The DOI matches its Crossref record; 144 of the 145 references it cites were found in a registry or an index.
Neuroimaging and Early Diagnosis of Alzheimer Disease: A Look to the Future
Abstract
Alzheimer disease (AD), a progressive neurodegenerative disorder, is the most common cause of dementia in the elderly. Current consensus statements have emphasized the need for early recognition and the fact that a diagnosis of AD can be made with high accuracy by using clinical, neuropsychologic, and imaging assessments. Magnetic resonance (MR) or computed tomographic (CT) imaging is recommended for the routine evaluation of AD. Coronal MR images can be useful to document or quantify atrophy of the hippocampus and entorhinal cortex, both of which occur early in the disease process. Both volumetric and subtraction MR techniques can be used to quantify and monitor dementia progression and rates of regional atrophy. MR measures are also increasingly being used to monitor treatment effects in clinical trials of cognitive enhancers and antidementia agents. Positron emission tomography (PET) and single photon emission CT offer value in the differential diagnosis of AD from other cortical and subcortical dementias and may also offer prognostic value. In addition, PET studies have demonstrated that subtle abnormalities may be apparent in the prodromal stages of AD and in subjects who carry susceptibility genes. PET ligands are in late-stage development for demonstration of amyloid plaques, and human studies have already begun. Functional MR-based memory challenge tests are in development as well.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“neuroradiological indexes of hippocampal atrophy [3], [4] and, consistent with the well-known role of the hippocampus in human declarative memory [5], episodic memory deficits [6], [7] are among the most powerful diagnostic indexes of AD from the very early phases, corresponding to the clinical condition of amnestic mild cognitive impairment (MCI).”
From Atrophy of presubiculum and subiculum is the earliest hippocampal anatomical marker of Alzheimer's disease (2015) · cites this paper as [4]
Citations
Cites
McKhann, G., Drachman, D., Folstein, M., Katzman, R., Price, D., & Stadlan, E. M. (1984) · Neurology · doi:10.1212/wnl.34.7.939 · Cited by 27,915
Neuropathological stageing of Alzheimer-related changes.
Braak, H., & Braak, E. (1991) · Acta Neuropathologica · doi:10.1007/bf00308809 · Cited by 16,123
Corder, E. H., Saunders, A. M., Strittmatter, W. J., Schmechel, D. E., Gaskell, P. C., Small, G. W., Roses, A. D., Haines, J. L., & Pericak-Vance, M. A. (1993) · Science · doi:10.1126/science.8346443 · Cited by 9,429
Mild Cognitive Impairment: Clinical Characterization and Outcome
Petersen, R. C., Smith, G. E., Waring, S. C., Ivnik, R. J., Tangalos, E. G., & Kokmen, E. (1999) · Archives of Neurology · doi:10.1001/archneur.56.3.303 · Cited by 8,980
Brain magnetic resonance imaging with contrast dependent on blood oxygenation.
Ogawa, S., Lee, T. M., Kay, A. R., & Tank, D. W. (1990) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.87.24.9868 · Cited by 6,483
Mirra, S. S., Heyman, A., McKeel, D., Sumi, S. M., Crain, B. J., Brownlee, L. M., Vogel, F. S., Hughes, J. P., Belle, G. V., Berg, L., et al. (1991) · Neurology · doi:10.1212/wnl.41.4.479 · Cited by 4,961
Román, G. C., Tatemichi, T. K., Erkinjuntti, T., Cummings, J. L., Masdeu, J. C., Garcia, J. H., Amaducci, L., Orgogozo, J.-M., Brun, A., Hofman, A., et al. (1993) · Neurology · doi:10.1212/wnl.43.2.250 · Cited by 4,921
McKeith, I. G., Galasko, D., Kosaka, K., Perry, E. K., Dickson, D. W., Hansen, L. A., Salmon, D. P., Lowe, J., Mirra, S. S., Byrne, E. J., et al. (1996) · Neurology · doi:10.1212/wnl.47.5.1113 · Cited by 3,960
Neurofibrillary tangles but not senile plaques parallel duration and severity of Alzheimer's disease
Arriagada, P. V., Growdon, J. H., Hedley-Whyte, E. T., & Hyman, B. T. (1992) · Neurology · doi:10.1212/wnl.42.3.631 · Cited by 2,668
Diffusion tensor MR imaging of the human brain
Pierpaoli, C., Jezzard, P., Basser, P. J., Barnett, A., & Di Chiro, G. (1996) · Radiology · doi:10.1148/radiology.201.3.8939209 · Cited by 2,664
Research works printed but not linked: 7
- Jellinger K.Morphology of Alzheimer disease and related disorders.In: Maurer K, Riederer P, Beckmann H, eds.Alzheimer disease: epidemiology, neuropathology and clinics.New York, NY: Springer-Verlag, 1990; 61-77.
- Adams RD, Victor M, Ropper A.Adams & Victor’s principles of neurology6th ed. New York, NY: McGraw-Hill, 1996; 121.
- Petersen RC.Mild cognitive impairment: transition between aging and Alzheimer’s disease.Neurologia2000; 15:93-101.
- Bradley WG.Normal pressure hydrocephalus: new concepts on etiology and diagnosis.AJNR Am J Neuroradiol2000; 21:1586-1590.
- 10.1073/pnas.95.3.906 · DOI
- Corkin S, Kennedy AM, Bucci J, et al.Relation between recognition performance and fMRI data in Alzheimer’s disease and older normal subjects.Soc Neuro1997; 23:193-195.
- George AE, Cha S.What role does functional MR imaging play in the diagnosis or prediction of future-onset Alzheimer’s disease?AJNR Am J Neuroradiol2001; 22:1017-1018.
Cited by
Sorted by citations
EEG dynamics in patients with Alzheimer's disease
Jeong, J. (2004) · Clinical Neurophysiology · doi:10.1016/j.clinph.2004.01.001 · Cited by 1,400
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
VoxResNet: Deep voxelwise residual networks for brain segmentation from 3D MR images
Chen, H., Dou, Q., Yu, L., Qin, J., & Heng, P. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.04.041 · Cited by 781
Johnson, N. A., Jahng, G., Weiner, M. W., Miller, B. L., Chui, H. C., Jagust, W. J., Gorno‐Tempini, M. L., & Schuff, N. W. (2005) · Radiology · doi:10.1148/radiol.2343040197 · Cited by 596
Diffusion tensor imaging of cingulum fibers in mild cognitive impairment and Alzheimer disease
Zhang, Y., Schuff, N. W., Jahng, G., Bayne, W., Mori, S., Schad, L. R., Mueller, S. G., Du, A., Kramer, J. H., Yaffe, K. S., et al. (2007) · Neurology · doi:10.1212/01.wnl.0000250326.77323.01 · Cited by 513
Metadata
- Authors
- Petrella, J. R., Coleman, R. E., & Doraiswamy, P. M.
- Affiliations
- Duke Medical Center (US)
- Venue
- Radiology
- Published
- 2003-02
- Volume
- 226
- Issue
- 2
- Pages
- 315-336
- ISSN
- 0033-8419 (ISSN-L)
- 1527-1315
- OpenAlex
- W2144803285
- Cited by
- 427
- References
- 145
- Citations by year
- 2026: 1 · 2025: 10 · 2024: 11 · 2023: 13 · 2022: 12 · 2021: 12 · 2020: 46 · 2019: 13 · 2018: 24 · 2017: 9 · 2016: 13 · 2015: 16 · 2014: 18 · 2013: 23 · 2012: 27
- FWCI
- 3.16
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Radiology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institute on Aging (R01AG019728)
- 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 › Radiology, Nuclear Medicine and Imaging › Medical Imaging Techniques and Applications
- Keywords
- Alzheimer's disease, early diagnosis, neuroimaging, hippocampal atrophy, entorhinal cortex atrophy, volumetric MRI, positron emission tomography, single-photon emission CT, differential diagnosis of dementia, prodromal Alzheimer's disease, treatment monitoring, dementia progression
- MeSH terms
- Alzheimer Disease, Diagnosis, Differential, Diagnostic Imaging, Humans, Magnetic Resonance Imaging, Predictive Value of Tests, Tomography, Emission-Computed, Tomography, X-Ray Computed, Tomography, Emission-Computed, Single-Photon
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
