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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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InfluentialSelf-citationPerspectives on Depression, Mild Cognitive Impairment, and Cognitive Decline
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“Jack et al. compared annual rates of volume decline for healthy individuals and individuals with AD (Jack et al., 2004).”
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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
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“…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 265
“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 244
“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
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 243
Neuropathologic Alterations in Mild Cognitive Impairment: A Review
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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
Self-citationStructural MRI biomarkers for preclinical and mild Alzheimer's disease
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The Role of Biomarkers in Clinical Trials for Alzheimer Disease
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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 240
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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
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 225
“[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 227
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Longitudinal 1H MRS changes in mild cognitive impairment and Alzheimer's disease
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Self-citationLifespan Changes of the Human Brain In Alzheimer’s Disease
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Subregional neuroanatomical change as a biomarker for Alzheimer's disease
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“The fact that atrophy associated with AD can be detected in vivo using MRI has long been known (2).”
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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 217
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Sleep Duration and Age-Related Changes in Brain Structure and Cognitive Performance
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Microglia and multiple sclerosis
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“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 192
“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
Longitudinal Change of Biomarkers in Cognitive Decline
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“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.”
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Boosting power for clinical trials using classifiers based on multiple biomarkers
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“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
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MRI predictors of risk of incident Alzheimer disease
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Alzheimer's Disease Diagnosis Using Landmark-Based Features From Longitudinal Structural MR Images
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“, 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
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Volumetric MRI vs clinical predictors of Alzheimer disease in mild cognitive impairment
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Self-citationAnatomical Brain Images Alone Can Accurately Diagnose Chronic Neuropsychiatric Illnesses
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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
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 177
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“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
Metadata
- 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
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Health Sciences › Medicine › Oncology › 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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