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Longitudinal Analysis of Amyloid PET and Brain MRI for Predicting Conversion from Mild Cognitive Impairment to Alzheimer’s Disease: Findings from the ADNI Cohort
Do-Hoon Kim. Tomography, 2025-03-19
Topic: Amyloid, tau and blood-test diagnosis
< 0.001). Shape features demonstrated the highest predictive accuracy for conversion, with areas under the curve of 0.891 at baseline and 0.898 at 2 years. Percent change analyses revealed significant increases in brain atrophy; amyloid deposition changes showed a paradoxical decrease in converters. Additionally, strong associations were observed between longitudinal changes in shape features and neuropsychological test results. The integration of amyloid PET and MRI biomarkers enhances the prediction of AD progression in patients with MCI. These findings support the potential of combined imaging approaches for early diagnosis and targeted interventions in AD.
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
APA 7th
Kim, D.-H. (2025). Longitudinal Analysis of Amyloid PET and Brain MRI for Predicting Conversion from Mild Cognitive Impairment to Alzheimer’s Disease: Findings from the ADNI Cohort. Tomography. https://doi.org/10.3390/tomography11030037
Vancouver
Kim D.-H. Longitudinal Analysis of Amyloid PET and Brain MRI for Predicting Conversion from Mild Cognitive Impairment to Alzheimer’s Disease: Findings from the ADNI Cohort. Tomography. 2025. doi:10.3390/tomography11030037. PMID: 40137577.
BibTeX
@article{kim2025-40137577,
author = {Kim, Do-Hoon},
title = {{Longitudinal Analysis of Amyloid PET and Brain MRI for Predicting Conversion from Mild Cognitive Impairment to Alzheimer’s Disease: Findings from the ADNI Cohort}},
journal = {Tomography},
year = {2025},
doi = {10.3390/tomography11030037},
pmid = {40137577},
url = {https://doi.org/10.3390/tomography11030037}
}
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.
Key findings
- Shape features demonstrated the highest predictive accuracy for conversion, with areas under the curve of 0.891 at baseline and 0.898 at 2 years.
- Percent change analyses revealed significant increases in brain atrophy; amyloid deposition changes showed a paradoxical decrease in converters.
- Additionally, strong associations were observed between longitudinal changes in shape features and neuropsychological test results.
- The integration of amyloid PET and MRI biomarkers enhances the prediction of AD progression in patients with MCI.
- These findings support the potential of combined imaging approaches for early diagnosis and targeted interventions in AD.
Why it matters
This longitudinal ADNI study found that combining amyloid PET and MRI biomarkers, particularly shape features, predicted conversion from MCI to Alzheimer's disease with areas under the curve of 0.891 at baseline and 0.898 at 2 years. The findings support combined imaging for early diagnosis and targeted interventions, but the study itself does not test any treatment.
Study details
- Study designlongitudinal study
- Participants180
- Evidence strengthModerate
How this study scored 49/100
Published in a peer-reviewed journal, and it is a longitudinal study following the same people over time. Scored zero for effect reported and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Tomography) |
| Journal's citation record | 0 / 4 | Tomography: journal h-index 43 (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 | 4 / 5 | 2025 — within 3 year(s) of the newest study here |
| Sample size | 2 / 4 | 180 participants |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 3 / 3 | Studied in people (participant count stated) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 2 / 7 | Cited 5 times (OpenAlex, 2026-10-10) |
| Citations per year | 1 / 5 | 1.7 citations a year over 3 year(s) since 2025 |
| Impact for its field and year | 3 / 6 | Cited 3.2× 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 5 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 1 / 4 | Last-listed author Do-Hoon Kim: h-index 10 (OpenAlex, whole career) |
| Institution's track record | 0 / 3 | Daejeon Eulji Medical Center, Eulji University: institution h-index 114 (OpenAlex) |
| Multi-centre collaboration | 0 / 3 | OpenAlex lists 1 institution(s) in 1 country — scores zero (affiliation lists can be incomplete) |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 40137577) |
| Free to read | 2 / 2 | Free to read |
| Total | 49 / 100 | — |
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