Errors from field placement and organ motion during conformal radiotherapy for prostate cancer
Bibliographic record
Abstract
Purpose. To evaluate the effect of positioning errors from setup and from prostate motion during escalated dose conformal prostate irradiation for localised prostate cancer. Methods. Thirteen patients with localised prostate cancer had lateral portal films taken three times weekly during escalated dose conformal prostate radiotherapy. Field placement errors were measured by matching corresponding bony landmarks to the simulator film. Prostate motion at the base, mid-gland and apex was measured by imaging the displacement of 3 gold fiducial markers implanted into the prostate before therapy. From these measurements a planning target volume (PTV) was derived that allowed for both the prostate motion and field placement errors. Results. The random isocentre positioning error was 2.2 mm (range 0.2–7.3 mm), and the mean systematic isocentre positioning error was 1.4 mm (range 0.2–3.3 mm). Mean prostatic motion at the base was anterior 1.5 mm (SD 2.9 mm, range posterior 11.8 mm to anterior 16.8 mm), and superior 0.2 mm (SD 2.1 mm, range inferior 6.8 mm to superior 10.8 mm). At mid-gland it was anterior 0.6 mm (SD 2.4 mm, range posterior 7.2 mm to anterior 9.2 mm). At the apex it was posterior 0.3 mm (SD 2.1 mm, range posterior 7.9 mm to anterior 9.4 mm), and superior 0.5 mm (SD 2.1 mm, range inferior 6.7 mm to superior 10.2 mm). The margin of PTV about the prostate needed to give a 99% probability of the GTV remaining within the 95% isodose line during the course of therapy for these patients is superior 5.8 mm, and inferior 5.6 mm. In the anterior and posterior direction, this margin is 7.2 mm at the base, 6.5 mm at the mid-gland and 6.0 mm at the apex. Conclusions. Systematic setup errors were minimised by patient immobilisation and real-time corrections of setup errors. Prostate motion contributes the largest source of error, and this motion is greatest at the base of the gland compared to the apex. A non-uniform planning margin will improve target coverage while limiting normal tissue exposure. Fiducial markers implanted in the prostate improved quality assurance for radiation delivery by allowing confirmation of organ position within the treatment field over the course of 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 | 0.013 |
| 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".