For Publishers
DiscoveryMetadataPeer reviewHostingPublishing
For Researchers
JoinPublishReviewCollect
Register
Blog
About
Search
Advanced search
My ScienceOpen
Search
For Publishers
For Researchers
Blog
About
3
views
64
references
 Top references
cited by
6
    
0 reviews
 Review
0
comments
 Comment
0
recommends
+1 Recommend
0 collections
    0
    shares
      150
      similar
       All similar
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Transient changes in white matter microstructure during general anesthesia

      research-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Cognitive dysfunction after surgery under general anesthesia is a well-recognized clinical phenomenon in the elderly. Physiological effects of various anesthetic agents have been studied at length. Very little is known about potential effects of anesthesia on brain structure. In this study we used Diffusion Tensor Imaging to compare the white matter microstructure of healthy control subjects under sevoflurane anesthesia with their awake state. Fractional Anisotropy, a white mater integrity index, transiently decreases throughout the brain during sevoflurane anesthesia and then returns back to baseline. Other DTI metrics such as mean diffusivity, axial diffusivity and radial diffusivity were increased under sevoflurane anesthesia. Although DTI metrics are age dependent, the transient changes due to sevoflurane were independent of age and sex. Volumetric analysis shows various white matter volumes decreased whereas some gray matter volumes increased during sevoflurane anesthesia. These results suggest that sevoflurane anesthesia has a significant, but transient, effect on white matter microstructure. In spite of the transient effects of sevoflurane anesthesia there were no measurable effects on brain white matter as determined by the DTI metrics at 2 days and 7 days following anesthesia. The role of white matter in the loss of consciousness under anesthesia will need to be studied and MRI studies with subjects under anesthesia will need to take these results into account.

          Related collections

          Most cited references64

          • Record: found
          • Abstract: found
          • Article: not found

          An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest.

          Rahul Desikan, Florent Ségonne, Bruce Fischl … (2006)
          In this study, we have assessed the validity and reliability of an automated labeling system that we have developed for subdividing the human cerebral cortex on magnetic resonance images into gyral based regions of interest (ROIs). Using a dataset of 40 MRI scans we manually identified 34 cortical ROIs in each of the individual hemispheres. This information was then encoded in the form of an atlas that was utilized to automatically label ROIs. To examine the validity, as well as the intra- and inter-rater reliability of the automated system, we used both intraclass correlation coefficients (ICC), and a new method known as mean distance maps, to assess the degree of mismatch between the manual and the automated sets of ROIs. When compared with the manual ROIs, the automated ROIs were highly accurate, with an average ICC of 0.835 across all of the ROIs, and a mean distance error of less than 1 mm. Intra- and inter-rater comparisons yielded little to no difference between the sets of ROIs. These findings suggest that the automated method we have developed for subdividing the human cerebral cortex into standard gyral-based neuroanatomical regions is both anatomically valid and reliable. This method may be useful for both morphometric and functional studies of the cerebral cortex as well as for clinical investigations aimed at tracking the evolution of disease-induced changes over time, including clinical trials in which MRI-based measures are used to examine response to treatment.
          Article 0 comments Cited 2718 times – based on 0 reviews     Review now
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Sleep drives metabolite clearance from the adult brain.

            Lulu Xie, Hongyi Kang, Qiwu Xu … (2013)
            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.
            Article 0 comments Cited 1025 times – based on 0 reviews     Review now
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Threshold-free cluster enhancement: addressing problems of smoothing, threshold dependence and localisation in cluster inference.

              Stephen Smith, Thomas Nichols (2009)
              Many image enhancement and thresholding techniques make use of spatial neighbourhood information to boost belief in extended areas of signal. The most common such approach in neuroimaging is cluster-based thresholding, which is often more sensitive than voxel-wise thresholding. However, a limitation is the need to define the initial cluster-forming threshold. This threshold is arbitrary, and yet its exact choice can have a large impact on the results, particularly at the lower (e.g., t, z < 4) cluster-forming thresholds frequently used. Furthermore, the amount of spatial pre-smoothing is also arbitrary (given that the expected signal extent is very rarely known in advance of the analysis). In the light of such problems, we propose a new method which attempts to keep the sensitivity benefits of cluster-based thresholding (and indeed the general concept of "clusters" of signal), while avoiding (or at least minimising) these problems. The method takes a raw statistic image and produces an output image in which the voxel-wise values represent the amount of cluster-like local spatial support. The method is thus referred to as "threshold-free cluster enhancement" (TFCE). We present the TFCE approach and discuss in detail ROC-based optimisation and comparisons with cluster-based and voxel-based thresholding. We find that TFCE gives generally better sensitivity than other methods over a wide range of test signal shapes and SNR values. We also show an example on a real imaging dataset, suggesting that TFCE does indeed provide not just improved sensitivity, but richer and more interpretable output than cluster-based thresholding.
              Article 0 comments Cited 939 times – based on 0 reviews     Review now
                Bookmark
                All references

                Author and article information

                Contributors
                Cheuk Y. Tang:
                ORCID: https://orcid.org/0000-0002-9828-0092
                Role: Data curationRole: Formal analysisRole: ResourcesRole: SoftwareRole: Writing – original draftRole: Writing – review & editing
                Victoria X. Wang: Role: ConceptualizationRole: Formal analysisRole: Project administrationRole: Writing – review & editing
                Min Yin Lun: Role: ConceptualizationRole: Formal analysisRole: ResourcesRole: Writing – review & editing
                Joshua S. Mincer:
                ORCID: https://orcid.org/0000-0002-2482-3154
                Role: Data curationRole: Project administrationRole: ResourcesRole: Supervision
                Johnny C. Ng: Role: Data curationRole: Formal analysisRole: Resources
                Jess W. Brallier: Role: Data curationRole: Resources
                Arthur E. Schwartz: Role: Data curationRole: Resources
                Helen Ahn: Role: Data curationRole: Resources
                Patrick J. McCormick:
                ORCID: https://orcid.org/0000-0002-7062-2409
                Role: Data curationRole: Resources
                Tommer Nir: Role: Data curationRole: Resources
                Bradley Delman: Role: Data curationRole: Resources
                Mary Sano: Role: ConceptualizationRole: Data curationRole: InvestigationRole: Resources
                Stacie G. Deiner: Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: Resources
                Mark G. Baxter: Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: SupervisionRole: Writing – review & editing
                Quan Jiang: Role: Editor
                Journal
                Journal ID (nlm-ta): PLoS One
                Journal ID (iso-abbrev): PLoS One
                Journal ID (publisher-id): plos
                Journal ID (pmc): plosone
                Title: PLoS ONE
                Publisher: Public Library of Science (San Francisco, CA USA )
                ISSN (Electronic): 1932-6203
                Publication date (Electronic): 26 March 2021
                Publication date Collection: 2021
                Publication date (Corrected, electronic): 6 April 2021
                Volume: 16
                Issue: 3
                Electronic Location Identifier: e0247678
                Affiliations
                [1 ] BioMedical Engineering Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
                [2 ] Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
                [3 ] Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
                [4 ] Department of Anesthesiology and Critical Care Medicine, Memorial Sloan Kettering Cancer, New York, NY, United States of America
                [5 ] Department of Anesthesiology, Perioperative and Pain Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
                [6 ] Department of Anesthesiology, Dartmouth Hitchcock, Lebanon, NH, United States of America
                Henry Ford Health System, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                https://orcid.org/0000-0002-9828-0092
                https://orcid.org/0000-0002-2482-3154
                https://orcid.org/0000-0002-7062-2409
                Article
                Publisher ID: PONE-D-20-30232
                DOI: 10.1371/journal.pone.0247678
                PMC ID: 7997710
                PubMed ID: 33770816
                SO-VID: aeeabb5b-8105-4888-ba23-889c2c2962aa
                Copyright © © 2021 Tang et al
                License:

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                Date received : 25 September 2020
                Date accepted : 10 February 2021
                Page count
                Figures: 4, Tables: 6, Pages: 19
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100000049, National Institute on Aging;
                Award ID: 5R01AG046634
                Award Recipient :
                This study was funded by: NIH 5R01AG046634, Trajectory of Recovery in the Elderly, PI: Mark Baxter (MB) The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Subject: Research Article
                Subject: Medicine and Health Sciences
                Subject: Anesthesiology
                Subject: Anesthesia
                Subject: Medicine and Health Sciences
                Subject: Pharmaceutics
                Subject: Drug Therapy
                Subject: Anesthesia
                Subject: Biology and Life Sciences
                Subject: Anatomy
                Subject: Nervous System
                Subject: Central Nervous System
                Subject: Medicine and Health Sciences
                Subject: Anatomy
                Subject: Nervous System
                Subject: Central Nervous System
                Subject: Biology and Life Sciences
                Subject: Neuroscience
                Subject: Brain Mapping
                Subject: Brain Morphometry
                Subject: Diffusion Tensor Imaging
                Subject: Medicine and Health Sciences
                Subject: Diagnostic Medicine
                Subject: Diagnostic Radiology
                Subject: Magnetic Resonance Imaging
                Subject: Brain Morphometry
                Subject: Diffusion Tensor Imaging
                Subject: Research and Analysis Methods
                Subject: Imaging Techniques
                Subject: Diagnostic Radiology
                Subject: Magnetic Resonance Imaging
                Subject: Brain Morphometry
                Subject: Diffusion Tensor Imaging
                Subject: Medicine and Health Sciences
                Subject: Radiology and Imaging
                Subject: Diagnostic Radiology
                Subject: Magnetic Resonance Imaging
                Subject: Brain Morphometry
                Subject: Diffusion Tensor Imaging
                Subject: Research and Analysis Methods
                Subject: Imaging Techniques
                Subject: Neuroimaging
                Subject: Brain Morphometry
                Subject: Diffusion Tensor Imaging
                Subject: Biology and Life Sciences
                Subject: Neuroscience
                Subject: Neuroimaging
                Subject: Brain Morphometry
                Subject: Diffusion Tensor Imaging
                Subject: Medicine and Health Sciences
                Subject: Anesthesiology
                Subject: Anesthesia
                Subject: General Anesthesia
                Subject: Medicine and Health Sciences
                Subject: Pharmaceutics
                Subject: Drug Therapy
                Subject: Anesthesia
                Subject: General Anesthesia
                Subject: Medicine and Health Sciences
                Subject: Diagnostic Medicine
                Subject: Diagnostic Radiology
                Subject: Magnetic Resonance Imaging
                Subject: Research and Analysis Methods
                Subject: Imaging Techniques
                Subject: Diagnostic Radiology
                Subject: Magnetic Resonance Imaging
                Subject: Medicine and Health Sciences
                Subject: Radiology and Imaging
                Subject: Diagnostic Radiology
                Subject: Magnetic Resonance Imaging
                Subject: Medicine and Health Sciences
                Subject: Anesthesiology
                Subject: Anesthesia
                Subject: Local and Regional Anesthesia
                Subject: Medicine and Health Sciences
                Subject: Pharmaceutics
                Subject: Drug Therapy
                Subject: Anesthesia
                Subject: Local and Regional Anesthesia
                Subject: Physical Sciences
                Subject: Materials Science
                Subject: Materials Physics
                Subject: Microstructure
                Subject: Physical Sciences
                Subject: Physics
                Subject: Materials Physics
                Subject: Microstructure
                Subject: Biology and Life Sciences
                Subject: Cell Biology
                Subject: Extracellular Space
                Custom metadata
                Data Availability The publicly accessible data is available through DRYAD, via this link: https://datadryad.org/stash/share/urpv1JLCCuHKNOUF_yr3LGTGENPl7chhjSAY_1ty3YQ.

                ScienceOpen disciplines: Uncategorized
                Data availability:
                ScienceOpen disciplines: Uncategorized

                Comments

                Comment on this article

                scite_

                Similar content150

                See all similar

                Cited by6

                See all cited by

                Most referenced authors730

                See all reference authors