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From Lesion to Decision: AI for ARIA Detection and Predictive Imaging in Alzheimer's Disease
Christodoulou RC, Papageorgiou PS, Sarquis MD, Rivera L, Morales Gonzalez C, Eller D, Rivera G, Petrou V et al.. Biomedicines, 2025-11-10
Topic: Amyloid, tau and blood-test diagnosis
The evidence is organized into six thematic domains: ARIA definitions, imaging challenges, foundations of AI in neuroimaging, detection tools, predictive frameworks, and future perspectives. AI offers promising avenues to standardize ARIA evaluation, improve lesion quantification, and enable individualized risk prediction. Progress will depend on multicenter datasets, shared frameworks, and prospective validation. Ultimately, AI-driven neuroimaging may transform how treatment-related complications are monitored in the era of anti-amyloid therapy.
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
APA 7th
Christodoulou, R. C., Papageorgiou, P. S., Sarquis, M. D., Rivera, L., Morales Gonzalez, C., Eller, D., et al. (2025). From Lesion to Decision: AI for ARIA Detection and Predictive Imaging in Alzheimer's Disease. Biomedicines. https://doi.org/10.3390/biomedicines13112739
Vancouver
Christodoulou RC, Papageorgiou PS, Sarquis MD, Rivera L, Morales Gonzalez C, Eller D, et al. From Lesion to Decision: AI for ARIA Detection and Predictive Imaging in Alzheimer's Disease. Biomedicines. 2025. doi:10.3390/biomedicines13112739. PMID: 41301832.
BibTeX
@article{christodoulou2025-41301832,
author = {Christodoulou, R. C. and Papageorgiou, P. S. and Sarquis, M. D. and Rivera, L. and Morales Gonzalez, C. and Eller, D. and Rivera, G. and Petrou, V. and others},
title = {{From Lesion to Decision: AI for ARIA Detection and Predictive Imaging in Alzheimer's Disease}},
journal = {Biomedicines},
year = {2025},
doi = {10.3390/biomedicines13112739},
pmid = {41301832},
url = {https://doi.org/10.3390/biomedicines13112739}
}
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Key findings
- The evidence is organized into six thematic domains: ARIA definitions, imaging challenges, foundations of AI in neuroimaging, detection tools, predictive frameworks, and future perspectives.
- AI offers promising avenues to standardize ARIA evaluation, improve lesion quantification, and enable individualized risk prediction.
- Progress will depend on multicenter datasets, shared frameworks, and prospective validation.
- Ultimately, AI-driven neuroimaging may transform how treatment-related complications are monitored in the era of anti-amyloid therapy.
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Study details
- Study designnarrative review
- Evidence strengthLow
How this study scored 45/100
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. We have no data on journal's citation record, times cited, citations per year, impact for its field and year, cited by studies here, still being cited, senior author's track record, institution's track record and multi-centre collaboration, so those were left out: it earned 26 of the 58 points we could judge it on, which is 45 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Biomedicines) |
| Journal's citation record | — / 4 | No journal record from OpenAlex — left out of this score |
| Study design | 0 / 12 | Design recorded as “narrative review”, which our rubric does not rank (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 | — / 7 | No citation count (not found in OpenAlex) — left out of this score |
| Citations per year | — / 5 | No citation count or no year — left out of this score |
| Impact for its field and year | — / 6 | No field-weighted citation impact (OpenAlex has none yet) — left out of this score |
| Cited by studies here | — / 6 | Not yet checked against this library's citation graph — left out of this score |
| Still being cited | — / 4 | No yearly citation counts — left out of this score |
| Senior author's track record | — / 4 | Senior author's record not available — left out of this score |
| Institution's track record | — / 3 | No institution listed in OpenAlex — left out of this score |
| Multi-centre collaboration | — / 3 | Institutions not listed — left out of this score |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 41301832) |
| Free to read | 2 / 2 | Free to read |
| Points | 26 / 58 | Scored on 11 of 20 parts. We have no data for the rest, so they are left out: 26 of the 58 points we could judge it on is 45 out of 100. |
| Total | 45 / 100 | — |
What each of these 20 components measures, and what this score is not →
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