Impact of multi-leaf collimator positioning accuracy on quality control of volumetric modulation arc therapy plan for cervical cancer treated with Elekta linear accelerator / 南方医科大学学报
Journal of Southern Medical University
; (12): 1089-1094, 2022.
Article
en Zh
| WPRIM
| ID: wpr-941046
Biblioteca responsable:
WPRO
ABSTRACT
OBJECTIVE@#To investigate the influence of positioning accuracy of the multi-leaf collimators (MLC) on the passing rate of the plan dose verification for volumetric modulation arc therapy (VMAT) of cervical cancer using an Elekta linear accelerator.@*METHODS@#The dose distributions were measured using Sun Nuclear's Mapcheck and Arccheck semiconductors matrix before and after MLC calibration in30 cervical cancer patients undergoing VMAT. Dosimetric comparisons were performed with 2D and 3D gamma passing rates of 3%, 3 mm and 2%, and 2 mm. The 3D gamma distribution was reconstructed with respect to the patient's anatomy using 3DVH software to evaluate the possible influence of MLC positioning accuracy.@*RESULTS@#Before and after MLC calibration, the gamma passing rates of Mapcheck were (88.80±1.81)% and (99.25 ± 0.53)% under 3% and 3 mm standard, respectively, with an average increase of 10.45%. The corresponding gamma passing rates of Arccheck were (87.61±1.98)% and (98.13±0.99)%, respectively, with an average increase of 10.52%. The gamma passing rates of 3DVH were (89.87±2.28)% and (98.3±1.15)%, respectively, with an average increase of 8.43%.@*CONCLUSION@#The MLC positioning accuracy is one of the main factors influencing dosimetric accuracy of VMAT for cervical cancer. The application of Autocal software facilitates MLC calibration and improves the accuracy and safety of VMAT delivery for cervical cancer.
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WPRIM
Asunto principal:
Aceleradores de Partículas
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Control de Calidad
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Dosificación Radioterapéutica
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Planificación de la Radioterapia Asistida por Computador
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Neoplasias del Cuello Uterino
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Radioterapia de Intensidad Modulada
Límite:
Female
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Humans
Idioma:
Zh
Revista:
Journal of Southern Medical University
Año:
2022
Tipo del documento:
Article