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      Modeling cerebrospinal fluid dynamics across the entire intracranial space through integration of four-dimensional flow and intravoxel incoherent motion magnetic resonance imaging

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          Abstract

          Background

          Bidirectional reciprocal motion of cerebrospinal fluid (CSF) was quantified using four-dimensional (4D) flow magnetic resonance imaging (MRI) and intravoxel incoherent motion (IVIM) MRI. To estimate various CSF motions in the entire intracranial region, we attempted to integrate the flow parameters calculated using the two MRI sequences. To elucidate how CSF dynamics deteriorate in Hakim’s disease, an age-dependent chronic hydrocephalus, flow parameters were estimated from the two MRI sequences to assess CSF motion in the entire intracranial region.

          Methods

          This study included 127 healthy volunteers aged ≥ 20 years and 44 patients with Hakim’s disease. On 4D flow MRI for measuring CSF motion, velocity encoding was set at 5 cm/s. For the IVIM MRI analysis, the diffusion-weighted sequence was set at six b-values (i.e., 0, 50, 100, 250, 500, and 1000 s/mm 2), and the biexponential IVIM fitting method was adapted. The relationships between the fraction of incoherent perfusion ( f) on IVIM MRI and 4D flow MRI parameters including velocity amplitude (VA), absolute maximum velocity, stroke volume, net flow volume, and reverse flow rate were comprehensively evaluated in seven locations in the ventricles and subarachnoid spaces. Furthermore, we developed a new parameter for fluid oscillation, the Fluid Oscillation Index (FOI), by integrating these two measurements. In addition, we investigated the relationship between the measurements and indices specific to Hakim’s disease and the FOIs in the entire intracranial space.

          Results

          The VA on 4D flow MRI was significantly associated with the mean f-values on IVIM MRI. Therefore, we estimated VA that could not be directly measured on 4D flow MRI from the mean f-values on IVIM MRI in the intracranial CSF space, using the following formula; e 0.2( f−85)  + 0.25. To quantify fluid oscillation using one integrated parameter with weighting, FOI was calculated as VA × 10 +  f × 0.02. In addition, the FOIs at the left foramen of Luschka had the strongest correlations with the Evans index (Pearson’s correlation coefficient: 0.78). The other indices related with Hakim’s disease were significantly associated with the FOIs at the cerebral aqueduct and bilateral foramina of Luschka. FOI at the cerebral aqueduct was also elevated in healthy controls aged ≥ 60 years.

          Conclusions

          We estimated pulsatile CSF movements in the entire intracranial CSF space in healthy individuals and patients with Hakim’s disease using FOI integrating VA from 4D flow MRI and f-values from IVIM MRI. FOI is useful for quantifying the CSF oscillation.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12987-024-00552-6.

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          Most cited references52

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          A paravascular pathway facilitates CSF flow through the brain parenchyma and the clearance of interstitial solutes, including amyloid β.

          Because it lacks a lymphatic circulation, the brain must clear extracellular proteins by an alternative mechanism. The cerebrospinal fluid (CSF) functions as a sink for brain extracellular solutes, but it is not clear how solutes from the brain interstitium move from the parenchyma to the CSF. We demonstrate that a substantial portion of subarachnoid CSF cycles through the brain interstitial space. On the basis of in vivo two-photon imaging of small fluorescent tracers, we showed that CSF enters the parenchyma along paravascular spaces that surround penetrating arteries and that brain interstitial fluid is cleared along paravenous drainage pathways. Animals lacking the water channel aquaporin-4 (AQP4) in astrocytes exhibit slowed CSF influx through this system and a ~70% reduction in interstitial solute clearance, suggesting that the bulk fluid flow between these anatomical influx and efflux routes is supported by astrocytic water transport. Fluorescent-tagged amyloid β, a peptide thought to be pathogenic in Alzheimer's disease, was transported along this route, and deletion of the Aqp4 gene suppressed the clearance of soluble amyloid β, suggesting that this pathway may remove amyloid β from the central nervous system. Clearance through paravenous flow may also regulate extracellular levels of proteins involved with neurodegenerative conditions, its impairment perhaps contributing to the mis-accumulation of soluble proteins.
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            Sleep drives metabolite clearance from the adult brain.

            The conservation of sleep across all animal species suggests that sleep serves a vital function. We here report that sleep has a critical function in ensuring metabolic homeostasis. Using real-time assessments of tetramethylammonium diffusion and two-photon imaging in live mice, we show that natural sleep or anesthesia are associated with a 60% increase in the interstitial space, resulting in a striking increase in convective exchange of cerebrospinal fluid with interstitial fluid. In turn, convective fluxes of interstitial fluid increased the rate of β-amyloid clearance during sleep. Thus, the restorative function of sleep may be a consequence of the enhanced removal of potentially neurotoxic waste products that accumulate in the awake central nervous system.
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              Brain charts for the human lifespan

              Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight 1 . Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data ( http://www.brainchart.io/ ). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories 2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones 3 , showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes. MRI data from more than 100 studies have been aggregated to yield new insights about brain development and ageing, and create an interactive open resource for comparison of brain structures throughout the human lifespan, including those associated with neurological and psychiatric disorders.
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                Author and article information

                Contributors
                shigekiyamada393@gmail.com
                Journal
                Fluids Barriers CNS
                Fluids Barriers CNS
                Fluids and Barriers of the CNS
                BioMed Central (London )
                2045-8118
                30 May 2024
                30 May 2024
                2024
                : 21
                : 47
                Affiliations
                [1 ]Department of Neurosurgery, Nagoya City University Graduate School of Medical Science, ( https://ror.org/04wn7wc95) Kawasumi 1, Mizuho-Cho, Mizuho-Ku, Nagoya, Aichi 467-8601 Japan
                [2 ]Interfaculty Initiative in Information Studies/Institute of Industrial Science, The University of Tokyo, ( https://ror.org/057zh3y96) Tokyo, Japan
                [3 ]Department of Mechanical Science and Bioengineering, Graduate School of Engineering Science, Osaka University, ( https://ror.org/035t8zc32) Osaka, Japan
                [4 ]Department of Mechanical Engineering, School of Engineering, Tokyo Institute of Technology, ( https://ror.org/0112mx960) Tokyo, Japan
                [5 ]Faculty of System Design, Tokyo Metropolitan University, ( https://ror.org/00ws30h19) Tokyo, Japan
                [6 ]GRID grid.410862.9, ISNI 0000 0004 1770 2279, Medical System Research & Development Center, , FUJIFILM Corporation, ; Tokyo, Japan
                [7 ]Department of Behavioural Neurology and Cognitive Neuroscience, Tohoku University Graduate School of Medicine, ( https://ror.org/01dq60k83) Sendai, Miyagi Japan
                [8 ]Division of Neurology and Clinical Neuroscience, Department of Internal Medicine III, Yamagata University School of Medicine, ( https://ror.org/00xy44n04) Yamagata, Japan
                [9 ]Department of Radiology, Shiga University of Medical Science, ( https://ror.org/00d8gp927) Shiga, Japan
                Author information
                http://orcid.org/0000-0001-7158-5569
                Article
                552
                10.1186/s12987-024-00552-6
                11138021
                38816737
                b874949d-e0c9-48c2-9cb6-f056f1496f69
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 17 December 2023
                : 21 May 2024
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001691, Japan Society for the Promotion of Science;
                Award ID: 21K09098
                Award ID: 22H03020
                Award ID: 22H00190
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100002424, Fujifilm Corporation;
                Funded by: G-7 Scholarship Foundation
                Funded by: FundRef http://dx.doi.org/10.13039/501100008927, Osaka Gas Group Welfare Foundation;
                Funded by: FundRef http://dx.doi.org/10.13039/100016289, Taiju Life Social Welfare Foundation;
                Funded by: FundRef http://dx.doi.org/10.13039/501100001700, Ministry of Education, Culture, Sports, Science and Technology;
                Award ID: DJPMXP1020230118
                Award Recipient :
                Categories
                Research
                Custom metadata
                © BioMed Central Ltd., part of Springer Nature 2024

                Neurology
                cerebrospinal fluid dynamics,idiopathic normal pressure hydrocephalus,aging,hakim’s disease,csf motion,fluid oscillation,4d flow mri,intravoxel incoherent motion,diffusion-weighted image

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