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Python Scripting to Identify Target Grouping Optimizations for Multiple Metastasis Treatment Planning

D Johnson1*, Z Xia2, (1) The University of Kansas Medical Center, Kansas City, KS, (2) University of Kansas Medical Center, Overland Park, KS

Presentations

PO-GePV-T-410 (Sunday, 7/10/2022)   [Eastern Time (GMT-4)]

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Purpose: Cranial radiosurgery treatment planning has traditionally entailed one target per isocenter. In cases of multiple targets, treatment efficiency has been increased with the introduction of techniques that enable the treatment of multiple targets per isocenter. Establishing the isocenter for a group of targets maybe limited by the geometric accuracies of the patient setup. Optimal target groups minimize the number of isocenters used while maintaining a clinically acceptable target-to-isocenter distance. The goal of the script optimization is to establish groupings more efficient than those selected by ‘educated-guess’.

Methods: A python script was developed to optimize target grouping for the BrainLab MME TPS. Each target’s coordinates were exported from the TPS for input into the script. The script assigns targets to a group if the distance between any two of them is less than 10 cm. The resulting distance between a target and the group isocenter will be no greater than 5 cm. This distance from isocenter was determined to be less than that resulting in an uncertainty of greater than 1mm. Targets beyond the 10 cm diameter of a group are placed into a second group.

Results: 10 clinical cases of SRS patients within multiple metastases were selected, and each patient’s lesions’ coordinators were imported to the python script. The groups established by the script optimization are compared to those clinically utilized. The size limited groups are compared to those established during clinical treatment planning.

Conclusion: As each additional isocenter used during treatment can increase patient time-on-machine by 30 min, the minimization of isocenters safely increases efficiency. Online Python compilers are free, easily accessible, and user friendly. This Python script can be used to help establish groupings for multi-met SRS planning.

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