[en] Previous studies have shown that the cholinergic nucleus basalis of Meynert and its white matter projections are affected in Alzheimer's disease dementia and mild cognitive impairment. However, it is still unknown whether these alterations can be found in individuals with subjective cognitive decline, and whether they are more pronounced than changes found in conventional brain volumetric measurements. To address these questions, we investigated microstructural alterations of two major cholinergic pathways in individuals along the Alzheimer's disease continuum using an in vivo model of the human cholinergic system based on neuroimaging. We included 402 participants (52 Alzheimer's disease, 66 mild cognitive impairment, 172 subjective cognitive decline and 112 healthy controls) from the Deutsches Zentrum für Neurodegenerative Erkrankungen Longitudinal Cognitive Impairment and Dementia Study. We modelled the cholinergic white matter pathways with an enhanced diffusion neuroimaging pipeline that included probabilistic fibre-tracking methods and prior anatomical knowledge. The integrity of the cholinergic white matter pathways was compared between stages of the Alzheimer's disease continuum, in the whole cohort and in a CSF amyloid-beta stratified subsample. The discriminative power of the integrity of the pathways was compared to the conventional volumetric measures of hippocampus and nucleus basalis of Meynert, using a receiver operating characteristics analysis. A multivariate model was used to investigate the role of these pathways in relation to cognitive performance. We found that the integrity of the cholinergic white matter pathways was significantly reduced in all stages of the Alzheimer's disease continuum, including individuals with subjective cognitive decline. The differences involved posterior cholinergic white matter in the subjective cognitive decline stage and extended to anterior frontal white matter in mild cognitive impairment and Alzheimer's disease dementia stages. Both cholinergic pathways and conventional volumetric measures showed higher predictive power in the more advanced stages of the disease, i.e. mild cognitive impairment and Alzheimer's disease dementia. In contrast, the integrity of cholinergic pathways was more informative in distinguishing subjective cognitive decline from healthy controls, as compared with the volumetric measures. The multivariate model revealed a moderate contribution of the cholinergic white matter pathways but not of volumetric measures towards memory tests in the subjective cognitive decline and mild cognitive impairment stages. In conclusion, we demonstrated that cholinergic white matter pathways are altered already in subjective cognitive decline individuals, preceding the more widespread alterations found in mild cognitive impairment and Alzheimer's disease. The integrity of the cholinergic pathways identified the early stages of Alzheimer's disease better than conventional volumetric measures such as hippocampal volume or volume of cholinergic nucleus basalis of Meynert.
Disciplines :
Neurologie
Auteur, co-auteur :
Nemy, Milan ; Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic ; Department of Biomedical Engineering and Assistive Technology, Czech Institute of Informatics, Robotics and Cybernetics, Czech Technical University in Prague, Prague, Czech Republic ; Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Stockholm, Sweden
Dyrba, Martin ; German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany
Brosseron, Frederic; German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
Buerger, Katharina; German Center for Neurodegenerative Diseases (DZNE), Munich, Germany ; Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
Dechent, Peter; MR-Research in Neurosciences, Department of Cognitive Neurology, Georg-August-University Goettingen, Goettingen, Germany
Dobisch, Laura; German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
Ewers, Michael ; German Center for Neurodegenerative Diseases (DZNE), Munich, Germany ; Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
Fliessbach, Klaus; German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany ; Department for Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Bonn, Germany
Glanz, Wenzel; German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
Goerss, Doreen ; German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany ; Department of Psychosomatic Medicine, Rostock University Medical Center, Rostock, Germany
HENEKA, Michael ; German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany ; Department for Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Bonn, Germany
Hetzer, Stefan; Berlin Center for Advanced Neuroimaging, Charité-Universitätsmedizin Berlin, Berlin, Germany
Incesoy, Enise I; German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany ; Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University, Magdeburg, Germany
Janowitz, Daniel; Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
Kilimann, Ingo ; German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany ; Department of Psychosomatic Medicine, Rostock University Medical Center, Rostock, Germany
Laske, Christoph; German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany ; Section for Dementia Research, Hertie Institute for Clinical Brain Research and Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
Maier, Franziska; Department of Psychiatry, Medical Faculty, University of Cologne, Cologne, Germany
Munk, Matthias H; German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany ; Section for Dementia Research, Hertie Institute for Clinical Brain Research and Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
Perneczky, Robert; German Center for Neurodegenerative Diseases (DZNE), Munich, Germany ; Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany ; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany ; Ageing Epidemiology Research Unit (AGE), School of Public Health, Imperial College London, London, UK ; Sheffield Institute for Translational Neurosciences (SITraN), University of Sheffield, Sheffield, UK
Peters, Oliver; German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany ; Department of Psychiatry, Charité-Universitätsmedizin Berlin, Campus Benjamin Franklin, Berlin, Germany
Preis, Lukas; Department of Psychiatry, Charité-Universitätsmedizin Berlin, Campus Benjamin Franklin, Berlin, Germany
Priller, Josef; German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany ; Department of Psychiatry and Psychotherapy, Charité, Berlin, Germany ; Department of Psychiatry and Psychotherapy, School of Medicine, Technical University of Munich, Munich, Germany ; Centre for Clinical Brain Sciences, University of Edinburgh and UK DRI, Edinburgh, UK
Rauchmann, Boris-Stephan; Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
Röske, Sandra; German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
Roy, Nina; German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
Scheffler, Klaus; Department for Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany
Schneider, Anja; German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany ; Department for Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Bonn, Germany
Schott, Björn H ; German Center for Neurodegenerative Diseases (DZNE), Goettingen, Germany ; Department of Psychiatry and Psychotherapy, University Medical Center Goettingen, University of Goettingen, Goettingen, Germany ; Leibniz Institute for Neurobiology, Magdeburg, Germany
Spottke, Annika; German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany ; Department of Neurology, University of Bonn, Bonn, Germany
Spruth, Eike J; German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany ; Department of Psychiatry and Psychotherapy, Charité, Berlin, Germany
Wagner, Michael; German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany ; Department for Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Bonn, Germany
Wiltfang, Jens; German Center for Neurodegenerative Diseases (DZNE), Goettingen, Germany ; Department of Psychiatry and Psychotherapy, University Medical Center Goettingen, University of Goettingen, Goettingen, Germany ; Neurosciences and Signaling Group, Institute of Biomedicine (iBiMED), Department of Medical Sciences, University of Aveiro, Aveiro, Portugal
Yakupov, Renat ; German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
Eriksdotter, Maria ; Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Stockholm, Sweden ; Theme Inflammation and Aging, Karolinska University Hospital, Stockholm, Sweden
Westman, Eric ; Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Stockholm, Sweden ; Department of Neuroimaging, Centre for Neuroimaging Science, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
Stepankova, Olga ; Department of Biomedical Engineering and Assistive Technology, Czech Institute of Informatics, Robotics and Cybernetics, Czech Technical University in Prague, Prague, Czech Republic
Vyslouzilova, Lenka ; Department of Biomedical Engineering and Assistive Technology, Czech Institute of Informatics, Robotics and Cybernetics, Czech Technical University in Prague, Prague, Czech Republic
Düzel, Emrah ; German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany ; Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University, Magdeburg, Germany
Jessen, Frank ; German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany ; Department of Psychiatry, Medical Faculty, University of Cologne, Cologne, Germany ; Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, Cologne, Germany
Teipel, Stefan J ; German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany ; Department of Psychosomatic Medicine, Rostock University Medical Center, Rostock, Germany
Ferreira, Daniel ; Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Stockholm, Sweden
Swedish Research Council Stockholm County Council Karolinska Institutet Center for Innovative Medicine Swedish Alzheimer Foundation Swedish Brain Foundation Neuro Fonden Czech Alzheimer Foundation Demensfonden Czech Technical University in Prague Federal Ministry of Research
Subventionnement (détails) :
This study was supported by the Swedish Research Council (2020-02014); the regional agreement on medical training and clinical research (ALF) between Stockholm County Council and Karolinska Institutet; Center for Innovative Medicine (CIMED); the Swedish Alzheimer Foundation; the Swedish Brain Foundation; Neuro Fonden, the Czech Alzheimer Foundation; and Demensfonden. Research by M.N., O.S. and L.V. was partially supported by institutional resources of Czech Technical University in Prague. The work was further supported by a grant to S.J.T. within the CureDem funding of the Bundesministerium für Bildung und Forschung (BMBF), grant number 01KX2130. The funding sources did not have any involvement in the study design; collection, analysis and interpretation of data; writing of the report and the decision to submit the article for publication.
Buchhave P, Minthon L, Zetterberg H, Wallin ÅK, Blennow K, Hansson O. Cerebrospinal fluid levels of β-amyloid 1–42, but not of tau, are fully changed already 5 to 10 years before the onset of Alzheimer dementia. Arch Gen Psychiatry. 2012;69: 98-106.
Villemagne VL, Burnham S, Bourgeat P, et al. Amyloid β deposition, neurodegeneration, and cognitive decline in sporadic Alzheimer’s disease: A prospective cohort study. Lancet Neurol. 2013;12:357-367.
Albert M, Zhu Y, Moghekar A, et al. Predicting progression from normal cognition to mild cognitive impairment for individuals at 5 years. Brain. 2018;141:877-887.
Sperling RA, Aisen PS, Beckett LA, et al. Toward defining the preclinical stages of Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s Dement. 2011;7:280-292.
Dubois B, Hampel H, Feldman HH, et al. Preclinical Alzheimer’s disease: Definition, natural history, and diagnostic criteria. Alzheimer’s Dement. 2016;12:292-323.
Jack CR, Bennett DA, Blennow K, et al. NIA-AA research framework: Toward a biological definition of Alzheimer’s disease. Alzheimer’s Dement. 2018;14:535-562.
Fu H, Hardy J, Duff KE. Selective vulnerability in neurodegenerative diseases. Nat Neurosci. 2018;21:1350-1358.
Brueggen K, Dyrba M, Barkhof F, et al. Basal forebrain and hippocampus as predictors of conversion to Alzheimer’s disease in patients with mild cognitive impairment–A multicenter DTI and volumetry study. J Alzheimer’s Dis. 2015;48:197-204.
Schmitz TW, Nathan Spreng R, Alzheimer’s Disease Neuroimaging Initiative. Basal forebrain degeneration precedes and predicts the cortical spread of Alzheimer’s pathology. Nat Commun. 2016;7:13249.
Bartus RT, Dean RL, Beer B, Lippa AS. The cholinergic hypothesis of geriatric memory dysfunction. Science. 1982;217:408-414.
Kanaan NM, Pigino GF, Brady ST, Lazarov O, Binder LI, Morfini GA. Axonal degeneration in Alzheimer’s disease: When signaling abnormalities meet the axonal transport system. Exp Neurol. 2013;246:44-53.
Li X, Li TQ, Andreasen N, Wiberg MK, Westman E, Wahlund LO. The association between biomarkers in cerebrospinal fluid and structural changes in the brain in patients with Alzheimer’s disease. J Intern Med. 2014;275:418-427.
Li X, Westman E, Ståhlbom AK, et al. White matter changes in familial Alzheimer’s disease. J Intern Med. 2015;278:211-218.
Schumacher J, Ray NJ, Hamilton CA, et al. Cholinergic white matter pathways in dementia with Lewy bodies and Alzheimer’s disease. Brain. 2022;145(5):1773-1784.
Ballinger EC, Ananth M, Talmage DA, Role LW. Basal forebrain cholinergic circuits and signaling in cognition and cognitive decline. Neuron. 2016;91:1199-1218.
Jessen F, Spottke A, Boecker H, et al. Design and first baseline data of the DZNE multicenter observational study on predementia Alzheimer’s disease (DELCODE). Alzheimer’s Res Ther. 2018;10:21.
Folstein MF, Folstein SE, McHugh PR. Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12:189-198.
Jessen F, Amariglio RE, Van Boxtel M, et al. A conceptual framework for research on subjective cognitive decline in preclinical Alzheimer’s disease. Alzheimer’s Dement. 2014; 10:844-852.
Albert MS, DeKosky ST, Dickson D, et al. The diagnosis of mild cognitive impairment due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s Dement. 2011;7:270-279.
McKhann GM, Knopman DS, Chertkow H, et al. The diagnosis of dementia due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s Dement. 2011;7:263-269.
Mohs RC, Knopman D, Petersen RC, et al. Development of cognitive instruments for use in clinical trials of antidementia drugs: Additions to the Alzheimer’s disease assessment scale that broaden its scope. Alzheimer Dis Assoc Disord. 1997;11:13-21.
Smith A. Symbol digit modality test (SDMT): Manual (revised). Western Psychological Services; 1982.
Reitan RM. Validity of the trail making test as an indicator of organic brain damage. Percept Mot Skills. 1958;8:271-276.
Janelidze S, Zetterberg H, Mattsson N, et al. CSF Aβ42/Aβ40 and Aβ42/Aβ38 ratios: Better diagnostic markers of Alzheimer disease. Ann Clin Transl Neurol. 2016;3:154-165.
Jezzard P, Balaban RS. Correction for geometric distortion in echo planar images from B0 field variations. Magn Reson Med. 1995;34:65-73.
Nemy M, Cedres N, Grothe MJ, et al. Cholinergic white matter pathways make a stronger contribution to attention and memory in normal aging than cerebrovascular health and nucleus basalis of Meynert. Neuroimage. 2020;211:116607.
Jenkinson M, Beckmann CF, Behrens TEJ, Woolrich MW, Smith SM. FSL. Neuroimage. 2012;62:782-790.
Smith SM. Fast robust automated brain extraction. Hum Brain Mapp. 2002;17:143-155.
Reber PJ, Wong EC, Buxton RB, Frank LR. Correction of off resonance-related distortion in echo-planar imaging using EPI-based field maps. Magn Reson Med. 1998;39:328-330.
Andersson JLR, Sotiropoulos SN. An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging. Neuroimage. 2016;125:1063-1078.
Behrens TEJ, Berg HJ, Jbabdi S, Rushworth MFS, Woolrich MW. Probabilistic diffusion tractography with multiple fibre orientations: What can we gain? Neuroimage. 2007;34:144-155.
Hernández M, Guerrero GD, Cecilia JM, et al. Accelerating fibre orientation estimation from diffusion weighted magnetic resonance imaging using GPUs. PLoS ONE. 2013;8:e61892.
Selden NR, Gitelman DR, Salamon-Murayama N, Parrish TB, Mesulam MM. Trajectories of cholinergic pathways within the cerebral hemispheres of the human brain. Brain. 1998;121: 2249-2257.
Kilimann I, Grothe M, Heinsen H, et al. Subregional basal forebrain atrophy in Alzheimer’s disease: A multicenter study. J Alzheimer’s Dis. 2014;40:687-700.
Mori S, Wakana S, Van Zijl PC, Nagae-Poetscher L. MRI atlas of human white matter. Elsevier; 2005.
Behrens TEJ, Woolrich MW, Jenkinson M, et al. Characterization and propagation of uncertainty in diffusion-weighted MR imaging. Magn Reson Med. 2003;50:1077-1088.
Zhang Y, Brady M, Smith S. Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm. IEEE Trans Med Imaging. 2001;20:45-57.
Buckner RL, Head D, Parker J, et al. A unified approach for morphometric and functional data analysis in young, old, and demented adults using automated atlas-based head size normalization: Reliability and validation against manual measurement of total intracranial volume. Neuroimage. 2004;23:724-738.
Kim HJ, Moon WJ, Han SH. Differential cholinergic pathway involvement in Alzheimer’s disease and subcortical ischemic vascular dementia. J Alzheimer’s Dis. 2013;35:129-136.
Cedres N, Ferreira D, Machado A, et al. Predicting Fazekas scores from automatic segmentations of white matter signal abnormalities. Aging (Albany NY). 2020;12:894-901.
Leritz EC, Shepel J, Williams VJ, et al. Associations between T1 white matter lesion volume and regional white matter microstructure in aging. Hum Brain Mapp. 2014;35:1085-1100.
Fischl B, Salat DH, Busa E, et al. Whole brain segmentation: Automated labeling of neuroanatomical structures in the human brain. Neuron. 2002;33:341-355.
Winkler AM, Ridgway GR, Webster MA, Smith SM, Nichols TE. Permutation inference for the general linear model. Neuroimage. 2014;92:381-397.
Cedres N, Ferreira D, Nemy M, et al. Association of cerebrovascular and Alzheimer disease biomarkers with cholinergic white matter degeneration in cognitively unimpaired individuals. Neurology. 2022;99(15):e1619-e1629.
Breiman L. Random forests. Mach Learn. 2001;45:5-32.
Breiman L. Bagging predictions. Mach Learn. 1996;24: 123-140.
Lebedev AV, Westman E, Van Westen GJP, et al. Random forest ensembles for detection and prediction of Alzheimer’s disease with a good between-cohort robustness. Neuroimage Clin. 2014; 6:115-125.
Strobl C, Boulesteix AL, Zeileis A, Hothorn T. Bias in random forest variable importance measures: Illustrations, sources and a solution. BMC Bioinf. 2007;8:25.
Robin X, Turck N, Hainard A, et al. pROC: An open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinf. 2011;12:77.
Lin C-P, Frigerio I, Boon BDC, et al. Structural (dys)connectivity associates with cholinergic cell density in Alzheimer’s disease. Brain. 2022;145:2869-2881.
Wolfsgruber S, Kleineidam L, Guski J, et al. Minor neuropsychological deficits in patients with subjective cognitive decline. Neurology. 2020;95:e1134-e1143.
Rami L, Fortea J, Bosch B, et al. Cerebrospinal fluid biomarkers and memory present distinct associations along the continuum from healthy subjects to AD patients. J Alzheimer’s Dis. 2011;23: 319-326.
Visser PJ, Verhey F, Knol DL, et al. Prevalence and prognostic value of CSF markers of Alzheimer’s disease pathology in patients with subjective cognitive impairment or mild cognitive impairment in the DESCRIPA study: A prospective cohort study. Lancet Neurol. 2009;8:619-627.
Antonell A, Fortea J, Rami L, et al. Different profiles of Alzheimer’s disease cerebrospinal fluid biomarkers in controls and subjects with subjective memory complaints. J Neural Transm. 2011;118:259-262.
Sánchez-Benavides G, Suárez-Calvet M, Milà-Alomà M, et al. Amyloid-β positive individuals with subjective cognitive decline present increased CSF neurofilament light levels that relate to lower hippocampal volume. Neurobiol Aging. 2021;104: 24-31.
Ferreira D, Falahati F, Linden C, et al. A “disease severity index” to identify individuals with subjective memory decline who will progress to mild cognitive impairment or dementia. Sci Rep. 2017;7:44368.
Ebenau JL, Pelkmans W, Verberk IMW, et al. Association of CSF, plasma, and imaging markers of neurodegeneration with clinical progression in people with subjective cognitive decline. Neurology. 2022;98:E1315-E1326.
Cicognola C, Hansson O, Scheltens P, et al. Cerebrospinal fluid N-224 tau helps discriminate Alzheimer’s disease from subjective cognitive decline and other dementias. Alzheimer’s Res Ther. 2021;13:38.
Sun X, Salat D, Upchurch K, Deason R, Kowall N, Budson A. Destruction of white matter integrity in patients with mild cognitive impairment and Alzheimer disease. J Investig Med. 2014; 62:927-933.
Teipel S, Heinsen H, Amaro E, et al. Cholinergic basal forebrain atrophy predicts amyloid burden in Alzheimer’s disease. Neurobiol Aging. 2014;35:482-491.
Lee PL, Chou KH, Chung CP, et al. Posterior cingulate cortex network predicts Alzheimer’s disease progression. Front Aging Neurosci. 2020;12:466.
Palmqvist S, Schöll M, Strandberg O, et al. Earliest accumulation of β-amyloid occurs within the default-mode network and concurrently affects brain connectivity. Nat Commun. 2017;8:1-13.
Fernández-Cabello S, Kronbichler M, van Dijk KRA, Goodman JA, Nathan Spreng R, Schmitz TW. Basal forebrain volume reliably predicts the cortical spread of Alzheimer’s degeneration. Brain. 2020;143:993-1009.
Schulz J, Pagano G, Fernández Bonfante JA, Wilson H, Politis M. Nucleus basalis of Meynert degeneration precedes and predicts cognitive impairment in Parkinson’s disease. Brain. 2018;141: 1501-1516.
Nishioka C, Liang HF, Barsamian B, Sun SW. Amyloid-beta induced retrograde axonal degeneration in a mouse tauopathy model. Neuroimage. 2019;189:180-191.
Teipel SJ, Kuper-Smith JO, Bartels C, et al. Multicenter tract-based analysis of microstructural lesions within the Alzheimer’s disease Spectrum: Association with amyloid pathology and diagnostic usefulness. J Alzheimers Dis. 2019;72: 455-465.
