Validation of the Spatial Accuracy of the ExacTrac® Adaptive Gating System
Bibliographic record
Abstract
Stereotactic body radiation therapy (SBRT) is a method of treatment that is used in extracranial locations, including the abdominal and thoracic cavities, as well as spinal and paraspinal locations. At the McGill University Health Centre, liver SBRT treatments include gating, which places the treatment beam on a duty cycle controlled by tracking of fiducial markers moving with the patient's breathing cycle. Respiratory gated treatments aim to spare normal tissue, while delivering a dose properly to a moving target. The ExacTrac® system (BrainLAB AG Germany) is an image-guided radiotherapy system consisting of a combination of infra-red (IR) cameras and dual kilovoltage (kV) X-ray tubes. The IR system is used to track patient positioning and respiratory motion, while the kV X-rays are used to determine a positional shift based on internal anatomy or fiducial markers. In order to validate the system's ability to treat under gating conditions, each step of the SBRT process was evaluated quantitatively. Initially the system was tested under ideal static conditions, followed by a study including gated parameters. The uncertainties of the isocenters, positioning algorithm, planning computed tomography (CT) and four dimensional CT (4DCT) scans, gating window size and tumor motion were evaluated for their contributions to the total uncertainty in treatment. The mechanical isocenter and 4DCT were found to be the largest sources of uncertainty. However, for tumors with large internal amplitudes (>2.25 cm) that are treated with large gating windows (>30%) the gating parameters can contribute more than 1.1 ± 1.8 mm.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".