Home › Research › Digital health tools
Automated hippocampal shape analysis predicts the onset of dementia in mild cognitive impairment
Costafreda SG, Dinov ID, Tu Z, Shi Y, Liu CY, Kloszewska I, Mecocci P, Soininen H et al.. NeuroImage, 2011-01-25
Topic: Risk, prevention and care in population studies
Plain-language summary
The hippocampus is involved at the onset of the neuropathological pathways leading to Alzheimer's disease (AD). Individuals with mild cognitive impairment (MCI) are at increased risk of AD. Hippocampal volume has been shown to predict which MCI subjects will convert to AD. Our aim in the present study was to produce a fully automated prognostic procedure, scalable to high throughput clinical and research applications, for the prediction of MCI conversion to AD using 3D hippocampal morphology. We used an automated analysis for the extraction and mapping of the hippocampus from structural magnetic resonance scans to extract 3D hippocampal shape morphology, and we then applied machine learning classification to predict conversion from MCI to AD. We investigated the accuracy of prediction in 103 MCI subjects (mean age 74.1 years) from the longitudinal AddNeuroMed study. Our model correctly predicted MCI conversion to dementia within a year at an accuracy of 80% (sensitivity 77%, specificity 80%), a performance which is competitive with previous predictive models dependent on manual measurements. Categorization of MCI subjects based on hippocampal morphology revealed more rapid cognitive deterioration in MMSE scores (p<0.01) and CERAD verbal memory (p<0.01) in those subjects who were predicted to develop dementia relative to those predicted to remain stable. The pattern of atrophy associated with increased risk of conversion demonstrated initial degeneration in the anterior part of the cornus ammonis 1 (CA1) hippocampal subregion. We conclude that automated shape analysis generates sensitive measurements of early neurodegeneration which predates the onset of dementia and thus provides a prognostic biomarker for conversion of MCI to AD.
What this study adds
Evidence grade: Moderate
This is a follow-up (cohort) study. An automated analysis of hippocampus shape predicted which people with mild cognitive impairment would develop dementia within a year, with about 80% accuracy. This is a prediction tool for identifying who may convert, not a treatment or cure.
Taken from this record’s own fields, not from reading the paper. The grade is assigned from the abstract’s wording; what that means.
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
APA 7th
Costafreda, S. G., Dinov, I. D., Tu, Z., Shi, Y., Liu, C. Y., Kloszewska, I., et al. (2011). Automated hippocampal shape analysis predicts the onset of dementia in mild cognitive impairment. NeuroImage. https://doi.org/10.1016/j.neuroimage.2011.01.050
Vancouver
Costafreda SG, Dinov ID, Tu Z, Shi Y, Liu CY, Kloszewska I, et al. Automated hippocampal shape analysis predicts the onset of dementia in mild cognitive impairment. NeuroImage. 2011. doi:10.1016/j.neuroimage.2011.01.050. PMID: 21272654.
BibTeX
@article{costafreda2011-21272654,
author = {Costafreda, S. G. and Dinov, I. D. and Tu, Z. and Shi, Y. and Liu, C. Y. and Kloszewska, I. and Mecocci, P. and Soininen, H. and others},
title = {{Automated hippocampal shape analysis predicts the onset of dementia in mild cognitive impairment}},
journal = {NeuroImage},
year = {2011},
doi = {10.1016/j.neuroimage.2011.01.050},
pmid = {21272654},
url = {https://doi.org/10.1016/j.neuroimage.2011.01.050}
}
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.
Key findings
- Individuals with mild cognitive impairment (MCI) are at increased risk of AD.
- Categorization of MCI subjects based on hippocampal morphology revealed more rapid cognitive deterioration in MMSE scores (p<0.01) and CERAD verbal memory (p<0.01) in those subjects who were predicted to develop dementia relative to those predicted to remain stable.
- The pattern of atrophy associated with increased risk of conversion demonstrated initial degeneration in the anterior part of the cornus ammonis 1 (CA1) hippocampal subregion.
- We conclude that automated shape analysis generates sensitive measurements of early neurodegeneration which predates the onset of dementia and thus provides a prognostic biomarker for conversion of MCI to AD.
Why it matters
An automated analysis of hippocampus shape predicted which people with mild cognitive impairment would develop dementia within a year, with about 80% accuracy. This is a prediction tool for identifying who may convert, not a treatment or cure.
New to this subject? Start with our plain-English guide: Digital health →
Study details
- Study designlongitudinal study
- Evidence strengthModerate
How this study scored 60/100
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 randomized / 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 | 2011 — 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) |
| Randomized / blinded | 0 / 2 | No randomization or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 5 / 7 | Cited 218 times (OpenAlex, 2026-10-10) |
| Citations per year | 3 / 5 | 12.8 citations a year over 17 year(s) since 2011 |
| Impact for its field and year | 4 / 6 | Cited 11.5× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 3 / 6 | Cited by 14 other studies in this library |
| Still being cited | 2 / 4 | Cited 22 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 4 / 4 | Last-listed author Andrew D. Simmons: h-index 102 (OpenAlex, whole career) |
| Institution's track record | 2 / 3 | Inserm: institution h-index 1,988 (OpenAlex) |
| Multicenter collaboration | 3 / 3 | OpenAlex lists 11 institution(s) in 8 countries |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 21272654) |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Total | 60 / 100 | — |
What each of these 20 components measures, and what this score is not →
Read the original
- DOI: 10.1016/j.neuroimage.2011.01.050
- PubMed: 21272654
- 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).
Related
Studies in the library that share something with this one. The line above each title says what.
Studies this one cites
Referenced by this study and also in the alzhub library, so you can read them here. Showing 12 of 30.
Later studies that cite this one
14 studies in the alzhub library list this one in their references. Showing the 8 highest-scoring.
Related studies in Digital health tools from nearby years
Also tagged “disorder”
492 studies in the library carry the topic tag “disorder”; these are this study's neighbours in a fixed, alphabetical-by-hash tour of them, not the closest in content. All 492 tagged studies.