Validation of contour-driven thin-plate splines for tracking fraction-to-fraction changes in anatomy and radiation therapy dose mapping
Bibliographic record
Abstract
The goal of this study is to validate a deformable model using contour-driven thin-plate splines for application to radiation therapy dose mapping. Our testing includes a virtual spherical phantom as well as real computed tomography (CT) data from ten prostate cancer patients with radio-opaque markers surgically implanted into the prostate and seminal vesicles. In the spherical mathematical phantom, homologous control points generated automatically given input contour data in CT slice geometry were compared to homologous control point placement using analytical geometry as the ground truth. The dose delivered to specific voxels driven by both sets of homologous control points were compared to determine the accuracy of dose tracking via the deformable model. A 3D analytical spherically symmetric dose distribution with a dose gradient of approximately 10% per mm was used for this phantom. This test showed that the uncertainty in calculating the delivered dose to a tissue element depends on slice thickness and the variation in defining homologous landmarks, where dose agreement of 3-4% in high dose gradient regions was achieved. In the patient data, radio-opaque marker positions driven by the thin-plate spline algorithm were compared to the actual marker positions as identified in the CT scans. It is demonstrated that the deformable model is accurate (approximately 2.5 mm) to within the intra-observer contouring variability. This work shows that the algorithm is appropriate for describing changes in pelvic anatomy and for the dose mapping application with dose gradients characteristic of conformal and intensity modulated radiation therapy.
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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 | 0.000 | 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".