SU‐E‐T‐509: Inter‐Observer and Inter‐Modality Contouring Analysis for Organs at Risk for HDR Gynecological Brachytherapy
Bibliographic record
Abstract
Purpose This study quantifies errors associated with MR‐guided High Dose Rate (HDR) gynecological brachytherapy. Uncertainties in this treatment results from contouring, organ motion between imaging and treatment delivery, dose calculation, and dose delivery. We focus on interobserver and inter‐modality variability in contouring and the motion of organs at risk (OARs) in the time span between the MR and CT scans (∼1 hour). We report the change in organ volume and position of center of mass (CM) between the two imaging modalities. Methods A total of 8 patients treated with MR‐guided HDR brachytherapy were included in this study. Two observers contoured the bladder and rectum on both MR and CT scans. The change in OAR volume and CM position between the MR and CT imaging sessions on both image sets were calculated. Results The absolute mean bladder volume change between the two imaging modalities is 67.1cc. The absolute mean inter‐observer difference in bladder volume is much lower at 15.5cc (MR) and 11.0cc (CT). This higher inter‐modality volume difference suggests a real change in the bladder filling between the two imaging sessions. Change in Rectum volume inter‐observer standard error of means (SEM) is 3.18cc (MR) and 3.09cc (CT), while the inter‐modality SEM is 3.65cc (observer 1), and 2.75cc (observer 2). The SEM for rectum CM position in the superior‐inferior direction was approximately three times higher than in other directions for both the inter—observer (0.77 cm, 0.92 cm for observers 1 and 2, respectively) and inter‐modality (0.91 cm, 0.95 cm for MR and CT, respectively) variability. Conclusion Bladder contours display good consistency between different observers on both CT and MR images. For rectum contouring the highest inconsistency stems from the observers’ choice of the superior‐inferior borders. A complete analysis of a larger patient cohort will enable us to separate the true organ motion from the inter‐observer variability.
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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 | 0.005 | 0.016 |
| 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 | 0.000 | 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".