Characterization of cylindrical ionization chambers for patient specific IMRT QA
Bibliographic record
Abstract
Proven conventional dosimetry techniques do not provide accuracy and precision in the measurement of inverse planned intensity modulated radiation therapy (IMRT) fields. Dynamic and step-and-shoot multileaf collimation (DMLC/SMLC) challenge current ionization chamber dosimetry practices. Ionization chamber performance in these fields is evaluated for three cylindrical chambers of varying volumes (PinPoint (PP): 0.015 cm3, IC10: 0.13 cm3, Farmer type NE2571 (FT): 0.69 cm3) in terms of measurement reproducibility, dose measurement linearity, and IMRT dose measurements. Fifty IMRT patient specific quality assurance dose measurements were performed with each chamber. DMLC measurements are compared between chambers, and to dose calculations from a commercial treatment planning system (TPS) that used a finite size pencil beam model (FSPB). Ten SMLC measurements are compared to Monte Carlo simulations available in the TPS. The three chambers demonstrated adequate measurement reproducibility characteristics for both open and DMLC fields with each chamber able to perform within 2% (2SD) for DMLC fields. Both smaller volume chambers over responded (> 5%) when irradiated with a small number of monitor units in open fields. FT and IC10 chambers demonstrated dose linearity in DMLC fields down to 10 monitor units, while dose linearity for the PP chamber broke down at 100 monitor units. The evaluation of fifty DMLC treatment plan quality assurance procedures revealed that the FT chamber measurements were closest to the FSPB calculated values (FSPB: 1.0, FT: 0.973 +/- 0.044, IC10: 0.963 +/- 0.048, PP: 0.944 +/- 0.071). Quality assurance plans calculated independently with Monte Carlo more closely matched chamber measurements (FSPB: 1.0, MC: 0.97, FT: 0.95). Measurements of absorbed dose to water in IMRT fields are highly chamber and IMRT plan dependent.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".