194: Population-Based Analysis of Stereotactic Body Radiotherapy (SBRT) for Oligometastatic Lymph Node Metastases
Bibliographic record
Abstract
inter-observer variability compared to post-operative radiosurgery.Methods and Materials: 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 and CyberKnife treatment plans were generated.The following parameters were evaluated in the two plans: Mean target volume (cc), 50% isodose volume(cc), Inter-observer variability (Jaccard Index JI) and Conformity Index (CI).Results were analyzed with STATA version 14. Results: Radiosurgery doses ranged from 18 Gy in 1 to 30 Gy in 5 fractions depending on the location and volume (Median 24 Gy in 3 fractions).There was no significant difference in the mean target volume, nor 50% isodose volume, between pre-and postoperative strategies.(17.6 +-SD 12.3 versus 19.4+-15 cc, p = 0.80; 61.7 +-37.7 versus 77.7 +-69.0 cc, p = 0.65).There was significantly less inter-observer variability and improved conformity in the pre-operative group (Mean JI 0.84+-0.04versus 0.70+-0.13,p = 0.005; Mean CI 1.32 +-0.09 versus 1.45 +-0.14, p = 0.01).Planned subgroup analysis did not reveal any significant difference (between pre-versus post-op) in the mean volume of cystic versus non-cystic metastasis.Deep lesions (> 2.5 cm from dura) had a larger post-operative target volume (25.8+-17.3versus 12.3+-9.3cc, p = 0.06) compared to superficial lesions.Conclusions: 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 postoperative 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".