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Automation of the Treatment Planning Process for IMRT Prostate Cases

P Kapoor1,2*, (1) Virginia Commonwealth University, (2)Hunter Holmes McGuire Veterans Affairs Medical Center, Richmond, VA


(Sunday, 7/12/2020)   [Eastern Time (GMT-4)]

Room: AAPM ePoster Library

Purpose: To introduce a solution that standardizes and improves the technique, quality, and efficiency for IMRT prostate treatment planning.

Methods: Treatment planning with the IMRT technique for prostate cancer though appears simple but takes up a considerable amount of time for the planners to create a good plan. There is a fair amount of consistency in the achievable dose coverage but a planner may approach the task with different planning techniques.
A good planning technique uses non-conflicting constraints; rings-structures to confine 50% dose-spillage; hotspots inside the PTV, etc. to improve plan quality and reduce monitor-units (MUs). Firstly, we implemented the AAPM-TG-263 recommendations on the standardization of structure nomenclature in our clinic. Standardizing nomenclature laid the foundation for building automated scripts for treatment planning using Pinnacle v9.8’s scripting library. The script is intended to automate the steps that are performed manually by the planner such as defining beam-angles, plan name, dose-grid, prescription, creating optimization structures, optimization objectives and parameters, etc. To test the value of the automated method over the manual method, 10 plans each were evaluated and total MUs; the average time spent by the planner was compared.

Results: The use of automated script reduced the number of re-plans from 20% to 1%. The average time spent by the planner was reduced by approx. 50-70%. The use of scripts for treatment planning has improved our plan-quality and reduced the total MUs per plan. The inter-user variability in the planning technique is minimal and we can achieve consistent dose-distribution. The t-test showed a statistically significant difference in MUs between the automated and manual methods (p-value=0.00402).

Conclusion: Standardization is key to improve efficiency, automate workflow and processes in a busy clinic. Implementing scripting tools in our workflow proved to be successful in improving plan quality and reduced variability in dose-distributions among planners.


Treatment Planning, Intensity Modulation, Treatment Techniques


TH- External Beam- Photons: Treatment planning using machine learning/Knowledge Based Planning/automation

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