Patient specific methods for room‐mounted x‐ray imagers for monoscopic/stereoscopic prostate motion monitoring
Bibliographic record
Abstract
PURPOSE: To investigate the improvement of combined monoscopic/stereoscopic prostate motion monitoring with room-mounted dual x-ray systems by adopting patient specific methods. METHODS: The linac couch was used as a motion stage to simulate 40 highly dynamic real patient prostate trajectories. For each trajectory, 40 s pretreatment and 120 s treatment periods were extracted to represent a typical treatment fraction. Motion was monitored via continuous stereoscopic x-ray imaging of a single gold fiducial and images were retrospectively divided into periods of stereoscopic and monoscopic imaging to simulate periodic blocking of the room-mounted system by the gantry during arc-based therapy. The accuracy of the combined motion monitoring was assessed by comparison with the linac couch log files. To estimate 3-D marker position during monoscopic imaging, the use of population statistics was compared to both maximum likelihood estimation and stereoscopic localization based estimation of individualized prostate probability density functions (PDFs) from the pretreatment period. The inclusion of intrafraction updating was compared to pretreatment initialization alone. RESULTS: Combined mono/stereoscopic localization was successfully implemented. During the transitions from stereoscopic to monoscopic imaging, fiducial localization exhibits sharp discontinuities when population PDFs were employed. Patient specific PDFs successfully reduced the localization error when estimated from stereoscopic localizations, whereas maximum likelihood estimation (MLE) was too unstable in the room-mounted geometry. Intrafraction stereoscopic updating provided further increases in accuracy. Residual error tended to decrease throughout the treatment fraction, as the patient-specific PDFs became more refined. CONCLUSIONS: This is the first demonstration of toggled monoscopic/stereoscopic localization using room-mounted dual x-ray imagers, enabling continuous intrafraction motion monitoring for these systems. We showed that both pretreatment individualization and intrafraction updating should be used to provide the most accurate motion monitoring.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".