Carl W Stanhope1,2, Douglas G Drake1, Jian Liang1, Markus Alber3,4, Matthias Söhn3, Charbel Habib1, Virgil Willcut5, Di Yan1. 1. Department of Radiation Oncology, William Beaumont Hospital, Royal Oak, MI, 48073, USA. 2. Department of Medical Physics, Wayne State University, Detroit, MI, 48202, USA. 3. ScientificRT GmbH, Munich, 81373, Germany. 4. Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, 61920, Germany. 5. Elekta AB, Stockholm, 113 57, Sweden.
Abstract
PURPOSE: A treatment planning/delivery QA tool using linac log files (LF) and Monte Carlo (MC) dose calculation is investigated as a standalone alternative to phantom-based patient-specific QA (ArcCHECK (AC)). METHODS: Delivering a variety of fields onto MapCHECK2 and ArcCHECK, diode sensitivity dependence on dose rate (in-field) and energy (primarily out-of-field) was quantified. AC and LF QAs were analyzed with respect to delivery complexity by delivering 12 × 12 cm static fields/arcs comprised of varying numbers of abutting sub-fields onto ArcCHECK. About 11 clinical dual-arc VMAT patients planned using Pinnacle's convolution-superposition (CS) were delivered on ArcCHECK and log file dose (LF-CS and LF-MC) calculated. To minimize calculation time, reduced LF-CS sampling (1/2/3/4° control point spacing) was investigated. Planned ("Plan") and LF-reconstructed CS and MC doses were compared with each other and AC measurement via statistical [mean ± StdDev(σ)] and gamma analyses to isolate dosimetric uncertainties and quantify the relative accuracies of AC QA and MC-based LF QA. RESULTS: Calculation and ArcCHECK measurement differed by up to 1.5% in-field due to variation in dose rate and up to 5% out-of-field. For the experimental segment-varying plans, despite CS calculation deviating by as much as 13% from measurement, Plan-MC and LF-MC doses generally matched AC measurement within 3%. Utilizing 1° control point spacing, 2%/2 mm LF-CS vs AC pass rates (97%) were slightly lower than Plan-CS vs AC pass rates (97.5%). Utilizing all log file samples, 2%/2 mm LF-MC vs AC pass rates (97.3%) were higher than Plan-MC vs AC (96.5%). Phantom-dependent, calculation algorithm-dependent (MC vs CS), and delivery error-dependent dose uncertainties were 0.8 ± 1.2%, 0.2 ± 1.1%, and 0.1 ± 0.9% respectively. CONCLUSION: Reconstructing every log file sample with no increase in computational cost, MC-based LF QA is faster and more accurate than CS-based LF QA. Offering similar dosimetric accuracy compared to AC measurement, MC-based log files can be used for treatment planning QA.
PURPOSE: A treatment planning/delivery QA tool using linac log files (LF) and Monte Carlo (MC) dose calculation is investigated as a standalone alternative to phantom-based patient-specific QA (ArcCHECK (AC)). METHODS: Delivering a variety of fields onto MapCHECK2 and ArcCHECK, diode sensitivity dependence on dose rate (in-field) and energy (primarily out-of-field) was quantified. AC and LF QAs were analyzed with respect to delivery complexity by delivering 12 × 12 cm static fields/arcs comprised of varying numbers of abutting sub-fields onto ArcCHECK. About 11 clinical dual-arc VMAT patients planned using Pinnacle's convolution-superposition (CS) were delivered on ArcCHECK and log file dose (LF-CS and LF-MC) calculated. To minimize calculation time, reduced LF-CS sampling (1/2/3/4° control point spacing) was investigated. Planned ("Plan") and LF-reconstructed CS and MC doses were compared with each other and AC measurement via statistical [mean ± StdDev(σ)] and gamma analyses to isolate dosimetric uncertainties and quantify the relative accuracies of AC QA and MC-based LF QA. RESULTS: Calculation and ArcCHECK measurement differed by up to 1.5% in-field due to variation in dose rate and up to 5% out-of-field. For the experimental segment-varying plans, despite CS calculation deviating by as much as 13% from measurement, Plan-MC and LF-MC doses generally matched AC measurement within 3%. Utilizing 1° control point spacing, 2%/2 mm LF-CS vs AC pass rates (97%) were slightly lower than Plan-CS vs AC pass rates (97.5%). Utilizing all log file samples, 2%/2 mm LF-MC vs AC pass rates (97.3%) were higher than Plan-MC vs AC (96.5%). Phantom-dependent, calculation algorithm-dependent (MC vs CS), and delivery error-dependent dose uncertainties were 0.8 ± 1.2%, 0.2 ± 1.1%, and 0.1 ± 0.9% respectively. CONCLUSION: Reconstructing every log file sample with no increase in computational cost, MC-based LF QA is faster and more accurate than CS-based LF QA. Offering similar dosimetric accuracy compared to AC measurement, MC-based log files can be used for treatment planning QA.
Authors: Michael Barnes; Dennis Pomare; Marcus Doebrich; Therese S Standen; Joshua Wolf; Peter Greer; John Simpson Journal: J Appl Clin Med Phys Date: 2022-06-09 Impact factor: 2.243
Authors: Philipp Szeverinski; Matthias Kowatsch; Thomas Künzler; Marco Meinschad; Patrick Clemens; Alexander F DeVries Journal: J Appl Clin Med Phys Date: 2021-06-20 Impact factor: 2.102