with decreased fractional anisotropy and axial diffusivity and an increased orientation dispersion index (ODI). The AFQ results showed microstructural abnormalities in T2DM patients in specific portions of the right superior longitudinal fasciculus (SLF), right arcuate fasciculus (ARC), left anterior thalamic radiation (ATR), and forceps major (FMA). In the right ARC of T2DM patients, an aberrant ODI was positively correlated with fasting insulin and insulin resistance, and an abnormal intracellular volume fraction was negatively correlated with fasting blood glucose. Additionally, negative associations were found between blood pressure and microstructural abnormalities in the right ARC, left ATR, and FMA in T2DM patients.
Conclusion
Using AFQ, together with DTI and NODDI, various kinds of microstructural alterations in the right SLF, right ARC, left ATR, and FMA can be accurately identified and may be associated with insulin and glucose status and blood pressure in T2DM patients.
Collapse
|
37
|
Glasser MF, Coalson TS, Harms MP, Xu J, Baum GL, Autio JA, Auerbach EJ, Greve DN, Yacoub E, Van Essen DC, Bock NA, Hayashi T. Empirical transmit field bias correction of T1w/T2w myelin maps. Neuroimage 2022; 258:119360. [PMID: 35697132 PMCID: PMC9483036 DOI: 10.1016/j.neuroimage.2022.119360] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Revised: 06/01/2022] [Accepted: 06/04/2022] [Indexed: 12/30/2022] Open
Abstract
T1-weighted divided by T2-weighted (T1w/T2w) myelin maps were initially developed for neuroanatomical analyses such as identifying cortical areas, but they are increasingly used in statistical comparisons across individuals and groups with other variables of interest. Existing T1w/T2w myelin maps contain radiofrequency transmit field (B1+) biases, which may be correlated with these variables of interest, leading to potentially spurious results. Here we propose two empirical methods for correcting these transmit field biases using either explicit measures of the transmit field or alternatively a 'pseudo-transmit' approach that is highly correlated with the transmit field at 3T. We find that the resulting corrected T1w/T2w myelin maps are both better neuroanatomical measures (e.g., for use in cross-species comparisons), and more appropriate for statistical comparisons of relative T1w/T2w differences across individuals and groups (e.g., sex, age, or body-mass-index) within a consistently acquired study at 3T. We recommend that investigators who use the T1w/T2w approach for mapping cortical myelin use these B1+ transmit field corrected myelin maps going forward.
Collapse
Affiliation(s)
| | | | - Michael P Harms
- Psychiatry, Washington University Medical School, St. Louis, MO, United States
| | - Junqian Xu
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States; Departments of Radiology and Psychiatry, Baylor College of Medicine, Houston, TX, United States
| | - Graham L Baum
- Department of Psychology, Harvard University, Cambridge, MA, United States
| | - Joonas A Autio
- RIKEN Center for Biosystems Dynamics Research, Kobe, Japan
| | - Edward J Auerbach
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States
| | - Douglas N Greve
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Essa Yacoub
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States
| | | | - Nicholas A Bock
- Department of Psychology, Neuroscience and Behaviour, McMaster University, Hamilton, ON, Canada
| | - Takuya Hayashi
- RIKEN Center for Biosystems Dynamics Research, Kobe, Japan
| |
Collapse
|
38
|
Uddin MN, Figley TD, Kornelsen J, Mazerolle EL, Helmick CA, O'Grady CB, Pirzada S, Patel R, Carter S, Wong K, Essig MR, Graff LA, Bolton JM, Marriott JJ, Bernstein CN, Fisk JD, Marrie RA, Figley CR. The comorbidity and cognition in multiple sclerosis (CCOMS) neuroimaging protocol: Study rationale, MRI acquisition, and minimal image processing pipelines. FRONTIERS IN NEUROIMAGING 2022; 1:970385. [PMID: 37555178 PMCID: PMC10406313 DOI: 10.3389/fnimg.2022.970385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 07/29/2022] [Indexed: 08/10/2023]
Abstract
The Comorbidity and Cognition in Multiple Sclerosis (CCOMS) study represents a coordinated effort by a team of clinicians, neuropsychologists, and neuroimaging experts to investigate the neural basis of cognitive changes and their association with comorbidities among persons with multiple sclerosis (MS). The objectives are to determine the relationships among psychiatric (e.g., depression or anxiety) and vascular (e.g., diabetes, hypertension, etc.) comorbidities, cognitive performance, and MRI measures of brain structure and function, including changes over time. Because neuroimaging forms the basis for several investigations of specific neural correlates that will be reported in future publications, the goal of the current manuscript is to briefly review the CCOMS study design and baseline characteristics for participants enrolled in the three study cohorts (MS, psychiatric control, and healthy control), and provide a detailed description of the MRI hardware, neuroimaging acquisition parameters, and image processing pipelines for the volumetric, microstructural, functional, and perfusion MRI data.
Collapse
Affiliation(s)
- Md Nasir Uddin
- Department of Radiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
| | - Teresa D. Figley
- Department of Radiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
| | - Jennifer Kornelsen
- Department of Radiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
- Department of Physiology and Pathophysiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Erin L. Mazerolle
- Department of Psychology, St. Francis Xavier University, Antigonish, NS, Canada
| | - Carl A. Helmick
- Division of Geriatric Medicine, Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
| | - Christopher B. O'Grady
- Department of Anesthesia and Biomedical Translational Imaging Centre, Dalhousie University, Halifax, NS, Canada
| | - Salina Pirzada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
- Department of Physiology and Pathophysiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Ronak Patel
- Department of Clinical Health Psychology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Sean Carter
- Department of Radiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
| | - Kaihim Wong
- Department of Radiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
| | - Marco R. Essig
- Department of Radiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
| | - Lesley A. Graff
- Department of Clinical Health Psychology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - James M. Bolton
- Department of Psychiatry, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - James J. Marriott
- Department of Internal Medicine, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Charles N. Bernstein
- Department of Internal Medicine, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - John D. Fisk
- Nova Scotia Health Authority and the Departments of Psychiatry, Psychology and Neuroscience, and Medicine, Dalhousie University, Halifax, NS, Canada
| | - Ruth Ann Marrie
- Department of Internal Medicine, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Department of Community Health Sciences, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Chase R. Figley
- Department of Radiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Health Sciences Centre Winnipeg, Winnipeg, MB, Canada
- Department of Physiology and Pathophysiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| |
Collapse
|
39
|
Patel R, Mackay CE, Jansen MG, Devenyi GA, O'Donoghue MC, Kivimäki M, Singh-Manoux A, Zsoldos E, Ebmeier KP, Chakravarty MM, Suri S. Inter- and intra-individual variation in brain structural-cognition relationships in aging. Neuroimage 2022; 257:119254. [PMID: 35490915 PMCID: PMC9393406 DOI: 10.1016/j.neuroimage.2022.119254] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Revised: 04/14/2022] [Accepted: 04/16/2022] [Indexed: 01/21/2023] Open
Abstract
The sources of inter- and intra-individual variability in age-related cognitive decline remain poorly understood. We examined the association between 20-year trajectories of cognitive decline and multimodal brain structure and morphology in older age. We used the Whitehall II Study, an extensively characterised cohort with 3T brain magnetic resonance images acquired at older age (mean age = 69.52 ± 4.9) and 5 repeated cognitive performance assessments between mid-life (mean age = 53.2 ±4.9 years) and late-life (mean age = 67.7 ± 4.9). Using non-negative matrix factorization, we identified 10 brain components integrating cortical thickness, surface area, fractional anisotropy, and mean and radial diffusivities. We observed two latent variables describing distinct brain-cognition associations. The first describes variations in 5 structural components associated with low mid-life performance across multiple cognitive domains, decline in reasoning, but maintenance of fluency abilities. The second describes variations in 6 structural components associated with low mid-life performance in fluency and memory, but retention of multiple abilities. Expression of latent variables predicts future cognition 3.2 years later (mean age = 70.87 ± 4.9). This data-driven approach highlights brain-cognition relationships wherein individuals degrees of cognitive decline and maintenance across diverse cognitive functions are both positively and negatively associated with markers of cortical structure.
Collapse
Affiliation(s)
- Raihaan Patel
- Computational Brain Anatomy Laboratory, Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, Québec, H4H 1R3, Canada; Department of Biological and Biomedical Engineering, McGill University, Montréal, Québec, H3A 2B4, Canada
| | - Clare E Mackay
- Department of Psychiatry, Warneford Hospital, University of Oxford, OX3 7JX, Oxford, United Kingdom; Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, OX3 7JX, Oxford, United Kingdom
| | - Michelle G Jansen
- Donders Centre for Cognition, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands
| | - Gabriel A Devenyi
- Computational Brain Anatomy Laboratory, Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, Québec, H4H 1R3, Canada; Department of Psychiatry, McGill University, Montréal, Québec, H3A 1A1, Canada
| | - M Clare O'Donoghue
- Department of Psychiatry, Warneford Hospital, University of Oxford, OX3 7JX, Oxford, United Kingdom; Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, OX3 7JX, Oxford, United Kingdom
| | - Mika Kivimäki
- Department of Epidemiology and Public Health, University College London, WC1E 6BT, London, United Kingdom
| | - Archana Singh-Manoux
- Department of Epidemiology and Public Health, University College London, WC1E 6BT, London, United Kingdom; Université de Paris, Inserm U1153, Epidemiology of Ageing and Neurodegenerative diseases, 7501020, Paris, France
| | - Enikő Zsoldos
- Department of Psychiatry, Warneford Hospital, University of Oxford, OX3 7JX, Oxford, United Kingdom; Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, OX3 7JX, Oxford, United Kingdom; Oxford Centre for Functional MRI of the Brain, Wellcome Centre for Integrative Neuroimaging, University of Oxford, OX3 9DU, Oxford, UK
| | - Klaus P Ebmeier
- Department of Psychiatry, Warneford Hospital, University of Oxford, OX3 7JX, Oxford, United Kingdom
| | - M Mallar Chakravarty
- Computational Brain Anatomy Laboratory, Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, Québec, H4H 1R3, Canada; Department of Biological and Biomedical Engineering, McGill University, Montréal, Québec, H3A 2B4, Canada; Department of Psychiatry, McGill University, Montréal, Québec, H3A 1A1, Canada
| | - Sana Suri
- Department of Psychiatry, Warneford Hospital, University of Oxford, OX3 7JX, Oxford, United Kingdom; Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, OX3 7JX, Oxford, United Kingdom.
| |
Collapse
|
40
|
Norbom LB, Hanson J, van der Meer D, Ferschmann L, Røysamb E, von Soest T, Andreassen OA, Agartz I, Westlye LT, Tamnes CK. Parental socioeconomic status is linked to cortical microstructure and language abilities in children and adolescents. Dev Cogn Neurosci 2022; 56:101132. [PMID: 35816931 PMCID: PMC9284438 DOI: 10.1016/j.dcn.2022.101132] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 05/11/2022] [Accepted: 06/30/2022] [Indexed: 12/17/2022] Open
Abstract
Gradients in parental socioeconomic status (SES) are closely linked to important life outcomes in children and adolescents, such as cognitive abilities, school achievement, and mental health. Parental SES may also influence brain development, with several magnetic resonance imaging (MRI) studies reporting associations with youth brain morphometry. However, MRI signal intensity metrics have not been assessed, but could offer a microstructural correlate, thereby increasing our understanding of SES influences on neurobiology. We computed a parental SES score from family income, parental education and parental occupation, and assessed relations with cortical microstructure as measured by T1w/T2w ratio (n = 504, age = 3-21 years). We found negative age-stabile relations between parental SES and T1w/T2w ratio, indicating that youths from lower SES families have higher ratio in widespread frontal, temporal, medial parietal and occipital regions, possibly indicating a more developed cortex. Effect sizes were small, but larger than for conventional morphometric properties i.e. cortical surface area and thickness, which were not significantly associated with parental SES. Youths from lower SES families had poorer language related abilities, but microstructural differences did not mediate these relations. T1w/T2w ratio appears to be a sensitive imaging marker for further exploring the association between parental SES and child brain development.
Collapse
Affiliation(s)
- Linn B Norbom
- PROMENTA Research Center, Department of Psychology, University of Oslo, Norway; NORMENT, Institute of Clinical Medicine, University of Oslo, Norway; Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway; Norwegian Institute of Public Health, Norway.
| | - Jamie Hanson
- Learning Research and Development Center University of Pittsburgh, USA; Department of Psychology, University of Pittsburgh, USA; Norwegian Institute of Public Health, Norway
| | - Dennis van der Meer
- NORMENT, Institute of Clinical Medicine, University of Oslo, Norway; School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, the Netherlands; Norwegian Institute of Public Health, Norway
| | - Lia Ferschmann
- PROMENTA Research Center, Department of Psychology, University of Oslo, Norway; Norwegian Institute of Public Health, Norway
| | - Espen Røysamb
- PROMENTA Research Center, Department of Psychology, University of Oslo, Norway; Department of Psychology, University of Oslo, Norway; Norwegian Institute of Public Health, Norway
| | - Tilmann von Soest
- PROMENTA Research Center, Department of Psychology, University of Oslo, Norway; Norwegian Institute of Public Health, Norway
| | - Ole A Andreassen
- K.G Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Norway; NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Norway; Norwegian Institute of Public Health, Norway
| | - Ingrid Agartz
- NORMENT, Institute of Clinical Medicine, University of Oslo, Norway; Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway; K.G Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Norway; Norwegian Institute of Public Health, Norway; Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet & Stockholm Health Care Services, Stockholm Region, Stockholm, Sweden
| | - Lars T Westlye
- K.G Jebsen Center for Neurodevelopmental Disorders, University of Oslo, Norway; NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Norway; Department of Psychology, University of Oslo, Norway; Norwegian Institute of Public Health, Norway
| | - Christian K Tamnes
- PROMENTA Research Center, Department of Psychology, University of Oslo, Norway; NORMENT, Institute of Clinical Medicine, University of Oslo, Norway; Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway; Norwegian Institute of Public Health, Norway
| |
Collapse
|
41
|
Fernandez-Alvarez M, Atienza M, Zallo F, Matute C, Capetillo-Zarate E, Cantero JL. Linking Plasma Amyloid Beta and Neurofilament Light Chain to Intracortical Myelin Content in Cognitively Normal Older Adults. Front Aging Neurosci 2022; 14:896848. [PMID: 35783126 PMCID: PMC9247578 DOI: 10.3389/fnagi.2022.896848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 05/23/2022] [Indexed: 11/29/2022] Open
Abstract
Evidence suggests that lightly myelinated cortical regions are vulnerable to aging and Alzheimer’s disease (AD). However, it remains unknown whether plasma markers of amyloid and neurodegeneration are related to deficits in intracortical myelin content, and whether this relationship, in turn, is associated with altered patterns of resting-state functional connectivity (rs-FC). To shed light into these questions, plasma levels of amyloid-β fragment 1–42 (Aβ1–42) and neurofilament light chain (NfL) were measured using ultra-sensitive single-molecule array (Simoa) assays, and the intracortical myelin content was estimated with the ratio T1-weigthed/T2-weighted (T1w/T2w) in 133 cognitively normal older adults. We assessed: (i) whether plasma Aβ1–42 and/or NfL levels were associated with intracortical myelin content at different cortical depths and (ii) whether cortical regions showing myelin reductions also exhibited altered rs-FC patterns. Surface-based multiple regression analyses revealed that lower plasma Aβ1–42 and higher plasma NfL were associated with lower myelin content in temporo-parietal-occipital regions and the insular cortex, respectively. Whereas the association with Aβ1–42 decreased with depth, the NfL-myelin relationship was most evident in the innermost layer. Older individuals with higher plasma NfL levels also exhibited altered rs-FC between the insula and medial orbitofrontal cortex. Together, these findings establish a link between plasma markers of amyloid/neurodegeneration and intracortical myelin content in cognitively normal older adults, and support the role of plasma NfL in boosting aberrant FC patterns of the insular cortex, a central brain hub highly vulnerable to aging and neurodegeneration.
Collapse
Affiliation(s)
- Marina Fernandez-Alvarez
- Laboratory of Functional Neuroscience, Pablo de Olavide University, Seville, Spain
- Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Mercedes Atienza
- Laboratory of Functional Neuroscience, Pablo de Olavide University, Seville, Spain
- Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Fatima Zallo
- Departamento de Neurociencias, Achucarro Basque Center for Neuroscience, Universidad del País Vasco, Leioa, Spain
| | - Carlos Matute
- Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- Departamento de Neurociencias, Achucarro Basque Center for Neuroscience, Universidad del País Vasco, Leioa, Spain
| | - Estibaliz Capetillo-Zarate
- Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- Departamento de Neurociencias, Achucarro Basque Center for Neuroscience, Universidad del País Vasco, Leioa, Spain
- Ikerbasque, Basque Foundation for Science, Bilbao, Spain
| | - Jose L. Cantero
- Laboratory of Functional Neuroscience, Pablo de Olavide University, Seville, Spain
- Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- *Correspondence: Jose L. Cantero,
| |
Collapse
|
42
|
Boaventura M, Sastre-Garriga J, Garcia-Vidal A, Vidal-Jordana A, Quartana D, Carvajal R, Auger C, Alberich M, Tintoré M, Rovira À, Montalban X, Pareto D. T1/T2-weighted ratio in multiple sclerosis: A longitudinal study with clinical associations. Neuroimage Clin 2022; 34:102967. [PMID: 35202997 PMCID: PMC8866895 DOI: 10.1016/j.nicl.2022.102967] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Revised: 02/04/2022] [Accepted: 02/14/2022] [Indexed: 11/29/2022]
Abstract
Alterations in T1-w/T2-w ratio precede lesion formation in CIS patients. Longitudinal decreases in T1-w/T2-w were associated with disease activity in CIS. Lower T1-w/T2-w was associated with longer disease duration and higher EDSS in MS.
Background T1w/T2-w ratio has been proposed as a clinically feasible MRI biomarker to assess tissue integrity in multiple sclerosis. However, no data is available in the earliest stages of the disease and longitudinal studies analysing clinical associations are scarce. Objective To describe longitudinal changes in T1-w/T2-w in patients with clinically isolated syndrome (CIS) and multiple sclerosis, and to investigate their clinical associations. Methods T1-w/T2-w images were generated and the mean value obtained in the corresponding lesion, normal-appearing grey (NAGM) and white matter (NAWM) masks. By co-registering baseline to follow-up MRI, evolved lesions were assessed; and by placing the mask of new lesions to the baseline study, the pre-lesional tissue integrity was measured. Results We included 171 CIS patients and 22 established multiple sclerosis patients. In CIS, evolved lesions showed significant T1-w/T2-w increases compared to baseline (+7.6%, P < 0.001). T1-w/T2-w values in new lesions were lower than in pre-lesional tissue (-28.2%, P < 0.001), and pre-lesional tissue was already lower than baseline NAWM (-7.8%, P < 0.001). In CIS at baseline, higher NAGM T1-w/T2-w was associated with multiple sclerosis diagnosis, and longitudinal decreases in NAGM and NAWM T1-w/T2-w were associated with disease activity. In established multiple sclerosis, T1-w/T2-w was inversely correlated with clinical disability and disease duration. Conclusion A decrease in T1-w/T2-w ratio precedes lesion formation. In CIS, higher T1-w/T2-w was associated with multiple sclerosis diagnosis. In established multiple sclerosis, lower T1-w/T2-w values were associated with clinical disability. The possible differential impact of chronic inflammation, iron deposition and demyelination should be considered to interpret these findings.
Collapse
Affiliation(s)
- Mateus Boaventura
- Department of Neurology-Neuroimmunology, Multiple Sclerosis Centre of Catalonia (Cemcat), Barcelona, Spain
| | - Jaume Sastre-Garriga
- Department of Neurology-Neuroimmunology, Multiple Sclerosis Centre of Catalonia (Cemcat), Barcelona, Spain
| | - Aran Garcia-Vidal
- Section of Neuroradiology, Department of Radiology, Vall d'Hebron University Hospital, Barcelona, Spain
| | - Angela Vidal-Jordana
- Department of Neurology-Neuroimmunology, Multiple Sclerosis Centre of Catalonia (Cemcat), Barcelona, Spain
| | - Davide Quartana
- Department of Neurology-Neuroimmunology, Multiple Sclerosis Centre of Catalonia (Cemcat), Barcelona, Spain
| | - René Carvajal
- Department of Neurology-Neuroimmunology, Multiple Sclerosis Centre of Catalonia (Cemcat), Barcelona, Spain
| | - Cristina Auger
- Section of Neuroradiology, Department of Radiology, Vall d'Hebron University Hospital, Barcelona, Spain
| | - Manel Alberich
- Section of Neuroradiology, Department of Radiology, Vall d'Hebron University Hospital, Barcelona, Spain
| | - Mar Tintoré
- Department of Neurology-Neuroimmunology, Multiple Sclerosis Centre of Catalonia (Cemcat), Barcelona, Spain
| | - Àlex Rovira
- Section of Neuroradiology, Department of Radiology, Vall d'Hebron University Hospital, Barcelona, Spain
| | - Xavier Montalban
- Department of Neurology-Neuroimmunology, Multiple Sclerosis Centre of Catalonia (Cemcat), Barcelona, Spain
| | - Deborah Pareto
- Section of Neuroradiology, Department of Radiology, Vall d'Hebron University Hospital, Barcelona, Spain.
| |
Collapse
|
43
|
Langensee L, Rumetshofer T, Behjat H, Novén M, Li P, Mårtensson J. T1w/T2w Ratio and Cognition in 9-to-11-Year-Old Children. Brain Sci 2022; 12:599. [PMID: 35624986 PMCID: PMC9139105 DOI: 10.3390/brainsci12050599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 04/28/2022] [Accepted: 05/03/2022] [Indexed: 11/28/2022] Open
Abstract
Childhood is a period of extensive cortical and neural development. Among other things, axons in the brain gradually become more myelinated, promoting the propagation of electrical signals between different parts of the brain, which in turn may facilitate skill development. Myelin is difficult to assess in vivo, and measurement techniques are only just beginning to make their way into standard imaging protocols in human cognitive neuroscience. An approach that has been proposed as an indirect measure of cortical myelin is the T1w/T2w ratio, a contrast that is based on the intensities of two standard structural magnetic resonance images. Although not initially intended as such, researchers have recently started to use the T1w/T2w contrast for between-subject comparisons of cortical data with various behavioral and cognitive indices. As a complement to these earlier findings, we computed individual cortical T1w/T2w maps using data from the Adolescent Brain Cognitive Development study (N = 960; 449 females; aged 8.9 to 11.0 years) and related the T1w/T2w maps to indices of cognitive ability; in contrast to previous work, we did not find significant relationships between T1w/T2w values and cognitive performance after correcting for multiple testing. These findings reinforce existent skepticism about the applicability of T1w/T2w ratio for inter-individual comparisons.
Collapse
Affiliation(s)
- Lara Langensee
- Faculty of Medicine, Department of Clinical Sciences Lund, Logopedics, Phoniatrics and Audiology, Lund University, 22100 Lund, Sweden; (T.R.); (J.M.)
| | - Theodor Rumetshofer
- Faculty of Medicine, Department of Clinical Sciences Lund, Logopedics, Phoniatrics and Audiology, Lund University, 22100 Lund, Sweden; (T.R.); (J.M.)
| | - Hamid Behjat
- Faculty of Engineering, Department of Biomedical Engineering, Lund University, 22100 Lund, Sweden;
| | - Mikael Novén
- Faculty of Science, Department of Nutrition, Exercise and Sports, University of Copenhagen, 2200 Copenhagen, Denmark;
| | - Ping Li
- Faculty of Humanities, Department of Chinese and Bilingual Studies, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China;
| | - Johan Mårtensson
- Faculty of Medicine, Department of Clinical Sciences Lund, Logopedics, Phoniatrics and Audiology, Lund University, 22100 Lund, Sweden; (T.R.); (J.M.)
| |
Collapse
|
44
|
Cacciaguerra L, Pagani E, Radaelli M, Mesaros S, Martinelli V, Ivanovic J, Drulovic J, Filippi M, Rocca MA. MR T2-relaxation time as an indirect measure of brain water content and disease activity in NMOSD. J Neurol Neurosurg Psychiatry 2022; 93:jnnp-2022-328956. [PMID: 35483915 DOI: 10.1136/jnnp-2022-328956] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Accepted: 03/31/2022] [Indexed: 11/03/2022]
Abstract
OBJECTIVE Since astrocytes at the blood-brain barrier are targeted by neuromyelitis optica spectrum disorder (NMOSD), this study aims to assess whether patients with NMOSD have a subclinical accumulation of brain water and if it differs according to disease activity. METHODS Seventy-seven aquaporin-4-positive patients with NMOSD and 105 healthy controls were enrolled at two European centres. Brain dual-echo turbo spin-echo MR images were evaluated and maps of T2 relaxation time (T2rt) in the normal-appearing white matter (NAWM), grey matter and basal ganglia were obtained. Patients with a clinical relapse within 1 month before or after MRI acquisition were defined 'active'. Differences between patients and controls were assessed using z-scores of T2rt obtained with age-adjusted and sex-adjusted linear models from each site. A stepwise binary logistic regression was run on clinical and MRI variables to identify independent predictors of disease activity. RESULTS Patients had increased T2rt in both white and grey matter structures (p range: 0.014 to <0.0001). Twenty patients with NMOSD were defined active. Despite similar clinical and MRI features, active patients had a significantly increased T2rt in the NAWM and grey matter compared with those clinically stable (p range: 0.010-0.002). The stepwise binary logistic regression selected the NAWM as independently associated with disease activity (beta=2.06, SE=0.58, Nagelkerke R2=0.46, p<0.001). CONCLUSIONS In line with the research hypothesis, patients with NMOSD have increased brain T2rt. The magnitude of this alteration might be useful for identifying those patients with active disease.
Collapse
Affiliation(s)
- Laura Cacciaguerra
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS Ospedale San Raffaele, Milano, Italy
- Neurology Unit, IRCCS Ospedale San Raffaele, Milano, Italy
- Vita-Salute San Raffaele University, Milano, Italy
| | - Elisabetta Pagani
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS Ospedale San Raffaele, Milano, Italy
| | - Marta Radaelli
- Neurology Unit, IRCCS Ospedale San Raffaele, Milano, Italy
| | - Sarlota Mesaros
- Clinic of Neurology, Faculty of Medicine, University of Belgrade, Beograd, Serbia
| | | | - Jovana Ivanovic
- Clinic of Neurology, Faculty of Medicine, University of Belgrade, Beograd, Serbia
| | - Jelena Drulovic
- Clinic of Neurology, Faculty of Medicine, University of Belgrade, Beograd, Serbia
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS Ospedale San Raffaele, Milano, Italy
- Neurology Unit, IRCCS Ospedale San Raffaele, Milano, Italy
- Vita-Salute San Raffaele University, Milano, Italy
- Nerorehabilitation Unit, IRCCS Ospedale San Raffaele, Milano, Italy
- Neurophysiology Service, IRCCS Ospedale San Raffaele, Milano, Italy
| | - Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS Ospedale San Raffaele, Milano, Italy
- Neurology Unit, IRCCS Ospedale San Raffaele, Milano, Italy
- Vita-Salute San Raffaele University, Milano, Italy
| |
Collapse
|
45
|
Schmidbauer VU, Yildirim MS, Dovjak GO, Goeral K, Buchmayer J, Weber M, Diogo MC, Giordano V, Mayr-Geisl G, Prayer F, Stuempflen M, Lindenlaub F, List V, Glatter S, Rauscher A, Stuhr F, Lindner C, Klebermass-Schrehof K, Berger A, Prayer D, Kasprian G. Different from the Beginning: WM Maturity of Female and Male Extremely Preterm Neonates-A Quantitative MRI Study. AJNR Am J Neuroradiol 2022; 43:611-619. [PMID: 35332014 PMCID: PMC8993206 DOI: 10.3174/ajnr.a7472] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2021] [Accepted: 01/25/2022] [Indexed: 12/31/2022]
Abstract
BACKGROUND AND PURPOSE Former preterm born males are at higher risk for neurodevelopmental disabilities compared with female infants born at the same gestational age. This retrospective study investigated sex-related differences in the maturity of early myelinating brain regions in infants born <28 weeks' gestational age using diffusion tensor- and relaxometry-based MR imaging. MATERIALS AND METHODS Quantitative MR imaging sequence acquisitions were analyzed in a sample of 35 extremely preterm neonates imaged at term-equivalent ages. Quantitative MR imaging metrics (fractional anisotropy; ADC [10-3mm2/s]; and T1-/T2-relaxation times [ms]) of the medulla oblongata, pontine tegmentum, midbrain, and the right/left posterior limbs of the internal capsule were determined on diffusion tensor- and multidynamic, multiecho sequence-based imaging data. ANCOVA and a paired t test were used to compare female and male infants and to detect hemispheric developmental asymmetries. RESULTS Seventeen female (mean gestational age at birth: 26 + 0 [SD, 1 + 4] weeks+days) and 18 male (mean gestational age at birth: 26 + 1 [SD, 1 + 3] weeks+days) infants were enrolled in this study. Significant differences were observed in the T2-relaxation time (P = .014) of the pontine tegmentum, T1-relaxation time (P = .011)/T2-relaxation time (P = .024) of the midbrain, and T1-relaxation time (P = .032) of the left posterior limb of the internal capsule. In both sexes, fractional anisotropy (P [♀] < .001/P [♂] < .001) and ADC (P [♀] = .017/P [♂] = .028) differed significantly between the right and left posterior limbs of the internal capsule. CONCLUSIONS The combined use of various quantitative MR imaging metrics detects sex-related and interhemispheric differences of WM maturity. The brainstem and the left posterior limb of the internal capsule of male preterm neonates are more immature compared with those of female infants at term-equivalent ages. Sex differences in WM maturation need further attention for the personalization of neonatal brain imaging.
Collapse
Affiliation(s)
- V U Schmidbauer
- From the Department of Biomedical Imaging and Image-guided Therapy (V.U.S., M.S.Y., G.O.D., M.W., F.P., M.S., F.L., F.S., C.L., D.P., G.K.)
| | - M S Yildirim
- From the Department of Biomedical Imaging and Image-guided Therapy (V.U.S., M.S.Y., G.O.D., M.W., F.P., M.S., F.L., F.S., C.L., D.P., G.K.)
| | - G O Dovjak
- From the Department of Biomedical Imaging and Image-guided Therapy (V.U.S., M.S.Y., G.O.D., M.W., F.P., M.S., F.L., F.S., C.L., D.P., G.K.)
| | - K Goeral
- Comprehensive Center for Pediatrics (K.G., J.B., V.G., V.L., S.G., K.K.-S., A.B.), Department of Pediatrics and Adolescent Medicine, Division of Neonatology, Pediatric Intensive Care and Neuropediatrics
| | - J Buchmayer
- Comprehensive Center for Pediatrics (K.G., J.B., V.G., V.L., S.G., K.K.-S., A.B.), Department of Pediatrics and Adolescent Medicine, Division of Neonatology, Pediatric Intensive Care and Neuropediatrics
| | - M Weber
- From the Department of Biomedical Imaging and Image-guided Therapy (V.U.S., M.S.Y., G.O.D., M.W., F.P., M.S., F.L., F.S., C.L., D.P., G.K.)
| | - M C Diogo
- Department of Neuroradiology (M.C.D.), Hospital Garcia de Orta, Almada, Portugal
| | - V Giordano
- Comprehensive Center for Pediatrics (K.G., J.B., V.G., V.L., S.G., K.K.-S., A.B.), Department of Pediatrics and Adolescent Medicine, Division of Neonatology, Pediatric Intensive Care and Neuropediatrics
| | - G Mayr-Geisl
- Department of Neurosurgery (G.M.-G.), Medical University of Vienna, Vienna, Austria
| | - F Prayer
- From the Department of Biomedical Imaging and Image-guided Therapy (V.U.S., M.S.Y., G.O.D., M.W., F.P., M.S., F.L., F.S., C.L., D.P., G.K.)
| | - M Stuempflen
- From the Department of Biomedical Imaging and Image-guided Therapy (V.U.S., M.S.Y., G.O.D., M.W., F.P., M.S., F.L., F.S., C.L., D.P., G.K.)
| | - F Lindenlaub
- From the Department of Biomedical Imaging and Image-guided Therapy (V.U.S., M.S.Y., G.O.D., M.W., F.P., M.S., F.L., F.S., C.L., D.P., G.K.)
| | - V List
- Comprehensive Center for Pediatrics (K.G., J.B., V.G., V.L., S.G., K.K.-S., A.B.), Department of Pediatrics and Adolescent Medicine, Division of Neonatology, Pediatric Intensive Care and Neuropediatrics
| | - S Glatter
- Comprehensive Center for Pediatrics (K.G., J.B., V.G., V.L., S.G., K.K.-S., A.B.), Department of Pediatrics and Adolescent Medicine, Division of Neonatology, Pediatric Intensive Care and Neuropediatrics
| | - A Rauscher
- Department of Pediatrics (A.R.), University of British Columbia, Vancouver, British Columbia, Canada
| | - F Stuhr
- From the Department of Biomedical Imaging and Image-guided Therapy (V.U.S., M.S.Y., G.O.D., M.W., F.P., M.S., F.L., F.S., C.L., D.P., G.K.)
| | - C Lindner
- From the Department of Biomedical Imaging and Image-guided Therapy (V.U.S., M.S.Y., G.O.D., M.W., F.P., M.S., F.L., F.S., C.L., D.P., G.K.)
| | - K Klebermass-Schrehof
- Comprehensive Center for Pediatrics (K.G., J.B., V.G., V.L., S.G., K.K.-S., A.B.), Department of Pediatrics and Adolescent Medicine, Division of Neonatology, Pediatric Intensive Care and Neuropediatrics
| | - A Berger
- Comprehensive Center for Pediatrics (K.G., J.B., V.G., V.L., S.G., K.K.-S., A.B.), Department of Pediatrics and Adolescent Medicine, Division of Neonatology, Pediatric Intensive Care and Neuropediatrics
| | - D Prayer
- From the Department of Biomedical Imaging and Image-guided Therapy (V.U.S., M.S.Y., G.O.D., M.W., F.P., M.S., F.L., F.S., C.L., D.P., G.K.)
| | - G Kasprian
- From the Department of Biomedical Imaging and Image-guided Therapy (V.U.S., M.S.Y., G.O.D., M.W., F.P., M.S., F.L., F.S., C.L., D.P., G.K.)
| |
Collapse
|
46
|
Yuan S, Liu M, Kim S, Yang J, Barkovich AJ, Xu D, Kim H. Cyto/myeloarchitecture of cortical gray matter and superficial white matter in early neurodevelopment: multimodal MRI study in preterm neonates. Cereb Cortex 2022; 33:357-373. [PMID: 35235643 PMCID: PMC9837610 DOI: 10.1093/cercor/bhac071] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Revised: 01/21/2022] [Accepted: 01/22/2022] [Indexed: 01/19/2023] Open
Abstract
The cerebral cortex undergoes rapid microstructural changes throughout the third trimester. Recently, there has been growing interest on imaging features that represent cyto/myeloarchitecture underlying intracortical myelination, cortical gray matter (GM), and its adjacent superficial whitematter (sWM). Using 92 magnetic resonance imaging scans from 78 preterm neonates, the current study used combined T1-weighted/T2-weighted (T1w/T2w) intensity ratio and diffusion tensor imaging (DTI) measurements, including fractional anisotropy (FA) and mean diffusivity (MD), to characterize the developing cyto/myeloarchitectural architecture. DTI metrics showed a linear trajectory: FA decreased in GM but increased in sWM with time; and MD decreased in both GM and sWM. Conversely, T1w/T2w measurements showed a distinctive parabolic trajectory, revealing additional cyto/myeloarchitectural signature inferred. Furthermore, the spatiotemporal courses were regionally heterogeneous: central, ventral, and temporal regions of GM and sWM exhibited faster T1w/T2w changes; anterior sWM areas exhibited faster FA increases; and central and cingulate areas in GM and sWM exhibited faster MD decreases. These results may explain cyto/myeloarchitectural processes, including dendritic arborization, synaptogenesis, glial proliferation, and radial glial cell organization and apoptosis. Finally, T1w/T2w values were significantly associated with 1-year language and cognitive outcome scores, while MD significantly decreased with intraventricular hemorrhage.
Collapse
Affiliation(s)
| | | | | | - Jingda Yang
- Department of Neurology, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Anthony James Barkovich
- Department of Radiology & Biomedical Imaging, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Duan Xu
- Department of Radiology & Biomedical Imaging, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Hosung Kim
- Corresponding author: 2025 Zonal Ave, Los Angeles, CA 90033, USA.
| |
Collapse
|
47
|
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.
Collapse
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
| |
Collapse
|
48
|
Kiely M, Triebswetter C, Cortina LE, Gong Z, Alsameen MH, Spencer RG, Bouhrara M. Insights into human cerebral white matter maturation and degeneration across the adult lifespan. Neuroimage 2022; 247:118727. [PMID: 34813969 PMCID: PMC8792239 DOI: 10.1016/j.neuroimage.2021.118727] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Revised: 10/15/2021] [Accepted: 11/12/2021] [Indexed: 01/01/2023] Open
Abstract
White matter (WM) microstructural properties change across the adult lifespan and with neuronal diseases. Understanding microstructural changes due to aging is paramount to distinguish them from neuropathological changes. Conducted on a large cohort of 147 cognitively unimpaired subjects, spanning a wide age range of 21 to 94 years, our study evaluated sex- and age-related differences in WM microstructure. Specifically, we used diffusion tensor imaging (DTI) magnetic resonance imaging (MRI) indices, sensitive measures of myelin and axonal density in WM, and myelin water fraction (MWF), a measure of the fraction of the signal of water trapped within the myelin sheets, to probe these differences. Furthermore, we examined regional correlations between MWF and DTI indices to evaluate whether the DTI metrics provide information complementary to MWF. While sexual dimorphism was, overall, nonsignificant, we observed region-dependent differences in MWF, that is, myelin content, and axonal density with age and found that both exhibit nonlinear, but distinct, associations with age. Furthermore, DTI indices were moderately correlated with MWF, indicating their good sensitivity to myelin content as well as to other constituents of WM tissue such as axonal density. The microstructural differences captured by our MRI metrics, along with their weak to moderate associations with MWF, strongly indicate the potential value of combining these outcome measures in a multiparametric approach. Furthermore, our results support the last-in-first-out and the gain-predicts-loss hypotheses of WM maturation and degeneration. Indeed, our results indicate that the posterior WM regions are spared from neurodegeneration as compared to anterior regions, while WM myelination follows a temporally symmetric time course across the adult life span.
Collapse
Affiliation(s)
- Matthew Kiely
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224 MD, USA
| | - Curtis Triebswetter
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224 MD, USA
| | - Luis E Cortina
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224 MD, USA
| | - Zhaoyuan Gong
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224 MD, USA
| | - Maryam H Alsameen
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224 MD, USA
| | - Richard G Spencer
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224 MD, USA
| | - Mustapha Bouhrara
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224 MD, USA.
| |
Collapse
|
49
|
Figley CR, Uddin MN, Wong K, Kornelsen J, Puig J, Figley TD. Potential Pitfalls of Using Fractional Anisotropy, Axial Diffusivity, and Radial Diffusivity as Biomarkers of Cerebral White Matter Microstructure. Front Neurosci 2022; 15:799576. [PMID: 35095400 PMCID: PMC8795606 DOI: 10.3389/fnins.2021.799576] [Citation(s) in RCA: 68] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 12/17/2021] [Indexed: 01/31/2023] Open
Abstract
Fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD) are commonly used as MRI biomarkers of white matter microstructure in diffusion MRI studies of neurodevelopment, brain aging, and neurologic injury/disease. Some of the more frequent practices include performing voxel-wise or region-based analyses of these measures to cross-sectionally compare individuals or groups, longitudinally assess individuals or groups, and/or correlate with demographic, behavioral or clinical variables. However, it is now widely recognized that the majority of cerebral white matter voxels contain multiple fiber populations with different trajectories, which renders these metrics highly sensitive to the relative volume fractions of the various fiber populations, the microstructural integrity of each constituent fiber population, and the interaction between these factors. Many diffusion imaging experts are aware of these limitations and now generally avoid using FA, AD or RD (at least in isolation) to draw strong reverse inferences about white matter microstructure, but based on the continued application and interpretation of these metrics in the broader biomedical/neuroscience literature, it appears that this has perhaps not yet become common knowledge among diffusion imaging end-users. Therefore, this paper will briefly discuss the complex biophysical underpinnings of these measures in the context of crossing fibers, provide some intuitive “thought experiments” to highlight how conventional interpretations can lead to incorrect conclusions, and suggest that future studies refrain from using (over-interpreting) FA, AD, and RD values as standalone biomarkers of cerebral white matter microstructure.
Collapse
Affiliation(s)
- Chase R. Figley
- Department of Radiology, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg, MB, Canada
- Department of Physiology & Pathophysiology, University of Manitoba, Winnipeg, MB, Canada
- *Correspondence: Chase R. Figley,
| | - Md Nasir Uddin
- Department of Radiology, University of Manitoba, Winnipeg, MB, Canada
- Department of Neurology, University of Rochester, Rochester, NY, United States
| | - Kaihim Wong
- Department of Radiology, University of Manitoba, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg, MB, Canada
| | - Jennifer Kornelsen
- Department of Radiology, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg, MB, Canada
- Department of Physiology & Pathophysiology, University of Manitoba, Winnipeg, MB, Canada
| | - Josep Puig
- Department of Radiology, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre, Winnipeg, MB, Canada
- Girona Biomedical Research Institute (IDIBGI), Hospital Universitari de Girona Dr. Josep Trueta, Girona, Spain
| | - Teresa D. Figley
- Department of Radiology, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg, MB, Canada
- Department of Physiology & Pathophysiology, University of Manitoba, Winnipeg, MB, Canada
| |
Collapse
|
50
|
Miletić S, Bazin PL, Isherwood SJS, Keuken MC, Alkemade A, Forstmann BU. Charting human subcortical maturation across the adult lifespan with in vivo 7 T MRI. Neuroimage 2022; 249:118872. [PMID: 34999202 DOI: 10.1016/j.neuroimage.2022.118872] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 12/20/2021] [Accepted: 01/03/2022] [Indexed: 12/26/2022] Open
Abstract
The human subcortex comprises hundreds of unique structures. Subcortical functioning is crucial for behavior, and disrupted function is observed in common neurodegenerative diseases. Despite their importance, human subcortical structures continue to be difficult to study in vivo. Here we provide a detailed account of 17 prominent subcortical structures and ventricles, describing their approximate iron and myelin contents, morphometry, and their age-related changes across the normal adult lifespan. The results provide compelling insights into the heterogeneity and intricate age-related alterations of these structures. They also show that the locations of many structures shift across the lifespan, which is of direct relevance for the use of standard magnetic resonance imaging atlases. The results further our understanding of subcortical morphometry and neuroimaging properties, and of normal aging processes which ultimately can improve our understanding of neurodegeneration.
Collapse
Affiliation(s)
- Steven Miletić
- University of Amsterdam, Department of Psychology, Integrative Model-based Cognitive Neuroscience research unit (IMCN), Nieuwe Achtergracht 129B, Amsterdam 1001 NK, the Netherlands.
| | - Pierre-Louis Bazin
- University of Amsterdam, Department of Psychology, Integrative Model-based Cognitive Neuroscience research unit (IMCN), Nieuwe Achtergracht 129B, Amsterdam 1001 NK, the Netherlands; Max Planck Institute for Human Cognitive and Brain Sciences, Departments of Neurophysics and Neurology, Stephanstraße 1A, Leipzig, Germany
| | - Scott J S Isherwood
- University of Amsterdam, Department of Psychology, Integrative Model-based Cognitive Neuroscience research unit (IMCN), Nieuwe Achtergracht 129B, Amsterdam 1001 NK, the Netherlands
| | - Max C Keuken
- University of Amsterdam, Department of Psychology, Integrative Model-based Cognitive Neuroscience research unit (IMCN), Nieuwe Achtergracht 129B, Amsterdam 1001 NK, the Netherlands
| | - Anneke Alkemade
- University of Amsterdam, Department of Psychology, Integrative Model-based Cognitive Neuroscience research unit (IMCN), Nieuwe Achtergracht 129B, Amsterdam 1001 NK, the Netherlands
| | - Birte U Forstmann
- University of Amsterdam, Department of Psychology, Integrative Model-based Cognitive Neuroscience research unit (IMCN), Nieuwe Achtergracht 129B, Amsterdam 1001 NK, the Netherlands.
| |
Collapse
|