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An Ideal Planning Assistant Application for Planning Guidance and Patient Review in Radiotherapy

C Kabat1*, J Solis1 , T Schantz1 , B Graham1 , D Defoor2 , P Myers1 , N Kirby1 , K Rasmussen1 , D Saenz1 , W Jones1 , P Mavroidis3 , N Papanikolaou1 , S Stathakis1 , (1) University of Texas HSC SA, San Antonio, TX, (2) Texas Oncology - Longview, Tyler, TX ,(3) Univ North Carolina, Chapel Hill, NC


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

Room: Stars at Night Ballroom 4

Purpose: Intensity-modulated radiation therapy, rotational or helical delivery technologies have developed to focus on maximizing dose to target volume(s) while sparing healthy tissues. This is achieved by varying the dose distribution to surrounding healthy tissues in a guided way, which depends on organ type, physician constraints, and published tissue-dose tolerance criteria. Normally, dosimetrists optimize each patient’s plan trying to satisfy those objectives. Nevertheless, healthy tissues for which no explicit dosimetric constraints are defined during plan optimization might receive unnecessary high doses. To enhance plan development and reduce dose to healthy tissue an application was developed that provides dosimetrists and physicians a means to produce individualized ideal plans.

Methods: The application was developed using the Matlab language and it integrates patient CT sets with segmented structures and calculates an ideal theoretical dose distribution utilizing organ criteria and linear accelerator beam parameters. Dose modifications can be employed for each structure to determine an ideal dose cloud arrangement that conforms to the prescription while demonstrating its association to the dose constraints and the potential for OAR sparing. Thirty historical patient plans were reviewed, which includes head and neck, thorax, and prostate plans. This application was used to create new plans.

Results: The dosimetric comparison of the new plans with the historical ones was able to identify OARs with unnecessary doses that could have benefited from more dose constraints while also defining areas in plans that were difficult to spare while maintaining PTV coverage. Planning guidelines generated by the application were used in creating unique plans that required less optimization time and had similar if not preferred DVHs over the historical plans.

Conclusion: The application demonstrated the ability of quickly creating effective dose distributions while providing an outline defining which OARs or healthy tissues can benefit from greater dose sparing without impacting PTV coverage.

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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