Event Title

Session 2C: Classification of proton treatment plans between SFUD, MFO and hybrid plans

Session Number

Session 2C: 2nd Presentation

Advisor(s)

Drs. Steven Laub and Aditya Panchal, Northwestern Medicine Chicago Proton Center

Location

Academic Pit

Start Date

26-4-2018 10:35 AM

End Date

26-4-2018 11:20 AM

Abstract

We developed a program that reads structure sets and dose grids from radiation treatment plans and outputs field-specific histograms of the number of voxels within the planning target volume that received dose. The program then normalizes each histogram to the percent volume of the target that received each field's contribution of the total dose. It then determines the number of Gaussian distributions in each histogram, which serves as an initial classification metric. The program also calculates additional metrics, including maximum dose in each distribution, the width of each dose distribution, and the rate at which the number of voxels decrease per change in dose. This data is compared to data from a standard Single­ Field Uniform Dose (SFUD) treatment plan and assessed for similarity. The program is able to classify hybrid treatment plans by assigning them a score based on calculated metrics that represent their correlation with a standard SFUD treatment plan. The program and percentage it outputs can aid in improved classification and differentiation of hybrid treatment plans to facilitate the precision of patient and target volume positioning.

Share

COinS
 
Apr 26th, 10:35 AM Apr 26th, 11:20 AM

Session 2C: Classification of proton treatment plans between SFUD, MFO and hybrid plans

Academic Pit

We developed a program that reads structure sets and dose grids from radiation treatment plans and outputs field-specific histograms of the number of voxels within the planning target volume that received dose. The program then normalizes each histogram to the percent volume of the target that received each field's contribution of the total dose. It then determines the number of Gaussian distributions in each histogram, which serves as an initial classification metric. The program also calculates additional metrics, including maximum dose in each distribution, the width of each dose distribution, and the rate at which the number of voxels decrease per change in dose. This data is compared to data from a standard Single­ Field Uniform Dose (SFUD) treatment plan and assessed for similarity. The program is able to classify hybrid treatment plans by assigning them a score based on calculated metrics that represent their correlation with a standard SFUD treatment plan. The program and percentage it outputs can aid in improved classification and differentiation of hybrid treatment plans to facilitate the precision of patient and target volume positioning.