Signal Intensities in Preoperative MRI Do Not Reflect Proliferative Activity in Meningioma
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Bibliographic record
Abstract
BACKGROUND: Identification of high-grade meningiomas in preoperative magnetic resonance imaging (MRI) is important for optimized surgical strategy and best possible resection. Numerous studies investigated subjectively determined morphological features as predictors of tumor biology in meningiomas. The aim of this study was to identify the predictive value of more reliable, quantitatively measured signal intensities in MRI for differentiation of high- and low-grade meningiomas and identification of meningiomas with high proliferation rates, respectively. PATIENTS AND METHODS: Sixty-six patients (56 World Health Organization [WHO] grade I, 9 WHO grade II, and 1 WHO grade I) were included in the study. Preoperative MRI signal intensities (fluid-attenuated inversion recovery [FLAIR], T1 precontrast, and T1 postcontrast as genuine and normalized values) were correlated with Ki-67 expression in tissue sections of resected meningiomas. Differences between the groups (analysis of variance) and Spearman rho correlation were computed using SPSS 22. RESULTS: Mean values of genuine signal intensities of meningiomas in FLAIR, T1 native, and T1 postcontrast were 323.9 ± 59, 332.8 ± 67.9, and 768.5 ± 165.3. Mean values of normalized (to the contralateral white matter) signal intensities of meningiomas in FLAIR, T1 native, and T1 postcontrast were 1.5 ± 0.3, 0.8 ± 0.1, and 1.9 ± 0.4. There was no significant correlation between MRI signal intensities and WHO grade or Ki-67 expression. Signal intensities did not differ significantly between WHO grade I and II/III meningiomas. Ki-67 expression was significantly increased in high-grade meningiomas compared with low-grade meningiomas (P < 0.01). Objectively measured values of MRI signal intensities (FLAIR, T1 precontrast, and T1 postcontrast enhancement) did not distinguish between high-grade and low-grade meningiomas. Furthermore, there was no association between MRI signal intensities and Ki-67 expression representing proliferative activity.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 it