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Alzheimer disease: quantitative structural neuroimaging for detection and prediction of clinical and structural changes in mild cognitive impairment
McEvoy LK, Fennema-Notestine C, Roddey JC, Hagler DJ, Holland D, Karow DS, Pung CJ, Brewer JB et al.. Radiology, 2009-02-06
Topic: Amyloid, tau and blood-test diagnosis
Purpose To use structural magnetic resonance (MR) images to identify a pattern of regional atrophy characteristic of mild Alzheimer disease (AD) and to investigate whether presence of this pattern prospectively can aid prediction of 1-year clinical decline and increased structural loss in mild cognitive impairment (MCI). Materials and methods The study was conducted with institutional review board approval and compliance with HIPAA regulations. Written informed consent was obtained from each participant. High-throughput volumetric segmentation and cortical surface reconstruction methods were applied to MR images from 84 subjects with mild AD, 175 with MCI, and 139 healthy control (HC) subjects. Stepwise linear discriminant analysis was used to identify regions that best can aid discrimination of HC subjects from subjects with AD. A classifier trained on data from HC subjects and those with AD was applied to data from subjects with MCI to determine whether presence of phenotypic AD atrophy at baseline was predictive of clinical decline and structural loss. Results Atrophy in mesial and lateral temporal, isthmus cingulate, and orbitofrontal areas aided discrimination of HC subjects from subjects with AD, with fully cross-validated sensitivity of 83% and specificity of 93%. Subjects with MCI who had phenotypic AD atrophy showed significantly greater 1-year clinical decline and structural loss than those who did not and were more likely to have progression to probable AD (annual progression rate of 29% for subjects with MCI who had AD atrophy vs 8% for those who did not). Conclusion Semiautomated, individually specific quantitative MR imaging methods can be used to identify a pattern of regional atrophy in MCI that is predictive of clinical decline. Such information may aid in prediction of patient prognosis and increase the efficiency of clinical trials.
Key findings
- Results Atrophy in mesial and lateral temporal, isthmus cingulate, and orbitofrontal areas aided discrimination of HC subjects from subjects with AD, with fully cross-validated sensitivity of 83% and specificity of 93%.
- Subjects with MCI who had phenotypic AD atrophy showed significantly greater 1-year clinical decline and structural loss than those who did not and were more likely to have progression to probable AD (annual progression rate of 29% for subjects with MCI who had AD atrophy vs 8% for those who did not).
Why it matters
A pattern of brain atrophy measured on MRI distinguished people with mild Alzheimer's disease from healthy controls with 83% sensitivity and 93% specificity. People with mild cognitive impairment who had this atrophy pattern showed greater one-year decline and were more likely to progress to probable Alzheimer's disease (29% per year versus 8%).
Study details
- Participants84
- Evidence strengthLow
How this study scored 53/100
Published in a peer-reviewed journal. Scored zero for study design, effect reported and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Radiology) |
| Journal's citation record | 3 / 4 | Radiology: journal h-index 431 (OpenAlex, 2026-10-29) |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 1 / 5 | 2009 — within 20 year(s) of the newest study here |
| Sample size | 1 / 4 | 84 participants |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 3 / 3 | Studied in people (participant count stated) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 6 / 7 | Cited 332 times (OpenAlex, 2026-10-10) |
| Citations per year | 3 / 5 | 17.5 citations a year over 19 year(s) since 2009 |
| Impact for its field and year | 5 / 6 | Cited 22.2× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 3 / 6 | Cited by 28 other studies in this library |
| Still being cited | 2 / 4 | Cited 32 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 4 / 4 | Last-listed author Anders Martin Dale: h-index 185 (OpenAlex, whole career) |
| Institution's track record | 2 / 3 | University of California San Diego: institution h-index 1,852 (OpenAlex) |
| Multi-centre collaboration | 0 / 3 | OpenAlex lists 1 institution(s) in 1 country — scores zero (affiliation lists can be incomplete) |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 19201945) |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Total | 53 / 100 | — |
What each of these 20 components measures, and what this score is not →
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APA 7th
McEvoy, L. K., Fennema-Notestine, C., Roddey, J. C., Hagler, D. J., Holland, D., Karow, D. S., et al. (2009). Alzheimer disease: quantitative structural neuroimaging for detection and prediction of clinical and structural changes in mild cognitive impairment. Radiology. https://doi.org/10.1148/radiol.2511080924
Vancouver
McEvoy LK, Fennema-Notestine C, Roddey JC, Hagler DJ, Holland D, Karow DS, et al. Alzheimer disease: quantitative structural neuroimaging for detection and prediction of clinical and structural changes in mild cognitive impairment. Radiology. 2009. doi:10.1148/radiol.2511080924. PMID: 19201945.
BibTeX
@article{mcevoy2009-19201945,
author = {McEvoy, L. K. and Fennema-Notestine, C. and Roddey, J. C. and Hagler, D. J. and Holland, D. and Karow, D. S. and Pung, C. J. and Brewer, J. B. and others},
title = {{Alzheimer disease: quantitative structural neuroimaging for detection and prediction of clinical and structural changes in mild cognitive impairment}},
journal = {Radiology},
year = {2009},
doi = {10.1148/radiol.2511080924},
pmid = {19201945},
url = {https://doi.org/10.1148/radiol.2511080924}
}
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