Baseline Brain Volumes Predict Future Brain Atrophy in Mild Cognitive Impairment: A Tensor-based Morphometry Study of the Alzheimer Continuum
Bibliographic record
Abstract
OBJECTIVE: Prognostic evaluation of patients with mild cognitive impairment (MCI) is of great importance, and magnetic resonance imaging, as a readily available modality, can play a pivotal role in this field. METHODS: Using the Alzheimer Disease Neuroimaging Initiative database, we conducted a retrospective longitudinal study of the associations between volumetric brain magnetic resonance imaging and cognitive composite scores in all domains (memory, executive function, language, and visuospatial) with annual whole-brain atrophy based on tensor-based morphometry (TBM) scores among patients with MCI and healthy controls (HCs). The Reliable Change Index was further used to categorize patients into 2 groups including (1) patients with meaningful 1-year reliable cognitive changes [reliable change (RC) group] and (2) patients without (non-RC). RESULTS: One hundred thirty-seven patients with MCI and 132 HCs were enrolled. The 2 groups showed no significant differences in age, sex, and apolipoprotein E4 expression ( P > 0.05). Based on the TBM score, patients with MCI had more significant 1-year brain volume loss than HCs ( P < 0.001). After multiple comparison corrections, the 1-year TBM atrophy score was positively correlated with baseline whole brain ( P = 0.03), hippocampus ( P < 0.0001), entorhinal ( P < 0.0001), and middle temporal ( P < 0.0001) volumes among MCI patients, indicating that lower volumes in these regions were associated with greater 1-year atrophy rates. Regression analyses showed a positive correlation between baseline and 1-year memory composite scores and annual brain atrophy rate in MCI patients ( P = 0.01, 0.04), demonstrating that lower cognitive scores were associated with a greater annual atrophy rate. However, the correlations no longer held significance after correction for multiple comparison ( P = 0.05, 0.17). MCI participants with RCs in language composite scores initially had significantly greater brain atrophy than those without ( P = 0.03, corrected P = 0.06). However, TBM scores showed no significant differences between RC and non-RC groups for other composite scores ( P > 0.05). CONCLUSIONS: Lower baseline volumes in multiple brain regions of MCI are associated with greater annual brain volume loss based on TBM, suggesting TBM as a potential imaging marker for conventional volumetric studies in MCI. Further research is needed to explore the link between cognitive scores and the application of Reliable Change Index in TBM imaging across the Alzheimer disease spectrum.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".