The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Diffusion Tensor Imaging Reliably Detects Experimental Traumatic Axonal Injury and Indicates Approximate Time of Injury
Open accessAbstract
Traumatic axonal injury (TAI) may contribute greatly to neurological impairments after traumatic brain injury, but it is difficult to assess with conventional imaging. We quantitatively compared diffusion tensor imaging (DTI) signal abnormalities with histological and electron microscopic characteristics of pericontusional TAI in a mouse model. Two DTI parameters, relative anisotropy and axial diffusivity, were significantly reduced 6 h to 4 d after trauma, corresponding to relatively isolated axonal injury. One to 4 weeks after trauma, relative anisotropy remained decreased, whereas axial diffusivity “pseudo-normalized” and radial diffusivity increased. These changes corresponded to demyelination, edema, and persistent axonal injury. At every time point, DTI was more sensitive to injury than conventional magnetic resonance imaging, and relative anisotropy distinguished injured from control mice with no overlap between groups. Remarkably, DTI changes strongly predicted the approximate time since trauma. These results provide an important validation of DTI for pericontusional TAI and suggest novel clinical and forensic applications.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Song, S.-K., Sun, S.-W., Ju, W.-K., Lin, S.-J., Cross, A. H., & Neufeld, A. H. (2003) · NeuroImage · doi:10.1016/j.neuroimage.2003.07.005 · Cited by 1,738
KOCHANEK, P. M., MARION, D. W., ZHANG, W., SCHIDING, J. K., WHITE, M., PALMER, A. M., CLARK, R. S. B., O'MALLEY, M. E., STYREN, S. D., HO, C., et al. (1995) · Journal of Neurotrauma · doi:10.1089/neu.1995.12.1015 · Cited by 203 · cited 1×
“…(Arfanakis et al., 2002; Naganawa et al., 2004; Voss et al., 2006) and none of the previous experimental animal studies (Hanstock et al., 1994; Kochanek et al., 1995; Alsop et al., 1996; Assaf et al., 1997; Albensi et al., 2000; Duhaime et al., 2003; Van Putten et al., 2005), to our…”
ResultSong, S.-K., Kim, J. H., Lin, S.-J., Brendza, R. P., & Holtzman, D. M. (2004) · Neurobiology of Disease · doi:10.1016/j.nbd.2003.12.003 · Cited by 170
Self-citation
Cited by
The New Neurometabolic Cascade of Concussion
Giza, C. C., & Hovda, D. A. (2014) · Neurosurgery · doi:10.1227/neu.0000000000000505 · Cited by 1,353
Inflammation after trauma: Microglial activation and traumatic brain injury
Ramlackhansingh, A. F., Brooks, D. J., Greenwood, R. J., Bose, S. K., Turkheimer, F. E., Kinnunen, K. M., Gentleman, S., Heckemann, R. A., Gunanayagam, K., Gelosa, G., et al. (2011) · Annals of Neurology · doi:10.1002/ana.22455 · Cited by 999
Salience network integrity predicts default mode network function after traumatic brain injury
Bonnelle, V., Ham, T. E., Leech, R., Kinnunen, K. M., Mehta, M. A., Greenwood, R. J., & Sharp, D. J. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1113455109 · Cited by 606
Detection of Blast-Related Traumatic Brain Injury in U.S. Military Personnel
Mac Donald, C. L., Johnson, A. M., Cooper, D., Nelson, E. C., Werner, N. J., Shimony, J. S., Snyder, A. Z., Raichle, M. E., Witherow, J. R., Fang, R., et al. (2011) · New England Journal of Medicine · doi:10.1056/nejmoa1008069 · Cited by 599
Self-citationThe molecular pathophysiology of concussive brain injury
Barkhoudarian, G., Hovda, D. A., & Giza, C. C. (2011) · Clinics in Sports Medicine · doi:10.1016/j.csm.2010.09.001 · Cited by 492
A prospective diffusion tensor imaging study in mild traumatic brain injury
Mayer, A. R., Ling, J., Mannell, M. V., Gasparovic, C., Phillips, J. P., Doezema, D., Reichard, R., & Yeo, R. A. (2010) · Neurology · doi:10.1212/wnl.0b013e3181d0ccdd · Cited by 459
Budde, M. D., Janes, L., Gold, E., Turtzo, L. C., & Frank, J. A. (2011) · Brain · doi:10.1093/brain/awr161 · Cited by 408
Tran, H. T., LaFerla, F. M., Holtzman, D. M., & Brody, D. L. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.0858-11.2011 · Cited by 255
Self-citationMild traumatic brain injury and diffuse axonal injury in swine
Browne, K. D., Chen, X.-H., Meaney, D. F., & Smith, D. H. (2011) · Journal of Neurotrauma · doi:10.1089/neu.2011.1913 · Cited by 248
Neurite beading is sufficient to decrease the apparent diffusion coefficient after ischemic stroke
Budde, M. D., & Frank, J. A. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1004841107 · Cited by 229
Traumatic brain injury impairs small-world topology
Pandit, A. S., Expert, P., Lambiotte, R., Bonnelle, V., Leech, R., Turkheimer, F. E., & Sharp, D. J. (2013) · Neurology · doi:10.1212/wnl.0b013e3182929f38 · Cited by 176
Xie, M., Tobin, J. E., Budde, M. D., Chen, C.-I., Trinkaus, K., Cross, A. H., McDaniel, D. P., Song, S.-K., & Armstrong, R. C. (2010) · Journal of Neuropathology & Experimental Neurology · doi:10.1097/nen.0b013e3181e3de90 · Cited by 175
Assessment of lesion pathology in a new animal model of MS by multiparametric MRI and DTI
Boretius, S., Escher, A., Dallenga, T., Wrzos, C., Tammer, R., Brück, W., Nessler, S., Frahm, J., & Stadelmann, C. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.08.051 · Cited by 128
Bendlin, B. B., Carlsson, C. M., Johnson, S. C., Zetterberg, H., Blennow, K., Willette, A. A., Okonkwo, O. C., Sodhi, A., Ries, M. L., Birdsill, A. C., et al. (2012) · PLoS ONE · doi:10.1371/journal.pone.0037720 · Cited by 91
Tran, H. T., Sanchez, L., Esparza, T. J., & Brody, D. L. (2011) · PLoS ONE · doi:10.1371/journal.pone.0025475 · Cited by 86
Self-citationPituitary dysfunction after blast traumatic brain injury: The UK BIOSAP study
Baxter, D., Sharp, D. J., Feeney, C., Papadopoulou, D., Ham, T. E., Jilka, S., Hellyer, P. J., Patel, M. C., Bennett, A. N., Mistlin, A., et al. (2013) · Annals of Neurology · doi:10.1002/ana.23958 · Cited by 81
Willie, J. T., Lim, M. M., Bennett, R. E., Azarion, A. A., Schwetye, K. E., & Brody, D. L. (2012) · Journal of Neurotrauma · doi:10.1089/neu.2012.2404 · Cited by 79
Self-citationStructural insights into the rodent CNS via diffusion tensor imaging.
Zhang, J., Aggarwal, M., & Mori, S. (2012) · Trends in Neurosciences · doi:10.1016/j.tins.2012.04.010 · Cited by 73
The Biological Basis of Diffusion Anisotropy
Beaulieu, C. (2014) · Diffusion MRI · doi:10.1016/b978-0-12-396460-1.00008-1 · Cited by 66
Benedetti, F., Poletti, S., Locatelli, C., Mazza, E., Lorenzi, C., Vitali, A., Riberto, M., Brioschi, S., Vai, B., Bollettini, I., et al. (2018) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2017.10.011 · Cited by 64
Schwetye, K. E., Cirrito, J. R., Esparza, T. J., Mac Donald, C. L., Holtzman, D. M., & Brody, D. L. (2010) · Neurobiology of Disease · doi:10.1016/j.nbd.2010.06.018 · Cited by 51
Self-citationMicrostructural imaging in the spinal cord and validation strategies
Cohen-Adad, J. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.04.009 · Cited by 50
Stone, D. B., Ryman, S. G., Hartman, A. P., Wertz, C. J., Vakhtin, A. A., & Initiative, A. D. N. (2021) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2021.711579 · Cited by 28
Understanding individual variability in symptoms and recovery following mTBI: a role for TMS-EEG
Coyle, H. L., Ponsford, J., & Hoy, K. E. (2018) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2018.05.027 · Cited by 21
Zheng, P., He, B., Guo, Y., Zeng, J., & Tong, W. (2015) · Journal of Neurosurgery · doi:10.3171/2014.12.jns132308 · Cited by 16
Zheng, P., He, B., & Tong, W. S. (2014) · Journal of Endocrinological Investigation · doi:10.1007/s40618-014-0059-8 · Cited by 12
Müller, H.-P., Roselli, F., Rasche, V., & Kassubek, J. (2020) · Frontiers in Neuroscience · doi:10.3389/fnins.2020.00734 · Cited by 12
Bao, J., Zhang, X., & Zhao, X. (2023) · Frontiers in Neuroscience · doi:10.3389/fnins.2023.1234049 · Cited by 6
Metadata
- Authors
- Mac Donald, C. L., Dikranian, K., Bayly, P., Holtzman, D., & Brody, D.
- Venue
- The Journal of Neuroscience
- Publisher
- Society for Neuroscience
- Published
- 2007-10-31
- Volume
- 27
- Issue
- 44
- Pages
- 11869-11876
- ISSN
- 0270-6474 (ISSN-L)
- 1529-2401
- OpenAlex
- W2083249651
- Cited by
- 435
- References
- 3
- FWCI
- 10.94
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.