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Zhang F, Chen Y, Ning L, Rushmore J, Liu Q, Du M, Hassanzadeh‐Behbahani S, Legarreta J, Yeterian E, Makris N, Rathi Y, O'Donnell L. Assessment of the Depiction of Superficial White Matter Using Ultra-High-Resolution Diffusion MRI. Hum Brain Mapp 2024; 45:e70041. [PMID: 39392220 PMCID: PMC11467805 DOI: 10.1002/hbm.70041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2024] [Accepted: 09/22/2024] [Indexed: 10/12/2024] Open
Abstract
The superficial white matter (SWM) consists of numerous short-range association fibers connecting adjacent and nearby gyri and plays an important role in brain function, development, aging, and various neurological disorders. Diffusion MRI (dMRI) tractography is an advanced imaging technique that enables in vivo mapping of the SWM. However, detailed imaging of the small, highly-curved fibers of the SWM is a challenge for current clinical and research dMRI acquisitions. This work investigates the efficacy of mapping the SWM using in vivo ultra-high-resolution dMRI data. We compare the SWM mapping performance from two dMRI acquisitions: a high-resolution 0.76-mm isotropic acquisition using the generalized slice-dithered enhanced resolution (gSlider) protocol and a lower resolution 1.25-mm isotropic acquisition obtained from the Human Connectome Project Young Adult (HCP-YA) database. Our results demonstrate significant differences in the cortico-cortical anatomical connectivity that is depicted by these two acquisitions. We perform a detailed assessment of the anatomical plausibility of these results with respect to the nonhuman primate (macaque) tract-tracing literature. We find that the high-resolution gSlider dataset is more successful at depicting a large number of true positive anatomical connections in the SWM. An additional cortical coverage analysis demonstrates significantly higher cortical coverage in the gSlider dataset for SWM streamlines under 40 mm in length. Overall, we conclude that the spatial resolution of the dMRI data is one important factor that can significantly affect the mapping of SWM. Considering the relatively long acquisition time, the application of dMRI tractography for SWM mapping in future work should consider the balance of data acquisition efforts and the efficacy of SWM depiction.
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Affiliation(s)
- Fan Zhang
- School of Information and Communication Engineering, University of Electronic Science and Technology of ChinaChengduChina
- Department of RadiologyBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Yuqian Chen
- Department of RadiologyBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Lipeng Ning
- Department of PsychiatryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Jarrett Rushmore
- Department of PsychiatryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of Anatomy and NeurobiologyBoston University School of MedicineBostonMassachusettsUSA
| | - Qiang Liu
- Department of PsychiatryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Mubai Du
- School of Information and Communication Engineering, University of Electronic Science and Technology of ChinaChengduChina
| | | | - Jon Haitz Legarreta
- Department of RadiologyBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Edward Yeterian
- Department of Anatomy and NeurobiologyBoston University School of MedicineBostonMassachusettsUSA
- Department of PsychologyColby CollegeWatervilleMaineUSA
| | - Nikos Makris
- Department of PsychiatryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Yogesh Rathi
- Department of PsychiatryBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Lauren J. O'Donnell
- School of Information and Communication Engineering, University of Electronic Science and Technology of ChinaChengduChina
- Department of RadiologyBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
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2
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Zhang D, Zong F, Zhang Q, Yue Y, Zhang F, Zhao K, Wang D, Wang P, Zhang X, Liu Y. Anat-SFSeg: Anatomically-guided superficial fiber segmentation with point-cloud deep learning. Med Image Anal 2024; 95:103165. [PMID: 38608510 DOI: 10.1016/j.media.2024.103165] [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: 09/29/2023] [Revised: 03/28/2024] [Accepted: 04/05/2024] [Indexed: 04/14/2024]
Abstract
Diffusion magnetic resonance imaging (dMRI) tractography is a critical technique to map the brain's structural connectivity. Accurate segmentation of white matter, particularly the superficial white matter (SWM), is essential for neuroscience and clinical research. However, it is challenging to segment SWM due to the short adjacent gyri connection in a U-shaped pattern. In this work, we propose an Anatomically-guided Superficial Fiber Segmentation (Anat-SFSeg) framework to improve the performance on SWM segmentation. The framework consists of a unique fiber anatomical descriptor (named FiberAnatMap) and a deep learning network based on point-cloud data. The spatial coordinates of fibers represented as point clouds, as well as the anatomical features at both the individual and group levels, are fed into a neural network. The network is trained on Human Connectome Project (HCP) datasets and tested on the subjects with a range of cognitive impairment levels. One new metric named fiber anatomical region proportion (FARP), quantifies the ratio of fibers in the defined brain regions and enables the comparison with other methods. Another metric named anatomical region fiber count (ARFC), represents the average fiber number in each cluster for the assessment of inter-subject differences. The experimental results demonstrate that Anat-SFSeg achieves the highest accuracy on HCP datasets and exhibits great generalization on clinical datasets. Diffusion tensor metrics and ARFC show disorder severity associated alterations in patients with Alzheimer's disease (AD) and mild cognitive impairments (MCI). Correlations with cognitive grades show that these metrics are potential neuroimaging biomarkers for AD. Furthermore, Anat-SFSeg could be utilized to explore other neurodegenerative, neurodevelopmental or psychiatric disorders.
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Affiliation(s)
- Di Zhang
- School of Airtificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
| | - Fangrong Zong
- School of Airtificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China.
| | - Qichen Zhang
- School of Airtificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
| | - Yunhui Yue
- School of Airtificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
| | - Fan Zhang
- School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China
| | - Kun Zhao
- School of Airtificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
| | - Dawei Wang
- Department of Radiology, Qilu Hospital of Shandong University, Jinan, China; Department of Epidemiology and Health Statistics, School of Public Health, Shandong University, Jinan, China; Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, China
| | - Pan Wang
- Department of Neurology, Tianjin Huanhu Hospital, Tianjin, China
| | - Xi Zhang
- Department of Neurology, the Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Yong Liu
- School of Airtificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
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3
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Huang HX, Inglese P, Tang J, Yagoubi R, Correia GDS, Horneffer-van der Sluis VM, Camuzeaux S, Wu V, Kopanitsa MV, Willumsen N, Jackson JS, Barron AM, Saito T, Saido TC, Gentlemen S, Takats Z, Matthews PM. Mass spectrometry imaging highlights dynamic patterns of lipid co-expression with Aβ plaques in mouse and human brains. J Neurochem 2024; 168:1193-1214. [PMID: 38372586 DOI: 10.1111/jnc.16042] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2023] [Revised: 11/13/2023] [Accepted: 12/06/2023] [Indexed: 02/20/2024]
Abstract
Lipids play crucial roles in the susceptibility and brain cellular responses to Alzheimer's disease (AD) and are increasingly considered potential soluble biomarkers in cerebrospinal fluid (CSF) and plasma. To delineate the pathological correlations of distinct lipid species, we conducted a comprehensive characterization of both spatially localized and global differences in brain lipid composition in AppNL-G-F mice with spatial and bulk mass spectrometry lipidomic profiling, using human amyloid-expressing (h-Aβ) and WT mouse brains controls. We observed age-dependent increases in lysophospholipids, bis(monoacylglycerol) phosphates, and phosphatidylglycerols around Aβ plaques in AppNL-G-F mice. Immunohistology-based co-localization identified associations between focal pro-inflammatory lipids, glial activation, and autophagic flux disruption. Likewise, in human donors with varying Braak stages, similar studies of cortical sections revealed co-expression of lysophospholipids and ceramides around Aβ plaques in AD (Braak stage V/VI) but not in earlier Braak stage controls. Our findings in mice provide evidence of temporally and spatially heterogeneous differences in lipid composition as local and global Aβ-related pathologies evolve. Observing similar lipidomic changes associated with pathological Aβ plaques in human AD tissue provides a foundation for understanding differences in CSF lipids with reported clinical stage or disease severity.
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Affiliation(s)
- Helen Xuexia Huang
- Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
- UK Dementia Research Institute at Imperial College London, Imperial College London, London, UK
| | - Paolo Inglese
- Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Jiabin Tang
- Department of Brain Sciences, Imperial College London, London, UK
| | - Riad Yagoubi
- Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
- UK Dementia Research Institute at Imperial College London, Imperial College London, London, UK
| | - Gonçalo D S Correia
- Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | | | - Stephane Camuzeaux
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Vincen Wu
- Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Maksym V Kopanitsa
- UK Dementia Research Institute at Imperial College London, Imperial College London, London, UK
| | - Nanet Willumsen
- UK Dementia Research Institute at Imperial College London, Imperial College London, London, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | - Johanna S Jackson
- UK Dementia Research Institute at Imperial College London, Imperial College London, London, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | - Anna M Barron
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Takashi Saito
- Laboratory for Proteolytic Neuroscience, RIKEN Center for Brain Science, Saitama, Japan
- Department of Neurocognitive Science, Institute of Brain Science, Nagoya City University, Graduate School of Medical Sciences, Nagoya, Aichi, Japan
| | - Takaomi C Saido
- Laboratory for Proteolytic Neuroscience, RIKEN Center for Brain Science, Saitama, Japan
- Department of Neurocognitive Science, Institute of Brain Science, Nagoya City University, Graduate School of Medical Sciences, Nagoya, Aichi, Japan
| | - Steve Gentlemen
- Department of Brain Sciences, Imperial College London, London, UK
| | - Zoltan Takats
- Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Paul M Matthews
- UK Dementia Research Institute at Imperial College London, Imperial College London, London, UK
- Department of Brain Sciences, Imperial College London, London, UK
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4
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Gilani N, Mikheev A, Brinkmann IM, Kumbella M, Babb JS, Basukala D, Wetscherek A, Benkert T, Chandarana H, Sigmund EE. Spatial profiling of in vivo diffusion-weighted MRI parameters in the healthy human kidney. MAGMA (NEW YORK, N.Y.) 2024:10.1007/s10334-024-01159-6. [PMID: 38703246 DOI: 10.1007/s10334-024-01159-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Revised: 01/17/2024] [Accepted: 03/26/2024] [Indexed: 05/06/2024]
Abstract
OBJECTIVE Diffusion-weighted MRI is a technique that can infer microstructural and microcirculatory features from biological tissue, with particular application to renal tissue. There is extensive literature on diffusion tensor imaging (DTI) of anisotropy in the renal medulla, intravoxel incoherent motion (IVIM) measurements separating microstructural from microcirculation effects, and combinations of the two. However, interpretation of these features and adaptation of more specific models remains an ongoing challenge. One input to this process is a whole organ distillation of corticomedullary contrast of diffusion metrics, as has been explored for other renal biomarkers. MATERIALS AND METHODS In this work, we probe the spatial dependence of diffusion MRI metrics with concentrically layered segmentation in 11 healthy kidneys at 3 T. The metrics include those from DTI, IVIM, a combined approach titled "REnal Flow and Microstructure AnisotroPy (REFMAP)", and a multiply encoded model titled "FC-IVIM" providing estimates of fluid velocity and branching length. RESULTS Fractional anisotropy decreased from the inner kidney to the outer kidney with the strongest layer correlation in both parenchyma (including cortex and medulla) and medulla with Spearman correlation coefficients and p-values (r, p) of (0.42, <0.001) and (0.37, <0.001), respectively. Also, dynamic parameters derived from the three models significantly decreased with a high correlation from the inner to the outer parenchyma or medulla with (r, p) ranges of (0.46-0.55, <0.001). CONCLUSIONS These spatial trends might find implications for indirect assessments of kidney physiology and microstructure using diffusion MRI.
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Affiliation(s)
- Nima Gilani
- Department of Radiology, Center for Advanced Imaging Innovation and Research (CAI2R), Center for Biomedical Imaging, NYU Langone Health, New York, USA.
| | - Artem Mikheev
- Department of Radiology, Center for Advanced Imaging Innovation and Research (CAI2R), Center for Biomedical Imaging, NYU Langone Health, New York, USA
| | | | - Malika Kumbella
- Department of Radiology, Center for Advanced Imaging Innovation and Research (CAI2R), Center for Biomedical Imaging, NYU Langone Health, New York, USA
| | - James S Babb
- Department of Radiology, Center for Advanced Imaging Innovation and Research (CAI2R), Center for Biomedical Imaging, NYU Langone Health, New York, USA
| | - Dibash Basukala
- Department of Radiology, Center for Advanced Imaging Innovation and Research (CAI2R), Center for Biomedical Imaging, NYU Langone Health, New York, USA
| | - Andreas Wetscherek
- Joint Department of Physics, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK
| | - Thomas Benkert
- MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany
| | - Hersh Chandarana
- Department of Radiology, Center for Advanced Imaging Innovation and Research (CAI2R), Center for Biomedical Imaging, NYU Langone Health, New York, USA
| | - Eric E Sigmund
- Department of Radiology, Center for Advanced Imaging Innovation and Research (CAI2R), Center for Biomedical Imaging, NYU Langone Health, New York, USA
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Wang X, Wang S, Holland MA. Axonal tension contributes to consistent fold placement. SOFT MATTER 2024; 20:3053-3065. [PMID: 38506323 DOI: 10.1039/d4sm00129j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/21/2024]
Abstract
Cortical folding is a critical process during brain development, resulting in morphologies that are both consistent and distinct between individuals and species. While earlier studies have highlighted important aspects of cortical folding, most existing computational models, based on the differential growth theory, fall short of explaining why folds tend to appear in particular locations. The axon tension hypothesis may provide insight into this conundrum; however, there has been significant controversy about a potential role of axonal tension during the gyrification. The common opinion in the field is that axonal tension is inadequate to drive gyrification, but we currently run the risk of discarding this hypothesis without comprehensively studying the role of axonal tension. Here we propose a novel bi-layered finite element model incorporating the two theories, including characteristic axonal tension in the subcortex and differential cortical growth. We show that axon tension can serve as a perturbation sufficient to trigger buckling in simulations; similarly to other types of perturbations, the natural stability behavior of the system tends to determine some characteristics of the folding morphology (e.g. the wavelength) while the perturbation determines the location of folds. Certain geometries, however, can interact or compete with the natural stability of the system to change the wavelength. When multiple perturbations are present, they similarly compete with each other. We found that an axon bundle of reasonable size will overpower up to a 5% thickness perturbation (typical in the literature) and determine fold placement. Finally, when multiple axon tracts are present, even a slight difference in axon stiffness, representing the heterogeneity of axonal connections, is enough to significantly change the folding pattern. While the simulations presented here are a very simple representation of white matter connectivity, our findings point to urgent future research on the role of axon connectivity in cortical folding.
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Affiliation(s)
- Xincheng Wang
- Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN 46556, USA.
| | - Shuolun Wang
- Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN 46556, USA.
| | - Maria A Holland
- Department of Aerospace and Mechanical Engineering, University of Notre Dame, Notre Dame, IN 46556, USA.
- Bioengineering Graduate Program, University of Notre Dame, Notre Dame, IN 46556, USA
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6
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He J, Wang Y. Superficial white matter microstructural imaging method based on time-space fractional-order diffusion. Phys Med Biol 2024; 69:065010. [PMID: 38394673 DOI: 10.1088/1361-6560/ad2ca1] [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: 09/10/2023] [Accepted: 02/23/2024] [Indexed: 02/25/2024]
Abstract
Objective. Microstructure imaging based on diffusion magnetic resonance signal is an advanced imaging technique that enablesin vivomapping of the brain's microstructure. Superficial white matter (SWM) plays an important role in brain development, maturation, and aging, while fewer microstructure imaging methods address the SWM due to its complexity. Therefore, this study aims to develop a diffusion propagation model to investigate the microstructural characteristics of the SWM region.Approach. In this paper, we hypothesize that the effect of cell membrane permeability and the water exchange between soma and dendrites cannot be neglected for typical clinical diffusion times (20 ms
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Affiliation(s)
- Jianglin He
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, People's Republic of China
| | - Yuanjun Wang
- School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, People's Republic of China
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Luo D, Peng Y, Zhu Q, Zheng Q, Luo Q, Han Y, Chen X, Li Y. U-fiber diffusion kurtosis and susceptibility characteristics in relapsing-remitting multiple sclerosis may be related to cognitive deficits and neurodegeneration. Eur Radiol 2024; 34:1422-1433. [PMID: 37658142 DOI: 10.1007/s00330-023-10114-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Revised: 05/30/2023] [Accepted: 07/01/2023] [Indexed: 09/03/2023]
Abstract
OBJECTIVES To evaluate the diffusion kurtosis and susceptibility change in the U-fiber region of patients with relapsing-remitting multiple sclerosis (pwRRMS) and their correlations with cognitive status and degeneration. MATERIALS AND METHODS Mean kurtosis (MK), axial kurtosis (AK), radial kurtosis (RK), kurtosis fractional anisotropy (KFA), and the mean relative quantitative susceptibility mapping (mrQSM) values in the U-fiber region were compared between 49 pwRRMS and 48 healthy controls (HCs). The U-fiber were divided into upper and deeper groups based on the location. The whole brain volume, gray and white matter volume, and cortical thickness were obtained. The correlations between the mrQSM values, DKI-derived metrics in the U-fiber region and clinical scale scores, brain morphologic parameters were further investigated. RESULTS The decreased MK, AK, RK, KFA, and increased mrQSM values in U-fiber lesions (p < 0.001, FDR corrected), decreased RK, KFA, and increased mrQSM values in U-fiber non-lesions (p = 0.034, p < 0.001, p < 0.001, FDR corrected) were found in pwRRMS. There were differences in DKI-derived metrics and susceptibility values between the upper U-fiber region and the deeper one for U-fiber non-lesion areas of pwRRMS and HCs (p < 0.05), but not for U-fiber lesions in DKI-derived metrics. The DKI-derived metrics and susceptibility values were widely related with cognitive tests and brain atrophy. CONCLUSION RRMS patients show abnormal diffusion kurtosis and susceptibility characteristics in the U-fiber region, and these underlying tissue abnormalities are correlated with cognitive deficits and degeneration. CLINICAL RELEVANCE STATEMENT The macroscopic and microscopic tissue damages of U-fiber help to identify cognitive impairment and brain atrophy in multiple sclerosis and provide underlying pathophysiological mechanism. KEY POINTS • Diffusion kurtosis and susceptibility changes are present in the U-fiber region of multiple sclerosis. • There are gradients in diffusion kurtosis and susceptibility characteristics in the U-fiber region. • Tissue damages in the U-fiber region are correlated with cognitive impairment and brain atrophy.
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Affiliation(s)
- Dan Luo
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuzhong District, Chongqing, 400016, China
| | - Yuling Peng
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuzhong District, Chongqing, 400016, China
| | - Qiyuan Zhu
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuzhong District, Chongqing, 400016, China
| | - Qiao Zheng
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuzhong District, Chongqing, 400016, China
| | - Qi Luo
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuzhong District, Chongqing, 400016, China
| | - Yongliang Han
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuzhong District, Chongqing, 400016, China
| | - Xiaoya Chen
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuzhong District, Chongqing, 400016, China.
| | - Yongmei Li
- Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuzhong District, Chongqing, 400016, China.
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8
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Sandgaard AD, Kiselev VG, Henriques RN, Shemesh N, Jespersen SN. Incorporating the effect of white matter microstructure in the estimation of magnetic susceptibility in ex vivo mouse brain. Magn Reson Med 2024; 91:699-715. [PMID: 37772624 DOI: 10.1002/mrm.29867] [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: 02/01/2023] [Revised: 08/07/2023] [Accepted: 08/25/2023] [Indexed: 09/30/2023]
Abstract
PURPOSE To extend quantitative susceptibility mapping to account for microstructure of white matter (WM) and demonstrate its effect on ex vivo mouse brain at 16.4T. THEORY AND METHODS Previous studies have shown that the MRI measured Larmor frequency also depends on local magnetic microstructure at the mesoscopic scale. Here, we include effects from WM microstructure using our previous results for the mesoscopic Larmor frequencyΩ ‾ Meso $$ {\overline{\Omega}}^{\mathrm{Meso}} $$ of cylinders with arbitrary orientations. We scrutinize the validity of our model and QSM in a digital brain phantom includingΩ ‾ Meso $$ {\overline{\Omega}}^{\mathrm{Meso}} $$ from a WM susceptibility tensor and biologically stored iron with scalar susceptibility. We also apply susceptibility tensor imaging to the phantom and investigate how the fitted tensors are biased fromΩ ‾ Meso $$ {\overline{\Omega}}^{\mathrm{Meso}} $$ . Last, we demonstrate how to combine multi-gradient echo and diffusion MRI images of ex vivo mouse brains acquired at 16.4T to estimate an apparent scalar susceptibility without sample rotations. RESULTS Our new model improves susceptibility estimation compared to QSM for the brain phantom. Applying susceptibility tensor imaging to the phantom withΩ ‾ Meso $$ {\overline{\Omega}}^{\mathrm{Meso}} $$ from WM axons with scalar susceptibility produces a highly anisotropic susceptibility tensor that mimics results from previous susceptibility tensor imaging studies. For the ex vivo mouse brain we find theΩ ‾ Meso $$ {\overline{\Omega}}^{\mathrm{Meso}} $$ due to WM microstructure to be substantial, changing susceptibility in WM up to 25% root-mean-squared-difference. CONCLUSION Ω ‾ Meso $$ {\overline{\Omega}}^{\mathrm{Meso}} $$ impacts susceptibility estimates and biases susceptibility tensor imaging fitting substantially. Hence, it should not be neglected when imaging structurally anisotropic tissue such as brain WM.
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Affiliation(s)
- Anders Dyhr Sandgaard
- Center for Functionally Integrative Neuroscience, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Valerij G Kiselev
- Division of Medical Physics, Department of Radiology, University Medical Center Freiburg, Freiburg, Germany
| | | | - Noam Shemesh
- Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Sune Nørhøj Jespersen
- Center for Functionally Integrative Neuroscience, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Department of Physics and Astronomy, Aarhus University, Aarhus, Denmark
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9
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Merenstein JL, Zhao J, Overson DK, Truong TK, Johnson KG, Song AW, Madden DJ. Depth- and curvature-based quantitative susceptibility mapping analyses of cortical iron in Alzheimer's disease. Cereb Cortex 2024; 34:bhad525. [PMID: 38185996 PMCID: PMC10839848 DOI: 10.1093/cercor/bhad525] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 11/21/2023] [Accepted: 12/15/2023] [Indexed: 01/09/2024] Open
Abstract
In addition to amyloid beta plaques and neurofibrillary tangles, Alzheimer's disease (AD) has been associated with elevated iron in deep gray matter nuclei using quantitative susceptibility mapping (QSM). However, only a few studies have examined cortical iron, using more macroscopic approaches that cannot assess layer-specific differences. Here, we conducted column-based QSM analyses to assess whether AD-related increases in cortical iron vary in relation to layer-specific differences in the type and density of neurons. We obtained global and regional measures of positive (iron) and negative (myelin, protein aggregation) susceptibility from 22 adults with AD and 22 demographically matched healthy controls. Depth-wise analyses indicated that global susceptibility increased from the pial surface to the gray/white matter boundary, with a larger slope for positive susceptibility in the left hemisphere for adults with AD than controls. Curvature-based analyses indicated larger global susceptibility for adults with AD versus controls; the right hemisphere versus left; and gyri versus sulci. Region-of-interest analyses identified similar depth- and curvature-specific group differences, especially for temporo-parietal regions. Finding that iron accumulates in a topographically heterogenous manner across the cortical mantle may help explain the profound cognitive deterioration that differentiates AD from the slowing of general motor processes in healthy aging.
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Affiliation(s)
- Jenna L Merenstein
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC 27710, United States
| | - Jiayi Zhao
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC 27710, United States
| | - Devon K Overson
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC 27710, United States
- Medical Physics Graduate Program, Duke University, Durham, NC 27708, United States
| | - Trong-Kha Truong
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC 27710, United States
- Medical Physics Graduate Program, Duke University, Durham, NC 27708, United States
| | - Kim G Johnson
- Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC 27710, United States
| | - Allen W Song
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC 27710, United States
- Medical Physics Graduate Program, Duke University, Durham, NC 27708, United States
| | - David J Madden
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC 27710, United States
- Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC 27710, United States
- Center for Cognitive Neuroscience, Duke University, Durham, NC 27708, United States
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Friederici AD, Wittig RM, Anwander A, Eichner C, Gräßle T, Jäger C, Kirilina E, Lipp I, Düx A, Edwards LJ, Girard-Buttoz C, Jauch A, Kopp KS, Paquette M, Pine KJ, Unwin S, Haun DBM, Leendertz FH, McElreath R, Morawski M, Gunz P, Weiskopf N, Crockford C. Brain structure and function: a multidisciplinary pipeline to study hominoid brain evolution. Front Integr Neurosci 2024; 17:1299087. [PMID: 38260006 PMCID: PMC10800984 DOI: 10.3389/fnint.2023.1299087] [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: 09/22/2023] [Accepted: 12/07/2023] [Indexed: 01/24/2024] Open
Abstract
To decipher the evolution of the hominoid brain and its functions, it is essential to conduct comparative studies in primates, including our closest living relatives. However, strong ethical concerns preclude in vivo neuroimaging of great apes. We propose a responsible and multidisciplinary alternative approach that links behavior to brain anatomy in non-human primates from diverse ecological backgrounds. The brains of primates observed in the wild or in captivity are extracted and fixed shortly after natural death, and then studied using advanced MRI neuroimaging and histology to reveal macro- and microstructures. By linking detailed neuroanatomy with observed behavior within and across primate species, our approach provides new perspectives on brain evolution. Combined with endocranial brain imprints extracted from computed tomographic scans of the skulls these data provide a framework for decoding evolutionary changes in hominin fossils. This approach is poised to become a key resource for investigating the evolution and functional differentiation of hominoid brains.
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Affiliation(s)
- Angela D. Friederici
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Roman M. Wittig
- Evolution of Brain Connectivity Project, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
- Institute for Cognitive Sciences Marc Jeannerod, UMR CNRS, University Claude Bernard Lyon, Bron, France
- Taï Chimpanzee Project, CSRS, Abidjan, Côte d'Ivoire
| | - Alfred Anwander
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Cornelius Eichner
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Tobias Gräßle
- Epidemiology of Highly Pathogenic Microorganisms, Robert Koch Institute, Berlin, Germany
| | - Carsten Jäger
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Medical Faculty, Center of Neuropathology and Brain Research, Paul Flechsig Institute, University of Leipzig, Leipzig, Germany
| | - Evgeniya Kirilina
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, 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, University of Greifswald, Greifswald, Germany
| | - Luke J. Edwards
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Cédric Girard-Buttoz
- Evolution of Brain Connectivity Project, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
- Institute for Cognitive Sciences Marc Jeannerod, UMR CNRS, University Claude Bernard Lyon, Bron, France
| | - 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 Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Kerrin J. Pine
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Steve Unwin
- School of Bioscience, University of Birmingham, Birmingham, United Kingdom
| | - Daniel B. M. Haun
- Department of Comparative Cultural Psychology, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
| | - Fabian H. Leendertz
- Epidemiology of Highly Pathogenic Microorganisms, Robert Koch Institute, Berlin, Germany
- Helmholtz Institute for One Health, University of Greifswald, Greifswald, Germany
| | - Richard McElreath
- Department of Human Behavior, Ecology and Culture, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
| | - Markus Morawski
- Medical Faculty, Center of Neuropathology and Brain Research, Paul Flechsig Institute, University of Leipzig, Leipzig, Germany
| | - Philipp Gunz
- Department of Human Origins, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Faculty of Physics and Earth System Sciences, Felix Bloch Institute for Solid State Physics, Leipzig University, Leipzig, Germany
| | - Catherine Crockford
- Evolution of Brain Connectivity Project, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
- Institute for Cognitive Sciences Marc Jeannerod, UMR CNRS, University Claude Bernard Lyon, Bron, France
- Taï Chimpanzee Project, CSRS, Abidjan, Côte d'Ivoire
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11
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Zheng G, Fei B, Ge A, Liu Y, Liu Y, Yang Z, Chen Z, Wang X, Wang H, Ding J. U-fiber analysis: a toolbox for automated quantification of U-fibers and white matter hyperintensities. Quant Imaging Med Surg 2024; 14:662-683. [PMID: 38223048 PMCID: PMC10784071 DOI: 10.21037/qims-23-847] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 11/13/2023] [Indexed: 01/16/2024]
Abstract
Background Whether white matter hyperintensities (WMHs) involve U-fibers is of great value in understanding the different etiologies of cerebral white matter (WM) lesions. However, clinical practice currently relies only on the naked eye to determine whether WMHs are in the vicinity of U-fibers, and there is a lack of good neuroimaging tools to quantify WMHs and U-fibers. Methods Here, we developed a multimodal neuroimaging toolbox named U-fiber analysis (UFA) that can automatically extract WMHs and quantitatively characterize the volume and number of WMHs in different brain regions. In addition, we proposed an anatomically constrained U-fiber tracking scheme and quantitatively characterized the microstructure diffusion properties, fiber length, and number of U-fibers in different brain regions to help clinicians to quantitatively determine whether WMHs in the proximal cortex disrupt the microstructure of U-fibers. To validate the utility of the UFA toolbox, we analyzed the neuroimaging data from 246 patients with cerebral small vessel disease (cSVD) enrolled at Zhongshan Hospital between March 2018 and November 2019 in a cross-sectional study. Results According to the manual judgment of the clinician, the patients with cSVD were divided into a WMHs involved U-fiber group (U-fiber-involved group, 51 cases) and WMHs not involved U-fiber group (U-fiber-spared group, 163 cases). There were no significant differences between the U-fiber-spared group and the U-fiber-involved group in terms of age (P=0.143), gender (P=0.462), education (P=0.151), Mini-Mental State Examination (MMSE) scores (P=0.151), and Montreal Cognitive Assessment (MoCA) scores (P=0.411). However, patients in the U-fiber-involved group had higher Fazekas scores (P<0.001) and significantly higher whole brain WMHs (P=0.046) and deep WMH volumes (P<0.001) compared to patients in the U-fiber-spared group. Moreover, the U-fiber-involved group had higher WMH volumes in the bilateral frontal [P(left) <0.001, P(right) <0.001] and parietal lobes [P(left) <0.001, P(right) <0.001]. On the other hand, patients in the U-fiber-involved group had higher mean diffusivity (MD) and axial diffusivity (AD) in the bilateral parietal [P(left, MD) =0.048, P(right, MD) =0.045, P(left, AD) =0.015, P(right, AD) =0.015] and right frontal-parietal regions [P(MD) =0.048, P(AD) =0.027], and had significantly reduced mean fiber length and number in the right parietal [P(length) =0.013, P(number) =0.028] and right frontal-parietal regions [P(length) =0.048] compared to patients in the U-fiber-spared group. Conclusions Our results suggest that WMHs in the proximal cortex may disrupt the microstructure of U-fibers. Our tool may provide new insights into the understanding of WM lesions of different etiologies in the brain.
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Affiliation(s)
- Gaoxing Zheng
- Department of Neurology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Beini Fei
- Department of Neurology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Anyan Ge
- Department of Neurology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yuchen Liu
- Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China
| | - Ying Liu
- Department of Neurology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Zidong Yang
- Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China
| | - Zhensen Chen
- Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China
| | - Xin Wang
- Department of Neurology, Zhongshan Hospital, Fudan University, Shanghai, China
| | - He Wang
- Department of Neurology, Zhongshan Hospital, Fudan University, Shanghai, China
- Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China
| | - Jing Ding
- Department of Neurology, Zhongshan Hospital, Fudan University, Shanghai, China
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12
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Li Y, Nie X, Fu Y, Shi Y. FASSt : Filtering via Symmetric Autoencoder for Spherical Superficial White Matter Tractography. COMPUTATIONAL DIFFUSION MRI : MICCAI WORKSHOP 2023; 14328:129-139. [PMID: 38500570 PMCID: PMC10948089 DOI: 10.1007/978-3-031-47292-3_12] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/20/2024]
Abstract
Superficial white matter (SWM) plays an important role in functioning of the human brain, and it contains a large amount of cortico-cortical connections. However, the difficulties of generating complete and reliable U-fibers make SWM-related analysis lag behind relatively matured Deep white matter (DWM) analysis. With the aid of some newly proposed surface-based SWM tractography algorithms, we have developed a specialized SWM filtering method based on a symmetric variational autoencoder (VAE). In this work, we first demonstrate the advantage of the spherical representation and generate these spherical tracts using the triangular mesh and the registered spherical surface. We then introduce the Filtering via symmetric Autoencoder for Spherical Superficial White Matter tractography (FASSt) framework with a novel symmetric weights module to perform the filtering task in a latent space. We evaluate and compare our method with the state-of-the-art clustering-based method on diffusion MRI data from Human Connectome Project (HCP). The results show that our proposed method outperform these clustering methods and achieves excellent performance in groupwise consistency and topographic regularity.
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Affiliation(s)
- Yuan Li
- Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California (USC), Los Angeles, CA 90033, USA
- Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California (USC), Los Angeles, CA 90089, USA
| | - Xinyu Nie
- Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California (USC), Los Angeles, CA 90033, USA
- Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California (USC), Los Angeles, CA 90089, USA
| | - Yao Fu
- Department of Computer and Data Sciences, Case School of Engineering, Case Western Reserve University (CWRU), Cleveland, OH 44106, USA
| | - Yonggang Shi
- Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California (USC), Los Angeles, CA 90033, USA
- Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California (USC), Los Angeles, CA 90089, USA
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13
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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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14
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Fritz FJ, Mordhorst L, Ashtarayeh M, Periquito J, Pohlmann A, Morawski M, Jaeger C, Niendorf T, Pine KJ, Callaghan MF, Weiskopf N, Mohammadi S. Fiber-orientation independent component of R 2* obtained from single-orientation MRI measurements in simulations and a post-mortem human optic chiasm. Front Neurosci 2023; 17:1133086. [PMID: 37694109 PMCID: PMC10491021 DOI: 10.3389/fnins.2023.1133086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Accepted: 08/04/2023] [Indexed: 09/12/2023] Open
Abstract
The effective transverse relaxation rate (R2*) is sensitive to the microstructure of the human brain like the g-ratio which characterises the relative myelination of axons. However, the fibre-orientation dependence of R2* degrades its reproducibility and any microstructural derivative measure. To estimate its orientation-independent part (R2,iso*) from single multi-echo gradient-recalled-echo (meGRE) measurements at arbitrary orientations, a second-order polynomial in time model (hereafter M2) can be used. Its linear time-dependent parameter, β1, can be biophysically related to R2,iso* when neglecting the myelin water (MW) signal in the hollow cylinder fibre model (HCFM). Here, we examined the performance of M2 using experimental and simulated data with variable g-ratio and fibre dispersion. We found that the fitted β1 can estimate R2,iso* using meGRE with long maximum-echo time (TEmax ≈ 54 ms), but not accurately captures its microscopic dependence on the g-ratio (error 84%). We proposed a new heuristic expression for β1 that reduced the error to 12% for ex vivo compartmental R2 values. Using the new expression, we could estimate an MW fraction of 0.14 for fibres with negligible dispersion in a fixed human optic chiasm for the ex vivo compartmental R2 values but not for the in vivo values. M2 and the HCFM-based simulations failed to explain the measured R2*-orientation-dependence around the magic angle for a typical in vivo meGRE protocol (with TEmax ≈ 18 ms). In conclusion, further validation and the development of movement-robust in vivo meGRE protocols with TEmax ≈ 54 ms are required before M2 can be used to estimate R2,iso* in subjects.
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Affiliation(s)
- Francisco J. Fritz
- Department of Systems Neurosciences, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Laurin Mordhorst
- Department of Systems Neurosciences, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Mohammad Ashtarayeh
- Department of Systems Neurosciences, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Joao Periquito
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Andreas Pohlmann
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Markus Morawski
- Paul Flechsig Institute – Center for Neuropathology and Brain Research, University of Leipzig, Leipzig, Germany
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Carsten Jaeger
- Paul Flechsig Institute – Center for Neuropathology and Brain Research, University of Leipzig, Leipzig, Germany
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Thoralf Niendorf
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max-Delbrueck-Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Kerrin J. Pine
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Martina F. Callaghan
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany
| | - Siawoosh Mohammadi
- Department of Systems Neurosciences, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Max Planck Research Group MR Physics, Max Planck Institute for Human Development, Berlin, Germany
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15
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Nishat E, Stojanovski S, Scratch SE, Ameis SH, Wheeler AL. Premature white matter microstructure in female children with a history of concussion. Dev Cogn Neurosci 2023; 62:101275. [PMID: 37441978 PMCID: PMC10439504 DOI: 10.1016/j.dcn.2023.101275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Revised: 05/18/2023] [Accepted: 07/06/2023] [Indexed: 07/15/2023] Open
Abstract
Childhood concussion may interfere with neurodevelopment and influence cognition. Females are more likely to experience persistent symptoms after concussion, yet the sex-specific impact of concussion on brain microstructure in children is understudied. This study examined white matter and cortical microstructure, based on neurite density (ND) from diffusion-weighted MRI, in 9-to-10-year-old children in the Adolescent Brain Cognitive Development Study with (n = 336) and without (n = 7368) a history of concussion, and its relationship with cognitive performance. Multivariate regression was used to investigate relationships between ND and group, sex, and age in deep and superficial white matter, subcortical structures, and cortex. Partial least square correlation was performed to identify associations between ND and performance on NIH Toolbox tasks in children with concussion. All tissue types demonstrated higher ND with age, reflecting brain maturation. Group comparisons revealed higher ND in deep and superficial white matter in females with concussion. In female but not male children with concussion, there were significant associations between ND and performance on cognitive tests. These results demonstrate a greater long-term impact of childhood concussion on white matter microstructure in females compared to males that is associated with cognitive function. The increase in ND in females may reflect premature white matter maturation.
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Affiliation(s)
- Eman Nishat
- Department of Physiology, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario M5S 1A8, Canada; Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada
| | - Sonja Stojanovski
- Department of Physiology, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario M5S 1A8, Canada; Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada
| | - Shannon E Scratch
- Department of Paediatrics, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario M5S 1A8, Canada; Rehabilitation Sciences Institute, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario M5G 1V7, Canada; Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Ontario M4G 1R8, Canada
| | - Stephanie H Ameis
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario M5T 1R8, Canada; Cundill Centre for Child and Youth Depression, Margaret and Wallace McCain Centre for Child, Youth and Family Mental Health, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario M6J 1H4, Canada
| | - Anne L Wheeler
- Department of Physiology, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario M5S 1A8, Canada; Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada.
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16
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Schilling KG, Archer D, Rheault F, Lyu I, Huo Y, Cai LY, Bunge SA, Weiner KS, Gore JC, Anderson AW, Landman BA. Superficial white matter across development, young adulthood, and aging: volume, thickness, and relationship with cortical features. Brain Struct Funct 2023; 228:1019-1031. [PMID: 37074446 PMCID: PMC10320929 DOI: 10.1007/s00429-023-02642-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Accepted: 04/08/2023] [Indexed: 04/20/2023]
Abstract
Superficial white matter (SWM) represents a significantly understudied part of the human brain, despite comprising a large portion of brain volume and making up a majority of cortico-cortical white matter connections. Using multiple, high-quality datasets with large sample sizes (N = 2421, age range 5-100) in combination with methodological advances in tractography, we quantified features of SWM volume and thickness across the brain and across development, young adulthood, and aging. We had four primary aims: (1) characterize SWM thickness across brain regions (2) describe associations between SWM volume and age (3) describe associations between SWM thickness and age, and (4) quantify relationships between SWM thickness and cortical features. Our main findings are that (1) SWM thickness varies across the brain, with patterns robust across individuals and across the population at the region-level and vertex-level; (2) SWM volume shows unique volumetric trajectories with age that are distinct from gray matter and other white matter trajectories; (3) SWM thickness shows nonlinear cross-sectional changes across the lifespan that vary across regions; and (4) SWM thickness is associated with features of cortical thickness and curvature. For the first time, we show that SWM volume follows a similar trend as overall white matter volume, peaking at a similar time in adolescence, leveling off throughout adulthood, and decreasing with age thereafter. Notably, the relative fraction of total brain volume of SWM continuously increases with age, and consequently takes up a larger proportion of total white matter volume, unlike the other tissue types that decrease with respect to total brain volume. This study represents the first characterization of SWM features across the large portion of the lifespan and provides the background for characterizing normal aging and insight into the mechanisms associated with SWM development and decline.
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Affiliation(s)
- Kurt G Schilling
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA.
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA.
| | - Derek Archer
- Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Francois Rheault
- Department of Electrical Engineering and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Ilwoo Lyu
- Computer Science and Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
| | - Yuankai Huo
- Department of Electrical Engineering and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Leon Y Cai
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Silvia A Bunge
- Department of Psychology, University of California at Berkeley, Berkeley, USA
| | - Kevin S Weiner
- Department of Psychology, University of California at Berkeley, Berkeley, USA
- Helen Wills Neuroscience Institute, University of California at Berkeley, Berkeley, USA
| | - John C Gore
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA
| | - Adam W Anderson
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Bennett A Landman
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA
- Computer Science and Engineering, Ulsan National Institute of Science and Technology, Ulsan, South Korea
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17
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van Gelderen P, Li X, de Zwart JA, Beck ES, Okar SV, Huang Y, Lai K, Sulam J, van Zijl PCM, Reich DS, Duyn JH, Liu J. Effect of motion, cortical orientation and spatial resolution on quantitative imaging of cortical R 2* and magnetic susceptibility at 0.3 mm in-plane resolution at 7 T. Neuroimage 2023; 270:119992. [PMID: 36858332 PMCID: PMC10278242 DOI: 10.1016/j.neuroimage.2023.119992] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2022] [Revised: 02/17/2023] [Accepted: 02/25/2023] [Indexed: 03/03/2023] Open
Abstract
MR images of the effective relaxation rate R2* and magnetic susceptibility χ derived from multi-echo T2*-weighted (T2*w) MRI can provide insight into iron and myelin distributions in the brain, with the potential of providing biomarkers for neurological disorders. Quantification of R2* and χ at submillimeter resolution in the cortex in vivo has been difficult because of challenges such as head motion, limited signal to noise ratio, long scan time, and motion related magnetic field fluctuations. This work aimed to improve the robustness for quantifying intracortical R2* and χ and analyze the effects from motion, spatial resolution, and cortical orientation. T2*w data was acquired with a spatial resolution of 0.3 × 0.3 × 0.4 mm3 at 7 T and downsampled to various lower resolutions. A combined correction for motion and B0 changes was deployed using volumetric navigators. Such correction improved the T2*w image quality rated by experienced image readers and test-retest reliability of R2* and χ quantification with reduced median inter-scan differences up to 10 s-1 and 5 ppb, respectively. R2* and χ near the line of Gennari, a cortical layer high in iron and myelin, were as much as 10 s-1 and 10 ppb higher than the region at adjacent cortical depth. In addition, a significant effect due to the cortical orientation relative to the static field (B0) was observed in χ with a peak-to-peak amplitude of about 17 ppb. In retrospectively downsampled data, the capability to distinguish different cortical depth regions based on R2* or χ contrast remained up to isotropic 0.5 mm resolution. This study highlights the unique characteristics of R2* and χ along the cortical depth at submillimeter resolution and the need for motion and B0 corrections for their robust quantification in vivo.
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Affiliation(s)
- Peter van Gelderen
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, NINDS, NIH, Bethesda, MD, United States of America
| | - Xu Li
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States of America; Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, United States of America
| | - Jacco A de Zwart
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, NINDS, NIH, Bethesda, MD, United States of America
| | - Erin S Beck
- Translational Neurology Section, NINDS, NIH, Bethesda, MD, United States of America; Department of Neurology, Icahn School of Medicine at Mount Sinai, New York City, NY, United States of America
| | - Serhat V Okar
- Translational Neurology Section, NINDS, NIH, Bethesda, MD, United States of America
| | - Yujia Huang
- Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, United States of America
| | - KuoWei Lai
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States of America; Department of Electrical & Computer Engineering, Georgia Institute of Technology, Atlanta, GA, United States of America
| | - Jeremias Sulam
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States of America
| | - Peter C M van Zijl
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States of America; Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, United States of America
| | - Daniel S Reich
- Translational Neurology Section, NINDS, NIH, Bethesda, MD, United States of America
| | - Jeff H Duyn
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, NINDS, NIH, Bethesda, MD, United States of America
| | - Jiaen Liu
- Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, United States of America.
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18
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Lipp I, Kirilina E, Edwards LJ, Pine KJ, Jäger C, Gräßle T, Weiskopf N, Helms G. B 1 + $$ {B}_1^{+} $$ -correction of magnetization transfer saturation maps optimized for 7T postmortem MRI of the brain. Magn Reson Med 2023; 89:1385-1400. [PMID: 36373175 DOI: 10.1002/mrm.29524] [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: 07/01/2022] [Revised: 10/06/2022] [Accepted: 10/25/2022] [Indexed: 11/15/2022]
Abstract
PURPOSE Magnetization transfer saturation ( MTsat $$ \mathrm{MTsat} $$ ) is a useful marker to probe tissue macromolecular content and myelination in the brain. The increased B 1 + $$ {B}_1^{+} $$ -inhomogeneity at ≥ 7 $$ \ge 7 $$ T and significantly larger saturation pulse flip angles which are often used for postmortem studies exceed the limits where previous MTsat $$ \mathrm{MTsat} $$ B 1 + $$ {B}_1^{+} $$ correction methods are applicable. Here, we develop a calibration-based correction model and procedure, and validate and evaluate it in postmortem 7T data of whole chimpanzee brains. THEORY The B 1 + $$ {B}_1^{+} $$ dependence of MTsat $$ \mathrm{MTsat} $$ was investigated by varying the off-resonance saturation pulse flip angle. For the range of saturation pulse flip angles applied in typical experiments on postmortem tissue, the dependence was close to linear. A linear model with a single calibration constant C $$ C $$ is proposed to correct bias in MTsat $$ \mathrm{MTsat} $$ by mapping it to the reference value of the saturation pulse flip angle. METHODS C $$ C $$ was estimated voxel-wise in five postmortem chimpanzee brains. "Individual-based global parameters" were obtained by calculating the mean C $$ C $$ within individual specimen brains and "group-based global parameters" by calculating the means of the individual-based global parameters across the five brains. RESULTS The linear calibration model described the data well, though C $$ C $$ was not entirely independent of the underlying tissue and B 1 + $$ {B}_1^{+} $$ . Individual-based correction parameters and a group-based global correction parameter ( C = 1 . 2 $$ C=1.2 $$ ) led to visible, quantifiable reductions of B 1 + $$ {B}_1^{+} $$ -biases in high-resolution MTsat $$ \mathrm{MTsat} $$ maps. CONCLUSION The presented model and calibration approach effectively corrects for B 1 + $$ {B}_1^{+} $$ inhomogeneities in postmortem 7T data.
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Affiliation(s)
- Ilona Lipp
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Evgeniya Kirilina
- 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
| | - Kerrin J Pine
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Carsten Jäger
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.,Paul Flechsig Institute of Brain Research, Medical Faculty, Leipzig University, Leipzig, Germany
| | - Tobias Gräßle
- Epidemiology of Highly Pathogenic Microorganisms, Robert Koch-Institute, Berlin, Germany
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- 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.,Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany
| | - Gunther Helms
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.,Department of Clinical Sciences and Medical Radiation Physics, Lunds Universitet, Lund, Sweden
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19
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Bo T, Li J, Hu G, Zhang G, Wang W, Lv Q, Zhao S, Ma J, Qin M, Yao X, Wang M, Wang GZ, Wang Z. Brain-wide and cell-specific transcriptomic insights into MRI-derived cortical morphology in macaque monkeys. Nat Commun 2023; 14:1499. [PMID: 36932104 PMCID: PMC10023667 DOI: 10.1038/s41467-023-37246-w] [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: 08/08/2022] [Accepted: 03/06/2023] [Indexed: 03/19/2023] Open
Abstract
Integrative analyses of transcriptomic and neuroimaging data have generated a wealth of information about biological pathways underlying regional variability in imaging-derived brain phenotypes in humans, but rarely in nonhuman primates due to the lack of a comprehensive anatomically-defined atlas of brain transcriptomics. Here we generate complementary bulk RNA-sequencing dataset of 819 samples from 110 brain regions and single-nucleus RNA-sequencing dataset, and neuroimaging data from 162 cynomolgus macaques, to examine the link between brain-wide gene expression and regional variation in morphometry. We not only observe global/regional expression profiles of macaque brain comparable to human but unravel a dorsolateral-ventromedial gradient of gene assemblies within the primate frontal lobe. Furthermore, we identify a set of 971 protein-coding and 34 non-coding genes consistently associated with cortical thickness, specially enriched for neurons and oligodendrocytes. These data provide a unique resource to investigate nonhuman primate models of human diseases and probe cross-species evolutionary mechanisms.
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Affiliation(s)
- Tingting Bo
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Clinical Neuroscience Center, Ruijin Hospital Luwan Branch, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jie Li
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Ganlu Hu
- Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University, Shanghai, China
| | - Ge Zhang
- Department of Medical Imaging, Henan Provincial People's Hospital & the People's Hospital of Zhengzhou University, No. 7 Weiwu Road, Zhengzhou, Henan, China
| | - Wei Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Qian Lv
- School of Psychological and Cognitive Sciences; Beijing Key Laboratory of Behavior and Mental Health; IDG/McGovern Institute for Brain Research; Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Shaoling Zhao
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Junjie Ma
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Meng Qin
- College of Life Science and Technology, Beijing University of Chemical Technology, Beijing, China
| | - Xiaohui Yao
- Qingdao Innovation and Development Center, Harbin Engineering University, Qingdao, Shandong, China
- College of Intelligent Systems Science and Engineering, Harbin Engineering University, Harbin, Heilongjiang, China
| | - Meiyun Wang
- Department of Medical Imaging, Henan Provincial People's Hospital & the People's Hospital of Zhengzhou University, No. 7 Weiwu Road, Zhengzhou, Henan, China.
| | - Guang-Zhong Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.
| | - Zheng Wang
- School of Psychological and Cognitive Sciences; Beijing Key Laboratory of Behavior and Mental Health; IDG/McGovern Institute for Brain Research; Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China.
- School of Biomedical Engineering, Hainan University, Haikou, Hainan, China.
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20
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Haenelt D, Trampel R, Nasr S, Polimeni JR, Tootell RBH, Sereno MI, Pine KJ, Edwards LJ, Helbling S, Weiskopf N. High-resolution quantitative and functional MRI indicate lower myelination of thin and thick stripes in human secondary visual cortex. eLife 2023; 12:e78756. [PMID: 36888685 PMCID: PMC9995117 DOI: 10.7554/elife.78756] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 02/08/2023] [Indexed: 03/09/2023] Open
Abstract
The characterization of cortical myelination is essential for the study of structure-function relationships in the human brain. However, knowledge about cortical myelination is largely based on post-mortem histology, which generally renders direct comparison to function impossible. The repeating pattern of pale-thin-pale-thick stripes of cytochrome oxidase (CO) activity in the primate secondary visual cortex (V2) is a prominent columnar system, in which histology also indicates different myelination of thin/thick versus pale stripes. We used quantitative magnetic resonance imaging (qMRI) in conjunction with functional magnetic resonance imaging (fMRI) at ultra-high field strength (7 T) to localize and study myelination of stripes in four human participants at sub-millimeter resolution in vivo. Thin and thick stripes were functionally localized by exploiting their sensitivity to color and binocular disparity, respectively. Resulting functional activation maps showed robust stripe patterns in V2 which enabled further comparison of quantitative relaxation parameters between stripe types. Thereby, we found lower longitudinal relaxation rates (R1) of thin and thick stripes compared to surrounding gray matter in the order of 1-2%, indicating higher myelination of pale stripes. No consistent differences were found for effective transverse relaxation rates (R2*). The study demonstrates the feasibility to investigate structure-function relationships in living humans within one cortical area at the level of columnar systems using qMRI.
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Affiliation(s)
- Daniel Haenelt
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
- International Max Planck Research School on Neuroscience of Communication: Function, Structure, and PlasticityLeipzigGermany
| | - Robert Trampel
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Shahin Nasr
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General HospitalCharlestownUnited States
- Department of Radiology, Harvard Medical SchoolBostonUnited States
| | - Jonathan R Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General HospitalCharlestownUnited States
- Department of Radiology, Harvard Medical SchoolBostonUnited States
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Roger BH Tootell
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General HospitalCharlestownUnited States
- Department of Radiology, Harvard Medical SchoolBostonUnited States
| | - Martin I Sereno
- Department of Psychology, College of Sciences, San Diego State UniversitySan DiegoUnited States
| | - Kerrin J Pine
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Luke J Edwards
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Saskia Helbling
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
- Poeppel Lab, Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck SocietyFrankfurt am MainGermany
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
- Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig UniversityLeipzigGermany
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21
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Lee S, Shin HG, Kim M, Lee J. Depth-wise profiles of iron and myelin in the cortex and white matter using χ-separation: A preliminary study. Neuroimage 2023; 273:120058. [PMID: 36997135 DOI: 10.1016/j.neuroimage.2023.120058] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Revised: 03/26/2023] [Accepted: 03/27/2023] [Indexed: 03/30/2023] Open
Abstract
The in-vivo profiling of iron and myelin across cortical depths and underlying white matter has important implications for advancing knowledge about their roles in brain development and degeneration. Here, we utilize χ-separation, a recently-proposed advanced susceptibility mapping that creates positive (χpos) and negative (χneg) susceptibility maps, to generate the depth-wise profiles of χpos and χneg as surrogate biomarkers for iron and myelin, respectively. Two regional sulcal fundi of precentral and middle frontal areas are profiled and compared with findings from previous studies. The results show that the χpos profiles peak at superificial white matter (SWM), which is an area beneath cortical gray matter known to have the highest accumulation of iron within the cortex and white matter. On the other hand, the χneg profiles increase in SWM toward deeper white matter. These characteristics in the two profiles are in agreement with histological findings of iron and myelin. Furthermore, the χneg profiles report regional differences that agree with well-known distributions of myelin concentration. When the two profiles are compared with those of QSM and R2*, different shapes and peak locations are observed. This preliminary study offers an insight into one of the possible applications of χ-separation for exploring microstructural information of the human brain, as well as clinical applications in monitoring changes of iron and myelin in related diseases.
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22
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Polk SE, Kleemeyer MM, Bodammer NC, Misgeld C, Porst J, Wolfarth B, Kühn S, Lindenberger U, Düzel S, Wenger E. Aerobic exercise is associated with region-specific changes in volumetric, tensor-based, and fixel-based measures of white matter integrity in healthy older adults. NEUROIMAGE: REPORTS 2023. [DOI: 10.1016/j.ynirp.2022.100155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
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23
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Paquola C, Hong SJ. The Potential of Myelin-Sensitive Imaging: Redefining Spatiotemporal Patterns of Myeloarchitecture. Biol Psychiatry 2023; 93:442-454. [PMID: 36481065 DOI: 10.1016/j.biopsych.2022.08.031] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 08/12/2022] [Accepted: 08/30/2022] [Indexed: 02/07/2023]
Abstract
Recent advances in magnetic resonance imaging (MRI) have paved the way for approximation of myelin content in vivo. In this review, our main goal was to determine how to best capitalize on myelin-sensitive imaging. First, we briefly overview the theoretical and empirical basis for the myelin sensitivity of different MRI markers and, in doing so, highlight how multimodal imaging approaches are important for enhancing specificity to myelin. Then, we discuss recent studies that have probed the nonuniform distribution of myelin across cortical layers and along white matter tracts. These approaches, collectively known as myelin profiling, have provided detailed depictions of myeloarchitecture in both the postmortem and living human brain. Notably, MRI-based profiling studies have recently focused on investigating whether it can capture interindividual variability in myelin characteristics as well as trajectories across the lifespan. Finally, another line of recent evidence emphasizes the contribution of region-specific myelination to large-scale organization, demonstrating the impact of myelination on global brain networks. In conclusion, we suggest that combining well-validated MRI markers with profiling techniques holds strong potential to elucidate individual differences in myeloarchitecture, which has important implications for understanding brain function and disease.
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Affiliation(s)
- Casey Paquola
- Institute of Neuroscience and Medicine, Forschungszentrum Jülich, Jülich, Germany.
| | - Seok-Jun Hong
- Center for Neuroscience Imaging Research, Institute for Basic Science, Sungkyunkwan University, Suwon, South Korea; Center for the Developing Brain, Child Mind Institute, New York, New York; Department of Biomedical Engineering, Sungkyunkwan University, Suwon, South Korea
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24
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Schilling KG, Archer D, Yeh FC, Rheault F, Cai LY, Shafer A, Resnick SM, Hohman T, Jefferson A, Anderson AW, Kang H, Landman BA. Short superficial white matter and aging: a longitudinal multi-site study of 1293 subjects and 2711 sessions. AGING BRAIN 2023; 3:100067. [PMID: 36817413 PMCID: PMC9937516 DOI: 10.1016/j.nbas.2023.100067] [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] [Indexed: 01/18/2023] Open
Abstract
It is estimated that short association fibers running immediately beneath the cortex may make up as much as 60% of the total white matter volume. However, these have been understudied relative to the long-range association, projection, and commissural fibers of the brain. This is largely because of limitations of diffusion MRI fiber tractography, which is the primary methodology used to non-invasively study the white matter connections. Inspired by recent anatomical considerations and methodological improvements in superficial white matter (SWM) tractography, we aim to characterize changes in these fiber systems in cognitively normal aging, which provide insight into the biological foundation of age-related cognitive changes, and a better understanding of how age-related pathology differs from healthy aging. To do this, we used three large, longitudinal and cross-sectional datasets (N = 1293 subjects, 2711 sessions) to quantify microstructural features and length/volume features of several SWM systems. We find that axial, radial, and mean diffusivities show positive associations with age, while fractional anisotropy has negative associations with age in SWM throughout the entire brain. These associations were most pronounced in the frontal, temporal, and temporoparietal regions. Moreover, measures of SWM volume and length decrease with age in a heterogenous manner across the brain, with different rates of change in inter-gyri and intra-gyri SWM, and at slower rates than well-studied long-range white matter pathways. These features, and their variations with age, provide the background for characterizing normal aging, and, in combination with larger association pathways and gray matter microstructural features, may provide insight into fundamental mechanisms associated with aging and cognition.
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Affiliation(s)
- Kurt G Schilling
- Department of Radiology & Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN
| | - Derek Archer
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN, USA,Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA,Vanderbilt Genetics Institute, Vanderbilt University School of Medicine, Nashville, TN
| | - Fang-Cheng Yeh
- Department of Neurological Surgery, University of Pittsburgh Medical Center, Pittsburgh, PA, USA; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Francois Rheault
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, United States
| | - Leon Y Cai
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, United States
| | - Andrea Shafer
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States of America
| | - Susan M. Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States of America
| | - Timothy Hohman
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN, USA,Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA,Vanderbilt Genetics Institute, Vanderbilt University School of Medicine, Nashville, TN
| | - Angela Jefferson
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN, USA,Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA,Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Adam W Anderson
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States
| | - Hakmook Kang
- Department of Biostatistics, Vanderbilt University, Nashville, TN, United States
| | - Bennett A Landman
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, United States
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25
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Lin Q, Hu DW, Hao XH, Zhang G, Lin L. Effect of Hypoxia-Ischemia on the Expression of Iron-Related Proteins in Neonatal Rat Brains. Neural Plast 2023; 2023:4226139. [PMID: 37124874 PMCID: PMC10139812 DOI: 10.1155/2023/4226139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Revised: 02/06/2023] [Accepted: 04/03/2023] [Indexed: 05/02/2023] Open
Abstract
Hypoxic-ischemic white matter injury (WMI) pathogenesis in preterm infants is not well established, and iron-related proteins in the brain may play an important role in imbalanced iron metabolism. We aimed to investigate the iron-related protein changes in neonatal rats after hypoxia-ischemia (HI), clarify the role of iron-related proteins in hypoxic-ischemic WMI, and potentially provide a new target for the clinical treatment of hypoxic-ischemic WMI in preterm infants. We adopted a WMI animal model of bilateral common carotid artery electrocoagulation combined with hypoxia in neonatal 3-day-old Sprague-Dawley rats. We observed basic myelin protein (MBP) and iron-related protein expression in the brain (ferritin, transferrin receptor [TfR], and membrane iron transporter 1 [FPN1]) via Western blot and double immunofluorescence staining. The expression of MBP in the WMI group was significantly downregulated on postoperative days (PODs) 14, 28, and 56. Ferritin levels were significantly increased on PODs 3, 7, 14, and 28 and were most significant on POD 28, returning to the sham group level on POD 56. FPN1 levels were significantly increased on PODs 7, 28, and 56 and were still higher than those in the sham group on POD 56. TfR expression was significantly upregulated on PODs 1, 7, and 28 and returned to the sham group level on POD 56. Immunofluorescence staining showed that ferritin, TfR, and FPN1 were expressed in neurons, blood vessels, and oligodendrocytes in the cortex and corpus callosum on POD 28. Compared with the sham group, the immune-positive markers of three proteins in the WMI group were significantly increased. The expression of iron-related proteins in the brain (ferritin, FPN1, and TfR) showed spatiotemporal dynamic changes and may play an important role in hypoxic-ischemic WMI.
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Affiliation(s)
- Qing Lin
- Laboratory of Clinical Applied Anatomy, Department of Human Anatomy, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350122, China
- Key Laboratory of Brain Aging and Neurodegenerative Diseases of Fujian Province, Fuzhou 350122, China
| | - Ding-Wang Hu
- Laboratory of Clinical Applied Anatomy, Department of Human Anatomy, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350122, China
- Key Laboratory of Brain Aging and Neurodegenerative Diseases of Fujian Province, Fuzhou 350122, China
| | - Xin-Hui Hao
- Laboratory of Clinical Applied Anatomy, Department of Human Anatomy, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350122, China
- Key Laboratory of Brain Aging and Neurodegenerative Diseases of Fujian Province, Fuzhou 350122, China
| | - Geng Zhang
- Laboratory of Clinical Applied Anatomy, Department of Human Anatomy, School of Basic Medical Sciences, Fujian Medical University, Fuzhou 350122, China
- Key Laboratory of Brain Aging and Neurodegenerative Diseases of Fujian Province, Fuzhou 350122, China
| | - Ling Lin
- Public Technology Service Center, Fujian Medical University, Fuzhou 350122, China
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26
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Edwards LJ, McColgan P, Helbling S, Zarkali A, Vaculčiaková L, Pine KJ, Dick F, Weiskopf N. Quantitative MRI maps of human neocortex explored using cell type-specific gene expression analysis. Cereb Cortex 2022; 33:5704-5716. [PMID: 36520483 PMCID: PMC10152104 DOI: 10.1093/cercor/bhac453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 10/20/2022] [Accepted: 10/21/2022] [Indexed: 12/23/2022] Open
Abstract
Abstract
Quantitative magnetic resonance imaging (qMRI) allows extraction of reproducible and robust parameter maps. However, the connection to underlying biological substrates remains murky, especially in the complex, densely packed cortex. We investigated associations in human neocortex between qMRI parameters and neocortical cell types by comparing the spatial distribution of the qMRI parameters longitudinal relaxation rate (${R_{1}}$), effective transverse relaxation rate (${R_{2}}^{\ast }$), and magnetization transfer saturation (MTsat) to gene expression from the Allen Human Brain Atlas, then combining this with lists of genes enriched in specific cell types found in the human brain. As qMRI parameters are magnetic field strength-dependent, the analysis was performed on MRI data at 3T and 7T. All qMRI parameters significantly covaried with genes enriched in GABA- and glutamatergic neurons, i.e. they were associated with cytoarchitecture. The qMRI parameters also significantly covaried with the distribution of genes enriched in astrocytes (${R_{2}}^{\ast }$ at 3T, ${R_{1}}$ at 7T), endothelial cells (${R_{1}}$ and MTsat at 3T), microglia (${R_{1}}$ and MTsat at 3T, ${R_{1}}$ at 7T), and oligodendrocytes and oligodendrocyte precursor cells (${R_{1}}$ at 7T). These results advance the potential use of qMRI parameters as biomarkers for specific cell types.
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Affiliation(s)
- Luke J Edwards
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences , Leipzig, DE, Germany
| | - Peter McColgan
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences , Leipzig, DE, Germany
- Huntington’s Disease Centre, University College London , London, UK
| | - Saskia Helbling
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences , Leipzig, DE, Germany
- Poeppel Lab, Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society , Frankfurt am Main, DE, Germany
| | - Angeliki Zarkali
- Dementia Research Centre, University College London , London, UK
| | - Lenka Vaculčiaková
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences , Leipzig, DE, Germany
| | - Kerrin J Pine
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences , Leipzig, DE, Germany
| | - Fred Dick
- Birkbeck/UCL Centre for Neuroimaging (BUCNI) , London, UK
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences , Leipzig, DE, Germany
- Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University , Leipzig, DE, Germany
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27
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A macroscopic link between interhemispheric tract myelination and cortico-cortical interactions during action reprogramming. Nat Commun 2022; 13:4253. [PMID: 35869067 PMCID: PMC9307658 DOI: 10.1038/s41467-022-31687-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Accepted: 06/16/2022] [Indexed: 11/15/2022] Open
Abstract
Myelination has been increasingly implicated in the function and dysfunction of the adult human brain. Although it is known that axon myelination shapes axon physiology in animal models, it is unclear whether a similar principle applies in the living human brain, and at the level of whole axon bundles in white matter tracts. Here, we hypothesised that in humans, cortico-cortical interactions between two brain areas may be shaped by the amount of myelin in the white matter tract connecting them. As a test bed for this hypothesis, we use a well-defined interhemispheric premotor-to-motor circuit. We combined TMS-derived physiological measures of cortico-cortical interactions during action reprogramming with multimodal myelin markers (MT, R1, R2* and FA), in a large cohort of healthy subjects. We found that physiological metrics of premotor-to-motor interaction are broadly associated with multiple myelin markers, suggesting interindividual differences in tract myelination may play a role in motor network physiology. Moreover, we also demonstrate that myelination metrics link indirectly to action switching by influencing local primary motor cortex dynamics. These findings suggest that myelination levels in white matter tracts may influence millisecond-level cortico-cortical interactions during tasks. They also unveil a link between the physiology of the motor network and the myelination of tracts connecting its components, and provide a putative mechanism mediating the relationship between brain myelination and human behaviour. Myelination is a key regulator of brain function. Here the authors use MR-based myelin measures to examine if cortico-cortical interactions, as assessed by paired pulse transcranial magnetic stimulation, are affected by variations in myelin in the human brain.
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Mesoscopic in vivo human T 2* dataset acquired using quantitative MRI at 7 Tesla. Neuroimage 2022; 264:119733. [PMID: 36375782 DOI: 10.1016/j.neuroimage.2022.119733] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 10/15/2022] [Accepted: 11/03/2022] [Indexed: 11/13/2022] Open
Abstract
Mesoscopic (0.1-0.5 mm) interrogation of the living human brain is critical for advancing neuroscience and bridging the resolution gap with animal models. Despite the variety of MRI contrasts measured in recent years at the mesoscopic scale, in vivo quantitative imaging of T2* has not been performed. Here we provide a dataset containing empirical T2* measurements acquired at 0.35 × 0.35 × 0.35 mm3 voxel resolution using 7 Tesla MRI. To demonstrate unique features and high quality of this dataset, we generate flat map visualizations that reveal fine-scale cortical substructures such as layers and vessels, and we report quantitative depth-dependent T2* (as well as R2*) values in primary visual cortex and auditory cortex that are highly consistent across subjects. This dataset is freely available at https://doi.org/10.17605/OSF.IO/N5BJ7, and may prove useful for anatomical investigations of the human brain, as well as for improving our understanding of the basis of the T2*-weighted (f)MRI signal.
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29
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Brammerloh M, Kirilina E, Alkemade A, Bazin PL, Jantzen C, Jäger C, Herrler A, Pine KJ, Gowland PA, Morawski M, Forstmann BU, Weiskopf N. Swallow Tail Sign: Revisited. Radiology 2022; 305:674-677. [PMID: 35972361 DOI: 10.1148/radiol.212696] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Malte Brammerloh
- From the Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr 1a, 04103 Leipzig, Germany (M.B., E.K., P.L.B., C. Jantzen, C. Jäger, K.J.P., M.M., N.W.); International Max Planck Research School on Neuroscience of Communication: Function, Structure, and Plasticity, Leipzig, Germany (M.B.); Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany (M.B., N.W.); Center for Cognitive Neuroscience Berlin, Free University Berlin, Berlin, Germany (E.K.); Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, the Netherlands (A.A., P.L.B., B.U.F.); Department of Anatomy and Embryology, Maastricht University, Maastricht, the Netherlands (A.H.); Sir Peter Mansfield Imaging Centre, School of Physics & Astronomy, University of Nottingham, Nottingham, UK (P.A.G.); and Paul Flechsig Institute-Center of Neuropathology and Brain Research, Faculty of Medicine, Universität Leipzig, Leipzig, Germany
| | - Evgeniya Kirilina
- From the Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr 1a, 04103 Leipzig, Germany (M.B., E.K., P.L.B., C. Jantzen, C. Jäger, K.J.P., M.M., N.W.); International Max Planck Research School on Neuroscience of Communication: Function, Structure, and Plasticity, Leipzig, Germany (M.B.); Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany (M.B., N.W.); Center for Cognitive Neuroscience Berlin, Free University Berlin, Berlin, Germany (E.K.); Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, the Netherlands (A.A., P.L.B., B.U.F.); Department of Anatomy and Embryology, Maastricht University, Maastricht, the Netherlands (A.H.); Sir Peter Mansfield Imaging Centre, School of Physics & Astronomy, University of Nottingham, Nottingham, UK (P.A.G.); and Paul Flechsig Institute-Center of Neuropathology and Brain Research, Faculty of Medicine, Universität Leipzig, Leipzig, Germany
| | - Anneke Alkemade
- From the Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr 1a, 04103 Leipzig, Germany (M.B., E.K., P.L.B., C. Jantzen, C. Jäger, K.J.P., M.M., N.W.); International Max Planck Research School on Neuroscience of Communication: Function, Structure, and Plasticity, Leipzig, Germany (M.B.); Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany (M.B., N.W.); Center for Cognitive Neuroscience Berlin, Free University Berlin, Berlin, Germany (E.K.); Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, the Netherlands (A.A., P.L.B., B.U.F.); Department of Anatomy and Embryology, Maastricht University, Maastricht, the Netherlands (A.H.); Sir Peter Mansfield Imaging Centre, School of Physics & Astronomy, University of Nottingham, Nottingham, UK (P.A.G.); and Paul Flechsig Institute-Center of Neuropathology and Brain Research, Faculty of Medicine, Universität Leipzig, Leipzig, Germany
| | - Pierre-Louis Bazin
- From the Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr 1a, 04103 Leipzig, Germany (M.B., E.K., P.L.B., C. Jantzen, C. Jäger, K.J.P., M.M., N.W.); International Max Planck Research School on Neuroscience of Communication: Function, Structure, and Plasticity, Leipzig, Germany (M.B.); Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany (M.B., N.W.); Center for Cognitive Neuroscience Berlin, Free University Berlin, Berlin, Germany (E.K.); Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, the Netherlands (A.A., P.L.B., B.U.F.); Department of Anatomy and Embryology, Maastricht University, Maastricht, the Netherlands (A.H.); Sir Peter Mansfield Imaging Centre, School of Physics & Astronomy, University of Nottingham, Nottingham, UK (P.A.G.); and Paul Flechsig Institute-Center of Neuropathology and Brain Research, Faculty of Medicine, Universität Leipzig, Leipzig, Germany
| | - Caroline Jantzen
- From the Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr 1a, 04103 Leipzig, Germany (M.B., E.K., P.L.B., C. Jantzen, C. Jäger, K.J.P., M.M., N.W.); International Max Planck Research School on Neuroscience of Communication: Function, Structure, and Plasticity, Leipzig, Germany (M.B.); Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany (M.B., N.W.); Center for Cognitive Neuroscience Berlin, Free University Berlin, Berlin, Germany (E.K.); Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, the Netherlands (A.A., P.L.B., B.U.F.); Department of Anatomy and Embryology, Maastricht University, Maastricht, the Netherlands (A.H.); Sir Peter Mansfield Imaging Centre, School of Physics & Astronomy, University of Nottingham, Nottingham, UK (P.A.G.); and Paul Flechsig Institute-Center of Neuropathology and Brain Research, Faculty of Medicine, Universität Leipzig, Leipzig, Germany
| | - Carsten Jäger
- From the Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr 1a, 04103 Leipzig, Germany (M.B., E.K., P.L.B., C. Jantzen, C. Jäger, K.J.P., M.M., N.W.); International Max Planck Research School on Neuroscience of Communication: Function, Structure, and Plasticity, Leipzig, Germany (M.B.); Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany (M.B., N.W.); Center for Cognitive Neuroscience Berlin, Free University Berlin, Berlin, Germany (E.K.); Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, the Netherlands (A.A., P.L.B., B.U.F.); Department of Anatomy and Embryology, Maastricht University, Maastricht, the Netherlands (A.H.); Sir Peter Mansfield Imaging Centre, School of Physics & Astronomy, University of Nottingham, Nottingham, UK (P.A.G.); and Paul Flechsig Institute-Center of Neuropathology and Brain Research, Faculty of Medicine, Universität Leipzig, Leipzig, Germany
| | - Andreas Herrler
- From the Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr 1a, 04103 Leipzig, Germany (M.B., E.K., P.L.B., C. Jantzen, C. Jäger, K.J.P., M.M., N.W.); International Max Planck Research School on Neuroscience of Communication: Function, Structure, and Plasticity, Leipzig, Germany (M.B.); Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany (M.B., N.W.); Center for Cognitive Neuroscience Berlin, Free University Berlin, Berlin, Germany (E.K.); Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, the Netherlands (A.A., P.L.B., B.U.F.); Department of Anatomy and Embryology, Maastricht University, Maastricht, the Netherlands (A.H.); Sir Peter Mansfield Imaging Centre, School of Physics & Astronomy, University of Nottingham, Nottingham, UK (P.A.G.); and Paul Flechsig Institute-Center of Neuropathology and Brain Research, Faculty of Medicine, Universität Leipzig, Leipzig, Germany
| | - Kerrin J Pine
- From the Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr 1a, 04103 Leipzig, Germany (M.B., E.K., P.L.B., C. Jantzen, C. Jäger, K.J.P., M.M., N.W.); International Max Planck Research School on Neuroscience of Communication: Function, Structure, and Plasticity, Leipzig, Germany (M.B.); Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany (M.B., N.W.); Center for Cognitive Neuroscience Berlin, Free University Berlin, Berlin, Germany (E.K.); Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, the Netherlands (A.A., P.L.B., B.U.F.); Department of Anatomy and Embryology, Maastricht University, Maastricht, the Netherlands (A.H.); Sir Peter Mansfield Imaging Centre, School of Physics & Astronomy, University of Nottingham, Nottingham, UK (P.A.G.); and Paul Flechsig Institute-Center of Neuropathology and Brain Research, Faculty of Medicine, Universität Leipzig, Leipzig, Germany
| | - Penny A Gowland
- From the Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr 1a, 04103 Leipzig, Germany (M.B., E.K., P.L.B., C. Jantzen, C. Jäger, K.J.P., M.M., N.W.); International Max Planck Research School on Neuroscience of Communication: Function, Structure, and Plasticity, Leipzig, Germany (M.B.); Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany (M.B., N.W.); Center for Cognitive Neuroscience Berlin, Free University Berlin, Berlin, Germany (E.K.); Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, the Netherlands (A.A., P.L.B., B.U.F.); Department of Anatomy and Embryology, Maastricht University, Maastricht, the Netherlands (A.H.); Sir Peter Mansfield Imaging Centre, School of Physics & Astronomy, University of Nottingham, Nottingham, UK (P.A.G.); and Paul Flechsig Institute-Center of Neuropathology and Brain Research, Faculty of Medicine, Universität Leipzig, Leipzig, Germany
| | - Markus Morawski
- From the Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr 1a, 04103 Leipzig, Germany (M.B., E.K., P.L.B., C. Jantzen, C. Jäger, K.J.P., M.M., N.W.); International Max Planck Research School on Neuroscience of Communication: Function, Structure, and Plasticity, Leipzig, Germany (M.B.); Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany (M.B., N.W.); Center for Cognitive Neuroscience Berlin, Free University Berlin, Berlin, Germany (E.K.); Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, the Netherlands (A.A., P.L.B., B.U.F.); Department of Anatomy and Embryology, Maastricht University, Maastricht, the Netherlands (A.H.); Sir Peter Mansfield Imaging Centre, School of Physics & Astronomy, University of Nottingham, Nottingham, UK (P.A.G.); and Paul Flechsig Institute-Center of Neuropathology and Brain Research, Faculty of Medicine, Universität Leipzig, Leipzig, Germany
| | - Birte U Forstmann
- From the Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr 1a, 04103 Leipzig, Germany (M.B., E.K., P.L.B., C. Jantzen, C. Jäger, K.J.P., M.M., N.W.); International Max Planck Research School on Neuroscience of Communication: Function, Structure, and Plasticity, Leipzig, Germany (M.B.); Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany (M.B., N.W.); Center for Cognitive Neuroscience Berlin, Free University Berlin, Berlin, Germany (E.K.); Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, the Netherlands (A.A., P.L.B., B.U.F.); Department of Anatomy and Embryology, Maastricht University, Maastricht, the Netherlands (A.H.); Sir Peter Mansfield Imaging Centre, School of Physics & Astronomy, University of Nottingham, Nottingham, UK (P.A.G.); and Paul Flechsig Institute-Center of Neuropathology and Brain Research, Faculty of Medicine, Universität Leipzig, Leipzig, Germany
| | - Nikolaus Weiskopf
- From the Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstr 1a, 04103 Leipzig, Germany (M.B., E.K., P.L.B., C. Jantzen, C. Jäger, K.J.P., M.M., N.W.); International Max Planck Research School on Neuroscience of Communication: Function, Structure, and Plasticity, Leipzig, Germany (M.B.); Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany (M.B., N.W.); Center for Cognitive Neuroscience Berlin, Free University Berlin, Berlin, Germany (E.K.); Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, the Netherlands (A.A., P.L.B., B.U.F.); Department of Anatomy and Embryology, Maastricht University, Maastricht, the Netherlands (A.H.); Sir Peter Mansfield Imaging Centre, School of Physics & Astronomy, University of Nottingham, Nottingham, UK (P.A.G.); and Paul Flechsig Institute-Center of Neuropathology and Brain Research, Faculty of Medicine, Universität Leipzig, Leipzig, Germany
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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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Rahmanzadeh R, Galbusera R, Lu PJ, Bahn E, Weigel M, Barakovic M, Franz J, Nguyen TD, Spincemaille P, Schiavi S, Daducci A, La Rosa F, Absinta M, Sati P, Cuadra MB, Radue EW, Leppert D, Kuhle J, Kappos L, Brück W, Reich DS, Stadelmann C, Wang Y, Granziera C. A new advanced MRI biomarker for remyelinated lesions in Multiple Sclerosis. Ann Neurol 2022; 92:486-502. [PMID: 35713309 PMCID: PMC9527017 DOI: 10.1002/ana.26441] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 06/12/2022] [Accepted: 06/14/2022] [Indexed: 11/28/2022]
Abstract
Objectives Neuropathological studies have shown that multiple sclerosis (MS) lesions are heterogeneous in terms of myelin/axon damage and repair as well as iron content. However, it remains a challenge to identify specific chronic lesion types, especially remyelinated lesions, in vivo in patients with MS. Methods We performed 3 studies: (1) a cross‐sectional study in a prospective cohort of 115 patients with MS and 76 healthy controls, who underwent 3 T magnetic resonance imaging (MRI) for quantitative susceptibility mapping (QSM), myelin water fraction (MWF), and neurite density index (NDI) maps. White matter (WM) lesions in QSM were classified into 5 QSM lesion types (iso‐intense, hypo‐intense, hyperintense, lesions with hypo‐intense rims, and lesions with paramagnetic rim legions [PRLs]); (2) a longitudinal study of 40 patients with MS to study the evolution of lesions over 2 years; (3) a postmortem histopathology‐QSM validation study in 3 brains of patients with MS to assess the accuracy of QSM classification to identify neuropathological lesion types in 63 WM lesions. Results At baseline, hypo‐ and isointense lesions showed higher mean MWF and NDI values compared to other QSM lesion types (p < 0.0001). Further, at 2‐year follow‐up, hypo‐/iso‐intense lesions showed an increase in MWF. Postmortem analyses revealed that QSM highly accurately identifies (1) fully remyelinated areas as hypo‐/iso‐intense (sensitivity = 88.89% and specificity = 100%), (2) chronic inactive lesions as hyperintense (sensitivity = 71.43% and specificity = 92.00%), and (3) chronic active/smoldering lesions as PRLs (sensitivity = 92.86% and specificity = 86.36%). Interpretation These results provide the first evidence that it is possible to distinguish chronic MS lesions in a clinical setting, hereby supporting with new biomarkers to develop and assess remyelinating treatments. ANN NEUROL 2022;92:486–502
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Affiliation(s)
- Reza Rahmanzadeh
- Neurology Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Riccardo Galbusera
- Neurology Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Po-Jui Lu
- Neurology Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Erik Bahn
- Institute of Neuropathology, University Medical Center, Göttingen, Germany
| | - Matthias Weigel
- Neurology Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland.,Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
| | - Muhamed Barakovic
- Neurology Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Jonas Franz
- Institute of Neuropathology, University Medical Center, Göttingen, Germany.,Max Planck Institute for Experimental Medicine, Göttingen, Germany.,Campus Institute for Dynamics of Biological Networks, University of Göttingen, Göttingen, Germany
| | - Thanh D Nguyen
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Pascal Spincemaille
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Simona Schiavi
- Department of Computer Science, University of Verona, Verona, Italy
| | | | - Francesco La Rosa
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.,Medical Image Analysis Laboratory (MIAL), Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Martina Absinta
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,Institute of Experimental Neurology, Division of Neuroscience, Vita-Salute San Raffaele University and Hospital, Milan, Italy
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, NIH, 10 Center Drive MSC 1400, Building 10 Room 5C103, Bethesda, Maryland, USA.,Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Meritxell Bach Cuadra
- Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.,Medical Image Analysis Laboratory (MIAL), Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Ernst-Wilhelm Radue
- Neurology Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland
| | - David Leppert
- Neurology Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Jens Kuhle
- Neurology Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Ludwig Kappos
- Neurology Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Wolfgang Brück
- Institute of Neuropathology, University Medical Center, Göttingen, Germany
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, NIH, 10 Center Drive MSC 1400, Building 10 Room 5C103, Bethesda, Maryland, USA
| | | | - Yi Wang
- Department of Radiology, Weill Cornell Medical College, New York, New York, USA
| | - Cristina Granziera
- Neurology Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland.,Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
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Grotheer M, Kubota E, Grill-Spector K. Establishing the functional relevancy of white matter connections in the visual system and beyond. Brain Struct Funct 2022; 227:1347-1356. [PMID: 34846595 PMCID: PMC9046284 DOI: 10.1007/s00429-021-02423-4] [Citation(s) in RCA: 2] [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: 05/24/2021] [Accepted: 11/02/2021] [Indexed: 01/04/2023]
Abstract
For over a century, researchers have examined the functional relevancy of white matter bundles. Consequently, many large-scale bundles spanning several centimeters have been associated in their entirety with specific brain functions, such as language or attention. However, these coarse structural-functional relationships are at odds with modern understanding of the fine-grained functional organization of human cortex, such as the mosaic of category-selective regions in ventral temporal cortex. Here, we review a multimodal approach that combines fMRI to define functional regions of interest within individual's brains with dMRI tractography to identify the white matter bundles of the same individual. Combining these data allows to determine which subsets of streamlines within a white matter bundle connect to specific functional regions in each individual. That is, this approach identifies the functionally defined white matter sub-bundles of the brain. We argue that this approach not only enhances the accuracy of interpreting the functional relevancy of white matter bundles, but also enables segmentation of these large-scale bundles into meaningful functional units, which can then be linked to behavior with enhanced precision. Importantly, this approach has the potential for making new discoveries of the fine-grained functional relevancy of white matter connections in the visual system and the brain more broadly, akin to the flurry of research that has identified functional regions in cortex.
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Affiliation(s)
- Mareike Grotheer
- Department of Psychology, Philipps-Universität Marburg, 35032, Marburg, Germany.
- Center for Mind, Brain and Behavior-CMBB, Philipps-Universität Marburg and Justus-Liebig-Universität Giessen, 35037, Marburg, Germany.
| | - Emily Kubota
- Psychology Department, Stanford University, Stanford, CA, 94305, USA
| | - Kalanit Grill-Spector
- Psychology Department, Stanford University, Stanford, CA, 94305, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, 94305, USA
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33
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Alkemade A, Bazin PL, Balesar R, Pine K, Kirilina E, Möller HE, Trampel R, Kros JM, Keuken MC, Bleys RLAW, Swaab DF, Herrler A, Weiskopf N, Forstmann BU. A unified 3D map of microscopic architecture and MRI of the human brain. SCIENCE ADVANCES 2022; 8:eabj7892. [PMID: 35476433 PMCID: PMC9045605 DOI: 10.1126/sciadv.abj7892] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
We present the first three-dimensional (3D) concordance maps of cyto- and fiber architecture of the human brain, combining histology, immunohistochemistry, and 7-T quantitative magnetic resonance imaging (MRI), in two individual specimens. These 3D maps each integrate data from approximately 800 microscopy sections per brain, showing neuronal and glial cell bodies, nerve fibers, and interneuronal populations, as well as ultrahigh-field quantitative MRI, all coaligned at the 200-μm scale to the stacked blockface images obtained during sectioning. These unprecedented 3D multimodal datasets are shared without any restrictions and provide a unique resource for the joint study of cell and fiber architecture of the brain, detailed anatomical atlasing, or modeling of the microscopic underpinnings of MRI contrasts.
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Affiliation(s)
- Anneke Alkemade
- Integrative Model-Based Neuroscience Research Unit, University of Amsterdam, Amsterdam, Netherlands
- Corresponding author. (A.A.); (B.U.F.)
| | - Pierre-Louis Bazin
- Integrative Model-Based Neuroscience Research Unit, University of Amsterdam, Amsterdam, Netherlands
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Rawien Balesar
- Department of Neuropsychiatric disorders, Netherlands Institute for Neuroscience, an Institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, Netherlands
| | - Kerrin Pine
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Evgeniya Kirilina
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Neurocomputation and Neuroimaging Unit, Department of Psychology and Educational Science, Free University Berlin, Habelschwerdter Allee 45, Berlin 14195, Germany
| | - Harald E. Möller
- NMR Methods Development Group, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Robert Trampel
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Johan M. Kros
- Department of Pathology, Erasmus Medical Center, Rotterdam, Netherlands
| | - Max C. Keuken
- Integrative Model-Based Neuroscience Research Unit, University of Amsterdam, Amsterdam, Netherlands
| | - Ronald L. A. W. Bleys
- Department of Anatomy, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Dick F. Swaab
- Department of Neuropsychiatric disorders, Netherlands Institute for Neuroscience, an Institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, Netherlands
| | - Andreas Herrler
- Department of Anatomy and Embryology, Maastricht University, Maastricht, Netherlands
| | - 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, Linnéstraße 5, Leipzig 04103, Germany
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, 12 Queen Square, London WC1N 3AR, UK
| | - Birte U. Forstmann
- Integrative Model-Based Neuroscience Research Unit, University of Amsterdam, Amsterdam, Netherlands
- Corresponding author. (A.A.); (B.U.F.)
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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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35
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Yuan S, Liu M, Kim S, Yang J, Barkovich AJ, Xu D, Kim H. Cyto/myeloarchitecture of cortical gray matter and superficial white matter in early neurodevelopment: multimodal MRI study in preterm neonates. Cereb Cortex 2022; 33:357-373. [PMID: 35235643 PMCID: PMC9837610 DOI: 10.1093/cercor/bhac071] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Revised: 01/21/2022] [Accepted: 01/22/2022] [Indexed: 01/19/2023] Open
Abstract
The cerebral cortex undergoes rapid microstructural changes throughout the third trimester. Recently, there has been growing interest on imaging features that represent cyto/myeloarchitecture underlying intracortical myelination, cortical gray matter (GM), and its adjacent superficial whitematter (sWM). Using 92 magnetic resonance imaging scans from 78 preterm neonates, the current study used combined T1-weighted/T2-weighted (T1w/T2w) intensity ratio and diffusion tensor imaging (DTI) measurements, including fractional anisotropy (FA) and mean diffusivity (MD), to characterize the developing cyto/myeloarchitectural architecture. DTI metrics showed a linear trajectory: FA decreased in GM but increased in sWM with time; and MD decreased in both GM and sWM. Conversely, T1w/T2w measurements showed a distinctive parabolic trajectory, revealing additional cyto/myeloarchitectural signature inferred. Furthermore, the spatiotemporal courses were regionally heterogeneous: central, ventral, and temporal regions of GM and sWM exhibited faster T1w/T2w changes; anterior sWM areas exhibited faster FA increases; and central and cingulate areas in GM and sWM exhibited faster MD decreases. These results may explain cyto/myeloarchitectural processes, including dendritic arborization, synaptogenesis, glial proliferation, and radial glial cell organization and apoptosis. Finally, T1w/T2w values were significantly associated with 1-year language and cognitive outcome scores, while MD significantly decreased with intraventricular hemorrhage.
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Affiliation(s)
| | | | | | - Jingda Yang
- Department of Neurology, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Anthony James Barkovich
- Department of Radiology & Biomedical Imaging, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Duan Xu
- Department of Radiology & Biomedical Imaging, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Hosung Kim
- Corresponding author: 2025 Zonal Ave, Los Angeles, CA 90033, USA.
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36
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White matter myelination during early infancy is linked to spatial gradients and myelin content at birth. Nat Commun 2022; 13:997. [PMID: 35194018 PMCID: PMC8863985 DOI: 10.1038/s41467-022-28326-4] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2021] [Accepted: 01/12/2022] [Indexed: 12/25/2022] Open
Abstract
Development of myelin, a fatty sheath that insulates nerve fibers, is critical for brain function. Myelination during infancy has been studied with histology, but postmortem data cannot evaluate the longitudinal trajectory of white matter development. Here, we obtained longitudinal diffusion MRI and quantitative MRI measures of longitudinal relaxation rate (R1) of white matter in 0, 3 and 6 months-old human infants, and developed an automated method to identify white matter bundles and quantify their properties in each infant's brain. We find that R1 increases from newborns to 6-months-olds in all bundles. R1 development is nonuniform: there is faster development in white matter that is less mature in newborns, and development rate increases along inferior-to-superior as well as anterior-to-posterior spatial gradients. As R1 is linearly related to myelin fraction in white matter bundles, these findings open new avenues to elucidate typical and atypical white matter myelination in early infancy.
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Conrad J, Habs M, Ruehl RM, Boegle R, Ertl M, Kirsch V, Eren O, Becker-Bense S, Stephan T, Wollenweber F, Duering M, Dieterich M, Zu Eulenburg P. Reorganization of sensory networks after subcortical vestibular infarcts - A longitudinal symptom-related VBM study. Eur J Neurol 2022; 29:1514-1523. [PMID: 35098611 DOI: 10.1111/ene.15263] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 01/16/2022] [Indexed: 11/29/2022]
Abstract
BACKGROUND We aimed to delineate common principles of reorganization after infarcts of the subcortical vestibular circuitry related to the clinical symptomatology. Our hypothesis was that the recovery of specific symptoms is associated with changes in distinct regions within the core vestibular, somatosensory and visual cortical and subcortical networks. METHODS We used voxel- and surface-based morphometry to investigate structural reorganization of subcortical and cortical brain areas in 42 patients with a unilateral, subcortical infarct with vestibular and ocular motor deficits in the acute phase. The patients received structural neuroimaging and clinical monitoring twice (acute phase and after 6 months) to detect within-subject changes over time. RESULTS In patients with vestibular signs such as tilts of the subjective visual vertical (SVV) and ocular torsion in the acute phase, significant volumetric increases in the superficial white matter around the parieto-(retro-)insular vestibular cortex (PIVC) were found at follow-up. In patients with SVV tilts, spontaneous nystagmus and rotatory vertigo in the acute phase gray matter volume decreases were located in the cerebellum and the visual cortex bilaterally at follow-up. Patients with saccade pathology demonstrated volumetric decreases in cerebellar, thalamic and cortical centers for ocular motor control. CONCLUSIONS The findings support the role of the PIVC as the key hub for vestibular processing and reorganization. The volumetric decreases represent the reciprocal interaction of the vestibular, visual and ocular motor systems during self-location and egomotion detection. A modulation in vestibular and ocular motor as well as visual networks was induced independent of the vestibular lesion site.
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Affiliation(s)
- Julian Conrad
- Department of Neurology, University Hospital, LMU Munich, Germany.,German Center for Vertigo and Balance Disorders (DSGZ), University Hospital, LMU Munich, Germany
| | - Maximilian Habs
- Department of Neurology, University Hospital, LMU Munich, Germany.,German Center for Vertigo and Balance Disorders (DSGZ), University Hospital, LMU Munich, Germany
| | - Ria Maxine Ruehl
- Department of Neurology, University Hospital, LMU Munich, Germany.,German Center for Vertigo and Balance Disorders (DSGZ), University Hospital, LMU Munich, Germany
| | - Rainer Boegle
- Department of Neurology, University Hospital, LMU Munich, Germany.,Graduate School of Systemic Neurosciences - GSN-LMU, LMU Munich, Germany
| | - Matthias Ertl
- Department of Psychology, University of Bern, Switzerland
| | - Valerie Kirsch
- Department of Neurology, University Hospital, LMU Munich, Germany.,German Center for Vertigo and Balance Disorders (DSGZ), University Hospital, LMU Munich, Germany.,Graduate School of Systemic Neurosciences - GSN-LMU, LMU Munich, Germany
| | - Ozan Eren
- Department of Neurology, University Hospital, LMU Munich, Germany
| | - Sandra Becker-Bense
- German Center for Vertigo and Balance Disorders (DSGZ), University Hospital, LMU Munich, Germany
| | - Thomas Stephan
- Department of Neurology, University Hospital, LMU Munich, Germany
| | - Frank Wollenweber
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Germany.,Department of Neurology, Helios Dr. Horst Schmidt Kliniken, Wiesbaden, Germany
| | - Marco Duering
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Germany.,Medical Image Analysis Center (MIAC) and qbig, Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Marianne Dieterich
- Department of Neurology, University Hospital, LMU Munich, Germany.,German Center for Vertigo and Balance Disorders (DSGZ), University Hospital, LMU Munich, Germany.,Graduate School of Systemic Neurosciences - GSN-LMU, LMU Munich, Germany.,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Peter Zu Eulenburg
- German Center for Vertigo and Balance Disorders (DSGZ), University Hospital, LMU Munich, Germany.,Graduate School of Systemic Neurosciences - GSN-LMU, LMU Munich, Germany.,Institute for Neuroradiology LMU Munich, Germany
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38
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Buyukturkoglu K, Vergara C, Fuentealba V, Tozlu C, Dahan JB, Carroll BE, Kuceyeski A, Riley CS, Sumowski JF, Guevara Oliva C, Sitaram R, Guevara P, Leavitt VM. Machine learning to investigate superficial white matter integrity in early multiple sclerosis. J Neuroimaging 2022; 32:36-47. [PMID: 34532924 PMCID: PMC8752496 DOI: 10.1111/jon.12934] [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: 05/29/2021] [Revised: 09/01/2021] [Accepted: 09/03/2021] [Indexed: 01/03/2023] Open
Abstract
BACKGROUND AND PURPOSE This study aims todetermine the sensitivity of superficial white matter (SWM) integrity as a metric to distinguish early multiple sclerosis (MS) patients from healthy controls (HC). METHODS Fractional anisotropy and mean diffusivity (MD) values from SWM bundles across the cortex and major deep white matter (DWM) tracts were extracted from 29 early MS patients and 31 age- and sex-matched HC. Thickness of 68 cortical regions and resting-state functional-connectivity (RSFC) among them were calculated. The distribution of structural and functional metrics between groups were compared using Wilcoxon rank-sum test. Utilizing a machine learning method (adaptive boosting), 6 models were built based on: 1-SWM, 2-DWM, 3-SWM and DWM, 4-cortical thickness, or 5-RSFC measures. In model 6, all features from previous models were incorporated. The models were trained with nested 5-folds cross-validation. Area under the receiver operating characteristic curve (AUCroc ) values were calculated to evaluate classification performance of each model. Permutation tests were used to compare the AUCroc values. RESULTS Patients had higher MD in SWM bundles including insula, inferior frontal, orbitofrontal, superior and medial temporal, and pre- and post-central cortices (p < .05). No group differences were found for any other MRI metric. The model incorporating SWM and DWM features provided the best classification (AUCroc = 0.75). The SWM model provided higher AUCroc (0.74), compared to DWM (0.63), cortical thickness (0.67), RSFC (0.63), and all-features (0.68) models (p < .001 for all). CONCLUSION Our results reveal a non-random pattern of SWM abnormalities at early stages of MS even before pronounced structural and functional alterations emerge.
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Affiliation(s)
- Korhan Buyukturkoglu
- Columbia University Irving Medical Center, Department of Neurology. New York, NY. USA
| | | | | | - Ceren Tozlu
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
| | - Jacob B. Dahan
- Columbia University Irving Medical Center, Department of Neurology. New York, NY. USA
| | - Britta E. Carroll
- Columbia University Irving Medical Center, Department of Neurology. New York, NY. USA
| | - Amy Kuceyeski
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
| | - Claire S. Riley
- Multiple Sclerosis Center, Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
| | - James F. Sumowski
- Corinne Goldsmith Dickinson Center for Multiple Sclerosis, Mount Sinai Hospital, New York, NY. USA
| | | | - Ranganatha Sitaram
- Diagnostic Imaging Department, St. Jude Children’s Research Hospital, Memphis TN. USA
| | | | - Victoria M. Leavitt
- Columbia University Irving Medical Center, Department of Neurology. New York, NY. USA
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Rusch H, Brammerloh M, Stieler J, Sonntag M, Mohammadi S, Weiskopf N, Arendt T, Kirilina E, Morawski M. Finding the best clearing approach - Towards 3D wide-scale multimodal imaging of aged human brain tissue. Neuroimage 2021; 247:118832. [PMID: 34929383 DOI: 10.1016/j.neuroimage.2021.118832] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Revised: 12/13/2021] [Accepted: 12/16/2021] [Indexed: 11/16/2022] Open
Abstract
The accessibility of new wide-scale multimodal imaging techniques led to numerous clearing techniques emerging over the last decade. However, clearing mesoscopic-sized blocks of aged human brain tissue remains an extremely challenging task. Homogenizing refractive indices and reducing light absorption and scattering are the foundation of tissue clearing. Due to its dense and highly myelinated nature, especially in white matter, the human brain poses particular challenges to clearing techniques. Here, we present a comparative study of seven tissue clearing approaches and their impact on aged human brain tissue blocks (> 5 mm). The goal was to identify the most practical and efficient method in regards to macroscopic transparency, brief clearing time, compatibility with immunohistochemical processing and wide-scale multimodal microscopic imaging. We successfully cleared 26 × 26 × 5 mm3-sized human brain samples with two hydrophilic and two hydrophobic clearing techniques. Optical properties as well as light and antibody penetration depths highly vary between these methods. In addition to finding the best clearing approach, we compared three microscopic imaging setups (the Zeiss Laser Scanning Microscope (LSM) 880 , the Miltenyi Biotec Ultramicroscope ll (UM ll) and the 3i Marianas LightSheet microscope) regarding optimal imaging of large-scale tissue samples. We demonstrate that combining the CLARITY technique (Clear Lipid-exchanged Acrylamide-hybridized Rigid Imaging compatible Tissue hYdrogel) with the Zeiss LSM 880 and combining the iDISCO technique (immunolabeling-enabled three-dimensional imaging of solvent-cleared organs) with the Miltenyi Biotec UM ll are the most practical and efficient approaches to sufficiently clear aged human brain tissue and generate 3D microscopic images. Our results point out challenges that arise from seven clearing and three imaging techniques applied to non-standardized tissue samples such as aged human brain tissue.
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Affiliation(s)
- Henriette Rusch
- Paul Flechsig Institute of Brain Research, Medical Faculty, University of Leipzig, Liebigstraße 19, Leipzig 04103, Germany
| | - Malte Brammerloh
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Science, Stephanstraße 1a, Leipzig 04103, Germany; Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, University of Leipzig, Linnéstraße 5, Leipzig 04103, Germany; International Max Planck Research School on Neuroscience of Communication: Function, Structure, and Plasticity, Stephanstraße 1a, Leipzig 04103, Germany
| | - Jens Stieler
- Paul Flechsig Institute of Brain Research, Medical Faculty, University of Leipzig, Liebigstraße 19, Leipzig 04103, Germany
| | - Mandy Sonntag
- Paul Flechsig Institute of Brain Research, Medical Faculty, University of Leipzig, Liebigstraße 19, Leipzig 04103, Germany
| | - Siawoosh Mohammadi
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Science, Stephanstraße 1a, Leipzig 04103, Germany; Institute of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Martinistraße 52, Hamburg 20246, Germany
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Science, Stephanstraße 1a, Leipzig 04103, Germany; Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, University of Leipzig, Linnéstraße 5, Leipzig 04103, Germany
| | - Thomas Arendt
- Paul Flechsig Institute of Brain Research, Medical Faculty, University of Leipzig, Liebigstraße 19, Leipzig 04103, Germany
| | - Evgeniya Kirilina
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Science, Stephanstraße 1a, Leipzig 04103, Germany; Center for Cognitive Neuroscience Berlin, Free University Berlin, Habelschwerdter Allee 45, Berlin 14195, Germany
| | - Markus Morawski
- Paul Flechsig Institute of Brain Research, Medical Faculty, University of Leipzig, Liebigstraße 19, Leipzig 04103, Germany; Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Science, Stephanstraße 1a, Leipzig 04103, Germany.
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40
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Blazquez Freches G, Haak KV, Beckmann CF, Mars RB. Connectivity gradients on tractography data: Pipeline and example applications. Hum Brain Mapp 2021; 42:5827-5845. [PMID: 34559432 PMCID: PMC8596970 DOI: 10.1002/hbm.25623] [Citation(s) in RCA: 3] [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: 11/16/2020] [Revised: 07/03/2021] [Accepted: 07/30/2021] [Indexed: 11/08/2022] Open
Abstract
Gray matter connectivity can be described in terms of its topographical organization, but the differential role of white matter connections underlying that organization is often unknown. In this study, we propose a method for unveiling principles of organization of both gray and white matter based on white matter connectivity as assessed using diffusion magnetic ressonance imaging (MRI) tractography with spectral embedding gradient mapping. A key feature of the proposed approach is its capacity to project the individual connectivity gradients it reveals back onto its input data in the form of projection images, allowing one to assess the contributions of specific white matter tracts to the observed gradients. We demonstrate the ability of our proposed pipeline to identify connectivity gradients in prefrontal and occipital gray matter. Finally, leveraging the use of tractography, we demonstrate that it is possible to observe gradients within the white matter bundles themselves. Together, the proposed framework presents a generalized way to assess both the topographical organization of structural brain connectivity and the anatomical features driving it.
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Affiliation(s)
- Guilherme Blazquez Freches
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical CenterNijmegenThe Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud UniversityNijmegenThe Netherlands
| | - Koen V. Haak
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical CenterNijmegenThe Netherlands
| | - Christian F. Beckmann
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical CenterNijmegenThe Netherlands
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nufeld Department of Clinical NeurosciencesJohn Radclife Hospital, University of OxfordOxfordUK
| | - Rogier B. Mars
- Donders Institute for Brain, Cognition and Behaviour, Radboud UniversityNijmegenThe Netherlands
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41
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Veale T, Malone IB, Poole T, Parker TD, Slattery CF, Paterson RW, Foulkes AJM, Thomas DL, Schott JM, Zhang H, Fox NC, Cash DM. Loss and dispersion of superficial white matter in Alzheimer's disease: a diffusion MRI study. Brain Commun 2021; 3:fcab272. [PMID: 34859218 PMCID: PMC8633427 DOI: 10.1093/braincomms/fcab272] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Revised: 09/24/2021] [Accepted: 10/18/2021] [Indexed: 11/22/2022] Open
Abstract
Pathological cerebral white matter changes in Alzheimer's disease have been shown using diffusion tensor imaging. Superficial white matter changes are relatively understudied despite their importance in cortico-cortical connections. Measuring superficial white matter degeneration using diffusion tensor imaging is challenging due to its complex organizational structure and proximity to the cortex. To overcome this, we investigated diffusion MRI changes in young-onset Alzheimer's disease using standard diffusion tensor imaging and Neurite Orientation Dispersion and Density Imaging to distinguish between disease-related changes that are degenerative (e.g. loss of myelinated fibres) and organizational (e.g. increased fibre dispersion). Twenty-nine young-onset Alzheimer's disease patients and 22 healthy controls had both single-shell and multi-shell diffusion MRI. We calculated fractional anisotropy, mean diffusivity, neurite density index, orientation dispersion index and tissue fraction (1-free water fraction). Diffusion metrics were sampled in 15 a priori regions of interest at four points along the cortical profile: cortical grey matter, grey/white boundary, superficial white matter (1 mm below grey/white boundary) and superficial/deeper white matter (2 mm below grey/white boundary). To estimate cross-sectional group differences, we used average marginal effects from linear mixed effect models of participants' diffusion metrics along the cortical profile. The superficial white matter of young-onset Alzheimer's disease individuals had lower neurite density index compared to controls in five regions (superior and inferior parietal, precuneus, entorhinal and parahippocampus) (all P < 0.05), and higher orientation dispersion index in three regions (fusiform, entorhinal and parahippocampus) (all P < 0.05). Young-onset Alzheimer's disease individuals had lower fractional anisotropy in the entorhinal and parahippocampus regions (both P < 0.05) and higher fractional anisotropy within the postcentral region (P < 0.05). Mean diffusivity was higher in the young-onset Alzheimer's disease group in the parahippocampal region (P < 0.05) and lower in the postcentral, precentral and superior temporal regions (all P < 0.05). In the overlying grey matter, disease-related changes were largely consistent with superficial white matter findings when using neurite density index and fractional anisotropy, but appeared at odds with orientation dispersion and mean diffusivity. Tissue fraction was significantly lower across all grey matter regions in young-onset Alzheimer's disease individuals (all P < 0.001) but group differences reduced in magnitude and coverage when moving towards the superficial white matter. These results show that microstructural changes occur within superficial white matter and along the cortical profile in individuals with young-onset Alzheimer's disease. Lower neurite density and higher orientation dispersion suggests underlying fibres undergo neurodegeneration and organizational changes, two effects previously indiscernible using standard diffusion tensor metrics in superficial white matter.
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Affiliation(s)
- Thomas Veale
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, University College London, London, UK
| | - Ian B Malone
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Teresa Poole
- Department of Medical Statistics, London School of Hygiene & Tropical Medicine, London, UK
| | - Thomas D Parker
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | - Catherine F Slattery
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Ross W Paterson
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, University College London, London, UK
| | - Alexander J M Foulkes
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - David L Thomas
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, UK
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, London, UK
| | - Jonathan M Schott
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Hui Zhang
- Department of Computer Science and Centre for Medical Image Computing, 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, University College London, London, UK
| | - David M Cash
- The Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, University College London, London, UK
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42
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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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43
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Viganò L, Howells H, Rossi M, Rabuffetti M, Puglisi G, Leonetti A, Bellacicca A, Conti Nibali M, Gay L, Sciortino T, Cerri G, Bello L, Fornia L. Stimulation of frontal pathways disrupts hand muscle control during object manipulation. Brain 2021; 145:1535-1550. [PMID: 34623420 PMCID: PMC9128819 DOI: 10.1093/brain/awab379] [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: 06/07/2021] [Revised: 08/20/2021] [Accepted: 09/15/2021] [Indexed: 11/13/2022] Open
Abstract
The activity of frontal motor areas during hand-object interaction is coordinated by dense communication along specific white matter pathways. This architecture allows the continuous shaping of voluntary motor output and, despite extensively investigated in non-human primate studies, remains poorly understood in humans. Disclosure of this system is crucial for predicting and treatment of motor deficits after brain lesions. For this purpose, we investigated the effect of direct electrical stimulation on white matter pathways within the frontal lobe on hand-object manipulation. This was tested in thirty-four patients (15 left hemisphere, mean age 42 years, 17 male, 15 with tractography) undergoing awake neurosurgery for frontal lobe tumour removal with the aid of the brain mapping technique. The stimulation outcome was quantified based on hand-muscle activity required by task execution. The white matter pathways responsive to stimulation with an interference on muscles were identified by means of probabilistic density estimation of stimulated sites, tract-based lesion-symptom (disconnectome) analysis and diffusion tractography on the single patient level. Finally, we assessed the effect of permanent tracts disconnection on motor outcome in the immediate postoperative period using a multivariate lesion-symptom mapping approach. The analysis showed that stimulation disrupted hand-muscle activity during task execution in 66 sites within the white matter below dorsal and ventral premotor regions. Two different EMG interference patterns associated with different structural architectures emerged: 1) an arrest pattern, characterised by complete impairment of muscle activity associated with an abrupt task interruption, occurred when stimulating a white matter area below the dorsal premotor region. Local mid-U-shaped fibres, superior fronto-striatal, corticospinal and dorsal fronto-parietal fibres intersected with this region. 2) a clumsy pattern, characterised by partial disruption of muscle activity associated with movement slowdown and/or uncoordinated finger movements, occurred when stimulating a white matter area below the ventral premotor region. Ventral fronto-parietal and inferior fronto-striatal tracts intersected with this region. Finally, only resections partially including the dorsal white matter region surrounding the supplementary motor area were associated with transient upper-limb deficit (p = 0.05; 5000 permutations). Overall, the results identify two distinct frontal white matter regions possibly mediating different aspects of hand-object interaction via distinct sets of structural connectivity. We suggest the dorsal region, associated with arrest pattern and post-operative immediate motor deficits, to be functionally proximal to motor output implementation, while the ventral region may be involved in sensorimotor integration required for task execution.
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Affiliation(s)
- Luca Viganò
- Neurosurgical Oncology Unit, Department of Oncology and Hemato-Oncology, Università degli Studi di Milano
| | - Henrietta Howells
- MoCA Laboratory, Department of Medical Biotechnology and Translational Medicine, Universita`degli Studi di Milano
| | - Marco Rossi
- Neurosurgical Oncology Unit, Department of Oncology and Hemato-Oncology, Università degli Studi di Milano
| | - Marco Rabuffetti
- Biomedical Technology Department, IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milano, Italy
| | - Guglielmo Puglisi
- Neurosurgical Oncology Unit, Department of Oncology and Hemato-Oncology, Università degli Studi di Milano.,MoCA Laboratory, Department of Medical Biotechnology and Translational Medicine, Universita`degli Studi di Milano
| | - Antonella Leonetti
- Neurosurgical Oncology Unit, Department of Oncology and Hemato-Oncology, Università degli Studi di Milano
| | - Andrea Bellacicca
- MoCA Laboratory, Department of Medical Biotechnology and Translational Medicine, Universita`degli Studi di Milano
| | - Marco Conti Nibali
- Neurosurgical Oncology Unit, Department of Oncology and Hemato-Oncology, Università degli Studi di Milano
| | - Lorenzo Gay
- Neurosurgical Oncology Unit, Department of Oncology and Hemato-Oncology, Università degli Studi di Milano
| | - Tommaso Sciortino
- Neurosurgical Oncology Unit, Department of Oncology and Hemato-Oncology, Università degli Studi di Milano
| | - Gabriella Cerri
- MoCA Laboratory, Department of Medical Biotechnology and Translational Medicine, Universita`degli Studi di Milano
| | - Lorenzo Bello
- Neurosurgical Oncology Unit, Department of Oncology and Hemato-Oncology, Università degli Studi di Milano
| | - Luca Fornia
- MoCA Laboratory, Department of Medical Biotechnology and Translational Medicine, Universita`degli Studi di Milano
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44
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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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45
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Feng R, Zhao J, Wang H, Yang B, Feng J, Shi Y, Zhang M, Liu C, Zhang Y, Zhuang J, Wei H. MoDL-QSM: Model-based deep learning for quantitative susceptibility mapping. Neuroimage 2021; 240:118376. [PMID: 34246768 DOI: 10.1016/j.neuroimage.2021.118376] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Revised: 07/02/2021] [Accepted: 07/07/2021] [Indexed: 11/25/2022] Open
Abstract
Quantitative susceptibility mapping (QSM) has demonstrated great potential in quantifying tissue susceptibility in various brain diseases. However, the intrinsic ill-posed inverse problem relating the tissue phase to the underlying susceptibility distribution affects the accuracy for quantifying tissue susceptibility. Recently, deep learning has shown promising results to improve accuracy by reducing the streaking artifacts. However, there exists a mismatch between the observed phase and the theoretical forward phase estimated by the susceptibility label. In this study, we proposed a model-based deep learning architecture that followed the STI (susceptibility tensor imaging) physical model, referred to as MoDL-QSM. Specifically, MoDL-QSM accounts for the relationship between STI-derived phase contrast induced by the susceptibility tensor terms (χ13, χ23 and χ33) and the acquired single-orientation phase. The convolutional neural networks are embedded into the physical model to learn a regularization term containing prior information. χ33 and phase induced by χ13 and χ23 terms were used as the labels for network training. Quantitative evaluation metrics were compared with recently developed deep learning QSM methods. The results showed that MoDL-QSM achieved superior performance, demonstrating its potential for future applications.
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Affiliation(s)
- Ruimin Feng
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Jiayi Zhao
- School of Psychology, Shanghai University of Sport, Shanghai, China
| | - He Wang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Baofeng Yang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Jie Feng
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Yuting Shi
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Ming Zhang
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Chunlei Liu
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA; Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA
| | - Yuyao Zhang
- School of Information and Science and Technology, ShanghaiTech University, Shanghai, China
| | - Jie Zhuang
- School of Psychology, Shanghai University of Sport, Shanghai, China
| | - Hongjiang Wei
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China; Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, China.
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46
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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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47
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Liu J, Beck ES, Filippini S, van Gelderen P, de Zwart JA, Norato G, Sati P, Al-Louzi O, Kolb H, Donadieu M, Morrison M, Duyn JH, Reich DS. Navigator-Guided Motion and B0 Correction of T2*-Weighted Magnetic Resonance Imaging Improves Multiple Sclerosis Cortical Lesion Detection. Invest Radiol 2021; 56:409-416. [PMID: 34086012 PMCID: PMC8269363 DOI: 10.1097/rli.0000000000000754] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
BACKGROUND Cortical lesions are common in multiple sclerosis (MS). T2*-weighted (T2*w) imaging at 7 T is relatively sensitive for cortical lesions, but quality is often compromised by motion and main magnetic field (B0) fluctuations. PURPOSE The aim of this study was to determine whether motion and B0 correction with a navigator-guided gradient-recalled echo sequence can improve cortical lesion detection in T2*w magnetic resonance imaging. MATERIALS AND METHODS In this prospective study, a gradient-recalled echo sequence incorporating a navigator allowing for motion and B0 field correction was applied to collect T2*w images at 7 T from adults with MS between August 2019 and March 2020. T2*-weighted images were acquired in 1 to 3 partially overlapping scans per individual and were reconstructed using global average B0 correction ("uncorrected") or motion correction and spatially linear B0 correction ("corrected"). Image quality rating and manual segmentation of cortical lesions were performed on uncorrected and corrected images. Lesions seen on a single scan were retrospectively evaluated on the complementary scan. The association of cortical lesions with clinical disability was assessed. Mixed models were used to determine the effect of correction on lesion detection as well as on the relationship between disability and lesion count. RESULTS A total of 22 T2*w scans were performed on 11 adults with MS (mean [SD] age, 49 [11] years; 8 women). Quality improved for 20 of 22 scans (91%) after correction. A total of 69 cortical lesions were identified on uncorrected images (median per scan, 2; range, 0-11) versus 148 on corrected images (median per scan, 4.5; range, 0-25; rate ratio [RR], 2.1; P < 0.0001). For low-quality uncorrected scans with moderate to severe motion artifact (18/22, 82%), there was an improvement in cortical lesion detection with correction (RR, 2.5; P < 0.0001), whereas there was no significant change in cortical lesion detection for high-quality scans (RR, 1.3; P = 0.43). CONCLUSIONS Navigator-guided motion and B0 correction substantially improves the overall image quality of T2*w magnetic resonance imaging at 7 T and increases its sensitivity for cortical lesions.
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Affiliation(s)
- Jiaen Liu
- Advanced MRI Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Erin S Beck
- Translational Neuroradiology Section, NINDS, NIH, Bethesda, MD, USA
| | - Stefano Filippini
- Translational Neuroradiology Section, NINDS, NIH, Bethesda, MD, USA
- Department of Neurosciences, Drug, and Child Health, University of Florence, Florence, Italy
| | - Peter van Gelderen
- Advanced MRI Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Jacco A de Zwart
- Advanced MRI Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Gina Norato
- Clinical Trials Unit, NINDS, NIH, Bethesda, MD, USA
| | - Pascal Sati
- Translational Neuroradiology Section, NINDS, NIH, Bethesda, MD, USA
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Omar Al-Louzi
- Translational Neuroradiology Section, NINDS, NIH, Bethesda, MD, USA
| | - Hadar Kolb
- Translational Neuroradiology Section, NINDS, NIH, Bethesda, MD, USA
| | - Maxime Donadieu
- Translational Neuroradiology Section, NINDS, NIH, Bethesda, MD, USA
| | - Mark Morrison
- Translational Neuroradiology Section, NINDS, NIH, Bethesda, MD, USA
| | - Jeff H Duyn
- Advanced MRI Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, USA
| | - Daniel S Reich
- Translational Neuroradiology Section, NINDS, NIH, Bethesda, MD, USA
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48
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Khattar N, Triebswetter C, Kiely M, Ferrucci L, Resnick SM, Spencer RG, Bouhrara M. Investigation of the association between cerebral iron content and myelin content in normative aging using quantitative magnetic resonance neuroimaging. Neuroimage 2021; 239:118267. [PMID: 34139358 PMCID: PMC8370037 DOI: 10.1016/j.neuroimage.2021.118267] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Revised: 06/10/2021] [Accepted: 06/11/2021] [Indexed: 12/24/2022] Open
Abstract
Myelin loss and iron accumulation are cardinal features of aging and various neurodegenerative diseases. Oligodendrocytes incorporate iron as a metabolic substrate for myelin synthesis and maintenance. An emerging hypothesis in Alzheimer’s disease research suggests that myelin breakdown releases substantial stores of iron that may accumulate, leading to further myelin breakdown and neurodegeneration. We assessed associations between iron content and myelin content in critical brain regions using quantitative magnetic resonance imaging (MRI) on a cohort of cognitively unimpaired adults ranging in age from 21 to 94 years. We measured whole-brain myelin water fraction (MWF), a surrogate of myelin content, using multicomponent relaxometry, and whole-brain iron content using susceptibility weighted imaging in all individuals. MWF was negatively associated with iron content in most brain regions evaluated indicating that lower myelin content corresponds to higher iron content. Moreover, iron content was significantly higher with advanced age in most structures, with men exhibiting a trend towards higher iron content as compared to women. Finally, relationship between MWF and age, in all brain regions investigated, suggests that brain myelination continues until middle age, followed by degeneration at older ages. This work establishes a foundation for further investigations of the etiology and sequelae of myelin breakdown and iron accumulation in neurodegeneration and may lead to new imaging markers for disease progression and treatment.
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Affiliation(s)
- Nikkita Khattar
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224 MD, United States
| | - Curtis Triebswetter
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224 MD, United States
| | - Matthew Kiely
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224 MD, United States
| | - Luigi Ferrucci
- Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, 21224 MD, United States
| | - Susan M Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, 21224 MD, United States
| | - Richard G Spencer
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224 MD, United States
| | - Mustapha Bouhrara
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224 MD, United States.
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49
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Distinct Functional and Structural Connectivity of the Human Hand-Knob Supported by Intraoperative Findings. J Neurosci 2021; 41:4223-4233. [PMID: 33827936 DOI: 10.1523/jneurosci.1574-20.2021] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2020] [Revised: 01/02/2021] [Accepted: 01/10/2021] [Indexed: 12/15/2022] Open
Abstract
Fine motor skills rely on the control of hand muscles exerted by a region of primary motor cortex (M1) that has been extensively investigated in monkeys. Although neuroimaging enables the exploration of this system also in humans, indirect measurements of brain activity prevent causal definitions of hand motor representations, which can be achieved using data obtained during brain mapping in tumor patients. High-frequency direct electrical stimulation delivered at rest (HF-DES-Rest) on the hand-knob region of the precentral gyrus has identified two sectors showing differences in cortical excitability. Using quantitative analysis of motor output elicited with HF DES-Rest, we characterized two sectors based on their excitability, higher in the posterior and lower in the anterior sector. We studied whether the different cortical excitability of these two regions reflected differences in functional connectivity (FC) and structural connectivity (SC). Using healthy adults from the Human Connectome Project (HCP), we computed FC and SC of the anterior and the posterior hand-knob sectors identified within a large cohort of patients. The comparison of FC of the two seeds showed that the anterior hand-knob, relative to the posterior hand-knob, showed stronger functional connections with a bilateral set of parietofrontal areas responsible for integrating perceptual and cognitive hand-related sensorimotor processes necessary for goal-related actions. This was reflected in different patterns of SC between the two sectors. Our results suggest that the human hand-knob is a functionally and structurally heterogeneous region organized along a motor-cognitive gradient.SIGNIFICANCE STATEMENT The capability to perform complex manipulative tasks is one of the major characteristics of primates and relies on the fine control of hand muscles exerted by a highly specialized region of the precentral gyrus, often termed the "hand-knob" sector. Using intraoperative brain mapping, we identify two hand-knob sectors (posterior and anterior) characterized by differences in cortical excitability. Based on resting-state functional connectivity (FC) and tractography in healthy subjects, we show that posterior and anterior hand-knob sectors differ in their functional connectivity (FC) and structural connectivity (SC) with frontoparietal regions. Thus, anteroposterior differences in cortical excitability are paralleled by differences in FC and SC that likely reflect a motor (posterior) to cognitive (anterior) organization of this cortical region.
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50
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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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