Aerrow: A probe‐format graphite calorimeter for absolute dosimetry of high‐energy photon beams in the clinical environment
Bibliographic record
Abstract
Purpose In this work, the design, operation, initial experimental evaluation, and characterization of a small‐scale graphite calorimeter probe — herein referred to as the Aerrow — developed for routine use in the clinical environment, are described. Similar in size and shape to a Farmer type cylindrical ionization chamber, the Aerrow represents the first translation of calorimetry intended for direct use by clinical physicists in the radiotherapy clinic. Methods Based on a numerically optimized design obtained in previous work, a functioning Aerrow prototype capable of two independent modes of operation (quasi‐adiabatic and isothermal) was constructed in‐house. Reference dose measurements were performed using both Aerrow operation modes in a 6 MV photon beam and were directly compared to results obtained with a calibrated reference‐class ionization chamber. The Aerrow was then used to quantify the absolute output of five clinical linac‐based photon beams (6 MV , 6 MV FFF , 10 MV , 10 MV FFF , and 15 MV ; 63.2% < % dd (10)× < 76.3%). Linearity, dose rate, and orientation dependences were also investigated. Results Compared to an ion chamber‐derived dose to water of 76.3 ± 0.7 cG y, the average doses measured using the Aerrow were 75.6 ± 0.7 and 74.7 ± 0.7 cG y/ MU for the quasi‐adiabatic and isothermal modes, respectively. All photon beam output measurements using the Aerrow in water‐equivalent phantom agreed with chamber‐based clinical reference dosimetry data within combined standard uncertainties. The linearity of the Aerrow's response was characterized by an adjusted R 2 value of 0.9998 in the dose range of 80 cG y to 470 cG y. For the dose‐rate dependence, no statistically significant effects were observed in the range of 0.5 Gy/min to 5.4 Gy/min. A relative photon beam quality dependence of 1.7% was calculated in the range of 60 Co to 24 MV (58.4% < % dd (10)× < 86.8%) using Monte Carlo. Finally, the angular dependence (gantry stationary and detector rotated) of the Aerrow's response was found to be insignificant to within ±0.5%. Conclusions This work demonstrates the feasibility of using an ion chamber‐sized calorimeter as a practical means of measuring absolute dose to water in the radiotherapy clinic. The potential introduction of calorimetry as a mainstream device into the clinical setting is powerful, as this fundamental technique has formed the basis of absorbed dose standards in many countries for decades and could one day form the basis of a new local absorbed dose standard for clinics.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".