Dosimetric effects caused by couch tops and immobilization devices: Report of AAPM Task Group 176
Bibliographic record
Abstract
The dosimetric impact from devices external to the patient is a complex combination of increased skin dose, reduced tumor dose, and altered dose distribution. Although small monitor unit or dose corrections are routinely made for blocking trays, ion chamber correction factors, e.g., accounting for temperature and pressure, or tissue inhomogeneities, the dose perturbation of the treatment couch top or immobilization devices is often overlooked. These devices also increase skin dose, an effect which is also often ignored or underestimated. These concerns have grown recently due to the increased use of monolithic carbon fiber couch tops which are optimal for imaging for patient position verification but cause attenuation and increased skin dose compared to the "tennis racket" style couch top they often replace. Also, arc delivery techniques have replaced stationary gantry techniques which cause a greater fraction of the dose to be delivered from posterior angles. A host of immobilization devices are available and used to increase patient positioning reproducibility, and these also have attenuation and skin dose implications which are often ignored. This report of Task Group 176 serves to present a survey of published data that illustrates the magnitude of the dosimetric effects of a wide range of devices external to the patient. The report also provides methods for modeling couch tops in treatment planning systems so the physicist can accurately compute the dosimetric effects for indexed patient treatments. Both photon and proton beams are considered. A discussion on avoidance of high density structures during beam planning is also provided. An important aspect of this report are the recommendations the authors make to clinical physicists, treatment planning system vendors, and device vendors on how to make measurements of surface dose and attenuation and how to report these values. For the vendors, an appeal is made to work together to provide accurate couch top models in planning systems.
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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 | 0.017 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".