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A direct morphometric comparison of five labeling protocols for multi-atlas driven automatic segmentation of the hippocampus in Alzheimer's disease
Nestor SM, Gibson E, Gao FQ, Kiss A, Black SE, Alzheimer's Disease Neuroimaging Initiative.. NeuroImage, 2012-11-07
Topic: Amyloid, tau and blood-test diagnosis
Hippocampal volumetry derived from structural MRI is increasingly used to delineate regions of interest for functional measurements, assess efficacy in therapeutic trials of Alzheimer's disease (AD) and has been endorsed by the new AD diagnostic guidelines as a radiological marker of disease progression. Unfortunately, morphological heterogeneity in AD can prevent accurate demarcation of the hippocampus. Recent developments in automated volumetry commonly use multi-template fusion driven by expert manual labels, enabling highly accurate and reproducible segmentation in disease and healthy subjects.
Key findings
- Unfortunately, morphological heterogeneity in AD can prevent accurate demarcation of the hippocampus.
- Recent developments in automated volumetry commonly use multi-template fusion driven by expert manual labels, enabling highly accurate and reproducible segmentation in disease and healthy subjects.
- However, there are several protocols to define the hippocampus anatomically in vivo, and the method used to generate atlases may impact automatic accuracy and sensitivity - particularly in pathologically heterogeneous samples.
- Here we report a fully automated segmentation technique that provides a robust platform to directly evaluate both technical and biomarker performance in AD among anatomically unique labeling protocols.
Why it matters
This study compared five different labeling protocols for automatic segmentation of the hippocampus in Alzheimer's disease. It is about improving brain imaging measurement, not about treating, curing, or preventing the disease.
Study details
- Study designlongitudinal study
- Evidence strengthModerate
How this study scored 53/100
Published in a peer-reviewed journal, and it is a longitudinal study following the same people over time. Scored zero for 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 (NeuroImage) |
| Journal's citation record | 4 / 4 | NeuroImage: journal h-index 523 (OpenAlex, 2026-10-29) |
| Study design | 7 / 12 | A longitudinal study following the same people over time |
| Strength of evidence | 3 / 5 | Rated “moderate” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 1 / 5 | 2013 — within 20 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 | 4 / 7 | Cited 60 times (OpenAlex, 2026-10-10) |
| Citations per year | 2 / 5 | 4.0 citations a year over 15 year(s) since 2013 |
| Impact for its field and year | 3 / 6 | Cited 5.5× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 1 / 6 | Cited by 2 other studies in this library |
| Still being cited | 1 / 4 | Cited 4 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 4 / 4 | Last-listed author Sandra E. Black: h-index 132 (OpenAlex, whole career) |
| Institution's track record | 2 / 3 | University of Toronto: institution h-index 1,923 (OpenAlex) |
| Multi-centre collaboration | 2 / 3 | OpenAlex lists 4 institution(s) in 1 country |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 23142652) |
| 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 →
Read the original
- DOI: 10.1016/j.neuroimage.2012.10.081
- PubMed: 23142652
- 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. Check the citation against the original before you use it.
APA 7th
Nestor, S. M., Gibson, E., Gao, F. Q., Kiss, A., Black, S. E., & Alzheimer's Disease Neuroimaging Initiative. (2013). A direct morphometric comparison of five labeling protocols for multi-atlas driven automatic segmentation of the hippocampus in Alzheimer's disease. NeuroImage. https://doi.org/10.1016/j.neuroimage.2012.10.081
Vancouver
Nestor SM, Gibson E, Gao FQ, Kiss A, Black SE, Alzheimer's Disease Neuroimaging Initiative. A direct morphometric comparison of five labeling protocols for multi-atlas driven automatic segmentation of the hippocampus in Alzheimer's disease. NeuroImage. 2013. doi:10.1016/j.neuroimage.2012.10.081. PMID: 23142652.
BibTeX
@article{nestor2013-23142652,
author = {Nestor, S. M. and Gibson, E. and Gao, F. Q. and Kiss, A. and Black, S. E. and {Alzheimer's Disease Neuroimaging Initiative}},
title = {{A direct morphometric comparison of five labeling protocols for multi-atlas driven automatic segmentation of the hippocampus in Alzheimer's disease}},
journal = {NeuroImage},
year = {2013},
doi = {10.1016/j.neuroimage.2012.10.081},
pmid = {23142652},
url = {https://doi.org/10.1016/j.neuroimage.2012.10.081}
}
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