Prediction of Radiation Therapy Dose for Lung Cancer IMRT Technique using Support Vector Regression Model

Optimal dose distribution in the treatment planning system (TPS) is crucial before being applied to radiotherapy patients. However, TPS still uses optimization methods that are time-consuming and user-dependent. This study aimed evaluate automatic prediction model, support vector regression (SVR), compare it with clinically planned of lung cancer Sixty patients treated intensity-modulated radiation therapy (IMRT) were used as objects this study. The target was evaluated based on conformity index (CI), homogeneity (HI). In contrast, mean maximum doses organs at risk (right lung, left heart, spinal cord). Statistical analysis performed using Wilcoxon test. A value <0.05 indicates a significant difference between two datasets. CI SVR clinical 1.154±0.003 1.181±0.136. HI for 0.075±0.016 0.083±0.030. test showed no statistically results. cardiac ( p =0.042), while other OARs did not show difference. strategies, except heart dose. model provides information about can be determine best technique use