The DOI matches its Crossref record; 66 of the 66 references it cites were found in a registry or an index.
DTI measures in crossing-fibre areas: increased diffusion anisotropy reveals early white matter alteration in MCI and mild Alzheimer’s disease
Open accessAbstract
Though mild cognitive impairment is an intermediate clinical state between healthy aging and Alzheimer's disease (AD), there are very few whole-brain voxel-wise diffusion MRI studies directly comparing changes in healthy control, mild cognitive impairment (MCI) and AD subjects. Here we report whole-brain findings from a comprehensive study of diffusion tensor indices and probabilistic tractography obtained in a very large population of healthy controls, MCI and probable AD subjects. As expected from the literature, all diffusion indices converged to show that the cingulum bundle, the uncinate fasciculus, the entire corpus callosum and the superior longitudinal fasciculus are the most affected white matter tracts in AD. Significant differences between MCI and AD were essentially confined to the corpus callosum. More importantly, we introduce for the first time in a degenerative disorder an application of a recently developed tensor index, the "mode" of anisotropy, as well as probabilistic crossing-fibre tractography. The mode of anisotropy specifies the type of anisotropy as a continuous measure reflecting differences in shape of the diffusion tensor ranging from planar (e.g., in regions of crossing fibres from two fibre populations of similar density or regions of "kissing" fibres) to linear (e.g., in regions where one fibre population orientation predominates), while probabilistic crossing-fibre tractography allows to accurately trace pathways from a crossing-fibre region. Remarkably, when looking for whole-brain diffusion differences between MCI patients and healthy subjects, the only region with significant abnormalities was a region of crossing fibres in the centrum semiovale, showing an increased mode of anisotropy. The only white matter region demonstrating a significant difference in correlations between neuropsychological scores and a diffusion measure (mode of anisotropy) across the three groups was the same region of crossing fibres. Further examination using probabilistic tractography established explicitly and quantitatively that this previously unreported increase of mode and co-localised increase of fractional anisotropy was explained by a relative preservation of motor-related projection fibres (at this early stage of the disease) crossing the association fibres of the superior longitudinal fasciculus. These findings emphasise the benefit of looking at the more complex regions in which spared and affected pathways are crossing to detect very early alterations of the white matter that could not be detected in regions consisting of one fibre population only. Finally, the methods used in this study may have general applicability for other degenerative disorders and, beyond the clinical sphere, they could contribute to a better quantification and understanding of subtle effects generated by normal processes such as visuospatial attention or motor learning.
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.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“In particular, major fibre tracts such as the forceps major and forceps minor, inferior fronto-occipital fasciculus as well as the posterior cingulum show white matter alterations in Alzheimer’s disease dementia (Taylor et al., 2001; Teipel et al., 2002; Douaud et al., 2011; Mito et al., 2018).”
From White matter diffusion alterations precede symptom onset in autosomal dominant Alzheimer’s disease (2018) · cites this paper as Douaud et al., 2011
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“DTI alterations such as those observed in the corticospinal tract in the current study should be interpreted with caution, as the current TBSS approach cannot be unambiguously attributed to that tract, but potentially are because of alterations in crossing fibres such as the superior longitudinal fasciculus or corpus callosum (Douaud et al., 2011; Teipel et al., 2014; Mito et al., 2018).”
From White matter diffusion alterations precede symptom onset in autosomal dominant Alzheimer’s disease (2018) · cites this paper as Douaud et al., 2011
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“In healthy tissue with crossing fibers, the DTI model may show low FA. FADTI may paradoxically appear to increase in regions where crossing fibers deteriorate in neurodegenerative diseases such as AD (Douaud et al., 2011).”
From Diffusion MRI Indices and Their Relation to Cognitive Impairment in Brain Aging: The Updated Multi-protocol Approach in ADNI3 (2019) · cites this paper as Douaud et al., 2011
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
Diagnostic and Statistical Manual of Mental Disorders
Williams, J. B. W., & First, M. B. (2013) · Oxford University Press eBooks · doi:10.1093/acrefore/9780199975839.013.104 · Cited by 109,845
McKhann, G., Drachman, D., Folstein, M., Katzman, R., Price, D., & Stadlan, E. M. (1984) · Neurology · doi:10.1212/wnl.34.7.939 · Cited by 27,915 · cited 1×
“The diagnosis of AD was made when both the DSM-IV criteria (American Psychiatric Association, 1994) and the NINCDS-ADRDA criteria (McKhann et al., 1984) were fulfilled.”
MethodAdvances in functional and structural MR image analysis and implementation as FSL
Smith, S. M., Jenkinson, M., Woolrich, M. W., Beckmann, C. F., Behrens, T. E. J., Johansen-Berg, H., Bannister, P. R., De Luca, M., Drobnjak, I., Flitney, D. E., et al. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.07.051 · Cited by 13,630 · cited 3×
“Voxel-wise differences in DTI indices were assessed using TBSS in FSL which increases the sensitivity and the interpretability of the results compared with voxel-based approaches based purely on non-linear registration (Smith et al., 2006).”
MethodSelf-citationDiagnostic and Statistical Manual of Mental Disorders
Siegel, L. J., & Fletcher‐Janzen, E. (2008) · Wiley eBooks · doi:10.1002/9780470373699.speced0655 · Cited by 8,467
Tract-based spatial statistics: Voxelwise analysis of multi-subject diffusion data
Smith, S. M., Jenkinson, M., Johansen‐Berg, H., Rueckert, D., Nichols, T. E., Mackay, C. E., Watkins, K. E., Ciccarelli, O., Cader, M. Z., Matthews, P. M., et al. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.02.024 · Cited by 6,598 · cited 4×
“Voxel-wise differences in DTI indices were assessed using TBSS in FSLwhich increases the sensitivity and the interpretability of the results compared with voxel-based approaches based purely on non-linear registration (Smith et al., 2006).”
MethodInfluentialNonparametric permutation tests for functional neuroimaging: A primer with examples
Nichols, T. E., & Holmes, A. P. (2002) · Human Brain Mapping · doi:10.1002/hbm.1058 · Cited by 6,256
SMITH, S., & NICHOLS, T. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2008.03.061 · Cited by 5,250 · cited 2×
“05, corrected for multiple comparisons using the “2D” parameter settings with threshold-free cluster enhancement (TFCE), a method which avoids using an arbitrary threshold for the initial cluster-formation (Smith and Nichols, 2009).”
MethodInfluentialWinblad, B., Palmer, K., Kivipelto, M., Jelic, V., Fratiglioni, L., Wahlund, L. ‐., Nordberg, A., Bäckman, L., Albert, M., Almkvist, O., et al. (2004) · Journal of Internal Medicine · doi:10.1111/j.1365-2796.2004.01380.x · Cited by 4,946 · cited 2×
“MCI subjects were diagnosed according to the criteria by Winblad and colleagues (Winblad et al., 2004).”
BackgroundMethodThe basis of anisotropic water diffusion in the nervous system—A technical review.
Beaulieu, C. (2002) · NMR in Biomedicine · doi:10.1002/nbm.782 · Cited by 4,628
Gauthier, S. G., Reisberg, ., Zaudig, M., Petersen, R. C., Ritchie, K. A., Broich, K., Belleville, S., Brodaty, H., Bennett, D. A., Chertkow, H. M., et al. (2006) · The Lancet · doi:10.1016/s0140-6736(06)68542-5 · Cited by 4,094
Cited by
Sorted by citations
Multimodal population brain imaging in the UK Biobank prospective epidemiological study
Miller, K. L., Alfaro-Almagro, F., Bangerter, N. K., Thomas, D. L., Yacoub, E., Xu, J., Bartsch, A. J., Jbabdi, S., Sotiropoulos, S. N., Andersson, J. L. R., et al. (2016) · Nature Neuroscience · doi:10.1038/nn.4393 · Cited by 2,020
“…exhibit the opposite, of FA increasing with aging, which may reflect degradation of secondary fibers or reduced fiber dispersion23; notably, none of the FA-based IDPs exhibit this significant positive correlation, demonstrating that averaging across tracts can sacrifice richness of information.”
SARS-CoV-2 is associated with changes in brain structure in UK Biobank
Douaud, G., Lee, S., Alfaro-Almagro, F., Arthofer, C., Wang, C., McCarthy, P., Lange, F., Andersson, J. L. R., Griffanti, L., Duff, E., et al. (2022) · Nature · doi:10.1038/s41586-022-04569-5 · Cited by 1,646
Jeurissen, B., Leemans, A., Tournier, J., Jones, D. K., & Sijbers, J. (2013) · Human Brain Mapping · doi:10.1002/hbm.22099 · Cited by 1,088
“In yet another study, increased diffusion anisotropy was measured in the centrum semiovale of patients with mild cognitive impairment and mild Alzheimer’s disease [Douaud et al., 2011].”
BackgroundDubois, J., Dehaene-Lambertz, G., Kulikova, S., Poupon, C., Hüppi, P. S., & Hertz-Pannier, L. (2014) · Neuroscience · doi:10.1016/j.neuroscience.2013.12.044 · Cited by 851
“bundles follow different maturational calendars: when the first bundle gets myelinated, anisotropy first increases, but it subsequently decreases when the second crossing bundle gets mature (the reverse argument has been detailed for neurodegenerative disorders (Douaud et al., 2011)); at the same time, diffusivities a…”
BackgroundA hitchhiker's guide to diffusion tensor imaging
Soares, J. M., Marques, P., Alves, V., & Sousa, N. (2013) · Frontiers in Neuroscience · doi:10.3389/fnins.2013.00031 · Cited by 893
Metadata
- Authors
- Douaud, G., Jbabdi, S., Behrens, T. E. J., Menke, R. A., Gass, A., Monsch, A. U., Rao, A., Whitcher, B., Kindlmann, G., Matthews, P. M., & Smith, S.
- Affiliations
- University of Oxford (GB)
- University Hospital of Basel (CH)
- GlaxoSmithKline (United Kingdom) (GB)
- University of Chicago (US)
- Corresponding author
- Douaud, Gwenaëlle
- ORCID
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2011-04
- Volume
- 55
- Issue
- 3
- Pages
- 880-890
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC7116583
- OpenAlex
- W2151712416
- Cited by
- 514
- References
- 66
- Citations by year
- 2026: 19 · 2025: 23 · 2024: 17 · 2023: 16 · 2022: 26 · 2021: 42 · 2020: 34 · 2019: 42 · 2018: 36 · 2017: 36 · 2016: 35 · 2015: 41 · 2014: 41 · 2013: 51 · 2012: 39
- FWCI
- 26.77
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- UK Engineering and Physical Sciences Research Council
- UK Medical Research Council
- Wellcome Trust
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Keywords
- mild cognitive impairment, Alzheimer's disease, white matter microstructure, crossing fibers, diffusion anisotropy, probabilistic tractography, centrum semiovale, superior longitudinal fasciculus, corpus callosum, cingulum, uncinate fasciculus, fractional anisotropy
- MeSH terms
- Adolescent, Adult, Aged, Aged, 80 and over, Aging, Algorithms, Alzheimer Disease, Brain, Brain Mapping, Cognition Disorders, Female, Humans, Image Processing, Computer-Assisted, Male, Middle Aged, Young Adult, Diffusion Tensor Imaging
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
