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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.
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“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
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“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
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“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
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“A very similar pattern of increasing FA and MO was recently reported in degeneration related to mild cognitive impairment and Alzheimer's disease, and further corroborated by tractography analysis indicating that this specific pattern may be explained by degeneration of the association pathways and a relative preserva…”
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“An added complication is that regions of crossing fibers may show a seemingly paradoxical increase of diffusion anisotropy when one of the two fiber populations undergoes degeneration (Pierpaoli et al., 2001; Douaud et al., 2011).”
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Mackey, A. P., Whitaker, K. J., & Bunge, S. A. (2012) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2012.00032 · Cited by 130
Bergamino, M., Walsh, R. R., & Stokes, A. M. (2021) · Scientific Reports · doi:10.1038/s41598-021-86505-7 · Cited by 124
Traudt, C. M., McPherson, R. J., Bauer, L. A., Richards, T. L., Burbacher, T. M., McAdams, R. M., & Juul, S. E. (2013) · Developmental Neuroscience · doi:10.1159/000355460 · Cited by 119
O'Dwyer, L., Lamberton, F., Bokde, A. L. W., Ewers, M., Faluyi, Y. O., Tanner, C., Mazoyer, B., O'Neill, D., Bartley, M., Collins, D. R., et al. (2011) · PLoS ONE · doi:10.1371/journal.pone.0021745 · Cited by 119
Schouten, T. M., Koini, M., de Vos, F., Seiler, S., van der Grond, J., Lechner, A., Hafkemeijer, A., Möller, C., Schmidt, R., de Rooij, M., et al. (2016) · NeuroImage Clinical · doi:10.1016/j.nicl.2016.01.002 · Cited by 125
“…been applied successfully to study average group differences between AD patients and controls in voxel based grey matter (Ferreira et al., 2011), white matter (Li et al., 2012), diffusion measures (Douaud et al., 2011), and functional connectivity (Gour et al., 2014; Binnewijzend et al., 2012).”
Teipel, S. J., Grothe, M. J., Zhou, J. H., Sepulcre, J., Dyrba, M., Sorg, C., & Babiloni, C. (2016) · Journal of the International Neuropsychological Society · doi:10.1017/s1355617715000995 · Cited by 117
“The rather counterintuitive observation of relatively increased FA values along cortico-fugal and cortico-petal fiber tracts in AD and MCI (Douaud et al., 2011) may likely be explained by the loss of intracortically projecting crossing fiber tracts, and hence a more linear shape of the resulting…”
BackgroundChad, J. A., Pasternak, O., Salat, D. H., & Chen, J. J. (2018) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2018.07.018 · Cited by 114
“While a higher FAt in older adults may seem counterintuitive, it is precisely what is reported among Alzheimer’s subjects (Doan et al., 2017; Douaud et al., 2011; Mito et al., 2018; Teipel et al., 2014).”
BackgroundGraña, M., Termenón, M., Savio, A. M., González-Pinto, A. M., Echeveste, J., Pérez, J. M., & Besga, A. (2011) · Neuroscience Letters · doi:10.1016/j.neulet.2011.07.049 · Cited by 114
Rae, C. L., Correia, M., Altena, E., Hughes, L. E., Barker, R. A., & Rowe, J. B. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.06.012 · Cited by 112
“Diffusion tensor imaging (DTI) is an effective non-invasive tool to investigate pathological changes in thewhitematter of living neurodegenerative and psychiatric patients (Acosta-Cabronero et al., 2010; Douaud et al., 2011; Kubicki and Shenton, 2009; Peran et al., 2010; Wang et al., 2009).”
BackgroundShiva Keihaninejad, A., Zhang, H. G., Ryan, N. S., Malone, I. B., Marc Modat, A., Cardoso, M. J., Cash, D. M., Fox, N. C., & Sebastien Ourselin, A. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.01.044 · Cited by 111
“Whilst a reduced FA and/or an increased MD in the corpus callosum is one of the most consistent findings in AD (Douaud et al., 2011; Liu et al., 2011), there has been conflicting evidence about whether the genu (Head et al.”
BackgroundResultMelah, K. E., Lu, S. Y.-F., Hoscheidt, S. M., Alexander, A. L., Adluru, N., Destiche, D. J., Carlsson, C. M., Zetterberg, H., Blennow, K., Okonkwo, O. C., et al. (2016) · Journal of Alzheimer s Disease · doi:10.3233/jad-150897 · Cited by 109
Approaches for the Integrated Analysis of Structure, Function and Connectivity of the Human Brain
Eickhoff, S. B., & Grefkes, C. (2011) · Clinical EEG and Neuroscience · doi:10.1177/155005941104200211 · Cited by 106
Samanez-Larkin, G. R., Levens, S. M., Perry, L. M., Dougherty, R. F., & Knutson, B. D. (2012) · Journal of Neuroscience · doi:10.1523/jneurosci.5756-11.2012 · Cited by 108
“The issue of crossing fibers (and, more generally, fiber directional coherence) poses challenges for the interpretation of diffusion data (Douaud et al., 2011).”
BackgroundKamagata, K., Tomiyama, H., Hatano, T., Motoi, Y., Abe, O., Shimoji, K., Kamiya, K., Suzuki, M., Hori, M., Yoshida, M., et al. (2014) · Neuroradiology · doi:10.1007/s00234-014-1327-1 · Cited by 107
“DKI is also potentially useful for evaluating crossing fibers [32], whereas DTI metrics such as FA andMD in white matter are influenced by the presence of crossing fibers [33–35].”
BackgroundDiffusion-MRI in neurodegenerative disorders
Goveas, J., O’Dwyer, L., Mascalchi, M., Cosottini, M., Diciotti, S., De Santis, S., Passamonti, L., Tessa, C., Toschi, N., & Giannelli, M. (2015) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2015.04.006 · Cited by 104
“evaluate diffusion changes in areas of crossing-fibers [88], where the DTI model (which is based on a single-fiber population model)”
BackgroundMethodAcosta‐Cabronero, J., & Nestor, P. J. (2014) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2014.00266 · Cited by 109
“Douaud et al. (2011) proposed that the λ1 increase could be explained as an artifact of loss of one fiber population in areas of crossing fibers (see Figure 3).”
BackgroundMethodResultInfluentialAlnæs, D., Kaufmann, T., Doan, N. T., Córdova‐Palomera, A., Wang, Y., Bettella, F., Moberget, T., Andreassen, O. A., & Westlye, L. T. (2018) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2017.4277 · Cited by 104
“Indeed, diffusion-weighted imaging–based indices of brain tissue organization may reflect the relative balance between differentiallyaffectedcrossingfiberpopulations.(11)Consequently, fusion of multimodal brain imaging indices, which allows for a joint considerationofdifferentbraincharacteristics,mayyieldmore biologic…”
BackgroundZhu, J., Zhuo, C., Qin, W., Wang, D., Ma, X., Zhou, Y., & Yu, C. (2014) · NeuroImage Clinical · doi:10.1016/j.nicl.2014.12.008 · Cited by 103
“However, it has limited capacity of detecting diffusion changes in white matter regions with complex fiber arrangement, such as fiber crossing (Douaud et al., 2011; Jbabdi et al., 2010; Vos et al., 2012).”
BackgroundZavaliangos-Petropulu, A., Nir, T. M., Thomopoulos, S. I., Reid, R. I., Bernstein, M. A., Borowski, B., Jack Jr., C. R., Weiner, M. W., Jahanshad, N., & Thompson, P. M. (2019) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2019.00002 · Cited by 101
Diffusion MRI in the brain – Theory and concepts
Tournier, J. (2019) · Progress in Nuclear Magnetic Resonance Spectroscopy · doi:10.1016/j.pnmrs.2019.03.001 · Cited by 110
Hampton, W. H., Hanik, I. M., & Olson, I. R. (2019) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2019.02.005 · Cited by 95
“Some groundwork for such studies has been laid by probabilistic tractography in other clinical populations including Alzheimer’s (Douaud et al., 2011), schizophrenia (Cho et al., 2015; Kubicki et al., 2005), and autism (Ikuta et al., 2014).”
BackgroundWhite Matter Degeneration with Aging: Longitudinal Diffusion MR Imaging Analysis
de Groot, M., Cremers, L. G. M., Ikram, M. A., Albert Hofman, D., Krestin, G. P., van der Lugt, A., Niessen, W. J., & Vernooij, M. W. (2015) · Radiology · doi:10.1148/radiol.2015150103 · Cited by 97
Foley, S. F., Tansey, K. E., Caseras, X., Lancaster, T. M., Bracht, T., Parker, G. D., Hall, J., Williams, J. H., & Linden, D. E. J. (2016) · Biological Psychiatry · doi:10.1016/j.biopsych.2016.02.033 · Cited by 98
“Changes in white matter parameters have indeed been observed in many DTI studies of AD, for example, decreased FA in the right fornix (10) and the left PHC (62), superior longitudinal fasciculus, temporal lobe (63,64), and cingulum (65).”
BackgroundDyrba, M., Barkhof, F., Fellgiebel, A., Filippi, M., Hausner, L., Hauenstein, K., Kirste, T., Teipel, S. J., & the EDSD study group (2015) · Journal of Neuroimaging · doi:10.1111/jon.12214 · Cited by 99
“14 Establishing DTI as an imaging marker of AD requires studying its diagnostic performance in large samples across multiple sites.”
BackgroundLópez‐Ortiz, S., Pinto-Fraga, J., Valenzuela, P. L., Martín-Hernández, J., Seisdedos, M. M., García, Ó., Toschi, N., Giuliano, F. D., Garaci, F. G., Mercuri, N. B., et al. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22062897 · Cited by 107
“DTI has demonstrated that WM is involved in cognitive impairment, as changes in the connections of the hippocampus [195], posterior cingulum [196], thalamus [197], and regions in the posterior WM were found.”
BackgroundGroeschel, S., Tournier, J., Northam, G. B., Baldeweg, T., Wyatt, J. S., Vollmer, B., & Connelly, A. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.10.034 · Cited by 93
“Furthermore, apparent changes in parallel or perpendicular diffusivities are difficult to interpret in crossing fibre regions, since the orientation of the principal eigenvectors is likely to be inconsistent (Douaud et al., 2011).”
InfluentialWhite matter alterations in early‐stage Alzheimer's disease: A tract‐specific study
Wen, Q., Mustafi, S. M., Li, J., Risacher, S. L., Tallman, E., Brown, S. A., West, J. D., Harezlak, J., Farlow, M. R., Unverzagt, F. W., et al. (2019) · Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring · doi:10.1016/j.dadm.2019.06.003 · Cited by 96
“Previous tract-specific AD studies focused on a single preselected tract, such as the uncinate fasciculus [53,54] and cingulum bundle [14], or on fibers in the limbic system [16,55], whereas few studies have thoroughly investigated whole brain white matter bundles [15,47].”
BackgroundMethodAxonal energy metabolism, and the effects in aging and neurodegenerative diseases
Yang, S., Park, J. H., & Lu, H.-C. (2023) · Molecular Neurodegeneration · doi:10.1186/s13024-023-00634-3 · Cited by 94
“Imaging: DTI with 61 ctrls, 56 MCI, 53 probable AD patients with‐ out a vascular component Aimed to report a comprehensive whole-brain study of diffusion tensor indices and probabilistic tractography obtained from healthy controls, MCI and probable AD subjects • Affected white matter in AD (vs ctrl): Cingulum bundle,…”
MethodNeuroimaging Endpoints in Amyotrophic Lateral Sclerosis
Menke, R., Agosta, F., Großkreutz, J., Filippi, M., & Turner, M. R. (2016) · Neurotherapeutics · doi:10.1007/s13311-016-0484-9 · Cited by 99
Pujol, J., Fenoll, R., Macià, D., Martínez‐Vilavella, G., Álvarez‐Pedrerol, M., Rivas, I., Forns, J., Deus, J., Blanco‐Hinojo, L., Querol, X., et al. (2016) · Brain and Behavior · doi:10.1002/brb3.467 · Cited by 93
“Nevertheless, in complex structures with tracts crossing in different directions, higher FA may denote less mature or less structured tissue (Douaud et al. 2011; Jones et al. 2013).”
Reijmer, Y. D., Leemans, A., Heringa, S. M., Wielaard, I., Jeurissen, B., Koek, H. L., & Biessels, G. J. (2012) · PLoS ONE · doi:10.1371/journal.pone.0044074 · Cited by 91
“This is supported by results from a recent study showing an increased mode of anisotropy in patients with MCI compared to controls only in areas where the SLF intersects the projection pathways [46].”
BackgroundResultStructural networks in Alzheimer's disease
Reid, A., & Evans, A. C. (2013) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2012.11.010 · Cited by 94
Kim, H., Mawla, I., Lee, J., Gerber, J. A., Walker, K. L., Kim, J., Ortiz, A., Chan, S., Loggia, M. L., Wasan, A. D., et al. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116899 · Cited by 91
“Notably, this mask did not include the superior longitudinal fasciculus, located medial to S1-adjacent U-fibers, as it is difficult to interpret fractional anisotropy in areas with high crossing-fiber density (Douaud et al., 2011).”
BackgroundNilsson, M., Szczepankiewicz, F., van Westen, D., & Hansson, O. (2015) · PLoS ONE · doi:10.1371/journal.pone.0141825 · Cited by 89
Itahashi, T., Yamada, T., Nakamura, M., Watanabe, H., Yamagata, B., Jimbo, D., Shioda, S., Kuroda, M., Toriizuka, K., Kato, N., et al. (2014) · NeuroImage Clinical · doi:10.1016/j.nicl.2014.11.019 · Cited by 91
“Although no studies to date have examined possible alterations in MO of ASD, its applicability has been demonstrated in a recent study of mild cognitive impairment in which abnormalities had been detected only in MO but not in FA (Douaud et al., 2011).”
BackgroundTract-based analysis of white matter degeneration in Alzheimer’s disease
Lee, S., Coutu, J., Wilkens, P. J., Yendiki, A., Rosas, H. D., & Salat, D. H. (2015) · Neuroscience · doi:10.1016/j.neuroscience.2015.05.049 · Cited by 91
“Overall, the fiber bundles demonstrating most significant alterations are known to support memory and these results confirm prior work using whole brain, region of interest, and more selective tractography (Acosta-Cabronero et al., 2010; Salat et al., 2010; Douaud et al., 2011; Liu et al., 2011; Hasan et al., 2012).”
MethodInfluentialLimbic Tract Integrity Contributes to Pattern Separation Performance Across the Lifespan
Bennett, I. J., Huffman, D. J., & Stark, C. E. L. (2014) · Cerebral Cortex · doi:10.1093/cercor/bhu093 · Cited by 90
“Whereas MO has been assessed in individuals diagnosed with mild cognitive impairment and Alzheimer’s disease (Douaud et al. 2011), to our knowledge this is the first examination of MO in healthy adults.”
BackgroundRight Arcuate Fasciculus Abnormality in Chronic Fatigue Syndrome
Zeineh, M., Kang, J. D., Atlas, S. W., Raman, M. M., Reiss, A. L., Norris, J. L., Valencia, I. J., & Montoya, J. G. (2014) · Radiology · doi:10.1148/radiol.14141079 · Cited by 87
Shared white-matter dysconnectivity in schizophrenia and bipolar disorder with psychosis
Kumar, J., Iwabuchi, S. J., Oowise, S., Balain, V., Palaniyappan, L. K., & Liddle, P. F. (2014) · Psychological Medicine · doi:10.1017/s0033291714001810 · Cited by 86
“MoA varies from −1 to +1, with values closer to −1 indicate regions where high number of crossing fibres can be expected and values closer to +1 indicate regions where one fibre orientation predominates (Douaud et al. 2011).”
BackgroundEarly limbic microstructural alterations in apathy and depression in de novo Parkinson's disease
Prange, S., Météreau, É., Maillet, A., Lhommée, E., Klinger, H., Pélissier, P., Ibarrola, D., Heckemann, R. A., Castrioto, A., Tremblay, L., et al. (2019) · Movement Disorders · doi:10.1002/mds.27793 · Cited by 86
Diffusion models reveal white matter microstructural changes with ageing, pathology and cognition
Raghavan, S., Reid, R. I., Przybelski, S. A., Lesnick, T. G., Graff-Radford, J., Schwarz, C. G., Knopman, D. S., Mielke, M. M., Machulda, M. M., Petersen, R. C., et al. (2021) · Brain Communications · doi:10.1093/braincomms/fcab106 · Cited by 79
Adluru, N., Destiche, D. J., Lu, S. Y.-F., Doran, S. T., Birdsill, A. C., Melah, K. E., Okonkwo, O. C., Alexander, A. L., Dowling, N. M., Johnson, S. C., et al. (2014) · NeuroImage: Clinical · doi:10.1016/j.nicl.2014.04.008 · Cited by 85
Shiva Keihaninejad, A., Ryan, N. S., Malone, I. B., Marc Modat, A., Cash, D. M., Ridgway, G. R., Zhang, H. G., Fox, N. C., & Sebastien Ourselin, A. (2012) · PLoS ONE · doi:10.1371/journal.pone.0045996 · Cited by 85
“uk/fsl/data/ FMRIB58_FA) and then averaging them [5].”
BackgroundMethodA review of the application of deep learning in the detection of Alzheimer's disease
Gao, S., & Lima, D. (2021) · International Journal of Cognitive Computing in Engineering · doi:10.1016/j.ijcce.2021.12.002 · Cited by 96
Naming and the Role of the Uncinate Fasciculus in Language Function
Papagno, C. (2011) · Current Neurology and Neuroscience Reports · doi:10.1007/s11910-011-0219-6 · Cited by 83
Teipel, S. J., the EDSD study group, Grothe, M. J., Filippi, M., Fellgiebel, A., Dyrba, M., Frisoni, G. B., Meindl, T., Bokde, A. L. W., Hampel, H., et al. (2014) · Journal of Alzheimer s Disease · doi:10.3233/jad-131829 · Cited by 82
“Consistent with the study by Douaud and colleagues [15], increase of FA was accompanied by increases of Mode”
InfluentialDeng, F., Wang, Y., Huang, H., Niu, M., Zhong, S., Zhao, L., Qi, Z., Wu, X., Sun, Y., Niu, C., et al. (2017) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2017.09.006 · Cited by 85
Zhang, Y., Schuff, N. W., Camacho, M. R., Chao, L. L., Fletcher, T. P., Yaffe, K. S., Woolley, S. C., Madison, C. A., Rosen, H. J., Miller, B. L., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0066367 · Cited by 85
“However, increased FA could also be methodological artifacts induced by variations in the macroscopic architecture of the long association fibers [60].”
BackgroundMamiya, P. C., Richards, T. L., & Kuhl, P. K. (2018) · Frontiers in Psychology · doi:10.3389/fpsyg.2018.00118 · Cited by 81
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
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