Volume specific response criteria for brain metastases following salvage stereotactic radiosurgery and associated predictors of response
Bibliographic record
Abstract
BACKGROUND: We aimed to derive three-dimensional volume-based (V(3D)) response criteria that approximate those based on Response Evaluation Criteria in Solid Tumours (RECIST) in patients with brain metastases (BM) treated with salvage stereotactic radiosurgery (SRS). MATERIAL AND METHODS: Seventy patients with 178 BM were treated with SRS. Each BM was characterised at baseline and at each follow-up MRI according to its widest diameter and V(3D) using ITK-SNAP image segmentation software. RESULTS: The median tumour diameter was 1.2 cm (range, 0.2-4.5 cm) and V(3D) was 0.73 cm(3) (range, 0.01-22.7 cm(3)). The V(3D) percent changes that best matched RECIST response criteria were: an increase of ≥71.5% for progressive disease, a ≥58.5% decrease for partial response and a <58.5% decrease or increase of <71.5% for stable disease (k =0.85). A baseline diameter >3.0 cm (p =0.006) and a V(3D) >6.0 cm(3) (p =0.043) predicted for local failure, and a baseline cumulative V(3D) of >3.0 cm(3) (p =0.02) was adversely prognostic for survival. CONCLUSIONS: We define 3D volume specific criteria to base response upon for brain metastases treated with salvage SRS. Tumours with a V(3D) of greater than 6 cm(3) are at a higher risk of local failure.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".