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A Graphical User Interface (GUI) Toolkit Created for Multi-Phase Biological Effective Dose (BED) Calculations Including Statistical Analyses

K Kauweloa

K Kauweloa1,2*, A Gutierrez1,2 , S Stathakis1,2 , N Papanikolaou1,2 , P Mavroidis3 , (1) University of Texas HSC SA, San Antonio, TX, (2) Cancer Therapy and Research Center, San Antonio, TX, (3) University of North Carolina, Chapel Hill, NC


SU-E-P-6 (Sunday, July 12, 2015) 3:00 PM - 6:00 PM Room: Exhibit Hall

Purpose:There is growing interest amongst clinics in applying the biological effective dose (BED) to their treatment plan evaluations, as well as potential optimizations due to its stronger correlation with radiobiological effects. An approximate, multi-phase biological effective dose (BEDA) equation was introduced in order to simplify BED calculations using many current treatment planning systems (TPS). The purpose of this work is to create a MATLAB graphical user interface (GUI) in order to determine the accuracy and precision of BEDA in common clinical treatments.

Methods:A number of algorithms were written in order to read exported treatment plans from the TPS Pinnacle. Those algorithms were then tested and compared with the results on Pinnacle in order to determine its accuracy. BED algorithms were then created in order to calculate the BEDT and BEDA distributions. The algorithms for the DVH statistics, the Bland-Altman Analysis, and the Percent Error were written and added to this GUI in order to study the accuracy and precision of BEDA.

Results:When comparing the DVH results from the created MATLAB GUI to those from Pinnacle, there was less than a 1% difference in the dose distribution statistics such as the maximum, minimum, mean, and standard deviation for the dose in the specific region of interest. The amount of time needed to calculate the BED distributions ranged anywhere from 5 to 90 seconds due to its dependence on the size of the dose distribution matrix.

Conclusion:Due to the dose distribution accuracy, it is safe to use this MATLAB GUI toolkit to study the approximate BED calculation method. It can also be used to analyze patient treatment plans using the true BED distributions and the biological effective dose volume histograms (BEDVHs). In addition, further studies can be performed in determining BED constraints for different organs and endpoints.

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