3D ultrasound for prostate localization in radiation therapy: A comparison with implanted fiducial markers
Bibliographic record
Abstract
This study compares prostate localization using three-dimensional ultrasound (3D US) to a standard technique using implanted fiducial markers (FMs) for prostate image guided radiation therapy (IGRT). Two methods to determine prostate position on US were evaluated: Assisted segmentation (prospectively) and manual segmentation (retrospectively). Daily couch shifts to align the prostate into treatment position were measured using each technique. A total of 278 FM couch shifts and 255 and 218 corresponding assisted and manual segmentation US couch shifts were analyzed in each direction: Anterior-posterior, right-left, and superior-inferior. Ninety five percent "limits-of-agreement" (LOA) were used to analyze paired couch shifts and to determine if US can reliably replace FMs. We chose an error tolerance of +/- 3 mm for the LOA analysis. For FM vs assisted-segmentation US, 35.3%, 51.0%, and 48.2% of couch shifts (anterior-posterior, right-left, and superior-inferior, respectively) agreed within +/- 3 mm. Agreement improved using manual segmentation US (corresponding agreements were 45.3%, 64.1%, and 55.2%), however, results still lie markedly below the 95% we consider to indicate clinical equivalence. Based on these results, our experience indicates US cannot replace FMs for prostate IGRT, using either assisted or manual segmentation. US couch shifts showed considerably greater variability than FM measures and US image quality is shown to affect agreement. Planning target volume margins for use with the US system were found to be 15.8, 8.7, and 12.5 mm for assisted segmentation and 13.1, 7.6, and 9.8 mm for manual segmentation. Comparison of these margins to those reported in recent studies for use with FM IGRT indicate FMs offer greater sparing of the rectum and bladder than the US system.
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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".