Fibre-specific white matter reductions in Alzheimer’s disease and mild cognitive impairment
Open accessAbstract
Alzheimer's disease is increasingly considered a large-scale network disconnection syndrome, associated with progressive aggregation of pathological proteins, cortical atrophy, and functional disconnections between brain regions. These pathological changes are posited to arise in a stereotypical spatiotemporal manner, targeting intrinsic networks in the brain, most notably the default mode network. While this network-specific disruption has been thoroughly studied with functional neuroimaging, changes to specific white matter fibre pathways within the brain's structural networks have not been closely investigated, largely due to the challenges of modelling complex white matter structure. Here, we applied a novel technique known as 'fixel-based analysis' to comprehensively investigate fibre tract-specific differences at a within-voxel level (called 'fixels') to assess potential axonal loss in subjects with Alzheimer's disease and mild cognitive impairment. We hypothesized that patients with Alzheimer's disease would exhibit extensive degeneration across key fibre pathways connecting default network nodes, while patients with mild cognitive impairment would exhibit selective degeneration within fibre pathways connecting regions previously identified as functionally implicated early in Alzheimer's disease. Diffusion MRI data from Alzheimer's disease (n = 49), mild cognitive impairment (n = 33), and healthy elderly control subjects (n = 95) were obtained from the Australian Imaging, Biomarkers and Lifestyle study of ageing. We assessed microstructural differences in fibre density, and macrostructural differences in fibre bundle morphology using fixel-based analysis. Whole-brain analysis was performed to compare groups across all white matter fixels. Subsequently, we performed a tract of interest analysis comparing fibre density and cross-section across 11 selected white matter tracts, to investigate potentially subtle degeneration within fibre pathways in mild cognitive impairment, initially by clinical diagnosis alone, and then by including amyloid status (i.e. a positive or negative amyloid PET scan). Our whole-brain analysis revealed significant white matter loss manifesting both microstructurally and macrostructurally in Alzheimer's disease patients, evident in specific fibre pathways associated with default mode network nodes. Reductions in fibre density and cross-section in mild cognitive impairment patients were only exhibited within the posterior cingulum when statistical analyses were limited to tracts of interest. Interestingly, these degenerative changes did not appear to be associated with high amyloid accumulation, given that amyloid-negative, but not positive, mild cognitive impairment subjects exhibited subtle focal left posterior cingulum deficits. The findings of this study demonstrated a stereotypical distribution of white matter degeneration in patients with Alzheimer's disease, which was in line with canonical findings from other imaging modalities, and with a network-based conceptualization of the disease.awx355media15726254535001.
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DTI alterations observed in the corticospinal tract in the current study cannot be unambiguously attributed to that tract and may be due to alterations in crossing fibres such as the superior longitudinal fasciculus or corpus callosum.
“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 Mito et al., 2018
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Cites
The Amyloid Hypothesis of Alzheimer’s Disease: Progress and Problems on the Road to Therapeutics
Hardy, J., & Selkoe, D. J. (2002) · Science · doi:10.1126/science.1072994 · Cited by 13,864 · see citing works
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
Mild cognitive impairment as a diagnostic entity
Petersen, R. C. (2004) · Journal of Internal Medicine · doi:10.1111/j.1365-2796.2004.01388.x · Cited by 7,864 · see citing works
Nonparametric 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 · see citing works
N4ITK: Improved N3 Bias Correction
Tustison, N. J., Avants, B., Cook, P. A., Zheng, Y., Egan, A., Yushkevich, P. A., & Gee, J. C. (2010) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2010.2046908 · Cited by 6,119 · see citing works
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., Watkins, K., Ciccarelli, O., Cader, M., Matthews, P., et al. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.02.024 · Cited by 6,035 · see citing works
Wardlaw, J. M., Smith, E. E., Biessels, G. J., Cordonnier, C., Fazekas, F., Frayne, R., Lindley, R. I., O'Brien, J. T., Barkhof, F., Benavente, O. R., et al. (2013) · The Lancet Neurology · doi:10.1016/s1474-4422(13)70124-8 · Cited by 5,560 · see citing works
SMITH, S., & NICHOLS, T. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2008.03.061 · Cited by 5,250 · see citing works
Winblad, 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 · see citing works
Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade
Jack, C. R., Knopman, D. S., Jagust, W. J., Shaw, L. M., Aisen, P. S., Weiner, M. W., Petersen, R. C., & Trojanowski, J. Q. (2010) · The Lancet Neurology · doi:10.1016/s1474-4422(09)70299-6 · Cited by 4,806 · see citing works
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 3,920 · see citing works
Greicius, M. D., Srivastava, G., Reiss, A. L., & Menon, V. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0308627101 · Cited by 3,684 · see citing works
Probabilistic diffusion tractography with multiple fibre orientations: What can we gain?
Behrens, T. E. J., Berg, H. J., Jbabdi, S., Rushworth, M. F. S., & Woolrich, M. W. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2006.09.018 · Cited by 3,471 · see citing works
Andersson, J., & Sotiropoulos, S. N. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.10.019 · Cited by 3,439 · see citing works
Buckner, R. L., Sepulcre, J., Talukdar, T., Krienen, F. M., Liu, H., Hedden, T., Andrews-Hanna, J. R., Sperling, R. A., & Johnson, K. A. (2009) · The Journal of Neuroscience · doi:10.1523/jneurosci.5062-08.2009 · Cited by 2,862 · see citing works
White matter integrity, fiber count, and other fallacies: The do's and don'ts of diffusion MRI
Jones, D. K., Knösche, T. R., & Turner, R. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2012.06.081 · Cited by 2,479 · see citing works
Toward a quantitative assessment of diffusion anisotropy
Pierpaoli, C. M., & Basser, P. J. (1996) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910360612 · Cited by 2,392 · see citing works
Neurodegenerative Diseases Target Large-Scale Human Brain Networks
Seeley, W. W., Crawford, R. K., Zhou, J., Miller, B. L., & Greicius, M. D. (2009) · Neuron · doi:10.1016/j.neuron.2009.03.024 · Cited by 2,350 · see citing works
Villemagne, V. L., Burnham, S., Bourgeat, P., Brown, B., Ellis, K. A., Salvado, O., Szoeke, C., Macaulay, S. L., Martins, R., Maruff, P., et al. (2013) · The Lancet Neurology · doi:10.1016/s1474-4422(13)70044-9 · Cited by 2,279 · see citing works
Self-citationTournier, J., Calamante, F., & Connelly, A. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.02.016 · Cited by 2,191 · see citing works
Self-citationResting-State Functional Connectivity Reflects Structural Connectivity in the Default Mode Network
Greicius, M. D., Supekar, K., Menon, V., & Dougherty, R. F. (2009) · Cerebral Cortex · doi:10.1093/cercor/bhn059 · Cited by 2,175 · see citing works
Buckner, R. L., Snyder, A. Z., Shannon, B. J., LaRossa, G., Sachs, R., Fotenos, A. F., Sheline, Y. I., Klunk, W. E., Mathis, C. A., Morris, J. C., et al. (2005) · The Journal of Neuroscience · doi:10.1523/jneurosci.2177-05.2005 · Cited by 2,140 · see citing works
Fiber Tract–based Atlas of Human White Matter Anatomy
Wakana, S., Jiang, H., Nagae‐Poetscher, L. M., van Zijl, P. C. M., & Mori, S. (2004) · Radiology · doi:10.1148/radiol.2301021640 · Cited by 2,023 · see citing works
Metabolic reduction in the posterior cingulate cortex in very early Alzheimer's disease
Minoshima, S., Giordani, B., Berent, S., Frey, K. A., Foster, N. L., & Kuhl, D. E. (1997) · Annals of Neurology · doi:10.1002/ana.410420114 · Cited by 1,802 · see citing works
Mitchell, A. J., & Shiri‐Feshki, M. (2009) · Acta Psychiatrica Scandinavica · doi:10.1111/j.1600-0447.2008.01326.x · Cited by 1,659 · cited 1× · see citing works
“…are at higher risk of progressing to Alzheimer’s disease than cognitively unimpaired elderly individuals (Petersen, 2004; Gauthier et al., 2006; Mitchell and Shiri-Feshki, 2009), only those MCI subjects who also exhibit a high amyloid-b accumulation are believed to represent a prodromal…”
BackgroundTournier, J.-D., Calamante, F., Gadian, D. G., & Connelly, A. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.07.037 · Cited by 1,635 · see citing works
Self-citationFiber tract-based atlas of human white matter anatomy
Wakana, S. (2006) · Medical Entomology and Zoology · Cited by 1,544 · see citing works
Limbic connections of the orbital and medial prefrontal cortex in macaque monkeys
Carmichael, S. T., & Price, J. L. (1995) · Journal of Comparative Neurology · doi:10.1002/cne.903630408 · Cited by 1,197 · see citing works
MRI Atlas of Human White Matter
Mori, S. (2005) · Cited by 1,103 · see citing works
Jeurissen, B., Leemans, A., Tournier, J., Jones, D. K., & Sijbers, J. (2013) · Human Brain Mapping · doi:10.1002/hbm.22099 · Cited by 1,088 · see citing works
Self-citationFrequent amyloid deposition without significant cognitive impairment among the elderly
Aizenstein, H. J., Nebes, R. D., Saxton, J. A., Price, J. C., Mathis, C. A., Tsopelas, N. D., Ziolko, S. K., James, J. A., Snitz, B. E., Houck, P. R., et al. (2008) · Archives of Neurology · doi:10.1001/archneur.65.11.1509 · Cited by 1,059 · see citing works
[ <sup>11</sup> C]PIB in a nondemented population: Potential antecedent marker of Alzheimer disease
Mintun, M. A., LaRossa, G. N., Sheline, Y. I., Dence, C. S., Lee, S. Y., Mach, R. H., Klunk, W. E., Mathis, C. A., DeKosky, S. T., & Morris, J. C. (2006) · Neurology · doi:10.1212/01.wnl.0000228230.26044.a4 · Cited by 1,036 · see citing works
MRI atlas of human white matter
Ling, C. L., & Rumpel, H. (2006) · Concepts in Magnetic Resonance Part A · doi:10.1002/cmr.a.20052 · Cited by 1,021 · see citing works
A white matter disorder in dementia of the Alzheimer type: A pathoanatomical study
Brun, A., & Englund, E. (1986) · Annals of Neurology · doi:10.1002/ana.410190306 · Cited by 1,014 · see citing works
Amyloid imaging results from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging
Rowe, C. C., Ellis, K. A., Rimajova, M., Bourgeat, P., Pike, K. E., Jones, G., Fripp, J., Tochon-Danguy, H., Morandeau, L., O'Keefe, G., et al. (2010) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2010.04.007 · Cited by 986 · see citing works
Self-citationEllis, K. A., Bush, A. I., Darby, D., Fazio, D. D., Foster, J. K., Hudson, P. J., Lautenschlager, N. T., Lenzo, N. P., Martins, R. N., Maruff, P. T., et al. (2009) · International Psychogeriatrics · doi:10.1017/s1041610209009405 · Cited by 970 · see citing works
Self-citationComposite hindered and restricted model of diffusion (CHARMED) MR imaging of the human brain
Assaf, Y., & Basser, P. J. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.03.042 · Cited by 856 · see citing works
Diffusion MRI noise mapping using random matrix theory
Veraart, J., Fieremans, E., & Novikov, D. S. (2015) · Magnetic Resonance in Medicine · doi:10.1002/mrm.26059 · Cited by 793 · see citing works
Prion-like mechanisms in neurodegenerative diseases
Frost, B., & Diamond, M. I. (2010) · Nature Reviews Neuroscience · doi:10.1038/nrn2786 · Cited by 776 · see citing works
SIFT: Spherical-deconvolution informed filtering of tractograms
Smith, R. E., Tournier, J.-D., Calamante, F., & Connelly, A. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2012.11.049 · Cited by 752 · see citing works
Self-citationA network diffusion model of disease progression in dementia
Raj, A., Kuceyeski, A., & Weiner, M. (2012) · Neuron · doi:10.1016/j.neuron.2011.12.040 · Cited by 723 · see citing works
Predicting Regional Neurodegeneration from the Healthy Brain Functional Connectome
Zhou, J., Gennatas, E. D., Kramer, J. H., Miller, B. L., & Seeley, W. W. (2012) · Neuron · doi:10.1016/j.neuron.2012.03.004 · Cited by 706 · see citing works
A network dysfunction perspective on neurodegenerative diseases
Palop, J. J., Chin, J., & Mucke, L. (2006) · Nature · doi:10.1038/nature05289 · Cited by 683 · see citing works
Alzheimer' Disease as a Disconnection Syndrome?
Delbeuck, X., der Linden, M. V., & Collette, F. (2003) · Neuropsychology Review · doi:10.1023/a:1023832305702 · Cited by 681 · see citing works
Incidence and outcome of mild cognitive impairment in a population-based prospective cohort
Larrieu, S., Letenneur, L., Orgogozo, J., Fabrigoule, C., Amieva, H., Carret, N. L., Barberger‐Gateau, P., & Dartigues, J. (2002) · Neurology · doi:10.1212/01.wnl.0000034176.07159.f8 · Cited by 663 · see citing works
Investigating white matter fibre density and morphology using fixel-based analysis.
Raffelt, D. A., Tournier, J.-D., Smith, R. E., Vaughan, D. N., Jackson, G., Ridgway, G. R., & Connelly, A. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2016.09.029 · Cited by 620 · cited 19× · see citing works
“…for both microstructural changes in density (with the fibre density metric), and macrostructural, morphometric changes (with the fibre bundle cross-section metric) enables a more comprehensive analysis of total intra-axonal volume changes within a fibre pathway (FDC metric) (Raffelt et al., 2017).”
BackgroundMethodInfluentialSelf-citationRaffelt, D., Tournier, J.-D., Rose, S., Ridgway, G., Henderson, R., Crozier, S., Salvado, O., & Connelly, A. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.10.045 · Cited by 616 · see citing works
Self-citationSiebner, H. R., Riemenschneider, M. J., Willoch, F., Minoshima, S., Schwaiger, M., Kurz, A., Drzezga, A. E., & Lautenschlager, N. T. (2003) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-003-1194-1 · Cited by 603 · see citing works
Oishi, K., Faria, A. V., Jiang, H., Li, X., Akhter, K., Zhang, J., Hsu, J. T., Miller, M. I., van Zijl, P. C. M., Albert, M., et al. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.01.002 · Cited by 574 · see citing works
Resting state fMRI in Alzheimer's disease: beyond the default mode network
Agosta, F., Pievani, M., Geroldi, C., Copetti, M., Frisoni, G. B., & Filippi, M. (2011) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2011.06.007 · Cited by 572 · see citing works
The road to restoring neural circuits for the treatment of Alzheimer's disease
Canter, R. G., Penney, J., & Tsai, L.-H. (2016) · Nature · doi:10.1038/nature20412 · Cited by 565 · see citing works
Topography of the Human Corpus Callosum
LACOSTE, M. C. D., Kirkpatrick, J. B., & Ross, E. D. (1985) · Journal of Neuropathology & Experimental Neurology · doi:10.1097/00005072-198511000-00004 · Cited by 537 · see citing works
Alexander, G. E., Chen, K., Pietrini, P., Rapoport, S. I., & Reiman, E. M. (2002) · American Journal of Psychiatry · doi:10.1176/appi.ajp.159.5.738 · Cited by 532 · see citing works
Cascading network failure across the Alzheimer’s disease spectrum
Jones, D. T., Knopman, D. S., Gunter, J. L., Graff‐Radford, J., Vemuri, P., Boeve, B. F., Petersen, R. C., Weiner, M. W., & Jack, C. R. (2015) · Brain · doi:10.1093/brain/awv338 · Cited by 532 · see citing works
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., et al. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.12.008 · Cited by 514 · see citing works
Diffusion tensor imaging of cingulum fibers in mild cognitive impairment and Alzheimer disease
Zhang, Y., Schuff, N. W., Jahng, G., Bayne, W., Mori, S., Schad, L. R., Mueller, S. G., Du, A., Kramer, J. H., Yaffe, K. S., et al. (2007) · Neurology · doi:10.1212/01.wnl.0000250326.77323.01 · Cited by 508 · see citing works
Alzheimer disease therapy—moving from amyloid-β to tau
Giacobini, E., & Gold, G. (2013) · Nature Reviews Neurology · doi:10.1038/nrneurol.2013.223 · Cited by 483 · see citing works
Aβ amyloid and glucose metabolism in three variants of primary progressive aphasia
Rabinovici, G. D., Jagust, W. J., Furst, A. J., Ogar, J. M., Racine, C. A., Mormino, E. C., O'Neil, J. P., Lal, R. A., Dronkers, N. F., Miller, B. L., et al. (2008) · Annals of Neurology · doi:10.1002/ana.21451 · Cited by 477 · see citing works
Rose, S. (2000) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp.69.4.528 · Cited by 465 · see citing works
Methodological considerations on tract-based spatial statistics (TBSS)
Bach, M., Laun, F. B., Leemans, A., Tax, C. M. W., Biessels, G. J., Stieltjes, B., & Maier-Hein, K. H. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.06.021 · Cited by 445 · see citing works
Efferent Association Pathways from the Rostral Prefrontal Cortex in the Macaque Monkey
Petrides, M., & Pandya, D. Ν. (2007) · Journal of Neuroscience · doi:10.1523/jneurosci.2419-07.2007 · Cited by 437 · see citing works
Extent and distribution of white matter hyperintensities in normal aging, MCI, and AD
Yoshita, M., Fletcher, E., Harvey, D., Ortega, M., Martinez, O., Mungas, D. M., Reed, B. R., & DeCarli, C. S. (2006) · Neurology · doi:10.1212/01.wnl.0000249119.95747.1f · Cited by 434 · see citing works
β-Amyloid burden in healthy aging: Regional distribution and cognitive consequences
Rodrigue, K. M., Kennedy, K. M., Devous, M. D., Rieck, J. R., Hebrank, A. C., Diaz-Arrastia, R., Mathews, D., & Park, D. C. (2012) · Neurology · doi:10.1212/wnl.0b013e318245d295 · Cited by 419 · see citing works
Limbic hypometabolism in Alzheimer's disease and mild cognitive impairment
Nestor, P. J., Fryer, T. D., Smielewski, P. S., & Hodges, J. R. (2003) · Annals of Neurology · doi:10.1002/ana.10669 · Cited by 414 · see citing works
A meta-analysis of diffusion tensor imaging in mild cognitive impairment and Alzheimer's disease
Sexton, C. E., Kalu, U. G., Filippini, N., Mackay, C. E., & Ebmeier, K. P. (2011) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2010.05.019 · Cited by 410 · see citing works
Neuropathologic Outcome of Mild Cognitive Impairment Following Progression to Clinical Dementia
Jicha, G. A., Parisi, J. E., Dickson, D. W., Johnson, K., Cha, R., Ivnik, R. J., Tangalos, E. G., Boeve, B. F., Knopman, D. S., Braak, H., et al. (2006) · Archives of Neurology · doi:10.1001/archneur.63.5.674 · Cited by 399 · see citing works
Absolute diffusivities define the landscape of white matter degeneration in Alzheimer’s disease
Acosta-Cabronero, J., Williams, G. B., Pengas, G., & Nestor, P. J. (2010) · Brain · doi:10.1093/brain/awp257 · Cited by 393 · see citing works
Raffelt, D., Smith, R., Ridgway, G., Tournier, J., Vaughan, D., Rose, S., Henderson, R., & Connelly, A. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.05.039 · Cited by 379 · see citing works
Self-citationVillain, N., Desgranges, B., Viader, F., de la Sayette, V., Mezenge, F., Landeau, B., Baron, J.-C., Eustache, F., & Chetelat, G. (2008) · Journal of Neuroscience · doi:10.1523/jneurosci.1392-08.2008 · Cited by 366 · see citing works
van den Heuvel, M., Mandl, R., Luigjes, J., & Hulshoff Pol, H. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.2964-08.2008 · Cited by 349 · see citing works
Challenges and limitations of quantifying brain connectivity <i>in vivo</i> with diffusion MRI
Jones, D. K. (2010) · Imaging in Medicine · doi:10.2217/iim.10.21 · Cited by 321 · see citing works
Leyton, C. E., Villemagne, V. L., Savage, S. A., Pike, K. E., Ballard, K. J., Piguet, O., Burrell, J. R., Rowe, C. C., & Hodges, J. R. (2011) · Brain · doi:10.1093/brain/awr216 · Cited by 311 · see citing works
Self-citationZhang, Y., Zhang, J., Oishi, K., Faria, A. V., Jiang, H., Li, X., Akhter, K., Rosa-Neto, P., Pike, G. B., Evans, A., et al. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.05.049 · Cited by 297 · see citing works
Symmetric diffeomorphic registration of fibre orientation distributions
Raffelt, D., Tournier, J.-D., Fripp, J., Crozier, S., Connelly, A., & Salvado, O. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.02.014 · Cited by 281 · see citing works
Self-citationDiffusion tensor imaging in mild cognitive impairment and Alzheimerʼs disease: a review
Chua, T. C., Wen, W., Slavin, M. J., & Sachdev, P. S. (2008) · Current Opinion in Neurology · doi:10.1097/wco.0b013e3282f4594b · Cited by 273 · see citing works
Bosch, B., Arenaza-Urquijo, E. M., Rami, L., Sala-Llonch, R., Junqué, C., Solé-Padullés, C., Peña-Gómez, C., Bargalló, N., Molinuevo, J. L., & Bartrés-Faz, D. (2012) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2010.02.004 · Cited by 272 · see citing works
Fellgiebel, A., Müller, M. J., Wille, P. R., Dellani, P. R., Scheurich, A., Schmidt, L., & Stoeter, P. (2005) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2004.11.006 · Cited by 261 · see citing works
White matter tract integrity in aging and Alzheimer's disease
Damoiseaux, J. S., Smith, S. M., Witter, M. P., Sanz‐Arigita, E., Barkhof, F., Scheltens, P., Stam, C. J., Zarei, M., & Rombouts, S. A. R. B. (2008) · Human Brain Mapping · doi:10.1002/hbm.20563 · Cited by 249 · see citing works
WHITE MATTER CHANGES IN DEMENTIA OF ALZHEIMER'S TYPE: BIOCHEMICAL AND NEUROPATHOLOGICAL CORRELATES
ENGLUND, E., BRUN, A., & ALLING, C. (1988) · Brain · doi:10.1093/brain/111.6.1425 · Cited by 228 · see citing works
Jones, D. K., Christiansen, K. F., Chapman, R. J., & Aggleton, J. P. (2013) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2012.11.018 · Cited by 223 · see citing works
Rowe, C. C., Bourgeat, P., Ellis, K. A., Brown, B., Lim, Y. Y., Mulligan, R., Jones, G., Maruff, P., Woodward, M., Price, R., et al. (2013) · Annals of Neurology · doi:10.1002/ana.24040 · Cited by 222 · see citing works
Self-citationVernooij, M. W., de Groot, M., van der Lugt, A., Ikram, M. A., Krestin, G. P., Albert Hofman, D., Niessen, W. J., & Breteler, M. M. B. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.07.052 · Cited by 203 · see citing works
White matter microstructure underlying default mode network connectivity in the human brain
Teipel, S. J., Bokde, A. L. W., Meindl, T., Amaro, E., Soldner, J., Reiser, M. F., Herpertz, S. C., Möller, H., & Hampel, H. J. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.10.067 · Cited by 200 · see citing works
Network Dysfunction in Alzheimer's Disease: Refining the Disconnection Hypothesis
Brier, M. R., Thomas, J., & Ances, B. M. (2014) · Brain Connectivity · doi:10.1089/brain.2014.0236 · Cited by 192 · see citing works
Schwarz, C., Reid, R. I., Gunter, J., Senjem, M., Przybelski, S., Zuk, S., Whitwell, J., Vemuri, P., Josephs, K., Kantarci, K., et al. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.03.026 · Cited by 171 · 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 · cited 2× · see citing works
“…the past decade, numerous DTI studies have re- ported spatial and temporal changes in white matter that arise over the course of Alzheimer’s disease, the results of which are summarized in a number of extensive reviews (Chua et al., 2008; Sexton et al., 2011; Gold et al., 2012; Mak et al., 2017).”
BackgroundWu, Y., Sun, D., Wang, Y., Wang, Y., & Ou, S. (2016) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2016.00084 · Cited by 161 · see citing works
Focal posterior cingulate atrophy in incipient Alzheimer's disease
Pengas, G., Hodges, J. R., Watson, P., & Nestor, P. J. (2008) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2008.03.014 · Cited by 150 · see citing works
Hau, J., Sarubbo, S., Perchey, G., Crivello, F., Zago, L., Mellet, E., Jobard, G., Joliot, M., Mazoyer, B. M., Tzourio-Mazoyer, N., et al. (2016) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2016.00058 · Cited by 142 · cited 1× · see citing works
“Degeneration of the inferior fronto-occipital fascic- ulus could also be associated with disconnections to DMN regions such as the angular gyrus to which it is believed to connect (Hau et al., 2016).”
BackgroundContemplating Alzheimer’s Disease and the Contribution of White Matter Hyperintensities
Brickman, A. M. (2013) · Current Neurology and Neuroscience Reports · doi:10.1007/s11910-013-0415-7 · Cited by 136 · see citing works
Reorientation of fiber orientation distributions using apodized point spread functions
Raffelt, D., Tournier, J.-D., Crozier, S., Connelly, A., & Salvado, O. (2012) · Magnetic Resonance in Medicine · doi:10.1002/mrm.23058 · Cited by 132 · see citing works
Self-citationTaoka, T., Iwasaki, S., Sakamoto, M., Nakagawa, H., Fukusumi, A., Myochin, K., Hirohashi, S., Hoshida, T., & Kichikawa, K. (2006) · PubMed Central · Cited by 127 · see citing works
Pathogenesis and Disease-modifying Therapy in Alzheimer's Disease: The Flat Line of Progress
Castellani, R. J., & Perry, G. L. (2012) · Archives of Medical Research · doi:10.1016/j.arcmed.2012.09.009 · Cited by 103 · see citing works
Thal, D. R., Attems, J., & Ewers, M. (2014) · Journal of Alzheimer s Disease · doi:10.3233/jad-141461 · Cited by 100 · see citing works
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 · see citing works
Tract-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 88 · see citing works
Tract-specific white matter hyperintensities disrupt neural network function in Alzheimer’s disease
Taylor, A. N. W., Kambeitz-Ilankovic, L., Gesierich, B., Simon-Vermot, L., Franzmeier, N., Araque Caballero, M. Á., Müller, S., Hesheng, L., Ertl-Wagner, B., Bürger, K., et al. (2017) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2016.06.2358 · Cited by 73 · see citing works
Mak, E., Gabel, S., Mirette, H., Su, L., Williams, G. B., Waldman, A., Wells, K., Ritchie, K., Ritchie, C., & O’Brien, J. (2017) · Ageing Research Reviews · doi:10.1016/j.arr.2016.10.001 · Cited by 71 · see citing works
Wright, D. K., Johnston, L. A., Kershaw, J., Ordidge, R. J., O'Brien, T. J., & Shultz, S. R. (2017) · Journal of Neurotrauma · doi:10.1089/neu.2016.4730 · Cited by 60 · see citing works
Altamura, C., Scrascia, F., Quattrocchi, C. C., Errante, Y., Gangemi, E., Curcio, G., Ursini, F., Silvestrini, M., Maggio, P., Zobel, B. B., et al. (2016) · Journal of Clinical Neurology · doi:10.3988/jcn.2016.12.2.201 · Cited by 59 · see citing works
Fibre-specific white matter changes in multiple sclerosis patients with optic neuritis
Gajamange, S., Raffelt, D., Dhollander, T., Lui, E. H., van der Walt, A., Kilpatrick, T., Fielding, J., Connelly, A., & Kolbe, S. (2017) · NeuroImage: Clinical · doi:10.1016/j.nicl.2017.09.027 · Cited by 55 · see citing works
Self-citationDoan, N. T., Engvig, A., Persson, K., Alnæs, D., Kaufmann, T., Rokicki, J., Córdova‐Palomera, A., Moberget, T., Brækhus, A., Barca, M. L., et al. (2017) · Scientific Reports · doi:10.1038/srep45131 · Cited by 48 · see citing works
Tract‐specific atrophy in focal epilepsy: Disease, genetics, or seizures?
Vaughan, D., Raffelt, D., Curwood, E., Tsai, M.-H., Tournier, J.-D., Connelly, A., & Jackson, G. (2017) · Annals of Neurology · doi:10.1002/ana.24848 · Cited by 44 · see citing works
Self-citationWhite matter alterations at pubertal onset
Genc, S., Seal, M., Dhollander, T., Malpas, C., Hazell, P., & Silk, T. (2017) · bioRxiv · doi:10.1016/j.neuroimage.2017.05.017 · Cited by 40 · see citing works
Self-citationWang, T., Shi, F., Jin, Y., Yap, P., Chong-yaw Wee, A., Zhang, J., Yang, C., Li, X., Xiao, S., & Shen, D. G. (2016) · Neural Plasticity · doi:10.1155/2016/2947136 · Cited by 38 · see citing works
Nakata, Y., Sato, N., Abe, O., Shikakura, S., Arima, K., Furuta, N., Uno, M., Hirai, S., Masutani, Y., Ohtomo, K., et al. (2008) · Radiation Medicine · doi:10.1007/s11604-008-0258-3 · Cited by 32 · see citing works
Flagged first, then by citations
Research works printed but not linked: 5
- Dhollander T, Connelly A. A novel iterative approach to reap the benefits of multi-tissue CSD from just single-shell ( + b = 0) diffu- sion MRI data. In: 24th International Society of Magnetic Resonance in Medicine, vol. 24. Singapore; 2016, p. 3010.
- Dhollander T, Raffelt D, Connelly A. Towards interpretation of 3- tissue constrained spherical deconvolution results in pathology. In: 25th International Society of Magnetic Resonance in Medicine, vol. 25. Honolulu, Hawaii; 2017, p. 1815.
- Dhollander T, Raffelt D, Connelly A. Unsupervised 3-tissue response function estimation from single-shell or multi-shell diffusion MR data without a co-registered T1 image. Proceedings of ISMRM Workshop on Breaking the Barriers of Diffusion MRI. Lisbon, Portugal; 2016, p.
- Englund E, Brun A, Alling C. White matter changes in dementia of Alzheimer's type. Brain 1988; 111: 1425-39.
- Mintun MA, Larossa GN, Sheline YI, Dence CS, Lee SY, Mach RH, et al. [11C] PIB in a nondemented population Potential antecedent marker of Alzheimer disease. Neurology 2006; 67: 446-52.
Cited by
Sorted by citations
MRtrix3: A fast, flexible and open software framework for medical image processing and visualisation
Tournier, J.-D., Smith, R., Raffelt, D., Tabbara, R., Dhollander, T., Pietsch, M., Christiaens, D., Jeurissen, B., Yeh, C.-H., & Connelly, A. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116137 · Cited by 2,974 · see citing works
Self-citationZhang, F., Daducci, A., He, Y., Schiavi, S., Seguin, C., Smith, R. E., Yeh, C.-H., Zhao, T., & O’Donnell, L. J. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2021.118870 · Cited by 302 · see citing works
“studies on various brain disorders including, but not limited to, multiple sclerosis (MS) [167, 407], amnestic mild cognitive impairment (aMCI) [22, 597], Alzheimer’s disease [236, 298, 322, 491], stroke [329], schizophrenia [109, 188, 533], depression [128, 265], obsessive-compulsive disorder (OCD) [75, 96, 177, 198,…”
BackgroundThe human connectome in Alzheimer disease — relationship to biomarkers and genetics
Yu, M., Sporns, O., & Saykin, A. J. (2021) · Nature Reviews Neurology · doi:10.1038/s41582-021-00529-1 · Cited by 265 · see citing works
Mapping Structural Connectivity Using Diffusion <scp>MRI</scp> : Challenges and Opportunities
Yeh, C., Jones, D. K., Liang, X., Descoteaux, M., & Connelly, A. (2021) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.27188 · Cited by 187 · see citing works
Self-citationWhite matter diffusion alterations precede symptom onset in autosomal dominant Alzheimer’s disease
Araque Caballero, M. Á., Suárez-Calvet, M., Duering, M., Franzmeier, N., Benzinger, T., Fagan, A. M., Bateman, R. J., Jack, C. R., Levin, J., Dichgans, M., et al. (2018) · Brain · doi:10.1093/brain/awy229 · Cited by 179 · see citing works
“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).”
BackgroundMethodFowler, C., Rainey-Smith, S. R., Bird, S., Bomke, J., Bourgeat, P., Brown, B. M., Burnham, S. C., Bush, A. I., Chadunow, C., Collins, S., et al. (2021) · Journal of Alzheimer's Disease Reports · doi:10.3233/adr-210005 · Cited by 164 · see citing works
Self-citationThe BIN1 rs744373 SNP is associated with increased tau-PET levels and impaired memory
Franzmeier, N., Rubinski, A., Neitzel, J., Ewers, M., (ADNI), T. A. D. N. I., Weiner, M. W., Aisen, P., Petersen, R., Jack, C. R., Jagust, W., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-09564-5 · Cited by 109 · see citing works
Dong, J. W., Jelescu, I. O., Ades-Aron, B., Novikov, D. S., Friedman, K., Babb, J. S., Osorio, R. S., Galvin, J. E., Shepherd, T. M., & Fieremans, E. (2020) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2020.01.009 · Cited by 70 · see citing works
Zarkali, A., McColgan, P., Leyland, L. A., Lees, A. J., & Weil, R. S. (2022) · Journal of Neurology, Neurosurgery & Psychiatry · doi:10.1136/jnnp-2021-326630 · Cited by 32 · see citing works
Disrupted structural connectivity in ArcAβ mouse model of Aβ amyloidosis
Al-Amin, M. M., Grandjean, J., Klohs, J., & Kim, J. (2020) · doi:10.1101/2020.04.27.064634 · Cited by 2 · see citing works
“Nevertheless, reduction in FD, FC and FDC are seen in patients with AD and mild cognitive impairment (Mito et al., 2018).”
Background
- Authors
- Mito, R., Raffelt, D., Dhollander, T., Vaughan, D. N., Tournier, J.-D., Salvado, O., Brodtmann, A., Rowe, C. C., Villemagne, V. L., & Connelly, A.
- Affiliations
- The University of Melbourne (AU)
- Florey Institute of Neuroscience and Mental Health (AU)
- King's College London (GB)
- Australian e-Health Research Centre (AU)
- Box Hill Hospital (AU)
- Corresponding author
- Mito, Remika
- ORCID
- Venue
- Brain
- Publisher
- Oxford University Press (OUP)
- Published
- 2018-01-04
- Volume
- 141
- Issue
- 3
- Pages
- 888-902
- ISSN
- 0006-8950 (ISSN-L)
- 1460-2156
- OpenAlex
- W2781581970
- Cited by
- 309
- References
- 106
- Citations by year
- 2026: 34 · 2025: 37 · 2024: 33 · 2023: 41 · 2022: 46 · 2021: 53 · 2020: 36 · 2019: 18 · 2018: 10
- FWCI
- 13.42
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Brain (publishedVersion)
- PubMed (publishedVersion)
- Research Portal (King's College London) (submittedVersion, other-oa)
- Funders
- National Health and Medical Research Council
- NHMRC Research Fellowship (1046571)
- University of Melbourne
- Yulgibar Alzheimer’s Research Program Award
- 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 › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Keywords
- Alzheimer's disease, mild cognitive impairment, white matter degeneration, fixel-based analysis, default mode network, posterior cingulum, amyloid PET, fiber density, fiber cross-section, white matter microstructure, network disconnection, axonal loss, diffusion MRI, brain aging, amyloid
- MeSH terms
- Aged, Aged, 80 and over, Alzheimer Disease, Aniline Compounds, Brain, Cross-Sectional Studies, Female, Humans, Male, Mental Status Schedule, Nerve Fibers, Thiazoles, Imaging, Three-Dimensional, Positron-Emission Tomography, Cognitive Dysfunction, White Matter
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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.
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