MLC光学センサーの頑健性試験：葉開時間再構成およびオンライン配信検証への応用
Nathan A Corradini1, Cristina Vite1, Patrizia Urso1
1Radiotherapy Center, Gruppo Ospedaliero Moncucco, Clinica Moncucco, Lugano, Switzerland.
Background:
Online adaptive radiotherapy (OART) requires the patient to remain on the treatment couch, necessitating alternative patient-specific quality assurance (PSQA) solutions to guarantee treatment delivery integrity. Multileaf collimator (MLC) optical sensors (OS) record leaf states on the Radixact linear accelerator and allow for leaf open time (LOT) reconstruction for online delivery verification. Assessment of the quality of the OS data and the OS reconstruction algorithm is important for understanding the reliability of this QA approach.
Purpose:
To assess the robustness of the OS LOT reconstruction method currently available to users on the Radixact platform.
Methods:
Raw OS and MVCT detector data were acquired daily for LOT latency curve testing over an 8-month period. More than 8600 datapoints were analyzed for each leaf and the datasets were used to assess OS response stability and OS response uncertainty. An in-house algorithm was developed and used to reconstruct delivered treatments for 55 patients from the raw OS data, which were compared against the vendor's Delivery Analysis (DA) software reconstructions to assess algorithm-based uncertainties.
Results:
OS LOT reconstructions remained stable when compared to those of the detector; however, statistically significant drift from baseline, which averaged 0.1 ms, was found in approximately 20% of evaluated signals. The standard deviation in LOT reconstruction differences between methods was between 0.5 and 0.6 ms when measuring leaf open times ≥25 ms. LOT reconstruction differences between methods was found to increase with the number of leaves simultaneously opening. A systematic shift of 0.4 ms in LOT method differences was found for the MLC's two leaf banks. In-house OS-reconstructed patient treatments were on average in agreement with the vendor's DA software reconstructions to within ±1 ms for 98.1% of all sinogram LOTs.
Conclusions:
Leaf OS signals provide a reliable measurement method for LOT reconstruction on the Radixact platform. The OS LOT reconstructions are a practical solution for online treatment delivery verification as part of the PSQA process for OART workflows. This work provides the basis for future needs in MLC OS QA on the Radixact system as well as evidencing future studies to better understand the relationship between individual LOT reconstruction and delivered dose.
