Comparison of different MRI brain atrophy rate measures with clinical disease progression in AD
Open accessAbstract
OBJECTIVE: To correlate different methods of measuring rates of brain atrophy from serial MRI with corresponding clinical change in normal elderly subjects, patients with mild cognitive impairment (MCI), and patients with probable Alzheimer disease (AD). METHODS: One hundred sixty subjects were recruited from the Mayo Clinic Alzheimer's Disease Research Center and Alzheimer's Disease Patient Registry Studies. At baseline, 55 subjects were cognitively normal, 41 met criteria for MCI, and 64 met criteria for AD. Each subject underwent an MRI examination of the brain at the time of the baseline clinical assessment and then again at the time of a follow-up clinical assessment, 1 to 5 years later. The annualized changes in volume of four structures were measured from the serial MRI studies: hippocampus, entorhinal cortex, whole brain, and ventricle. Rates of change on several cognitive tests/rating scales were also assessed. Subjects who were classified as normal or MCI at baseline could either remain stable or convert to a lower-functioning group. AD subjects were dichotomized into slow vs fast progressors. RESULTS: All four atrophy rates were greater among normal subjects who converted to MCI or AD than among those who remained stable, greater among MCI subjects who converted to AD than among those who remained stable, and greater among fast than slow AD progressors. In general, atrophy on MRI was detected more consistently than decline on specific cognitive tests/rating scales. With one exception, no differences were found among the four MRI rate measures in the strength of the correlation with clinical deterioration at different stages of the disease. CONCLUSIONS: These data support the use of rates of change from serial MRI studies in addition to standard clinical/psychometric measures as surrogate markers of disease progression in AD. Estimated sample sizes required to power a therapeutic trial in MCI were an order of magnitude less for MRI than for change measures based on cognitive tests/rating scales.
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Self-citationA meta-analysis of hippocampal atrophy rates in Alzheimer's disease
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“In addition, loss of tissue volume over time can also be detected in large regions such as the whole brain (Jack et al., 2004) and in smaller temporal areas such as the hippocampus (Jack et al., 2004) and entorhinal cortex (Du et al., 2004).”
BackgroundMethodInfluentialApostolova, L. G., Green, A. E., Babakchanian, S., Hwang, K., Chou, Y., Toga, A. W., & Thompson, P. M. (2011) · Alzheimer Disease & Associated Disorders · doi:10.1097/wad.0b013e3182163b62 · Cited by 363 · see citing works
“over time relative to their cognitively stable counterparts.(12,14,15) Ventricular enlargement is strongly correlated with decline in cognitive performance(5,16,20) and with cerebrospinal fluid(16) and pathologic markers of AD.”
BackgroundHippocampal hypometabolism predicts cognitive decline from normal aging
Mosconi, L., De Santi, S., Li, J., Tsui, W. H., Li, Y., Boppana, M., Laska, E., Rusinek, H., & de Leon, M. J. (2008) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2006.12.008 · Cited by 360 · see citing works
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Hua, X., Leow, A., Parikshak, N., Lee, S., Chiang, M.-C., Toga, A. W., Jack, C. R., Weiner, M. W., & Thompson, P. M. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.07.013 · Cited by 359 · see citing works
“…conversion to AD over a specific follow-up interval (Jack et al., 1998; Scahill et al., 2003; Apostolova et al., 2006; Fleisher et al., 2008), and which measures link best with standard cognitive assessments (Fox et al., 1999; Jack et al., 2004; Thompson and Apostolova, 2007; Ridha et al., 2008).”
Self-citationThe Dynamics of Cortical and Hippocampal Atrophy in Alzheimer Disease
Sabuncu, M. R. (2011) · Archives of Neurology · doi:10.1001/archneurol.2011.167 · Cited by 360 · see citing works
“Most prior longitudinal studies have found that brain atrophy progressively accelerates throughout the disease process, although those studies mostly focus on global measures, such as wholebrain or ventricular volume,(3) or on a single anatomical structure, such as the hippocampus.(5,10,12) In this study, we used long…”
Diffusion tensor MRI as a biomarker in axonal and myelin damage
Aung, W. Y., Mar, S., & Benzinger, T. L. S. (2013) · Imaging in Medicine · doi:10.2217/iim.13.49 · Cited by 351 · see citing works
Longitudinal changes in cortical thickness associated with normal aging
Thambisetty, M., Wan, J., Carass, A., An, Y., Prince, J. L., & Resnick, S. M. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.04.258 · Cited by 343 · see citing works
“…such as the hippocampus and entorhinal cortex are especially vulnerable to early atrophic changes in AD (Du et al., 2004; Du et al., 2003; Jack et al., 2004), and accelerated longitudinal tissue loss in these structures has been shown to precede the onset of cognitive impairment in…”
BackgroundHigh‐field magnetic resonance imaging of brain iron: birth of a biomarker?
Schenck, J. F., & Zimmerman, E. A. (2004) · NMR in Biomedicine · doi:10.1002/nbm.922 · Cited by 330 · see citing works
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Tracking atrophy progression in familial Alzheimer's disease: a serial MRI study
Ridha, B. H., Barnes, J., Bartlett, J. W., Godbolt, A., Pepple, T., Rossor, M. N., & Fox, N. C. (2006) · The Lancet Neurology · doi:10.1016/s1474-4422(06)70550-6 · Cited by 326 · see citing works
Longitudinal volumetric MRI change and rate of cognitive decline
Mungas, D., Harvey, D., Reed, B. R., Jagust, W. J., DeCarli, C., Beckett, L., Mack, W. J., Kramer, J. H., Weiner, M. W., Schuff, N., et al. (2005) · Neurology · doi:10.1212/01.wnl.0000172913.88973.0d · Cited by 311 · see citing works
Subregional hippocampal atrophy predicts Alzheimer's dementia in the cognitively normal
Apostolova, L. G., Mosconi, L., Thompson, P. M., Green, A. E., Hwang, K., Ramírez, A., Mistur, R. L., Tsui, W. H., & de Leon, M. J. (2008) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2008.08.008 · Cited by 313 · see citing works
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van Oostveen, W. M., & de Lange, E. C. M. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22042110 · Cited by 297 · see citing works
“, the above structural MRI measures were combined and evaluated on their ability to predict disease progression [152].”
BackgroundInflammatory biomarkers are associated with total brain volume
Jefferson, A. L., Massaro, J. M., Wolf, P. A., Seshadri, S. S., Au, R., Vasan, R. S., Larson, M. G., Meigs, J. B., Keaney, J. F., Lipinska, I., et al. (2007) · Neurology · doi:10.1212/01.wnl.0000257815.20548.df · Cited by 277 · see citing works
“Systolic blood pressure, mm Hg 124 (19) 127 (17)”
BackgroundLongitudinal MRI atrophy biomarkers: Relationship to conversion in the ADNI cohort
Risacher, S. L., Shen, L., West, J. D., Kim, S., McDonald, B. C., Beckett, L. A., Harvey, D. J., Jack, C. R., Weiner, M. W., & Saykin, A. J. (2010) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2010.04.029 · Cited by 276 · see citing works
“…2006; Jack et al., 2000, 2004, 2005; Sluimer et al., 2008; Stoub et al., 2008), with patients who convert from MCI to probable AD showing higher rates of hippocampal atrophy compared with patients with a stable diagnosis of MCI, reported as 3.5% and 2.2%, respectively (Jack et al., 2000, 2004).”
InfluentialSelf-citationPerspectives on Depression, Mild Cognitive Impairment, and Cognitive Decline
Steffens, D. C., Otey, E., Alexopoulos, G. S., Butters, M. A., Cuthbert, B., Ganguli, M., Geda, Y. E., Hendrie, H. C., Krishnan, R. R., Kumar, A., et al. (2006) · Archives of General Psychiatry · doi:10.1001/archpsyc.63.2.130 · Cited by 274 · see citing works
Self-citationAccuracy of dementia diagnosis: a direct comparison between radiologists and a computerized method
Kloppel, S., Stonnington, C. M., Barnes, J., Chen, F., Chu, C., Good, C. D., Mader, I., Mitchell, L. A., Patel, A. C., Roberts, C. C., et al. (2008) · Brain · doi:10.1093/brain/awn239 · Cited by 271 · see citing works
Self-citationProgression of language decline and cortical atrophy in subtypes of primary progressive aphasia
Rogalski, E., Cobia, D., Harrison, T. M., Wieneke, C., Weintraub, S., & Mesulam, M.-M. (2011) · Neurology · doi:10.1212/wnl.0b013e31821ccd3c · Cited by 252 · see citing works
Brain aging mechanisms with mechanical manifestations
Blinkouskaya, Y., Caçoilo, A., Gollamudi, T., Jalalian, S., & Weickenmeier, J. (2021) · Mechanisms of Ageing and Development · doi:10.1016/j.mad.2021.111575 · Cited by 274 · see citing works
“Jack et al. compared annual rates of volume decline for healthy individuals and individuals with AD (Jack et al., 2004).”
Backgroundden Heijer, T., van der Lijn, F., Koudstaal, P. J., Hofman, A., van der Lugt, A., Krestin, G. P., Niessen, W. J., & Breteler, M. M. B. (2010) · Brain · doi:10.1093/brain/awq048 · Cited by 261 · see citing works
“In the elderly, rates of hippocampal atrophy on MRI were found to be higher in cases with Alzheimer’s disease and mild cognitive impairment compared with controls (Du et al., 2004; Jack et al., 2004).”
BackgroundPredicting clinical scores from magnetic resonance scans in Alzheimer's disease
Stonnington, C. M., Chu, C., Klöppel, S., Jack, C. R., Ashburner, J., & Frackowiak, R. S. J. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.03.051 · Cited by 256 · see citing works
“…measures and structural changes with MRI has been previously examined using voxel based morphometry (VBM) (Baxter et al., 2006; Jack et al., 2008b) and region of interest studies (Apostolova et al., 2006; Duchesne et al., 2009; Fama et al., 1997; Ferrarini et al., 2008; Jack et al., 2004).”
Self-citation3D comparison of hippocampal atrophy in amnestic mild cognitive impairment and Alzheimer's disease
Apostolova, L. G., Dinov, I. D., Dutton, R. A., Hayashi, K. M., Toga, A. W., Cummings, J. L., & Thompson, P. M. (2006) · Brain · doi:10.1093/brain/awl274 · Cited by 251 · see citing works
Apostolova, L. G. (2016) · CONTINUUM Lifelong Learning in Neurology · doi:10.1212/con.0000000000000307 · Cited by 253 · see citing works
Leung, K. K., Barnes, J., Ridgway, G. R., Bartlett, J. W., Clarkson, M. J., Macdonald, K. E., Schuff, N. W., Fox, N. C., & Sebastien Ourselin, A. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.03.018 · Cited by 244 · see citing works
“…controls, with those progressing to a diagnosis of dementia having higher rates than those remaining stable: median rates being 4.3% vs. 3.0% per year (mean age = 71 in MCI) (Henneman et al., 2009), 3.3% vs 1.8% per year (mean age = 77 in converters and 76 in stable subjects) (Jack et al., 2004).”
InfluentialRole of structural MRI in Alzheimer's disease
Vemuri, P., & Jack, C. R. (2010) · Alzheimer s Research & Therapy · doi:10.1186/alzrt47 · Cited by 246 · see citing works
“Unlike BSI, which analyzes only spatial shift in the brain surfaces, TBM provides a 3D profi le of voxel-level brain degeneration.”
MethodInfluentialSelf-citationMorra, J. H., Tu, Z., Apostolova, L. G., Green, A. E., Avedissian, C., Madsen, S. K., Parikshak, N., Toga, A. W., Jack, C. R., Schuff, N. W., et al. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.10.043 · Cited by 241 · see citing works
“3 shows that, in linewithmany prior longitudinal studies of AD versus controls (Jack et al., 1998, 2004) and versus MCI subjects (Jack et al., 2000, 2004), hippocampal tissue loss is detected in all 3 diagnostic groups.”
Self-citationNeurostructural predictors of Alzheimer's disease: A meta-analysis of VBM studies
Ferreira, L. K., Diniz, B. S., Forlenza, O. V., Busatto, G. F., & Zanetti, M. V. (2009) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2009.11.008 · Cited by 241 · see citing works
Neuropathologic Alterations in Mild Cognitive Impairment: A Review
Markesbery, W. R. (2010) · Journal of Alzheimer's Disease · doi:10.3233/jad-2010-1220 · Cited by 236 · see citing works
Smith, E. E., Egorova, S., Blacker, D., Killiany, R., Muzikansky, A., Dickerson, B. C., Tanzi, R. E., Albert, M., Greenberg, S. M., & Guttmann, C. R. G. (2008) · Archives of Neurology · doi:10.1001/archneurol.2007.23 · Cited by 238 · see citing works
Sex and age differences in atrophic rates: an ADNI study with n=1368 MRI scans
Hua, X., Hibar, D. P., Lee, S., Toga, A. W., Jack, C. R., Weiner, M. W., & Thompson, P. M. (2010) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2010.04.033 · Cited by 234 · see citing works
Self-citationStructural MRI biomarkers for preclinical and mild Alzheimer's disease
Fennema‐Notestine, C., Hagler, D. J., McEvoy, L. K., Fleisher, A. S., Wu, E. H., Karow, D. S., & Dale, A. M. (2009) · Human Brain Mapping · doi:10.1002/hbm.20744 · Cited by 233 · see citing works
The Role of Biomarkers in Clinical Trials for Alzheimer Disease
Thal, L. J., Kantarci, K., Reiman, E. M., Klunk, W. E., Weiner, M. W., Zetterberg, H., Galasko, D., Praticò, D., Griffin, S. T., Schenk, D., et al. (2006) · Alzheimer Disease & Associated Disorders · doi:10.1097/01.wad.0000191420.61260.a8 · Cited by 233 · see citing works
β‐amyloid burden is not associated with rates of brain atrophy
Josephs, K. A., Whitwell, J. L., Ahmed, Z., Shiung, M. M., Weigand, S. D., Knopman, D. S., Boeve, B. F., Parisi, J. E., Petersen, R. C., Dickson, D. W., et al. (2007) · Annals of Neurology · doi:10.1002/ana.21223 · Cited by 224 · see citing works
Self-citationFotenos, A. F., Mintun, M., Snyder, A., Morris, J., & Buckner, R. (2008) · Archives of Neurology · doi:10.1001/archneurol.2007.27 · Cited by 228 · see citing works
Brain imaging evidence of preclinical Alzheimer's disease in normal aging
Jagust, W., Gitcho, A., Sun, F., Kuczynski, B., Mungas, D., & Haan, M. (2006) · Annals of Neurology · doi:10.1002/ana.20799 · Cited by 222 · see citing works
Jack, C. R., Barkhof, F., Bernstein, M. A., Cantillon, M., Cole, P. E., DeCarli, C. S., Dubois, B., Duchesne, S., Fox, N. C., Frisoni, G. B., et al. (2011) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2011.04.007 · Cited by 219 · see citing works
“[28] Jack CR Jr, Shiung MM, Gunter JL, O’Brien PC, Weigand SD, Knopman DS, et al.”
BackgroundInfluentialSelf-citationNutrient biomarker patterns, cognitive function, and MRI measures of brain aging
Bowman, G. L., Silbert, L. C., Howieson, D. B., Dodge, H. H., Traber, M. G., Frei, B. B., Kaye, J. A., Shannon, J., & Quinn, J. F. (2011) · Neurology · doi:10.1212/wnl.0b013e3182436598 · Cited by 218 · see citing works
Lombardi, G., Crescioli, G., Cavedo, E., Lucenteforte, E., Casazza, G., Bellatorre, A.-G., Lista, C., Costantino, G., Frisoni, G., Virgili, G., et al. (2020) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd009628.pub2 · Cited by 214 · see citing works
Longitudinal 1H MRS changes in mild cognitive impairment and Alzheimer's disease
Kantarci, K., Weigand, S. D., Petersen, R. C., Boeve, B. F., Knopman, D. S., Gunter, J. L., Reyes, D. A., Shiung, M. S., O’Brien, P. C., Smith, G. E., et al. (2006) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2006.06.018 · Cited by 213 · see citing works
Self-citationLifespan Changes of the Human Brain In Alzheimer’s Disease
Pierrick Coupé, A., Manjón, J. V., Lanuza, E., & Catheline, G. (2019) · Scientific Reports · doi:10.1038/s41598-019-39809-8 · Cited by 213 · see citing works
Subregional neuroanatomical change as a biomarker for Alzheimer's disease
Holland, D., Brewer, J. B., Hagler, D. J., Fennema-Notestine, C., Dale, A. M., Initiative, T. A. D. N., Weiner, M., Thal, L., Petersen, R., Jack, C. R., et al. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0906053106 · Cited by 210 · see citing works
“The fact that atrophy associated with AD can be detected in vivo using MRI has long been known (2).”
Self-citationIm, K., Lee, J. M., Seo, S. W., Kim, S. H., Kim, S. I., & Na, D. L. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.07.016 · Cited by 204 · see citing works
Frisoni, G. B., Jack, C. R., Bocchetta, M., Bauer, C. M., Frederiksen, K. S., Liu, Y., Preboske, G. M., Swihart, T., Blair, M., Cavedo, E., et al. (2014) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2014.05.1756 · Cited by 207 · see citing works
Self-citationMolano, J. R. V., Boeve, B. F., Ferman, T. J., Smith, G. E., Parisi, J. E., Dickson, D. W., Knopman, D. S., Graff‐Radford, N. R., Geda, Y. E., Lucas, J. A., et al. (2009) · Brain · doi:10.1093/brain/awp280 · Cited by 206 · see citing works
Self-citationHu, C., Yu, D., Sun, X., Zhang, M., Wang, L., & Qin, H. (2017) · International Psychogeriatrics · doi:10.1017/s1041610217000473 · Cited by 201 · see citing works
Sleep Duration and Age-Related Changes in Brain Structure and Cognitive Performance
Lo, J. C.-Y., Loh, K. K., Zheng, H., Sim, S. K. Y., & Chee, M. W. L. (2014) · SLEEP · doi:10.5665/sleep.3832 · Cited by 191 · see citing works
Microglia and multiple sclerosis
Jack, C., Ruffini, F., Bar-Or, A., & Antel, J. (2005) · Journal of Neuroscience Research · doi:10.1002/jnr.20482 · Cited by 205 · see citing works
“In cultures of microglia isolated from normalappearing human white matter biopsies, we detected variable expression of TLR2, 3, and 4 at the RNA level, with TLR4 expression being the most consistent (Jack et al., 2004b).”
BackgroundSelf-citationde Vos, F., Koini, M., Schouten, T. M., Seiler, S., van der Grond, J., Lechner, A., Schmidt, R., de Rooij, M., & Rombouts, S. A. R. B. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.11.025 · Cited by 191 · see citing works
“Alzheimer's disease (AD) is a neurodegenerative disorder characterized by widespread grey matter atrophy (Jack et al., 2004), specifically hippocampal atrophy is considered to be the hallmark of AD (Morra et al., 2010).”
BackgroundRose, S. (2006) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp.2005.074336 · Cited by 189 · see citing works
Longitudinal Change of Biomarkers in Cognitive Decline
Lo, R. Y. (2011) · Archives of Neurology · doi:10.1001/archneurol.2011.123 · Cited by 190 · see citing works
“and early conversion to dementia in mild cognitive impairment (MCI) in previous studies.(10-13) Several longitudinal FDG-PET studies also suggested that regional hypometabolism predicted clinical progression or conversion to AD.”
Jernerén, F., Elshorbagy, A. K., Oulhaj, A., Smith, S. M., Refsum, H., & Smith, A. D. (2015) · American Journal of Clinical Nutrition · doi:10.3945/ajcn.114.103283 · Cited by 189 · see citing works
Boosting power for clinical trials using classifiers based on multiple biomarkers
Kohannim, O., Hua, X., Hibar, D. P., Lee, S., Chou, Y.-Y., Toga, A. W., Jack, C. R., Weiner, M. W., & Thompson, P. M. (2010) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2010.04.022 · Cited by 190 · see citing works
“Brain atrophy rates measured by MRI correlate with the progression of Alzheimer’s disease, and offer baseline and transitional predictive power for diagnosis, making them clinically relevant endpoints for power analysis (Duara et al., 2008, Fox et al., 2000, Jack et al., 2004).”
Self-citationEarly detection of Alzheimer’s disease using neuroimaging
Mosconi, L., Bryś, M., Głodzik-Sobańska, L., Santi, S. D., Rusinek, H., & de Leon, M. J. (2006) · Experimental Gerontology · doi:10.1016/j.exger.2006.05.016 · Cited by 186 · see citing works
MRI predictors of risk of incident Alzheimer disease
Stoub, T. R., Bulgakova, M., Leurgans, S. E., Bennett, D. A., Fleischman, D. A., Turner, D. A., & deToledo‐Morrell, L. (2005) · Neurology · doi:10.1212/01.wnl.0000160089.43264.1a · Cited by 188 · see citing works
Alzheimer's Disease Diagnosis Using Landmark-Based Features From Longitudinal Structural MR Images
Zhang, J., Liu, M., An, L., Gao, Y., & Shen, D. G. (2017) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2017.2704614 · Cited by 181 · see citing works
“, hippocampus, entorhinal cortex, whole brain, and ventricle), and supported the idea of using changing rates as biomarkers for AD diagnosis [17].”
BackgroundA systematic review and meta-analysis of longitudinal hippocampal atrophy in healthy human ageing
Fraser, M. A., Shaw, M. E., & Cherbuin, N. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.03.035 · Cited by 175 · see citing works
Volumetric MRI vs clinical predictors of Alzheimer disease in mild cognitive impairment
Fleisher, A., Sun, S., Taylor, C., Ward, C., Gamst, A. C., Petersen, R. C., Jack, C. R., Aisen, P. S. S., & Thal, L. J. (2008) · Neurology · doi:10.1212/01.wnl.0000287091.57376.65 · Cited by 177 · see citing works
Self-citationAnatomical Brain Images Alone Can Accurately Diagnose Chronic Neuropsychiatric Illnesses
Bansal, R., Staib, L. H., Laine, A. F., Hao, X., Xu, D., Liu, J., Weissman, M. M., & Peterson, B. S. (2012) · PLoS ONE · doi:10.1371/journal.pone.0050698 · Cited by 176 · see citing works
Atrophy rates accelerate in amnestic mild cognitive impairment
Jack, C. R., Weigand, S. D., Shiung, M. M., Przybelski, S. A., O’Brien, P. C., Gunter, J. L., Knopman, D. S., Boeve, B. F., Smith, G. E., & Petersen, R. C. (2007) · Neurology · doi:10.1212/01.wnl.0000281688.77598.35 · Cited by 175 · see citing works
Self-citationWhole-Brain Atrophy Rate and Cognitive Decline: Longitudinal MR Study of Memory Clinic Patients
Sluimer, J. D., van der Flier, W. M., Karas, G. B., Fox, N. C., Scheltens, P., Barkhof, F., & Vrenken, H. (2008) · Radiology · doi:10.1148/radiol.2482070938 · Cited by 173 · see citing works
Iglesias, J. E., Leemput, K. V., Augustinack, J. C., Insausti, R., Fischl, B. R., & Reuter, M. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.07.020 · Cited by 170 · see citing works
“This is consistent with the results of other studies based on manual (Jack et al., 2000, 2004) and automated segmentations (Risacher et al., 2009).”
ResultInfluential
- Authors
- Jack, C. R., Shiung, M. M., Gunter, J. L., O’Brien, P. C., Weigand, S. D., Knopman, D. S., Boeve, B. F., Ivnik, R. J., Smith, G. E., Cha, R. H., Tangalos, E. G., & Petersen, R. C.
- Affiliations
- Mayo Clinic (US)
- ORCID
- Venue
- Neurology
- Published
- 2004-02-24
- Volume
- 62
- Issue
- 4
- Pages
- 591-600
- ISSN
- 0028-3878 (ISSN-L)
- 1526-632X
- PMC
- PMC2730165
- OpenAlex
- W2005133023
- Cited by
- 827
- References
- 41
- Citations by year
- 2026: 17 · 2025: 19 · 2024: 21 · 2023: 25 · 2022: 20 · 2021: 36 · 2020: 27 · 2019: 38 · 2018: 36 · 2017: 37 · 2016: 33 · 2015: 39 · 2014: 41 · 2013: 48 · 2012: 38
- FWCI
- 28.59
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Neurology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute on Aging (AG-06786, AG 16574, U01AG006786, R01AG011378, AG-11378, U19AG010483, R37AG011378, P50AG016574)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Cancer-related cognitive impairment studies
- Keywords
- Alzheimer's disease, brain atrophy rate, serial MRI, hippocampal atrophy, entorhinal cortex atrophy, whole brain atrophy, ventriculomegaly, mild cognitive impairment, disease progression, surrogate markers, cognitive decline, trial size, MCI conversion
- MeSH terms
- Aged, Aged, 80 and over, Alzheimer Disease, Apolipoproteins E, Atrophy, Brain, Cognition Disorders, Female, Hippocampus, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Cohort Studies, Disease Progression, Entorhinal Cortex, Apolipoprotein E4
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