The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Changes in premorbid brain volume predict Alzheimer’s disease pathology
Abstract
OBJECTIVE: To assess whether changes in antemortem MRI brain volume measurements are valid predictors of subsequent Alzheimer disease (AD) pathology. METHODS: Thirty-nine subjects, 15 nondemented and 24 with cognitive impairment, were followed until death. Regional postmortem measures of senile plaque (SP) and neurofibrillary tangle (NFT) severity were examined in relationship to cross-sectional and longitudinal volumetric measurements obtained from antemortem MRI. RESULTS: Total brain volume change over time was related to the accumulation of cortical NFT. The rate of ventricular CSF volume increase was related to both cortical NFT and SP. The last hippocampal volume prior to death was related to hippocampal NFT burden; the rate of hippocampal volume atrophy was not related to hippocampal NFT pathology. These significant relationships continue to exist when all nondemented subjects are excluded from analysis. In subjects with cognitive impairment, the best predictor of cortical NFT and SP is the rate of ventricular volume increase. Excluding subjects with long duration between MRI and death did not appreciably alter results. CONCLUSIONS: MRI volumes measured over time are valid biomarkers of pathologic progression of AD across a range of antemortem clinical states. The rate of ventricular volume enlargement can be used to monitor disease progression or response to treatment in future clinical trials that are targeted at NFT and SP pathology.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Neuropathological stageing of Alzheimer-related changes.
Braak, H., & Braak, E. (1991) · Acta Neuropathologica · doi:10.1007/bf00308809 · Cited by 16,123
The Clinical Dementia Rating (CDR): Current version and scoring rules
Morris, J. C. (1993) · Neurology · doi:10.1212/wnl.43.11.2412-a · Cited by 9,882
Antemortem MRI findings correlate with hippocampal neuropathology in typical aging and dementia
Jack, C. R., Dickson, D. W., Parisi, J. E., Xu, Y. C., Cha, R. H., O’Brien, P. C., Edland, S. D., Smith, G. E., Boeve, B. F., Tangalos, E. G., et al. (2002) · Neurology · doi:10.1212/wnl.58.5.750 · Cited by 610
Kaye, J. A., Swihart, T., Howieson, D., Dame, A., Moore, M. M., Karnos, T., Camicioli, R., Ball, M., Oken, B., & Sexton, G. (1997) · Neurology · doi:10.1212/wnl.48.5.1297 · Cited by 399
Self-citation“Preclinical” AD revisited: Neuropathology of cognitively normal older adults
Schmitt, F. A., Davis, D. G., Wekstein, D. R., Smith, C. D., Ashford, J. W., & Markesbery, W. R. (2000) · Neurology · doi:10.1212/wnl.55.3.370 · Cited by 369
BOBINSKI, M., WEGIEL, J., TARNAWSKI, M., BOBINSKI, M., REISBERG, B., DE LEON, M. J., MILLER, D. C., & WISNIEWSKI, H. M. (1997) · Journal of Neuropathology and Experimental Neurology · doi:10.1097/00005072-199704000-00010 · Cited by 208
Cited by
Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade
Jack, C. R., Knopman, D. S., Jagust, W. J., Shaw, L. M., Aisen, P. S., Weiner, M. W., Petersen, R. C., & Trojanowski, J. Q. (2010) · The Lancet Neurology · doi:10.1016/s1474-4422(09)70299-6 · Cited by 4,806
Mueller, S. G., Weiner, M. W., Thal, L. J., Petersen, R. C., Jack, C. R., Jagust, W., Trojanowski, J. Q., Toga, A. W., & Beckett, L. (2005) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2005.06.003 · Cited by 1,233
Dickerson, B. C., Bakkour, A., Salat, D. H., Feczko, E., Pacheco, J., Greve, D. N., Grodstein, F., Wright, C. I., Blacker, D., Rosas, H. D., et al. (2009) · Cerebral Cortex · doi:10.1093/cercor/bhn113 · Cited by 1,153
Jack, C. R., Lowe, V. J., Weigand, S. D., Wiste, H. J., Senjem, M. L., Knopman, D. S., Shiung, M. M., Gunter, J. L., Boeve, B. F., Kemp, B. J., et al. (2009) · Brain · doi:10.1093/brain/awp062 · Cited by 1,099
Jack, C. R., Lowe, V. J., Senjem, M. L., Weigand, S. D., Kemp, B. J., Shiung, M. M., Knopman, D. S., Boeve, B. F., Klunk, W. E., Mathis, C. A., et al. (2008) · Brain · doi:10.1093/brain/awm336 · Cited by 958
Metadata
- Authors
- Silbert, L. C., Quinn, J. F., Moore, M. M., Corbridge, E., Ball, M. J., Murdoch, G., Sexton, G., & Kaye, J. A.
- Venue
- Neurology
- Published
- 2003-08-26
- Volume
- 61
- Issue
- 4
- Pages
- 487-492
- ISSN
- 0028-3878 (ISSN-L)
- 1526-632X
- OpenAlex
- W2162936584
- Cited by
- 279
- References
- 6
- FWCI
- 7.20
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.