Radiomic assessment of the progression of acoustic neuroma after gamma knife stereotactic radiosurgery
Bibliographic record
Abstract
Introduction: The aim of this study was to determine whether radiomic features measured at baseline in Magnetic Resonance images (MRI) of acoustic neuromas (AN) can predict Gamma Knife (GK) treatment outcome.Methods: The study was conducted on pre- and post-GK MRI-T2 scans of 32 patients with AN who underwent stereotactic radiosurgery (SRS) for 12 Gy dose. Radiomic features extracted include Intensity, Fractals, Laplacian of Gaussian and textural Co-Occurrence, Run-length (RL), Size Zone, and Neighborhood Gray-Tone Difference matrices (NGTDM) features. Subjects were classified as treatment failures (TF) if tumor volume increased > 10%. Pre- and post-SRS audiology reports were utilized in hearing evaluation.Results: Fifteen subjects (47%) qualified as TFs. In univariate receiver operating characteristic (ROC) analysis, two radiomicfeatures, complexity in NGTDM and run percentage in RL, displayed areas under curves of > 0.65.Conclusion: This initial radiomic study establishes features that illustrates the prognostic ability of the SRS treatment in acousticneuroma. Hearing preservation was achieved in a majority of acoustic neuroma patients treated in Gamma Knife.
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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 | 0.000 |
| 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".