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Automated MRI-based classification of primary progressive aphasia variants
Wilson SM, Ogar JM, Laluz V, Growdon M, Jang J, Glenn S, Miller BL, Weiner MW et al.. NeuroImage, 2009-06-06
Topic: Amyloid, tau and blood-test diagnosis
Degeneration of language regions in the dominant hemisphere can result in primary progressive aphasia (PPA), a clinical syndrome characterized by progressive deficits in speech and/or language function. Recent studies have identified three variants of PPA: progressive non-fluent aphasia (PNFA), semantic dementia (SD) and logopenic progressive aphasia (LPA). Each variant is associated with characteristic linguistic features, distinct patterns of brain atrophy, and different likelihoods of particular underlying pathogenic processes, which makes correct differential diagnosis highly clinically relevant. Evaluation of linguistic behavior can be challenging for non-specialists, and neuroimaging findings in single subjects are often difficult to evaluate by eye. We investigated the utility of automated structural MR image analysis to discriminate PPA variants (N=86) from each other and from normal controls (N=115). T1 images were preprocessed to obtain modulated grey matter (GM) images. Feature selection was performed with principal components analysis (PCA) on GM images as well as images of lateralized atrophy. PC coefficients were classified with linear support vector machines, and a cross-validation scheme was used to obtain accuracy rates for generalization to novel cases. The overall mean accuracy in discriminating between pairs of groups was 92.2%. For one pair of groups, PNFA and SD, we also investigated the utility of including several linguistic variables as features. Models with both imaging and linguistic features performed better than models with only imaging or only linguistic features. These results suggest that automated methods could assist in the differential diagnosis of PPA variants, enabling therapies to be targeted to likely underlying etiologies.
Key findings
- Degeneration of language regions in the dominant hemisphere can result in primary progressive aphasia (PPA), a clinical syndrome characterized by progressive deficits in speech and/or language function.
- Each variant is associated with characteristic linguistic features, distinct patterns of brain atrophy, and different likelihoods of particular underlying pathogenic processes, which makes correct differential diagnosis highly clinically relevant.
- The overall mean accuracy in discriminating between pairs of groups was 92.2%.
- These results suggest that automated methods could assist in the differential diagnosis of PPA variants, enabling therapies to be targeted to likely underlying etiologies.
Why it matters
This study used automated MRI analysis to tell apart variants of primary progressive aphasia and normal controls with high accuracy. It is a diagnostic classification study and does not test any treatment, cure, or prevention for Alzheimer's disease.
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Study details
- Participants86
- Effect size92.2%
- Evidence strengthLow
How this study scored 49/100
Published in a peer-reviewed journal. Scored zero for study design and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (NeuroImage) |
| Journal's citation record | 4 / 4 | NeuroImage: journal h-index 523 (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 | 86 participants |
| Effect reported | 2 / 3 | Effect reported as a number, without an interval or test |
| 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 | 4 / 7 | Cited 91 times (OpenAlex, 2026-10-10) |
| Citations per year | 2 / 5 | 4.8 citations a year over 19 year(s) since 2009 |
| Impact for its field and year | 3 / 6 | Cited 5.6× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 2 / 6 | Cited by 6 other studies in this library |
| Still being cited | 1 / 4 | Cited 11 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 3 / 4 | Last-listed author Maria Luisa Gorno‐Tempini: h-index 92 (OpenAlex, whole career) |
| Institution's track record | 2 / 3 | University of California, San Francisco: institution h-index 1,915 (OpenAlex) |
| Multi-centre collaboration | 1 / 3 | OpenAlex lists 2 institution(s) in 1 country |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 19501654) |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Total | 49 / 100 | — |
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Read the original
- DOI: 10.1016/j.neuroimage.2009.05.085
- PubMed: 19501654
- Original source →
- Free full text: PubMed Central →
Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. The record's author list ends in “et al.”, so not every author is named. Check the citation against the original before you use it.
APA 7th
Wilson, S. M., Ogar, J. M., Laluz, V., Growdon, M., Jang, J., Glenn, S., et al. (2009). Automated MRI-based classification of primary progressive aphasia variants. NeuroImage. https://doi.org/10.1016/j.neuroimage.2009.05.085
Vancouver
Wilson SM, Ogar JM, Laluz V, Growdon M, Jang J, Glenn S, et al. Automated MRI-based classification of primary progressive aphasia variants. NeuroImage. 2009. doi:10.1016/j.neuroimage.2009.05.085. PMID: 19501654.
BibTeX
@article{wilson2009-19501654,
author = {Wilson, S. M. and Ogar, J. M. and Laluz, V. and Growdon, M. and Jang, J. and Glenn, S. and Miller, B. L. and Weiner, M. W. and others},
title = {{Automated MRI-based classification of primary progressive aphasia variants}},
journal = {NeuroImage},
year = {2009},
doi = {10.1016/j.neuroimage.2009.05.085},
pmid = {19501654},
url = {https://doi.org/10.1016/j.neuroimage.2009.05.085}
}
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