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Lee JJ, Scheuren PS, Liu H, Loke RWJ, Laule C, Loucks CM, Kramer JLK. The myelin water imaging transcriptome: myelin water fraction regionally varies with oligodendrocyte-specific gene expression. Mol Brain 2024; 17:45. [PMID: 39044257 PMCID: PMC11264438 DOI: 10.1186/s13041-024-01115-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Accepted: 06/19/2024] [Indexed: 07/25/2024] Open
Abstract
Identifying sensitive and specific measures that can quantify myelin are instrumental in characterizing microstructural changes in neurological conditions. Neuroimaging transcriptomics is emerging as a valuable technique in this regard, offering insights into the molecular basis of promising candidates for myelin quantification, such as myelin water fraction (MWF). We aimed to demonstrate the utility of neuroimaging transcriptomics by validating MWF as a myelin measure. We utilized data from a normative MWF brain atlas, comprised of 50 healthy subjects (mean age = 25 years, range = 17-42 years) scanned at 3 Tesla. Magnetic resonance imaging data included myelin water imaging to extract MWF and T1 anatomical scans for image registration and segmentation. We investigated the inter-regional distributions of gene expression data from the Allen Human Brain Atlas in conjunction with inter-regional MWF distribution patterns. Pearson correlations were used to identify genes with expression profiles mirroring MWF. The Single Cell Type Atlas from the Human Protein Atlas was leveraged to classify genes into gene sets with high cell type specificity, and a control gene set with low cell type specificity. Then, we compared the Pearson correlation coefficients for each gene set to determine if cell type-specific gene expression signatures correlate with MWF. Pearson correlation coefficients between MWF and gene expression for oligodendrocytes and adipocytes were significantly higher than for the control gene set, whereas correlations between MWF and inhibitory/excitatory neurons were significantly lower. Our approach in integrating transcriptomics with neuroimaging measures supports an emerging technique for understanding and validating MRI-derived markers such as MWF.
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Affiliation(s)
- Jaimie J Lee
- International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, BC, Canada
- Department of Anesthesiology, Pharmacology, and Therapeutics, University of British Columbia, Vancouver, BC, Canada
| | - Paulina S Scheuren
- International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, BC, Canada
- Department of Anesthesiology, Pharmacology, and Therapeutics, University of British Columbia, Vancouver, BC, Canada
| | - Hanwen Liu
- Department of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Ryan W J Loke
- International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, BC, Canada
- Department of Anesthesiology, Pharmacology, and Therapeutics, University of British Columbia, Vancouver, BC, Canada
| | - Cornelia Laule
- International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, BC, Canada
- Department of Radiology, University of British Columbia, Vancouver, BC, Canada
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
| | - Catrina M Loucks
- Department of Anesthesiology, Pharmacology, and Therapeutics, University of British Columbia, Vancouver, BC, Canada
- Division of Translational Therapeutics, Department of Pediatrics, University of British Columbia, Vancouver, BC, Canada
- BC Children's Hospital Research Institute, Vancouver, BC, Canada
| | - John L K Kramer
- International Collaboration on Repair Discoveries (ICORD), University of British Columbia, Vancouver, BC, Canada.
- Department of Anesthesiology, Pharmacology, and Therapeutics, University of British Columbia, Vancouver, BC, Canada.
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2
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Herthum H, Hetzer S. Tensor denoising of quantitative multi-parameter mapping. Magn Reson Med 2024; 92:145-157. [PMID: 38368616 DOI: 10.1002/mrm.30050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 01/12/2024] [Accepted: 01/25/2024] [Indexed: 02/20/2024]
Abstract
PURPOSE Quantitative multi-parameter mapping (MPM) provides maps of physical quantities representing physiologically meaningful tissue characteristics, which allows to investigate microstructure-function relationships reflecting normal or pathologic processes in the brain. However, the achievable spatial resolution and stability of MPM for basic research or clinical applications is severely constrained by SNR limits of the MR acquisition process, resulting in relatively long acquisition times. To increase SNR, we denoise MPM acquisitions using principal component analysis along tensors exploiting the Marchenko-Pastur law (tMPPCA). METHODS tMPPCA denoising was applied to three sets of MPM raw data before the quantification of maps of proton density, magnetization transfer saturation, R1, and R2*. The regional SNR gain for high-resolution MPM was investigated as well as reproducibility gains for clinically optimized protocols with moderate and high acceleration factors at different image resolutions. RESULTS Substantial noise reduction in raw data was achieved, resulting in reduced noise for quantitative mapping up to sixfold without introducing bias of mean values (below 1%). Scan-rescan fluctuations were reduced up to threefold. Denoising allowed to decrease the voxel volume fourfold at the same scan time or reduce the scan time twofold at same voxel volume without loss of sensitivity. CONCLUSIONS tMPPCA denoising can (a) improve of fine spatial and temporal patterns, (b) considerably reduce scan time for clinical applications, or (c) increase resolution to potentially push cutting-edge MPM protocols from the upper to the lower limit of the mesoscopic scale.
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Affiliation(s)
- Helge Herthum
- Berlin Center for Advanced Neuroimaging, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
- Bernstein Center for Computational Neuroscience, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Stefan Hetzer
- Berlin Center for Advanced Neuroimaging, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
- Bernstein Center for Computational Neuroscience, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
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Takemura H, Kruper JA, Miyata T, Rokem A. Tractometry of Human Visual White Matter Pathways in Health and Disease. Magn Reson Med Sci 2024; 23:316-340. [PMID: 38866532 PMCID: PMC11234945 DOI: 10.2463/mrms.rev.2024-0007] [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] [Indexed: 06/14/2024] Open
Abstract
Diffusion-weighted MRI (dMRI) provides a unique non-invasive view of human brain tissue properties. The present review article focuses on tractometry analysis methods that use dMRI to assess the properties of brain tissue within the long-range connections comprising brain networks. We focus specifically on the major white matter tracts that convey visual information. These connections are particularly important because vision provides rich information from the environment that supports a large range of daily life activities. Many of the diseases of the visual system are associated with advanced aging, and tractometry of the visual system is particularly important in the modern aging society. We provide an overview of the tractometry analysis pipeline, which includes a primer on dMRI data acquisition, voxelwise model fitting, tractography, recognition of white matter tracts, and calculation of tract tissue property profiles. We then review dMRI-based methods for analyzing visual white matter tracts: the optic nerve, optic tract, optic radiation, forceps major, and vertical occipital fasciculus. For each tract, we review background anatomical knowledge together with recent findings in tractometry studies on these tracts and their properties in relation to visual function and disease. Overall, we find that measurements of the brain's visual white matter are sensitive to a range of disorders and correlate with perceptual abilities. We highlight new and promising analysis methods, as well as some of the current barriers to progress toward integration of these methods into clinical practice. These barriers, such as variability in measurements between protocols and instruments, are targets for future development.
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Affiliation(s)
- Hiromasa Takemura
- Division of Sensory and Cognitive Brain Mapping, Department of System Neuroscience, National Institute for Physiological Sciences, Okazaki, Aichi, Japan
- Graduate Institute for Advanced Studies, SOKENDAI, Hayama, Kanagawa, Japan
- Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology, Suita, Osaka, Japan
| | - John A Kruper
- Department of Psychology and eScience Institute, University of Washington, Seattle, WA, USA
| | - Toshikazu Miyata
- Division of Sensory and Cognitive Brain Mapping, Department of System Neuroscience, National Institute for Physiological Sciences, Okazaki, Aichi, Japan
- Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology, Suita, Osaka, Japan
| | - Ariel Rokem
- Department of Psychology and eScience Institute, University of Washington, Seattle, WA, USA
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Filip P, Mana J, Lasica A, Keller J, Urgošík D, May J, Mueller K, Jech R, Bezdicek O, Růžička F. Structural and microstructural predictors of cognitive decline in deep brain stimulation of subthalamic nucleus in Parkinson's disease. Neuroimage Clin 2024; 42:103617. [PMID: 38749145 PMCID: PMC11112358 DOI: 10.1016/j.nicl.2024.103617] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Revised: 03/22/2024] [Accepted: 05/06/2024] [Indexed: 05/26/2024]
Abstract
BACKGROUND AND OBJECTIVES The intricate relationship between deep brain stimulation (DBS) in Parkinson's disease (PD) and cognitive impairment has lately garnered substantial attention. The presented study evaluated pre-DBS structural and microstructural cerebral patterns as possible predictors of future cognitive decline in PD DBS patients. METHODS Pre-DBS MRI data in 72 PD patients were combined with neuropsychological examinations and follow-up for an average of 2.3 years after DBS implantation procedure using a screening cognitive test validated for diagnosis of mild cognitive impairment in PD in a Czech population - Dementia Rating Scale 2. RESULTS PD patients who would exhibit post-DBS cognitive decline were found to have, already at the pre-DBS stage, significantly lower cortical thickness and lower microstructural complexity than cognitively stable PD patients. Differences in the regions directly related to cognition as bilateral parietal, insular and cingulate cortices, but also occipital and sensorimotor cortex were detected. Furthermore, hippocampi, putamina, cerebellum and upper brainstem were implicated as well, all despite the absence of pre-DBS differences in cognitive performance and in the position of DBS leads or stimulation parameters between the two groups. CONCLUSIONS Our findings indicate that the cognitive decline in the presented PD cohort was not attributable primarily to DBS of the subthalamic nucleus but was associated with a clinically silent structural and microstructural predisposition to future cognitive deterioration present already before the DBS system implantation.
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Affiliation(s)
- Pavel Filip
- Department of Neurology, Charles University, First Faculty of Medicine and General University Hospital, Prague, Czech Republic; Department of Cybernetics, Czech Technical University in Prague, Prague, Czech Republic; Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, MN, USA
| | - Josef Mana
- Department of Neurology, Charles University, First Faculty of Medicine and General University Hospital, Prague, Czech Republic
| | - Andrej Lasica
- Department of Neurology, Charles University, First Faculty of Medicine and General University Hospital, Prague, Czech Republic
| | - Jiří Keller
- Department of Radiology, Na Homolce Hospital, Prague, Czech Republic; Third Faculty of Medicine, Charles University in Prague, Prague, Czech Republic
| | - Dušan Urgošík
- Department of Stereotactic and Radiation Neurosurgery, Na Homolce Hospital, Prague, Czech Republic
| | - Jaromír May
- Department of Stereotactic and Radiation Neurosurgery, Na Homolce Hospital, Prague, Czech Republic
| | - Karsten Mueller
- Department of Neurology, Charles University, First Faculty of Medicine and General University Hospital, Prague, Czech Republic; Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Robert Jech
- Department of Neurology, Charles University, First Faculty of Medicine and General University Hospital, Prague, Czech Republic.
| | - Ondrej Bezdicek
- Department of Neurology, Charles University, First Faculty of Medicine and General University Hospital, Prague, Czech Republic
| | - Filip Růžička
- Department of Neurology, Charles University, First Faculty of Medicine and General University Hospital, Prague, Czech Republic
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De Benedictis A, Rossi-Espagnet MC, de Palma L, Sarubbo S, Marras CE. Structural networking of the developing brain: from maturation to neurosurgical implications. Front Neuroanat 2023; 17:1242757. [PMID: 38099209 PMCID: PMC10719860 DOI: 10.3389/fnana.2023.1242757] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Accepted: 11/09/2023] [Indexed: 12/17/2023] Open
Abstract
Modern neuroscience agrees that neurological processing emerges from the multimodal interaction among multiple cortical and subcortical neuronal hubs, connected at short and long distance by white matter, to form a largely integrated and dynamic network, called the brain "connectome." The final architecture of these circuits results from a complex, continuous, and highly protracted development process of several axonal pathways that constitute the anatomical substrate of neuronal interactions. Awareness of the network organization of the central nervous system is crucial not only to understand the basis of children's neurological development, but also it may be of special interest to improve the quality of neurosurgical treatments of many pediatric diseases. Although there are a flourishing number of neuroimaging studies of the connectome, a comprehensive vision linking this research to neurosurgical practice is still lacking in the current pediatric literature. The goal of this review is to contribute to bridging this gap. In the first part, we summarize the main current knowledge concerning brain network maturation and its involvement in different aspects of normal neurocognitive development as well as in the pathophysiology of specific diseases. The final section is devoted to identifying possible implications of this knowledge in the neurosurgical field, especially in epilepsy and tumor surgery, and to discuss promising perspectives for future investigations.
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Affiliation(s)
| | | | - Luca de Palma
- Clinical and Experimental Neurology, Bambino Gesù Children’s Hospital, Rome, Italy
| | - Silvio Sarubbo
- Department of Neurosurgery, Santa Chiara Hospital, Azienda Provinciale per i Servizi Sanitari (APSS), Trento, Italy
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Talwar P, Deantoni M, Van Egroo M, Muto V, Chylinski D, Koshmanova E, Jaspar M, Meyer C, Degueldre C, Berthomier C, Luxen A, Salmon E, Collette F, Dijk DJ, Schmidt C, Phillips C, Maquet P, Sherif S, Vandewalle G. In vivo marker of brainstem myelin is associated to quantitative sleep parameters in healthy young men. Sci Rep 2023; 13:20873. [PMID: 38012207 PMCID: PMC10682495 DOI: 10.1038/s41598-023-47753-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 11/17/2023] [Indexed: 11/29/2023] Open
Abstract
The regional integrity of brain subcortical structures has been implicated in sleep-wake regulation, however, their associations with sleep parameters remain largely unexplored. Here, we assessed association between quantitative Magnetic Resonance Imaging (qMRI)-derived marker of the myelin content of the brainstem and the variability in the sleep electrophysiology in a large sample of 18-to-31 years healthy young men (N = 321; ~ 22 years). Separate Generalized Additive Model for Location, Scale and Shape (GAMLSS) revealed that sleep onset latency and slow wave energy were significantly associated with MTsat estimates in the brainstem (pcorrected ≤ 0.03), with overall higher MTsat value associated with values reflecting better sleep quality. The association changed with age, however (MTsat-by-age interaction-pcorrected ≤ 0.03), with higher MTsat value linked to better values in the two sleep metrics in the younger individuals of our sample aged ~ 18 to 20 years. Similar associations were detected across different parts of the brainstem (pcorrected ≤ 0.03), suggesting that the overall maturation and integrity of the brainstem was associated with both sleep metrics. Our results suggest that myelination of the brainstem nuclei essential to regulation of sleep is associated with inter-individual differences in sleep characteristics during early adulthood. They may have implications for sleep disorders or neurological diseases related to myelin.
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Affiliation(s)
- Puneet Talwar
- GIGA-Institute, CRC-In Vivo Imaging Unit, Bâtiment B30, Université de Liège, 4000, Liège, Belgium
| | - Michele Deantoni
- GIGA-Institute, CRC-In Vivo Imaging Unit, Bâtiment B30, Université de Liège, 4000, Liège, Belgium
| | - Maxime Van Egroo
- GIGA-Institute, CRC-In Vivo Imaging Unit, Bâtiment B30, Université de Liège, 4000, Liège, Belgium
- Faculty of Health, Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, Maastricht, The Netherlands
| | - Vincenzo Muto
- GIGA-Institute, CRC-In Vivo Imaging Unit, Bâtiment B30, Université de Liège, 4000, Liège, Belgium
- Walloon Excellence in Life Sciences and Biotechnology (WELBIO), Wallonia, Belgium
- Psychology and Cognitive Neuroscience Research Unit, University of Liège, Liège, Belgium
| | - Daphne Chylinski
- GIGA-Institute, CRC-In Vivo Imaging Unit, Bâtiment B30, Université de Liège, 4000, Liège, Belgium
| | - Ekaterina Koshmanova
- GIGA-Institute, CRC-In Vivo Imaging Unit, Bâtiment B30, Université de Liège, 4000, Liège, Belgium
| | - Mathieu Jaspar
- GIGA-Institute, CRC-In Vivo Imaging Unit, Bâtiment B30, Université de Liège, 4000, Liège, Belgium
- Walloon Excellence in Life Sciences and Biotechnology (WELBIO), Wallonia, Belgium
| | - Christelle Meyer
- GIGA-Institute, CRC-In Vivo Imaging Unit, Bâtiment B30, Université de Liège, 4000, Liège, Belgium
- Walloon Excellence in Life Sciences and Biotechnology (WELBIO), Wallonia, Belgium
| | - Christian Degueldre
- GIGA-Institute, CRC-In Vivo Imaging Unit, Bâtiment B30, Université de Liège, 4000, Liège, Belgium
| | | | - André Luxen
- GIGA-Institute, CRC-In Vivo Imaging Unit, Bâtiment B30, Université de Liège, 4000, Liège, Belgium
| | - Eric Salmon
- GIGA-Institute, CRC-In Vivo Imaging Unit, Bâtiment B30, Université de Liège, 4000, Liège, Belgium
- Psychology and Cognitive Neuroscience Research Unit, University of Liège, Liège, Belgium
- Department of Neurology, CHU of Liège, Liège, Belgium
| | - Fabienne Collette
- GIGA-Institute, CRC-In Vivo Imaging Unit, Bâtiment B30, Université de Liège, 4000, Liège, Belgium
- Psychology and Cognitive Neuroscience Research Unit, University of Liège, Liège, Belgium
| | - D-J Dijk
- Sleep Research Centre, University of Surrey, Guildford, UK
- UK Dementia Research Institute, University of Surrey, Guildford, UK
| | - Christina Schmidt
- GIGA-Institute, CRC-In Vivo Imaging Unit, Bâtiment B30, Université de Liège, 4000, Liège, Belgium
- Psychology and Cognitive Neuroscience Research Unit, University of Liège, Liège, Belgium
| | - Christophe Phillips
- GIGA-Institute, CRC-In Vivo Imaging Unit, Bâtiment B30, Université de Liège, 4000, Liège, Belgium
- In Silico Medicine Unit, GIGA-Institute, University of Liège, Liège, Belgium
| | - Pierre Maquet
- GIGA-Institute, CRC-In Vivo Imaging Unit, Bâtiment B30, Université de Liège, 4000, Liège, Belgium
- Walloon Excellence in Life Sciences and Biotechnology (WELBIO), Wallonia, Belgium
- Department of Neurology, CHU of Liège, Liège, Belgium
| | - Siya Sherif
- GIGA-Institute, CRC-In Vivo Imaging Unit, Bâtiment B30, Université de Liège, 4000, Liège, Belgium
| | - Gilles Vandewalle
- GIGA-Institute, CRC-In Vivo Imaging Unit, Bâtiment B30, Université de Liège, 4000, Liège, Belgium.
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Filo S, Shaharabani R, Bar Hanin D, Adam M, Ben-David E, Schoffman H, Margalit N, Habib N, Shahar T, Mezer AA. Non-invasive assessment of normal and impaired iron homeostasis in the brain. Nat Commun 2023; 14:5467. [PMID: 37699931 PMCID: PMC10497590 DOI: 10.1038/s41467-023-40999-z] [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: 01/10/2023] [Accepted: 08/17/2023] [Indexed: 09/14/2023] Open
Abstract
Strict iron regulation is essential for normal brain function. The iron homeostasis, determined by the milieu of available iron compounds, is impaired in aging, neurodegenerative diseases and cancer. However, non-invasive assessment of different molecular iron environments implicating brain tissue's iron homeostasis remains a challenge. We present a magnetic resonance imaging (MRI) technology sensitive to the iron homeostasis of the living brain (the r1-r2* relaxivity). In vitro, our MRI approach reveals the distinct paramagnetic properties of ferritin, transferrin and ferrous iron ions. In the in vivo human brain, we validate our approach against ex vivo iron compounds quantification and gene expression. Our approach varies with the iron mobilization capacity across brain regions and in aging. It reveals brain tumors' iron homeostasis, and enhances the distinction between tumor tissue and non-pathological tissue without contrast agents. Therefore, our approach may allow for non-invasive research and diagnosis of iron homeostasis in living human brains.
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Affiliation(s)
- Shir Filo
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel.
| | - Rona Shaharabani
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Daniel Bar Hanin
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Miriam Adam
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Eliel Ben-David
- The Department of Radiology, Shaare Zedek Medical Center, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Hanan Schoffman
- The Laboratory of Molecular Neuro-Oncology, Shaare Zedek Medical Center, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Nevo Margalit
- The Department of Neurosurgery, Shaare Zedek Medical Center, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Naomi Habib
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Tal Shahar
- The Laboratory of Molecular Neuro-Oncology, Shaare Zedek Medical Center, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
- The Department of Neurosurgery, Shaare Zedek Medical Center, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
- The Department of Neurosurgery, Tel Aviv Sourasky Medical Center, Affiliated with Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Aviv A Mezer
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
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8
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Hamid C, Maiworm M, Wagner M, Knake S, Nöth U, Deichmann R, Gracien RM, Seiler A. Focal epilepsy without overt epileptogenic lesions: no evidence of microstructural brain tissue damage in multi-parametric quantitative MRI. Front Neurol 2023; 14:1175971. [PMID: 37528856 PMCID: PMC10389268 DOI: 10.3389/fneur.2023.1175971] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 07/03/2023] [Indexed: 08/03/2023] Open
Abstract
Background and purpose In patients with epilepsies of structural origin, brain atrophy and pathological alterations of the tissue microstructure extending beyond the putative epileptogenic lesion have been reported. However, in patients without any evidence of epileptogenic lesions on diagnostic magnetic resonance imaging (MRI), impairment of the brain microstructure has been scarcely elucidated. Using multiparametric quantitative (q) magnetic resonance imaging MRI, we aimed to investigate diffuse impairment of the microstructural tissue integrity in MRI-negative focal epilepsy patients. Methods 27 MRI-negative patients with focal epilepsy (mean age 33.1 ± 14.2 years) and 27 matched healthy control subjects underwent multiparametric qMRI including T1, T2, and PD mapping at 3 T. After tissue segmentation based on synthetic anatomies, mean qMRI parameter values were extracted from the cerebral cortex, the white matter (WM) and the deep gray matter (GM) and compared between patients and control subjects. Apart from calculating mean values for the qMRI parameters across the respective compartments, voxel-wise analyses were performed for each tissue class. Results There were no significant differences for mean values of quantitative T1, T2, and PD obtained from the cortex, the WM and the deep GM between the groups. Furthermore, the voxel-wise analyses did not reveal any clusters indicating significant differences between patients and control subjects for the qMRI parameters in the respective compartments. Conclusions Based on the employed methodology, no indication for an impairment of the cerebral microstructural tissue integrity in MRI-negative patients with focal epilepsy was found in this study. Further research will be necessary to identify relevant factors and mechanisms contributing to microstructural brain tissue damage in various subgroups of patients with epilepsy.
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Affiliation(s)
- Celona Hamid
- Department of Neurology, Goethe University Hospital, Frankfurt, Germany
- Brain Imaging Center, Goethe University Frankfurt, Frankfurt, Germany
- Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Frankfurt, Germany
| | - Michelle Maiworm
- Department of Neurology, Goethe University Hospital, Frankfurt, Germany
- Brain Imaging Center, Goethe University Frankfurt, Frankfurt, Germany
| | - Marlies Wagner
- Brain Imaging Center, Goethe University Frankfurt, Frankfurt, Germany
- Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Frankfurt, Germany
- Institute of Neuroradiology, Goethe University Hospital, Frankfurt, Germany
| | - Susanne Knake
- Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Frankfurt, Germany
- Epilepsy Center Hessen and Department of Neurology, Philipps-University Marburg, Marburg, Germany
| | - Ulrike Nöth
- Brain Imaging Center, Goethe University Frankfurt, Frankfurt, Germany
- Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Frankfurt, Germany
| | - Ralf Deichmann
- Brain Imaging Center, Goethe University Frankfurt, Frankfurt, Germany
- Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Frankfurt, Germany
| | - René-Maxime Gracien
- Department of Neurology, Goethe University Hospital, Frankfurt, Germany
- Brain Imaging Center, Goethe University Frankfurt, Frankfurt, Germany
- Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Frankfurt, Germany
| | - Alexander Seiler
- Department of Neurology, Goethe University Hospital, Frankfurt, Germany
- Brain Imaging Center, Goethe University Frankfurt, Frankfurt, Germany
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9
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Bazinet V, Hansen JY, Vos de Wael R, Bernhardt BC, van den Heuvel MP, Misic B. Assortative mixing in micro-architecturally annotated brain connectomes. Nat Commun 2023; 14:2850. [PMID: 37202416 DOI: 10.1038/s41467-023-38585-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 05/08/2023] [Indexed: 05/20/2023] Open
Abstract
The wiring of the brain connects micro-architecturally diverse neuronal populations, but the conventional graph model, which encodes macroscale brain connectivity as a network of nodes and edges, abstracts away the rich biological detail of each regional node. Here, we annotate connectomes with multiple biological attributes and formally study assortative mixing in annotated connectomes. Namely, we quantify the tendency for regions to be connected based on the similarity of their micro-architectural attributes. We perform all experiments using four cortico-cortical connectome datasets from three different species, and consider a range of molecular, cellular, and laminar annotations. We show that mixing between micro-architecturally diverse neuronal populations is supported by long-distance connections and find that the arrangement of connections with respect to biological annotations is associated to patterns of regional functional specialization. By bridging scales of cortical organization, from microscale attributes to macroscale connectivity, this work lays the foundation for next-generation annotated connectomics.
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Affiliation(s)
- Vincent Bazinet
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada
| | - Justine Y Hansen
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada
| | - Reinder Vos de Wael
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada
| | - Boris C Bernhardt
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada
| | - Martijn P van den Heuvel
- Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Bratislav Misic
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada.
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10
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Morita T, Takemura H, Naito E. Functional and Structural Properties of Interhemispheric Interaction between Bilateral Precentral Hand Motor Regions in a Top Wheelchair Racing Paralympian. Brain Sci 2023; 13:brainsci13050715. [PMID: 37239187 DOI: 10.3390/brainsci13050715] [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: 03/15/2023] [Revised: 04/14/2023] [Accepted: 04/23/2023] [Indexed: 05/28/2023] Open
Abstract
Long-term motor training can cause functional and structural changes in the human brain. Assessing how the training of specific movements affects specific parts of the neural circuitry is essential to understand better the underlying mechanisms of motor training-induced plasticity in the human brain. We report a single-case neuroimaging study that investigated functional and structural properties in a professional athlete of wheelchair racing. As wheelchair racing requires bilateral synchronization of upper limb movements, we hypothesized that functional and structural properties of interhemispheric interactions in the central motor system might differ between the professional athlete and controls. Functional and diffusion magnetic resonance imaging (fMRI and dMRI) data were obtained from a top Paralympian (P1) in wheelchair racing. With 23 years of wheelchair racing training starting at age eight, she holds an exceptional competitive record. Furthermore, fMRI and dMRI data were collected from three other paraplegic participants (P2-P4) with long-term wheelchair sports training other than wheelchair racing and 37 able-bodied control volunteers. Based on the fMRI data analyses, P1 showed activation in the bilateral precentral hand sections and greater functional connectivity between these sections during a right-hand unimanual task. In contrast, other paraplegic participants and controls showed activation in the contralateral hemisphere and deactivation in the ipsilateral hemisphere. Moreover, dMRI data analysis revealed that P1 exhibited significantly lower mean diffusivity along the transcallosal pathway connecting the bilateral precentral motor regions than control participants, which was not observed in the other paraplegic participants. These results suggest that long-term training with bilaterally synchronized upper-limb movements may promote bilateral recruitment of the precentral hand sections. Such recruitment may affect the structural circuitry involved in the interhemispheric interaction between the bilateral precentral regions. This study provides valuable evidence of the extreme adaptability of the human brain.
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Affiliation(s)
- Tomoyo Morita
- Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology (NICT), 2A6 1-4 Yamadaoka, Suita 565-0871, Osaka, Japan
- Graduate School of Frontier Biosciences, Osaka University, 1-3 Yamadaoka, Suita 565-0871, Osaka, Japan
| | - Hiromasa Takemura
- Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology (NICT), 2A6 1-4 Yamadaoka, Suita 565-0871, Osaka, Japan
- Division of Sensory and Cognitive Brain Mapping, Department of System Neuroscience, National Institute for Physiological Sciences, 38 Nishigonaka Myodaiji, Okazaki 444-8585, Aichi, Japan
- The Graduate Institute for Advanced Studies, SOKENDAI, Shonan Village, Hayama 240-0193, Kanagawa, Japan
| | - Eiichi Naito
- Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology (NICT), 2A6 1-4 Yamadaoka, Suita 565-0871, Osaka, Japan
- Graduate School of Frontier Biosciences, Osaka University, 1-3 Yamadaoka, Suita 565-0871, Osaka, Japan
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11
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Piredda GF, Caneschi S, Hilbert T, Bonanno G, Joseph A, Egger K, Peter J, Klöppel S, Jehli E, Grieder M, Slotboom J, Seiffge D, Goeldlin M, Hoepner R, Willems T, Vulliemoz S, Seeck M, Venkategowda PB, Corredor Jerez RA, Maréchal B, Thiran JP, Wiest R, Kober T, Radojewski P. Submillimeter T 1 atlas for subject-specific abnormality detection at 7T. Magn Reson Med 2023; 89:1601-1616. [PMID: 36478417 DOI: 10.1002/mrm.29540] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 10/14/2022] [Accepted: 11/07/2022] [Indexed: 12/12/2022]
Abstract
PURPOSE Studies at 3T have shown that T1 relaxometry enables characterization of brain tissues at the single-subject level by comparing individual physical properties to a normative atlas. In this work, an atlas of normative T1 values at 7T is introduced with 0.6 mm isotropic resolution and its clinical potential is explored in comparison to 3T. METHODS T1 maps were acquired in two separate healthy cohorts scanned at 3T and 7T. Using transfer learning, a template-based brain segmentation algorithm was adapted to ultra-high field imaging data. After segmenting brain tissues, volumes were normalized into a common space, and an atlas of normative T1 values was established by modeling the T1 inter-subject variability. A method for single-subject comparisons restricted to white matter and subcortical structures was developed by computing Z-scores. The comparison was applied to eight patients scanned at both field strengths for proof of concept. RESULTS The proposed method for morphometry delivered segmentation masks without statistically significant differences from those derived with the original pipeline at 3T and achieved accurate segmentation at 7T. The established normative atlas allowed characterizing tissue alterations in single-subject comparisons at 7T, and showed greater anatomical details compared with 3T results. CONCLUSION A high-resolution quantitative atlas with an adapted pipeline was introduced and validated. Several case studies on different clinical conditions showed the feasibility, potential and limitations of high-resolution single-subject comparisons based on quantitative MRI atlases. This method in conjunction with 7T higher resolution broadens the range of potential applications of quantitative MRI in clinical practice.
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Affiliation(s)
- Gian Franco Piredda
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland.,Human Neuroscience Platform, Fondation Campus Biotech Geneva, Geneva, Switzerland.,CIBM-AIT, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Samuele Caneschi
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland.,Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tom Hilbert
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland.,Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Gabriele Bonanno
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Bern, Switzerland.,Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland.,Magnetic Resonance Methodology, Institute of Diagnostic and Interventional Neuroradiology, University of Bern, Bern, Switzerland
| | - Arun Joseph
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Bern, Switzerland.,Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland.,Magnetic Resonance Methodology, Institute of Diagnostic and Interventional Neuroradiology, University of Bern, Bern, Switzerland
| | - Karl Egger
- Department of Neuroradiology, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Jessica Peter
- University Hospital of Old Age Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Stefan Klöppel
- University Hospital of Old Age Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Elisabeth Jehli
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland.,Department of Neurosurgery, University Hospital of Zurich, Zurich, Switzerland
| | - Matthias Grieder
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Johannes Slotboom
- Support Center for Advanced Neuroimaging, Institute for Diagnostic and Interventional Neuroradiology, Inselspital, University of Bern, Bern, Switzerland
| | - David Seiffge
- Department of Neurology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Martina Goeldlin
- Department of Neurology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Robert Hoepner
- Department of Neurology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Tom Willems
- Institute of Psychology, University of Bern, Bern, Switzerland
| | - Serge Vulliemoz
- EEG and Epilepsy Unit, Department of Clinical Neurosciences, Geneva University Hospitals and Faculty of Medicine, Geneva, Switzerland
| | - Margitta Seeck
- EEG and Epilepsy Unit, Department of Clinical Neurosciences, Geneva University Hospitals and Faculty of Medicine, Geneva, Switzerland
| | | | - Ricardo A Corredor Jerez
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland.,Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Bénédicte Maréchal
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland.,Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Jean-Philippe Thiran
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Roland Wiest
- Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland.,Support Center for Advanced Neuroimaging, Institute for Diagnostic and Interventional Neuroradiology, Inselspital, University of Bern, Bern, Switzerland
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland.,Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Piotr Radojewski
- Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland.,Support Center for Advanced Neuroimaging, Institute for Diagnostic and Interventional Neuroradiology, Inselspital, University of Bern, Bern, Switzerland
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12
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Milotta G, Green I, Roiser JP, Callaghan MF. In vivo multi-parameter mapping of the habenula using MRI. Sci Rep 2023; 13:3754. [PMID: 36882432 PMCID: PMC9992523 DOI: 10.1038/s41598-023-28446-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Accepted: 01/18/2023] [Indexed: 03/09/2023] Open
Abstract
The habenula is a small, epithalamic brain structure situated between the mediodorsal thalamus and the third ventricle. It plays an important role in the reward circuitry of the brain and is implicated in psychiatric conditions, such as depression. The importance of the habenula for human cognition and mental health make it a key structure of interest for neuroimaging studies. However, few studies have characterised the physical properties of the human habenula using magnetic resonance imaging because its challenging visualisation in vivo, primarily due to its subcortical location and small size. To date, microstructural characterization of the habenula has focused on quantitative susceptibility mapping. In this work, we complement this previous characterisation with measures of longitudinal and effective transverse relaxation rates, proton density and magnetisation transfer saturation using a high-resolution quantitative multi-parametric mapping protocol at 3T, in a cohort of 26 healthy participants. The habenula had consistent boundaries across the various parameter maps and was most clearly visualised on the longitudinal relaxation rate maps. We have provided a quantitative multi-parametric characterisation that may be useful for future sequence optimisation to enhance visualisation of the habenula, and additionally provides reference values for future studies investigating pathological differences in habenula microstructure.
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Affiliation(s)
- Giorgia Milotta
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK.
| | - Isobel Green
- Program in Neuroscience, Harvard Medical School, Boston, MA, 02115, USA
| | - Jonathan P Roiser
- UCL Institute of Cognitive Neuroscience, 17 Queen Square, London, WC1N 3AZ, UK
| | - Martina F Callaghan
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
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13
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Moinian S, Vegh V, Reutens D. Towards automated in vivo parcellation of the human cerebral cortex using supervised classification of magnetic resonance fingerprinting residuals. Cereb Cortex 2023; 33:1550-1565. [PMID: 35483706 PMCID: PMC9977388 DOI: 10.1093/cercor/bhac155] [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: 11/23/2021] [Revised: 03/29/2022] [Accepted: 03/30/2022] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Accurate parcellation of the cerebral cortex in an individual is a guide to its underlying organization. The most promising in vivo quantitative magnetic resonance (MR)-based microstructural cortical mapping methods are yet to achieve a level of parcellation accuracy comparable to quantitative histology. METHODS We scanned 6 participants using a 3D echo-planar imaging MR fingerprinting (EPI-MRF) sequence on a 7T Siemens scanner. After projecting MRF signals to the individual-specific inflated model of the cortical surface, normalized autocorrelations of MRF residuals of vertices of 8 microstructurally distinct areas (BA1, BA2, BA4a, BA6, BA44, BA45, BA17, and BA18) from 3 cortical regions were used as feature vector inputs into linear support vector machine (SVM), radial basis function SVM (RBF-SVM), random forest, and k-nearest neighbors supervised classification algorithms. The algorithms' prediction performance was compared using: (i) features from each vertex or (ii) features from neighboring vertices. RESULTS The neighborhood-based RBF-SVM classifier achieved the highest prediction score of 0.85 for classification of MRF residuals in the central region from a held-out participant. CONCLUSIONS We developed an automated method of cortical parcellation using a combination of MR fingerprinting residual analysis and machine learning classification. Our findings provide the basis for employing unsupervised learning algorithms for whole-cortex structural parcellation in individuals.
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Affiliation(s)
- Shahrzad Moinian
- Centre for Advanced Imaging, The University of Queensland, Building 57, Research Road, St Lucia, QLD 4072, Australia
- ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Building 57, Research Road, St Lucia, QLD 4072, Australia
| | - Viktor Vegh
- Centre for Advanced Imaging, The University of Queensland, Building 57, Research Road, St Lucia, QLD 4072, Australia
- ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Building 57, Research Road, St Lucia, QLD 4072, Australia
| | - David Reutens
- Centre for Advanced Imaging, The University of Queensland, Building 57, Research Road, St Lucia, QLD 4072, Australia
- ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Building 57, Research Road, St Lucia, QLD 4072, Australia
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14
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Guo H, Zhou J, Liu P, Chen H. Phase-constrained reconstruction method with compressed sensing for multi-parametric quantitative magnetic resonance imaging. Biomed Signal Process Control 2023. [DOI: 10.1016/j.bspc.2022.104383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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15
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Gräßle T, Crockford C, Eichner C, Girard‐Buttoz C, Jäger C, Kirilina E, Lipp I, Düx A, Edwards L, Jauch A, Kopp KS, Paquette M, Pine K, Haun DBM, McElreath R, Anwander A, Gunz P, Morawski M, Friederici AD, Weiskopf N, Leendertz FH, Wittig RM, Albig K, Amarasekaran B, Angedakin S, Anwander A, Aschoff D, Asiimwe C, Bailanda L, Beehner JC, Belais R, Bergman TJ, Blazey B, Bernhard A, Bock C, Carlier P, Chantrey J, Crockford C, Deschner T, Düx A, Edwards L, Eichner C, Escoubas G, Ettaj M, Fedurek P, Flores K, Francke R, Friederici AD, Girard‐Buttoz C, Fortun JG, GoneBi ZB, Gräßle T, Gruber‐Dujardin E, Gunz P, Hartel J, Haun DBM, Henshall M, Hobaiter C, Hofman N, Jaffe JE, Jäger C, Jauch A, Kahemere S, Kirilina E, Klopfleisch R, Knauf‐Witzens T, Kopp KS, Kouima GLM, Lange B, Langergraber K, Lawrenz A, Leendertz FH, Lipp I, Liptovszky M, Theron TL, Lumbu CP, Nzassi PM, Mätz‐Rensing K, McElreath R, McLennan M, Mezö Z, Moittie S, Møller T, Morawski M, Morgan D, Mugabe T, Muller M, Müller M, Njumboket I, Olofsson‐Sannö K, Ondzie A, Otali E, Paquette M, Pika S, Pine K, Pizarro A, Pléh K, Rendel J, Reichler‐Danielowski S, Robbins MM, Forero AR, Ruske K, Samuni L, Sanz C, Schüle A, Schwabe I, Schwalm K, Speede S, Southern L, Steiner J, Stidworthy M, Surbeck M, Szentiks C, Tanga T, Ulrich R, Unwin S, van de Waal E, Walker S, Weiskopf N, Wibbelt G, Wittig RM, Wood K, Zuberbühler K. Sourcing high tissue quality brains from deceased wild primates with known socio‐ecology. Methods Ecol Evol 2023. [DOI: 10.1111/2041-210x.14039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Affiliation(s)
- Tobias Gräßle
- Epidemiology of highly pathogenic microorganisms Robert Koch‐Institute Berlin Germany
- Helmholtz Institute for One Health Greifswald Germany
| | - Catherine Crockford
- Ape Social Mind Lab Institute of Cognitive Science Marc Jeannerod, UMR 5229, CNRS Lyon France
- Department of Human Behavior, Ecology and Culture Max Planck Institute for Evolutionary Anthropology Leipzig Germany
- Taï Chimpanzee Project Centre Suisse de Recherches Scientifiques en Côte d'Ivoire Abidjan Ivory Coast
| | - Cornelius Eichner
- Department of Neuropsychology Max Planck Institute for Human Cognitive and Brain Sciences Leipzig Germany
| | - Cédric Girard‐Buttoz
- Ape Social Mind Lab Institute of Cognitive Science Marc Jeannerod, UMR 5229, CNRS Lyon France
- Department of Human Behavior, Ecology and Culture Max Planck Institute for Evolutionary Anthropology Leipzig Germany
- Taï Chimpanzee Project Centre Suisse de Recherches Scientifiques en Côte d'Ivoire Abidjan Ivory Coast
| | - Carsten Jäger
- Department of Neurophysics Max Planck Institute for Human Cognitive and Brain Sciences Leipzig Germany
- Paul Flechsig Institute ‐ Center of Neuropathology and Brain Research, Faculty of Medicine Universität Leipzig Germany
| | - Evgeniya Kirilina
- Department of Neurophysics Max Planck Institute for Human Cognitive and Brain Sciences Leipzig Germany
- Center for Cognitive Neuroscience Berlin Freie Universität Berlin Berlin Germany
| | - Ilona Lipp
- Department of Neurophysics Max Planck Institute for Human Cognitive and Brain Sciences Leipzig Germany
| | - Ariane Düx
- Epidemiology of highly pathogenic microorganisms Robert Koch‐Institute Berlin Germany
- Helmholtz Institute for One Health Greifswald Germany
| | - Luke Edwards
- Department of Neurophysics Max Planck Institute for Human Cognitive and Brain Sciences Leipzig Germany
| | - Anna Jauch
- Department of Neurophysics Max Planck Institute for Human Cognitive and Brain Sciences Leipzig Germany
| | - Kathrin S. Kopp
- Department of Comparative Cultural Psychology Max Planck Institute for Evolutionary Anthropology Leipzig Germany
| | - Michael Paquette
- Department of Neurophysics Max Planck Institute for Human Cognitive and Brain Sciences Leipzig Germany
| | - Kerrin Pine
- Department of Neurophysics Max Planck Institute for Human Cognitive and Brain Sciences Leipzig Germany
| | - Daniel B. M. Haun
- Department of Comparative Cultural Psychology Max Planck Institute for Evolutionary Anthropology Leipzig Germany
| | - Richard McElreath
- Department of Human Behavior, Ecology and Culture Max Planck Institute for Evolutionary Anthropology Leipzig Germany
| | - Alfred Anwander
- Department of Neuropsychology Max Planck Institute for Human Cognitive and Brain Sciences Leipzig Germany
| | - Philipp Gunz
- Department of Human Evolution Max Planck Institute for Evolutionary Anthropology Leipzig Germany
| | - Markus Morawski
- Department of Neurophysics Max Planck Institute for Human Cognitive and Brain Sciences Leipzig Germany
- Paul Flechsig Institute ‐ Center of Neuropathology and Brain Research, Faculty of Medicine Universität Leipzig Germany
| | - Angela D. Friederici
- Department of Neuropsychology Max Planck Institute for Human Cognitive and Brain Sciences Leipzig Germany
| | - 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
| | - Fabian H. Leendertz
- Epidemiology of highly pathogenic microorganisms Robert Koch‐Institute Berlin Germany
- Helmholtz Institute for One Health Greifswald Germany
| | - Roman M. Wittig
- Ape Social Mind Lab Institute of Cognitive Science Marc Jeannerod, UMR 5229, CNRS Lyon France
- Department of Human Behavior, Ecology and Culture Max Planck Institute for Evolutionary Anthropology Leipzig Germany
- Taï Chimpanzee Project Centre Suisse de Recherches Scientifiques en Côte d'Ivoire Abidjan Ivory Coast
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Milotta G, Corbin N, Lambert C, Lutti A, Mohammadi S, Callaghan MF. Mitigating the impact of flip angle and orientation dependence in single compartment R2* estimates via 2-pool modeling. Magn Reson Med 2023; 89:128-143. [PMID: 36161672 PMCID: PMC9827921 DOI: 10.1002/mrm.29428] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Revised: 07/08/2022] [Accepted: 08/08/2022] [Indexed: 01/12/2023]
Abstract
PURPOSE The effective transverse relaxation rate (R 2 * $$ {\mathrm{R}}_2^{\ast } $$ ) is influenced by biological features that make it a useful means of probing brain microstructure. However, confounding factors such as dependence on flip angle (α) and fiber orientation with respect to the main field (θ $$ \uptheta $$ ) complicate interpretation. The α- andθ $$ \uptheta $$ -dependence stem from the existence of multiple sub-voxel micro-environments (e.g., myelin and non-myelin water compartments). Ordinarily, it is challenging to quantify these sub-compartments; therefore, neuroscientific studies commonly make the simplifying assumption of a mono-exponential decay obtaining a singleR 2 * $$ {\mathrm{R}}_2^{\ast } $$ estimate per voxel. In this work, we investigated how the multi-compartment nature of tissue microstructure affects single compartmentR 2 * $$ {\mathrm{R}}_2^{\ast } $$ estimates. METHODS We used 2-pool (myelin and non-myelin water) simulations to characterize the bias in single compartmentR 2 * $$ {\mathrm{R}}_2^{\ast } $$ estimates. Based on our numeric observations, we introduced a linear model that partitionsR 2 * $$ {\mathrm{R}}_2^{\ast } $$ into α-dependent and α-independent components and validated this in vivo at 7T. We investigated the dependence of both components on the sub-compartment properties and assessed their robustness, orientation dependence, and reproducibility empirically. RESULTS R 2 * $$ {\mathrm{R}}_2^{\ast } $$ increased with myelin water fraction and residency time leading to a linear dependence on α. We observed excellent agreement between our numeric and empirical results. Furthermore, the α-independent component of the proposed linear model was robust to the choice of α and reduced dependence on fiber orientation, although it suffered from marginally higher noise sensitivity. CONCLUSION We have demonstrated and validated a simple approach that mitigates flip angle and orientation biases in single-compartmentR 2 * $$ {\mathrm{R}}_2^{\ast } $$ estimates.
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Affiliation(s)
- Giorgia Milotta
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of NeurologyUniversity College London
LondonUnited Kingdom
| | - Nadège Corbin
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of NeurologyUniversity College London
LondonUnited Kingdom
- Centre de Résonance Magnétique des Systèmes Biologiques, UMR5536CNRS/University BordeauxBordeauxFrance
| | - Christian Lambert
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of NeurologyUniversity College London
LondonUnited Kingdom
| | - Antoine Lutti
- Laboratory for Research in Neuroimaging, Department for Clinical NeuroscienceLausanne University Hospital and University of LausanneLausanneSwitzerland
| | - Siawoosh Mohammadi
- Department of Systems NeurosciencesUniversity Medical Center Hamburg‐EppendorfHamburgGermany
- Department of NeurophysicsMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Martina F. Callaghan
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of NeurologyUniversity College London
LondonUnited Kingdom
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17
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Oishi H, Takemura H, Amano K. Macromolecular tissue volume mapping of lateral geniculate nucleus subdivisions in living human brains. Neuroimage 2023; 265:119777. [PMID: 36462730 DOI: 10.1016/j.neuroimage.2022.119777] [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: 03/08/2022] [Revised: 11/26/2022] [Accepted: 11/29/2022] [Indexed: 12/03/2022] Open
Abstract
The lateral geniculate nucleus (LGN) is a key thalamic nucleus in the visual system, which has an important function in relaying retinal visual input to the visual cortex. The human LGN is composed mainly of magnocellular (M) and parvocellular (P) subdivisions, each of which has different stimulus selectivity in neural response properties. Previous studies have discussed the potential relationship between LGN subdivisions and visual disorders based on psychophysical data on specific types of visual stimuli. However, these relationships remain speculative because non-invasive measurements of these subdivisions are difficult due to the small size of the LGN. Here we propose a method to identify these subdivisions by combining two structural MR measures: high-resolution proton-density weighted images and macromolecular tissue volume (MTV) maps. We defined the M and P subdivisions based on MTV fraction data and tested the validity of the definition by (1) comparing the data with that from human histological studies, (2) comparing the data with functional magnetic resonance imaging measurements on stimulus selectivity, and (3) analyzing the test-retest reliability. The findings demonstrated that the spatial organization of the M and P subdivisions was consistent across subjects and in line with LGN subdivisions observed in human histological data. Moreover, the difference in stimulus selectivity between the subdivisions identified using MTV was consistent with previous physiology literature. The definition of the subdivisions based on MTV was shown to be robust over measurements taken on different days. These results suggest that MTV mapping is a promising approach for evaluating the tissue properties of LGN subdivisions in living humans. This method potentially will enable neuroscientific and clinical hypotheses about the human LGN subdivisions to be tested.
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Affiliation(s)
- Hiroki Oishi
- Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology, Suita 565-0871, Japan; Graduate School of Frontier Biosciences, Osaka University, Suita 565-0871, Japan; Department of Psychology, University of California, Berkeley, Berkeley, CA 94704, United States.
| | - Hiromasa Takemura
- Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology, Suita 565-0871, Japan; Graduate School of Frontier Biosciences, Osaka University, Suita 565-0871, Japan; Division of Sensory and Cognitive Brain Mapping, Department of System Neuroscience, National Institute for Physiological Sciences, Okazaki 444-8585, Japan; Department of Physiological Sciences, School of Life Science, SOKENDAI (The Graduate University for Advanced Studies), Hayama 240-0193, Japan.
| | - Kaoru Amano
- Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology, Suita 565-0871, Japan; Graduate School of Frontier Biosciences, Osaka University, Suita 565-0871, Japan; Graduate School of Information Science and Technology, The University of Tokyo, Tokyo 113-8656, Japan
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18
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Marchi NA, Pizzarotti B, Solelhac G, Berger M, Haba‐Rubio J, Preisig M, Vollenweider P, Marques‐Vidal P, Lutti A, Kherif F, Heinzer R, Draganski B. Abnormal brain iron accumulation in obstructive sleep apnea: A quantitative MRI study in the HypnoLaus cohort. J Sleep Res 2022; 31:e13698. [PMID: 35830960 PMCID: PMC9787990 DOI: 10.1111/jsr.13698] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 05/23/2022] [Accepted: 06/28/2022] [Indexed: 12/30/2022]
Abstract
Obstructive sleep apnea syndrome (OSA) may be a risk factor for Alzheimer's disease. One of the hallmarks of Alzheimer's disease is disturbed iron homeostasis leading to abnormal iron deposition in brain tissue. To date, there is no empirical evidence to support the hypothesis of altered brain iron homeostasis in patients with obstructive sleep apnea as well. Data were analysed from 773 participants in the HypnoLaus study (mean age 55.9 ± 10.3 years) who underwent polysomnography and brain MRI. Cross-sectional associations were tested between OSA parameters and the MRI effective transverse relaxation rate (R2*) - indicative of iron content - in 68 grey matter regions, after adjustment for confounders. The group with severe OSA (apnea-hypopnea index ≥30/h) had higher iron levels in the left superior frontal gyrus (F3,760 = 4.79, p = 0.003), left orbital gyri (F3,760 = 5.13, p = 0.002), right and left middle temporal gyrus (F3,760 = 4.41, p = 0.004 and F3,760 = 13.08, p < 0.001, respectively), left angular gyrus (F3,760 = 6.29, p = 0.001), left supramarginal gyrus (F3,760 = 4.98, p = 0.003), and right cuneus (F3,760 = 7.09, p < 0.001). The parameters of nocturnal hypoxaemia were all consistently associated with higher iron levels. Measures of sleep fragmentation had less consistent associations with iron content. This study provides the first evidence of increased brain iron levels in obstructive sleep apnea. The observed iron changes could reflect underlying neuropathological processes that appear to be driven primarily by hypoxaemic mechanisms.
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Affiliation(s)
- Nicola Andrea Marchi
- Centre for Investigation and Research on Sleep, Department of MedicineLausanne University Hospital (CHUV) and University of LausanneLausanneSwitzerland
- Laboratory for Research in Neuroimaging, Department of Clinical NeurosciencesLausanne University Hospital (CHUV) and University of LausanneLausanneSwitzerland
| | - Beatrice Pizzarotti
- Laboratory for Research in Neuroimaging, Department of Clinical NeurosciencesLausanne University Hospital (CHUV) and University of LausanneLausanneSwitzerland
| | - Geoffroy Solelhac
- Centre for Investigation and Research on Sleep, Department of MedicineLausanne University Hospital (CHUV) and University of LausanneLausanneSwitzerland
| | - Mathieu Berger
- Centre for Investigation and Research on Sleep, Department of MedicineLausanne University Hospital (CHUV) and University of LausanneLausanneSwitzerland
| | - José Haba‐Rubio
- Centre for Investigation and Research on Sleep, Department of MedicineLausanne University Hospital (CHUV) and University of LausanneLausanneSwitzerland
| | - Martin Preisig
- Centre for Research in Psychiatric Epidemiology and Psychopathology, Department of PsychiatryLausanne University Hospital (CHUV) and University of LausanneLausanneSwitzerland
| | - Peter Vollenweider
- Service of Internal Medicine, Department of MedicineLausanne University Hospital (CHUV) and University of LausanneLausanneSwitzerland
| | - Pedro Marques‐Vidal
- Service of Internal Medicine, Department of MedicineLausanne University Hospital (CHUV) and University of LausanneLausanneSwitzerland
| | - Antoine Lutti
- Laboratory for Research in Neuroimaging, Department of Clinical NeurosciencesLausanne University Hospital (CHUV) and University of LausanneLausanneSwitzerland
| | - Ferath Kherif
- Laboratory for Research in Neuroimaging, Department of Clinical NeurosciencesLausanne University Hospital (CHUV) and University of LausanneLausanneSwitzerland
| | - Raphael Heinzer
- Centre for Investigation and Research on Sleep, Department of MedicineLausanne University Hospital (CHUV) and University of LausanneLausanneSwitzerland
| | - Bogdan Draganski
- Laboratory for Research in Neuroimaging, Department of Clinical NeurosciencesLausanne University Hospital (CHUV) and University of LausanneLausanneSwitzerland
- Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
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19
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Zhang Y, Zhang Y, Ai H, Van Dam NT, Qian L, Hou G, Xu P. Microstructural deficits of the thalamus in major depressive disorder. Brain Commun 2022; 4:fcac236. [PMID: 36196087 PMCID: PMC9525011 DOI: 10.1093/braincomms/fcac236] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 07/14/2022] [Accepted: 09/16/2022] [Indexed: 11/16/2022] Open
Abstract
Macroscopic structural abnormalities in the thalamus and thalamic circuits have been implicated in the neuropathology of major depressive disorder. However, cytoarchitectonic properties underlying these macroscopic abnormalities remain unknown. Here, we examined systematic deficits of brain architecture in depression, from structural brain network organization to microstructural properties. A multi-modal neuroimaging approach including diffusion, anatomical and quantitative MRI was used to examine structural-related alternations in 56 patients with depression compared with 35 age- and sex-matched controls. The seed-based probabilistic tractography showed multiple alterations of structural connectivity within a set of subcortical areas and their connections to cortical regions in patients with depression. These subcortical regions included the putamen, thalamus and caudate, which are predominantly involved in the limbic-cortical-striatal-pallidal-thalamic network. Structural connectivity was disrupted within and between large-scale networks, including the subcortical network, default-mode network and salience network. Consistently, morphometric measurements, including cortical thickness and voxel-based morphometry, showed widespread volume reductions of these key regions in patients with depression. A conjunction analysis identified common structural alternations of the left orbitofrontal cortex, left putamen, bilateral thalamus and right amygdala across macro-modalities. Importantly, the microstructural properties, longitudinal relaxation time of the left thalamus was increased and inversely correlated with its grey matter volume in patients with depression. Together, this work to date provides the first macro-micro neuroimaging evidence for the structural abnormalities of the thalamus in patients with depression, shedding light on the neuropathological disruptions of the limbic-cortical-striatal-pallidal-thalamic circuit in major depressive disorder. These findings have implications in understanding the abnormal changes of brain structures across the development of depression.
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Affiliation(s)
- Yuxuan Zhang
- Beijing Key Laboratory of Applied Experimental Psychology, National Demonstration Center for Experimental Psychology Education (BNU), Faculty of Psychology, Beijing Normal University, Beijing 100875, China
| | - Yingli Zhang
- Department of Depressive Disorders, Shenzhen Kangning Hospital, Shenzhen Mental Health Center, Shenzhen 518020, China
| | - Hui Ai
- Shenzhen Key Laboratory of Affective and Social Neuroscience, Magnetic Resonance Imaging Center, Center for Brain Disorders and Cognitive Sciences, Shenzhen University, Shenzhen 518052, China
| | - Nicholas T Van Dam
- Melbourne School of Psychological Sciences, The University of Melbourne, Melbourne 3010, Australia
| | - Long Qian
- MR Research, GE Healthcare, Beijing 100176, China
| | - Gangqiang Hou
- Department of Radiology, Shenzhen Kangning Hospital, Shenzhen Mental Health Center, Shenzhen 518020, China
| | - Pengfei Xu
- Beijing Key Laboratory of Applied Experimental Psychology, National Demonstration Center for Experimental Psychology Education (BNU), Faculty of Psychology, Beijing Normal University, Beijing 100875, China
- Center for Neuroimaging, Shenzhen Institute of Neuroscience, Shenzhen 518107, China
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20
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Foit NA, Yung S, Lee HM, Bernasconi A, Bernasconi N, Hong SJ. A whole-brain 3D myeloarchitectonic atlas: Mapping the Vogt-Vogt legacy to the cortical surface. Neuroimage 2022; 263:119617. [PMID: 36084859 DOI: 10.1016/j.neuroimage.2022.119617] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Revised: 09/03/2022] [Accepted: 09/05/2022] [Indexed: 11/18/2022] Open
Abstract
Building precise and detailed parcellations of anatomically and functionally distinct brain areas has been a major focus in Neuroscience. Pioneer anatomists parcellated the cortical manifold based on extensive histological studies of post-mortem brain, harnessing local variations in cortical cyto- and myeloarchitecture to define areal boundaries. Compared to the cytoarchitectonic field, where multiple neuroimaging studies have recently translated this old legacy data into useful analytical resources, myeloarchitectonics, which parcellate the cortex based on the organization of myelinated fibers, has received less attention. Here, we present the neocortical surface-based myeloarchitectonic atlas based on the histology-derived maps of the Vogt-Vogt school and its 2D translation by Nieuwenhuys. In addition to a myeloarchitectonic parcellation, our package includes intracortical laminar profiles of myelin content based on Vogt-Vogt-Hopf original publications. Histology-derived myelin density mapped on our atlas demonstrated a close overlap with in vivo quantitative MRI markers for myelin and relates to cytoarchitectural features. Complementing the existing battery of approaches for digital cartography, the whole-brain myeloarchitectonic atlas offers an opportunity to validate imaging surrogate markers of myelin in both health and disease.
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Affiliation(s)
- Niels A Foit
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, QC, Canada; Department of Neurosurgery, Medical Center - University of Freiburg, Freiburg, Germany
| | - Seles Yung
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, QC, Canada
| | - Hyo Min Lee
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, QC, Canada
| | - Andrea Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, QC, Canada
| | - Neda Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, QC, Canada
| | - Seok-Jun Hong
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, QC, Canada; Center for the Developing Brain, Child Mind Institute, NY, USA; Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, South Korea; Department of Biomedical Engineering, Sungkyunkwan University, Suwon, South Korea.
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21
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Park MTM, Jeon P, French L, Dempster K, Chakravarty MM, MacKinley M, Richard J, Khan AR, Théberge J, Palaniyappan L. Microstructural imaging and transcriptomics of the basal forebrain in first-episode psychosis. Transl Psychiatry 2022; 12:358. [PMID: 36050318 PMCID: PMC9436926 DOI: 10.1038/s41398-022-02136-0] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 08/16/2022] [Accepted: 08/23/2022] [Indexed: 11/26/2022] Open
Abstract
Cholinergic dysfunction has been implicated in the pathophysiology of psychosis and psychiatric disorders such as schizophrenia, depression, and bipolar disorder. The basal forebrain (BF) cholinergic nuclei, defined as cholinergic cell groups Ch1-3 and Ch4 (Nucleus Basalis of Meynert; NBM), provide extensive cholinergic projections to the rest of the brain. Here, we examined microstructural neuroimaging measures of the cholinergic nuclei in patients with untreated psychosis (~31 weeks of psychosis, <2 defined daily dose of antipsychotics) and used magnetic resonance spectroscopy (MRS) and transcriptomic data to support our findings. We used a cytoarchitectonic atlas of the BF to map the nuclei and obtained measures of myelin (quantitative T1, or qT1 as myelin surrogate) and microstructure (axial diffusion; AxD). In a clinical sample (n = 85; 29 healthy controls, 56 first-episode psychosis), we found significant correlations between qT1 of Ch1-3, left NBM and MRS-based dorsal anterior cingulate choline in healthy controls while this relationship was disrupted in FEP (p > 0.05). Case-control differences in qT1 and AxD were observed in the Ch1-3, with increased qT1 (reflecting reduced myelin content) and AxD (reflecting reduced axonal integrity). We found clinical correlates between left NBM qT1 with manic symptom severity, and AxD with negative symptom burden in FEP. Intracortical and subcortical myelin maps were derived and correlated with BF myelin. BF-cortical and BF-subcortical myelin correlations demonstrate known projection patterns from the BF. Using data from the Allen Human Brain Atlas, cholinergic nuclei showed significant enrichment for schizophrenia and depression-related genes. Cell-type specific enrichment indicated enrichment for cholinergic neuron markers as expected. Further relating the neuroimaging correlations to transcriptomics demonstrated links with cholinergic receptor genes and cell type markers of oligodendrocytes and cholinergic neurons, providing biological validity to the measures. These results provide genetic, neuroimaging, and clinical evidence for cholinergic dysfunction in schizophrenia.
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Affiliation(s)
- Min Tae M. Park
- grid.39381.300000 0004 1936 8884Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, Canada
| | - Peter Jeon
- grid.39381.300000 0004 1936 8884Department of Medical Biophysics, Western University, London, Canada ,grid.39381.300000 0004 1936 8884Robarts Research Institute, Western University, London, Canada ,grid.415847.b0000 0001 0556 2414Lawson Health Research Institute, London, Canada
| | - Leon French
- grid.17063.330000 0001 2157 2938Department of Psychiatry, University of Toronto, Toronto, Canada
| | - Kara Dempster
- grid.55602.340000 0004 1936 8200Department of Psychiatry, Dalhousie University, Halifax, Canada
| | - M. Mallar Chakravarty
- grid.14709.3b0000 0004 1936 8649Departments of Psychiatry and Biological and Biomedical Engineering, McGill University, Montreal, Canada ,Cerebral Imaging Centre, Douglas Research Centre, Montreal, Canada
| | - Michael MacKinley
- grid.39381.300000 0004 1936 8884Robarts Research Institute, Western University, London, Canada
| | - Julie Richard
- grid.39381.300000 0004 1936 8884Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, Canada
| | - Ali R. Khan
- grid.39381.300000 0004 1936 8884Department of Medical Biophysics, Western University, London, Canada ,grid.39381.300000 0004 1936 8884Robarts Research Institute, Western University, London, Canada
| | - Jean Théberge
- grid.39381.300000 0004 1936 8884Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, Canada ,grid.39381.300000 0004 1936 8884Department of Medical Biophysics, Western University, London, Canada ,grid.415847.b0000 0001 0556 2414Lawson Health Research Institute, London, Canada
| | - Lena Palaniyappan
- Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, Canada. .,Department of Medical Biophysics, Western University, London, Canada. .,Robarts Research Institute, Western University, London, Canada. .,Lawson Health Research Institute, London, Canada. .,Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Canada.
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22
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Karakuzu A, Appelhoff S, Auer T, Boudreau M, Feingold F, Khan AR, Lazari A, Markiewicz C, Mulder M, Phillips C, Salo T, Stikov N, Whitaker K, de Hollander G. qMRI-BIDS: An extension to the brain imaging data structure for quantitative magnetic resonance imaging data. Sci Data 2022; 9:517. [PMID: 36002444 PMCID: PMC9402561 DOI: 10.1038/s41597-022-01571-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Accepted: 07/19/2022] [Indexed: 11/16/2022] Open
Abstract
The Brain Imaging Data Structure (BIDS) established community consensus on the organization of data and metadata for several neuroimaging modalities. Traditionally, BIDS had a strong focus on functional magnetic resonance imaging (MRI) datasets and lacked guidance on how to store multimodal structural MRI datasets. Here, we present and describe the BIDS Extension Proposal 001 (BEP001), which adds a range of quantitative MRI (qMRI) applications to the BIDS. In general, the aim of qMRI is to characterize brain microstructure by quantifying the physical MR parameters of the tissue via computational, biophysical models. By proposing this new standard, we envision standardization of qMRI through multicenter dissemination of interoperable datasets. This way, BIDS can act as a catalyst of convergence between qMRI methods development and application-driven neuroimaging studies that can help develop quantitative biomarkers for neural tissue characterization. In conclusion, this BIDS extension offers a common ground for developers to exchange novel imaging data and tools, reducing the entrance barrier for qMRI in the field of neuroimaging.
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Affiliation(s)
- Agah Karakuzu
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montréal, QC, Canada.
- Montreal Heart Institute, Montreal, QC, Canada.
| | - Stefan Appelhoff
- Center for Adaptive Rationality, Max Planck Institute for Human Development, Berlin, Germany
| | - Tibor Auer
- NeuroModulation Lab, School of Psychology, University of Surrey, Guildford, UK
| | - Mathieu Boudreau
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montréal, QC, Canada
- Montreal Heart Institute, Montreal, QC, Canada
| | | | - Ali R Khan
- Department of Medical Biophysics, Robarts Research Institute, University of Western Ontario, London, Canada
| | - Alberto Lazari
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | | | - Martijn Mulder
- Department of Experimental Psychology, Utrecht University, Utrecht, the Netherlands
| | - Christophe Phillips
- GIGA Cyclotron Research Centre in vivo imaging, GIGA Institute, University of Liège, Liège, Belgium
| | - Taylor Salo
- Florida International University, Miami, FL, USA
| | - Nikola Stikov
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montréal, QC, Canada
- Montreal Heart Institute, Montreal, QC, Canada
- Center for Advanced Interdisciplinary Research, Ss. Cyril and Methodius University, Skopje, North Macedonia
| | | | - Gilles de Hollander
- Zurich Center for Neuroeconomics (ZNE), Department of Economics, University of Zurich, Zurich, Switzerland.
- Spinoza Centre for Neuroimaging, Amsterdam, The Netherlands.
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23
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Error quantification in multi-parameter mapping facilitates robust estimation and enhanced group level sensitivity. Neuroimage 2022; 262:119529. [PMID: 35926761 DOI: 10.1016/j.neuroimage.2022.119529] [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: 12/29/2021] [Revised: 07/20/2022] [Accepted: 08/01/2022] [Indexed: 11/20/2022] Open
Abstract
Multi-Parameter Mapping (MPM) is a comprehensive quantitative neuroimaging protocol that enables estimation of four physical parameters (longitudinal and effective transverse relaxation rates R1 and R2*, proton density PD, and magnetization transfer saturation MTsat) that are sensitive to microstructural tissue properties such as iron and myelin content. Their capability to reveal microstructural brain differences, however, is tightly bound to controlling random noise and artefacts (e.g. caused by head motion) in the signal. Here, we introduced a method to estimate the local error of PD, R1, and MTsat maps that captures both noise and artefacts on a routine basis without requiring additional data. To investigate the method's sensitivity to random noise, we calculated the model-based signal-to-noise ratio (mSNR) and showed in measurements and simulations that it correlated linearly with an experimental raw-image-based SNR map. We found that the mSNR varied with MPM protocols, magnetic field strength (3T vs. 7T) and MPM parameters: it halved from PD to R1 and decreased from PD to MTsat by a factor of 3-4. Exploring the artefact-sensitivity of the error maps, we generated robust MPM parameters using two successive acquisitions of each contrast and the acquisition-specific errors to down-weight erroneous regions. The resulting robust MPM parameters showed reduced variability at the group level as compared to their single-repeat or averaged counterparts. The error and mSNR maps may better inform power-calculations by accounting for local data quality variations across measurements. Code to compute the mSNR maps and robustly combined MPM maps is available in the open-source hMRI toolbox.
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24
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Drori E, Berman S, Mezer AA. Mapping microstructural gradients of the human striatum in normal aging and Parkinson's disease. SCIENCE ADVANCES 2022; 8:eabm1971. [PMID: 35857492 PMCID: PMC9286505 DOI: 10.1126/sciadv.abm1971] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Mapping structural spatial change (i.e., gradients) in the striatum is essential for understanding the function of the basal ganglia in both health and disease. We developed a method to identify and quantify gradients of microstructure in the single human brain in vivo. We found spatial gradients in the putamen and caudate nucleus of the striatum that were robust across individuals, clinical conditions, and datasets. By exploiting multiparametric quantitative MRI, we found distinct, spatially dependent, aging-related alterations in water content and iron concentration. Furthermore, we found cortico-striatal microstructural covariation, showing relations between striatal structural gradients and cortical hierarchy. In Parkinson's disease (PD) patients, we found abnormal gradients in the putamen, revealing changes in the posterior putamen that explain patients' dopaminergic loss and motor dysfunction. Our work provides a noninvasive approach for studying the spatially varying, structure-function relationship in the striatum in vivo, in normal aging and PD.
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Affiliation(s)
- Elior Drori
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Shai Berman
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Aviv A Mezer
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
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25
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Aye N, Lehmann N, Kaufmann J, Heinze HJ, Düzel E, Taubert M, Ziegler G. Test-retest reliability of multi-parametric maps (MPM) of brain microstructure. Neuroimage 2022; 256:119249. [PMID: 35487455 DOI: 10.1016/j.neuroimage.2022.119249] [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: 09/08/2021] [Revised: 04/22/2022] [Accepted: 04/25/2022] [Indexed: 10/18/2022] Open
Abstract
Multiparameter mapping (MPM) is a quantitative MRI protocol that is promising for studying microstructural brain changes in vivo with high specificity. Reliability values are an important prior knowledge for efficient study design and facilitating replicable findings in development, aging and neuroplasticity research. To explore longitudinal reliability of MPM we acquired the protocol in 31 healthy young subjects twice over a rescan interval of 4 weeks. We assessed the within-subject coefficient of variation (WCV), the between-subject coefficient of variation (BCV), and the intraclass correlation coefficient (ICC). Using these metrics, we investigated the reliability of (semi-) quantitative magnetization transfer saturation (MTsat), proton density (PD), transversal relaxation (R2*) and longitudinal relaxation (R1). To increase relevance for explorative studies in development and training-induced plasticity, we assess reliability both on local voxel- as well as ROI-level. Finally, we disentangle contributions and interplay of within- and between-subject variability to ICC and assess the optimal degree of spatial smoothing applied to the data. We reveal evidence that voxelwise ICC reliability of MPMs is moderate to good with median values in cortex (subcortical GM): MT: 0.789 (0.447) PD: 0.553 (0.264) R1: 0.555 (0.369) R2*: 0.624 (0.477). The Gaussian smoothing kernel of 2 to 4 mm FWHM resulted in optimal reproducibility. We discuss these findings in the context of longitudinal intervention studies and the application to research designs in neuroimaging field.
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Affiliation(s)
- Norman Aye
- Faculty of Human Sciences, Institute III, Department of Sport Science, Otto von Guericke University, Zschokkestraße 32, 39104 Magdeburg, Germany.
| | - Nico Lehmann
- Faculty of Human Sciences, Institute III, Department of Sport Science, Otto von Guericke University, Zschokkestraße 32, 39104 Magdeburg, Germany; Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1a, 04103 Leipzig, Germany
| | - Jörn Kaufmann
- Department of Neurology, Otto von Guericke University, Leipziger Straße 44, 39120 Magdeburg, Germany
| | - Hans-Jochen Heinze
- Department of Neurology, Otto von Guericke University, Leipziger Straße 44, 39120 Magdeburg, Germany; German Center for Neurodegenerative Diseases (DZNE), Leipziger Straße 44, 39120 Magdeburg, Germany; Center for Behavioral and Brain Science (CBBS), Otto von Guericke University, Universitätsplatz 2, 39106 Magdeburg, Germany; Leibniz-Institute for Neurobiology (LIN), Brenneckestraße 6, 39118 Magdeburg, Germany
| | - Emrah Düzel
- German Center for Neurodegenerative Diseases (DZNE), Leipziger Straße 44, 39120 Magdeburg, Germany; Center for Behavioral and Brain Science (CBBS), Otto von Guericke University, Universitätsplatz 2, 39106 Magdeburg, Germany; Institute of Cognitive Neurology and Dementia Research, Otto von Guericke University, Leipziger Str. 44, 39120 Magdeburg, Germany; Institute of Cognitive Neuroscience, University College London, Alexandra House, 17-19 Queen Square, Bloomsbury, London, WC1N 3AZ United Kingdom
| | - Marco Taubert
- Faculty of Human Sciences, Institute III, Department of Sport Science, Otto von Guericke University, Zschokkestraße 32, 39104 Magdeburg, Germany; Center for Behavioral and Brain Science (CBBS), Otto von Guericke University, Universitätsplatz 2, 39106 Magdeburg, Germany
| | - Gabriel Ziegler
- German Center for Neurodegenerative Diseases (DZNE), Leipziger Straße 44, 39120 Magdeburg, Germany; Institute of Cognitive Neurology and Dementia Research, Otto von Guericke University, Leipziger Str. 44, 39120 Magdeburg, Germany
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26
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Oliveira R, Pelentritou A, Di Domenicantonio G, De Lucia M, Lutti A. In vivo Estimation of Axonal Morphology From Magnetic Resonance Imaging and Electroencephalography Data. Front Neurosci 2022; 16:874023. [PMID: 35527816 PMCID: PMC9070985 DOI: 10.3389/fnins.2022.874023] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Accepted: 03/24/2022] [Indexed: 11/13/2022] Open
Abstract
Purpose We present a novel approach that allows the estimation of morphological features of axonal fibers from data acquired in vivo in humans. This approach allows the assessment of white matter microscopic properties non-invasively with improved specificity. Theory The proposed approach is based on a biophysical model of Magnetic Resonance Imaging (MRI) data and of axonal conduction velocity estimates obtained with Electroencephalography (EEG). In a white matter tract of interest, these data depend on (1) the distribution of axonal radius [P(r)] and (2) the g-ratio of the individual axons that compose this tract [g(r)]. P(r) is assumed to follow a Gamma distribution with mode and scale parameters, M and θ, and g(r) is described by a power law with parameters α and β. Methods MRI and EEG data were recorded from 14 healthy volunteers. MRI data were collected with a 3T scanner. MRI-measured g-ratio maps were computed and sampled along the visual transcallosal tract. EEG data were recorded using a 128-lead system with a visual Poffenberg paradigm. The interhemispheric transfer time and axonal conduction velocity were computed from the EEG current density at the group level. Using the MRI and EEG measures and the proposed model, we estimated morphological properties of axons in the visual transcallosal tract. Results The estimated interhemispheric transfer time was 11.72 ± 2.87 ms, leading to an average conduction velocity across subjects of 13.22 ± 1.18 m/s. Out of the 4 free parameters of the proposed model, we estimated θ – the width of the right tail of the axonal radius distribution – and β – the scaling factor of the axonal g-ratio, a measure of fiber myelination. Across subjects, the parameter θ was 0.40 ± 0.07 μm and the parameter β was 0.67 ± 0.02 μm−α. Conclusion The estimates of axonal radius and myelination are consistent with histological findings, illustrating the feasibility of this approach. The proposed method allows the measurement of the distribution of axonal radius and myelination within a white matter tract, opening new avenues for the combined study of brain structure and function, and for in vivo histological studies of the human brain.
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27
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Vaculčiaková L, Podranski K, Edwards LJ, Ocal D, Veale T, Fox NC, Haak R, Ehses P, Callaghan MF, Pine KJ, Weiskopf N. Combining navigator and optical prospective motion correction for high-quality 500 μm resolution quantitative multi-parameter mapping at 7T. Magn Reson Med 2022; 88:787-801. [PMID: 35405027 DOI: 10.1002/mrm.29253] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2021] [Revised: 03/10/2022] [Accepted: 03/10/2022] [Indexed: 12/15/2022]
Abstract
PURPOSE High-resolution quantitative multi-parameter mapping shows promise for non-invasively characterizing human brain microstructure but is limited by physiological artifacts. We implemented corrections for rigid head movement and respiration-related B0-fluctuations and evaluated them in healthy volunteers and dementia patients. METHODS Camera-based optical prospective motion correction (PMC) and FID navigator correction were implemented in a gradient and RF-spoiled multi-echo 3D gradient echo sequence for mapping proton density (PD), longitudinal relaxation rate (R1) and effective transverse relaxation rate (R2*). We studied their effectiveness separately and in concert in young volunteers and then evaluated the navigator correction (NAVcor) with PMC in a group of elderly volunteers and dementia patients. We used spatial homogeneity within white matter (WM) and gray matter (GM) and scan-rescan measures as quality metrics. RESULTS NAVcor and PMC reduced artifacts and improved the homogeneity and reproducibility of parameter maps. In elderly participants, NAVcor improved scan-rescan reproducibility of parameter maps (coefficient of variation decreased by 14.7% and 11.9% within WM and GM respectively). Spurious inhomogeneities within WM were reduced more in the elderly than in the young cohort (by 9% vs. 2%). PMC increased regional GM/WM contrast and was especially important in the elderly cohort, which moved twice as much as the young cohort. We did not find a significant interaction between the two corrections. CONCLUSION Navigator correction and PMC significantly improved the quality of PD, R1, and R2* maps, particularly in less compliant elderly volunteers and dementia patients.
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Affiliation(s)
- Lenka Vaculčiaková
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Kornelius Podranski
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Luke J Edwards
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Dilek Ocal
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Thomas Veale
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK.,UK Dementia Research Institute at UCL, UCL, London, UK
| | - Nick C Fox
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK.,UK Dementia Research Institute at UCL, UCL, London, UK
| | - Rainer Haak
- Department of Cariology, Endodontology and Periodontology, University of Leipzig, Leipzig, Germany
| | - Philipp Ehses
- Department of MR Physics, German Center for Neurodegenerative Diseases, Bonn, Germany
| | - Martina F Callaghan
- The Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Kerrin J Pine
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.,The Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK.,Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany
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28
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Berg RC, Leutritz T, Weiskopf N, Preibisch C. Multi-parameter quantitative mapping of R1, R2*, PD, and MTsat is reproducible when accelerated with Compressed SENSE. Neuroimage 2022; 253:119092. [PMID: 35288281 DOI: 10.1016/j.neuroimage.2022.119092] [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: 10/12/2021] [Revised: 03/07/2022] [Accepted: 03/08/2022] [Indexed: 10/18/2022] Open
Abstract
Multi-parameter mapping (MPM) magnetic resonance imaging (MRI) provides quantitative estimates of the longitudinal and effective transverse relaxation rates R1 and R2*, proton density (PD), and magnetization transfer saturation (MTsat). Thereby, MPM enables better comparability across sites and time than conventional weighted MRI. However, for MPM, several contrasts must be acquired, resulting in prolonged measurement durations and thus preventing MPM's application in clinical routines. State-of-the-art imaging acceleration techniques such as Compressed SENSE (CS), a combination of compressed sensing and sensitivity encoding, can be used to reduce the scan time of MPM. However, the accuracy and precision of the resulting quantitative parameter maps have not been systematically evaluated. In this study, we therefore investigated the effect of CS acceleration on the fidelity and reproducibility of MPM acquisitions. In five healthy volunteers and in a phantom, we compared MPM metrics acquired without imaging acceleration, with the standard acceleration (SENSE factor 2.5), and with Compressed SENSE with acceleration factors 4 and 6 using a 32-channel head coil. We evaluated the reproducibility and repeatability of accelerated MPM using data from three scan sessions in gray and white matter volumes-of-interest (VOIs). Accelerated MPM provided precise and accurate quantitative parameter maps. For most parameters, the results of the CS-accelerated protocols correlated more strongly with the non-accelerated protocol than the standard SENSE-accelerated protocols. Furthermore, for most VOIs and contrasts, coefficients of variation were lower when calculated from data acquired with different imaging accelerations within a single scan session than from data acquired in different scan sessions. These results suggest that MPM with Compressed SENSE acceleration factors up to at least 6 yields reproducible quantitative parameter maps that are highly comparable to those acquired without imaging acceleration. Compressed SENSE can thus be used to considerably reduce the scan duration of R1, R2*, PD, and MTsat mapping, and is highly promising for clinical applications of MPM.
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Affiliation(s)
- Ronja C Berg
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Neurology, Munich, Germany.
| | - Tobias Leutritz
- Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neurophysics, Leipzig, Germany.
| | - Nikolaus Weiskopf
- Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neurophysics, Leipzig, Germany; Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany.
| | - Christine Preibisch
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Neurology, Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, TUM Neuroimaging Center, Munich, Germany.
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29
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Loued-Khenissi L, Trofimova O, Vollenweider P, Marques-Vidal P, Preisig M, Lutti A, Kliegel M, Sandi C, Kherif F, Stringhini S, Draganski B. Signatures of life course socioeconomic conditions in brain anatomy. Hum Brain Mapp 2022; 43:2582-2606. [PMID: 35195323 PMCID: PMC9057097 DOI: 10.1002/hbm.25807] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 01/19/2022] [Accepted: 01/31/2022] [Indexed: 11/11/2022] Open
Abstract
Socioeconomic status (SES) plays a significant role in health and disease. At the same time, early-life conditions affect neural function and structure, suggesting the brain may be a conduit for the biological embedding of SES. Here, we investigate the brain anatomy signatures of SES in a large-scale population cohort aged 45-85 years. We assess both gray matter morphometry and tissue properties indicative of myelin content. Higher life course SES is associated with increased volume in several brain regions, including postcentral and temporal gyri, cuneus, and cerebellum. We observe more widespread volume differences and higher myelin content in the sensorimotor network but lower myelin content in the temporal lobe associated with childhood SES. Crucially, childhood SES differences persisted in adult brains even after controlling for adult SES, highlighting the unique contribution of early-life conditions to brain anatomy, independent of later changes in SES. These findings inform on the biological underpinnings of social inequality, particularly as they pertain to early-life conditions.
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Affiliation(s)
- Leyla Loued-Khenissi
- Laboratory for Research in Neuroimaging, Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Lausanne.,Theory of Pain Laboratory, University of Geneva, Geneva
| | - Olga Trofimova
- Laboratory for Research in Neuroimaging, Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Lausanne
| | - Peter Vollenweider
- Department of medicine, Internal medicine, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Pedro Marques-Vidal
- Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Martin Preisig
- Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Antoine Lutti
- Laboratory for Research in Neuroimaging, Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Lausanne
| | - Matthias Kliegel
- Laboratoire du Vieillissement Cognitif, Université de Genève, Geneva, Switzerland
| | - Carmen Sandi
- Laboratory of Behavioral Genetics, Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne, Switzerland
| | - Ferhat Kherif
- Laboratory for Research in Neuroimaging, Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Lausanne
| | - Silvia Stringhini
- University Centre for General Medicine and Public Health (UNISANTE), Lausanne University, Lausanne, Switzerland.,Unit of Population Epidemiology, Primary Care Division, Geneva University Hospitals, Geneva, Switzerland
| | - Bogdan Draganski
- Laboratory for Research in Neuroimaging, Department of Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Lausanne.,Neurology Department, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
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30
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Ogawa S, Takemura H, Horiguchi H, Miyazaki A, Matsumoto K, Masuda Y, Yoshikawa K, Nakano T. Multi-Contrast Magnetic Resonance Imaging of Visual White Matter Pathways in Patients With Glaucoma. Invest Ophthalmol Vis Sci 2022; 63:29. [PMID: 35201263 PMCID: PMC8883150 DOI: 10.1167/iovs.63.2.29] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Accepted: 02/03/2022] [Indexed: 11/24/2022] Open
Abstract
Purpose Glaucoma is a disorder that involves visual field loss caused by retinal ganglion cell damage. Previous diffusion magnetic resonance imaging (dMRI) studies have demonstrated that retinal ganglion cell damage affects tissues in the optic tract (OT) and optic radiation (OR). However, because previous studies have used a simple diffusion tensor model to analyze dMRI data, the microstructural interpretation of white matter tissue changes remains uncertain. In this study, we used a multi-contrast MRI approach to further clarify the type of microstructural damage that occurs in patients with glaucoma. Methods We collected dMRI data from 17 patients with glaucoma and 30 controls using 3-tesla (3T) MRI. Using the dMRI data, we estimated three types of tissue property metrics: intracellular volume fraction (ICVF), orientation dispersion index (ODI), and isotropic volume fraction (IsoV). Quantitative T1 (qT1) data, which may be relatively specific to myelin, were collected from all subjects. Results In the OT, all four metrics showed significant differences between the glaucoma and control groups. In the OR, only the ICVF showed significant between-group differences. ICVF was significantly correlated with qT1 in the OR of the glaucoma group, although qT1 did not show any abnormality at the group level. Conclusions Our results suggest that, at the group level, tissue changes in OR caused by glaucoma might be explained by axonal damage, which is reflected in the intracellular diffusion signals, rather than myelin damage. The significant correlation between ICVF and qT1 suggests that myelin damage might also occur in a smaller number of severe cases.
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Affiliation(s)
- Shumpei Ogawa
- Department of Ophthalmology, The Jikei University School of Medicine, Tokyo, Japan
| | - Hiromasa Takemura
- Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology, Suita, Japan
| | - Hiroshi Horiguchi
- Department of Ophthalmology, The Jikei University School of Medicine, Tokyo, Japan
| | | | - Kenji Matsumoto
- Brain Science Institute, Tamagawa University, Machida, Japan
| | - Yoichiro Masuda
- Department of Ophthalmology, The Jikei University School of Medicine, Tokyo, Japan
| | - Keiji Yoshikawa
- Department of Ophthalmology, The Jikei University School of Medicine, Tokyo, Japan
- Yoshikawa Eye Clinic, Machida, Japan
| | - Tadashi Nakano
- Department of Ophthalmology, The Jikei University School of Medicine, Tokyo, Japan
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31
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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.
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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.
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32
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Chow-Wing-Bom HT, Callaghan MF, Wang J, Wei S, Dick F, Yu-Wai-Man P, Dekker TM. Neuroimaging in Leber Hereditary Optic Neuropathy: State-of-the-art and future prospects. Neuroimage Clin 2022; 36:103240. [PMID: 36510411 PMCID: PMC9668671 DOI: 10.1016/j.nicl.2022.103240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Revised: 06/14/2022] [Accepted: 10/17/2022] [Indexed: 11/05/2022]
Abstract
Leber Hereditary Optic Neuropathy (LHON) is an inherited mitochondrial retinal disease that causes the degeneration of retinal ganglion cells and leads to drastic loss of visual function. In the last decades, there has been a growing interest in using Magnetic Resonance Imaging (MRI) to better understand mechanisms of LHON beyond the retina. This is partially due to the emergence of gene-therapies for retinal diseases, and the accompanying expanded need for reliably quantifying and monitoring visual processing and treatment efficiency in patient populations. This paper aims to draw a current picture of key findings in this field so far, the challenges of using neuroimaging methods in patients with LHON, and important open questions that MRI can help address about LHON disease mechanisms and prognoses, including how downstream visual brain regions are affected by the disease and treatment and why, and how scope for neural plasticity in these pathways may limit or facilitate recovery.
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Affiliation(s)
- Hugo T Chow-Wing-Bom
- Institute of Ophthalmology, University College London (UCL), London, United Kingdom; Birkbeck/UCL Centre for NeuroImaging, London, United Kingdom.
| | - Martina F Callaghan
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Junqing Wang
- Department of Ophthalmology, The Chinese People's Liberation Army General Hospital, The Chinese People's Liberation Army Medical School, Beijing, China
| | - Shihui Wei
- Department of Ophthalmology, The Chinese People's Liberation Army General Hospital, The Chinese People's Liberation Army Medical School, Beijing, China
| | - Frederic Dick
- Birkbeck/UCL Centre for NeuroImaging, London, United Kingdom; Department of Psychological Sciences, Birkbeck, University of London, United Kingdom; Department of Experimental Psychology, UCL, London, United Kingdom
| | - Patrick Yu-Wai-Man
- Institute of Ophthalmology, University College London (UCL), London, United Kingdom; John van Geest Centre for Brain Repair and MRC Mitochondrial Biology Unit, Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom; Cambridge Eye Unit, Addenbrooke's Hospital, Cambridge University Hospitals, Cambridge, United Kingdom; Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom
| | - Tessa M Dekker
- Institute of Ophthalmology, University College London (UCL), London, United Kingdom; Birkbeck/UCL Centre for NeuroImaging, London, United Kingdom; Department of Experimental Psychology, UCL, London, United Kingdom
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33
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Kobeleva X, López-González A, Kringelbach ML, Deco G. Revealing the Relevant Spatiotemporal Scale Underlying Whole-Brain Dynamics. Front Neurosci 2021; 15:715861. [PMID: 34744605 PMCID: PMC8569182 DOI: 10.3389/fnins.2021.715861] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Accepted: 09/23/2021] [Indexed: 12/02/2022] Open
Abstract
The brain rapidly processes and adapts to new information by dynamically transitioning between whole-brain functional networks. In this whole-brain modeling study we investigate the relevance of spatiotemporal scale in whole-brain functional networks. This is achieved through estimating brain parcellations at different spatial scales (100-900 regions) and time series at different temporal scales (from milliseconds to seconds) generated by a whole-brain model fitted to fMRI data. We quantify the richness of the dynamic repertoire at each spatiotemporal scale by computing the entropy of transitions between whole-brain functional networks. The results show that the optimal relevant spatial scale is around 300 regions and a temporal scale of around 150 ms. Overall, this study provides much needed evidence for the relevant spatiotemporal scales and recommendations for analyses of brain dynamics.
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Affiliation(s)
- Xenia Kobeleva
- Department of Neurology, University of Bonn, Bonn, Germany
- Computational Neuroscience Group, Department of Information and Communication Technologies, Center for Brain and Cognition, Universitat Pompeu Fabra, Barcelona, Spain
- German Center for Neurodegenerative Diseases (DZNE) Bonn, Bonn, Germany
| | - Ane López-González
- Computational Neuroscience Group, Department of Information and Communication Technologies, Center for Brain and Cognition, Universitat Pompeu Fabra, Barcelona, Spain
| | - Morten L. Kringelbach
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
- Centre for Eudaimonia and Human Flourishing, University of Oxford, Oxford, United Kingdom
- Department of Clinical Medicine, Center for Music in the Brain, Aarhus University, Aarhus, Denmark
| | - Gustavo Deco
- Computational Neuroscience Group, Department of Information and Communication Technologies, Center for Brain and Cognition, Universitat Pompeu Fabra, Barcelona, Spain
- Institució Catalana de la Recerca i Estudis Avançats (ICREA), Barcelona, Spain
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- School of Psychological Sciences, Monash University, Clayton, VIC, Australia
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34
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McColgan P, Helbling S, Vaculčiaková L, Pine K, Wagstyl K, Attar FM, Edwards L, Papoutsi M, Wei Y, Van den Heuvel MP, Tabrizi SJ, Rees G, Weiskopf N. Relating quantitative 7T MRI across cortical depths to cytoarchitectonics, gene expression and connectomics. Hum Brain Mapp 2021; 42:4996-5009. [PMID: 34272784 PMCID: PMC8449108 DOI: 10.1002/hbm.25595] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 06/26/2021] [Accepted: 07/06/2021] [Indexed: 12/24/2022] Open
Abstract
Ultra-high field MRI across the depth of the cortex has the potential to provide anatomically precise biomarkers and mechanistic insights into neurodegenerative disease like Huntington's disease that show layer-selective vulnerability. Here we compare multi-parametric mapping (MPM) measures across cortical depths for a 7T 500 μm whole brain acquisition to (a) layer-specific cell measures from the von Economo histology atlas, (b) layer-specific gene expression, using the Allen Human Brain atlas and (c) white matter connections using high-fidelity diffusion tractography, at a 1.3 mm isotropic voxel resolution, from a 300mT/m Connectom MRI system. We show that R2*, but not R1, across cortical depths is highly correlated with layer-specific cell number and layer-specific gene expression. R1- and R2*-weighted connectivity strength of cortico-striatal and intra-hemispheric cortical white matter connections was highly correlated with grey matter R1 and R2* across cortical depths. Limitations of the layer-specific relationships demonstrated are at least in part related to the high cross-correlations of von Economo atlas cell counts and layer-specific gene expression across cortical layers. These findings demonstrate the potential and limitations of combining 7T MPMs, gene expression and white matter connections to provide an anatomically precise framework for tracking neurodegenerative disease.
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Affiliation(s)
- Peter McColgan
- Department of NeurophysicsMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
- Huntington's Disease Research Centre, Institute of NeurologyUniversity College LondonLondon
| | - Saskia Helbling
- Department of NeurophysicsMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Lenka Vaculčiaková
- Department of NeurophysicsMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Kerrin Pine
- Department of NeurophysicsMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Konrad Wagstyl
- The Wellcome Centre for Human Neuroimaging, Institute of NeurologyUniversity College LondonLondonUK
| | | | - Luke Edwards
- Department of NeurophysicsMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Marina Papoutsi
- Huntington's Disease Research Centre, Institute of NeurologyUniversity College LondonLondon
| | - Yongbin Wei
- Vrije Universiteit AmsterdamComplex Traits Genetics LabAmsterdamNetherlands
| | | | - Sarah J Tabrizi
- Huntington's Disease Research Centre, Institute of NeurologyUniversity College LondonLondon
| | - Geraint Rees
- The Wellcome Centre for Human Neuroimaging, Institute of NeurologyUniversity College LondonLondonUK
| | - Nikolaus Weiskopf
- Department of NeurophysicsMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
- Felix Bloch Institute for Solid State PhysicsFaculty of Physics and Earth Sciences, Leipzig UniversityLeipzigGermany
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35
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Lavrova E, Lommers E, Woodruff HC, Chatterjee A, Maquet P, Salmon E, Lambin P, Phillips C. Exploratory Radiomic Analysis of Conventional vs. Quantitative Brain MRI: Toward Automatic Diagnosis of Early Multiple Sclerosis. Front Neurosci 2021; 15:679941. [PMID: 34421515 PMCID: PMC8374240 DOI: 10.3389/fnins.2021.679941] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Accepted: 06/14/2021] [Indexed: 12/23/2022] Open
Abstract
Conventional magnetic resonance imaging (cMRI) is poorly sensitive to pathological changes related to multiple sclerosis (MS) in normal-appearing white matter (NAWM) and gray matter (GM), with the added difficulty of not being very reproducible. Quantitative MRI (qMRI), on the other hand, attempts to represent the physical properties of tissues, making it an ideal candidate for quantitative medical image analysis or radiomics. We therefore hypothesized that qMRI-based radiomic features have added diagnostic value in MS compared to cMRI. This study investigated the ability of cMRI (T1w) and qMRI features extracted from white matter (WM), NAWM, and GM to distinguish between MS patients (MSP) and healthy control subjects (HCS). We developed exploratory radiomic classification models on a dataset comprising 36 MSP and 36 HCS recruited in CHU Liege, Belgium, acquired with cMRI and qMRI. For each image type and region of interest, qMRI radiomic models for MS diagnosis were developed on a training subset and validated on a testing subset. Radiomic models based on cMRI were developed on the entire training dataset and externally validated on open-source datasets with 167 HCS and 10 MSP. Ranked by region of interest, the best diagnostic performance was achieved in the whole WM. Here the model based on magnetization transfer imaging (a type of qMRI) features yielded a median area under the receiver operating characteristic curve (AUC) of 1.00 in the testing sub-cohort. Ranked by image type, the best performance was achieved by the magnetization transfer models, with median AUCs of 0.79 (0.69-0.90, 90% CI) in NAWM and 0.81 (0.71-0.90) in GM. The external validation of the T1w models yielded an AUC of 0.78 (0.47-1.00) in the whole WM, demonstrating a large 95% CI and a low sensitivity of 0.30 (0.10-0.70). This exploratory study indicates that qMRI radiomics could provide efficient diagnostic information using NAWM and GM analysis in MSP. T1w radiomics could be useful for a fast and automated check of conventional MRI for WM abnormalities once acquisition and reconstruction heterogeneities have been overcome. Further prospective validation is needed, involving more data for better interpretation and generalization of the results.
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Affiliation(s)
- Elizaveta Lavrova
- The D-Lab, Department of Precision Medicine, GROW—School for Oncology, Maastricht University, Maastricht, Netherlands
- GIGA Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
| | - Emilie Lommers
- GIGA Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
- Clinical Neuroimmunology Unit, Neurology Department, CHU Liège, Liège, Belgium
| | - Henry C. Woodruff
- The D-Lab, Department of Precision Medicine, GROW—School for Oncology, Maastricht University, Maastricht, Netherlands
- Department of Radiology and Nuclear Imaging, GROW – School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht, Netherlands
| | - Avishek Chatterjee
- The D-Lab, Department of Precision Medicine, GROW—School for Oncology, Maastricht University, Maastricht, Netherlands
| | - Pierre Maquet
- GIGA Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
- Clinical Neuroimmunology Unit, Neurology Department, CHU Liège, Liège, Belgium
| | - Eric Salmon
- GIGA Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
| | - Philippe Lambin
- The D-Lab, Department of Precision Medicine, GROW—School for Oncology, Maastricht University, Maastricht, Netherlands
- Department of Radiology and Nuclear Imaging, GROW – School for Oncology and Developmental Biology, Maastricht University Medical Centre, Maastricht, Netherlands
| | - Christophe Phillips
- GIGA Cyclotron Research Centre In Vivo Imaging, University of Liège, Liège, Belgium
- GIGA In Silico Medicine, University of Liège, Liège, Belgium
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36
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Clark IA, Callaghan MF, Weiskopf N, Maguire EA, Mohammadi S. Reducing Susceptibility Distortion Related Image Blurring in Diffusion MRI EPI Data. Front Neurosci 2021; 15:706473. [PMID: 34421526 PMCID: PMC8376472 DOI: 10.3389/fnins.2021.706473] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Accepted: 07/09/2021] [Indexed: 11/21/2022] Open
Abstract
Diffusion magnetic resonance imaging (MRI) is an increasingly popular technique in basic and clinical neuroscience. One promising application is to combine diffusion MRI with myelin maps from complementary MRI techniques such as multi-parameter mapping (MPM) to produce g-ratio maps that represent the relative myelination of axons and predict their conduction velocity. Statistical Parametric Mapping (SPM) can process both diffusion data and MPMs, making SPM the only widely accessible software that contains all the processing steps required to perform group analyses of g-ratio data in a common space. However, limitations have been identified in its method for reducing susceptibility-related distortion in diffusion data. More generally, susceptibility-related image distortion is often corrected by combining reverse phase-encoded images (blip-up and blip-down) using the arithmetic mean (AM), however, this can lead to blurred images. In this study we sought to (1) improve the susceptibility-related distortion correction for diffusion MRI data in SPM; (2) deploy an alternative approach to the AM to reduce image blurring in diffusion MRI data when combining blip-up and blip-down EPI data after susceptibility-related distortion correction; and (3) assess the benefits of these changes for g-ratio mapping. We found that the new processing pipeline, called consecutive Hyperelastic Susceptibility Artefact Correction (HySCO) improved distortion correction when compared to the standard approach in the ACID toolbox for SPM. Moreover, using a weighted average (WA) method to combine the distortion corrected data from each phase-encoding polarity achieved greater overlap of diffusion and more anatomically faithful structural white matter probability maps derived from minimally distorted multi-parameter maps as compared to the AM. Third, we showed that the consecutive HySCO WA performed better than the AM method when combined with multi-parameter maps to perform g-ratio mapping. These improvements mean that researchers can conveniently access a wide range of diffusion-related analysis methods within one framework because they are now available within the open-source ACID toolbox as part of SPM, which can be easily combined with other SPM toolboxes, such as the hMRI toolbox, to facilitate computation of myelin biomarkers that are necessary for g-ratio mapping.
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Affiliation(s)
- Ian A. Clark
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Martina F. Callaghan
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Nikolaus Weiskopf
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
- 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
| | - Eleanor A. Maguire
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Siawoosh Mohammadi
- Institute of Systems Neuroscience, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany
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37
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Shin HG, Lee J, Yun YH, Yoo SH, Jang J, Oh SH, Nam Y, Jung S, Kim S, Fukunaga M, Kim W, Choi HJ, Lee J. χ-separation: Magnetic susceptibility source separation toward iron and myelin mapping in the brain. Neuroimage 2021; 240:118371. [PMID: 34242783 DOI: 10.1016/j.neuroimage.2021.118371] [Citation(s) in RCA: 48] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Revised: 07/04/2021] [Accepted: 07/05/2021] [Indexed: 11/26/2022] Open
Abstract
Obtaining a histological fingerprint from the in-vivo brain has been a long-standing target of magnetic resonance imaging (MRI). In particular, non-invasive imaging of iron and myelin, which are involved in normal brain functions and are histopathological hallmarks in neurodegenerative diseases, has practical utilities in neuroscience and medicine. Here, we propose a biophysical model that describes the individual contribution of paramagnetic (e.g., iron) and diamagnetic (e.g., myelin) susceptibility sources to the frequency shift and transverse relaxation of MRI signals. Using this model, we develop a method, χ-separation, that generates the voxel-wise distributions of the two sources. The method is validated using computer simulation and phantom experiments, and applied to ex-vivo and in-vivo brains. The results delineate the well-known histological features of iron and myelin in the specimen, healthy volunteers, and multiple sclerosis patients. This new technology may serve as a practical tool for exploring the microstructural information of the brain.
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Affiliation(s)
- Hyeong-Geol Shin
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea
| | - Jingu Lee
- AIRS Medical Inc., Seoul, Republic of Korea
| | - Young Hyun Yun
- Department of Medicine, Anatomy and Cell Biology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Seong Ho Yoo
- Department of Forensic Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jinhee Jang
- Department of Radiology, Seoul St Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Se-Hong Oh
- Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea
| | - Yoonho Nam
- Division of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea
| | - Sehoon Jung
- Research Institute of Industrial Science and Technology, Pohang, Republic of Korea
| | - Sunhye Kim
- Research Institute of Industrial Science and Technology, Pohang, Republic of Korea
| | - Masaki Fukunaga
- Division of Cerebral Integration, National Institute for Physiological Sciences, Okazaki, Japan
| | - Woojun Kim
- Department of Neurology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Hyung Jin Choi
- Department of Biomedical Sciences, Anatomy and Cell Biology, Neuroscience Research Institute, Wide River Institute of Immunology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Jongho Lee
- Laboratory for Imaging Science and Technology, Department of Electrical and Computer Engineering, Seoul National University, Seoul, Republic of Korea.
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38
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Hahn A, Bode J, Alexander A, Karimian-Jazi K, Schregel K, Schwarz D, Sommerkamp AC, Krüwel T, Abdollahi A, Wick W, Platten M, Bendszus M, Tews B, Kurz FT, Breckwoldt MO. Large-scale characterization of the microvascular geometry in development and disease by tissue clearing and quantitative ultramicroscopy. J Cereb Blood Flow Metab 2021; 41:1536-1546. [PMID: 33043767 PMCID: PMC8217891 DOI: 10.1177/0271678x20961854] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Revised: 08/04/2020] [Accepted: 08/30/2020] [Indexed: 12/16/2022]
Abstract
Three-dimensional assessment of optically cleared, entire organs and organisms has recently become possible by tissue clearing and selective plane illumination microscopy ("ultramicroscopy"). Resulting datasets can be highly complex, encompass over a thousand images with millions of objects and data of several gigabytes per acquisition. This constitutes a major challenge for quantitative analysis. We have developed post-processing tools to quantify millions of microvessels and their distribution in three-dimensional datasets from ultramicroscopy and demonstrate the capabilities of our pipeline within entire mouse brains and embryos. Using our developed acquisition, segmentation, and analysis platform, we quantify physiological vascular networks in development and the healthy brain. We compare various geometric vessel parameters (e.g. vessel density, radius, tortuosity) in the embryonic spinal cord and brain as well as in different brain regions (basal ganglia, corpus callosum, cortex). White matter tract structures (corpus callosum, spinal cord) showed lower microvascular branch densities and longer vessel branch length compared to grey matter (cortex, basal ganglia). Furthermore, we assess tumor neoangiogenesis in a mouse glioma model to compare tumor core and tumor border. The developed methodology allows rapid quantification of three-dimensional datasets by semi-automated segmentation of fluorescently labeled objects with conventional computer hardware. Our approach can aid preclinical investigations and paves the way towards "quantitative ultramicroscopy".
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Affiliation(s)
- Artur Hahn
- Neuroradiology Department, University Hospital Heidelberg, Heidelberg, Germany
- Department of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany
| | - Julia Bode
- Schaller Research Group at the University of Heidelberg and the German Cancer Research Center (DKFZ), Molecular Mechanisms of Tumor Invasion, Heidelberg, Germany
| | - Allen Alexander
- Neuroradiology Department, University Hospital Heidelberg, Heidelberg, Germany
- Clinical Cooperation Unit Neuroimmunology and Brain Tumor Immunology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | - Katharina Schregel
- Neuroradiology Department, University Hospital Heidelberg, Heidelberg, Germany
| | - Daniel Schwarz
- Neuroradiology Department, University Hospital Heidelberg, Heidelberg, Germany
| | - Alexander C Sommerkamp
- Schaller Research Group at the University of Heidelberg and the German Cancer Research Center (DKFZ), Molecular Mechanisms of Tumor Invasion, Heidelberg, Germany
- Faculty of Biosciences, Heidelberg University, Heidelberg, Germany
| | - Thomas Krüwel
- Schaller Research Group at the University of Heidelberg and the German Cancer Research Center (DKFZ), Molecular Mechanisms of Tumor Invasion, Heidelberg, Germany
| | - Amir Abdollahi
- German Cancer Consortium and Heidelberg Institute of Radiation Oncology, National Center for Radiation Research in Oncology, Heidelberg, Germany
- Heidelberg University School of Medicine, Heidelberg University, Heidelberg, Germany
- Translational Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Wolfgang Wick
- Neurology Clinic and National Center for Tumor Diseases, University Hospital Heidelberg, Heidelberg, Germany
- Clinical Cooperation Unit Neurooncology, German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Michael Platten
- Clinical Cooperation Unit Neuroimmunology and Brain Tumor Immunology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Neurology, University Medical Center Mannheim, Heidelberg University, Heidelberg, Germany
| | - Martin Bendszus
- Neuroradiology Department, University Hospital Heidelberg, Heidelberg, Germany
| | - Björn Tews
- Schaller Research Group at the University of Heidelberg and the German Cancer Research Center (DKFZ), Molecular Mechanisms of Tumor Invasion, Heidelberg, Germany
| | - Felix T Kurz
- Neuroradiology Department, University Hospital Heidelberg, Heidelberg, Germany
| | - Michael O Breckwoldt
- Neuroradiology Department, University Hospital Heidelberg, Heidelberg, Germany
- Clinical Cooperation Unit Neuroimmunology and Brain Tumor Immunology, German Cancer Research Center (DKFZ), Heidelberg, Germany
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39
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Kyathanahally SP, Azzarito M, Rosner J, Calhoun VD, Blaiotta C, Ashburner J, Weiskopf N, Wiech K, Friston K, Ziegler G, Freund P. Microstructural plasticity in nociceptive pathways after spinal cord injury. J Neurol Neurosurg Psychiatry 2021; 92:jnnp-2020-325580. [PMID: 34039630 PMCID: PMC8292587 DOI: 10.1136/jnnp-2020-325580] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Revised: 03/12/2021] [Accepted: 04/21/2021] [Indexed: 12/26/2022]
Abstract
OBJECTIVE To track the interplay between (micro-) structural changes along the trajectories of nociceptive pathways and its relation to the presence and intensity of neuropathic pain (NP) after spinal cord injury (SCI). METHODS A quantitative neuroimaging approach employing a multiparametric mapping protocol was used, providing indirect measures of myelination (via contrasts such as magnetisation transfer (MT) saturation, longitudinal relaxation (R1)) and iron content (via effective transverse relaxation rate (R2*)) was used to track microstructural changes within nociceptive pathways. In order to characterise concurrent changes along the entire neuroaxis, a combined brain and spinal cord template embedded in the statistical parametric mapping framework was used. Multivariate source-based morphometry was performed to identify naturally grouped patterns of structural variation between individuals with and without NP after SCI. RESULTS In individuals with NP, lower R1 and MT values are evident in the primary motor cortex and dorsolateral prefrontal cortex, while increases in R2* are evident in the cervical cord, periaqueductal grey (PAG), thalamus and anterior cingulate cortex when compared with pain-free individuals. Lower R1 values in the PAG and greater R2* values in the cervical cord are associated with NP intensity. CONCLUSIONS The degree of microstructural changes across ascending and descending nociceptive pathways is critically implicated in the maintenance of NP. Tracking maladaptive plasticity unravels the intimate relationships between neurodegenerative and compensatory processes in NP states and may facilitate patient monitoring during therapeutic trials related to pain and neuroregeneration.
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Affiliation(s)
- Sreenath P Kyathanahally
- Spinal Cord Injury Center, University Hospital Balgrist, University of Zurich, Zurich, Switzerland
| | - Michela Azzarito
- Spinal Cord Injury Center, University Hospital Balgrist, University of Zurich, Zurich, Switzerland
| | - Jan Rosner
- Spinal Cord Injury Center, University Hospital Balgrist, University of Zurich, Zurich, Switzerland
- Department of Neurology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Vince D Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia, USA
| | - Claudia Blaiotta
- Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, UCL, London, UK
| | - John Ashburner
- Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, UCL, London, UK
| | - Nikolaus Weiskopf
- Neurophysics, Max-Planck-Institut fur Kognitions- und Neurowissenschaften, Leipzig, Germany
| | - Katja Wiech
- Wellcome Centre for Integrative Neuroimaging (WIN), Nuffield Department of Clinical Neurosciences, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Karl Friston
- Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, UCL, London, UK
| | - Gabriel Ziegler
- German Center for Neurodegenerative Disease (DZNE), Magdeburg, Germany
| | - Patrick Freund
- Spinal Cord Injury Center, University Hospital Balgrist, University of Zurich, Zurich, Switzerland
- Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, UCL, London, UK
- Neurophysics, Max-Planck-Institut fur Kognitions- und Neurowissenschaften, Leipzig, Germany
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40
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Tremblay SA, Jäger AT, Huck J, Giacosa C, Beram S, Schneider U, Grahl S, Villringer A, Tardif CL, Bazin PL, Steele CJ, Gauthier CJ. White matter microstructural changes in short-term learning of a continuous visuomotor sequence. Brain Struct Funct 2021; 226:1677-1698. [PMID: 33885965 DOI: 10.1007/s00429-021-02267-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2020] [Accepted: 03/26/2021] [Indexed: 11/29/2022]
Abstract
Efficient neural transmission is crucial for optimal brain function, yet the plastic potential of white matter (WM) has long been overlooked. Growing evidence now shows that modifications to axons and myelin occur not only as a result of long-term learning, but also after short training periods. Motor sequence learning (MSL), a common paradigm used to study neuroplasticity, occurs in overlapping learning stages and different neural circuits are involved in each stage. However, most studies investigating short-term WM plasticity have used a pre-post design, in which the temporal dynamics of changes across learning stages cannot be assessed. In this study, we used multiple magnetic resonance imaging (MRI) scans at 7 T to investigate changes in WM in a group learning a complex visuomotor sequence (LRN) and in a control group (SMP) performing a simple sequence, for five consecutive days. Consistent with behavioral results, where most improvements occurred between the two first days, structural changes in WM were observed only in the early phase of learning (d1-d2), and in overall learning (d1-d5). In LRNs, WM microstructure was altered in the tracts underlying the primary motor and sensorimotor cortices. Moreover, our structural findings in WM were related to changes in functional connectivity, assessed with resting-state functional MRI data in the same cohort, through analyses in regions of interest (ROIs). Significant changes in WM microstructure were found in a ROI underlying the right supplementary motor area. Together, our findings provide evidence for highly dynamic WM plasticity in the sensorimotor network during short-term MSL.
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Affiliation(s)
- Stéfanie A Tremblay
- Department of Physics/PERFORM Center, Concordia University, Montreal, QC, Canada.,Montreal Heart Institute, Montreal, QC, Canada
| | - Anna-Thekla Jäger
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.,Charite Universitätsmedizin, Charite, Berlin, Germany
| | - Julia Huck
- Department of Physics/PERFORM Center, Concordia University, Montreal, QC, Canada
| | - Chiara Giacosa
- Department of Physics/PERFORM Center, Concordia University, Montreal, QC, Canada
| | - Stephanie Beram
- Department of Physics/PERFORM Center, Concordia University, Montreal, QC, Canada
| | - Uta Schneider
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Sophia Grahl
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Arno Villringer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.,Clinic for Cognitive Neurology, Leipzig, Germany.,Leipzig University Medical Centre, IFB Adiposity Diseases, Leipzig, Germany.,Collaborative Research Centre 1052-A5, University of Leipzig, Leipzig, Germany
| | - Christine L Tardif
- Department of Biomedical Engineering, McGill University, Montreal, QC, Canada.,Montreal Neurological Institute, Montreal, QC, Canada
| | - Pierre-Louis Bazin
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.,Faculty of Social and Behavioral Sciences, University of Amsterdam, Amsterdam, Netherlands
| | - Christopher J Steele
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.,Department of Psychology, Concordia University, Montreal, QC, Canada
| | - Claudine J Gauthier
- Department of Physics/PERFORM Center, Concordia University, Montreal, QC, Canada. .,Montreal Heart Institute, Montreal, QC, Canada.
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41
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Lazari A, Lipp I. Can MRI measure myelin? Systematic review, qualitative assessment, and meta-analysis of studies validating microstructural imaging with myelin histology. Neuroimage 2021; 230:117744. [PMID: 33524576 PMCID: PMC8063174 DOI: 10.1016/j.neuroimage.2021.117744] [Citation(s) in RCA: 84] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Revised: 01/05/2021] [Accepted: 01/09/2021] [Indexed: 12/16/2022] Open
Abstract
Recent years have seen an increased understanding of the importance of myelination in healthy brain function and neuropsychiatric diseases. Non-invasive microstructural magnetic resonance imaging (MRI) holds the potential to expand and translate these insights to basic and clinical human research, but the sensitivity and specificity of different MR markers to myelination is a subject of debate. To consolidate current knowledge on the topic, we perform a systematic review and meta-analysis of studies that validate microstructural imaging by combining it with myelin histology. We find meta-analytic evidence for correlations between various myelin histology metrics and markers from different MRI modalities, including fractional anisotropy, radial diffusivity, macromolecular pool, magnetization transfer ratio, susceptibility and longitudinal relaxation rate, but not mean diffusivity. Meta-analytic correlation effect sizes range widely, between R2 = 0.26 and R2 = 0.82. However, formal comparisons between MRI-based myelin markers are limited by methodological variability, inconsistent reporting and potential for publication bias, thus preventing the establishment of a single most sensitive strategy to measure myelin with MRI. To facilitate further progress, we provide a detailed characterisation of the evaluated studies as an online resource. We also share a set of 12 recommendations for future studies validating putative MR-based myelin markers and deploying them in vivo in humans.
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Affiliation(s)
- Alberto Lazari
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, UK
| | - Ilona Lipp
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
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42
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Ganepola T, Lee Y, Alexander DC, Sereno MI, Nagy Z. Multiple b-values improve discrimination of cortical gray matter regions using diffusion MRI: an experimental validation with a data-driven approach. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2021; 34:677-687. [PMID: 33709225 PMCID: PMC8421285 DOI: 10.1007/s10334-021-00914-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Revised: 12/14/2020] [Accepted: 02/04/2021] [Indexed: 11/28/2022]
Abstract
Objective To investigate whether varied or repeated b-values provide better diffusion MRI data for discriminating cortical areas with a data-driven approach. Methods Data were acquired from three volunteers at 1.5T with b-values of 800, 1400, 2000 s/mm2 along 64 diffusion-encoding directions. The diffusion signal was sampled from gray matter in seven regions of interest (ROIs). Rotational invariants of the local diffusion profile were extracted as features that characterize local tissue properties. Random forest classification experiments assessed whether classification accuracy improved when data with multiple b-values were used over repeated acquisition of the same (1400 s/mm2) b-value to compare all possible pairs of the seven ROIs. Three data sets from the Human Connectome Project were subjected to similar processing and analysis pipelines in eight ROIs. Results Three different b-values showed an average improvement in correct classification rates of 5.6% and 4.6%, respectively, in the local and HCP data over repeated measurements of the same b-value. The improvement in correct classification rate reached as high as 16% for individual binary classification experiments between two ROIs. Often using only two of the available three b-values were adequate to make such an improvement in classification rates. Conclusion Acquisitions with varying b-values are more suitable for discriminating cortical areas.
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Affiliation(s)
- Tara Ganepola
- Department of Cognitive, Perceptual and Brain Sciences, University College London, London, UK.,Center for Medical Image Computing, Department of Computer Science, University College London, London, UK
| | - Yoojin Lee
- Laboratory for Social and Neural Systems Research, University of Zurich, Rämistrasse 100, P.O. Box 149, Zurich, Switzerland.,Institute of Biomedical Engineering, ETH Zurich, Zurich, Switzerland
| | - Daniel C Alexander
- Center for Medical Image Computing, Department of Computer Science, University College London, London, UK
| | - Martin I Sereno
- Department of Cognitive, Perceptual and Brain Sciences, University College London, London, UK.,Department of Psychology and Neuroimaging Centre, SDSU, San Diego, USA
| | - Zoltan Nagy
- Laboratory for Social and Neural Systems Research, University of Zurich, Rämistrasse 100, P.O. Box 149, Zurich, Switzerland. .,Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, London, UK.
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43
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Seiler A, Nöth U, Hok P, Reiländer A, Maiworm M, Baudrexel S, Meuth S, Rosenow F, Steinmetz H, Wagner M, Hattingen E, Deichmann R, Gracien RM. Multiparametric Quantitative MRI in Neurological Diseases. Front Neurol 2021; 12:640239. [PMID: 33763021 PMCID: PMC7982527 DOI: 10.3389/fneur.2021.640239] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Accepted: 02/12/2021] [Indexed: 11/27/2022] Open
Abstract
Magnetic resonance imaging (MRI) is the gold standard imaging technique for diagnosis and monitoring of many neurological diseases. However, the application of conventional MRI in clinical routine is mainly limited to the visual detection of macroscopic tissue pathology since mixed tissue contrasts depending on hardware and protocol parameters hamper its application for the assessment of subtle or diffuse impairment of the structural tissue integrity. Multiparametric quantitative (q)MRI determines tissue parameters quantitatively, enabling the detection of microstructural processes related to tissue remodeling in aging and neurological diseases. In contrast to measuring tissue atrophy via structural imaging, multiparametric qMRI allows for investigating biologically distinct microstructural processes, which precede changes of the tissue volume. This facilitates a more comprehensive characterization of tissue alterations by revealing early impairment of the microstructural integrity and specific disease-related patterns. So far, qMRI techniques have been employed in a wide range of neurological diseases, including in particular conditions with inflammatory, cerebrovascular and neurodegenerative pathology. Numerous studies suggest that qMRI might add valuable information, including the detection of microstructural tissue damage in areas appearing normal on conventional MRI and unveiling the microstructural correlates of clinical manifestations. This review will give an overview of current qMRI techniques, the most relevant tissue parameters and potential applications in neurological diseases, such as early (differential) diagnosis, monitoring of disease progression, and evaluating effects of therapeutic interventions.
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Affiliation(s)
- Alexander Seiler
- Department of Neurology, Goethe University, Frankfurt, Germany.,Brain Imaging Center, Goethe University, Frankfurt, Germany
| | - Ulrike Nöth
- Brain Imaging Center, Goethe University, Frankfurt, Germany.,Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Goethe University, Frankfurt, Germany
| | - Pavel Hok
- Department of Neurology, Palacký University Olomouc and University Hospital Olomouc, Olomouc, Czechia
| | - Annemarie Reiländer
- Department of Neurology, Goethe University, Frankfurt, Germany.,Brain Imaging Center, Goethe University, Frankfurt, Germany
| | - Michelle Maiworm
- Department of Neurology, Goethe University, Frankfurt, Germany.,Brain Imaging Center, Goethe University, Frankfurt, Germany.,Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Goethe University, Frankfurt, Germany
| | - Simon Baudrexel
- Department of Neurology, Goethe University, Frankfurt, Germany.,Brain Imaging Center, Goethe University, Frankfurt, Germany
| | - Sven Meuth
- Department of Neurology, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Felix Rosenow
- Department of Neurology, Goethe University, Frankfurt, Germany.,Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Goethe University, Frankfurt, Germany.,Epilepsy Center Frankfurt Rhine-Main, Center of Neurology and Neurosurgery, University Hospital, Frankfurt, Germany
| | - Helmuth Steinmetz
- Department of Neurology, Goethe University, Frankfurt, Germany.,Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Goethe University, Frankfurt, Germany
| | - Marlies Wagner
- Brain Imaging Center, Goethe University, Frankfurt, Germany.,Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Goethe University, Frankfurt, Germany
| | - Elke Hattingen
- Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Goethe University, Frankfurt, Germany.,Department of Neuroradiology, Goethe University, Frankfurt, Germany
| | - Ralf Deichmann
- Brain Imaging Center, Goethe University, Frankfurt, Germany.,Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Goethe University, Frankfurt, Germany
| | - René-Maxime Gracien
- Department of Neurology, Goethe University, Frankfurt, Germany.,Brain Imaging Center, Goethe University, Frankfurt, Germany.,Center for Personalized Translational Epilepsy Research (CePTER) Consortium, Goethe University, Frankfurt, Germany
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44
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Corbin N, Callaghan MF. Imperfect spoiling in variable flip angle T 1 mapping at 7T: Quantifying and minimizing impact. Magn Reson Med 2021; 86:693-708. [PMID: 33645814 PMCID: PMC8436769 DOI: 10.1002/mrm.28720] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2020] [Revised: 01/15/2021] [Accepted: 01/17/2021] [Indexed: 02/06/2023]
Abstract
Purpose The variable flip angle (VFA) approach to T1 mapping assumes perfectly spoiled transverse magnetisation at the end of each repetition time (TR). Despite radiofrequency (RF) and gradient spoiling, this condition is rarely met, leading to erroneous T1 estimates (T1app). Theoretical corrections can be applied but make assumptions about tissue properties, for example, a global T2 time. Here, we investigate the effect of imperfect spoiling at 7T and the interaction between the RF and gradient spoiling conditions, additionally accounting for diffusion. We provide guidance on the optimal approach to maximise the accuracy of the T1 estimate in the context of 3D multi‐echo acquisitions. Methods The impact of the spoiling regime was investigated through numerical simulations, phantom and invivo experiments. Results The predicted dependence of T1app on tissue properties, system settings, and spoiling conditions was observed in both phantom and in vivo experiments. Diffusion effects modulated the dependence of T1app on both B1+ efficiency and T2 times. Conclusion Error in T1app can be minimized by using an RF spoiling increment and gradient spoiler moment combination that minimizes T2‐dependence and safeguards image quality. Although the diffusion effect was comparatively small at 7T, correction factors accounting for this effect are recommended. Click here for author‐reader discussions
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Affiliation(s)
- Nadège Corbin
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Martina F Callaghan
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
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Voelker MN, Kraff O, Goerke S, Laun FB, Hanspach J, Pine KJ, Ehses P, Zaiss M, Liebert A, Straub S, Eckstein K, Robinson S, Nagel AN, Stefanescu MR, Wollrab A, Klix S, Felder J, Hock M, Bosch D, Weiskopf N, Speck O, Ladd ME, Quick HH. The traveling heads 2.0: Multicenter reproducibility of quantitative imaging methods at 7 Tesla. Neuroimage 2021; 232:117910. [PMID: 33647497 DOI: 10.1016/j.neuroimage.2021.117910] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Revised: 01/25/2021] [Accepted: 02/20/2021] [Indexed: 12/14/2022] Open
Abstract
OBJECT This study evaluates inter-site and intra-site reproducibility at ten different 7 T sites for quantitative brain imaging. MATERIAL AND METHODS Two subjects - termed the "traveling heads" - were imaged at ten different 7 T sites with a harmonized quantitative brain MR imaging protocol. In conjunction with the system calibration, MP2RAGE, QSM, CEST and multi-parametric mapping/relaxometry were examined. RESULTS Quantitative measurements with MP2RAGE showed very high reproducibility across sites and subjects, and errors were in concordance with previous results and other field strengths. QSM had high inter-site reproducibility for relevant subcortical volumes. CEST imaging revealed systematic differences between the sites, but reproducibility was comparable to results in the literature. Relaxometry had also very high agreement between sites, but due to the high sensitivity, differences caused by different applications of the B1 calibration of the two RF coil types used were observed. CONCLUSION Our results show that quantitative brain imaging can be performed with high reproducibility at 7 T and with similar reliability as found at 3 T for multicenter studies of the supratentorial brain.
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Affiliation(s)
- Maximilian N Voelker
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, University Duisburg-Essen, Essen, Germany; High-Field and Hybrid MR Imaging, University Hospital Essen, University Duisburg-Essen, Essen, Germany.
| | - Oliver Kraff
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, University Duisburg-Essen, Essen, Germany
| | - Steffen Goerke
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Frederik B Laun
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Jannis Hanspach
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Kerrin J Pine
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Philipp Ehses
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Moritz Zaiss
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany; Max Planck Institute for Biological Cybernetics, Tübingen, Germany
| | - Andrzej Liebert
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Sina Straub
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Korbinian Eckstein
- High Field MR Center, Department for Biomedical Imaging and Image guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Simon Robinson
- High Field MR Center, Department for Biomedical Imaging and Image guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Armin N Nagel
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Maria R Stefanescu
- Chair of Cellular and Molecular Imaging, Comprehensive Heart Failure Center (CHFC), University Hospital Wuerzburg, Wuerzburg, Germany
| | - Astrid Wollrab
- Otto-von-Guericke-University Magdeburg, Magdeburg, Germany
| | - Sabrina Klix
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrueck-Center for Molecular Medicine, Berlin-Buch, Germany
| | - Jörg Felder
- Institute of Neuroscience and Medicine (INM-4), Forschungszentrum Jülich, Jülich, Germany
| | - Michael Hock
- Chair of Cellular and Molecular Imaging, Comprehensive Heart Failure Center (CHFC), University Hospital Wuerzburg, Wuerzburg, Germany
| | - Dario Bosch
- Max Planck Institute for Biological Cybernetics, Tübingen, Germany
| | - 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
| | - Oliver Speck
- Otto-von-Guericke-University Magdeburg, Magdeburg, Germany; Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Mark E Ladd
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, University Duisburg-Essen, Essen, Germany; Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany; Faculty of Medicine and Faculty of Physics and Astronomy, Heidelberg University, Heidelberg, Germany
| | - Harald H Quick
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, University Duisburg-Essen, Essen, Germany; High-Field and Hybrid MR Imaging, University Hospital Essen, University Duisburg-Essen, Essen, Germany
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Variable flip angle echo planar time-resolved imaging (vFA-EPTI) for fast high-resolution gradient echo myelin water imaging. Neuroimage 2021; 232:117897. [PMID: 33621694 PMCID: PMC8221177 DOI: 10.1016/j.neuroimage.2021.117897] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 02/01/2021] [Accepted: 02/16/2021] [Indexed: 12/14/2022] Open
Abstract
Myelin water imaging techniques based on multi-compartment relaxometry have been developed as an important tool to measure myelin concentration in vivo, but are limited by the long scan time of multi-contrast multi-echo acquisition. In this work, a fast imaging technique, termed variable flip angle Echo Planar Time-Resolved Imaging (vFA-EPTI), is developed to acquire multi-echo and multi-flip-angle gradient-echo data with significantly reduced acquisition time, providing rich information for multi-compartment analysis of gradient-echo myelin water imaging (GRE-MWI). The proposed vFA-EPTI method achieved 26 folds acceleration with good accuracy by utilizing an efficient continuous readout, optimized spatiotemporal encoding across echoes and flip angles, as well as a joint subspace reconstruction. An approach to estimate off-resonance field changes between different flip-angle acquisitions was also developed to ensure high-quality joint reconstruction across flip angles. The accuracy of myelin water fraction (MWF) estimate under high acceleration was first validated by a retrospective undersampling experiment using a lengthy fully-sampled data as reference. Prospective experiments were then performed where whole-brain MWF and multi-compartment quantitative maps were obtained in 5 min at 1.5 mm isotropic resolution and 24 min at 1 mm isotropic resolution at 3T. Additionally, ultra-high resolution data at 600 μm isotropic resolution were acquired at 7T, which show detailed structures within the cortex such as the line of Gennari, demonstrating the ability of the proposed method for submillimeter GRE-MWI that can be used to study cortical myeloarchitecture in vivo.
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Temporal trajectory of brain tissue property changes induced by electroconvulsive therapy. Neuroimage 2021; 232:117895. [PMID: 33617994 DOI: 10.1016/j.neuroimage.2021.117895] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 12/31/2020] [Accepted: 02/16/2021] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND After more than eight decades of electroconvulsive therapy (ECT) for pharmaco-resistant depression, the mechanisms governing its anti-depressant effects remain poorly understood. Computational anatomy studies using longitudinal T1-weighted magnetic resonance imaging (MRI) data have demonstrated ECT effects on hippocampus volume and cortical thickness, but they lack the interpretational specificity about underlying neurobiological processes. METHODS We sought to fill in the gap of knowledge by acquiring quantitative MRI indicative for brain's myelin, iron and tissue water content at multiple time-points before, during and after ECT treatment. We adapted established tools for longitudinal spatial registration of MRI data to the relaxometry-based multi-parameter maps aiming to preserve the initial total signal amount and introduced a dedicated multivariate analytical framework. RESULTS The whole-brain voxel-based analysis based on a multivariate general linear model showed that there is no brain tissue oedema contributing to the predicted ECT-induced hippocampus volume increase neither in the short, nor in the long-term observations. Improvements in depression symptom severity over time were associated with changes in both volume estimates and brain tissue properties expanding beyond mesial temporal lobe structures to anterior cingulate cortex, precuneus and striatum. CONCLUSION The obtained results stemming from multi-contrast MRI quantitative data provided a fingerprint of ECT-induced brain tissue changes over time that are contrasted against the background of established morphometry findings. The introduced data processing and statistical testing algorithms provided a reliable analytical framework for longitudinal multi-parameter brain maps. The results, particularly the evidence of lack of ECT impact on brain tissue water, should be considered preliminary considering the small sample size of the study.
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Brain tissue properties link cardio-vascular risk factors, mood and cognitive performance in the CoLaus|PsyCoLaus epidemiological cohort. Neurobiol Aging 2021; 102:50-63. [PMID: 33765431 DOI: 10.1016/j.neurobiolaging.2021.02.002] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Revised: 01/31/2021] [Accepted: 02/04/2021] [Indexed: 01/15/2023]
Abstract
Given the controversy about the impact of modifiable risk factors on mood and cognition in ageing, we sought to investigate the associations between cardio-vascular risk, mental health, cognitive performance and brain anatomy in mid- to old age. We analyzed a set of risk factors together with multi-parameter magnetic resonance imaging (MRI) in the CoLaus|PsyCoLaus cohort (n > 1200). Cardio-vascular risk was associated with differences in brain tissue properties - myelin, free tissue water, iron content - and regional brain volumes that we interpret in the context of micro-vascular hypoxic lesions and neurodegeneration. The interaction between clinical subtypes of major depressive disorder and cardio-vascular risk factors showed differential associations with brain structure depending on individuals' lifetime trajectory. There was a negative correlation between melancholic depression, anxiety and MRI markers of myelin and iron content in the hippocampus and anterior cingulate. Verbal memory and verbal fluency performance were positively correlated with left amygdala volumes. The concomitant analysis of brain morphometry and tissue properties allowed for a neuro-biological interpretation of the link between modifiable risk factors and brain health.
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Grotheer M, Yeatman J, Grill-Spector K. White matter fascicles and cortical microstructure predict reading-related responses in human ventral temporal cortex. Neuroimage 2021; 227:117669. [PMID: 33359351 PMCID: PMC8416179 DOI: 10.1016/j.neuroimage.2020.117669] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Revised: 12/10/2020] [Accepted: 12/12/2020] [Indexed: 01/30/2023] Open
Abstract
Reading-related responses in the lateral ventral temporal cortex (VTC) show a consistent spatial layout across individuals, which is puzzling, since reading skills are acquired during childhood. Here, we tested the hypothesis that white matter fascicles and gray matter microstructure predict the location of reading-related responses in lateral VTC. We obtained functional (fMRI), diffusion (dMRI), and quantitative (qMRI) magnetic resonance imaging data in 30 adults. fMRI was used to map reading-related responses by contrasting responses in a reading task with those in adding and color tasks; dMRI was used to identify the brain's fascicles and to map their endpoint densities in lateral VTC; qMRI was used to measure proton relaxation time (T1), which depends on cortical tissue microstructure. We fit linear models that predict reading-related responses in lateral VTC from endpoint density and T1 and used leave-one-subject-out cross-validation to assess prediction accuracy. Using a subset of our participants (N=10, feature selection set), we find that i) endpoint densities of the arcuate fasciculus (AF), inferior longitudinal fasciculus (ILF), and vertical occipital fasciculus (VOF) are significant predictors of reading-related responses, and ii) cortical T1 of lateral VTC further improves the predictions of the fascicle model. In the remaining participants (N=20, validation set), we show that a linear model that includes T1, AF, ILF and VOF significantly predicts i) the map of reading-related responses across lateral VTC and ii) the location of the visual word form area, a region critical for reading. Overall, our data-driven approach reveals that the AF, ILF, VOF and cortical microstructure have a consistent spatial relationship with an individual's reading-related responses in lateral VTC.
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Affiliation(s)
- Mareike Grotheer
- Psychology Department, Stanford University, Stanford, CA 94305, USA..
| | - Jason Yeatman
- Psychology Department, Stanford University, Stanford, CA 94305, USA.; Graduate School of Education, Stanford University, Stanford, CA 94305, USA.; Division of Developmental-Behavioral Pediatrics, Stanford University School of Medicine, Stanford, CA 94305, USA.; Wu Tsai Neurosciences Institute, Stanford University, CA 94305, USA
| | - Kalanit Grill-Spector
- Psychology Department, Stanford University, Stanford, CA 94305, USA.; Wu Tsai Neurosciences Institute, Stanford University, CA 94305, USA
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Mohammadi S, Callaghan MF. Towards in vivo g-ratio mapping using MRI: Unifying myelin and diffusion imaging. J Neurosci Methods 2021; 348:108990. [PMID: 33129894 PMCID: PMC7840525 DOI: 10.1016/j.jneumeth.2020.108990] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 09/21/2020] [Accepted: 10/20/2020] [Indexed: 12/19/2022]
Abstract
BACKGROUND The g-ratio, quantifying the comparative thickness of the myelin sheath encasing an axon, is a geometrical invariant that has high functional relevance because of its importance in determining neuronal conduction velocity. Advances in MRI data acquisition and signal modelling have put in vivo mapping of the g-ratio, across the entire white matter, within our reach. This capacity would greatly increase our knowledge of the nervous system: how it functions, and how it is impacted by disease. NEW METHOD This is the second review on the topic of g-ratio mapping using MRI. RESULTS This review summarizes the most recent developments in the field, while also providing methodological background pertinent to aggregate g-ratio weighted mapping, and discussing pitfalls associated with these approaches. COMPARISON WITH EXISTING METHODS Using simulations based on recently published data, this review reveals caveats to the state-of-the-art calibration methods that have been used for in vivo g-ratio mapping. It highlights the need to estimate both the slope and offset of the relationship between these MRI-based markers and the true myelin volume fraction if we are really to achieve the goal of precise, high sensitivity g-ratio mapping in vivo. Other challenges discussed in this review further evidence the need for gold standard measurements of human brain tissue from ex vivo histology. CONCLUSIONS We conclude that the quest to find the most appropriate MRI biomarkers to enable in vivo g-ratio mapping is ongoing, with the full potential of many novel techniques yet to be investigated.
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Affiliation(s)
- Siawoosh Mohammadi
- Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany; Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| | - Martina F Callaghan
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, UK
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