SU‐DD‐A3‐01: Dosimetric Evaluation of Daily Rigid and Non‐Rigid Geometric Correction Strategies During On‐Line Image‐Guided Radiation Therapy (IGRT) of Prostate Cancer
Bibliographic record
Abstract
Purpose: To evaluate a geometric image guidance strategy that simultaneously correct for various interfractional rigid and non‐rigid geometric uncertainties in an on‐line environment, using field shape corrections (by modifying MLC). This technique was dosimetrically compared to simpler and more popular image guidance strategies (e.g., linear corrections). Method and Materials: Five prostate cancer patients with daily CT studies were analyzed. All patients were planned with a simplified intensity modulated radiation therapy (SIMAT) technique. A uniform 5‐mm margin was used. The image‐guided geometric correction strategies simulated were (1) translational correction based on daily gross CTV registration (“CTV”), (2) translational correction with daily MU recalculation (“MU‐CTV”), and finally, (3) translational correction with MU re‐calculation and daily MLC corrections to account for prostate deformations (“MU‐MLC”). Deformable image registration was performed on all treatment CT studies for dose accumulation. Generalized equivalent uniform dose (gEUD) index was used for dosimetric comparisons. Results: As expected, some dosimetric differences in the target volume were observed between the three image guidance strategies. For example, up to ± 2% discrepancy in prostate minimum dose were observed among the techniques. Of them, only the “MU‐MLC” technique did not reduce the prostate minimum dose for all patients (i.e., ⩾ 100%). However, the differences were clinically not significant to indicate the preference of one strategy over another, when using a uniform 5‐mm margin size. For the organ‐at‐risks (OARs), large rectum sparing effect (⩽ 5.7 Gy, gEUD) and bladder overdosing effect (⩽ 16 Gy, gEUD) were observed. Conclusion: The results suggest that a linear translational correction (i.e., “CTV”) is adequate to maintain target coverage, for margin sizes at least as large as 5 mm. In addition, due to large fluctuations in OAR volumes, innovative image guidance strategies are needed to minimize dose and maintain consistent sparing during the whole course of radiation therapy.
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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 | 0.001 | 0.002 |
| 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) | 0.001 | 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".