Abstract Matching multiple linacs to common baseline data allows patients to be treated, and patient‐specific quality assurance (PSQA) to be completed on any linac. Stereotactic body radiotherapy (SBRT) requires higher… Click to show full abstract
Abstract Matching multiple linacs to common baseline data allows patients to be treated, and patient‐specific quality assurance (PSQA) to be completed on any linac. Stereotactic body radiotherapy (SBRT) requires higher levels of accuracy and quality assurance than routine radiotherapy. The achieved linac matching must therefore be evaluated before distributive treatment or PSQA models can be implemented safely. This investigation aimed to propose metrics for defining linacs to be matched for SBRT deliveries, assess 12 linacs against these criteria, and determine if a distributive PSQA model could be implemented by reviewing the rates of false PSQA results. Ten SBRT spine plans were delivered by 12 matched Elekta linacs and measured using one of seven SRS MapCHECK devices. For gamma criteria of (3%, 2 mm), 96.9% of equivalent location detectors, showed a range of gamma ≤ 1.0 and 99.9% showed a standard deviation of ≤ 0.5. For criteria of (3%,1 mm) and (2%,1 mm), these ranges decreased to 92.1% and 80.2% while the standard deviations decreased to 99.3% and 95.7%, respectively. The dose differences showed that 43.6%, 82.7%, and 91.4% of detectors had a dose range of ≤ 3.0%, ≤ 5.0%, and ≤ 6.0%, respectively. Standard deviations of dose differences were 1.5%, 2.5%, and 3.0% for 94.1%, 98.3%, and 99.5% of detectors, respectively. For the fleet of linacs, distributive PSQA yielded false results for 0.0%, 17.7%, and 33.0% of plans, equivalent to 1.2%, 3.5%, and 9.4% of detectors when using gamma criteria of (3%,2 mm), (3%,1 mm), or (2%,1 mm), respectively. These linacs could be considered matched for SBRT treatments and implement a distributive PSQA model when gamma analysis was completed with a criterion of (3%, 2 mm). For stricter criterion of (3%,1 mm) or (2%,1 mm), they did not meet the proposed metrics.
               
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