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JOURNAL ARTICLE

End-to-end testing of automatic plan optimization using RayStation scripting for hypofractionated multimetastatic brain stereotactic radiosurgery

Eun Young Han, Gwe-Ya Kim, Neal Rebueno, Debra N Yeboa, Tina M Briere
Medical Dosimetry: Official Journal of the American Association of Medical Dosimetrists 2019 January 14
30655170
For external beam stereotactic radiosurgery of multiple brain metastatic lesions, it is difficult to select optimal treatment isocenters because the orientation and volume of each planning target volume (PTV) and its proximity to critical structures are unique for each patient. The RayStation treatment planning system offers Python-based scripting to optimize the placement of the treatment isocenter by comparing scenario-based plans. This can improve the plan quality by reducing the dose to the normal brain and increasing planning efficiency. The purpose of the current study was to compare the isocenter-optimized plans generated by RayStation with clinical plans created by the Pinnacle treatment planning system and to validate the RayStation treatment planning and delivery with end-to-end testing. Ten patient plans were automatically regenerated using the script in RayStation. For each patient, 4 plans with 4 different types of isocenters were generated: (1) 2 separate isocenters at the PTV centroids, (2) a single isocenter at the mid-point of 2 centroids, (3) a single isocenter at PTV1, and (4) a single isocenter at PTV2. The best plans were compared with paired Pinnacle plans using plan quality parameters, including normal brain volume excluding PTVs receiving 4 Gy (V4Gy ), normal brain volume excluding PTVs receiving 12 Gy (V12Gy ), maximum dose to the brainstem, homogeneity index, conformity indices, gradient index of each PTV, and monitor units per fraction. All plans were verified with a cylindrical quality assurance phantom, and end-to-end testing was performed with an anthropomorphic head phantom with a radiochromic film. The script was executed within 5-6 minutes to generate 4 scenario-based automatic plans. The homogeneity index and conformity indices showed small but statistically significant improvement with the RayStation plans. The gradient index (3.9 ± 0.9 for Pinnacle and 3.5 ± 0.6 for RayStation, p = 0.04) was also more favorable in the RayStation plans. V12Gy was significantly reduced by 13% and V4Gy was reduced by 5%. The total monitor units per fraction was significantly reduced by 20% for the RayStation plans. Plan optimization time using RayStation was reduced by 64%. The measured doses at each PTV centroid agreed within 3%, and all RayStation plans passed quality assurance verification tests. Scenario-based automatic plan generation using Python scripting helps identify an optimal treatment isocenter to reduce the dose to the normal brain and improve planning efficiency. RayStation plans provided better plan quality, especially lower doses to the normal brain, than Pinnacle plans. Thus, RayStation is a suitable planning modality for hypofractionated stereotactic radiosurgery for multiple brain metastases.

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