Image-guided radiation therapy for post-operative gynaecologic cancer: patient set up verification with and without implanted fiducial markers
Bibliographic record
Abstract
BACKGROUND: Intensity modulated radiotherapy (IMRT) is increasingly being used to treat gynaecological malignancies in the postoperative setting. The purpose of this study was to evaluate the use of image-guided radiotherapy (IGRT) using cone-beam computed tomography (CBCT) with fiducial markers for daily localization. MATERIAL AND METHODS: A single institution study was performed of consecutive cervical or endometrial cancer patients receiving adjuvant external beam radiotherapy (n = 15). Patients were set up at treatment using daily CBCT and alignment of implanted fiducial markers. Image registration was retrospectively completed based on soft tissue matching and the resulting couch shifts from each IGRT method were compared (n = 122). RESULTS: The median shift between IGRT methods was 2 mm, 1 mm and 1 mm in the anterior-posterior (A-P), superior-inferior (S-I), and lateral directions, respectively. The largest deviations were observed in the A-P direction; however, more than 90% were within 5 mm and 63.9% were within 2.5 mm. CONCLUSIONS: IGRT based on soft tissue match provides a noninvasive convenient method for daily localization and is accurate within treatment uncertainty for the majority of cases.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".