TH‐A‐BRA‐01: Contouring Variations and Their Impact on Dose‐Volume Histograms in Non‐Small‐Cell Lung Cancer Radiotherapy: Analysis of a Multi‐ Institutional Pre‐Clinical Trial Planning Study
Bibliographic record
Abstract
Purpose: To quantify variations in target and normal structure contouring and evaluate dosimetric impact of these variations on conformal radiotherapy plans in non‐small‐cell lung cancer(NSCLC) cases.Methods: Two NSCLC cases were distributed and highly conformal radiotherapy plans generated by multiple institutions as a pre‐clinical trial planning study for RTOG protocol 1106 were used in this analysis. The same PET‐CT scans were provided to each institution for contouring and planning (prescription dose 74Gy). Eleven plans for Case1 and seven plans for Case2 were collected. Based on the contours from multiple sites, a consensus structure set was initially generated using Simultaneous Truth and Performance Level Estimation (STAPLE) algorithm, and then reviewed by physicians from participating institutions for agreement. The volume variation among institution contours and the deviation of them from consensus contour were analyzed. The dose‐volume histograms(DVH) for individual institution plans were re‐calculated using consensus contours and compared with their submitted DVH. Tumor Control Probability (TCP) was also calculated using both DVHs.Results: Planning target volumes(PTV) from different institutions ranged from 349cc to 522cc in Case1, and from 339cc to 686cc in Case2. The mean surface distance and Dice's coefficient between institutions' PTV and consensus PTV were 2.6±0.7mm(1.9– 4.4mm)(mean±SD(range)) and 92.4±3.3%(83.6‐95.4%) respectively for Case1, and 4.7±2.2mm(2.3–8.1mm) and 86.4±7.6%(74.7–94.5%) for Case2. For normal structures, brachial plexus presented large variation in contouring(Dice's coefficient below 50%), cord and esophagus presented moderate variation(Dice's coefficient around 78%), and lungs and heart presented least variation. The PTV D95% changed from 69.9±4.0Gy/74.2±0.5Gy(Case1/Case2) to 66.3±7.7Gy/59.3±18.9Gy when consensus PTV was used for re‐calculation. Maximum cord dose changed from 47.8±3.2Gy/35.3±9.7Gy to 51.1±4.3Gy/36.6±10.8Gy. TCP decreased from 84.3±6.5%/87.8±1.9% to 72.6±24.7%/52.8±44.4% with consensus contours.Conclusions: The amount of contouring variations in two NSCLC cases was presented and analysis shows the impact on DVH parameters can be significant. Quality assurance of contouring is essential for successful multi‐institutional clinical trial. This project is funded, in part, under a grant with the Pennsylvania Department of Health. The Department specifically declaims responsibility for any analyses, interpretations or conclusions.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".