A Comparative Study on Tissue Classification of Brain MR Images Using DIPY, SPM, and FSL Frameworks
Publish place: Iranian Journal of Medical Physics، Vol: 21، Issue: 2
Publish Year: 1403
نوع سند: مقاله ژورنالی
زبان: English
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JR_IJMP-21-2_002
تاریخ نمایه سازی: 6 خرداد 1403
Abstract:
Introduction: Complexity metrics have been suggested to characterize treatment plans based on machine parameters such as multileaf collimator (MLC) position. Several complexity metrics have been proposed and related to the Intensity-modulated radiation therapy (IMRT) quality assurance results. This study aims to evaluate aperture-based complexity metrics on MLC openings used in clinicaland establish a correlation between plan complexity and the gamma passing rate (GPR) for the IMRT plans.Material and Methods: We implemented the aperture-based complexity metric on MLC openings of the IMRT treatment plan for breast and central nervous system (CNS) cases . The modulation complexity score (MCS), the edge area metric (EAM), the converted area metric (CAM), the circumference/area (CPA), and the ratio monitor unit MU/Gy are evaluated in this study. The complexity score was calculated using Matlab. The MatriXX Evolution was used for dose verification. The dose distribution was analyzed using the OmniPro-I'mRT program and the gamma index was assessed using two criteria: ۳%/۳ mm and ۳%/۲ mm. The correlation between the calculated complexity score and the GPR is analyzed using SPSS.Results: The complexity score calculated by MCS, EAM, CAM, CPA, and MU/Gy shows breast plan is more complex than the CNS plan. The results of the correlation test of the complexity metric and GPR show that only the EAM metric shows a good correlation with GPR for both cases.Conclusion: EAM strongly correlates with the gamma pass rate. The MCS, CAM, CPA, and MU/Gy have a weak correlation with the GPR.
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Authors
Iman Azinkhah
Fintech in Medicine Research Center, Iran University of Medical Sciences, Tehran, Iran Medical physics department, Faculty of medicine, Iran university of medical sciences, Tehran, Iran
Mahdi Sadeghi
Fintech in Medicine Research Center, Iran University of Medical Sciences, Tehran, Iran Medical physics department, Faculty of medicine, Iran university of medical sciences, Tehran, Iran
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