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White Matter Damage in Alzheimer Disease and Its Relationship to Gray Matter Atrophy
Abstract
PURPOSE: To explore the regional patterns of white matter (WM) tract damage in (a) patients with probable Alzheimer disease (AD) and (b) patients with amnestic mild cognitive impairment (aMCI) and at least one abnormal biomarker and to investigate whether WM damage is related to gray matter (GM) atrophy. MATERIALS AND METHODS: This study was approved by the institutional review board, and written informed consent was obtained from each participant. Twenty-three patients with AD, 15 patients with aMCI, and 15 healthy control subjects underwent diffusion tensor magnetic resonance imaging. WM tract damage was investigated by using tract-based spatial statistics, and GM atrophy was measured by using voxel-based morphometry. RESULTS: Compared with control subjects, patients with AD had an increase in mean diffusivity in all major WM tracts studied, including the limbic, cortico-cortical, interhemispheric, and corticospinal tracts. Conversely, fractional anisotropy decreased only in the parahippocampal tract, fornix, and small, inferior parietal regions. In addition, patients with AD showed a widespread increase in axial and radial diffusivity compared with control subjects. Patients with aMCI showed an increase in axial diffusivity only in tracts projecting to the frontal cortex and splenium of the corpus callosum. Significant and anatomically congruent correlations between WM changes and regional GM atrophy were found in patients with AD. Conversely, damage to most WM tracts in patients with aMCI did not correlate with GM atrophy. CONCLUSION: In AD, the observed patterns of WM abnormalities may reflect the advanced phase of a secondary degenerative process and an association, especially in the early phases of the disease, with primary WM tract damage over and above GM abnormalities.
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“Such white matter alterations cannot be fully accounted for as degenerative processes secondary to grey matter damage (Brun and Englund, 1986; Englund, 1998; Agosta et al., 2011), but may stem from vascular amyloid deposition and microvascular damage (Weller et al., 2009).”
From White matter diffusion alterations precede symptom onset in autosomal dominant Alzheimer’s disease (2018) · cites this paper as Agosta et al., 2011
Citations
Cites
Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975) · Journal of Psychiatric Research · doi:10.1016/0022-3956(75)90026-6 · Cited by 88,282
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
Neuropathological stageing of Alzheimer-related changes.
Braak, H., & Braak, E. (1991) · Acta Neuropathologica · doi:10.1007/bf00308809 · Cited by 16,123
VALIDITY OF THE TRAIL MAKING TEST AS AN INDICATOR OF ORGANIC BRAIN DAMAGE
Reitan, R. M. (1958) · Perceptual and Motor Skills · doi:10.2466/pms.1958.8.3.271 · Cited by 8,167
A fast diffeomorphic image registration algorithm
Ashburner, J. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.07.007 · Cited by 8,122
Ashburner, J., & Friston, K. J. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.02.018 · Cited by 7,507
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
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
SMITH, S., & NICHOLS, T. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2008.03.061 · Cited by 5,250
Maldjian, J. A., Laurienti, P. J., Kraft, R., & Burdette, J. H. (2003) · NeuroImage · doi:10.1016/s1053-8119(03)00169-1 · Cited by 5,066
Flagged first, then by citations
Research works printed but not linked: 7
- Salat DH, Neurobiol Aging
- Stenset V, Neurobiol Aging
- Barigazzi R, 1987, Ric Psicol, 1, 50
- Novelli G, 1986, Arch Psicol Neurol Psichiatr, 47, 477
- Spinnler H, 1987, Ital J Neurol Sci, 6, 1
- Ferreira LK, Neurobiol Aging
- Pievani M, Hum Brain Mapp
Cited by
Sorted by citations
Items 101–200 of 287
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Chao, L. L., Zhang, Y., & Buckley, S. T. (2015) · NeuroToxicology · doi:10.1016/j.neuro.2015.04.005 · Cited by 40
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Veale, T. D., Malone, I. B., Poole, T., Parker, T. D., Slattery, C. F., Paterson, R. W., Foulkes, A., Thomas, D. L., Schott, J. M., Zhang, H. G., et al. (2021) · Brain Communications · doi:10.1093/braincomms/fcab272 · Cited by 39
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Mascalchi, M., Toschi, N., Giannelli, M., Ginestroni, A., Nave, R. D., Nicolai, E., Bianchi, A., Tessa, C., Salvatore, E., Aiello, M., et al. (2015) · American Journal of Neuroradiology · doi:10.3174/ajnr.a4343 · Cited by 40
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Filippi, M., & Agosta, F. (2016) · Handbook of clinical neurology · doi:10.1016/b978-0-444-53486-6.00056-9 · Cited by 41
Self-citationNishioka, C., Initiative, A. D. N., Poh, C., & Sun, S. (2015) · Journal of Alzheimer s Disease · doi:10.3233/jad-141239 · Cited by 40
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Manuello, J., Nani, A., Premi, E., Borroni, B., Costa, T., Tatu, K., Liloia, D., Duca, S., & Cauda, F. (2018) · Frontiers in Neurology · doi:10.3389/fneur.2017.00739 · Cited by 38
Knight, M. J., Wearn, A. R., Coulthard, E. J., & Kauppinen, R. A. (2018) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.26195 · Cited by 38
Chen, S., Xu, W., Xue, C., Hu, G., Ma, W., Qi, W., Lin, D., Lin, X., & Chen, J. (2020) · Journal of Alzheimer s Disease · doi:10.3233/jad-200659 · Cited by 38
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Masdeu, J. C., Kreisl, W. C., & Berman, K. F. (2012) · Current Opinion in Neurology · doi:10.1097/wco.0b013e3283557b36 · Cited by 39
Li, H., for the BGBH Study Group, Liang, Y., Chen, K., Li, X., Shu, N., Zhang, Z., & Wang, Y. (2013) · Journal of Alzheimer s Disease · doi:10.3233/jad-122023 · Cited by 35
Gonzales, M. M., Insel, P. S., Nelson, C. J., Tosun, D., Mattsson, N., Mueller, S. G., Sacuiu, S. F., Bickford, D. D., Weiner, M. W., & Mackin, R. S. (2017) · American Journal of Geriatric Psychiatry · doi:10.1016/j.jagp.2017.04.011 · Cited by 34
Rahmati, M., Joneydi, M. S., Koyanagi, A., Yang, G., Ji, B., Lee, S. W., Yon, D. K., Smith, L., Shin, J. I., & Li, Y. (2023) · Scientific Reports · doi:10.1038/s41598-023-29406-1 · Cited by 34
Palesi, F., Vitali, P., Chiarati, P., Castellazzi, G., Caverzasi, E., Pichiecchio, A., Tibaldi, E. C., D’Amore, F., D'Errico, I., Sinforiani, E., et al. (2011) · Neurology Research International · doi:10.1155/2012/517876 · Cited by 34
Carmeli, C., Fornari, E., Jalili, M., Meuli, R. A., & Knyazeva, M. G. (2014) · Brain and Behavior · doi:10.1002/brb3.252 · Cited by 32
Wen, J., Samper‐Gonzàlez, J., Bottani, S., Routier, A., Burgos, N., Jacquemont, T., Fontanella, S., Durrleman, S., Epelbaum, S., Bertrand, A., et al. (2020) · Neuroinformatics · doi:10.1007/s12021-020-09469-5 · Cited by 38
Hurley, M. J., Deacon, R. M. J., Beyer, K., Ioannou, E., Ibáñez, A. M., Teeling, J. L., & Cogram, P. (2018) · Pharmacology & Therapeutics · doi:10.1016/j.pharmthera.2018.03.001 · Cited by 32
Wegrzyn, M., Teipel, S. J., Oltmann, I., Bauer, A. J., Thome, J., Großmann, A., Hauenstein, K., & Höppner, J. (2012) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2012.04.008 · Cited by 31
Sexual Dimorphism in Healthy Aging and Mild Cognitive Impairment: A DTI Study
O’Dwyer, L., Lamberton, F., Bokde, A. L. W., Ewers, M., Faluyi, Y. O., Tanner, C. J., Mazoyer, B. M., O’Neill, D. J., Bartley, M. M., Collins, R., et al. (2012) · PLoS ONE · doi:10.1371/journal.pone.0037021 · Cited by 30
Hattori, T., Sato, R., Aoki, S., Yuasa, T., & Mizusawa, H. (2011) · American Journal of Neuroradiology · doi:10.3174/ajnr.a2780 · Cited by 30
Guo, H., Song, X., Vandorpe, R. A., Zhang, Y., Chen, W., Zhang, N., Schmidt, M. H., & Rockwood, K. J. (2013) · American Journal of Neuroradiology · doi:10.3174/ajnr.a3709 · Cited by 29
Павлов, А. Н., Николаевна, П. Е., Frolov, N. S., Badarin, A., Pavlova, O. N., & Hramov, A. E. (2020) · Sensors · doi:10.3390/s20205843 · Cited by 29
Xie, Y., Cui, Z., Zhang, Z., Sun, Y., Sheng, C., Li, K., Gong, G., Han, Y., & Jia, J. (2015) · Journal of Alzheimer s Disease · doi:10.3233/jad-150184 · Cited by 30
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
Kim, E., Figueiredo, I., Simmons, C., Randall, K., Gonzalez, L. R., Wood, T., Ranieri, B., Sureda-Gibert, P., Howes, O. D., Pariante, C. M., et al. (2023) · Brain Behavior and Immunity · doi:10.1016/j.bbi.2023.07.010 · Cited by 28
Xekardaki, A., Giannakopoulos, P., & Haller, S. (2011) · Journal of Aging Research · doi:10.4061/2011/286564 · Cited by 28
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Silvestrini, M., Viticchi, G., Altamura, C., Luzzi, S., Balucani, C., & Vernieri, F. (2012) · Journal of Alzheimer s Disease · doi:10.3233/jad-2012-121240 · Cited by 29
Ribeiro, L. G., & Busatto, G. F. (2016) · Dementia & Neuropsychologia · doi:10.1590/s1980-5764-2016dn1002006 · Cited by 28
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Zhu, Q., Bi, S., Yao, X.-T., Ni, Z., Li, Y., Chen, B., Fan, G., & Shang, X. (2015) · Metabolic Brain Disease · doi:10.1007/s11011-015-9708-7 · Cited by 30
Rowley, J., Fonov, V., Wu, O., Eskildsen, S. F., Schoemaker, D., Wu, L., Mohades, S., Shin, M., Sziklas, V., Cheewakriengkrai, L., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0074776 · Cited by 27
Lancaster, M. A., Seidenberg, M., Smith, J. C., Nielson, K. A., Woodard, J. L., Durgerian, S., & Rao, S. M. (2016) · Journal of the International Neuropsychological Society · doi:10.1017/s1355617716000904 · Cited by 26
Lei, M., Teo, J. D., Song, H., McEwen, H. P., Yup Lee, J., Couttas, T. A., Duncan, T., Chesworth, R., Bertz, J., Przybyla, M., et al. (2019) · The Journal of Neuroscience · doi:10.1523/jneurosci.0524-19.2019 · Cited by 27
Wang, Z., Dai, Z., Shu, H., Liu, D., Guo, Q., He, Y., & Zhang, Z. (2017) · Journal of Alzheimer’s Disease · doi:10.3233/jad-160724 · Cited by 26
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Yu, Z., Si, X., Chen, Y., Chao, Y., Lin, C., Li, S., Zhang, X., Ming, D., & Li, Q. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab407 · Cited by 26
Moody, J. F., Dean, D., Kecskemeti, S. R., Blennow, K., Zetterberg, H., Kollmorgen, G., Suridjan, I., Wild, N., Carlsson, C. M., Johnson, S. C., et al. (2022) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1002/dad2.12381 · Cited by 24
Wang, D., Li, Y., Luo, J., & Li, Y. (2014) · Archives of Gerontology and Geriatrics · doi:10.1016/j.archger.2014.04.002 · Cited by 26
Initiative, A. D. N., Schilling, L. P., Pascoal, T. A., Zimmer, E. R., Mathotaarachchi, S. S., Shin, M., Rieder, C. R. D. M., Gauthier, S. G., Palmini, A., & Rosa‐Neto, P. (2018) · Molecular Neurobiology · doi:10.1007/s12035-018-1405-1 · Cited by 25
Sun, X., Salat, D. H., Upchurch, K., Deason, R. G., Kowall, N. W., & Budson, A. E. (2014) · Journal of Investigative Medicine · doi:10.1097/jim.0000000000000102 · Cited by 25
Bejanin, A., Desgranges, B., Joie, R. L., Landeau, B., Perrotin, A., Mézenge, F., Belliard, S., Sayette, V. D. L., Eustache, F., & Chételat, G. (2016) · Human Brain Mapping · doi:10.1002/hbm.23482 · Cited by 27
Ramanan, S., Marstaller, L., Hodges, J. R., Piguet, O., & Irish, M. (2020) · Cortex · doi:10.1016/j.cortex.2019.12.026 · Cited by 24
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Roy, M., Rheault, F., Croteau, É., Castellano, C., Fortier, M., St‐Pierre, V., Houde, J., Turcotte, É. E., Bocti, C., Fülöp, T., et al. (2020) · Journal of Alzheimer s Disease · doi:10.3233/jad-200213 · Cited by 23
Nonparenchymal fluid is the source of increased mean diffusivity in preclinical Alzheimer's disease
Sepehrband, F., Cabeen, R. P., Barisano, G., Sheikh‐Bahaei, N., Choupan, J., Law, M., Toga, A. W., & Initiative, A. D. N. (2019) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1016/j.dadm.2019.03.002 · Cited by 24
Ito, K., Sasaki, M., Takahashi, J., Uwano, I., Yamashita, F., Higuchi, S., Goodwin, J., Harada, T., Kudo, K., & Terayama, Y. (2015) · Psychiatry Research: Neuroimaging · doi:10.1016/j.pscychresns.2015.01.020 · Cited by 26
Maiella, M., Mencarelli, L., Casula, E. P., Borghi, I., Assogna, M., Lorenzo, F. D., Bonnı̀, S., Pezzopane, V., Martorana, A., & Koch, G. (2024) · Clinical Neurophysiology · doi:10.1016/j.clinph.2024.09.007 · Cited by 26
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Saini, F., Dell’Acqua, F., & Strydom, A. (2022) · Frontiers in Neuroscience · doi:10.3389/fnins.2022.908413 · Cited by 22
Meyer, P., Feldkamp, H., Hoppstädter, M., King, A. V., Frölich, L., Wessa, M., & Flor, H. (2013) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2013.00089 · Cited by 23
Scrascia, F., Curcio, G., Ursini, F., Trotta, L., Quintiliani, L., Migliore, S., Altamura, C., Pitocco, F., Altavilla, R., Melgari, J.-M., et al. (2013) · Journal of Alzheimer s Disease · doi:10.3233/jad-130788 · Cited by 22
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Xu, Z., He, S., Begum, M. M., & Han, X. (2024) · Antioxidants and Redox Signaling · doi:10.1089/ars.2024.0676 · Cited by 24
Steketee, R. M. E., Meijboom, R., de Groot, M., Bron, E. E., Niessen, W. J., van der Lugt, A., Swieten, J. C. V., & Smits, M. (2016) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2016.03.031 · Cited by 22
Zarini-Gakiye, E., Amini, J., Sanadgol, N., Vaezi, G., & Kazem, P. (2020) · Current Molecular Pharmacology · doi:10.2174/1874467213666200422090135 · Cited by 22
Hsu, Y., Huang, C.-F., Tu, M.-C., & Hua, M. (2014) · PLoS ONE · doi:10.1371/journal.pone.0112210 · Cited by 24
Rosas, H. D., Hsu, E., Mercaldo, N. D., Lai, F., Pulsifer, M. B., Keator, D. B., Brickman, A. M., Price, J. C., Yassa, M. A., Hom, C. L., et al. (2020) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1002/dad2.12040 · Cited by 17
Sun, X., Liang, Y., Wang, J., Chen, K., Chen, Y., Zhou, X., Jia, J., & Zhang, Z. (2014) · Journal of Alzheimer s Disease · doi:10.3233/jad-131709 · Cited by 21
Profiling heterogeneity of Alzheimer's disease using white-matter impairment factors
Sui, X., & Rajapakse, J. C. (2018) · NeuroImage Clinical · doi:10.1016/j.nicl.2018.10.026 · Cited by 21
Grazzini, I., Venezia, D., & Cuneo, G. L. (2020) · The Neuroradiology Journal · doi:10.1177/1971400920975153 · Cited by 21
Imaging multiple sclerosis and other neurodegenerative diseases
Inglese, M., & Petracca, M. (2013) · Prion · doi:10.4161/pri.22650 · Cited by 22
Emotion recognition deficits exist in mild cognitive impairment, but only in the amnestic subtype.
McCade, D., Savage, G. R., Guastella, A. J., Lewis, S. J. G., & Naismith, S. L. (2013) · Psychology and Aging · doi:10.1037/a0033077 · Cited by 21
Pansieri, J., Hadley, G., Lockhart, A., Pisa, M., & DeLuca, G. C. (2023) · Frontiers in Neurology · doi:10.3389/fneur.2023.1199491 · Cited by 21
Yang, C., Gao, X., Liu, N., Sun, H., Gong, Q., Li, Y., & Lui, S. (2023) · Cerebral Cortex · doi:10.1093/cercor/bhad167 · Cited by 20
Casamitjana, A., Mancini, M., Robinson, E., Peter, L., Annunziata, R., Althonayan, J. I. M., Crampsie, S., Blackburn, E., Billot, B., Atzeni, A., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.02.05.579016 · Cited by 20
Coluzzi, D., Bordin, V., Rivolta, M. W., Fortel, I., Zhan, L., Leow, A., & Baselli, G. (2025) · Bioengineering · doi:10.3390/bioengineering12010082 · Cited by 23
Zhang, N., Song, X., & Zhang, Y. (2012) · Dementia and Geriatric Cognitive Disorders · doi:10.1159/000339364 · Cited by 19
Min, J., Xu-xin, Z., Zhou, F., Tan, Y., & Wang, W. (2019) · Brazilian Journal of Medical and Biological Research · doi:10.1590/1414-431x20198244 · Cited by 19
Distinct fiber-specific white matter reductions pattern in early- and late-onset Alzheimer’s disease
Luo, X., Wang, S., Jiaerken, Y., Li, K., Zeng, Q., Hong, H., Guan⁴, X., Guo, T., Wang, C., Zhang, R., et al. (2021) · Aging · doi:10.18632/aging.202702 · Cited by 19
Fornix degeneration in risk factors of Alzheimer's disease, possible trigger of cognitive decline
Lacalle‐Aurioles, M., & Iturria‐Medina, Y. (2023) · Cerebral Circulation - Cognition and Behavior · doi:10.1016/j.cccb.2023.100158 · Cited by 20
Amato, L. G., Vergani, A. A., Lassi, M., Fabbiani, C., Mazzeo, S., Burali, R., Nacmias, B., Sorbi, S., Mannella, R., Grippo, A., et al. (2024) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1002/dad2.12526 · Cited by 17
Gold, B. T., Jiang, Y., Powell, D. K., & Smith, C. D. (2012) · Journal of Alzheimer s Disease · doi:10.3233/jad-2012-112165 · Cited by 17
Roldán-Valadéz, E., Becerra‐Laparra, I. K., Cortez-Conradis, D., García-Lázaro, H. G., & Martı́nez-López, M. (2020) · Neurology India · doi:10.4103/0028-3886.284376 · Cited by 16
A review of neuroimaging-based data-driven approach for Alzheimer’s disease heterogeneity analysis
Liu, L., Sun, S., Kang, W., Wu, S., & Lin, L. (2024) · Reviews in the Neurosciences · doi:10.1515/revneuro-2023-0033 · Cited by 16
Diverging Progression of Network Disruption and Atrophy in Alzheimer’s Disease and Semantic Dementia
Andreotti, J., Dierks, T., Wahlund, L., & Grieder, M. (2016) · Journal of Alzheimer s Disease · doi:10.3233/jad-160571 · Cited by 17
Sharma, R., Goel, T., Tanveer, M., & Al‐Dhaifallah, M. (2025) · IEEE Transactions on Emerging Topics in Computational Intelligence · doi:10.1109/tetci.2024.3523714 · Cited by 16
Transfer learning on T1-weighted images for brain age estimation
Jiang, H., Guo, J., Du, H., Xu, J., & Qiu, B. (2019) · Mathematical Biosciences & Engineering · doi:10.3934/mbe.2019218 · Cited by 16
Chia, S.-Y., Li, M., Li, Z., Tu, H., Lee, J. W. L., Qiu, L., Ling, J., Reynolds, R., Albani, S., Tan, E.-K., et al. (2025) · Genome Medicine · doi:10.1186/s13073-025-01519-4 · Cited by 15
The use of positron emission tomography/magnetic resonance imaging in dementia: A literature review
Lorking, N., Murray, A. D., & O'Brien, J. T. (2021) · International Journal of Geriatric Psychiatry · doi:10.1002/gps.5586 · Cited by 15
Gaonkar, B., Pohl, K. M., & Davatzikos, C. A. (2011) · Lecture notes in computer science · doi:10.1007/978-3-642-23629-7_56 · Cited by 15
Fjell, A. M., Westlye, L. T., Amlien, I. K., & Walhovd, K. B. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.03.007 · Cited by 15
Corrêa, D. G., Zimmermann, N., Pereira, D. B., Doring, T. M., Netto, T. M., Ventura, N., Fonseca, R. P., & Gasparetto, E. L. (2016) · Neuroradiology · doi:10.1007/s00234-016-1688-8 · Cited by 15
Sivera, R., Capet, N., Manera, V., Fabre, R., Lorenzi, M., Delingette, H., Xavier Pennec, B., Ayache, N., & Robert, P. H. (2020) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2019.11.020 · Cited by 19
Gilligan, T. M., Sibilia, F., Farrell, D., Lyons, D., Kennelly, S., & Bokde, A. L. W. (2019) · PLoS ONE · doi:10.1371/journal.pone.0222977 · Cited by 13
The role of multimodal MRI in mild cognitive impairment and Alzheimer's disease
Knudsen, L. V., Gazerani, P., Duan, Y., Michel, T. M., & Vafaee, M. S. (2021) · Journal of Neuroimaging · doi:10.1111/jon.12940 · Cited by 16
The missing role of gray matter in studying brain controllability
Jamalabadi, H., Zuberer, A., Kumar, V., Li, M., Alizadeh, S., Amani, A. M., Christian Gaser, B., Esterman, M. S., & Walter, M. (2020) · Network Neuroscience · doi:10.1162/netn_a_00174 · Cited by 14
Boespflug, E. L., Storrs, J. M., Sadat-Hossieny, S., Eliassen, J. C., Shidler, M. D., Norris, M. M., & Krikorian, R. (2013) · Brain Structure and Function · doi:10.1007/s00429-013-0506-x · Cited by 14
The Estimation of Free-Water Corrected Diffusion Tensors
Pasternak, O., Maier-Hein, K. H., Baumgartner, C. F., Shenton, M. E., Yogesh Rathi, A., & Westin, C. (2014) · Mathematics and visualization · doi:10.1007/978-3-642-54301-2_11 · Cited by 13
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Gullett, J. M., Lamb, D. G., Porges, E. C., Woods, A. J., Rieke, J. D., Thompson, P. M., Jahanshad, N., Nir, T. M., Tashima, K. T., & Cohen, R. A. (2018) · Alcoholism Clinical and Experimental Research · doi:10.1111/acer.13823 · Cited by 14
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Metadata
- Authors
- Agosta, F., Pievani, M., Sala, S., Geroldi, C., Galluzzi, S., Frisoni, G. B., & Filippi, M.
- Affiliations
- IRCCS Ospedale San Raffaele (IT)
- Centro San Giovanni di Dio Fatebenefratelli (IT)
- Vita-Salute San Raffaele University (IT)
- ORCID
- Venue
- Radiology
- Published
- 2011-03
- Volume
- 258
- Issue
- 3
- Pages
- 853-863
- ISSN
- 0033-8419 (ISSN-L)
- 1527-1315
- OpenAlex
- W2168463796
- Cited by
- 288
- References
- 53
- Citations by year
- 2026: 8 · 2025: 13 · 2024: 12 · 2023: 21 · 2022: 11 · 2021: 17 · 2020: 24 · 2019: 14 · 2018: 17 · 2017: 11 · 2016: 27 · 2015: 25 · 2014: 19 · 2013: 26 · 2012: 26
- FWCI
- 14.96
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Radiology (publishedVersion)
- PubMed (publishedVersion)
- Archivio Istituzionale della Ricerca - Università Vita-Salute San Raffaele (submittedVersion)
- 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
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Keywords
- Alzheimer's disease, white matter injury, gray matter atrophy, amnestic mild cognitive impairment, diffusion tensor imaging, mean diffusivity, fractional anisotropy, axial and radial diffusivity, white matter tracts, corticospinal tract, fornix, corpus callosum, tract-based spatial statistics, voxel-based morphometry
- MeSH terms
- Aged, Alzheimer Disease, Atrophy, Cognition Disorders, Female, Humans, Male, Nerve Fibers, Myelinated, Neuropsychological Tests, Prospective Studies, Biomarkers, Case-Control Studies, Statistics, Nonparametric, Diffusion Magnetic Resonance Imaging
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