Treatment plan prescreening for patient-specific quality assurance measurements using independent Monte Carlo dose calculations

Abstract

PurposeThis study proposes a method to identify plans that failed patient-specific quality assurance (QA) and attempts to establish a criterion to prescreen treatment plans for patient-specific QA measurements with independent Monte Carlo dose calculations.Materials and methodsPatient-specific QA results measured with an ArcCHECK diode array of 207 patients (head and neck: 25; thorax: 61; abdomen: 121) were retrospectively analyzed. All patients were treated with the volumetric modulated arc therapy (VMAT) technique and plans were optimized with a Pinnacle v16.2 treatment planning system using an analytical algorithm-based dose engine. Afterwards, phantom verification plans were designed and recalculated by an independent GPU-accelerated Monte Carlo (MC) dose engine, ArcherQA. Moreover, sensitivity and specificity analyzes of gamma passing rates between measurements and MC calculations were carried out to show the ability of MC to monitor failing plans (ArcCHECK 3%/3 mm,<90%), and attempt to determine the appropriate threshold and gamma passing rate criterion utilized by ArcherQA to prescreen treatment plans for ArcCHECK measurements. The receiver operator characteristic (ROC) curve was also utilized to characterize the performance of different gamma passing rate criterion used by ArcherQA.ResultsThe thresholds for 100% sensitivity to detect plans that failed patient-specific QA by independent calculation were 97.0%, 95.4%, and 91.0% for criterion 3%/3 mm, 3%/2 mm, and 2%/2 mm, respectively, which corresponded to specificities of 0.720, 0.528, and 0.585, respectively. It was shown that the 3%/3 mm criterion with 97% threshold for ArcherQA demonstrated perfect sensitivity and the highest specificity compared with other criteria, which may be suitable for prescreening treatment plans treated with the investigated machine to implement measurement-based patient-specific QA of patient plans. In addition, the area under the curve (AUC) calculated from ROC analysis for criterion 3%/3 mm, 3%/2 mm, and 2%/2 mm used by ArcherQA were 0.948, 0.924, and 0.929, respectively.ConclusionsIndependent dose calculation with the MC-based program ArcherQA has potential as a prescreen treatment for measurement-based patient-specific QA. AUC values (>0.9) showed excellent classification accuracy for monitoring failing plans with independent MC calculations.

Sensitivity and specificity of secondary dose calculation for head and neck treatment plans

“…Xu et al suggested independent dose calculation to be used for screening plans that need to be measured. 15 The measurement-based QA approach failed to reliably detect errors related to density irregularities applied to the patient CT and some of the beam modeling errors affecting small field output factors and penumbra. All errors connected to density issues cannot be detected when the plan is copied to the phantom for calculation.…”

“…Xu et al. suggested independent dose calculation to be used for screening plans that need to be measured 15 …”

“…An overview of products and guidance on commissioning and utilizing a secondary monitor unit (MU) check program was given in a recent task group report 13 . While the report focuses primarily on point‐dose/MU checks, programs now typically allow for a three‐dimensional dose calculation on the patient anatomy and a comparison of dose maps or assessment of DVH parameters 14,15 …”

“…as one systematic way to obtain those thresholds for IMRT plan‐specific QA 16 . It was since then applied to different QA systems 3,5,15,17 . Unlike other methods, ROC analysis is performed on a dataset of acceptable and unacceptable plans and derives decision thresholds by maximizing the sensitivity and specificity of a decision criterion.…”

“…13 While the report focuses primarily on pointdose/MU checks, programs now typically allow for a three-dimensional dose calculation on the patient anatomy and a comparison of dose maps or assessment of DVH parameters. 14,15 Decision thresholds are important for users to identify whether a plan is acceptable for irradiation or whether the plan will fail to lead to the desired clinical outcome. The criteria to apply, depend on the QA tool, evaluation methodology and workflow details, and are usually derived individually by institutions.…”