Magnetic resonance imaging of fixed <i>post mortem</i> brains reliably reflects subcortical vascular pathology of frontal, parietal and occipital white matter
Bibliographic record
Abstract
AIMS: Subcortical vascular pathology of the white and deep grey matter (WM and DGM) is associated with cognitive impairment. Routine neuropathological assessment of subcortical vascular pathology is based on semiquantitative scoring of characteristic lesions in a limited number of histological slides from selected WM and DGM areas. Clinically, WM and DGM lesions are visualized as hyper-intensities on magnetic resonance imaging (MRI). The aim of this study was to evaluate the feasibility of MRI on fixed post mortem brain hemispheres to complement routine neuropathological assessment of subcortical vascular pathology. METHODS: We assessed subcortical vascular pathology in 40 post mortem brain hemispheres from demented (n = 26) and nondemented (n = 14) individuals (mean age 83.2 ± 14.8 years; 62.5% female) using (i) routine histological assessment; (ii) extensive histological assessment of the entire hemisphere at 7-mm intervals; and (iii) full T2-weighted MRI performed on fixed post mortem brain hemispheres. RESULTS: In both WM and DGM routine histological scores for subcortical vascular pathology were significantly lower (P < 0.01) than the corresponding scores obtained by extensive histological assessment. In contrast, no significant differences were seen between scores obtained by MRI and extensive histological assessment in frontal, parietal and occipital lobes while MRI scores were significantly lower in the temporal WM and DGM (P < 0.01). CONCLUSIONS: The results of our study indicate that routine histological assessment underrates subcortical vascular pathology and we conclude that MRI could be used in addition to complement neuropathological post mortem assessment of subcortical vascular pathology of the WM.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".