SU-E-T-667: Accuracy of XiO Treatment Planning System in Predicting Lateral Penumbra for Different Air Gap and Compensator Thickness in Uniform Scanning Proton Therapy

2013 ◽  
Vol 40 (6Part21) ◽  
pp. 359-359
Author(s):  
S Rana ◽  
O Zeidan ◽  
E Ramirez ◽  
M Rains ◽  
J Gao ◽  
...  
Keyword(s):  
Treatment Planning ◽  
Proton Therapy ◽  
Air Gap ◽  
Planning System ◽  
Treatment Planning System ◽  
Uniform Scanning

scholarly journals [OA051] Toward a new treatment planning system accounting for in-vivo proton range verification in proton therapy

2018 ◽  
Vol 52 ◽  
pp. 21
Author(s):  
Liheng Tian ◽  
Georgios Dedes ◽  
Guillaume Landry ◽  
Florian Kamp ◽  
Katharina Niepel ◽  
...  
Keyword(s):  
Treatment Planning ◽  
Proton Therapy ◽  
Planning System ◽  
Treatment Planning System ◽  
New Treatment ◽  
Range Verification

scholarly journals Treatment planning for proton therapy: what is needed in the next 10 years?

2020 ◽  
Vol 93 (1107) ◽  
pp. 20190304 ◽  
Author(s):  
Hakan Nystrom ◽  
Maria Fuglsang Jensen ◽  
Petra Witt Nystrom
Keyword(s):  
Treatment Planning ◽  
Proton Therapy ◽  
Computational Thinking ◽  
Dose Calculation ◽  
Target Volume ◽  
Planning System ◽  
Treatment Planning System ◽  
Biological Efficiency ◽  
Dose Calculation Algorithms ◽  
Computerized Treatment

Treatment planning is the process where the prescription of the radiation oncologist is translated into a deliverable treatment. With the complexity of contemporary radiotherapy, treatment planning cannot be performed without a computerized treatment planning system. Proton therapy (PT) enables highly conformal treatment plans with a minimum of dose to tissues outside the target volume, but to obtain the most optimal plan for the treatment, there are a multitude of parameters that need to be addressed. In this review areas of ongoing improvements and research in the field of PT treatment planning are identified and discussed. The main focus is on issues of immediate clinical and practical relevance to the PT community highlighting the needs for the near future but also in a longer perspective. We anticipate that the manual tasks performed by treatment planners in the future will involve a high degree of computational thinking, as many issues can be solved much better by e.g. scripting. More accurate and faster dose calculation algorithms are needed, automation for contouring and planning is required and practical tools to handle the variable biological efficiency in PT is urgently demanded just to mention a few of the expected improvements over the coming 10 years.

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