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Complexity of VMAT MLC Sequences Planned with Eclipse TPS for Elekta Synergy Linac

A Usynin1*, C Ramsey2, (1) Thompson Cancer Survival Center-Sevier, Sevierville, TN, (2) Thompson Cancer Survival Center, Knoxville, TN

Presentations

(Saturday, 4/4/2020)   [Mountain Time (GMT-6)]

Purpose: To establish and characterize the relationship between the complexity of a given VMAT MLC sequence and the outcome of a phantom-based QA test characterized by the gamma index-based evaluation.

Methods: We retrospectively evaluated clinical VMAT plans devised with a relatively rare combination of the Eclipse TPS and an Elekta Synergy linac equipped with the MLCi head. The initial data were composed of 62 plans for which we computed an originally developed VMAT complexity metric and performed the phantom-based QA test. The computed values were graphically represented as a scatter plot revealing the relationship between the VMAT complexity and the QA test results.

Results: Three major groups of VMAT plans were revealed. The “Normal Complexity” group (n=46) was where the VMAT complexity was moderately correlated with the QA results at the same time exhibiting the gamma index percentage well below the clinical threshold (the group of well-accepted plans). The “High Complexity” group (n=7) was where the complexity metric was strongly correlated with the QA results and showed the high VMAT complexity and the gamma index percentage close to the clinical threshold (the nearly accepted plans). The ‘Sub-optimal QA” group (n=9) was where the gamma index percentage was close to the clinical threshold but the MLC complexity metric was relatively low, thus, revealing the plans where the choice of certain aspects of the performed QA procedure was likely sub-optimal.

Conclusion: We developed a metric characterizing the complexity of a VMAT MLC sequence. The complexity metric could serve as an initial assessment tool for predicting how accurately the VMAT MLC sequence would be delivered. The VMAT complexity metric coupled with the phantom-based QA result could identify such QA procedures that were performed in an inefficient manner for a given combination of the VMAT sequence and the dose detector.

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