Verification of monitor unit calculations for non‐IMRT clinical radiotherapy: Report of AAPM Task Group 114
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The requirement of an independent verification of the monitor units (MU) or time calculated to deliver the prescribed dose to a patient has been a mainstay of radiation oncology quality assurance. The need for and value of such a verification was obvious when calculations were performed by hand using look-up tables, and the verification was achieved by a second person independently repeating the calculation. However, in a modern clinic using CT/MR/PET simulation, computerized 3D treatment planning, heterogeneity corrections, and complex calculation algorithms such as convolution/superposition and Monte Carlo, the purpose of and methodology for the MU verification have come into question. In addition, since the verification is often performed using a simpler geometrical model and calculation algorithm than the primary calculation, exact or almost exact agreement between the two can no longer be expected. Guidelines are needed to help the physicist set clinically reasonable action levels for agreement. This report addresses the following charges of the task group: (1) To re-evaluate the purpose and methods of the "independent second check" for monitor unit calculations for non-IMRT radiation treatment in light of the complexities of modern-day treatment planning. (2) To present recommendations on how to perform verification of monitor unit calculations in a modern clinic. (3) To provide recommendations on establishing action levels for agreement between primary calculations and verification, and to provide guidance in addressing discrepancies outside the action levels. These recommendations are to be used as guidelines only and shall not be interpreted as requirements.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 it