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Gamma analysis of patient specific quality assurance by hybrid acceptance criterion method
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| A. Watcharawipha, I. Chitapanarux |
| Division of Radiation Oncology, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand , imjai@hotmail.com |
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Abstract: (568 Views) |
Background: Gamma analysis is an effective tool used to verify treatment plan accuracy with regard to patient specific quality assurance. In this method, accuracy is validated through the major parameters presented in the acceptance criterion (AC). The Hybrid AC (HAC) method has been proposed and validated via the Traditional AC (TAC) method of comparison. Materials and Methods: The performance of the HAC method was investigated through one-dimensional (1D) relative dose profile and clinical planar dose distribution. By employing the HAC method, Gamma values were observed at different regions of the profile as well as at the different treatment sites of clinical planar dose distribution. Both results were compared by employing the TAC method, but only planar dose distribution was analyzed by 95% confidence interval of statistics. Results: The results of the HAC method indicate higher Gamma values at the penumbra of the dose profile when compared with the results of the TAC method. In low dose and high dose areas, both methods produced comparable results. In terms of planar dose distribution, the proposed method demonstrated a higher degree of sensitivity than the TAC method by indicating low values for the Gamma passing rate at all treatment sites. Conclusion: The HAC method could effectively increase the sensitivity of the tool at a high dose gradient of planar dose distribution, whereas it had no impact on the area of the low dose gradient. Therefore, this method could be an alternative option for evaluation of treatment planning accuracy in clinical practice. |
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| Keywords: Gamma index, gamma analysis, patient specific quality assurance, acceptance criterion, dose distribution. |
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Full-Text [PDF 1049 kb]
(137 Downloads)
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Type of Study: Original Research |
Subject:
Radiation Biology
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