PURPOSE: Advanced radiotherapy treatments require appropriate quality assurance (QA) to verify 3D dose distributions. Moreover, increase in patient numbers demand efficient QA-methods. In this study, a time efficient method that combines model-based QA and measurement-based QA was developed; i.e., the hybrid-QA. The purpose of this study was to determine the reliability of the model-based QA and to evaluate time efficiency of the hybrid-QA method. METHODS: Accuracy of the model-based QA was determined by comparison of COMPASS calculated dose with Monte Carlo calculations for heterogeneous media. In total, 330 intensity modulated radiation therapy (IMRT) treatment plans were evaluated based on the mean gamma index (GI) with criteria of 3%∕3mm and classification of PASS (GI ≤ 0.4), EVAL (0.4 < GI > 0.6), and FAIL (GI ≥ 0.6). Agreement between model-based QA and measurement-based QA was determined for 48 treatment plans, and linac stability was verified for 15 months. Finally, time efficiency improvement of the hybrid-QA was quantified for four representative treatment plans. RESULTS: COMPASS calculated dose was in agreement with Monte Carlo dose, with a maximum error of 3.2% in heterogeneous media with high density (2.4 g∕cm(3)). Hybrid-QA results for IMRT treatment plans showed an excellent PASS rate of 98% for all cases. Model-based QA was in agreement with measurement-based QA, as shown by a minimal difference in GI of 0.03 ± 0.08. Linac stability was high with an average GI of 0.28 ± 0.04. The hybrid-QA method resulted in a time efficiency improvement of 15 min per treatment plan QA compared to measurement-based QA. CONCLUSIONS: The hybrid-QA method is adequate for efficient and accurate 3D dose verification. It combines time efficiency of model-based QA with reliability of measurement-based QA and is suitable for implementation within any radiotherapy department.
PURPOSE: Advanced radiotherapy treatments require appropriate quality assurance (QA) to verify 3D dose distributions. Moreover, increase in patient numbers demand efficient QA-methods. In this study, a time efficient method that combines model-based QA and measurement-based QA was developed; i.e., the hybrid-QA. The purpose of this study was to determine the reliability of the model-based QA and to evaluate time efficiency of the hybrid-QA method. METHODS: Accuracy of the model-based QA was determined by comparison of COMPASS calculated dose with Monte Carlo calculations for heterogeneous media. In total, 330 intensity modulated radiation therapy (IMRT) treatment plans were evaluated based on the mean gamma index (GI) with criteria of 3%∕3mm and classification of PASS (GI ≤ 0.4), EVAL (0.4 < GI > 0.6), and FAIL (GI ≥ 0.6). Agreement between model-based QA and measurement-based QA was determined for 48 treatment plans, and linac stability was verified for 15 months. Finally, time efficiency improvement of the hybrid-QA was quantified for four representative treatment plans. RESULTS: COMPASS calculated dose was in agreement with Monte Carlo dose, with a maximum error of 3.2% in heterogeneous media with high density (2.4 g∕cm(3)). Hybrid-QA results for IMRT treatment plans showed an excellent PASS rate of 98% for all cases. Model-based QA was in agreement with measurement-based QA, as shown by a minimal difference in GI of 0.03 ± 0.08. Linac stability was high with an average GI of 0.28 ± 0.04. The hybrid-QA method resulted in a time efficiency improvement of 15 min per treatment plan QA compared to measurement-based QA. CONCLUSIONS: The hybrid-QA method is adequate for efficient and accurate 3D dose verification. It combines time efficiency of model-based QA with reliability of measurement-based QA and is suitable for implementation within any radiotherapy department.
Authors: X Ronald Zhu; Yupeng Li; Dennis Mackin; Heng Li; Falk Poenisch; Andrew K Lee; Anita Mahajan; Steven J Frank; Michael T Gillin; Narayan Sahoo; Xiaodong Zhang Journal: Cancers (Basel) Date: 2015-04-10 Impact factor: 6.639
Authors: Pascal Hauri; Sarah Verlaan; Shaun Graydon; Linda Ahnen; Stephan Klöck; Stephanie Lang Journal: J Appl Clin Med Phys Date: 2014-03-06 Impact factor: 2.102