Home › Research › Long-term cohort studies
DIVE: A spatiotemporal progression model of brain pathology in neurodegenerative disorders
Marinescu RV, Eshaghi A, Lorenzi M, Young AL, Oxtoby NP, Garbarino S, Crutch SJ, Alexander DC et al.. NeuroImage, 2019-03-04
Topic: Brain proteins, microglia and lab models
Current models of progression in neurodegenerative diseases use neuroimaging measures that are averaged across pre-defined regions of interest (ROIs). Such models are unable to recover fine details of atrophy patterns; they tend to impose an assumption of strong spatial correlation within each ROI and no correlation among ROIs. Such assumptions may be violated by the influence of underlying brain network connectivity on pathology propagation - a strong hypothesis e.g. in Alzheimer's Disease.
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
APA 7th
Marinescu, R. V., Eshaghi, A., Lorenzi, M., Young, A. L., Oxtoby, N. P., Garbarino, S., et al. (2019). DIVE: A spatiotemporal progression model of brain pathology in neurodegenerative disorders. NeuroImage. https://doi.org/10.1016/j.neuroimage.2019.02.053
Vancouver
Marinescu RV, Eshaghi A, Lorenzi M, Young AL, Oxtoby NP, Garbarino S, et al. DIVE: A spatiotemporal progression model of brain pathology in neurodegenerative disorders. NeuroImage. 2019. doi:10.1016/j.neuroimage.2019.02.053. PMID: 30844504.
BibTeX
@article{marinescu2019-30844504,
author = {Marinescu, R. V. and Eshaghi, A. and Lorenzi, M. and Young, A. L. and Oxtoby, N. P. and Garbarino, S. and Crutch, S. J. and Alexander, D. C. and others},
title = {{DIVE: A spatiotemporal progression model of brain pathology in neurodegenerative disorders}},
journal = {NeuroImage},
year = {2019},
doi = {10.1016/j.neuroimage.2019.02.053},
pmid = {30844504},
url = {https://doi.org/10.1016/j.neuroimage.2019.02.053}
}
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
- Such models are unable to recover fine details of atrophy patterns; they tend to impose an assumption of strong spatial correlation within each ROI and no correlation among ROIs.
- Such assumptions may be violated by the influence of underlying brain network connectivity on pathology propagation - a strong hypothesis e.g. in Alzheimer's Disease.
- Here we present DIVE: Data-driven Inference of Vertexwise Evolution.
- DIVE is an image-based disease progression model with single-vertex resolution, designed to reconstruct long-term patterns of brain pathology from short-term longitudinal data sets.
Why it matters
This is a computer modeling study that proposes a new way to map how brain shrinkage spreads over time in neurodegenerative diseases like Alzheimer's. It is a technical tool for research and does not test any treatment, cure, or prevention in patients.
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 | 2 / 5 | 2019 — within 10 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 61 times (OpenAlex, 2026-10-10) |
| Citations per year | 2 / 5 | 6.8 citations a year over 9 year(s) since 2019 |
| Impact for its field and year | 3 / 6 | Cited 7.4× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 1 / 6 | Cited by 1 other studies in this library |
| Still being cited | 1 / 4 | Cited 13 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 3 / 4 | Last-listed author Daniel C. Alexander: h-index 93 (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 30844504) |
| 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.2019.02.053
- PubMed: 30844504
- Original source →
- Free full text: arXiv (Cornell University) →
Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).
Studies this one cites
Referenced by this study and also in the alzhub library, so you can read them here.
Later studies that cite this one
1 study in the alzhub library lists this one in its references.
Related studies in Long-term cohort studies
Also tagged “vessel”
900 studies in the library carry the topic tag “vessel”; these are this study's neighbours in a fixed, alphabetical-by-hash tour of them, not the closest in content. All 900 tagged studies.