A Contouring Strategy and Reference Atlases for the Full Abdominopelvic Bowel Bag on Treatment Planning and Cone Beam Computed Tomography Images
Bibliographic record
Abstract
Purpose: To establish a practical contouring strategy with reference atlases for the abdominopelvic bowel bag on treatment planning computed tomography (TPCT) and cone beam computed tomography (CBCT) images. Methods and Materials: A scoping literature review was done to evaluate the existing definitions and contouring guidelines for bowel bag and small bowel planning-at-risk volume-like structures. A comprehensive definition was proposed for the abdominopelvic bowel bag that expanded the Radiation Therapy Oncology Group Pelvic Normal Tissue Consensus definition. Seven patients with TPCT and first-treatment-day CBCT images were selected from an institutional database to represent a range of normal anatomy and CBCT image quality. The TPCT and CBCT images were contoured using the proposed definition. During contouring, the Radiation Therapy Oncology Group definition's list of inclusion and exclusion structures was expanded. For areas with limited visibility of the bowel bag on either TPCT or CBCT, a set of operational definitions was developed based on consistently visible reference structures. Results: A literature review showed that previously existing bowel bag definitions predominantly focused on the pelvic region and did not provide a complete and practical description of the full abdominopelvic contour relative to structures consistently visible in all radiation therapy images. The proposed contouring strategy had 4 components: a definition, a list of inclusion and exclusion structures, 15 tabulated operational definitions, and a set of atlases. The bowel bag was defined as the peritoneal cavity and retroperitoneal duodenum and ascending and descending colon, as visualized at the time of image acquisition. The operational definitions formalized the location of the peritoneal fascial planes through a simple look-up table. The proposed contouring strategy and reference atlases were successfully used on both TPCT and CBCT images. Conclusions: This study produced a practical contouring strategy and reference atlases to enable reproducible delineation of the full bowel bag on TPCT and CBCT images. The strategy is a necessary first step toward consensus contouring with reduced observer variability, which is a prerequisite for evaluation of cumulative dose and its correlation with toxic effects, adaptive planning strategies, and automated contouring potential.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".