SU‐E‐T‐430: Planning and Dosimetric Comparison of the Gamma Knife Convolution and TMR 10 Algorithms - Cates, J; Drzymala, R; Izaguirre, E; Sun, B (Medical Physics, 2013)
Purpose: To compare the dose distributions for identical treatment plans calculated by the Gamma Knife TMR 10 and convolution algorithms and measured with film dosimetry. Methods: An anthropomorphic head phantom was CT imaged with EBT2 film placed between each of seven axial sections. The resulting data set was used to plan three 16mm collimated targets on the Gamma Knife Perfexion, with each target centered on a film plane. Target 1 was placed within a homogeneous region while Targets 2 and 3 were placed in heterogeneous regions, i.e. tissue‐air and bone‐tissue interfaces, respectively. Plans using the same targets were made using both the TMR 10 and convolution algorithms. The prescription was delivered to the phantom using the TMR 10 treatment plans after which the convolution treatment plans were adjusted to Result in identical treatment times, thus ensuring identical dose delivery. Film dosimetry was done to determine actual dose delivered at target center and was compared to the predicted dose for each algorithm. Results: While there was strong correlation between both algorithms, the convolution algorithm predicted a higher delivered maximum dose than TMR 10, up to 2.5% higher in homogeneous tissue and up to 7% near an air cavity. Film dosimetry results were consistent with the convolution algorithm predictions, with an error of less than three percent. Conclusion: The Gamma Knife convolution algorithm predicts delivered dose to a clinically acceptable level, which was confirmed by film dosimetry. However, film in an anthropomorphic head phantom may not be adequate to measure the most significant differences between the two algorithms. Precise stereotactic treatments will require precise dosimetry, and a phantom developed specifically with Gamma Knife geometry in mind may be necessary to fully characterize the dosimetry at anatomy interfaces.