Hybrid 3D analytical linear energy transfer calculation algorithm based on precalculated data from Monte Carlo simulations

• Published in: Medical physics (Lancaster) Vol. 47; no. 2; p. 745
• Main Authors: Deng, Wei, Ding, Xiaoning, Younkin, James E, Shen, Jiajian, Bues, Martin, Schild, Steven E, Patel, Samir H, Liu, Wei
• Format: Journal Article
• Language: English
• Published: United States 01.02.2020
• Subjects: analytical calculation; linear energy transfer; proton therapy
• ISSN: 2473-4209
• DOI: 10.1002/mp.13934

The dose-averaged linear energy transfer (LET ) for intensity-modulated proton therapy (IMPT) calculated by one-dimensional (1D) analytical models deviates from more accurate but time-consuming Monte Carlo (MC) simulations. We developed a fast hybrid three-dimensional (3D) analytical LET calculation that is more accurate than 1D analytical model. We used the Geant4 MC code to generate 3D LET distributions of monoenergetic proton beams in water for all energies and used a customized error function to fit the LET lateral profiles at various depths to the MC simulation. The 3D LET calculation kernel was a lookup table of these fitted coefficients, and LET was determined directly from spot energies and voxel coordinates during analytical dose calculations. We validated our new method by comparing the calculated LET distributions to MC results using 3D Gamma index analysis with 3%/2 mm criteria in 12 patient geometries. The significance of the improvement in Gamma index analysis passing rates over the 1D analytical model was determined using the Wilcoxon rank-sum test. The passing rate of 3D Gamma analysis comparing LET distributions from the hybrid 3D method and the 1D method to MC simulations was significantly improved from 94.0% ± 2.5% to 98.0% ± 1.0% (P = 0.0003). The typical time to calculate dose and LET simultaneously using an Intel Xeon E5-2680 2.50 GHz workstation was approximately 2.5 min. Our new method significantly improved the LET calculation accuracy compared to the 1D method while maintaining significantly shorter calculation time even comparing with the GPU-based fast MC code.