A pulmonary vein atlas for radiotherapy planning
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Cardiac arrhythmia is a recognised potential complication of thoracic radiotherapy, but the responsible cardiac substructures for arrhythmogenesis have not been identified. Arrhythmogenic tissue is commonly located in the pulmonary veins (PVs) of cardiology patients with arrhythmia, however these structures are not currently considered organs-at-risk during radiotherapy planning. A standardised approach to their delineation was developed and evaluated. MATERIALS AND METHODS: The gross and radiological anatomy relevant to atrial fibrillation was derived from cardiology and radiology literature by a multidisciplinary team. A region of interest and contouring instructions for radiotherapy computed tomography scans were iteratively developed and subsequently evaluated. Radiation oncologists (n = 5) and radiation technologists (n = 2) contoured the PVs on the four-dimensional planning datasets of five patients with locally advanced lung cancer treated with 1.8-2.75 Gy fractions. Contours were compared to reference contours agreed by the researchers using geometric and dosimetric parameters. RESULTS: The mean dose to the PVs was 35% prescription dose. Geometric and dosimetric similarity of the observer contours with reference contours was fair, with an overall mean Dice of 0.80 ± 0.02. The right superior PV (mean DSC 0.83 ± 0.02) had better overlap than the left (mean DSC 0.80 ± 0.03), but the inferior PVs were equivalent (mean DSC of 0.78). The mean difference in mean dose was 0.79 Gy ± 0.71 (1.46% ± 1.25). CONCLUSION: A PV atlas with multidisciplinary approval led to reproducible delineation for radiotherapy planning, supporting the utility of the atlas in future clinical radiotherapy cardiotoxicity research encompassing arrhythmia endpoints.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.005 |
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".