4.6 Article

Optimization of Monte Carlo particle transport parameters and validation of a novel high throughput experimental setup to measure the biological effects of particle beams

Journal

MEDICAL PHYSICS
Volume 44, Issue 11, Pages 6061-6073

Publisher

WILEY
DOI: 10.1002/mp.12568

Keywords

high throughput experiments; Monte Carlo simulations; protons; relative biological effectiveness

Funding

  1. Department of Scientific Publications of The University of Texas MD Anderson Cancer Center
  2. Sister Institution Network Funds (SINF) grant titled The Future of Particle Therapy: Physics and Biology of Light Ions from MDAnderson Cancer Center, Global Academic Programs

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PurposeAccurate modeling of the relative biological effectiveness (RBE) of particle beams requires increased systematic invitro studies with human cell lines with care towards minimizing uncertainties in biologic assays as well as physical parameters. In this study, we describe a novel high-throughput experimental setup and an optimized parameterization of the Monte Carlo (MC) simulation technique that is universally applicable for accurate determination of RBE of clinical ion beams. Clonogenic cell-survival measurements on a human lung cancer cell line (H460) are presented using proton irradiation. MethodsExperiments were performed at the Heidelberg Ion Therapy Center (HIT) with support from the Deutsches Krebsforschungszentrum (DKFZ) in Heidelberg, Germany using a mono-energetic horizontal proton beam. A custom-made variable range selector was designed for the horizontal beam line using the Geant4 MC toolkit. This unique setup enabled a high-throughput clonogenic assay investigation of multiple, well defined dose and linear energy transfer (LETs) per irradiation for human lung cancer cells (H460) cultured in a 96-well plate. Sensitivity studies based on application of different physics lists in conjunction with different electromagnetic constructors and production threshold values to the MC simulations were undertaken for accurate assessment of the calculated dose and the dose-averaged LET (LETd). These studies were extended to helium and carbon ion beams. ResultsSensitivity analysis of the MC parameterization revealed substantial dependence of the dose and LETd values on both the choice of physics list and the production threshold values. While the dose and LETd calculations using FTFP_BERT_LIV, FTFP_BERT_EMZ, FTFP_BERT_PEN and QGSP_BIC_EMY physics lists agree well with each other for all three ions, they show large differences when compared to the FTFP_BERT physics list with the default electromagnetic constructor. For carbon ions, the dose corresponding to the largest LETd value is observed to differ by as much as 78% between FTFP_BERT and FTFP_BERT_LIV. Furthermore, between the production threshold of 700m and 5m, proton dose varies by as much as 19% corresponding to the largest LETd value sampled in the current investigation. Based on the sensitivity studies, the FTFP_BERT physics list with the low energy Livermore electromagnetic constructor and a production threshold of 5m was employed for determining accurate dose and LETd. The optimized MC parameterization results in a different LETd dependence of the RBE curve for 10% SF of the H460 cell line irradiated with proton beam when compared with the results from a previous study using the same cell line. When the MC parameters are kept consistent between the studies, the proton RBE results agree well with each other within the experimental uncertainties. ConclusionsA custom high-throughput, high-accuracy experimental design for accurate invitro cell survival measurements was employed at a horizontal beam line. High sensitivity of the physics-based optimization establishes the importance of accurate MC parameterization and hence the conditioning of the MC system on a case-by-case basis. The proton RBE results from current investigations are observed to agree with a previous measurement made under different experimental conditions. This establishes the consistency of our experimental findings across different experiments and institutions.

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