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Featured researches published by R Taleei.


Scientific Reports | 2015

Spatial mapping of the biologic effectiveness of scanned particle beams: towards biologically optimized particle therapy

Fada Guan; Lawrence Bronk; U Titt; Steven H. Lin; Dragan Mirkovic; M Kerr; X. Ronald Zhu; Jeffrey Dinh; Mary Sobieski; Clifford Stephan; C Peeler; R Taleei; Radhe Mohan; David R. Grosshans

The physical properties of particles used in radiation therapy, such as protons, have been well characterized, and their dose distributions are superior to photon-based treatments. However, proton therapy may also have inherent biologic advantages that have not been capitalized on. Unlike photon beams, the linear energy transfer (LET) and hence biologic effectiveness of particle beams varies along the beam path. Selective placement of areas of high effectiveness could enhance tumor cell kill and simultaneously spare normal tissues. However, previous methods for mapping spatial variations in biologic effectiveness are time-consuming and often yield inconsistent results with large uncertainties. Thus the data needed to accurately model relative biological effectiveness to guide novel treatment planning approaches are limited. We used Monte Carlo modeling and high-content automated clonogenic survival assays to spatially map the biologic effectiveness of scanned proton beams with high accuracy and throughput while minimizing biological uncertainties. We found that the relationship between cell kill, dose, and LET, is complex and non-unique. Measured biologic effects were substantially greater than in most previous reports, and non-linear surviving fraction response was observed even for the highest LET values. Extension of this approach could generate data needed to optimize proton therapy plans incorporating variable RBE.


Medical Physics | 2015

Analysis of the track- and dose-averaged LET and LET spectra in proton therapy using the GEANT4 Monte Carlo code

Fada Guan; C Peeler; Lawrence Bronk; Changran Geng; R Taleei; S Randeniya; S Ge; Dragan Mirkovic; David R. Grosshans; Radhe Mohan; U Titt

PURPOSE The motivation of this study was to find and eliminate the cause of errors in dose-averaged linear energy transfer (LET) calculations from therapeutic protons in small targets, such as biological cell layers, calculated using the geant 4 Monte Carlo code. Furthermore, the purpose was also to provide a recommendation to select an appropriate LET quantity from geant 4 simulations to correlate with biological effectiveness of therapeutic protons. METHODS The authors developed a particle tracking step based strategy to calculate the average LET quantities (track-averaged LET, LETt and dose-averaged LET, LETd) using geant 4 for different tracking step size limits. A step size limit refers to the maximally allowable tracking step length. The authors investigated how the tracking step size limit influenced the calculated LETt and LETd of protons with six different step limits ranging from 1 to 500 μm in a water phantom irradiated by a 79.7-MeV clinical proton beam. In addition, the authors analyzed the detailed stochastic energy deposition information including fluence spectra and dose spectra of the energy-deposition-per-step of protons. As a reference, the authors also calculated the averaged LET and analyzed the LET spectra combining the Monte Carlo method and the deterministic method. Relative biological effectiveness (RBE) calculations were performed to illustrate the impact of different LET calculation methods on the RBE-weighted dose. RESULTS Simulation results showed that the step limit effect was small for LETt but significant for LETd. This resulted from differences in the energy-deposition-per-step between the fluence spectra and dose spectra at different depths in the phantom. Using the Monte Carlo particle tracking method in geant 4 can result in incorrect LETd calculation results in the dose plateau region for small step limits. The erroneous LETd results can be attributed to the algorithm to determine fluctuations in energy deposition along the tracking step in geant 4. The incorrect LETd values lead to substantial differences in the calculated RBE. CONCLUSIONS When the geant 4 particle tracking method is used to calculate the average LET values within targets with a small step limit, such as smaller than 500 μm, the authors recommend the use of LETt in the dose plateau region and LETd around the Bragg peak. For a large step limit, i.e., 500 μm, LETd is recommended along the whole Bragg curve. The transition point depends on beam parameters and can be found by determining the location where the gradient of the ratio of LETd and LETt becomes positive.


Medical Physics | 2015

WE-EF-BRA-05: Experimental Design for High-Throughput In-Vitro RBE Measurements Using Protons, Helium and Carbon Ions

Fada Guan; U Titt; D Patel; Lawrence Bronk; R Taleei; C Peeler; Dragan Mirkovic; David R. Grosshans; Oliver Jäkel; Radhe Mohan

Purpose: To design and validate experimental setups for investigation of dose and LET effects in cell kill for protons, helium and carbon ions, in high throughput and high accuracy cell experiments. Methods: Using the Geant4 Monte Carlo toolkit, we designed 3 custom range compensators to simultaneously expose cancer cells to different doses and LETs from selected portions of pristine ion beams from the entrance to points just beyond the Bragg peak. To minimize the spread of LET, we utilized mono-energetic uniformly scanned beams at the HIT facility with support from the DKFZ. Using different entrance doses and LETs, a matrix of cell survival data was acquired leading to a specific RBE matrix. We utilized the standard clonogenic assay for H460 and H1437 lung-cancer cell lines grown in 96-well plates. Using these plates, the data could be acquired in a small number of exposures. The ion specific compensators were located in a horizontal beam, designed to hold two 96-wells plates (12 columns by 8 rows) at an angle of 30o with respect to the beam direction. Results: Using about 20 hours of beam time, a total of about 11,000 wells containing cancer cells could be irradiated. The H460 and H1437 cell lines exhibited a significant dependence on LET when they were exposed to comparable doses. The results were similar for each of the investigated ion species, and indicate the need to incorporate RBE into the ion therapy planning process. Conclusion: The experimental design developed is a viable approach to rapidly acquire large amounts of accurate in-vitro RBE data. We plan to further improve the design to achieve higher accuracy and throughput, thereby facilitating the irradiation of multiple cell types. The results are indicative of the possibility to develop a new degree of freedom (variable RBE) for future clinical ion therapy optimization. Work supported by the Sister Institute Network Fund (SINF), University of Texas MD Anderson Cancer Center.


Medical Physics | 2015

TU-EF-304-09: Quantifying the Biological Effects of Therapeutic Protons by LET Spectrum Analysis

Fada Guan; Lawrence Bronk; M Kerr; U Titt; X Wang; R Taleei; C Peeler; D Patel; Dragan Mirkovic; David R. Grosshans; Radhe Mohan

Purpose: To correlate in vitro cell kill with linear energy transfer (LET) spectra using Monte Carlo simulations and knowledge obtained from previous high-throughput in vitro proton relative biological effectiveness (RBE) measurements. Methods: The Monte Carlo simulation toolkit Geant4 was used to design the experimental setups and perform the dose, dose-averaged LET, and LET spectra calculations. The clonogenic assay was performed using the H460 lung cancer cell line in standard 6-well plates. Using two different experimental setups, the same dose and dose-averaged LET (12.6 keV/µm) was delivered to the cell layer; however, each respective energy or LET spectrum was different. We quantified the dose contributions from high-LET (≥10 keV/µm, threshold determined by previous RBE measurements) events in the LET spectra separately for these two setups as 39% and 53%. 8 dose levels with 1 Gy increments were delivered. The photon reference irradiation was performed using 6 MV x-rays from a LINAC. Results: The survival curves showed that both proton irradiations demonstrated an increased RBE compared to the reference photon irradiation. Within the proton-irradiated cells, the setup with 53% dose contribution from high-LET events exhibited the higher biological effectiveness. Conclusion: The experimental results indicate that the dose-averaged LET may not be an appropriate indicator to quantify the biological effects of protons when the LET spectrum is broad enough to contain both low- and high-LET events. Incorporating the LET spectrum distribution into robust intensity-modulated proton therapy optimization planning may provide more accurate biological dose distribution than using the dose-averaged LET. NIH Program Project Grant 2U19CA021239-35


Medical Physics | 2014

SU-E-T-47: Application of the Repair-Misrepair-Fixation RBE Model to Describe the Results of High Resolution Proton Irradiation Cell Survival Experiments

C Peeler; R Taleei; Fada Guan; L Bronk; David R. Grosshans; Dragan Mirkovic; U Titt; Radhe Mohan

PURPOSE To develop a system to rapidly and accurately calculate RBE with the repair-misrepair-fixation (RMF) model for proton therapy data sets and to evaluate its effectiveness in modeling RBE for cell survival experiments performed with the H460 cell line for a range of proton LET. METHODS A system for using the Monte Carlo Damage Simulation (MCDS) software with high performance computing was developed. Input for the MCDS software for a range of proton energies in increments of 0.1 MeV was generated and simulated. The output data were then used to determine doseaveraged quantities for the RMF model based on equivalently binned proton energy spectra. The method was applied to calculate RBE at 50% survival for experimental cell survival data. Experimental data were obtained using a system which allowed for the accumulation of cell survival data at known values of dose-averaged proton LETs at a range of doses. RBE was calculated based directly on a Cs-137 reference experiment and, additionally, according to fitted values of the θ and κ terms of the RMF model. RESULTS Dose-averaged RMF model quantities were calculated using the HPC system. Compared to experimental RBE determined using a Cs-137 irradiation as a reference, the RBE from the model differed by at most 49%. RBE based on the fitted values of θ and κ differed by at most 18% for the highest LET. CONCLUSION A system for rapidly generating data necessary to calculate RBE with the RMF model has been developed. For the H460 cell line, the RMF model could not reproduce the experimentally determined RBE based solely on the photon reference data. Fitting of the θ and κ terms of the RMF model indicates that their values increase for proton LET exceeding approximately 10 keV/µm. NIH Program Project Grant P01CA021239.


Medical Physics | 2014

TH-A-19A-05: Modeling Physics Properties and Biologic Effects Induced by Proton and Helium Ions

R Taleei; U Titt; C Peeler; Fada Guan; Dragan Mirkovic; David R. Grosshans; Radhe Mohan

PURPOSE Currently, proton and carbon ions are used for cancer treatment. More recently, other light ions including helium ions have shown interesting physical and biological properties. The purpose of this work is to study the biological and physical properties of helium ions (He-3) in comparison to protons. METHODS Monte Carlo simulations with FLUKA, GEANT4 and MCNPX were used to calculate proton and He-3 dose distributions in water phantoms. The energy spectra of proton and He-3 beams were calculated with high resolution for use in biological models. The repair-misrepairfixation (RMF) model was subsequently used to calculate the RBE. RESULTS The proton Bragg curve calculations show good agreement between the three general purpose Monte Carlo codes. In contrast, the He-3 Bragg curve calculations show disagreement (for the magnitude of the Bragg peak) between FLUKA and the other two Monte Carlo codes. The differences in the magnitude of the Bragg peak are mainly due to the discrepancy in the secondary fragmentation cross sections used by the codes. The RBE for V79 cell lines is about 0.96 and 0.98 at the entrance of proton and He-3 ions depth dose respectively. The RBE increases to 1.06 and 1.59 at the Bragg peak of proton and He-3 ions. The results demonstrated that LET, microdosimetric parameters (such as dose-mean lineal energy) and RBE are nearly constant along the plateau region of Bragg curve, while all parameters increase within the Bragg peak and at the distal edge for both proton and He-3 ions. CONCLUSION The Monte Carlo codes should revise the fragmentation cross sections to more accurately simulate the physical properties of He-3 ions. The increase in RBE for He-3 ions is higher than for proton beams at the Bragg peak.


Medical Physics | 2015

SU‐E‐T‐549: Modeling Relative Biological Effectiveness of Protons for Radiation Induced Brain Necrosis

Dragan Mirkovic; C Peeler; David R. Grosshans; U Titt; R Taleei; Radhe Mohan


Medical Physics | 2018

Erratum: “Analysis of the track‐ and dose‐averaged LET and LET spectra in proton therapy using the geant4 Monte Carlo code” [Med. Phys. 42 (11), page range 6234‐6247(2015)]

Fada Guan; C Peeler; Lawrence Bronk; Changran Geng; R Taleei; S Randeniya; S Ge; Dragan Mirkovic; David R. Grosshans; Radhe Mohan; U Titt


Medical Physics | 2018

Erratum: “Monte Carlo simulations of 3He ion physical characteristics in a water phantom and evaluation of radiobiological effectiveness” [Med. Phys. 43 (2), page range 761‐776(2016)]

R Taleei; Fada Guan; Chris Peeler; Lawrence Bronk; D Patel; Dragan Mirkovic; David R. Grosshans; Radhe Mohan; U Titt


Medical Physics | 2015

SU-E-T-547: Modeling Biological Response to Proton Irradiation and Evaluating Its Potential Clinical Consequences

R Taleei; C Peeler; Fada Guan; D Patel; U Titt; Dragan Mirkovic; David R. Grosshans; Radhe Mohan

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David R. Grosshans

University of Texas MD Anderson Cancer Center

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Dragan Mirkovic

University of Texas MD Anderson Cancer Center

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Radhe Mohan

University of Texas MD Anderson Cancer Center

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U Titt

University of Texas MD Anderson Cancer Center

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C Peeler

University of Texas MD Anderson Cancer Center

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Fada Guan

University of Texas MD Anderson Cancer Center

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Lawrence Bronk

University of Texas MD Anderson Cancer Center

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D Patel

University of Texas MD Anderson Cancer Center

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M Kerr

University of Texas MD Anderson Cancer Center

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S Ge

University of Texas MD Anderson Cancer Center

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