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A Monte Carlo Based Dose Verification Tool for Gamma Knife Radiosurgery Treatment

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J Yuan

J Yuan*, J Sohn , C Cheng , B Wessels , A Kumar , D Mansur , M Machtay , University Hospitals Case Medical Center, Cleveland, OH

Presentations

SU-I-GPD-T-350 (Sunday, July 30, 2017) 3:00 PM - 6:00 PM Room: Exhibit Hall


Purpose: To develop a Monte Carlo (MC) based simulation tool for patient-specific dose verification and plan evaluation for Gamma Knife (GK) Perfexion radiosurgery treatment.

Methods: We have previously established a source model for MC simulations of the LGK PFX for the purpose of the treatment planning system (TPS) dose verification and plan evaluation. To make practical and effective use of the model in clinic, thorough commissioning procedures have been carried out to ensure the validity of the model parameters, such as the source-to-focus (STF) distance, the source solid angle. An efficient source particle sampling method has also been implemented to facilitate dose calculations for multi-target and multi-shot configurations in patient treatment plans. The dose algorithm depends on the CT image for density and material information in the MC calculations. However, in clinical most of the time the MRI image is solely used for target delineation and planning with tissue maximum ratio (TMR) dose algorithm. To incorporate this scenario into our tool, we create a head water phantom from the skull structure in the RTStruct Dicom format exported from the GK treatment planning system.

Results: The agreement between the MC calculation and TPS was very good for the homogenous phantom. The difference of the full width at half maximum (FWHM) of the profile was less than 1 mm except for the profile for 16 mm collimator along Z-axis (less than 2 mm). To make the tool easily usable clinically, we have developed a graphical user interface to facilitate the quality assurance (QA) procedure.

Conclusion: Our MC based dose algorithm is suitable for patient-specific dose verification for GK Perfexion radiosurgery treatments.


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