Stereotactic radiosurgery for resected brain metastasis: Cavity dynamics and factors affecting its evolution.
Bibliographic record
Abstract
OBJECTIVE: To determine changes in post-surgical cavity volume for metastases based on time from surgery, pre-operative tumor dimensions and other predictors, in patients planned for post-operative stereotactic radiosurgery (SRS). METHODS: Patients with resected brain metastases from a primary solid tumor, treated with post-operative surgical cavity SRS from 2008 to 2014 were identified from an institutional prospective database. The segmented three-dimensional (3D) volume of the pre-operative tumor and post-operative surgical cavity were determined based on MRI and percent volume change was calculated. Patients were grouped according to early (<21 days), intermediate (22-42 days), and late (>42 days) intervals based on the number of days between the date of surgery and the treatment planning MRI. Potential predictive factors including tumor size, location, age, dural involvement, and degree of surgical resection were also analyzed. RESULTS: , p=0.03) was observed comparing tumor and cavity volumes. For larger tumors, an average volume reduction of 11.6% (p=0.01) was observed compared to an increase of 34.4% in smaller tumors (p=0.69). For both large and small tumors, cavities were larger in the early interval especially for smaller tumors. During the intermediate interval, a significant volume reduction was observed for larger tumors (28%, p=0.0007). Tumor size, dural involvement, age and time from surgery were significant predictors for volume change on univariate analysis. On multivariate analysis, tumor size, dural involvement and time from surgery were significant. CONCLUSION: Tumor size (>3cm), dural involvement and longer time from surgery were significant predictors of cavity volume reduction. Caution must be taken when treating cavities in the early (<21 days) interval after surgery as it may lead to irradiating more normal tissue especially in small tumors.
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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 | 0.001 | 0.002 |
| 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".