Diffusion tensor imaging in Alzheimer’s disease and mild cognitive impairment.
Open accessAbstract
Structural magnetic resonance imaging (MRI) studies of Alzheimer’s disease and mild cognitive impairment (MCI) have focused on the hippocampus and entorhinal cortex; gray matter structures in the medial temporal lobe. Few studies have investigated the integrity of white matter in patients with AD or MCI. Diffusion tensor imaging (DTI) is a MRI technique that allows for the interrogation of the microstructural integrity of white matter. Based on increases in translational diffusion (mean diffusivity: MD) and decreases directional diffusion (fractional anisotropy: FA) damage to white matter can be assessed. Studies have identified regions of increased MD and decreased FA in patients with AD and MCI in all lobes of the brain, as well as medial temporal lobe structures including the hippocampus, entorhinal cortex and parahippocampal white matter. The pattern of white matter integrity disruption tends to follow an anterior to posterior gradient with greater damage noted in posterior regions in AD and MCI. Recent studies have exploited inter-voxel directional similarities to develop models of white matter pathways, and have used these models to assess the integrity of inter-cerebral connections. Particular focus has been applied to the parahippocampal white matter (including the perforant path) and the posterior cingulum. Although many studies have found DTI indicators of impaired white matter in AD and MCI, other studies have failed to detect any differences in MD or FA between the groups, demonstrating the need for large replicative studies. DTI is an evolving technique and advances in its application ought to provide new insights into AD and MCI.
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Diffusion MRI is more sensitive to brain microstructural changes than conventional volumetric MRI and has been widely used for evaluation of white matter integrity.
“Compared to the conventional volumetric MRI methods, diffusion MRI (dMRI) is more sensitive to the brain microstructural changes and has been widely used for the evaluation of white matter integrity (Bozzali et al., 2002; Mielke et al., 2009; Stebbins and Murphy, 2009; Wang et al., 2019b; Harrison et al., 2020; Veale et al., 2021).”
From Age-dependent microstructure alterations in 5xFAD mice by high-resolution diffusion tensor imaging (2022) · cites this paper as Stebbins and Murphy, 2009
The animal fractional anisotropy data differ from patterns of FA changes in patients with Alzheimer's disease.
“The animal data differ from patterns of FA changes in patients with AD, where regions marked by reduced FA include the temporal lobes, hippocampus, posterior cingulum and occipital lobe (Stebbins and Murphy, 2009).”
From Early Alterations in Functional Connectivity and White Matter Structure in a Transgenic Mouse Model of Cerebral Amyloidosis (2014) · cites this paper as Stebbins and Murphy, 2009
Cites
Mild Cognitive Impairment: Clinical Characterization and Outcome
Petersen, R. C., Smith, G. E., Waring, S. C., Ivnik, R. J., Tangalos, E. G., & Kokmen, E. (1999) · Archives of Neurology · doi:10.1001/archneur.56.3.303 · Cited by 8,980 · see citing works
The 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 4,653 · see citing works
The Medial Temporal Lobe Memory System
Squire, L. R., & Zola-Morgan, S. (1991) · Science · doi:10.1126/science.1896849 · Cited by 3,282 · see citing works
Dysmyelination revealed through MRI as increased radial (but unchanged axial) diffusion of water
Song, S.-K., Sun, S.-W., Ramsbottom, M. J., Chang, C., Russell, J., & Cross, A. H. (2002) · NeuroImage · doi:10.1006/nimg.2002.1267 · Cited by 2,582 · see citing works
Alzheimer's disease: cell-specific pathology isolates the hippocampal formation.
Hyman, B. T., Van Hoesen, G. W., Damasio, A. R., & Barnes, C. L. (1984) · Science · doi:10.1126/science.6474172 · Cited by 2,268 · see citing works
Zola-Morgan, S., Squire, L., & Amaral, D. (1986) · The Journal of Neuroscience · doi:10.1523/jneurosci.06-10-02950.1986 · Cited by 1,997 · see citing works
Whitwell, J. L., Przybelski, S. A., Weigand, S. D., Knopman, D. S., Boeve, B. F., Petersen, R. C., & Jack, C. R. (2007) · Brain · doi:10.1093/brain/awm112 · Cited by 607 · see citing works
Bartzokis, G., Sultzer, D., Lu, P. H., Nuechterlein, K. H., Mintz, J., & Cummings, J. L. (2004) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2003.09.005 · Cited by 363 · see citing works
White matter pathology isolates the hippocampal formation in Alzheimer's disease
Salat, D. H., Tuch, D. S., van der Kouwe, A. J. W., Greve, D. N., Pappu, V., Lee, S. Y., Hevelone, N. D., Zaleta, A. K., Growdon, J. H., Corkin, S., et al. (2010) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2008.03.013 · Cited by 279 · see citing works
White matter integrity linked to functional impairments in aging and early Alzheimer’s disease
Kavcic, V., Ni, H., Zhu, T., Zhong, J., & Duffy, C. J. (2008) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2008.07.001 · Cited by 65 · see citing works
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Spurious group differences due to head motion in a diffusion MRI study
Yendiki, A., Koldewyn, K., Kakunoori, S., Kanwisher, N., & Fischl, B. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2013.11.027 · Cited by 508 · see citing works
Zetterberg, H., Skillbäck, T., Mattsson, N., Trojanowski, J. Q., Portelius, E., Shaw, L. M., Weiner, M. W., Blennow, K., & Initiative, F. T. A. D. N. (2016) · JAMA Neurology · doi:10.1001/jamaneurol.2015.3037 · Cited by 487 · see citing works
Effectiveness of regional DTI measures in distinguishing Alzheimer’s disease, MCI, and normal aging
Nir, T. M., Jahanshad, N., Villalon-Reina, J. E., Toga, A. W., Jack, C. R., Weiner, M. W., & Thompson, P. M. (2013) · NeuroImage: Clinical · doi:10.1016/j.nicl.2013.07.006 · Cited by 348 · see citing works
Ryan, N. S., Keihaninejad, S., Shakespeare, T. J., Lehmann, M., Crutch, S. J., Malone, I. B., Thornton, J. S., Mancini, L., Hyare, H., Yousry, T., et al. (2013) · Brain · doi:10.1093/brain/awt065 · Cited by 205 · see citing works
Suri, S., Heise, V., Trachtenberg, A. J., & Mackay, C. E. (2013) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2013.10.010 · Cited by 183 · see citing works
Gold, B. T., Johnson, N. F., Powell, D. K., & Smith, C. D. (2012) · Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease · doi:10.1016/j.bbadis.2011.07.009 · Cited by 170 · see citing works
The APOE ɛ4 allele modulates brain white matter integrity in healthy adults
Heise, V, Filippini, N., Ebmeier, K. P., & Mackay, C. E. (2011) · Molecular Psychiatry · doi:10.1038/mp.2010.90 · Cited by 152 · see citing works
Gold, B. T., Powell, D. K., Andersen, A. H., & Smith, C. D. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.05.036 · Cited by 112 · see citing works
A review of β-amyloid neuroimaging in Alzheimer's disease
Adlard, P. A., Tran, B. A., Finkelstein, D. I., Desmond, P. M., Johnston, L. A., Bush, A. I., & Egan, G. F. (2014) · Frontiers in Neuroscience · doi:10.3389/fnins.2014.00327 · Cited by 93 · see citing works
Huang, C.-W., Tsai, M.-H., Chen, N.-C., Chen, W.-H., Lu, Y.-T., Lui, C.-C., Chang, Y.-T., Chang, W.-N., Chang, A. Y. W., & Chang, C.-C. (2015) · Thrombosis and Haemostasis · doi:10.1160/th14-11-0938 · Cited by 82 · see citing works
Memory binding and white matter integrity in familial Alzheimer’s disease
Parra, M. A., Saarimäki, H., Bastin, M. E., Londoño, A. C., Pettit, L., Lopera, F., Della Sala, S., & Abrahams, S. (2015) · Brain · doi:10.1093/brain/awv048 · Cited by 79 · see citing works
Grandjean, J., Schroeter, A., He, P., Tanadini, M., Keist, R., Krstic, D., Konietzko, U., Klohs, J., Nitsch, R. M., & Rudin, M. (2014) · The Journal of Neuroscience · doi:10.1523/jneurosci.4762-13.2014 · Cited by 70 · see citing works
Hong, Y. J., Yoon, B., Lim, S.-C., Shim, Y. S., Kim, J.-Y., Ahn, K. J., Han, I.-W., & Yang, D. W. (2013) · Neurological Sciences · doi:10.1007/s10072-012-1225-4 · Cited by 48 · see citing works
Age-related white matter integrity differences in oldest-old without dementia
Bennett, I. J., Greenia, D. E., Maillard, P., Sajjadi, S. A., DeCarli, C., Corrada, M. M., & Kawas, C. H. (2017) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2017.04.013 · Cited by 41 · see citing works
Staging Neurodegenerative Disorders: Structural, Regional, Biomarker, and Functional Progressions
Archer, T., Kostrzewa, R. M., Beninger, R. J., & Palomo, T. (2011) · Neurotoxicity Research · doi:10.1007/s12640-010-9190-2 · Cited by 34 · see citing works
Alzheimer's disease biomarkers: correspondence between human studies and animal models
Sabbagh, J. J., Kinney, J. W., & Cummings, J. L. (2013) · Neurobiology of Disease · doi:10.1016/j.nbd.2013.04.010 · Cited by 27 · see citing works
Diffusion tensor magnetic resonance imaging of the brain in app transgenic mice: A cohort study.
Müller, H.-P., Kassubek, J., Vernikouskaya, I., Ludolph, A. C., Stiller, D., & Rasche, V. (2013) · PLoS ONE · doi:10.1371/journal.pone.0067630 · Cited by 22 · see citing works
Diffusion MRI detects early brain microstructure abnormalities in 2-month-old 3×Tg-AD mice
Falangola, M. F., Nie, X., Ward, R., McKinnon, E. T., Dhiman, S., Nietert, P. J., Helpern, J. A., & Jensen, J. H. (2020) · NMR in Biomedicine · doi:10.1002/nbm.4346 · Cited by 22 · see citing works
Han, X., Maharjan, S., Chen, J., Zhao, Y., Qi, Y., White, L. E., Johnson, G. A., & Wang, N. (2024) · NeuroImage · doi:10.1016/j.neuroimage.2024.120734 · Cited by 15 · see citing works
Age-dependent microstructure alterations in 5xFAD mice by high-resolution diffusion tensor imaging
Maharjan, S., Tsai, A. P., Lin, P. B., Ingraham, C., Jewett, M. R., Landreth, G. E., Oblak, A. L., & Wang, N. (2022) · Frontiers in Neuroscience · doi:10.3389/fnins.2022.964654 · Cited by 11 · see citing works
Falangola, M. F., Nie, X., Voltin, J., Ward, R., Dhiman, S., Nietert, P. J., & Jensen, J. H. (2022) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2022.09.002 · Cited by 6 · see citing works
- Authors
- Stebbins, G. T., & Murphy, C. M.
- Affiliations
- Rush University Medical Center (US)
- Corresponding author
- Stebbins, G. T.
- ORCID
- Stebbins, G. T.
- Venue
- Behavioural Neurology
- Publisher
- Wiley
- Published
- 2009
- Volume
- 21
- Issue
- 1-2
- Pages
- 39-49
- ISSN
- 0953-4180 (ISSN-L)
- 1875-8584
- PMC
- PMC3010401
- OpenAlex
- W4231345253
- Cited by
- 245
- References
- 10
- Citations by year
- 2026: 5 · 2025: 13 · 2024: 8 · 2023: 10 · 2022: 12 · 2021: 13 · 2020: 10 · 2019: 11 · 2018: 11 · 2017: 15 · 2016: 17 · 2015: 20 · 2014: 23 · 2013: 25 · 2012: 14
- FWCI
- 10.72
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Behavioural Neurology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Institute on Aging (P01 AG09466)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Keywords
- Alzheimer's disease, mild cognitive impairment, white matter integrity, diffusion tensor imaging, mean diffusivity, fractional anisotropy, perforant path, posterior cingulum, hippocampus, entorhinal cortex, white matter microstructure
- MeSH terms
- Alzheimer Disease, Brain, Brain Mapping, Cognition Disorders, Humans, Image Processing, Computer-Assisted, Nerve Fibers, Myelinated, Anisotropy, Diffusion Magnetic Resonance Imaging
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