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The diagnostic accuracy of CTseg segmentation software for dementia in a New Zealand memory service
Y Mukish M Yelanchezian, Cristian González-Prieto, Bede Oulaghan, Susan Yates, Catherine Morgan, Gillian Dobbie, Daniel H J Davis, Sarah J. Cullum. Journal of Alzheimer s Disease Reports, 2025-05-21
Topic: Risk, prevention and care in population studies
This study examines the accuracy of CTseg segmentation software to diagnose Alzheimer's disease dementia and other dementias using routine CT scans from a New Zealand memory service. Analyzing 168 scans (89 with dementia and 79 without dementia) the software segmented the brain to produce total brain volume and hippocampal volume. CTseg-derived total brain volume (sensitivity 72%, specificity 58%) and hippocampal volume (sensitivity 71%, specificity 62%) were reasonably effective at differentiating dementia from non-dementia at time of diagnosis. Our findings suggest that CTseg automated volumetric analysis has some potential to aid dementia diagnosis in real-world clinical settings.
Key findings
- Our findings suggest that CTseg automated volumetric analysis has some potential to aid dementia diagnosis in real-world clinical settings.
Why it matters
This study found that CTseg segmentation software using routine CT scans had reasonable but limited accuracy for differentiating dementia from non-dementia, with sensitivity around 71-72% and specificity around 58-62%. It suggests some potential to aid diagnosis in real-world settings and does not address treatment or cure.
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Study details
- Evidence strengthLow
How this study scored 34/100
Published in a peer-reviewed journal. Scored zero for study design, sample size, effect reported, studied in people and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Journal of Alzheimer s Disease Reports) |
| Journal's citation record | 0 / 4 | Journal of Alzheimer s Disease Reports: journal h-index 40 (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 | 4 / 5 | 2025 — within 3 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 1 / 7 | Cited 1 times (OpenAlex, 2026-10-10) |
| Citations per year | 0 / 5 | 0.3 citations a year over 3 year(s) since 2025 |
| Impact for its field and year | 1 / 6 | Cited 0.6× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 0 / 6 | No other study in this library cites it |
| Still being cited | 0 / 4 | Cited 1 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 2 / 4 | Last-listed author Sarah J. Cullum: h-index 25 (OpenAlex, whole career) |
| Institution's track record | 2 / 3 | University College London: institution h-index 2,029 (OpenAlex) |
| Multi-centre collaboration | 2 / 3 | OpenAlex lists 5 institution(s) in 2 countries |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 40406677) |
| Free to read | 2 / 2 | Free to read |
| Total | 34 / 100 | — |
What each of these 20 components measures, and what this score is not →
Read the original
- DOI: 10.1177/25424823251332448
- PubMed: 40406677
- Original source →
- Free full text: Journal of Alzheimer s Disease Reports →
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 names 8 authors; APA and Vancouver show the first six, BibTeX and the downloads carry all of them. Check the citation against the original before you use it.
APA 7th
Yelanchezian, Y. M. M., González-Prieto, C., Oulaghan, B., Yates, S., Morgan, C., Dobbie, G., et al. (2025). The diagnostic accuracy of CTseg segmentation software for dementia in a New Zealand memory service. Journal of Alzheimer s Disease Reports. https://doi.org/10.1177/25424823251332448
Vancouver
Yelanchezian YMM, González-Prieto C, Oulaghan B, Yates S, Morgan C, Dobbie G, et al. The diagnostic accuracy of CTseg segmentation software for dementia in a New Zealand memory service. Journal of Alzheimer s Disease Reports. 2025. doi:10.1177/25424823251332448. PMID: 40406677.
BibTeX
@article{yelanchezian2025-40406677,
author = {Yelanchezian, Y Mukish M and González-Prieto, Cristian and Oulaghan, Bede and Yates, Susan and Morgan, Catherine and Dobbie, Gillian and Davis, Daniel H J and Cullum, Sarah J.},
title = {{The diagnostic accuracy of CTseg segmentation software for dementia in a New Zealand memory service}},
journal = {Journal of Alzheimer s Disease Reports},
year = {2025},
doi = {10.1177/25424823251332448},
pmid = {40406677},
url = {https://doi.org/10.1177/25424823251332448}
}
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