AAPM task group report 351: Protocol for clinical reference dosimetry in external beam MR‐guided radiotherapy
Bibliographic record
Abstract
Abstract Background Magnetic Resonance‐guided Radiation Therapy (MRgRT) systems are increasingly used in clinical practice, necessitating a dedicated dosimetry protocol to address the challenges posed by the presence of strong magnetic fields. Purpose AAPM TG351 introduces a reference dosimetry protocol for external beam MRgRT systems, aligning with AAPM TG51 reports and incorporating elements from the IAEA TRS398 code of practice. Methods The protocol offers practical guidance on beam quality and dosimetry setup in the presence of strong magnetic fields. It reviews relevant literature to identify reference‐class chambers suitable for external beam MRgRT systems and determines their beam quality conversion and other relevant correction factors through a detailed analysis of available data and associated uncertainties. Results AAPM TG351 offers a comprehensive dosimetry protocol for external beam MRgRT systems, addressing the unique challenges posed by the presence of magnetic fields. It includes detailed guidance for measurement setups, a list of reference‐class chambers appropriate for reference dosimetry in MRgRT systems, and updated beam quality conversion and correction factors. Additionally, the protocol presents an in‐depth analysis of the uncertainty budget, identifying key contributors and providing strategies to minimize uncertainties, thereby enhancing clinical accuracy and reliability. Conclusions This protocol provides a practical, evidence‐based reference for medical physicists conducting reference dosimetry in external beam MRgRT 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 | 0.094 | 0.161 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.008 | 0.004 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.032 | 0.035 |
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".