Pre-operative versus post-operative radiosurgery for brain metastasis: Effects on treatment volume and inter-observer variability.
Bibliographic record
Abstract
PURPOSE/OBJECTIVES: Compared to post-operative whole brain radiotherapy, resection cavity radiosurgery reduces impact on neuro-cognitive function and improves quality-of-life. However, coverage of the operative tract, in addition to tumour bed, may lead to large treatment volumes and inter-observer variability. We hypothesized that pre-operative radiosurgery reduces target volume size and inter-observer variability compared to post-operative radiosurgery. MATERIALS/METHODS: We identified 10 consecutive patients, with solitary brain metastasis, treated with post-operative cavity radiosurgery.Pre- and post-operative axial T1 contrast MRI were co-registered with the planning CT scans. Three radiation oncologists independently contoured the target volumes on the pre- and post-operative imaging. A 2mm-PTV margin was utilized for both strategies and radiosurgery treatment plans were generated. The following parameters were evaluated in the 2 plans: Mean target volume (cc), 50% isodose volume (cc), Inter-observer variability (Jaccard Index JI) and Conformity Index (CI). RESULTS: There was no significant difference in the mean target volume, nor 50% isodose volume, between pre- and post-operative strategies. (17.6 (95% CI 9.98 - 25.22) versus 19.4 (95% CI 10.11 - 28.69) cc, P=0.80; 61.7 (95% CI 38.4 - 85.0) vs 77.7 (95% CI 34.94 - 120.46) cc, P=0.65). There was significantly less inter-observer variability and improved conformity in the pre-operative group (Mean JI 0.84(95% CI 0.82 - 0.86) versus 0.70 (95% CI 0.62 - 0.78), P = 0.005; Mean CI 1.32 (95% CI 1.26 - 1.38) vs 1.45 (95% CI 1.36 - 1.54), P= 0.01). Planned subgroup analysis did not reveal any significant difference (between pre- vs post-op) in the mean volume of cystic versus non-cystic metastasis. Deep lesions (>2.5cm from dura) had a larger post-operative target volume (25.8 (95% CI 15.1 - 36.5) vs 12.3 (95% CI 6.54 - 18.06) cc, P=0.06) compared to superficial lesions. CONCLUSION: Pre-operative radiosurgery has less inter-observer variability and improved plan conformity. However, there was no difference in mean target volume between the pre- versus post-operative radiation. Contouring guidelines, and peer review, may help to reduce inter-observer variability for cavity radiosurgery.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.001 | 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".