Sci‐Fri PM: Radiation Therapy, Planning, Imaging, and Special Techniques ‐ 09: Impact of the distance of reflective markers from linac isocenter on the positional accuracy of an infrared tracking system
Bibliographic record
Abstract
Purpose: The HexaPOD™ six degree of freedom couchtop is equipped with an optical tracking system, consisting of a stereoscopic camera and a reference frame (RF) carrying infrared reflective markers. The manufacturer recommends placing the RF within 50 cm from linac isocenter (ISO), which is a serious limitation since the RF does not fit around the shoulders of most brain patients. This study quantifies the impact of extended RF distances from ISO on positional accuracy. Methods: An in‐house tool with an estimated resolution of 0.3 mm and 0.1° was used. It is a large cube and a mathematical model of HexaPOD motion to determine the intersection of room lasers with the ruled cube edges. Combinations of translations (±1 and ±3 cm) and rotations (±2.5°) were executed on two HexaPOD couchtops for multiple RF distances from ISO (35 to 77 cm). For each combination, ten laser readings were fed into a least squares algorithm to determine the executed translations and rotations while minimizing operator reading errors. Results: The usable tracking volume is up to an RF distance of 82 cm from ISO. Positional accuracy of the HexaPOD/iGuide system is 0.6 mm and 0.1° (95% confidence). Positional accuracy variations versus RF distance from ISO are statistically insignificant (p = 0.05). Our results generally confirm recent internal estimates by the manufacturer (for future release). Conclusions: RF distances up to 77 cm from ISO are clinically acceptable, provided performing a patient safety study with a verification scan.
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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 | 0.006 |
| 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) | 0.004 | 0.001 |
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".