Feasibility of using a transmission ion chamber for QA tests of medical linear accelerators
Bibliographic record
Abstract
PURPOSE: To study the feasibility of using the Integral Quality Monitoring (IQM) system for routine quality assurance (QA) of photon beams. METHODS: The IQM system is a commercially available dose delivery verification tool, which consists of a spatially sensitive large area transmission ion chamber, mounted on the Linac collimator, and a calculation algorithm to predict the signals in response to radiation beams. By comparing the measured and predicted signals the system verifies the accuracy of beam delivery. The ion chamber unit is a battery powered system including a dual-electrometer, temperature and pressure sensors, and inclinometers. The feasibility of using the IQM system for routine QA tests was investigated by measuring constancy values of beam parameters, with specially designed tests fields, and comparing them with those determined by a conventional system. RESULTS: The sensitivity of the beam output constancy measurements by the IQM system was found to agree with those measured by a Farmer type ion chamber placed in water phantoms to within 0.1% for typical daily output variation of ± 0.5% and ± 1%. The beam symmetry was measured with a 4 cm × 4 cm aperture at multiple off-axis distances and was found to have a highly linear relationship with those measured in a water phantom scan for intentionally introduced asymmetry between -3% and +3%. The beam flatness was measured with a two-field ratio method and was found to be linearly correlated with those measured by water phantom scan. The dosimetric equivalent of a picket fence test performed by the IQM system can serve as a constancy check of the multileaf collimator (MLC) bank positioning test. CONCLUSIONS: The IQM system has been investigated for constancy measurements of various beam parameters for photon beams. The results suggest that the system can be used for most of the routine QA tests effectively and efficiently.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".