Author ORCID Identifier

0000-0001-6780-4458

Date of Graduation

8-2020

Document Type

Dissertation (PhD)

Program Affiliation

Medical Physics

Degree Name

Doctor of Philosophy (PhD)

Advisor/Committee Chair

Stephen F. Kry, PhD

Committee Member

David S. Followill, PhD

Committee Member

Rebecca M. Howell, PhD

Committee Member

Julianne M. Pollard-Larkin, PhD

Committee Member

Christine B. Peterson, PhD

Abstract

In radiation therapy, proper commissioning of the treatment planning system’s (TPS) dose calculation algorithm is critical because any errors in this process impact all treatment plans prepared in the system. Previously, TPS errors have been identified as a major cause for poor phantom irradiation performance, which may also mean that patients are treated suboptimally. The purpose of this work was to investigate the TPS beam modeling developed by the radiotherapy community to understand where inconsistencies may arise, which variables are most susceptible to variations, and in what way changing these variables can alter dose calculations.

Using the Imaging and Radiation Oncology Core (IROC) Houston phantom credentialing framework, common observational characteristics among poor-performing phantoms were identified based on retrospective analyses of prior head and neck phantom performance. Next, treatment plan complexity, as defined by 16 different metrics, was considered and evaluated for relationships with treatment delivery accuracy for over 300 phantom irradiations. A survey was developed and deployed to the radiotherapy community to understand how institutions with similar linear accelerators (Linacs) establish their clinical beam models. From this survey information, a sensitivity analysis was completed on several head and neck phantom plans for parameters vi modeling the multileaf collimator (MLC) characteristics in Eclipse and RayStation. Finally, previous phantom irradiation cases with concurrent survey results were investigated for relationships between beam modeling parameter choice and phantom performance accuracy.

The overwhelming majority of failing (>7% error) and poor performing (>5% error) irradiations were diagnosed as having systematic dose errors (>58% of cases). Treatment plan complexity was completely non-predictive of phantom performance (p>0.01, Bonferroni-corrected) and all correlations between complexity and performance accuracy were weak (less than ±0.30). The TPS beam modeling parameter survey generated 2818 responses from 642 institutions and revealed extensive variations in the modeling of MLC characteristics (leaf offset and transmission factor). These same parameters, namely Eclipse’s dosimetric leaf gap and RayStation’s MLC position offset, produced clinically significant dose changes when manipulated on 5 phantom treatment plans. Finally, the dosimetric leaf gap was associated with both poor-performing and failing phantom irradiations and correlated with TPS accuracy (r=0.397, p=0.048).

In conclusion, atypical beam modeling parameter values, specifically related to the representation of the MLC, are related to phantom performance and thus require careful attention in developing and performing quality assurance on the dose calculation.

Keywords

radiation therapy, phantom, treatment planning system, beam modeling, multileaf collimator, quality assurance, MLC, TPS

Available for download on Thursday, October 01, 2020

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