1
|
Zhang J, Wang Y, Shu Z, Ouyang Y, Zhang X, Wang H, Zhang L, Fang S, Ye X, Li J. Tracing volitional recovery in post-stroke akinetic mutism using longitudinal microstructure imaging: Insights from a single case study. Cortex 2024; 180:55-63. [PMID: 39369575 DOI: 10.1016/j.cortex.2024.09.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Revised: 06/23/2024] [Accepted: 09/06/2024] [Indexed: 10/08/2024]
Abstract
Lesions in the frontal-subcortical circuitry can lead to akinetic mutism (AM) characterized by diminished volition. However, the microstructural changes in the damaged network underlying its recovery remain unknown. Clinical examination and neuropsychological assessment were performed on a patient with post-stroke AM. Multimodal MRI scans were performed at baseline and follow-ups. We used diffusion MRI and biophysical models, specifically utilizing neurite orientation dispersion and density imaging for assessing gray matter microstructure, and fixel-based analysis for the evaluation of white matter. Longitudinal comparisons were performed between the patient and healthy controls. Pronounced recovery of volition was observed after dopamine agonist therapy combined with physical therapy. In addition to infarcts in the bilateral medial cortex, microstructure imaging detected reduced neurite density in extensive areas, specifically in temporal areas and subcortical nuclei, and decreased fiber density of white matter tracts (TFCE-corrected p < .05). Microstructural degeneration in the anterior cingulate cortex and cingulum was relatively persistent (Bonferroni-corrected p < .05). However, most tracts within the frontal-subcortical circuitry showed increased fiber density during the recovery stage. Microstructure of an extensive network may contribute to the disruption and recovery of volition. Fiber density within the frontal-subcortical circuitry could be a promising biomarker indicating volitional recovery.
Collapse
Affiliation(s)
- Jie Zhang
- Center for Rehabilitation Medicine, Rehabilitation and Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, China; Wellcome Center for Human Neuroimaging, Department of Imaging Neuroscience, Institute of Neurology, University College London, London, UK
| | - Yingqiao Wang
- Center for Rehabilitation Medicine, Rehabilitation and Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, China
| | - Zhenyu Shu
- Department of Radiology, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Yao Ouyang
- Center for Rehabilitation Medicine, Rehabilitation and Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, China
| | - Xingru Zhang
- Center for Rehabilitation Medicine, Rehabilitation and Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, China
| | - Huiqi Wang
- Center for Rehabilitation Medicine, Rehabilitation and Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, China
| | - Li Zhang
- Center for Rehabilitation Medicine, Rehabilitation and Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, China
| | - Shan Fang
- Center for Rehabilitation Medicine, Rehabilitation and Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, China
| | - Xiangming Ye
- Center for Rehabilitation Medicine, Rehabilitation and Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, China.
| | - Juebao Li
- Center for Rehabilitation Medicine, Rehabilitation and Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, China.
| |
Collapse
|
2
|
Solé-Guardia G, Luijten M, Janssen E, Visch R, Geenen B, Küsters B, Claassen JAHR, Litjens G, de Leeuw FE, Wiesmann M, Kiliaan AJ. Deep learning-based segmentation in MRI-(immuno)histological examination of myelin and axonal damage in normal-appearing white matter and white matter hyperintensities. Brain Pathol 2024:e13301. [PMID: 39175459 DOI: 10.1111/bpa.13301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2024] [Accepted: 07/17/2024] [Indexed: 08/24/2024] Open
Abstract
The major vascular cause of dementia is cerebral small vessel disease (SVD). Its diagnosis relies on imaging hallmarks, such as white matter hyperintensities (WMH). WMH present a heterogenous pathology, including myelin and axonal loss. Yet, these might be only the "tip of the iceberg." Imaging modalities imply that microstructural alterations underlie still normal-appearing white matter (NAWM), preceding the conversion to WMH. Unfortunately, direct pathological characterization of these microstructural alterations affecting myelinated axonal fibers in WMH, and especially NAWM, is still missing. Given that there are no treatments to significantly reduce WMH progression, it is important to extend our knowledge on pathological processes that might already be occurring within NAWM. Staining of myelin with Luxol Fast Blue, while valuable, fails to assess subtle alterations in white matter microstructure. Therefore, we aimed to quantify myelin surrounding axonal fibers and axonal- and microstructural damage in detail by combining (immuno)histochemistry with polarized light imaging (PLI). To study the extent (of early) microstructural damage from periventricular NAWM to the center of WMH, we refined current analysis techniques by using deep learning to define smaller segments of white matter, capturing increasing fluid-attenuated inversion recovery signal. Integration of (immuno)histochemistry and PLI with post-mortem imaging of the brains of individuals with hypertension and normotensive controls enables voxel-wise assessment of the pathology throughout periventricular WMH and NAWM. Myelin loss, axonal integrity, and white matter microstructural damage are not limited to WMH but already occur within NAWM. Notably, we found that axonal damage is higher in individuals with hypertension, particularly in NAWM. These findings highlight the added value of advanced segmentation techniques to visualize subtle changes occurring already in NAWM preceding WMH. By using quantitative MRI and advanced diffusion MRI, future studies may elucidate these very early mechanisms leading to neurodegeneration, which ultimately contribute to the conversion of NAWM to WMH.
Collapse
Affiliation(s)
- Gemma Solé-Guardia
- Department of Medical Imaging, Anatomy, Research Institute for Medical Innovation, Radboud University Medical Center, Donders Institute for Brain, Cognition & Behavior, Center for Medical Neuroscience, Preclinical Imaging Center PRIME, Radboud Alzheimer Center, Nijmegen, The Netherlands
| | - Matthijs Luijten
- Department of Medical Imaging, Anatomy, Research Institute for Medical Innovation, Radboud University Medical Center, Donders Institute for Brain, Cognition & Behavior, Center for Medical Neuroscience, Preclinical Imaging Center PRIME, Radboud Alzheimer Center, Nijmegen, The Netherlands
| | - Esther Janssen
- Department of Medical Imaging, Anatomy, Research Institute for Medical Innovation, Radboud University Medical Center, Donders Institute for Brain, Cognition & Behavior, Center for Medical Neuroscience, Preclinical Imaging Center PRIME, Radboud Alzheimer Center, Nijmegen, The Netherlands
| | - Ruben Visch
- Department of Medical Imaging, Anatomy, Research Institute for Medical Innovation, Radboud University Medical Center, Donders Institute for Brain, Cognition & Behavior, Center for Medical Neuroscience, Preclinical Imaging Center PRIME, Radboud Alzheimer Center, Nijmegen, The Netherlands
| | - Bram Geenen
- Department of Medical Imaging, Anatomy, Research Institute for Medical Innovation, Radboud University Medical Center, Donders Institute for Brain, Cognition & Behavior, Center for Medical Neuroscience, Preclinical Imaging Center PRIME, Radboud Alzheimer Center, Nijmegen, The Netherlands
| | - Benno Küsters
- Department of Pathology, Research Institute for Medical Innovation, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jurgen A H R Claassen
- Department of Geriatrics, Research Institute for Medical Innovation, Radboud University Medical Center, Donders Institute for Brain, Cognition & Behavior, Radboud Alzheimer Center, Nijmegen, The Netherlands
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
| | - Geert Litjens
- Department of Pathology, Research Institute for Medical Innovation, Radboud University Medical Center, Nijmegen, The Netherlands
- Computational Pathology Group, Research Institute for Medical Innovation, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Frank-Erik de Leeuw
- Department of Neurology, Research Institute for Medical Innovation, Radboud University Medical Center, Donders Institute for Brain, Cognition & Behavior, Center for Medical Neuroscience, Nijmegen, The Netherlands
| | - Maximilian Wiesmann
- Department of Medical Imaging, Anatomy, Research Institute for Medical Innovation, Radboud University Medical Center, Donders Institute for Brain, Cognition & Behavior, Center for Medical Neuroscience, Preclinical Imaging Center PRIME, Radboud Alzheimer Center, Nijmegen, The Netherlands
| | - Amanda J Kiliaan
- Department of Medical Imaging, Anatomy, Research Institute for Medical Innovation, Radboud University Medical Center, Donders Institute for Brain, Cognition & Behavior, Center for Medical Neuroscience, Preclinical Imaging Center PRIME, Radboud Alzheimer Center, Nijmegen, The Netherlands
| |
Collapse
|
3
|
Bautin P, Fortier MA, Sean M, Little G, Martel M, Descoteaux M, Léonard G, Tétreault P. What has brain diffusion magnetic resonance imaging taught us about chronic primary pain: a narrative review. Pain 2024:00006396-990000000-00689. [PMID: 39172945 DOI: 10.1097/j.pain.0000000000003345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2024] [Accepted: 06/13/2024] [Indexed: 08/24/2024]
Abstract
ABSTRACT Chronic pain is a pervasive and debilitating condition with increasing implications for public health, affecting millions of individuals worldwide. Despite its high prevalence, the underlying neural mechanisms and pathophysiology remain only partly understood. Since its introduction 35 years ago, brain diffusion magnetic resonance imaging (MRI) has emerged as a powerful tool to investigate changes in white matter microstructure and connectivity associated with chronic pain. This review synthesizes findings from 58 articles that constitute the current research landscape, covering methods and key discoveries. We discuss the evidence supporting the role of altered white matter microstructure and connectivity in chronic primary pain conditions, highlighting the importance of studying multiple chronic pain syndromes to identify common neurobiological pathways. We also explore the prospective clinical utility of diffusion MRI, such as its role in identifying diagnostic, prognostic, and therapeutic biomarkers. Furthermore, we address shortcomings and challenges associated with brain diffusion MRI in chronic primary pain studies, emphasizing the need for the harmonization of data acquisition and analysis methods. We conclude by highlighting emerging approaches and prospective avenues in the field that may provide new insights into the pathophysiology of chronic pain and potential new therapeutic targets. Because of the limited current body of research and unidentified targeted therapeutic strategies, we are forced to conclude that further research is required. However, we believe that brain diffusion MRI presents a promising opportunity for enhancing our understanding of chronic pain and improving clinical outcomes.
Collapse
Affiliation(s)
- Paul Bautin
- Department of Anesthesiology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC, Canada
- Centre de recherche du Centre hospitalier universitaire de Sherbrooke, Sherbrooke, QC, Canada
| | - Marc-Antoine Fortier
- Department of Anesthesiology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC, Canada
- Centre de recherche du Centre hospitalier universitaire de Sherbrooke, Sherbrooke, QC, Canada
| | - Monica Sean
- Department of Anesthesiology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC, Canada
- Centre de recherche du Centre hospitalier universitaire de Sherbrooke, Sherbrooke, QC, Canada
| | - Graham Little
- Sherbrooke Connectivity Imaging Lab (SCIL), Computer Science Department, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Marylie Martel
- Centre de recherche du Centre hospitalier universitaire de Sherbrooke, Sherbrooke, QC, Canada
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Lab (SCIL), Computer Science Department, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Guillaume Léonard
- School of Rehabilitation, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC, Canada
- Research Centre on Aging du Centre intégré universitaire de santé et de services sociaux de l'Estrie-Centre hospitalier universitaire de Sherbrooke, Sherbrooke, QC, Canada
| | - Pascal Tétreault
- Department of Anesthesiology, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC, Canada
- Centre de recherche du Centre hospitalier universitaire de Sherbrooke, Sherbrooke, QC, Canada
- Department of Medical Imaging and Radiation Sciences, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC, Canada
| |
Collapse
|
4
|
Yeh LH, Ivanov IE, Chandler T, Byrum JR, Chhun BB, Guo SM, Foltz C, Hashemi E, Perez-Bermejo JA, Wang H, Yu Y, Kazansky PG, Conklin BR, Han MH, Mehta SB. Permittivity tensor imaging: modular label-free imaging of 3D dry mass and 3D orientation at high resolution. Nat Methods 2024; 21:1257-1274. [PMID: 38890427 PMCID: PMC11239526 DOI: 10.1038/s41592-024-02291-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: 12/19/2020] [Accepted: 04/24/2024] [Indexed: 06/20/2024]
Abstract
The dry mass and the orientation of biomolecules can be imaged without a label by measuring their permittivity tensor (PT), which describes how biomolecules affect the phase and polarization of light. Three-dimensional (3D) imaging of PT has been challenging. We present a label-free computational microscopy technique, PT imaging (PTI), for the 3D measurement of PT. PTI encodes the invisible PT into images using oblique illumination, polarization-sensitive detection and volumetric sampling. PT is decoded from the data with a vectorial imaging model and a multi-channel inverse algorithm, assuming uniaxial symmetry in each voxel. We demonstrate high-resolution imaging of PT of isotropic beads, anisotropic glass targets, mouse brain tissue, infected cells and histology slides. PTI outperforms previous label-free imaging techniques such as vector tomography, ptychography and light-field imaging in resolving the 3D orientation and symmetry of organelles, cells and tissue. We provide open-source software and modular hardware to enable the adoption of the method.
Collapse
Affiliation(s)
- Li-Hao Yeh
- Chan Zuckerberg Biohub, San Francisco, CA, USA
- ASML, San Jose, CA, USA
| | | | | | - Janie R Byrum
- Chan Zuckerberg Biohub, San Francisco, CA, USA
- California's Stem Cell Agency, South San Francisco, CA, USA
| | - Bryant B Chhun
- Chan Zuckerberg Biohub, San Francisco, CA, USA
- Eikon Therapeutics, Hayward, CA, USA
| | - Syuan-Ming Guo
- Chan Zuckerberg Biohub, San Francisco, CA, USA
- Insitro, South San Francisco, CA, USA
| | - Cameron Foltz
- Chan Zuckerberg Biohub, San Francisco, CA, USA
- Quantinuum, Broomfield, CO, USA
| | | | - Juan A Perez-Bermejo
- Gladstone Institutes, San Francisco, CA, USA
- Genentech, South San Francisco, CA, USA
| | | | - Yanhao Yu
- University of Southampton, Southampton, UK
| | | | - Bruce R Conklin
- Gladstone Institutes, San Francisco, CA, USA
- University of California San Francisco, San Francisco, CA, USA
| | - May H Han
- Stanford University, Palo Alto, CA, USA
| | | |
Collapse
|
5
|
Bonaventura J, Morara K, Carlson R, Comrie C, Twer A, Hutchinson E, Sawyer TW. Evaluating backscattering polarized light imaging microstructural mapping capabilities through neural tissue and analogous phantom imaging. JOURNAL OF BIOMEDICAL OPTICS 2024; 29:052914. [PMID: 38077501 PMCID: PMC10704260 DOI: 10.1117/1.jbo.29.5.052914] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Revised: 10/01/2023] [Accepted: 11/06/2023] [Indexed: 12/18/2023]
Abstract
Significance Knowledge of fiber microstructure and orientation in the brain is critical for many applications. Polarized light imaging (PLI) has been shown to have potential for better understanding neural fiber microstructure and directionality due to the anisotropy in myelin sheaths surrounding nerve fibers of the brain. Continuing to advance backscattering based PLI systems could provide a valuable avenue for in vivo neural imaging. Aim To assess the potential of backscattering PLI systems, the ability to resolve crossing fibers, and the sensitivity to fiber inclination and curvature are considered across different imaging wavelengths. Approach Investigation of these areas of relative uncertainty is undergone through imaging potential phantoms alongside analogous regions of interest in fixed ferret brain samples with a five-wavelength backscattering Mueller matrix polarimeter. Results Promising phantoms are discovered for which the retardance, diattenuation and depolarization mappings are derived from the Mueller matrix and studied to assess the sensitivity of this polarimeter configuration to fiber orientations and tissue structures. Conclusions Rich avenues for future study include further classifying this polarimeter's sensitivity to fiber inclination and fiber direction to accurately produce microstructural maps of neural tissue.
Collapse
Affiliation(s)
- Justina Bonaventura
- University of Arizona, Wyant College of Optical Sciences, Tucson, Arizona, United States
| | - Kellys Morara
- University of Arizona, Department of Biomedical Engineering, Tucson, Arizona, United States
| | - Rhea Carlson
- University of Arizona, Department of Biomedical Engineering, Tucson, Arizona, United States
| | - Courtney Comrie
- University of Arizona, Department of Biomedical Engineering, Tucson, Arizona, United States
| | - AnneLeigh Twer
- University of Arizona, Department of Molecular and Cellular Biology, Tucson, Arizona, United States
| | - Elizabeth Hutchinson
- University of Arizona, Department of Biomedical Engineering, Tucson, Arizona, United States
| | - Travis W. Sawyer
- University of Arizona, Wyant College of Optical Sciences, Tucson, Arizona, United States
- University of Arizona, Department of Biomedical Engineering, Tucson, Arizona, United States
| |
Collapse
|
6
|
Mavrovounis G, Skouroliakou A, Kalatzis I, Stranjalis G, Kalamatianos T. Over 30 Years of DiI Use for Human Neuroanatomical Tract Tracing: A Scoping Review. Biomolecules 2024; 14:536. [PMID: 38785943 PMCID: PMC11117484 DOI: 10.3390/biom14050536] [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: 03/26/2024] [Revised: 04/16/2024] [Accepted: 04/17/2024] [Indexed: 05/25/2024] Open
Abstract
In the present study, we conducted a scoping review to provide an overview of the existing literature on the carbocyanine dye DiI, in human neuroanatomical tract tracing. The PubMed, Scopus, and Web of Science databases were systematically searched. We identified 61 studies published during the last three decades. While studies incorporated specimens across human life from the embryonic stage onwards, the majority of studies focused on adult human tissue. Studies that utilized peripheral nervous system (PNS) tissue were a minority, with the majority of studies focusing on the central nervous system (CNS). The most common topic of interest in previous tract tracing investigations was the connectivity of the visual pathway. DiI crystals were more commonly applied. Nevertheless, several studies utilized DiI in a paste or dissolved form. The maximum tracing distance and tracing speed achieved was, respectively, 70 mm and 1 mm/h. We identified studies that focused on optimizing tracing efficacy by varying parameters such as fixation, incubation temperature, dye re-application, or the application of electric fields. Additional studies aimed at broadening the scope of DiI use by assessing the utility of archival tissue and compatibility of tissue clearing in DiI applications. A combination of DiI tracing and immunohistochemistry in double-labeling studies have been shown to provide the means for assessing connectivity of phenotypically defined human CNS and PNS neuronal populations.
Collapse
Affiliation(s)
- Georgios Mavrovounis
- Department of Neurosurgery, School of Medicine, National and Kapodistrian University of Athens, Evangelismos Hospital, 10676 Athens, Greece; (G.M.); (G.S.)
| | - Aikaterini Skouroliakou
- Department of Biomedical Engineering, The University of West Attica, 12243 Athens, Greece; (A.S.); (I.K.)
| | - Ioannis Kalatzis
- Department of Biomedical Engineering, The University of West Attica, 12243 Athens, Greece; (A.S.); (I.K.)
| | - George Stranjalis
- Department of Neurosurgery, School of Medicine, National and Kapodistrian University of Athens, Evangelismos Hospital, 10676 Athens, Greece; (G.M.); (G.S.)
- Hellenic Centre for Neurosurgery Research “Professor Petros S. Kokkalis”, 10675 Athens, Greece
| | - Theodosis Kalamatianos
- Department of Neurosurgery, School of Medicine, National and Kapodistrian University of Athens, Evangelismos Hospital, 10676 Athens, Greece; (G.M.); (G.S.)
- Hellenic Centre for Neurosurgery Research “Professor Petros S. Kokkalis”, 10675 Athens, Greece
- Clinical and Experimental Neuroscience Research Group, Department of Neurosurgery, National and Kapodistrian University of Athens, 10675 Athens, Greece
| |
Collapse
|
7
|
Cerdán Cerdá A, Toschi N, Treaba CA, Barletta V, Herranz E, Mehndiratta A, Gomez-Sanchez JA, Mainero C, De Santis S. A translational MRI approach to validate acute axonal damage detection as an early event in multiple sclerosis. eLife 2024; 13:e79169. [PMID: 38192199 PMCID: PMC10776086 DOI: 10.7554/elife.79169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Accepted: 12/05/2023] [Indexed: 01/10/2024] Open
Abstract
Axonal degeneration is a central pathological feature of multiple sclerosis and is closely associated with irreversible clinical disability. Current noninvasive methods to detect axonal damage in vivo are limited in their specificity and clinical applicability, and by the lack of proper validation. We aimed to validate an MRI framework based on multicompartment modeling of the diffusion signal (AxCaliber) in rats in the presence of axonal pathology, achieved through injection of a neurotoxin damaging the neuronal terminal of axons. We then applied the same MRI protocol to map axonal integrity in the brain of multiple sclerosis relapsing-remitting patients and age-matched healthy controls. AxCaliber is sensitive to acute axonal damage in rats, as demonstrated by a significant increase in the mean axonal caliber along the targeted tract, which correlated with neurofilament staining. Electron microscopy confirmed that increased mean axonal diameter is associated with acute axonal pathology. In humans with multiple sclerosis, we uncovered a diffuse increase in mean axonal caliber in most areas of the normal-appearing white matter, preferentially affecting patients with short disease duration. Our results demonstrate that MRI-based axonal diameter mapping is a sensitive and specific imaging biomarker that links noninvasive imaging contrasts with the underlying biological substrate, uncovering generalized axonal damage in multiple sclerosis as an early event.
Collapse
Affiliation(s)
| | - Nicola Toschi
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical SchoolBostonUnited States
- Department of Biomedicine and Prevention, University of Rome Tor VergataRomeItaly
| | - Constantina A Treaba
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical SchoolBostonUnited States
| | - Valeria Barletta
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical SchoolBostonUnited States
| | - Elena Herranz
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical SchoolBostonUnited States
| | - Ambica Mehndiratta
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical SchoolBostonUnited States
| | - Jose A Gomez-Sanchez
- Instituto de Neurociencias de Alicante, CSIC-UMHSan Juan de AlicanteSpain
- Instituto de Investigación Sanitaria y Biomédica de Alicante (ISABIAL)AlicanteSpain
- Millennium Nucleus for the Study of Pain (MiNuSPain)SantiagoChile
| | - Caterina Mainero
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical SchoolBostonUnited States
| | - Silvia De Santis
- Instituto de Neurociencias de Alicante, CSIC-UMHSan Juan de AlicanteSpain
| |
Collapse
|
8
|
Lehmann N, Aye N, Kaufmann J, Heinze HJ, Düzel E, Ziegler G, Taubert M. Changes in Cortical Microstructure of the Human Brain Resulting from Long-Term Motor Learning. J Neurosci 2023; 43:8637-8648. [PMID: 37875377 PMCID: PMC10727185 DOI: 10.1523/jneurosci.0537-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 08/08/2023] [Accepted: 09/04/2023] [Indexed: 10/26/2023] Open
Abstract
The mechanisms subserving motor skill acquisition and learning in the intact human brain are not fully understood. Previous studies in animals have demonstrated a causal relationship between motor learning and structural rearrangements of synaptic connections, raising the question of whether neurite-specific changes are also observable in humans. Here, we use advanced diffusion magnetic resonance imaging (MRI), sensitive to dendritic and axonal processes, to investigate neuroplasticity in response to long-term motor learning. We recruited healthy male and female human participants (age range 19-29) who learned a challenging dynamic balancing task (DBT) over four consecutive weeks. Diffusion MRI signals were fitted using Neurite Orientation Dispersion and Density Imaging (NODDI), a theory-driven biophysical model of diffusion, yielding measures of tissue volume, neurite density and the organizational complexity of neurites. While NODDI indices were unchanged and reliable during the control period, neurite orientation dispersion increased significantly during the learning period mainly in primary sensorimotor, prefrontal, premotor, supplementary, and cingulate motor areas. Importantly, reorganization of cortical microstructure during the learning phase predicted concurrent behavioral changes, whereas there was no relationship between microstructural changes during the control phase and learning. Changes in neurite complexity were independent of alterations in tissue density, cortical thickness, and intracortical myelin. Our results are in line with the notion that structural modulation of neurites is a key mechanism supporting complex motor learning in humans.SIGNIFICANCE STATEMENT The structural correlates of motor learning in the human brain are not fully understood. Results from animal studies suggest that synaptic remodeling (e.g., reorganization of dendritic spines) in sensorimotor-related brain areas is a crucial mechanism for the formation of motor memory. Using state-of-the-art diffusion magnetic resonance imaging (MRI), we found a behaviorally relevant increase in the organizational complexity of neocortical microstructure, mainly in primary sensorimotor, prefrontal, premotor, supplementary, and cingulate motor regions, following training of a challenging dynamic balancing task (DBT). Follow-up analyses suggested structural modulation of synapses as a plausible mechanism driving this increase, while colocalized changes in cortical thickness, tissue density, and intracortical myelin could not be detected. These results advance our knowledge about the neurobiological basis of motor learning in humans.
Collapse
Affiliation(s)
- Nico Lehmann
- Faculty of Human Sciences, Institute III, Department of Sport Science, Otto von Guericke University, Magdeburg 39104, Germany
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig 04103, Germany
| | - Norman Aye
- Faculty of Human Sciences, Institute III, Department of Sport Science, Otto von Guericke University, Magdeburg 39104, Germany
| | - Jörn Kaufmann
- Department of Neurology, Otto von Guericke University, Magdeburg 39120, Germany
| | - Hans-Jochen Heinze
- Department of Neurology, Otto von Guericke University, Magdeburg 39120, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg 39120, Germany
- Center for Behavioral and Brain Science (CBBS), Otto von Guericke University, Magdeburg 39106, Germany
- Leibniz-Institute for Neurobiology (LIN), Magdeburg 39118, Germany
| | - Emrah Düzel
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg 39120, Germany
- Center for Behavioral and Brain Science (CBBS), Otto von Guericke University, Magdeburg 39106, Germany
- Institute of Cognitive Neurology and Dementia Research, Otto von Guericke University, Magdeburg 39120, Germany
- Institute of Cognitive Neuroscience, University College London, London WC1N 3AZ, United Kingdom
| | - Gabriel Ziegler
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg 39120, Germany
- Institute of Cognitive Neurology and Dementia Research, Otto von Guericke University, Magdeburg 39120, Germany
| | - Marco Taubert
- Faculty of Human Sciences, Institute III, Department of Sport Science, Otto von Guericke University, Magdeburg 39104, Germany
- Center for Behavioral and Brain Science (CBBS), Otto von Guericke University, Magdeburg 39106, Germany
| |
Collapse
|
9
|
Zhang J, Li L, Ji R, Shang D, Wen X, Hu J, Wang Y, Wu D, Zhang L, He F, Ye X, Luo B. NODDI Identifies Cognitive Associations with In Vivo Microstructural Changes in Remote Cortical Regions and Thalamocortical Pathways in Thalamic Stroke. Transl Stroke Res 2023:10.1007/s12975-023-01221-w. [PMID: 38049671 DOI: 10.1007/s12975-023-01221-w] [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: 10/26/2023] [Revised: 11/23/2023] [Accepted: 11/27/2023] [Indexed: 12/06/2023]
Abstract
The roles of cerebral structures distal to isolated thalamic infarcts in cognitive deficits remain unclear. We aimed to identify the in vivo microstructural characteristics of remote gray matter (GM) and thalamic pathways and elucidate their roles across cognitive domains. Patients with isolated ischemic thalamic stroke and healthy controls underwent neuropsychological assessment and magnetic resonance imaging. Neurite orientation dispersion and density imaging (NODDI) was modeled to derive the intracellular volume fraction (VFic) and orientation dispersion index. Fiber density (FD) was determined by constrained spherical deconvolution, and tensor-derived fractional anisotropy (FA) was calculated. Voxel-wise GM analysis and thalamic pathway tractography were performed. Twenty-six patients and 26 healthy controls were included. Patients exhibited reduced VFic in remote GM regions, including ipsilesional insular and temporal subregions. The microstructural metrics VFic, FD, and FA within ipsilesional thalamic pathways decreased (false discovery rate [FDR]-p < 0.05). Noteworthy associations emerged as VFic within insular cortices (ρ = -0.791 to -0.630; FDR-p < 0.05) and FD in tracts connecting the thalamus and insula (ρ = 0.830 to 0.971; FDR-p < 0.001) were closely associated with executive function. The VFic in Brodmann area 52 (ρ = -0.839; FDR-p = 0.005) and FA within its thalamic pathway (ρ = -0.799; FDR-p = 0.003) correlated with total auditory memory scores. In conclusion, NODDI revealed neurite loss in remote normal-appearing GM regions and ipsilesional thalamic pathways in thalamic stroke. Reduced cortical dendritic density and axonal density of thalamocortical tracts in specific subregions were associated with improved cognitive functions. Subacute microstructural alterations beyond focal thalamic infarcts might reflect beneficial remodeling indicating post-stroke plasticity.
Collapse
Affiliation(s)
- Jie Zhang
- Department of Neurology, Brain Medical Center, The First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, 310003, Hangzhou, China
- Center for Rehabilitation Medicine, Rehabilitation and Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, 310014, China
| | - Lingling Li
- Department of Neurology, Dongyang People's Hospital, Wenzhou Medical University, Dongyang, 322109, China
| | - Renjie Ji
- Department of Neurology, Brain Medical Center, The First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, 310003, Hangzhou, China
| | - Desheng Shang
- Department of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China
| | - Xinrui Wen
- Department of Neurology, Brain Medical Center, The First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, 310003, Hangzhou, China
| | - Jun Hu
- Department of Neurology, Brain Medical Center, The First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, 310003, Hangzhou, China
| | - Yingqiao Wang
- Center for Rehabilitation Medicine, Rehabilitation and Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, 310014, China
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, 310027, China
| | - Li Zhang
- Department of Neurology, Brain Medical Center, The First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, 310003, Hangzhou, China
- Center for Rehabilitation Medicine, Rehabilitation and Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, 310014, China
| | - Fangping He
- Department of Neurology, Brain Medical Center, The First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, 310003, Hangzhou, China
| | - Xiangming Ye
- Center for Rehabilitation Medicine, Rehabilitation and Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, 310014, China
| | - Benyan Luo
- Department of Neurology, Brain Medical Center, The First Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang, 310003, Hangzhou, China.
- MOE Frontier Science Center for Brain Science & Brain-Machine Integration, Zhejiang University, Hangzhou, 310003, China.
| |
Collapse
|
10
|
Vinh To X, Kurniawan ND, Cumming P, Nasrallah FA. A cross-comparative analysis of in vivo versus ex vivo MRI indices in a mouse model of concussion. Brain Res 2023; 1820:148562. [PMID: 37673379 DOI: 10.1016/j.brainres.2023.148562] [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: 04/19/2023] [Revised: 08/01/2023] [Accepted: 08/31/2023] [Indexed: 09/08/2023]
Abstract
BACKGROUND We present a cross-sectional, case-matched, and pair-wise comparison of structural magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), and neurite orientation dispersion and density imaging (NODDI) measures in vivo and ex vivo in a mouse model of concussion, thus aiming to establish the concordance of structural and diffusion imaging findings in living brain and after fixation. METHODS We allocated 28 male mice aged 3-4 months to sham injury and concussion (CON) groups. CON mice had received a single concussive impact on day 0 and underwent MRI at day 2 (n = 9) or 7 (n = 10) post-impact, and sham control mice likewise underwent imaging at day 2 (n = 5) or 7 (n = 4). Immediately after the final scanning, we collected the perfusion-fixed brains, which were stored for imaging ex vivo 6-12 months later. We then compared the structural imaging, DTI, and NODDI results between different methods. RESULTS In vivo to ex vivo structural and DTI/NODDI findings were in notably poor agreement regarding the effects of concussion on structural integrity of the brain. COMPARISON WITH EXISTING METHODS ex vivo imaging was frequently done to study the effects of diseases and treatments, but our results showed that ex vivo and in vivo imaging can detect completely opposite and contradictory results. This is also the first study that compares in vivo and ex vivo NODDI. CONCLUSION Our findings call for caution in extrapolating translational capabilities obtained ex vivo to physiological measurements in vivo. The divergent findings may reflect fixation artefacts and the contribution of the glymphatic system changes.
Collapse
Affiliation(s)
- Xuan Vinh To
- The Queensland Brain Institute, The University of Queensland, Australia
| | | | - Paul Cumming
- Department of Nuclear Medicine, Bern University Hospital, Bern, Switzerland; School of Psychology and Counselling, Queensland University of Technology, Brisbane, Australia
| | - Fatima A Nasrallah
- The Queensland Brain Institute, The University of Queensland, Australia; Centre for Advanced Imaging, The University of Queensland, Australia.
| |
Collapse
|
11
|
Faigle W, Piccirelli M, Hortobágyi T, Frontzek K, Cannon AE, Zürrer WE, Granberg T, Kulcsar Z, Ludersdorfer T, Frauenknecht KBM, Reimann R, Ineichen BV. The Brainbox -a tool to facilitate correlation of brain magnetic resonance imaging features to histopathology. Brain Commun 2023; 5:fcad307. [PMID: 38025281 PMCID: PMC10664401 DOI: 10.1093/braincomms/fcad307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 07/20/2023] [Accepted: 11/07/2023] [Indexed: 12/01/2023] Open
Abstract
Magnetic resonance imaging (MRI) has limitations in identifying underlying tissue pathology, which is relevant for neurological diseases such as multiple sclerosis, stroke or brain tumours. However, there are no standardized methods for correlating MRI features with histopathology. Thus, here we aimed to develop and validate a tool that can facilitate the correlation of brain MRI features to corresponding histopathology. For this, we designed the Brainbox, a waterproof and MRI-compatible 3D printed container with an integrated 3D coordinate system. We used the Brainbox to acquire post-mortem ex vivo MRI of eight human brains, fresh and formalin-fixed, and correlated focal imaging features to histopathology using the built-in 3D coordinate system. With its built-in 3D coordinate system, the Brainbox allowed correlation of MRI features to corresponding tissue substrates. The Brainbox was used to correlate different MR image features of interest to the respective tissue substrate, including normal anatomical structures such as the hippocampus or perivascular spaces, as well as a lacunar stroke. Brain volume decreased upon fixation by 7% (P = 0.01). The Brainbox enabled degassing of specimens before scanning, reducing susceptibility artefacts and minimizing bulk motion during scanning. In conclusion, our proof-of-principle experiments demonstrate the usability of the Brainbox, which can contribute to improving the specificity of MRI and the standardization of the correlation between post-mortem ex vivo human brain MRI and histopathology. Brainboxes are available upon request from our institution.
Collapse
Affiliation(s)
- Wolfgang Faigle
- Neuroimmunology and MS Research Section, Neurology Clinic, University Zurich, University Hospital Zurich, CH-8091 Zurich, Switzerland
| | - Marco Piccirelli
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, CH-8091 Zurich, Switzerland
| | - Tibor Hortobágyi
- Institute of Neuropathology, University of Zurich, CH-8091 Zurich, Switzerland
| | - Karl Frontzek
- Institute of Neuropathology, University of Zurich, CH-8091 Zurich, Switzerland
- Queen Square Brain Bank for Neurological Disorders, UCL Queen Square Institute of Neurology, WC1N 1PJ London, United Kingdom
| | - Amelia Elaine Cannon
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, CH-8091 Zurich, Switzerland
| | - Wolfgang Emanuel Zürrer
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, CH-8091 Zurich, Switzerland
| | - Tobias Granberg
- Department of Neuroradiology, Karolinska University Hospital, S-141 86 Stockholm, Sweden
| | - Zsolt Kulcsar
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, CH-8091 Zurich, Switzerland
| | - Thomas Ludersdorfer
- Neuroimmunology and MS Research Section, Neurology Clinic, University Zurich, University Hospital Zurich, CH-8091 Zurich, Switzerland
| | - Katrin B M Frauenknecht
- Institute of Neuropathology, University of Zurich, CH-8091 Zurich, Switzerland
- Luxembourg Center of Neuropathology (LCNP), Laboratoire National de Santé, 3555 Dudelange, Luxembourg
- National Center of Pathology (NCP), Laboratoire National de Santé, 3555 Dudelange, Luxembourg
| | - Regina Reimann
- Institute of Neuropathology, University of Zurich, CH-8091 Zurich, Switzerland
| | - Benjamin Victor Ineichen
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, CH-8091 Zurich, Switzerland
- Center for Reproducible Science, University of Zurich, CH-8001 Zurich, Switzerland
| |
Collapse
|
12
|
Blanke N, Chang S, Novoseltseva A, Wang H, Boas DA, Bigio IJ. Multiscale label-free imaging of myelin in human brain tissue with polarization-sensitive optical coherence tomography and birefringence microscopy. BIOMEDICAL OPTICS EXPRESS 2023; 14:5946-5964. [PMID: 38021128 PMCID: PMC10659784 DOI: 10.1364/boe.499354] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 08/03/2023] [Accepted: 09/06/2023] [Indexed: 12/01/2023]
Abstract
The combination of polarization-sensitive optical coherence tomography (PS-OCT) and birefringence microscopy (BRM) enables multiscale assessment of myelinated axons in postmortem brain tissue, and these tools are promising for the study of brain connectivity and organization. We demonstrate label-free imaging of myelin structure across the mesoscopic and microscopic spatial scales by performing serial-sectioning PS-OCT of a block of human brain tissue and periodically sampling thin sections for high-resolution imaging with BRM. In co-registered birefringence parameter maps, we observe good correspondence and demonstrate that BRM enables detailed validation of myelin (hence, axonal) organization, thus complementing the volumetric information content of PS-OCT.
Collapse
Affiliation(s)
- Nathan Blanke
- Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston, MA 02215, USA
| | - Shuaibin Chang
- Department of Electrical & Computer Engineering, Boston University, 8 St. Mary’s St., Boston, MA 02215, USA
| | - Anna Novoseltseva
- Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston, MA 02215, USA
| | - Hui Wang
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 149 13th St., Charlestown, MA 02129, USA
| | - David A. Boas
- Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston, MA 02215, USA
| | - Irving J. Bigio
- Department of Biomedical Engineering, Boston University, 44 Cummington Mall, Boston, MA 02215, USA
- Department of Electrical & Computer Engineering, Boston University, 8 St. Mary’s St., Boston, MA 02215, USA
| |
Collapse
|
13
|
Hu C, Grech‐Sollars M, Statton B, Li Z, Gao F, Williams GR, Parker GJM, Zhou F. Direct jet coaxial electrospinning of axon-mimicking fibers for diffusion tensor imaging. POLYM ADVAN TECHNOL 2023; 34:2573-2584. [PMID: 38505514 PMCID: PMC10946859 DOI: 10.1002/pat.6073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 04/01/2023] [Accepted: 04/16/2023] [Indexed: 03/21/2024]
Abstract
Hollow polymer microfibers with variable microstructural and hydrophilic properties were proposed as building elements to create axon-mimicking phantoms for validation of diffusion tensor imaging (DTI). The axon-mimicking microfibers were fabricated in a mm-thick 3D anisotropic fiber strip, by direct jet coaxial electrospinning of PCL/polysiloxane-based surfactant (PSi) mixture as shell and polyethylene oxide (PEO) as core. Hydrophilic PCL-PSi fiber strips were first obtained by carefully selecting appropriate solvents for the core and appropriate fiber collector rotating and transverse speeds. The porous cross-section and anisotropic orientation of axon-mimicking fibers were then quantitatively evaluated using two ImageJ plugins-nearest distance (ND) and directionality based on their scanning electron microscopy (SEM) images. Third, axon-mimicking phantom was constructed from PCL-PSi fiber strips with variable porous-section and fiber orientation and tested on a 3T clinical MR scanner. The relationship between DTI measurements (mean diffusivity [MD] and fractional anisotropy [FA]) of phantom samples and their pore size and fiber orientation was investigated. Two key microstructural parameters of axon-mimicking phantoms including normalized pore distance and dispersion of fiber orientation could well interpret the variations in DTI measurements. Two PCL-PSi phantom samples made from different regions of the same fiber strips were found to have similar MD and FA values, indicating that the direct jet coaxial electrospun fiber strips had consistent microstructure. More importantly, the MD and FA values of the developed axon-mimicking phantoms were mostly in the biologically relevant range.
Collapse
Affiliation(s)
- Chunyan Hu
- College of Textiles and ClothingQingdao UniversityQingdaoChina
| | - Matthew Grech‐Sollars
- Department of Computer ScienceUniversity College LondonLondonUK
- Lysholm Department of Neuroradiology, National Hospital for Neurology and NeurosurgeryUniversity College London Hospitals NHS Foundation TrustLondonUK
| | - Ben Statton
- Medical Research Council, London Institute of Medical SciencesImperial College LondonLondonUK
| | - Zhanxiong Li
- College of Textile and Clothing EngineeringSoochow UniversitySuzhouChina
| | - Fei Gao
- Department of Radiology, Shandong Provincial Hospital, Cheeloo College of MedicineShandong UniversityJinanChina
| | | | - Geoff J. M. Parker
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical EngineeringUniversity College LondonLondonUK
- Bioxydyn LimitedManchesterUK
| | - Feng‐Lei Zhou
- College of Textiles and ClothingQingdao UniversityQingdaoChina
- School of PharmacyUniversity College LondonLondonUK
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical EngineeringUniversity College LondonLondonUK
| |
Collapse
|
14
|
Wang JY, Sonico GJ, Salcedo-Arellano MJ, Hagerman RJ, Martinez-Cerdeno V. A Postmortem MRI Study of Cerebrovascular Disease and Iron Content at End-Stage of Fragile X-Associated Tremor/Ataxia Syndrome. Cells 2023; 12:1898. [PMID: 37508562 PMCID: PMC10377990 DOI: 10.3390/cells12141898] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Revised: 07/03/2023] [Accepted: 07/14/2023] [Indexed: 07/30/2023] Open
Abstract
Brain changes at the end-stage of fragile X-associated tremor/ataxia syndrome (FXTAS) are largely unknown due to mobility impairment. We conducted a postmortem MRI study of FXTAS to quantify cerebrovascular disease, brain atrophy and iron content, and examined their relationships using principal component analysis (PCA). Intracranial hemorrhage (ICH) was observed in 4/17 FXTAS cases, among which one was confirmed by histologic staining. Compared with seven control brains, FXTAS cases showed higher ratings of T2-hyperintensities (indicating cerebral small vessel disease) in the cerebellum, globus pallidus and frontoparietal white matter, and significant atrophy in the cerebellar white matter, red nucleus and dentate nucleus. PCA of FXTAS cases revealed negative associations of T2-hyperintensity ratings with anatomic volumes and iron content in the white matter, hippocampus and amygdala, that were independent from a highly correlated number of regions with ICH and iron content in subcortical nuclei. Post-hoc analysis confirmed PCA findings and further revealed increased iron content in the white matter, hippocampus and amygdala in FXTAS cases compared to controls, after adjusting for T2-hyperintensity ratings. These findings indicate that both ischemic and hemorrhagic brain damage may occur in FXTAS, with the former being marked by demyelination/iron depletion and atrophy, and the latter by ICH and iron accumulation in basal ganglia.
Collapse
Affiliation(s)
- Jun Yi Wang
- Center for Mind and Brain, University of California Davis, Davis, CA 95618, USA
| | - Gerard J. Sonico
- Imaging Research Center, University of California Davis, Sacramento, CA 95817, USA;
| | - Maria Jimena Salcedo-Arellano
- Department of Pathology and Laboratory Medicine, University of California Davis School of Medicine, Sacramento, CA 95817, USA;
- MIND Institute, University of California Davis Health, Sacramento, CA 95817, USA;
- Institute for Pediatric Regenerative Medicine and Shriners Hospitals for Children Northern California, Sacramento, CA 95817, USA
| | - Randi J. Hagerman
- MIND Institute, University of California Davis Health, Sacramento, CA 95817, USA;
- Department of Pediatrics, University of California Davis School of Medicine, Sacramento, CA 95817, USA
| | - Veronica Martinez-Cerdeno
- Department of Pathology and Laboratory Medicine, University of California Davis School of Medicine, Sacramento, CA 95817, USA;
- MIND Institute, University of California Davis Health, Sacramento, CA 95817, USA;
- Institute for Pediatric Regenerative Medicine and Shriners Hospitals for Children Northern California, Sacramento, CA 95817, USA
| |
Collapse
|
15
|
Howard AFD, Huszar IN, Smart A, Cottaar M, Daubney G, Hanayik T, Khrapitchev AA, Mars RB, Mollink J, Scott C, Sibson NR, Sallet J, Jbabdi S, Miller KL. An open resource combining multi-contrast MRI and microscopy in the macaque brain. Nat Commun 2023; 14:4320. [PMID: 37468455 PMCID: PMC10356772 DOI: 10.1038/s41467-023-39916-1] [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: 09/16/2022] [Accepted: 07/03/2023] [Indexed: 07/21/2023] Open
Abstract
Understanding brain structure and function often requires combining data across different modalities and scales to link microscale cellular structures to macroscale features of whole brain organisation. Here we introduce the BigMac dataset, a resource combining in vivo MRI, extensive postmortem MRI and multi-contrast microscopy for multimodal characterisation of a single whole macaque brain. The data spans modalities (MRI and microscopy), tissue states (in vivo and postmortem), and four orders of spatial magnitude, from microscopy images with micrometre or sub-micrometre resolution, to MRI signals on the order of millimetres. Crucially, the MRI and microscopy images are carefully co-registered together to facilitate quantitative multimodal analyses. Here we detail the acquisition, curation, and first release of the data, that together make BigMac a unique, openly-disseminated resource available to researchers worldwide. Further, we demonstrate example analyses and opportunities afforded by the data, including improvement of connectivity estimates from ultra-high angular resolution diffusion MRI, neuroanatomical insight provided by polarised light imaging and myelin-stained histology, and the joint analysis of MRI and microscopy data for reconstruction of the microscopy-inspired connectome. All data and code are made openly available.
Collapse
Affiliation(s)
- Amy F D Howard
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
| | - Istvan N Huszar
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Adele Smart
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Michiel Cottaar
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Greg Daubney
- Wellcome Centre for Integrative Neuroimaging, Experimental Psychology, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Taylor Hanayik
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | | | - Rogier B Mars
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Jeroen Mollink
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Connor Scott
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | | | - Jerome Sallet
- Wellcome Centre for Integrative Neuroimaging, Experimental Psychology, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Saad Jbabdi
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Karla L Miller
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| |
Collapse
|
16
|
Alkemade A, Großmann R, Bazin PL, Forstmann BU. Mixed methodology in human brain research: integrating MRI and histology. Brain Struct Funct 2023; 228:1399-1410. [PMID: 37365411 PMCID: PMC10335951 DOI: 10.1007/s00429-023-02675-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Accepted: 06/20/2023] [Indexed: 06/28/2023]
Abstract
Postmortem magnetic resonance imaging (MRI) can provide a bridge between histological observations and the in vivo anatomy of the human brain. Approaches aimed at the co-registration of data derived from the two techniques are gaining interest. Optimal integration of the two research fields requires detailed knowledge of the tissue property requirements for individual research techniques, as well as a detailed understanding of the consequences of tissue fixation steps on the imaging quality outcomes for both MRI and histology. Here, we provide an overview of existing studies that bridge between state-of-the-art imaging modalities, and discuss the background knowledge incorporated into the design, execution and interpretation of postmortem studies. A subset of the discussed challenges transfer to animal studies as well. This insight can contribute to furthering our understanding of the normal and diseased human brain, and to facilitate discussions between researchers from the individual disciplines.
Collapse
Affiliation(s)
- Anneke Alkemade
- Integrative Model-Based Cognitive Neuroscience Unit, Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands.
| | - Rosa Großmann
- Integrative Model-Based Cognitive Neuroscience Unit, Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands
| | - Pierre-Louis Bazin
- Integrative Model-Based Cognitive Neuroscience Unit, Department of Psychology, University of Amsterdam, Amsterdam, The 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
| | - Birte U Forstmann
- Integrative Model-Based Cognitive Neuroscience Unit, Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands
| |
Collapse
|
17
|
Delinte N, Dricot L, Macq B, Gosse C, Van Reybroeck M, Rensonnet G. Unraveling multi-fixel microstructure with tractography and angular weighting. Front Neurosci 2023; 17:1199568. [PMID: 37351427 PMCID: PMC10282555 DOI: 10.3389/fnins.2023.1199568] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 05/15/2023] [Indexed: 06/24/2023] Open
Abstract
Recent advances in MRI technology have enabled richer multi-shell sequences to be implemented in diffusion MRI, allowing the investigation of both the microscopic and macroscopic organization of the brain white matter and its complex network of neural fibers. The emergence of advanced diffusion models has enabled a more detailed analysis of brain microstructure by estimating the signal received from a voxel as the combination of responses from multiple fiber populations. However, disentangling the individual microstructural properties of different macroscopic white matter tracts where those pathways intersect remains a challenge. Several approaches have been developed to assign microstructural properties to macroscopic streamlines, but often present shortcomings. ROI-based heuristics rely on averages that are not tract-specific. Global methods solve a computationally-intensive global optimization but prevent the use of microstructural properties not included in the model and often require restrictive hypotheses. Other methods use atlases that might not be adequate in population studies where the shape of white matter tracts varies significantly between patients. We introduce UNRAVEL, a framework combining the microscopic and macroscopic scales to unravel multi-fixel microstructure by utilizing tractography. The framework includes commonly-used heuristics as well as a new algorithm, estimating the microstructure of a specific white matter tract with angular weighting. Our framework grants considerable freedom as the inputs required, a set of streamlines defining a tract and a multi-fixel diffusion model estimated in each voxel, can be defined by the user. We validate our approach on synthetic data and in vivo data, including a repeated scan of a subject and a population study of children with dyslexia. In each case, we compare the estimation of microstructural properties obtained with angular weighting to other commonly-used approaches. Our framework provides estimations of the microstructure at the streamline level, volumetric maps for visualization and mean microstructural values for the whole tract. The angular weighting algorithm shows increased accuracy, robustness to uncertainties in its inputs and maintains similar or better reproducibility compared to commonly-used analysis approaches. UNRAVEL will provide researchers with a flexible and open-source tool enabling them to study the microstructure of specific white matter pathways with their diffusion model of choice.
Collapse
Affiliation(s)
- Nicolas Delinte
- Institute of Information and Communication Technologies, Electronics and Applied Mathematics, Université Catholique de Louvain, Louvain-la-Neuve, Belgium
- Institute of NeuroScience, Université Catholique de Louvain, Brussels, Belgium
| | - Laurence Dricot
- Institute of NeuroScience, Université Catholique de Louvain, Brussels, Belgium
| | - Benoit Macq
- Institute of Information and Communication Technologies, Electronics and Applied Mathematics, Université Catholique de Louvain, Louvain-la-Neuve, Belgium
| | - Claire Gosse
- Institute of NeuroScience, Université Catholique de Louvain, Brussels, Belgium
- Psychological Sciences Research Institute, Université Catholique de Louvain, Louvain-la-Neuve, Belgium
| | - Marie Van Reybroeck
- Institute of NeuroScience, Université Catholique de Louvain, Brussels, Belgium
- Psychological Sciences Research Institute, Université Catholique de Louvain, Louvain-la-Neuve, Belgium
| | - Gaetan Rensonnet
- Institute of Information and Communication Technologies, Electronics and Applied Mathematics, Université Catholique de Louvain, Louvain-la-Neuve, Belgium
| |
Collapse
|
18
|
Park E, Lee YJ, Kim C, Eom TJ. Azimuth mapping of fibrous tissue in linear dichroism-sensitive photoacoustic microscopy. PHOTOACOUSTICS 2023; 31:100510. [PMID: 37228578 PMCID: PMC10203768 DOI: 10.1016/j.pacs.2023.100510] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 04/05/2023] [Accepted: 05/09/2023] [Indexed: 05/27/2023]
Abstract
Photoacoustic imaging (PAI) has emerged as a molecular-selective imaging technology based on optical absorption contrast. Dichroism-sensitive photoacoustic (DS-PA) imaging has been reported, where the absorption coefficient has a vector characteristic, featuring dimensions of contrast in polarization and wavelength. Herein, we present a DS-PA microscopy (DS-PAM) system that implements optical anisotropy contrast and molecular selectivity. Moreover, we propose mathematical solutions to fully derive dichroic properties. A wavelength for the PAI of collagenous tissue was used, and the proposed algorithms were validated using linear dichroic materials. We successfully mapped dichroic information in fibrous tissue imaging based on the degree of anisotropy and axis orientation, and also deduced mechanical assessment from the tissue arrangement. The proposed DS-PAM system and algorithms have great potential in various diagnostic fields using polarimetry, such as musculoskeletal and cardiovascular systems.
Collapse
Affiliation(s)
- Eunwoo Park
- Department of Convergence IT Engineering, Electrical Engineering, Mechanical Engineering, Medical Science and Engineering, Graduate School of Artificial Intelligence, and Medical Device Innovation Center, Pohang University of Science and Technology (POSTECH), Pohang, Gyeongbuk 37673, the Republic of Korea
| | - Yong-Jae Lee
- Engineering Research Center for Color-Modulated Extra-Sensory Perception Technology, Pusan National University, Busan 46241, the Republic of Korea
| | - Chulhong Kim
- Department of Convergence IT Engineering, Electrical Engineering, Mechanical Engineering, Medical Science and Engineering, Graduate School of Artificial Intelligence, and Medical Device Innovation Center, Pohang University of Science and Technology (POSTECH), Pohang, Gyeongbuk 37673, the Republic of Korea
| | - Tae Joong Eom
- Engineering Research Center for Color-Modulated Extra-Sensory Perception Technology, Pusan National University, Busan 46241, the Republic of Korea
- Department of Congo-Mechatronics Engineering, Pusan National University, Busan 46241, Republic of Korea
| |
Collapse
|
19
|
Menzel M, Gräßel D, Rajkovic I, Zeineh MM, Georgiadis M. Using light and X-ray scattering to untangle complex neuronal orientations and validate diffusion MRI. eLife 2023; 12:e84024. [PMID: 37166005 PMCID: PMC10259419 DOI: 10.7554/elife.84024] [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: 10/07/2022] [Accepted: 05/02/2023] [Indexed: 05/12/2023] Open
Abstract
Disentangling human brain connectivity requires an accurate description of nerve fiber trajectories, unveiled via detailed mapping of axonal orientations. However, this is challenging because axons can cross one another on a micrometer scale. Diffusion magnetic resonance imaging (dMRI) can be used to infer axonal connectivity because it is sensitive to axonal alignment, but it has limited spatial resolution and specificity. Scattered light imaging (SLI) and small-angle X-ray scattering (SAXS) reveal axonal orientations with microscopic resolution and high specificity, respectively. Here, we apply both scattering techniques on the same samples and cross-validate them, laying the groundwork for ground-truth axonal orientation imaging and validating dMRI. We evaluate brain regions that include unidirectional and crossing fibers in human and vervet monkey brain sections. SLI and SAXS quantitatively agree regarding in-plane fiber orientations including crossings, while dMRI agrees in the majority of voxels with small discrepancies. We further use SAXS and dMRI to confirm theoretical predictions regarding SLI determination of through-plane fiber orientations. Scattered light and X-ray imaging can provide quantitative micrometer 3D fiber orientations with high resolution and specificity, facilitating detailed investigations of complex fiber architecture in the animal and human brain.
Collapse
Affiliation(s)
- Miriam Menzel
- Department of Imaging Physics, Faculty of Applied Sciences, Delft University of TechnologyDelftNetherlands
- Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich GmbHJülichGermany
| | - David Gräßel
- Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich GmbHJülichGermany
| | - Ivan Rajkovic
- Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator LaboratoryStandfordUnited States
| | - Michael M Zeineh
- Department of Radiology, Stanford School of MedicineStanfordUnited States
| | - Marios Georgiadis
- Department of Radiology, Stanford School of MedicineStanfordUnited States
| |
Collapse
|
20
|
Genc S, Raven EP, Drakesmith M, Blakemore SJ, Jones DK. Novel insights into axon diameter and myelin content in late childhood and adolescence. Cereb Cortex 2023; 33:6435-6448. [PMID: 36610731 PMCID: PMC10183755 DOI: 10.1093/cercor/bhac515] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 12/05/2022] [Accepted: 12/07/2022] [Indexed: 01/09/2023] Open
Abstract
White matter microstructural development in late childhood and adolescence is driven predominantly by increasing axon density and myelin thickness. Ex vivo studies suggest that the increase in axon diameter drives developmental increases in axon density observed with pubertal onset. In this cross-sectional study, 50 typically developing participants aged 8-18 years were scanned using an ultra-strong gradient magnetic resonance imaging scanner. Microstructural properties, including apparent axon diameter $({d}_a)$, myelin content, and g-ratio, were estimated in regions of the corpus callosum. We observed age-related differences in ${d}_a$, myelin content, and g-ratio. In early puberty, males had larger ${d}_a$ in the splenium and lower myelin content in the genu and body of the corpus callosum, compared with females. Overall, this work provides novel insights into developmental, pubertal, and cognitive correlates of individual differences in apparent axon diameter and myelin content in the developing human brain.
Collapse
Affiliation(s)
- Sila Genc
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United Kingdom
| | - Erika P Raven
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United Kingdom
- Department of Radiology, New York University School of Medicine, 550 1st Ave., New York, NY 10016, United States
| | - Mark Drakesmith
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United Kingdom
| | - Sarah-Jayne Blakemore
- Department of Psychology, University of Cambridge, Downing Pl, Cambridge CB2 3EB, United Kingdom
| | - Derek K Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Maindy Rd, Cardiff CF24 4HQ, United Kingdom
| |
Collapse
|
21
|
Liang Z, Arefin TM, Lee CH, Zhang J. Using mesoscopic tract-tracing data to guide the estimation of fiber orientation distributions in the mouse brain from diffusion MRI. Neuroimage 2023; 270:119999. [PMID: 36871795 PMCID: PMC10052941 DOI: 10.1016/j.neuroimage.2023.119999] [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: 12/30/2022] [Revised: 02/21/2023] [Accepted: 02/28/2023] [Indexed: 03/07/2023] Open
Abstract
Diffusion MRI (dMRI) tractography is the only tool for non-invasive mapping of macroscopic structural connectivity over the entire brain. Although it has been successfully used to reconstruct large white matter tracts in the human and animal brains, the sensitivity and specificity of dMRI tractography remained limited. In particular, the fiber orientation distributions (FODs) estimated from dMRI signals, key to tractography, may deviate from histologically measured fiber orientation in crossing fibers and gray matter regions. In this study, we demonstrated that a deep learning network, trained using mesoscopic tract-tracing data from the Allen Mouse Brain Connectivity Atlas, was able to improve the estimation of FODs from mouse brain dMRI data. Tractography results based on the network generated FODs showed improved specificity while maintaining sensitivity comparable to results based on FOD estimated using a conventional spherical deconvolution method. Our result is a proof-of-concept of how mesoscale tract-tracing data can guide dMRI tractography and enhance our ability to characterize brain connectivity.
Collapse
Affiliation(s)
- Zifei Liang
- Department of Radiology, Bernard and Irene Schwartz Center for Biomedical Imaging, New York University School of Medicine, 660 First Ave, New York, NY 10016, USA
| | - Tanzil Mahmud Arefin
- Department of Radiology, Bernard and Irene Schwartz Center for Biomedical Imaging, New York University School of Medicine, 660 First Ave, New York, NY 10016, USA
| | - Choong H Lee
- Department of Radiology, Bernard and Irene Schwartz Center for Biomedical Imaging, New York University School of Medicine, 660 First Ave, New York, NY 10016, USA
| | - Jiangyang Zhang
- Department of Radiology, Bernard and Irene Schwartz Center for Biomedical Imaging, New York University School of Medicine, 660 First Ave, New York, NY 10016, USA.
| |
Collapse
|
22
|
Lohkamp KJ, van den Hoek AM, Solé-Guardia G, Lisovets M, Alves Hoffmann T, Velanaki K, Geenen B, Verweij V, Morrison MC, Kleemann R, Wiesmann M, Kiliaan AJ. The Preventive Effect of Exercise and Oral Branched-Chain Amino Acid Supplementation on Obesity-Induced Brain Changes in Ldlr−/−.Leiden Mice. Nutrients 2023; 15:nu15071716. [PMID: 37049556 PMCID: PMC10097391 DOI: 10.3390/nu15071716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Revised: 03/28/2023] [Accepted: 03/29/2023] [Indexed: 04/03/2023] Open
Abstract
Exercise and dietary interventions are promising approaches to tackle obesity and its obesogenic effects on the brain. We investigated the impact of exercise and possible synergistic effects of exercise and branched-chain amino acids (BCAA) supplementation on the brain and behavior in high-fat-diet (HFD)-induced obese Ldlr−/−.Leiden mice. Baseline measurements were performed in chow-fed Ldlr−/−.Leiden mice to assess metabolic risk factors, cognition, and brain structure using magnetic resonance imaging. Thereafter, a subgroup was sacrificed, serving as a healthy reference. The remaining mice were fed an HFD and divided into three groups: (i) no exercise, (ii) exercise, or (iii) exercise and dietary BCAA. Mice were followed for 6 months and aforementioned tests were repeated. We found that exercise alone changed cerebral blood flow, attenuated white matter loss, and reduced neuroinflammation compared to non-exercising HFD-fed mice. Contrarily, no favorable effects of exercise on the brain were found in combination with BCAA, and neuroinflammation was increased. However, cognition was slightly improved in exercising mice on BCAA. Moreover, BCAA and exercise increased the percentage of epididymal white adipose tissue and muscle weight, decreased body weight and fasting insulin levels, improved the circadian rhythm, and transiently improved grip strength. In conclusion, BCAA should be supplemented with caution, although beneficial effects on metabolism, behavior, and cognition were observed.
Collapse
Affiliation(s)
- Klara J. Lohkamp
- Department of Medical Imaging, Anatomy, Radboud University Medical Center, Donders Institute for Brain, Cognition, and Behavior, Preclinical Imaging Center PRIME, Radboud Alzheimer Center, 6525 EZ Nijmegen, The Netherlands; (K.J.L.); (G.S.-G.); (M.L.); (T.A.H.); (K.V.); (B.G.); (V.V.); (M.W.)
| | - Anita M. van den Hoek
- Department of Metabolic Health Research, Netherlands Organisation for Applied Scientific Research (TNO), 2333 BE Leiden, The Netherlands; (A.M.v.d.H.); (M.C.M.); (R.K.)
| | - Gemma Solé-Guardia
- Department of Medical Imaging, Anatomy, Radboud University Medical Center, Donders Institute for Brain, Cognition, and Behavior, Preclinical Imaging Center PRIME, Radboud Alzheimer Center, 6525 EZ Nijmegen, The Netherlands; (K.J.L.); (G.S.-G.); (M.L.); (T.A.H.); (K.V.); (B.G.); (V.V.); (M.W.)
| | - Maria Lisovets
- Department of Medical Imaging, Anatomy, Radboud University Medical Center, Donders Institute for Brain, Cognition, and Behavior, Preclinical Imaging Center PRIME, Radboud Alzheimer Center, 6525 EZ Nijmegen, The Netherlands; (K.J.L.); (G.S.-G.); (M.L.); (T.A.H.); (K.V.); (B.G.); (V.V.); (M.W.)
| | - Talissa Alves Hoffmann
- Department of Medical Imaging, Anatomy, Radboud University Medical Center, Donders Institute for Brain, Cognition, and Behavior, Preclinical Imaging Center PRIME, Radboud Alzheimer Center, 6525 EZ Nijmegen, The Netherlands; (K.J.L.); (G.S.-G.); (M.L.); (T.A.H.); (K.V.); (B.G.); (V.V.); (M.W.)
| | - Konstantina Velanaki
- Department of Medical Imaging, Anatomy, Radboud University Medical Center, Donders Institute for Brain, Cognition, and Behavior, Preclinical Imaging Center PRIME, Radboud Alzheimer Center, 6525 EZ Nijmegen, The Netherlands; (K.J.L.); (G.S.-G.); (M.L.); (T.A.H.); (K.V.); (B.G.); (V.V.); (M.W.)
| | - Bram Geenen
- Department of Medical Imaging, Anatomy, Radboud University Medical Center, Donders Institute for Brain, Cognition, and Behavior, Preclinical Imaging Center PRIME, Radboud Alzheimer Center, 6525 EZ Nijmegen, The Netherlands; (K.J.L.); (G.S.-G.); (M.L.); (T.A.H.); (K.V.); (B.G.); (V.V.); (M.W.)
| | - Vivienne Verweij
- Department of Medical Imaging, Anatomy, Radboud University Medical Center, Donders Institute for Brain, Cognition, and Behavior, Preclinical Imaging Center PRIME, Radboud Alzheimer Center, 6525 EZ Nijmegen, The Netherlands; (K.J.L.); (G.S.-G.); (M.L.); (T.A.H.); (K.V.); (B.G.); (V.V.); (M.W.)
| | - Martine C. Morrison
- Department of Metabolic Health Research, Netherlands Organisation for Applied Scientific Research (TNO), 2333 BE Leiden, The Netherlands; (A.M.v.d.H.); (M.C.M.); (R.K.)
| | - Robert Kleemann
- Department of Metabolic Health Research, Netherlands Organisation for Applied Scientific Research (TNO), 2333 BE Leiden, The Netherlands; (A.M.v.d.H.); (M.C.M.); (R.K.)
| | - Maximilian Wiesmann
- Department of Medical Imaging, Anatomy, Radboud University Medical Center, Donders Institute for Brain, Cognition, and Behavior, Preclinical Imaging Center PRIME, Radboud Alzheimer Center, 6525 EZ Nijmegen, The Netherlands; (K.J.L.); (G.S.-G.); (M.L.); (T.A.H.); (K.V.); (B.G.); (V.V.); (M.W.)
| | - Amanda J. Kiliaan
- Department of Medical Imaging, Anatomy, Radboud University Medical Center, Donders Institute for Brain, Cognition, and Behavior, Preclinical Imaging Center PRIME, Radboud Alzheimer Center, 6525 EZ Nijmegen, The Netherlands; (K.J.L.); (G.S.-G.); (M.L.); (T.A.H.); (K.V.); (B.G.); (V.V.); (M.W.)
- Correspondence:
| |
Collapse
|
23
|
Pang Y. Phase-shifted transverse relaxation orientation dependences in human brain white matter. NMR IN BIOMEDICINE 2023:e4925. [PMID: 36908074 DOI: 10.1002/nbm.4925] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 02/24/2023] [Accepted: 03/02/2023] [Indexed: 06/18/2023]
Abstract
This work aimed to demonstrate an essential phase shift ε 0 $$ {\varepsilon}_0 $$ for better quantifying R 2 $$ {R}_2 $$ and R 2 * $$ {R}_2^{\ast } $$ in human brain white matter (WM), and to further elucidate its origin related to the directional diffusivities from standard diffusion tensor imaging (DTI). ε 0 $$ {\varepsilon}_0 $$ was integrated into a proposed generalized transverse relaxation model for characterizing previously published R 2 $$ {R}_2 $$ and R 2 * $$ {R}_2^{\ast } $$ orientation dependence profiles in brain WM, and then comparisons were made with those without ε 0 $$ {\varepsilon}_0 $$ . It was theorized that anisotropic diffusivity direction ε $$ \varepsilon $$ was collinear with an axon fiber subject to all eigenvalues and eigenvectors from an apparent diffusion tensor. To corroborate the origin of ε 0 $$ {\varepsilon}_0 $$ , R 2 $$ {R}_2 $$ orientation dependences referenced by ε $$ \varepsilon $$ were compared with those referenced by the standard principal diffusivity direction Φ $$ \Phi $$ at b-values of 1000 and 2500 (s/mm2 ). These R 2 $$ {R}_2 $$ orientation dependences were obtained from T 2 $$ {T}_2 $$ -weighted images (b = 0) of ultrahigh-resolution Connectome DTI datasets in the public domain. A normalized root-mean-square error ( NRMSE % $$ NRMSE\% $$ ) and an F $$ F $$ -test were used for evaluating curve-fittings, and statistical significance was considered to be a p of 0.05 or less. A phase-shifted model resulted in significantly reduced NRMSE % $$ NRMSE\% $$ compared with that without ε 0 $$ {\varepsilon}_0 $$ in quantifying various R 2 $$ {R}_2 $$ and R 2 * $$ {R}_2^{\ast } $$ profiles, both in vivo and ex vivo at multiple B 0 $$ {B}_0 $$ fields. The R 2 $$ {R}_2 $$ profiles based on Φ $$ \Phi $$ manifested a right-shifted phase ( ε 0 > 0 $$ {\varepsilon}_0>0 $$ ) at two b-values, while those based on ε $$ \varepsilon $$ became free from ε 0 $$ {\varepsilon}_0 $$ . For all phase-shifted R 2 $$ {R}_2 $$ and R 2 * $$ {R}_2^{\ast } $$ profiles, ε 0 $$ {\varepsilon}_0 $$ generally depended on the directional diffusivities by tan - 1 D ⊥ / D ∥ $$ {\tan}^{-1}\left({D}_{\perp }/{D}_{\parallel}\right) $$ , as predicted. In summary, a ubiquitous phase shift ε 0 $$ {\varepsilon}_0 $$ has been demonstrated as a prerequisite for better quantifying transverse relaxation orientation dependences in human brain WM. Furthermore, the origin of ε 0 $$ {\varepsilon}_0 $$ associated with the directional diffusivities from DTI has been elucidated. These findings could have a significant impact on interpretations of prior R 2 $$ {R}_2 $$ and R 2 * $$ {R}_2^{\ast } $$ datasets and on future research.
Collapse
Affiliation(s)
- Yuxi Pang
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| |
Collapse
|
24
|
Wang JY, Sonico GJ, Salcedo-Arellano MJ, Hagerman RJ, Martínez-Cerdeño V. A postmortem MRI study of cerebrovascular disease and iron content at end-stage of fragile X-associated tremor/ataxia syndrome. RESEARCH SQUARE 2023:rs.3.rs-2440612. [PMID: 36711694 PMCID: PMC9882645 DOI: 10.21203/rs.3.rs-2440612/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Brain changes at end-stage of fragile X-associated tremor/ataxia syndrome (FXTAS) are largely unknown due to mobility impairment. We conducted a postmortem MRI study of FXTAS to quantify cerebrovascular disease, brain atrophy, and iron content and examined their relationships using principal component analysis (PCA). Intracranial hemorrhage (ICH) was observed in 4/17 FXTAS cases among which one was confirmed by histologic staining. Compared with seven control brains, FXTAS cases showed higher ratings of T2-hyperintensities (indicating cerebral small vessel disease) in the cerebellum, globus pallidus, and frontoparietal white matter and significant atrophy in cerebellar white matter, red nucleus, and dentate nucleus. PCA of FXTAS cases revealed negative associations of T2-hyperintensity ratings with anatomic volumes and iron content in the white matter, hippocampus, and amygdala, that were independent from highly correlated number of regions with ICH and iron content in subcortical nuclei. Post hoc analysis confirmed PCA findings and further revealed increased iron content in the white matter, hippocampus, and amygdala in FXTAS cases than controls after adjusting for T2-hyperintensity ratings. These findings indicate that both ischemic and hemorrhagic brain damage may occur in FXTAS, with the former marked by demyelination/iron depletion and atrophy and the latter, ICH and iron accumulation in basal ganglia.
Collapse
|
25
|
Axer M, Amunts K. Scale matters: The nested human connectome. Science 2022; 378:500-504. [DOI: 10.1126/science.abq2599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
A comprehensive description of how neurons and entire brain regions are interconnected is fundamental for a mechanistic understanding of brain function and dysfunction. Neuroimaging has shaped the way to approaching the human brain’s connectivity on the basis of diffusion magnetic resonance imaging and tractography. At the same time, polarization, fluorescence, and electron microscopy became available, which pushed spatial resolution and sensitivity to the axonal or even to the synaptic level. New methods are mandatory to inform and constrain whole-brain tractography by regional, high-resolution connectivity data and local fiber geometry. Machine learning and simulation can provide predictions where experimental data are missing. Future interoperable atlases require new concepts, including high-resolution templates and directionality, to represent variants of tractography solutions and estimates of their accuracy.
Collapse
Affiliation(s)
- Markus Axer
- Institute of Neurosciences and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- Department of Physics, School of Mathematics and Natural Sciences, Bergische Universität Wuppertal, Wuppertal, Germany
| | - Katrin Amunts
- Institute of Neurosciences and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- Cécile and Oskar Vogt Institute for Brain Research, Medical Faculty, University Hospital Düsseldorf, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
| |
Collapse
|
26
|
Guberinic A, van den Elshout R, Kozicz T, Laan MT, Henssen D. Overview of the microanatomy of the human brainstem in relation to the safe entry zones. J Neurosurg 2022; 137:1524-1534. [PMID: 35395628 DOI: 10.3171/2022.2.jns211997] [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: 09/04/2021] [Accepted: 02/07/2022] [Indexed: 11/06/2022]
Abstract
OBJECTIVE The primary objective of this anatomical study was to apply innovative imaging techniques to increase understanding of the microanatomical structures of the brainstem related to safe entry zones. The authors hypothesized that such a high-detail overview would enhance neurosurgeons' abilities to approach and define anatomical safe entry zones for use with microsurgical resection techniques for intrinsic brainstem lesions. METHODS The brainstems of 13 cadavers were studied with polarized light imaging (PLI) and 11.7-T MRI. The brainstem was divided into 3 compartments-mesencephalon, pons, and medulla-for evaluation with MRI. Tissue was further sectioned to 100 μm with a microtome. MATLAB was used for further data processing. Segmentation of the internal structures of the brainstem was performed with the BigBrain database. RESULTS Thirteen entry zones were reported and assessed for their safety, including the anterior mesencephalic zone, lateral mesencephalic sulcus, interpeduncular zone, intercollicular region, supratrigeminal zone, peritrigeminal zone, lateral pontine zone, median sulcus, infracollicular zone, supracollicular zone, olivary zone, lateral medullary zone, and anterolateral sulcus. The microanatomy, safety, and approaches are discussed. CONCLUSIONS PLI and 11.7-T MRI data show that a neurosurgeon possibly does not need to consider the microanatomical structures that would not be visible on conventional MRI and tractography when entering the mentioned safe entry zones. However, the detailed anatomical images may help neurosurgeons increase their understanding of the internal architecture of the human brainstem, which in turn could lead to safer neurosurgical intervention.
Collapse
Affiliation(s)
- Alis Guberinic
- 1Department of Neurosurgery, Radboud University Medical Center, Radboud Institute for Health Sciences, Nijmegen, The Netherlands
| | - Rik van den Elshout
- 2Department of Radiology, Radboud University Medical Center, Radboud Institute for Health Sciences, Nijmegen, The Netherlands
| | - Tamas Kozicz
- 3Department of Biochemistry and Molecular Biology, Mayo Clinic, Rochester, Minnesota; and
- 4Department of Clinical Genomics, Mayo Clinic, Rochester, Minnesota
| | - Mark Ter Laan
- 1Department of Neurosurgery, Radboud University Medical Center, Radboud Institute for Health Sciences, Nijmegen, The Netherlands
| | - Dylan Henssen
- 2Department of Radiology, Radboud University Medical Center, Radboud Institute for Health Sciences, Nijmegen, The Netherlands
| |
Collapse
|
27
|
Damatac CG, Chauvin RJM, Zwiers MP, van Rooij D, Akkermans SEA, Naaijen J, Hoekstra PJ, Hartman CA, Oosterlaan J, Franke B, Buitelaar JK, Beckmann CF, Sprooten E. White Matter Microstructure in Attention-Deficit/Hyperactivity Disorder: A Systematic Tractography Study in 654 Individuals. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2022; 7:979-988. [PMID: 33054990 DOI: 10.1016/j.bpsc.2020.07.015] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Revised: 07/21/2020] [Accepted: 07/21/2020] [Indexed: 12/14/2022]
Abstract
BACKGROUND Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by age-inappropriate levels of inattention and/or hyperactivity-impulsivity. ADHD has been related to differences in white matter (WM) microstructure. However, much remains unclear regarding the nature of these WM differences and which clinical aspects of ADHD they reflect. We systematically investigated whether fractional anisotropy (FA) is associated with current and/or lifetime categorical diagnosis, impairment in daily life, and continuous ADHD symptom measures. METHODS Diffusion-weighted imaging data were obtained from 654 participants (322 unaffected, 258 affected, 74 subthreshold; 7-29 years of age). We applied automated global probabilistic tractography on 18 major WM pathways. Linear mixed-effects regression models were used to examine associations of clinical measures with overall brain and tract-specific FA. RESULTS There were significant interactions of tract with all ADHD variables on FA. There were no significant associations of FA with current or lifetime diagnosis, nor with impairment. Lower FA in the right cingulum angular bundle was associated with higher hyperactivity-impulsivity symptom severity (pfamilywise error = .045). There were no significant effects for other tracts. CONCLUSIONS This is the first time global probabilistic tractography has been applied to an ADHD dataset of this size. We found no evidence for altered FA in association with ADHD diagnosis. Our findings indicate that associations of FA with ADHD are not uniformly distributed across WM tracts. Continuous symptom measures of ADHD may be more sensitive to FA than diagnostic categories. The right cingulum angular bundle in particular may play a role in symptoms of hyperactivity and impulsivity.
Collapse
Affiliation(s)
- Christienne G Damatac
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands; Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands.
| | - Roselyne J M Chauvin
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands; Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Marcel P Zwiers
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands; Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Daan van Rooij
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands; Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Sophie E A Akkermans
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands; Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Jilly Naaijen
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands; Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Pieter J Hoekstra
- Department of Psychiatry, University Medical Center Groningen, University of Groningen, the Netherlands
| | - Catharina A Hartman
- Department of Psychiatry, University Medical Center Groningen, University of Groningen, the Netherlands
| | - Jaap Oosterlaan
- Department of Clinical Neuropsychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Barbara Franke
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands; Department of Psychiatry, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Jan K Buitelaar
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands; Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands; Karakter Child and Adolescent Psychiatry University Centre, Nijmegen, the Netherlands
| | - Christian F Beckmann
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands; Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands; Centre for Functional MRI of the Brain, University of Oxford, Oxford, United Kingdom
| | - Emma Sprooten
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands; Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| |
Collapse
|
28
|
Miyata T, Benson NC, Winawer J, Takemura H. Structural Covariance and Heritability of the Optic Tract and Primary Visual Cortex in Living Human Brains. J Neurosci 2022; 42:6761-6769. [PMID: 35853720 PMCID: PMC9436011 DOI: 10.1523/jneurosci.0043-22.2022] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 05/31/2022] [Accepted: 07/11/2022] [Indexed: 11/21/2022] Open
Abstract
Individual differences among human brains exist at many scales, spanning gene expression, white matter tissue properties, and the size and shape of cortical areas. One notable example is an approximately 3-fold range in the size of human primary visual cortex (V1), a much larger range than is found in overall brain size. A previous study (Andrews et al., 1997) reported a correlation between optic tract (OT) cross-section area and V1 size in postmortem human brains, suggesting that there may be a common developmental mechanism for multiple components of the visual pathways. We evaluated the relationship between properties of the OT and V1 in a much larger sample of living human brains by analyzing the Human Connectome Project (HCP) 7 Tesla Retinotopy Dataset (including 107 females and 71 males). This dataset includes retinotopic maps measured with functional MRI (fMRI) and fiber tract data measured with diffusion MRI (dMRI). We found a negative correlation between OT fractional anisotropy (FA) and V1 surface area (r = -0.19). This correlation, although small, was consistent across multiple dMRI datasets differing in acquisition parameters. Further, we found that both V1 surface area and OT properties were correlated among twins, with higher correlations for monozygotic (MZ) than dizygotic (DZ) twins, indicating a high degree of heritability for both properties. Together, these results demonstrate covariation across individuals in properties of the retina (OT) and cortex (V1) and show that each is influenced by genetic factors.SIGNIFICANCE STATEMENT The size of human primary visual cortex (V1) has large interindividual differences. These differences do not scale with overall brain size. A previous postmortem study reported a correlation between the size of the human optic tract (OT) and V1. In this study, we evaluated the relationship between the OT and V1 in living humans by analyzing a neuroimaging dataset that included functional MRI (fMRI) and diffusion MRI (dMRI) data. We found a small, but robust correlation between OT tissue properties and V1 size, supporting the existence of structural covariance between the OT and V1 in living humans. The results suggest that characteristics of retinal ganglion cells (RGCs), reflected in OT measurements, are correlated with individual differences in human V1.
Collapse
Affiliation(s)
- Toshikazu Miyata
- Graduate School of Frontier Biosciences, Osaka University, Suita-shi 565-0871, Japan
- Center for Information and Neural Networks (CiNet), Advanced ICT Institute, National Institute of Information and Communications Technology (NICT), Suita-shi 565-0871, Japan
- Division of Sensory and Cognitive Brain Mapping, Department of System Neuroscience, National Institute for Physiological Sciences, Okazaki-shi 444-8585, Japan
| | - Noah C Benson
- eScience Institute, University of Washington, Seattle, 98195, Washington
| | - Jonathan Winawer
- Department of Psychology and Center for Neural Science, New York University, New York, NY 10003
| | - Hiromasa Takemura
- Graduate School of Frontier Biosciences, Osaka University, Suita-shi 565-0871, Japan
- Center for Information and Neural Networks (CiNet), Advanced ICT Institute, National Institute of Information and Communications Technology (NICT), Suita-shi 565-0871, Japan
- Division of Sensory and Cognitive Brain Mapping, Department of System Neuroscience, National Institute for Physiological Sciences, Okazaki-shi 444-8585, Japan
- Department of Physiological Sciences, School of Life Science, SOKENDAI (The Graduate University for Advanced Studies), Hayama-cho 240-0193, Japan
| |
Collapse
|
29
|
Yendiki A, Aggarwal M, Axer M, Howard AF, van Cappellen van Walsum AM, Haber SN. Post mortem mapping of connectional anatomy for the validation of diffusion MRI. Neuroimage 2022; 256:119146. [PMID: 35346838 PMCID: PMC9832921 DOI: 10.1016/j.neuroimage.2022.119146] [Citation(s) in RCA: 43] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 03/02/2022] [Accepted: 03/23/2022] [Indexed: 01/13/2023] Open
Abstract
Diffusion MRI (dMRI) is a unique tool for the study of brain circuitry, as it allows us to image both the macroscopic trajectories and the microstructural properties of axon bundles in vivo. The Human Connectome Project ushered in an era of impressive advances in dMRI acquisition and analysis. As a result of these efforts, the quality of dMRI data that could be acquired in vivo improved substantially, and large collections of such data became widely available. Despite this progress, the main limitation of dMRI remains: it does not image axons directly, but only provides indirect measurements based on the diffusion of water molecules. Thus, it must be validated by methods that allow direct visualization of axons but that can only be performed in post mortem brain tissue. In this review, we discuss methods for validating the various features of connectional anatomy that are extracted from dMRI, both at the macro-scale (trajectories of axon bundles), and at micro-scale (axonal orientations and other microstructural properties). We present a range of validation tools, including anatomic tracer studies, Klingler's dissection, myelin stains, label-free optical imaging techniques, and others. We provide an overview of the basic principles of each technique, its limitations, and what it has taught us so far about the accuracy of different dMRI acquisition and analysis approaches.
Collapse
Affiliation(s)
- Anastasia Yendiki
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States,Corresponding author (A. Yendiki)
| | - Manisha Aggarwal
- Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Markus Axer
- Forschungszentrum Jülich, Institute of Neuroscience and Medicine, Jülich, Germany,Department of Physics, University of Wuppertal Germany
| | - Amy F.D. Howard
- Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Anne-Marie van Cappellen van Walsum
- Department of Medical Imaging, Anatomy, Radboud University Medical Center, Nijmegen, the Netherland,Cognition and Behaviour, Donders Institute for Brain, Nijmegen, the Netherland
| | - Suzanne N. Haber
- Department of Pharmacology and Physiology, University of Rochester, Rochester, NY, United States,McLean Hospital, Belmont, MA, United States
| |
Collapse
|
30
|
Garcia-Hernandez R, Cerdán Cerdá A, Trouve Carpena A, Drakesmith M, Koller K, Jones DK, Canals S, De Santis S. Mapping microglia and astrocyte activation in vivo using diffusion MRI. SCIENCE ADVANCES 2022; 8:eabq2923. [PMID: 35622913 PMCID: PMC9140964 DOI: 10.1126/sciadv.abq2923] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 04/13/2022] [Indexed: 05/04/2023]
Abstract
While glia are increasingly implicated in the pathophysiology of psychiatric and neurodegenerative disorders, available methods for imaging these cells in vivo involve either invasive procedures or positron emission tomography radiotracers, which afford low resolution and specificity. Here, we present a noninvasive diffusion-weighted magnetic resonance imaging (MRI) method to image changes in glia morphology. Using rat models of neuroinflammation, degeneration, and demyelination, we demonstrate that diffusion-weighted MRI carries a fingerprint of microglia and astrocyte activation and that specific signatures from each population can be quantified noninvasively. The method is sensitive to changes in glia morphology and proliferation, providing a quantitative account of neuroinflammation, regardless of the existence of a concomitant neuronal loss or demyelinating injury. We prove the translational value of the approach showing significant associations between MRI and histological microglia markers in humans. This framework holds the potential to transform basic and clinical research by clarifying the role of inflammation in health and disease.
Collapse
Affiliation(s)
| | | | | | - Mark Drakesmith
- CUBRIC, School of Psychology, Cardiff University, Cardiff, UK
| | - Kristin Koller
- CUBRIC, School of Psychology, Cardiff University, Cardiff, UK
| | - Derek K. Jones
- CUBRIC, School of Psychology, Cardiff University, Cardiff, UK
| | - Santiago Canals
- Instituto de Neurociencias, CSIC/UMH, San Juan de Alicante, Alicante, Spain
| | - Silvia De Santis
- Instituto de Neurociencias, CSIC/UMH, San Juan de Alicante, Alicante, Spain
- CUBRIC, School of Psychology, Cardiff University, Cardiff, UK
| |
Collapse
|
31
|
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.
Collapse
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.)
| |
Collapse
|
32
|
Shi Y, Zhao Z, Tang H, Huang S. Intellectual Structure and Emerging Trends of White Matter Hyperintensity Studies: A Bibliometric Analysis From 2012 to 2021. Front Neurosci 2022; 16:866312. [PMID: 35478843 PMCID: PMC9036105 DOI: 10.3389/fnins.2022.866312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 02/18/2022] [Indexed: 11/26/2022] Open
Abstract
White matter hyperintensities (WMHs), which have a significant effect on human health, have received increasing attention since their number of publications has increased in the past 10 years. We aimed to explore the intellectual structure, hotspots, and emerging trends of publications on WMHs using bibliometric analysis from 2012 to 2021. Publications on WMHs from 2012 to 2021 were retrieved from the Web of Science Core Collection. CiteSpace 5.8.R3, VOSviewer 1.6.17, and an online bibliometric analysis platform (Bibliometric. com) were used to quantitatively analyze the trends of publications from multiple perspectives. A total of 29,707 publications on WMHs were obtained, and the number of annual publications generally increased from 2012 to 2021. Neurology had the most publications on WMHs. The top country and institution were the United States and Harvard University, respectively. Massimo Filippi and Stephen M. Smith were the most productive and co-cited authors, respectively. Thematic concentrations primarily included cerebral small vessel disease, diffusion magnetic resonance imaging (dMRI), schizophrenia, Alzheimer’s disease, multiple sclerosis, microglia, and oligodendrocyte. The hotspots were clustered into five groups: white matter and diffusion tensor imaging, inflammation and demyelination, small vessel disease and cognitive impairment, MRI and multiple sclerosis, and Alzheimer’s disease. Emerging trends mainly include deep learning, machine learning, perivascular space, convolutional neural network, neurovascular unit, and neurite orientation dispersion and density imaging. This study presents an overview of publications on WMHs and provides insights into the intellectual structure of WMH studies. Our study provides information to help researchers and clinicians quickly and comprehensively understand the hotspots and emerging trends within WMH studies as well as providing direction for future basic and clinical studies on WMHs.
Collapse
Affiliation(s)
- Yanan Shi
- Research and Development Center of Traditional Chinese Medicine, Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Zehua Zhao
- Graduate School, Beijing University of Chinese Medicine, Beijing, China
| | - Huan Tang
- Graduate School, Beijing University of Chinese Medicine, Beijing, China
| | - Shijing Huang
- Research and Development Center of Traditional Chinese Medicine, Guang’anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China
- *Correspondence: Shijing Huang,
| |
Collapse
|
33
|
Resolution and b value dependent Structural Connectome in ex vivo Mouse Brain. Neuroimage 2022; 255:119199. [PMID: 35417754 PMCID: PMC9195912 DOI: 10.1016/j.neuroimage.2022.119199] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2021] [Revised: 04/05/2022] [Accepted: 04/07/2022] [Indexed: 12/24/2022] Open
Abstract
Diffusion magnetic resonance imaging has been widely used in both clinical and preclinical studies to characterize tissue microstructure and structural connectivity. The diffusion MRI protocol for the Human Connectome Project (HCP) has been developed and optimized to obtain high-quality, high-resolution diffusion MRI (dMRI) datasets. However, such efforts have not been fully explored in preclinical studies, especially for rodents. In this study, high quality dMRI datasets of mouse brains were acquired at 9.4T system from two vendors. In particular, we acquired a high-spatial resolution dMRI dataset (25 μm isotropic with 126 diffusion encoding directions), which we believe to be the highest spatial resolution yet obtained; and a high-angular resolution dMRI dataset (50 μm isotropic with 384 diffusion encoding directions), which we believe to be the highest angular resolution compared to the dMRI datasets at the microscopic resolution. We systematically investigated the effects of three important parameters that affect the final outcome of the connectome: b value (1000s/mm2 to 8000 s/mm2), angular resolution (10 to 126), and spatial resolution (25 μm to 200 μm). The stability of tractography and connectome increase with the angular resolution, where more than 50 angles is necessary to achieve consistent results. The connectome and quantitative parameters derived from graph theory exhibit a linear relationship to the b value (R2 > 0.99); a single-shell acquisition with b value of 3000 s/mm2 shows comparable results to the multi-shell high angular resolution dataset. The dice coefficient decreases and both false positive rate and false negative rate gradually increase with coarser spatial resolution. Our study provides guidelines and foundations for exploration of tradeoffs among acquisition parameters for the structural connectome in ex vivo mouse brain.
Collapse
|
34
|
Chan KS, Hédouin R, Mollink J, Schulz J, van Cappellen van Walsum AM, Marques JP. Imaging white matter microstructure with gradient-echo phase imaging: Is ex vivo imaging with formalin-fixed tissue a good approximation of the in vivo brain? Magn Reson Med 2022; 88:380-390. [PMID: 35344591 PMCID: PMC9314807 DOI: 10.1002/mrm.29213] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 01/17/2022] [Accepted: 02/10/2022] [Indexed: 11/20/2022]
Abstract
Purpose Ex vivo imaging is a commonly used approach to investigate the biophysical mechanism of orientation‐dependent signal phase evolution in white matter. Yet, how phase measurements are influenced by the structural alteration in the tissue after formalin fixation is not fully understood. Here, we study the effects on magnetic susceptibility, microstructural compartmentalization, and chemical exchange measurement with a postmortem formalin‐fixed whole‐brain human tissue. Methods A formalin‐fixed, postmortem human brain specimen was scanned with multiple orientations to the main magnetic field direction for robust bulk magnetic susceptibility measurement with conventional quantitative susceptibility imaging models. White matter samples were subsequently excised from the whole‐brain specimen and scanned in multiple rotations on an MRI scanner to measure the anisotropic magnetic susceptibility and microstructure‐related contributions in the signal phase and to validate the findings of the whole‐brain data. Results The bulk isotropic magnetic susceptibility of ex vivo whole‐brain imaging is comparable to in vivo imaging, with noticeable enhanced nonsusceptibility contributions. The excised specimen experiment reveals that anisotropic magnetic susceptibility and compartmentalization phase effect were considerably reduced in the formalin‐fixed white matter specimens. Conclusions Formalin‐fixed postmortem white matter exhibits comparable isotropic magnetic susceptibility to previous in vivo imaging findings. However, the measured phase and magnitude data of the fixed white matter tissue shows a significantly weaker orientation dependency and compartmentalization effect. Alternatives to formalin fixation are needed to better reproduce the in vivo microstructural effects in postmortem samples.
Collapse
Affiliation(s)
- Kwok-Shing Chan
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | - Renaud Hédouin
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands.,Empenn, INRIA, INSERM, CNRS, Université de Rennes 1, Rennes, France
| | - Jeroen Mollink
- Department of Medical Imaging, Anatomy, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jenni Schulz
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | - Anne-Marie van Cappellen van Walsum
- Department of Medical Imaging, Anatomy, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - José P Marques
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| |
Collapse
|
35
|
Tendler BC, Hanayik T, Ansorge O, Bangerter-Christensen S, Berns GS, Bertelsen MF, Bryant KL, Foxley S, van den Heuvel MP, Howard AFD, Huszar IN, Khrapitchev AA, Leonte A, Manger PR, Menke RAL, Mollink J, Mortimer D, Pallebage-Gamarallage M, Roumazeilles L, Sallet J, Scholtens LH, Scott C, Smart A, Turner MR, Wang C, Jbabdi S, Mars RB, Miller KL. The Digital Brain Bank, an open access platform for post-mortem imaging datasets. eLife 2022; 11:e73153. [PMID: 35297760 PMCID: PMC9042233 DOI: 10.7554/elife.73153] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Accepted: 03/17/2022] [Indexed: 11/13/2022] Open
Abstract
Post-mortem magnetic resonance imaging (MRI) provides the opportunity to acquire high-resolution datasets to investigate neuroanatomy and validate the origins of image contrast through microscopy comparisons. We introduce the Digital Brain Bank (open.win.ox.ac.uk/DigitalBrainBank), a data release platform providing open access to curated, multimodal post-mortem neuroimaging datasets. Datasets span three themes-Digital Neuroanatomist: datasets for detailed neuroanatomical investigations; Digital Brain Zoo: datasets for comparative neuroanatomy; and Digital Pathologist: datasets for neuropathology investigations. The first Digital Brain Bank data release includes 21 distinctive whole-brain diffusion MRI datasets for structural connectivity investigations, alongside microscopy and complementary MRI modalities. This includes one of the highest-resolution whole-brain human diffusion MRI datasets ever acquired, whole-brain diffusion MRI in fourteen nonhuman primate species, and one of the largest post-mortem whole-brain cohort imaging studies in neurodegeneration. The Digital Brain Bank is the culmination of our lab's investment into post-mortem MRI methodology and MRI-microscopy analysis techniques. This manuscript provides a detailed overview of our work with post-mortem imaging to date, including the development of diffusion MRI methods to image large post-mortem samples, including whole, human brains. Taken together, the Digital Brain Bank provides cross-scale, cross-species datasets facilitating the incorporation of post-mortem data into neuroimaging studies.
Collapse
Affiliation(s)
- Benjamin C Tendler
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Taylor Hanayik
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Olaf Ansorge
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Sarah Bangerter-Christensen
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | | | - Mads F Bertelsen
- Centre for Zoo and Wild Animal Health, Copenhagen ZooFrederiksbergDenmark
| | - Katherine L Bryant
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Sean Foxley
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
- Department of Radiology, University of ChicagoChicagoUnited States
| | - Martijn P van den Heuvel
- Department of Complex Trait Genetics, Centre for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit AmsterdamAmsterdamNetherlands
- Department of Child Psychiatry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit AmsterdamAmsterdamNetherlands
| | - Amy FD Howard
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Istvan N Huszar
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Alexandre A Khrapitchev
- Medical Research Council Oxford Institute for Radiation Oncology, University of OxfordOxfordUnited Kingdom
| | - Anna Leonte
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Paul R Manger
- School of Anatomical Sciences, Faculty of Health Sciences, University of the WitwatersrandJohannesburgSouth Africa
| | - Ricarda AL Menke
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Jeroen Mollink
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Duncan Mortimer
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Menuka Pallebage-Gamarallage
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Lea Roumazeilles
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of OxfordOxfordUnited Kingdom
| | - Jerome Sallet
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of OxfordOxfordUnited Kingdom
- Stem Cell and Brain Research Institute, Université Lyon 1, INSERMBronFrance
| | - Lianne H Scholtens
- Department of Complex Trait Genetics, Centre for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit AmsterdamAmsterdamNetherlands
| | - Connor Scott
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Adele Smart
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Martin R Turner
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Chaoyue Wang
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Saad Jbabdi
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Rogier B Mars
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
- Donders Institute for Brain, Cognition and Behaviour, Radboud University NijmegenNijmegenNetherlands
| | - Karla L Miller
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| |
Collapse
|
36
|
van Cappellen van Walsum A, Henssen DJ. E-Learning Three-Dimensional Anatomy of the Brainstem: Impact of Different Microscopy Techniques and Spatial Ability. ANATOMICAL SCIENCES EDUCATION 2022; 15:317-329. [PMID: 33507593 PMCID: PMC9292761 DOI: 10.1002/ase.2056] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Revised: 01/08/2021] [Accepted: 01/23/2021] [Indexed: 05/05/2023]
Abstract
Polarized light imaging (PLI) is a new method which quantifies and visualizes nerve fiber direction. In this study, the educational value of PLI sections of the human brainstem were compared to histological sections stained with Luxol fast blue (LFB) using e-learning modules. Mental Rotations Test (MRT) was used to assess the spatial ability. Pre-intervention, post-intervention, and long-term (1 week) anatomical tests were provided to assess the baseline knowledge and retention. One-on-one electronic interviews after the last test were carried out to understand the students' perceptions of the intervention. Thirty-eight medical students, (19 female and 19 males, mean age 21.5 ± SD 2.4; median age: 21.0 years) participated with a mean MRT score of 13.2 ± 5.2 points and a mean pre-intervention knowledge test score of 49.9 ± 11.8%. A significant improvement in both, post-intervention and long-term test scores occurred after learning with either PLI or LFB e-learning module on brainstem anatomy (both P < 0.001). No difference was observed between groups in post-intervention test scores and long-term test scores (P = 0.913 and P = 0.403, respectively). A higher MRT-score was significantly correlated with a higher post-intervention test score (rk = 0.321; P < 0.05, respectively), but there was not a significant association between the MRT- and the long-term scores (rk = -0.078; P = 0.509). Interviews (n = 10) revealed three major topics: Learning (brainstem) anatomy by use of e-learning modules; The "need" of technological background information when studying brainstem sections; and Mnemonics when studying brainstem anatomy. Future studies should assess the cognitive burden of cross-sectional learning methods with PLI and/or LFB sections and their effects on knowledge retention.
Collapse
Affiliation(s)
- Anne‐Marie van Cappellen van Walsum
- Department of Medical ImagingRadboud University Medical CenterNijmegenThe Netherlands
- Donders Institute for Brain, Cognition and BehaviourRadboud UniversityNijmegenThe Netherlands
| | - Dylan J.H.A. Henssen
- Department of Medical ImagingRadboud University Medical CenterNijmegenThe Netherlands
- Donders Institute for Brain, Cognition and BehaviourRadboud UniversityNijmegenThe Netherlands
| |
Collapse
|
37
|
Tract-specific statistics based on diffusion-weighted probabilistic tractography. Commun Biol 2022; 5:138. [PMID: 35177755 PMCID: PMC8854429 DOI: 10.1038/s42003-022-03073-w] [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: 05/05/2021] [Accepted: 01/24/2022] [Indexed: 11/09/2022] Open
Abstract
Diffusion-weighted neuroimaging approaches provide rich evidence for estimating the structural integrity of white matter in vivo, but typically do not assess white matter integrity for connections between two specific regions of the brain. Here, we present a method for deriving tract-specific diffusion statistics, based upon predefined regions of interest. Our approach derives a population distribution using probabilistic tractography, based on the Nathan Kline Institute (NKI) Enhanced Rockland sample. We determine the most likely geometry of a path between two regions and express this as a spatial distribution. We then estimate the average orientation of streamlines traversing this path, at discrete distances along its trajectory, and the fraction of diffusion directed along this orientation for each participant. The resulting participant-wise metrics (tract-specific anisotropy; TSA) can then be used for statistical analysis on any comparable population. Based on this method, we report both negative and positive associations between age and TSA for two networks derived from published meta-analytic studies (the “default mode” and “what-where” networks), along with more moderate sex differences and age-by-sex interactions. The proposed method can be applied to any arbitrary set of brain regions, to estimate both the spatial trajectory and DWI-based anisotropy specific to those regions. Andrew Reid et al. use publicly available data to present a method for deriving tract-specific statistics based on diffusion-weighted MRI, based upon arbitrarily-defined regions of interest. Their approach enables them to report both negative and positive associations between age and tract-specific anisotropy along with more moderate sex differences and age-by-sex interactions.
Collapse
|
38
|
Ogawa S, Takemura H, Horiguchi H, Miyazaki A, Matsumoto K, Masuda Y, Yoshikawa K, Nakano T. Multi-Contrast Magnetic Resonance Imaging of Visual White Matter Pathways in Patients With Glaucoma. Invest Ophthalmol Vis Sci 2022; 63:29. [PMID: 35201263 PMCID: PMC8883150 DOI: 10.1167/iovs.63.2.29] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Accepted: 02/03/2022] [Indexed: 11/24/2022] Open
Abstract
Purpose Glaucoma is a disorder that involves visual field loss caused by retinal ganglion cell damage. Previous diffusion magnetic resonance imaging (dMRI) studies have demonstrated that retinal ganglion cell damage affects tissues in the optic tract (OT) and optic radiation (OR). However, because previous studies have used a simple diffusion tensor model to analyze dMRI data, the microstructural interpretation of white matter tissue changes remains uncertain. In this study, we used a multi-contrast MRI approach to further clarify the type of microstructural damage that occurs in patients with glaucoma. Methods We collected dMRI data from 17 patients with glaucoma and 30 controls using 3-tesla (3T) MRI. Using the dMRI data, we estimated three types of tissue property metrics: intracellular volume fraction (ICVF), orientation dispersion index (ODI), and isotropic volume fraction (IsoV). Quantitative T1 (qT1) data, which may be relatively specific to myelin, were collected from all subjects. Results In the OT, all four metrics showed significant differences between the glaucoma and control groups. In the OR, only the ICVF showed significant between-group differences. ICVF was significantly correlated with qT1 in the OR of the glaucoma group, although qT1 did not show any abnormality at the group level. Conclusions Our results suggest that, at the group level, tissue changes in OR caused by glaucoma might be explained by axonal damage, which is reflected in the intracellular diffusion signals, rather than myelin damage. The significant correlation between ICVF and qT1 suggests that myelin damage might also occur in a smaller number of severe cases.
Collapse
Affiliation(s)
- Shumpei Ogawa
- Department of Ophthalmology, The Jikei University School of Medicine, Tokyo, Japan
| | - Hiromasa Takemura
- Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology, Suita, Japan
| | - Hiroshi Horiguchi
- Department of Ophthalmology, The Jikei University School of Medicine, Tokyo, Japan
| | | | - Kenji Matsumoto
- Brain Science Institute, Tamagawa University, Machida, Japan
| | - Yoichiro Masuda
- Department of Ophthalmology, The Jikei University School of Medicine, Tokyo, Japan
| | - Keiji Yoshikawa
- Department of Ophthalmology, The Jikei University School of Medicine, Tokyo, Japan
- Yoshikawa Eye Clinic, Machida, Japan
| | - Tadashi Nakano
- Department of Ophthalmology, The Jikei University School of Medicine, Tokyo, Japan
| |
Collapse
|
39
|
Jones R, Maffei C, Augustinack J, Fischl B, Wang H, Bilgic B, Yendiki A. High-fidelity approximation of grid- and shell-based sampling schemes from undersampled DSI using compressed sensing: Post mortem validation. Neuroimage 2021; 244:118621. [PMID: 34587516 PMCID: PMC8631240 DOI: 10.1016/j.neuroimage.2021.118621] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 09/02/2021] [Accepted: 09/24/2021] [Indexed: 12/31/2022] Open
Abstract
While many useful microstructural indices, as well as orientation distribution functions, can be obtained from multi-shell dMRI data, there is growing interest in exploring the richer set of microstructural features that can be extracted from the full ensemble average propagator (EAP). The EAP can be readily computed from diffusion spectrum imaging (DSI) data, at the cost of a very lengthy acquisition. Compressed sensing (CS) has been used to make DSI more practical by reducing its acquisition time. CS applied to DSI (CS-DSI) attempts to reconstruct the EAP from significantly undersampled q-space data. We present a post mortem validation study where we evaluate the ability of CS-DSI to approximate not only fully sampled DSI but also multi-shell acquisitions with high fidelity. Human brain samples are imaged with high-resolution DSI at 9.4T and with polarization-sensitive optical coherence tomography (PSOCT). The latter provides direct measurements of axonal orientations at microscopic resolutions, allowing us to evaluate the mesoscopic orientation estimates obtained from diffusion MRI, in terms of their angular error and the presence of spurious peaks. We test two fast, dictionary-based, L2-regularized algorithms for CS-DSI reconstruction. We find that, for a CS acceleration factor of R=3, i.e., an acquisition with 171 gradient directions, one of these methods is able to achieve both low angular error and low number of spurious peaks. With a scan length similar to that of high angular resolution multi-shell acquisition schemes, this CS-DSI approach is able to approximate both fully sampled DSI and multi-shell data with high accuracy. Thus it is suitable for orientation reconstruction and microstructural modeling techniques that require either grid- or shell-based acquisitions. We find that the signal-to-noise ratio (SNR) of the training data used to construct the dictionary can have an impact on the accuracy of CS-DSI, but that there is substantial robustness to loss of SNR in the test data. Finally, we show that, as the CS acceleration factor increases beyond R=3, the accuracy of these reconstruction methods degrade, either in terms of the angular error, or in terms of the number of spurious peaks. Our results provide useful benchmarks for the future development of even more efficient q-space acceleration techniques.
Collapse
Affiliation(s)
- Robert Jones
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA 02129, USA.
| | - Chiara Maffei
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA 02129, USA
| | - Jean Augustinack
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA 02129, USA
| | - Bruce Fischl
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA 02129, USA; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Hui Wang
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA 02129, USA
| | - Berkin Bilgic
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA 02129, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Anastasia Yendiki
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA 02129, USA
| |
Collapse
|
40
|
Schurr R, Mezer AA. The glial framework reveals white matter fiber architecture in human and primate brains. Science 2021; 374:762-767. [PMID: 34618596 DOI: 10.1126/science.abj7960] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
[Figure: see text].
Collapse
Affiliation(s)
- Roey Schurr
- Edmond and Lily Safra Center for Brain Sciences, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Aviv A Mezer
- Edmond and Lily Safra Center for Brain Sciences, Hebrew University of Jerusalem, Jerusalem, Israel
| |
Collapse
|
41
|
Huang SY, Witzel T, Keil B, Scholz A, Davids M, Dietz P, Rummert E, Ramb R, Kirsch JE, Yendiki A, Fan Q, Tian Q, Ramos-Llordén G, Lee HH, Nummenmaa A, Bilgic B, Setsompop K, Wang F, Avram AV, Komlosh M, Benjamini D, Magdoom KN, Pathak S, Schneider W, Novikov DS, Fieremans E, Tounekti S, Mekkaoui C, Augustinack J, Berger D, Shapson-Coe A, Lichtman J, Basser PJ, Wald LL, Rosen BR. Connectome 2.0: Developing the next-generation ultra-high gradient strength human MRI scanner for bridging studies of the micro-, meso- and macro-connectome. Neuroimage 2021; 243:118530. [PMID: 34464739 PMCID: PMC8863543 DOI: 10.1016/j.neuroimage.2021.118530] [Citation(s) in RCA: 59] [Impact Index Per Article: 19.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 08/10/2021] [Accepted: 08/27/2021] [Indexed: 11/26/2022] Open
Abstract
The first phase of the Human Connectome Project pioneered advances in MRI technology for mapping the macroscopic structural connections of the living human brain through the engineering of a whole-body human MRI scanner equipped with maximum gradient strength of 300 mT/m, the highest ever achieved for human imaging. While this instrument has made important contributions to the understanding of macroscale connectional topology, it has also demonstrated the potential of dedicated high-gradient performance scanners to provide unparalleled in vivo assessment of neural tissue microstructure. Building on the initial groundwork laid by the original Connectome scanner, we have now embarked on an international, multi-site effort to build the next-generation human 3T Connectome scanner (Connectome 2.0) optimized for the study of neural tissue microstructure and connectional anatomy across multiple length scales. In order to maximize the resolution of this in vivo microscope for studies of the living human brain, we will push the diffusion resolution limit to unprecedented levels by (1) nearly doubling the current maximum gradient strength from 300 mT/m to 500 mT/m and tripling the maximum slew rate from 200 T/m/s to 600 T/m/s through the design of a one-of-a-kind head gradient coil optimized to minimize peripheral nerve stimulation; (2) developing high-sensitivity multi-channel radiofrequency receive coils for in vivo and ex vivo human brain imaging; (3) incorporating dynamic field monitoring to minimize image distortions and artifacts; (4) developing new pulse sequences to integrate the strongest diffusion encoding and highest spatial resolution ever achieved in the living human brain; and (5) calibrating the measurements obtained from this next-generation instrument through systematic validation of diffusion microstructural metrics in high-fidelity phantoms and ex vivo brain tissue at progressively finer scales with accompanying diffusion simulations in histology-based micro-geometries. We envision creating the ultimate diffusion MRI instrument capable of capturing the complex multi-scale organization of the living human brain - from the microscopic scale needed to probe cellular geometry, heterogeneity and plasticity, to the mesoscopic scale for quantifying the distinctions in cortical structure and connectivity that define cyto- and myeloarchitectonic boundaries, to improvements in estimates of macroscopic connectivity.
Collapse
Affiliation(s)
- Susie Y Huang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
| | | | - Boris Keil
- Institute of Medical Physics and Radiation Protection (IMPS), TH-Mittelhessen University of Applied Sciences (THM), Giessen, Germany
| | - Alina Scholz
- Institute of Medical Physics and Radiation Protection (IMPS), TH-Mittelhessen University of Applied Sciences (THM), Giessen, Germany
| | - Mathias Davids
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | | | | | | | - John E Kirsch
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Anastasia Yendiki
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Qiuyun Fan
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Qiyuan Tian
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Gabriel Ramos-Llordén
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Hong-Hsi Lee
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Aapo Nummenmaa
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Kawin Setsompop
- Radiological Sciences Laboratory, Department of Radiology, Stanford University, Stanford, CA, USA
| | - Fuyixue Wang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Alexandru V Avram
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Michal Komlosh
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Dan Benjamini
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Kulam Najmudeen Magdoom
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Sudhir Pathak
- Learning Research and Development Center, University of Pittsburgh, Pittsburgh, PA, USA
| | - Walter Schneider
- Learning Research and Development Center, University of Pittsburgh, Pittsburgh, PA, USA
| | - Dmitry S Novikov
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA; Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, New York, NY, USA
| | - Els Fieremans
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA; Center for Advanced Imaging Innovation and Research (CAI2R), New York University School of Medicine, New York, NY, USA
| | - Slimane Tounekti
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Choukri Mekkaoui
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Jean Augustinack
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Daniel Berger
- Department of Molecular and Cell Biology and Center for Brain Science, Harvard University, Cambridge, MA, USA
| | - Alexander Shapson-Coe
- Department of Molecular and Cell Biology and Center for Brain Science, Harvard University, Cambridge, MA, USA
| | - Jeff Lichtman
- Department of Molecular and Cell Biology and Center for Brain Science, Harvard University, Cambridge, MA, USA
| | - Peter J Basser
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Lawrence L Wald
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Bruce R Rosen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| |
Collapse
|
42
|
Grisot G, Haber SN, Yendiki A. Diffusion MRI and anatomic tracing in the same brain reveal common failure modes of tractography. Neuroimage 2021; 239:118300. [PMID: 34171498 PMCID: PMC8475636 DOI: 10.1016/j.neuroimage.2021.118300] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Revised: 04/29/2021] [Accepted: 06/21/2021] [Indexed: 12/15/2022] Open
Abstract
Anatomic tracing is recognized as a critical source of knowledge on brain circuitry that can be used to assess the accuracy of diffusion MRI (dMRI) tractography. However, most prior studies that have performed such assessments have used dMRI and tracer data from different brains and/or have been limited in the scope of dMRI analysis methods allowed by the data. In this work, we perform a quantitative, voxel-wise comparison of dMRI tractography and anatomic tracing data in the same macaque brain. An ex vivo dMRI acquisition with high angular resolution and high maximum b-value allows us to compare a range of q-space sampling, orientation reconstruction, and tractography strategies. The availability of tracing in the same brain allows us to localize the sources of tractography errors and to identify axonal configurations that lead to such errors consistently, across dMRI acquisition and analysis strategies. We find that these common failure modes involve geometries such as branching or turning, which cannot be modeled well by crossing fibers. We also find that the default thresholds that are commonly used in tractography correspond to rather conservative, low-sensitivity operating points. While deterministic tractography tends to have higher sensitivity than probabilistic tractography in that very conservative threshold regime, the latter outperforms the former as the threshold is relaxed to avoid missing true anatomical connections. On the other hand, the q-space sampling scheme and maximum b-value have less of an impact on accuracy. Finally, using scans from a set of additional macaque brains, we show that there is enough inter-individual variability to warrant caution when dMRI and tracer data come from different animals, as is often the case in the tractography validation literature. Taken together, our results provide insights on the limitations of current tractography methods and on the critical role that anatomic tracing can play in identifying potential avenues for improvement.
Collapse
Affiliation(s)
| | - Suzanne N Haber
- Department of Pharmacology and Physiology, University of Rochester, Rochester, NY, United States; McLean Hospital, Belmont, MA, United States
| | - Anastasia Yendiki
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States.
| |
Collapse
|
43
|
Maiti S, Frielinghaus H, Gräßel D, Dulle M, Axer M, Förster S. Distribution and orientation of nerve fibers and myelin assembly in a brain section retrieved by small-angle neutron scattering. Sci Rep 2021; 11:17306. [PMID: 34453063 PMCID: PMC8397781 DOI: 10.1038/s41598-021-92995-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Accepted: 05/24/2021] [Indexed: 11/29/2022] Open
Abstract
The structural connectivity of the brain has been addressed by various imaging techniques such as diffusion weighted magnetic resonance imaging (DWMRI) or specific microscopic approaches based on histological staining or label-free using polarized light (e.g., three-dimensional Polarized Light Imaging (3D-PLI), Optical Coherence Tomography (OCT)). These methods are sensitive to different properties of the fiber enwrapping myelin sheaths i.e. the distribution of myelin basic protein (histology), the apparent diffusion coefficient of water molecules restricted in their movements by the myelin sheath (DWMRI), and the birefringence of the oriented myelin lipid bilayers (3D-PLI, OCT). We show that the orientation and distribution of nerve fibers as well as myelin in thin brain sections can be determined using scanning small angle neutron scattering (sSANS). Neutrons are scattered from the fiber assembly causing anisotropic diffuse small-angle scattering and Bragg peaks related to the highly ordered periodic myelin multilayer structure. The scattering anisotropy, intensity, and angular position of the Bragg peaks can be mapped across the entire brain section. This enables mapping of the fiber and myelin distribution and their orientation in a thin brain section, which was validated by 3D-PLI. The experiments became possible by optimizing the neutron beam collimation to highest flux and enhancing the myelin contrast by deuteration. This method is very sensitive to small microstructures of biological tissue and can directly extract information on the average fiber orientation and even myelin membrane thickness. The present results pave the way toward bio-imaging for detecting structural aberrations causing neurological diseases in future.
Collapse
Affiliation(s)
- Santanu Maiti
- Jülich Centre of Neutron Science (JCNS-1/IBI-8), Forschungszentrum Jülich GmbH, 52425, Jülich, Germany.,Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich GmbH, 52425, Jülich, Germany
| | - Henrich Frielinghaus
- Jülich Centre for Neutron Science at Heinz Maier-Leibnitz Zentrum (JCNS-MLZ), Forschungszentrum Jülich GmbH, 85748, Garching, Germany
| | - David Gräßel
- Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich GmbH, 52425, Jülich, Germany
| | - Martin Dulle
- Jülich Centre of Neutron Science (JCNS-1/IBI-8), Forschungszentrum Jülich GmbH, 52425, Jülich, Germany
| | - Markus Axer
- Institute of Neuroscience and Medicine (INM-1), Forschungszentrum Jülich GmbH, 52425, Jülich, Germany
| | - Stephan Förster
- Jülich Centre of Neutron Science (JCNS-1/IBI-8), Forschungszentrum Jülich GmbH, 52425, Jülich, Germany. .,Institute of Physical Chemistry, RWTH Aachen University, 52074, Aachen, Germany.
| |
Collapse
|
44
|
Trinkle S, Foxley S, Kasthuri N, Rivière PL. Synchrotron X-ray micro-CT as a validation dataset for diffusion MRI in whole mouse brain. Magn Reson Med 2021; 86:1067-1076. [PMID: 33768633 PMCID: PMC8076078 DOI: 10.1002/mrm.28776] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2020] [Revised: 01/26/2021] [Accepted: 02/28/2021] [Indexed: 12/13/2022]
Abstract
PURPOSE To introduce synchrotron X-ray microcomputed tomography (microCT) and demonstrate its use as a natively isotropic, nondestructive, 3D validation modality for diffusion MRI in whole, fixed mouse brain. METHODS Postmortem diffusion MRI and microCT data were acquired of the same whole mouse brain. Diffusion data were processed using constrained spherical deconvolution. Synchrotron data were acquired at an isotropic voxel size of 1.17 μm. Structure tensor analysis was used to calculate fiber orientation distribution functions from the microCT data. A pipeline was developed to spatially register the 2 datasets in order to perform qualitative comparisons of fiber geometries represented by fiber orientation distribution functions. Fiber orientations from both modalities were used to perform whole-brain deterministic tractography to demonstrate validation of long-range white matter pathways. RESULTS Fiber orientation distribution functions were able to be extracted throughout the entire microCT dataset, with spatial registration to diffusion MRI simplified due to the whole brain extent of the microCT data. Fiber orientations and tract pathways showed good agreement between modalities. CONCLUSION Synchrotron microCT is a potentially valuable new tool for future multi-scale diffusion MRI validation studies, providing comparable value to optical histology validation methods while addressing some key limitations in data acquisition and ease of processing.
Collapse
Affiliation(s)
- Scott Trinkle
- Department of Radiology, University of Chicago, Chicago, IL, USA
| | - Sean Foxley
- Department of Radiology, University of Chicago, Chicago, IL, USA
| | | | | |
Collapse
|
45
|
Gooijers J, De Luca A, Zivari Adab H, Leemans A, Roebroeck A, Swinnen SP. Indices of callosal axonal density and radius from diffusion MRI relate to upper and lower limb motor performance. Neuroimage 2021; 241:118433. [PMID: 34324975 DOI: 10.1016/j.neuroimage.2021.118433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Revised: 07/15/2021] [Accepted: 07/26/2021] [Indexed: 11/16/2022] Open
Abstract
Understanding the relationship between human brain structure and functional outcome is of critical importance in systems neuroscience. Diffusion MRI (dMRI) studies show that fractional anisotropy (FA) is predictive of motor control, underscoring the importance of white matter (WM). However, as FA is a surrogate marker of WM, we aim to shed new light on the structural underpinnings of this relationship by applying a multi-compartment microstructure model providing axonal density/radius indices. Sixteen young adults (7 males / 9 females), performed a hand/foot tapping task and a Multi Limb Reaction Time task. Furthermore, diffusion (STEAM &HARDI) and fMRI (localizer hand/foot activations) data were obtained. Sphere ROIs were placed on activation clusters with highest t value to guide interhemispheric WM tractography. Axonal radius/density indices of callosal parts intersecting with tractography were calculated from STEAM, using the diffusion-time dependent AxCaliber model, and correlated with behavior. Results indicated a possible association between larger apparent axonal radii of callosal motor fibers of the hand and higher tapping scores of both hands, and faster selection-related processing (normalized reaction) times (RTs) on diagonal limb combinations. Additionally, a trend was present for faster selection-related processing (normalized reaction) times for lower limbs being related with higher axonal density of callosal foot motor fibers, and for higher FA values of callosal motor fibers in general being related with better tapping and faster selection-related processing (normalized reaction) times. Whereas FA is sensitive in demonstrating associations with motor behavior, axon radius/density (i.e., fiber geometry) measures are promising to explain the physiological source behind the observed FA changes, contributing to deeper insights into brain-behavior interactions.
Collapse
Affiliation(s)
- J Gooijers
- Movement Control and Neuroplasticity Research Group, Department of Movement Sciences, KU Leuven, Leuven (3000), Belgium; LBI-KU Leuven Brain Institute, Leuven (3000), Belgium.
| | - A De Luca
- PROVIDI Lab, Image Sciences Institute, University Medical Center Utrecht, Utrecht 3584 CX, Netherlands; Neurology Department, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht 3584 CX, Netherlands
| | - H Zivari Adab
- Movement Control and Neuroplasticity Research Group, Department of Movement Sciences, KU Leuven, Leuven (3000), Belgium; LBI-KU Leuven Brain Institute, Leuven (3000), Belgium
| | - A Leemans
- PROVIDI Lab, Image Sciences Institute, University Medical Center Utrecht, Utrecht 3584 CX, Netherlands
| | - A Roebroeck
- Department of Cognitive Neuroscience, Faculty of Psychology & Neuroscience, Maastricht University, Maastricht 6229 EV, Netherlands
| | - S P Swinnen
- Movement Control and Neuroplasticity Research Group, Department of Movement Sciences, KU Leuven, Leuven (3000), Belgium; LBI-KU Leuven Brain Institute, Leuven (3000), Belgium
| |
Collapse
|
46
|
Lohkamp KJ, Kiliaan AJ, Shenk J, Verweij V, Wiesmann M. The Impact of Voluntary Exercise on Stroke Recovery. Front Neurosci 2021; 15:695138. [PMID: 34321996 PMCID: PMC8311567 DOI: 10.3389/fnins.2021.695138] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Accepted: 06/15/2021] [Indexed: 12/29/2022] Open
Abstract
Stroke treatment is limited to time-critical thrombectomy and rehabilitation by physiotherapy. Studies report beneficial effects of exercise; however, a knowledge gap exists regarding underlying mechanisms that benefit recovery of brain networks and cognition. This study aims to unravel therapeutic effects of voluntary exercise in stroke-induced mice to develop better personalized treatments. Male C57Bl6/JOlaHsd mice were subjected to transient middle cerebral artery occlusion. After surgery, the animals were divided in a voluntary exercise group with access to running wheels (RW), and a control group without running wheels (NRW). During 6 days post-stroke, activity/walking patterns were measured 24/7 in digital ventilated cages. Day 7 post-surgery, animals underwent MRI scanning (11.7T) to investigate functional connectivity (rsfMRI) and white matter (WM) integrity (DTI). Additionally, postmortem polarized light imaging (PLI) was performed to quantify WM fiber density and orientation. After MRI the animals were sacrificed and neuroinflammation and cerebral vascularisation studied. Voluntary exercise promoted myelin density recovery corresponding to higher fractional anisotropy. The deteriorating impact of stroke on WM dispersion was detected only in NRW mice. Moreover, rsfMRI revealed increased functional connectivity, cerebral blood flow and vascular quality leading to improved motor skills in the RW group. Furthermore, voluntary exercise showed immunomodulatory properties post-stroke. This study not only helped determining the therapeutic value of voluntary exercise, but also provided understanding of pathological mechanisms involved in stroke.
Collapse
Affiliation(s)
- Klara J Lohkamp
- Department of Medical Imaging, Anatomy, Radboud University Medical Center, Preclinical Imaging Center - PRIME, Radboud Alzheimer Center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, Netherlands
| | - Amanda J Kiliaan
- Department of Medical Imaging, Anatomy, Radboud University Medical Center, Preclinical Imaging Center - PRIME, Radboud Alzheimer Center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, Netherlands
| | - Justin Shenk
- Department of Medical Imaging, Anatomy, Radboud University Medical Center, Preclinical Imaging Center - PRIME, Radboud Alzheimer Center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, Netherlands
| | - Vivienne Verweij
- Department of Medical Imaging, Anatomy, Radboud University Medical Center, Preclinical Imaging Center - PRIME, Radboud Alzheimer Center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, Netherlands
| | - Maximilian Wiesmann
- Department of Medical Imaging, Anatomy, Radboud University Medical Center, Preclinical Imaging Center - PRIME, Radboud Alzheimer Center, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, Netherlands
| |
Collapse
|
47
|
Scan-rescan repeatability of axonal imaging metrics using high-gradient diffusion MRI and statistical implications for study design. Neuroimage 2021; 240:118323. [PMID: 34216774 PMCID: PMC8646020 DOI: 10.1016/j.neuroimage.2021.118323] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Revised: 05/12/2021] [Accepted: 06/26/2021] [Indexed: 11/29/2022] Open
Abstract
Axon diameter mapping using diffusion MRI in the living human brain has attracted growing interests with the increasing availability of high gradient strength MRI systems. A systematic assessment of the consistency of axon diameter estimates within and between individuals is needed to gain a comprehensive understanding of how such methods extend to quantifying differences in axon diameter index between groups and facilitate the design of neurobiological studies using such measures. We examined the scan-rescan repeatability of axon diameter index estimation based on the spherical mean technique (SMT) approach using diffusion MRI data acquired with gradient strengths up to 300 mT/m on a 3T Connectom system in 7 healthy volunteers. We performed statistical power analyses using data acquired with the same protocol in a larger cohort consisting of 15 healthy adults to investigate the implications for study design. Results revealed a high degree of repeatability in voxel-wise restricted volume fraction estimates and tract-wise estimates of axon diameter index derived from high-gradient diffusion MRI data. On the region of interest (ROI) level, across white matter tracts in the whole brain, the Pearson’s correlation coefficient of the axon diameter index estimated between scan and rescan experiments was r = 0.72 with an absolute deviation of 0.18 μm. For an anticipated 10% effect size in studies of axon diameter index, most white matter regions required a sample size of less than 15 people to observe a measurable difference between groups using an ROI-based approach. To facilitate the use of high-gradient strength diffusion MRI data for neuroscientific studies of axonal microstructure, the comprehensive multi-gradient strength, multi-diffusion time data used in this work will be made publicly available, in support of open science and increasing the accessibility of such data to the greater scientific community.
Collapse
|
48
|
Granziera C, Wuerfel J, Barkhof F, Calabrese M, De Stefano N, Enzinger C, Evangelou N, Filippi M, Geurts JJG, Reich DS, Rocca MA, Ropele S, Rovira À, Sati P, Toosy AT, Vrenken H, Gandini Wheeler-Kingshott CAM, Kappos L. Quantitative magnetic resonance imaging towards clinical application in multiple sclerosis. Brain 2021; 144:1296-1311. [PMID: 33970206 PMCID: PMC8219362 DOI: 10.1093/brain/awab029] [Citation(s) in RCA: 73] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2020] [Revised: 10/25/2020] [Accepted: 11/16/2020] [Indexed: 12/11/2022] Open
Abstract
Quantitative MRI provides biophysical measures of the microstructural integrity of the CNS, which can be compared across CNS regions, patients, and centres. In patients with multiple sclerosis, quantitative MRI techniques such as relaxometry, myelin imaging, magnetization transfer, diffusion MRI, quantitative susceptibility mapping, and perfusion MRI, complement conventional MRI techniques by providing insight into disease mechanisms. These include: (i) presence and extent of diffuse damage in CNS tissue outside lesions (normal-appearing tissue); (ii) heterogeneity of damage and repair in focal lesions; and (iii) specific damage to CNS tissue components. This review summarizes recent technical advances in quantitative MRI, existing pathological validation of quantitative MRI techniques, and emerging applications of quantitative MRI to patients with multiple sclerosis in both research and clinical settings. The current level of clinical maturity of each quantitative MRI technique, especially regarding its integration into clinical routine, is discussed. We aim to provide a better understanding of how quantitative MRI may help clinical practice by improving stratification of patients with multiple sclerosis, and assessment of disease progression, and evaluation of treatment response.
Collapse
Affiliation(s)
- Cristina Granziera
- Neurologic 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
| | - Jens Wuerfel
- Medical Image Analysis Center, Basel, Switzerland
- Quantitative Biomedical Imaging Group (qbig), Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, multiple sclerosis Center Amsterdam, Amsterdam University Medical Center, Amsterdam, The Netherlands
- UCL Institutes of Healthcare Engineering and Neurology, London, UK
| | - Massimiliano Calabrese
- Neurology B, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Nicola De Stefano
- Neurology, Department of Medicine, Surgery and Neuroscience, University of Siena, Italy
| | - Christian Enzinger
- Department of Neurology and Division of Neuroradiology, Medical University of Graz, Graz, Austria
| | - Nikos Evangelou
- Division of Clinical Neuroscience, University of Nottingham, Nottingham, UK
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, multiple sclerosis Center Amsterdam, Neuroscience Amsterdam, Amsterdam University Medical Centers, location VUmc, Amsterdam, The Netherlands
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), Bethesda, MD, USA
| | - Maria A Rocca
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, and Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Stefan Ropele
- Neuroimaging Research Unit, Department of Neurology, Medical University of Graz, Graz, Austria
| | - Àlex Rovira
- Section of Neuroradiology (Department of Radiology), Vall d'Hebron University Hospital and Research Institute, Barcelona, Spain
| | - Pascal Sati
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health (NIH), Bethesda, MD, USA
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Ahmed T Toosy
- Queen Square multiple sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, University College London, London, UK
| | - Hugo Vrenken
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, multiple sclerosis Center Amsterdam, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Claudia A M Gandini Wheeler-Kingshott
- Queen Square multiple sclerosis Centre, Department of Neuroinflammation, Queen Square Institute of Neurology, University College London, London, UK
- Department of Brain and Behavioural Sciences, University of Pavia, Pavia, Italy
- Brain MRI 3T Research Centre, IRCCS Mondino Foundation, Pavia, Italy
| | - Ludwig Kappos
- Neurologic 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
| |
Collapse
|
49
|
Scholz A, Etzel R, May MW, Mahmutovic M, Tian Q, Ramos-Llordén G, Maffei C, Bilgiç B, Witzel T, Stockmann JP, Mekkaoui C, Wald LL, Huang SY, Yendiki A, Keil B. A 48-channel receive array coil for mesoscopic diffusion-weighted MRI of ex vivo human brain on the 3 T connectome scanner. Neuroimage 2021; 238:118256. [PMID: 34118399 PMCID: PMC8439104 DOI: 10.1016/j.neuroimage.2021.118256] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Revised: 06/04/2021] [Accepted: 06/07/2021] [Indexed: 12/14/2022] Open
Abstract
In vivo diffusion-weighted magnetic resonance imaging is limited in signal-to-noise-ratio (SNR) and acquisition time, which constrains spatial resolution to the macroscale regime. Ex vivo imaging, which allows for arbitrarily long scan times, is critical for exploring human brain structure in the mesoscale regime without loss of SNR. Standard head array coils designed for patients are sub-optimal for imaging ex vivo whole brain specimens. The goal of this work was to design and construct a 48-channel ex vivo whole brain array coil for high-resolution and high b-value diffusion-weighted imaging on a 3T Connectome scanner. The coil was validated with bench measurements and characterized by imaging metrics on an agar brain phantom and an ex vivo human brain sample. The two-segment coil former was constructed for a close fit to a whole human brain, with small receive elements distributed over the entire brain. Imaging tests including SNR and G-factor maps were compared to a 64-channel head coil designed for in vivo use. There was a 2.9-fold increase in SNR in the peripheral cortex and a 1.3-fold gain in the center when compared to the 64-channel head coil. The 48-channel ex vivo whole brain coil also decreases noise amplification in highly parallel imaging, allowing acceleration factors of approximately one unit higher for a given noise amplification level. The acquired diffusion-weighted images in a whole ex vivo brain specimen demonstrate the applicability and advantage of the developed coil for high-resolution and high b-value diffusion-weighted ex vivo brain MRI studies.
Collapse
Affiliation(s)
- Alina Scholz
- Institute of Medical Physics and Radiation Protection (IMPS), TH-Mittelhessen University of Applied Sciences (THM), 14 Wiesenstrasse, Giessen 35390, Germany.
| | - Robin Etzel
- Institute of Medical Physics and Radiation Protection (IMPS), TH-Mittelhessen University of Applied Sciences (THM), 14 Wiesenstrasse, Giessen 35390, Germany
| | - Markus W May
- Institute of Medical Physics and Radiation Protection (IMPS), TH-Mittelhessen University of Applied Sciences (THM), 14 Wiesenstrasse, Giessen 35390, Germany
| | - Mirsad Mahmutovic
- Institute of Medical Physics and Radiation Protection (IMPS), TH-Mittelhessen University of Applied Sciences (THM), 14 Wiesenstrasse, Giessen 35390, Germany
| | - Qiyuan Tian
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Gabriel Ramos-Llordén
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Chiara Maffei
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Berkin Bilgiç
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, USA
| | - Thomas Witzel
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Jason P Stockmann
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Choukri Mekkaoui
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Lawrence L Wald
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, USA
| | - Susie Yi Huang
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, USA
| | - Anastasia Yendiki
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Boris Keil
- Institute of Medical Physics and Radiation Protection (IMPS), TH-Mittelhessen University of Applied Sciences (THM), 14 Wiesenstrasse, Giessen 35390, Germany; Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| |
Collapse
|
50
|
Evangelou E, Suzuki H, Bai W, Pazoki R, Gao H, Matthews PM, Elliott P. Alcohol consumption in the general population is associated with structural changes in multiple organ systems. eLife 2021; 10:65325. [PMID: 34059199 PMCID: PMC8192119 DOI: 10.7554/elife.65325] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 06/01/2021] [Indexed: 12/15/2022] Open
Abstract
Background: Excessive alcohol consumption is associated with damage to various organs, but its multi-organ effects have not been characterised across the usual range of alcohol drinking in a large general population sample. Methods: We assessed global effect sizes of alcohol consumption on quantitative magnetic resonance imaging phenotypic measures of the brain, heart, aorta, and liver of UK Biobank participants who reported drinking alcohol. Results: We found a monotonic association of higher alcohol consumption with lower normalised brain volume across the range of alcohol intakes (–1.7 × 10−3 ± 0.76 × 10−3 per doubling of alcohol consumption, p=3.0 × 10−14). Alcohol consumption was also associated directly with measures of left ventricular mass index and left ventricular and atrial volume indices. Liver fat increased by a mean of 0.15% per doubling of alcohol consumption. Conclusions: Our results imply that there is not a ‘safe threshold’ below which there are no toxic effects of alcohol. Current public health guidelines concerning alcohol consumption may need to be revisited. Funding: See acknowledgements.
Collapse
Affiliation(s)
- Evangelos Evangelou
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom.,Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece
| | - Hideaki Suzuki
- Department of Cardiovascular Medicine, Tohoku University Hospital, Sendai, Japan.,Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.,Department of Brain Sciences, Imperial College London, London, United Kingdom
| | - Wenjia Bai
- Department of Brain Sciences, Imperial College London, London, United Kingdom.,Data Science Institute, Imperial College London, London, United Kingdom
| | - Raha Pazoki
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.,Division of Biomedical Sciences, Department of Life Sciences, College of Health, Medicine and Life Sciences, Brunel University London, London, United Kingdom
| | - He Gao
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom.,MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom
| | - Paul M Matthews
- Department of Brain Sciences, Imperial College London, London, United Kingdom.,UK Dementia Research Institute at Imperial College London, London, United Kingdom.,National Institute for Health Research Imperial College Biomedical Research Centre, Imperial College London, London, United Kingdom
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom.,MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom.,UK Dementia Research Institute at Imperial College London, London, United Kingdom.,National Institute for Health Research Imperial College Biomedical Research Centre, Imperial College London, London, United Kingdom.,British Heart Foundation Centre for Research Excellence, Imperial College London, London, United Kingdom
| |
Collapse
|