Academic Journal

SU‐E‐T‐502: Initial Results of a Comparison of Treatment Plans Produced From Automated Prioritized Planning Method and a Commercial Treatment Planning System

التفاصيل البيبلوغرافية
العنوان: SU‐E‐T‐502: Initial Results of a Comparison of Treatment Plans Produced From Automated Prioritized Planning Method and a Commercial Treatment Planning System
المؤلفون: Tiwari, P, Hong, L, Apte, A, Yang, J, Mechalakos, J, Mageras, G, Hunt, M, Chen, Y, Deasy, J
المصدر: Medical Physics ; volume 42, issue 6Part20, page 3450-3450 ; ISSN 0094-2405 2473-4209
بيانات النشر: Wiley
سنة النشر: 2015
المجموعة: Wiley Online Library (Open Access Articles via Crossref)
الوصف: Purpose We developed an automated treatment planning system based on a hierarchical goal programming approach. To demonstrate the feasibility of our method, we report the comparison of prostate treatment plans produced from the automated treatment planning system with those produced by a commercial treatment planning system. Methods In our approach, we prioritized the goals of the optimization, and solved one goal at a time. The purpose of prioritization is to ensure that higher priority dose‐volume planning goals are not sacrificed to improve lower priority goals. The algorithm has four steps. The first step optimizes dose to the target structures, while sparing key sensitive organs from radiation. In the second step, the algorithm finds the best beamlet weight to reduce toxicity risks to normal tissue while holding the objective function achieved in the first step as a constraint, with a small amount of allowed slip. Likewise, the third and fourth steps introduce lower priority normal tissue goals and beam smoothing. We compared with prostate treatment plans from Memorial Sloan Kettering Cancer Center developed using Eclipse, with a prescription dose of 72 Gy. A combination of liear, quadratic, and gEUD objective functions were used with a modified open source solver code (IPOPT). Results Initial plan results on 3 different cases show that the automated planning system is capable of competing or improving on expert‐driven eclipse plans. Compared to the Eclipse planning system, the automated system produced up to 26% less mean dose to rectum and 24% less mean dose to bladder while having the same D95 (after matching) to the target. Conclusion We have demonstrated that Pareto optimal treatment plans can be generated automatically without a trial‐and‐error process. The solver finds an optimal plan for the given patient, as opposed to database‐driven approaches that set parameters based on geometry and population modeling.
نوع الوثيقة: article in journal/newspaper
اللغة: English
DOI: 10.1118/1.4924864
DOI: 10.1118/1.4924864/fullpdf
الاتاحة: http://dx.doi.org/10.1118/1.4924864
https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1118%2F1.4924864
http://onlinelibrary.wiley.com/wol1/doi/10.1118/1.4924864/fullpdf
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رقم الانضمام: edsbas.4B4C46C2
قاعدة البيانات: BASE