Voxel-wise radiogenomic mapping of tumor location with key molecular alterations in patients with glioma
Bibliographic record
Abstract
Background: This study aims to evaluate the impact of tumor location on key molecular alterations on a single voxel level in patients with newly diagnosed glioma. Methods: A consecutive series of n = 237 patients with newly diagnosed glioblastoma and n = 131 patients with lower-grade glioma was analyzed. Volumetric tumor segmentation was performed on preoperative MRI with a semi-automated approach and images were registered to the standard Montreal Neurological Institute 152 space. Using a voxel-based lesion symptom mapping (VLSM) analysis, we identified specific brain regions that were associated with tumor-specific molecular alterations. We assessed a predefined set of n = 17 molecular characteristics in the glioblastoma cohort and n = 2 molecular characteristics in the lower-grade glioma cohort. Permutation adjustment (n = 1000 iterations) was used to correct for multiple testing, and voxel t-values that were greater than the t-value in >95% of the permutations were retained in the VLSM results (α = 0.05, power > 0.8). Results: Tumor location predilection for isocitrate dehydrogenase (IDH) mutant tumors was found in both glioblastoma and lower-grade glioma cohorts, each showing a concordant predominance in the frontal lobe adjacent to the rostral extension of the lateral ventricles (permutation-adjusted P = 0.021 for the glioblastoma and 0.013 for the lower-grade glioma cohort). Apart from that, the VLSM analysis did not reveal a significant association of the tumor location with any other key molecular alteration in both cohorts (permutation-adjusted P > 0.05 each). Conclusion: Our study highlights the unique properties of IDH mutations and underpins the hypothesis that the rostral extension of the lateral ventricles is a potential location for the cell of origin in IDH-mutant gliomas.
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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) | 0.000 | 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 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".