Evaluating the neuromodulative effects of radiosurgery on the brain tissue
Bibliographic record
Abstract
Introduction: Stereotactic radiosurgery (SRS) has proven an effective tool for treatment of tumors, arterio-venous malformation, acoustic neuroma, and functional conditions, in which cell death is the desired treatment outcome. However, radiation-induced therapeutic effect in the remaining living cells in functional SRS is also suggested. Modulation of the neuronal activity without causing death requires knowledge of radiation dose tolerance at very small tissue volume. The aim of the presented study was to document the thresholds for late-onset cell death when high doses of radiation are delivered to small brain volumes. Methods: Six female Gottingen minipigs were used. At baseline, the MRI was acquired. Five animals received focal stereotactic radiosurgery in the left primary motor cortex and to the right cortical white matter, and one animal remained as unirradiated control. Follow-up MRI and PET scans were done at three weeks, three and six months after the irradiation, followed by analysis of the histological changes at 6 months post-radiation after euthanization and fixation. Results: We observed a dose dependent gradient of cellular reaction to the radiation and spreading inflammatory changes along the neural tracts in white matter. Necrotic changes in both MRI and histology were seen at 6 months post-radiation. The threshold of radio-destructive lesions was 100 Gy in cortical gray matter, and 60 Gy in white matter. Conclusion: The threshold for radiation doses causing necrotic changes were defined in this study. Radiosurgery have both direct dose-dependent effect, and possibly indirect neuromodulatory effects; mediated by endogenous immunoreactive agents. Neuromodulative responses to radiation may be mediated by both vascular changes, as well as neuronal cell changes and glial cell remodeling.
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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 | 0.000 | 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) | 0.003 | 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".