‘Compromise position’ image alignment to accommodate independent motion of multiple clinical target volumes during radiotherapy: A high risk prostate cancer example
Bibliographic record
Abstract
INTRODUCTION: Inclusion of multiple independently moving clinical target volumes (CTVs) in the irradiated volume causes an image guidance conundrum. The purpose of this research was to use high risk prostate cancer as a clinical example to evaluate a 'compromise' image alignment strategy. METHODS: The daily pre-treatment orthogonal EPI for 14 consecutive patients were included in this analysis. Image matching was performed by aligning to the prostate only, the bony pelvis only and using the 'compromise' strategy. Residual CTV surrogate displacements were quantified for each of the alignment strategies. RESULTS: = 0.95 (LR), 0.67 (AP) and 0.59 (SI). Differences between the surrogates displacements (95% range) were -0.4 to 1.8 mm (LR), -1.2 to 5.2 mm (SI) and -1.2 to 5.2 mm (AP). The distribution of the residual displacements was significantly smaller using the 'compromise' strategy, compared to the other strategies (p 0.005). The 'compromise' strategy ensured the CTV was encompassed by the PTV in all fractions, compared to 47 PTV violations when aligned to prostate only. CONCLUSIONS: This study demonstrated the feasibility of a compromise position image guidance strategy to accommodate simultaneous displacements of two independently moving CTVs. Application of this strategy was facilitated by correlation between the CTV displacements and resulted in no geometric excursions of the CTVs beyond standard sized PTVs. This simple image guidance strategy may also be applicable to other disease sites that concurrently irradiate multiple CTVs, such as head and neck, lung and cervix cancer.
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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 | 0.001 | 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".