The DOI matches its Crossref record; 40 of the 41 references it cites were found in a registry or an index.
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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“Among them, three COM texture features were negatively correlated with the MMSE scores (Table 5), while one COM texture feature was positively correlated with the clinical scale (Table 5).”
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Entorhinal Cortex Thickness Predicts Cognitive Decline in Alzheimer's Disease
Velayudhan, L., Proitsi, P., Westman, E., Muehlboeck, J., Mecocci, P., Vellas, B. J., Tsolaki, M., Kłoszewska, I., Soininen, H. S., Spenger, C., et al. (2013) · Journal of Alzheimer s Disease · doi:10.3233/jad-2012-121408 · Cited by 132
Neuroimaging Modalities in Alzheimer’s Disease: Diagnosis and Clinical Features
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Progression of Atrophy in Alzheimer’s Disease and Related Disorders
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Self-citationSpatial patterns of brain amyloid- burden and atrophy rate associations in mild cognitive impairment
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Depressive Symptoms and Biomarkers of Alzheimer’s Disease in Cognitively Normal Older Adults
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BackgroundResultInfluentialSex differences in grey matter atrophy patterns among AD and aMCI patients: Results from ADNI
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“MRI measurements of volume loss have been used to assess atrophy in AD (Freeborough et al., 1997; O’Brien et al., 2001) and to differentiate both single-domain and multi-domain aMCI and AD from control (Jack et al., 2004; Jack et al., 2005; Sluimer et al., 2008).”
Relationship between regional atrophy rates and cognitive decline in mild cognitive impairment
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“Whole brain atrophy rates have been associated with decline on measures of global cognition (Evans et al.; Sluimer et al., 2008), verbal memory (Jack et al., 2004), and set-shifting performance (Evans et al.).”
Whole-brain atrophy rate in Alzheimer disease: Identifying fast progressors
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Rate of entorhinal and hippocampal atrophy in incipient and mild AD: Relation to memory function
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BackgroundPotential Predictors of Hippocampal Atrophy in Alzheimerʼs Disease
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Mapping Neurodegenerative Disease Onset and ProgressionPreprint
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Reduced gray matter volume in normal adults with a maternal family history of Alzheimer disease
Honea, R. A., Swerdlow, R. H., Vidoni, E. D., Goodwin, J., & Burns, J. M. (2010) · Neurology · doi:10.1212/wnl.0b013e3181c918cb · Cited by 106
Acosta‐Cabronero, J., & Nestor, P. J. (2014) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2014.00266 · Cited by 109
“Torrey, H. C. (1956). Bloch equations with diffusion terms.”
BackgroundBarnes, J., Scahill, R. I., Schott, J. M., Frost, C. D., Rossor, M. N., & Fox, N. C. (2005) · Dementia and Geriatric Cognitive Disorders · doi:10.1159/000084560 · Cited by 108
The unsolved relationship of brain aging and late-onset Alzheimer disease
Kern, A., & Behl, C. (2009) · Biochimica et Biophysica Acta (BBA) - General Subjects · doi:10.1016/j.bbagen.2009.07.016 · Cited by 108
“The expansion of brain atrophy correlates with the cognitive decline observed in LOAD patients [17,18].”
BackgroundDifferentiating AD from aging using semiautomated measurement of hippocampal atrophy rates
Barnes, J., Scahill, R. I., Boyes, R. G., Frost, C. D., Lewis, E. B., Rossor, C. L., Rossor, M. N., & Fox, N. C. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.06.028 · Cited by 103
Belleville, S., Fouquet, C., Duchesne, S., Collins, D. L., & Hudon, C. (2014) · Journal of Alzheimer s Disease · doi:10.3233/jad-141470 · Cited by 114
“Whole brain and ventricular volumes have also been shown to predict progression, although the overall predictive accuracy level was relatively low [67].”
Vitali, P., Migliaccio, R., Agosta, F., Rosen, H., & Geschwind, M. D. (2008) · Seminars in Neurology · doi:10.1055/s-0028-1083695 · Cited by 105
3D comparison of low, intermediate, and advanced hippocampal atrophy in MCI
Apostolova, L. G., Thompson, P. M., Green, A. E., Hwang, K., Zoumalan, C., Jack, C. R., Harvey, D. J., Petersen, R. C., Thal, L. J., Aisen, P. S. S., et al. (2010) · Human Brain Mapping · doi:10.1002/hbm.20905 · Cited by 100
“Hippocampal atrophy is commonly seen in subjects with amnestic MCI [Apostolova et al., 2006b; De Leon et al., 1997; Dickerson et al., 2001; Jack et al., 2004; Morra, 2009a,b; Mueller and Dickerson, 2008].”
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Kim, S. H., Kandiah, N., Hsu, J., Suthisisang, C. C., Udommongkol, C., & Dash, A. (2017) · British Journal of Pharmacology · doi:10.1111/bph.14030 · Cited by 100
“Increasing rates of hippocampal atrophy have been correlated with progression of AD according to cognitive rating scale scores (MMSE and global and sum-of-boxes Clinical Dementia Rating scale) (Dubois et al., 2015; Morra et al., 2009; Jack et al., 2004; Henneman et al., 2009; Vos et al., 2013).”
BackgroundCole, J. H., Caan, M. W. A., Underwood, J., Francesco, D. D., van Zoest, R. A., Wit, F. W. N. M., Mutsaerts, H. J. M. M., Leech, R., Geurtsen, G. J., Portegies, P., et al. (2018) · Clinical Infectious Diseases · doi:10.1093/cid/cix1124 · Cited by 98
“, Alzheimer’s disease, traumatic brain injury) commonly report changes above and beyond expected ageing-related declines in shorter timescales [36, 37].”
Magnetic resonance spectroscopy reveals abnormalities of glucose metabolism in the Alzheimer's brain
Mullins, R. J., Reiter, D. A., & Kapogiannis, D. (2018) · Annals of Clinical and Translational Neurology · doi:10.1002/acn3.530 · Cited by 98
Carmichael, O. T., Kuller, L. H., López, O. L., Thompson, P. M., Dutton, R. A., Lu, A. P., Lee, S. E., Lee, J. Y., Aizenstein, H. J., MELTZER, C. C., et al. (2007) · Alzheimer Disease & Associated Disorders · doi:10.1097/wad.0b013e318032d2b1 · Cited by 101
“Table 5 shows the annual percent change in brain and ventricular volume in this report and a similar previous paper by Jack et al.34 Variability in both measures is generally higher in our sample; this could reflect differences in a variety of factors, including imaging data quality, data processing software, MCI diag…”
BackgroundMethodResultInfluentialEvaluating Alzheimer’s Disease Progression Using Rate of Regional Hippocampal Atrophy
Frankó, E., Joly, O., & Initiative, A. D. N. (2013) · PLoS ONE · doi:10.1371/journal.pone.0071354 · Cited by 98
Tosun, D., Schuff, N. W., Truran‐Sacrey, D., Shaw, L. M. J., Trojanowski, J. Q., Aisen, P. S. S., Peterson, R., & Weiner, M. W. (2010) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2010.04.030 · Cited by 99
Frisoni, G. B., & Jack, C. R. (2011) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2010.06.007 · Cited by 98
Self-citationAccelerating regional atrophy rates in the progression from normal aging to Alzheimer’s disease
Sluimer, J. D., van der Flier, W. M., Karas, G. B., van Schijndel, R. A., Barnes, J., Boyes, R. G., Cover, K. S., Olabarriaga, S. D., Fox, N. C., Scheltens, P., et al. (2009) · European Radiology · doi:10.1007/s00330-009-1512-5 · Cited by 99
“Previous studies report increased cerebral atrophy rates and ventricular enlargement in AD versus controls [9, 24].”
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Baseline predictors of rates of hippocampal atrophy in mild cognitive impairment
van de Pol, L. A., van der Flier, W. M., Korf, E. S. C., Fox, N. C., Barkhof, F., & Scheltens, P. (2007) · Neurology · doi:10.1212/01.wnl.0000277458.26846.96 · Cited by 94
Longitudinal Study of CSF Biomarkers in Patients with Alzheimer's Disease
Buchhave, P., Blennow, K., Zetterberg, H., Stomrud, E., Londos, E., Andreasen, N., Minthon, L., & Hansson, O. (2009) · PLoS ONE · doi:10.1371/journal.pone.0006294 · Cited by 95
Ally, B. A., Gold, C. A., & Budson, A. E. (2008) · Brain and Cognition · doi:10.1016/j.bandc.2008.11.003 · Cited by 99
“These results are consistent with neuropathological studies showing that the hippocampus (Jack et al., 2004; Karas et al., 2004) and anterior medial temporal regions (Csernansky et al., 2004; Gomez-Isla et al., 1996; Kantarci et al., 2005) appear to be the earliest affected by neurofibrillary…”
Exercise Improves Vascular Function, but does this Translate to the Brain?
Barnes, J. N., & Corkery, A. T. (2018) · Brain Plasticity · doi:10.3233/bpl-180075 · Cited by 105
Hedden, T., & Gabrieli, J. D. E. (2005) · Current Opinion in Neurology · doi:10.1097/01.wco.0000189875.29852.48 · Cited by 91
MRI measures of temporoparietal regions show differential rates of atrophy during prodromal AD
Desikan, R. S., Fischl, B. R., Cabral, H., Kemper, T. L., Guttmann, C. R. G., Blacker, D., Hyman, B. T., Albert, M., & Killiany, R. (2008) · Neurology · doi:10.1212/01.wnl.0000320055.57329.34 · Cited by 93
Verclytte, S., Lopes, R., Lenfant, P., Rollin, A., Semah, F., Leclerc, X., Pasquier, F., & Delmaire, C. (2015) · Journal of Neuroimaging · doi:10.1111/jon.12264 · Cited by 93
High Degree of Heterogeneity in Alzheimer's Disease Progression Patterns
Komarova, N. L., & Thalhauser, C. J. (2011) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002251 · Cited by 97
Shi, J., Thompson, P. M., Gutman, B. A., & Wang, Y. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.04.018 · Cited by 92
“Although most subcortical structure analysis work used volume as the atrophy measurement (Jack et al., 2003; Jack et al., 2004; Ridha et al., 2008; Holland et al., 2009; den Heijer et al., 2010; Dewey et al., 2010; Wolz et al., 2010), recent researches (Thompson et al.”
Eckerström, C., Olsson, E., Borga, M., EKHOLM, S. E., Ribbelin, S., Rolstad, S., Starck, G., Edman, Å., Wallin, A., & Malmgren, H. (2008) · Journal of the Neurological Sciences · doi:10.1016/j.jns.2008.04.024 · Cited by 88
“2% in MCI [18] and the decline appears to be increased in converting MCI and AD patients compared to stable MCI patients and cognitively stable controls [19,20].”
ResultBiomarkers for neurodegenerative diseases
Henley, S. M. D., Bates, G. P., & Tabrizi, S. J. (2005) · Current Opinion in Neurology · doi:10.1097/01.wco.0000186842.51129.cb · Cited by 91
Amyloid-β deposition and regional grey matter atrophy rates in dementia with Lewy bodies
Sarro, L., Senjem, M. L., Lundt, E. S., Przybelski, S. A., Lesnick, T. G., Graff-Radford, J., Boeve, B. F., Lowe, V. J., Ferman, T. J., Knopman, D. S., et al. (2016) · Brain · doi:10.1093/brain/aww193 · Cited by 89
Self-citationThe diffeomorphometry of temporal lobe structures in preclinical Alzheimer's disease
Miller, M. I., Younes, L., Ratnanather, J. T., Brown, T., Trinh, H., Postell, E., Lee, D. S., Wang, M.-C., Mori, S., O'Brien, R., et al. (2013) · NeuroImage: Clinical · doi:10.1016/j.nicl.2013.09.001 · Cited by 88
“Differences in atrophy rate of the entorhinal cortex (Jack et al., 2004), the hippocampus or subvolumes of the hippocampus (Jack et al., 2004; Apostolova et al., 2010) and ventricular volume (Carlson et al., 2008) have been demonstrated during preclinical AD.”
Brain and ventricular volumetric changes in frontotemporal lobar degeneration over 1 year
Knopman, D. S., Jack, C. R., Kramer, J. H., Boeve, B. F., Caselli, R. J., Graff-Radford, N. R., Mendez, M. F., Miller, B. L., & Mercaldo, N. D. (2009) · Neurology · doi:10.1212/wnl.0b013e3181a71236 · Cited by 85
Self-citationClerx, L., van Rossum, I. A., Burns, L., Knol, D. L., Scheltens, P., Verhey, F., Aalten, P., Lapuerta, P., van de Pol, L., van Schijndel, R., et al. (2013) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2013.02.002 · Cited by 98
Unbiased comparison of sample size estimates from longitudinal structural measures in ADNI
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“Atrophy measures in neuroanatomical subregions correlate well with disease stage determined from histopathology [Vemuri et al., 2008], and with clinical measures of disease severity [Jack et al., 2004; McDonald et al., 2009].”
BackgroundCortical thickness in relation to clinical symptom onset in preclinical AD
Pettigrew, C. A., Soldan, A., Zhu, Y., Wang, M., Moghekar, A., Brown, T., Miller, M. I., & Albert, M. (2016) · NeuroImage Clinical · doi:10.1016/j.nicl.2016.06.010 · Cited by 88
Brain Behavior Relationships Among African Americans, Whites, and Hispanics
DeCarli, C. S., Reed, B., Jagust, W. J., Martinez, O., Ortega, M., & Mungas, D. (2008) · Alzheimer Disease & Associated Disorders · doi:10.1097/wad.0b013e318185e7fe · Cited by 83
Novel neuroprotective effects of the aqueous extracts from Verbena officinalis Linn
Lai, S.-W., Yu, M.-S., Yuen, W.-H., & Chang, R. C. (2006) · Neuropharmacology · doi:10.1016/j.neuropharm.2005.11.009 · Cited by 85
A Systematic Review of Longitudinal Studies Which Measure Alzheimer’s Disease Biomarkers
Lawrence, E., Vegvari, C., Ower, A. K., Hadjichrysanthou, C., de Wolf, F., & Anderson, R. M. (2017) · Journal of Alzheimer s Disease · doi:10.3233/jad-170261 · Cited by 89
Li, H., & Fan, Y. (2019) · 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019) · doi:10.1109/isbi.2019.8759397 · Cited by 83
“Longitudinal changes of biomarkers and imaging markers have been investigated for AD diagnosis/prognosis, for instance, changes of neuropsychological measures [12], atrophy rate in cortical thickness and subcortical volume [9, 13-15], and changes in brain tissue intensity/density map [10].”
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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