SBRT of ventricular tachycardia using 4pi optimized trajectories
Bibliographic record
Abstract
PURPOSE: To investigate the possible advantages of using 4pi-optimized arc trajectories in stereotactic body radiation therapy of ventricular tachycardia (VT-SBRT) to minimize exposure of healthy tissues. METHODS AND MATERIALS: Thorax computed tomography (CT) data for 15 patients were used for contouring organs at risk (OARs) and defining realistic planning target volumes (PTVs). A conventional trajectory plan, defined as two full coplanar arcs was compared to an optimized-trajectory plan provided by a 4pi algorithm that penalizes geometric overlap of PTV and OARs in the beam's-eye-view. A single fraction of 25 Gy was prescribed to the PTV in both plans and a comparison of dose sparing to OARs was performed based on comparisons of maximum, mean, and median dose. RESULTS: A significant average reduction in maximum dose was observed for esophagus (18%), spinal cord (26%), and trachea (22%) when using 4pi-optimized trajectories. Mean doses were also found to decrease for esophagus (19%), spinal cord (33%), skin (18%), liver (59%), lungs (19%), trachea (43%), aorta (11%), inferior vena cava (25%), superior vena cava (33%), and pulmonary trunk (26%). A median dose reduction was observed for esophagus (40%), spinal cord (48%), skin (36%), liver (72%), lungs (41%), stomach (45%), trachea (53%), aorta (45%), superior vena cava (38%), pulmonary veins (32%), and pulmonary trunk (39%). No significant difference was observed for maximum dose (p = 0.650) and homogeneity index (p = 0.156) for the PTV. Average values of conformity number were 0.86 ± 0.05 and 0.77 ± 0.09 for the conventional and 4pi optimized plans respectively. CONCLUSIONS: 4pi optimized trajectories provided significant reduction to mean and median doses to cardiac structures close to the target but did not decrease maximum dose. Significant improvement in maximum, mean and median doses for noncardiac OARs makes 4pi optimized trajectories a suitable delivery technique for treating VT.
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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 | 0.001 |
| 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".