The Factors Affecting Small Bowel Volume in the Pelvis of Patients Receiving Radiotherapy for Rectal Cancer
Bibliographic record
Abstract
Purpose: Radiation (RT)-Induced Gastrointestinal (GI) toxicities are associated the small bowel volume irradiated and the dosage received.However, rectal cancer patients treated with neoadjuvant Chemoradiotherapy (CRT) experience less GI toxicities compared to adjuvant chemoradiotherapy.The purpose of this study was to explore the factors which are associated with the small bowel volume in the pelvic radiation fields. Materials and methods:Patients with rectal cancer who had pre-or post-surgery CRT and were treated by a single radiation oncologist were included.All patients were treated with 3-D conformal radiotherapy.The volume of the organs was determined from planning CT scans.Acute toxicity was graded using Radiation Therapy Oncology Group (RTOG) Common Toxicity Criteria.Acute GI toxicity and its associated determinants such as age, bladder volume, gender, Body Mass Index (BMI), and type of surgery were documented.Results: A total of 119 patients (71 males, 48 females) 35 to 88 years of age were recruited.Sixty one out of 119 patients had pre-surgery RT or CRT and 58 patients had post-surgery therapy.Single predictors for greater irradiated small bowel volume were post-surgery treatment, female sex, smaller bladder volume and older age.The small bowel volume tended to increase with lower BMI and abdominoperineal resection.Multivariate analysis indicated that post-surgery treatment, being a female, and having a smaller bladder volume were predictors of greater irradiated volume of the small bowel.Conclusion: Factors such as pelvic surgery, being female, flat bladder, and older age are associated with increased small bowel volumes in pelvis.These would increase the irradiated small bowel volumes in patients receiving radiotherapy for rectal cancer.Therefore, giving radiotherapy before the surgery or using technical such as IMRT or Rapid Arc to avoid or reduce the small bowel volumes being irradiated is warranted.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".