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A Flexible Radiobiological Tool for the Evaluation of Radiotherapy Treatment Plans

C Kabat1*, P Mavroidis2 , H Parenica1 , D Nicewonger1 , D Defoor3 , K Rasmussen1 , P Myers1 , D Saenz1 , N Kirby1 , S Stathakis1 , N Papanikolaou1 , (1) University of Texas HSC SA, San Antonio, TX, (2) Univ North Carolina, Chapel Hill, NC, (3) Texas Oncology - Longview, Tyler, TX


(Sunday, 7/14/2019) 4:00 PM - 5:00 PM

Room: Stars at Night Ballroom 4

Purpose: In modern radiation therapy, typically dose volume histograms (DVHs), isodose distributions, and physical dose indices are used in the evaluation for a treatment plan. However, when reviewing these plans radiobiological objectives for tumor control and normal tissue complications probabilities are usually indirectly estimated from clinical experience and knowledge. In this direction, a flexible and user-friendly application was devised to provide assistance in radiobiological evaluation for clinical use.

Methods: A graphical interface was developed using the MATLAB coding language. The application utilizes a set of dose and structure data (using the DICOM-RT protocol) to derive the dose matrices and DVHs of the relevant targets and organs at risk (OARs). Currently the Poisson model for tumors and the Lyman-Kutcher-Burman (LKB) and Relative Seriality models are used to calculate the tumor control and normal tissue complication probabilities (TCP and NTCP) The output of the application is the response probabilities of the different targets and OARs together with their biological effective uniform doses (BEUD), the overall control probability (when multiple targets are involved) PB, the overall complication probability (when multiple OARs are involved) PI, and the complication-free tumor control probability, Pâ‚Š, which is an index of the overall quality of the plan.

Results: The application can handle an unlimited amount of treatment plans for quick comparisons for institutional and multi-centric studies. The application was found compatible with the DICOM formats of all used treatment planning systems. Plots and charts are produced on-the-fly with TCP/NTCP/BEUD/Pâ‚Š results and comparisons in an interactive mode to help determine the best radiobiological plan or scenario possible for a patient.

Conclusion: Using this toolkit, physicians can establish comparisons between radiobiological effectiveness from different plans to effectively select the one that offers the optimal radiobiological response for the individual patient.

Funding Support, Disclosures, and Conflict of Interest: This work is partially supported by the Cancer Prevention & Research Institute of Texas Training Award. (RP170345)


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