Geometric Performance and Efficiency of an Optical Tracking System for Daily Pre-treatment Positioning in Pelvic Radiotherapy Patients
Bibliographic record
Abstract
The purpose of this study was to characterize the accuracy of a novel in-house optical tracking system (OTS), and to determine its efficiency for daily pre-treatment positioning of pelvic radiotherapy patients compared to conventional optical distance indicator (ODI) methodology. The OTS is comprised of a passive infrared stereoscopic camera, and custom control software for use in assisting radiotherapy patient setup. Initially, the system was calibrated and tested for stability inside a radiation therapy treatment room. Subsequently, under an ethics approved protocol, the clinical efficiency of the OTS was compared to conventional ODI setup methodology through 17 pelvic radiotherapy patients. Differences between orthogonal source-to-skin distance (SSD) readings and overall set-up time resultant from both systems were compared. The precision of the OTS was 0.01 ± 0.01 mm, 0.02 ± 0.02 mm, and -0.01 ± 0.06 mm in the left/right (L/R), anterior/posterior (A/P), and cranial/caudal (C/C) directions, respectively. Discrepancies measured between the linac radiographic center in the treatment room and the calibrated origin of the camera (OTS) by two independent observers was submillimeter. Analysis of 146 fractions from 17 patients showed a high correlation between the SSD readings of the OTS and ODI setup methodologies (r = 0.99). The average time for pre-treatment positioning using the OTS couch shift calculation was 2.60 ± 0.69 minutes, and for conventional ODI setup, 3.62 ± 0.82 minutes; the difference of 1.02 minutes was statistically significant (p < 0.001). In conclusion, the OTS is a precise and robust tool for use as an independent check of treatment room patient positioning. The system is indicated as geometrically equivalent to current methods of daily pre-treatment patient positioning with potential for gains in efficiency by decreasing setup times in the treatment room.
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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 | 0.007 |
| 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".