Real‐time verification of multileaf collimator‐driven radiotherapy using a novel optical attenuation‐based fluence monitor
Bibliographic record
Abstract
PURPOSE: Multileaf collimator (MLC)-driven conformal radiotherapy modalities [e.g., such as intensity-modulated radiotherapy (IMRT), intensity-modulated arc therapy, and stereotactic body radiotherapy] are more subject to delivery errors and dose calculation inaccuracies than standard modalities. Fluence monitoring during treatment delivery could reduce such errors by allowing an independent interface to quantify and assess measured difference between the delivered and planned treatment administration. We developed an optical attenuation-based detector to monitor fluence for the on-line quality control of radiotherapy delivery. The purpose of the current study was to develop the theoretical background of the invention and to evaluate the detector's performance both statistically and in clinical situations. METHODS: We aligned 60 27-cm scintillating fibers coupled to a photodetector via clear optical fibers in the direction of motion of each of the 60 leaf pairs of a 120 leaves Millenium MLC on a Varian Clinac iX. We developed a theoretical model to predict the intensity of light collected on each side of the scintillating fibers when placed under radiation fields of varying sizes, intensities, and positions. The model showed that both the central position of the radiation field on the fiber (x(c)) and the integral fluence passing through the fiber (phi(int)) could be assessed independently in a single measurement. We evaluated the performance of the prototype by (1) measuring the intrinsic variation of the measured values of x(c) and phi(int), (2) measuring the impact on the measured values of x(c) and phi(int) of random leaf positioning errors introduced into IMRT fields, and (3) comparing the predicted values of x(c) and phi(int) calculated with the treatment planning software to the measured values of x(c) and phi(int) in order to assess the predictive effectiveness of the developed theoretical model. RESULTS: We observed a very low intrinsic dispersion, dominated by Poisson statistics, for both x(c) (standard deviations of less than 1 mm) and phi(int) (standard deviations of less than 0.20%). When confronted with random leaf positioning errors from IMRT segments, phi(int) was highly sensitive to single leaf positioning errors as small as 1 mm at isocenter, while x(c) was sensitive to leaf pair translation errors of at least 2 mm at isocenter. Owing to the uncertainties in the doses calculated in regions of high perpendicular dose gradients, the measured values of x(c) and phi(int) deviated from the predicted values of x(c) and phi(int) by a mean of 1.3 mm and 2.6%, respectively. CONCLUSION: Our study showed that an optical attenuation-based detector can be used to effectively monitor integral fluence during radiotherapy delivery. The performance of such a system would enable real-time quality control of the incident fluence in current MLC-driven treatments such as IMRT and future adaptive radiotherapy procedures where new treatment plans will have to be delivered without passing thru the current standard quality control chain.
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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 | 0.000 | 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 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".