Browsing by Author "Yepes, Pablo"
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Item An empirical model of proton RBE based on the linear correlation between x-ray and proton radiosensitivity(Wiley, 2022) Flint, David B.; Ruff, Chase E.; Bright, Scott J.; Yepes, Pablo; Wang, Qianxia; Manandhar, Mandira; Kacem, Mariam Ben; Turner, Broderick X.; Martinus, David K. J.; Shaitelman, Simona F.; Sawakuchi, Gabriel O.Background Proton relative biological effectiveness (RBE) is known to depend on physical factors of the proton beam, such as its linear energy transfer (LET), as well as on cell-line specific biological factors, such as their ability to repair DNA damage. However, in a clinical setting, proton RBE is still considered to have a fixed value of 1.1 despite the existence of several empirical models that can predict proton RBE based on how a cell's survival curve (linear-quadratic model [LQM]) parameters α and β vary with the LET of the proton beam. Part of the hesitation to incorporate variable RBE models in the clinic is due to the great noise in the biological datasets on which these models are trained, often making it unclear which model, if any, provides sufficiently accurate RBE predictions to warrant a departure from RBE = 1.1. Purpose Here, we introduce a novel model of proton RBE based on how a cell's intrinsic radiosensitivity varies with LET, rather than its LQM parameters. Methods and materials We performed clonogenic cell survival assays for eight cell lines exposed to 6 MV x-rays and 1.2, 2.6, or 9.9 keV/µm protons, and combined our measurements with published survival data (n = 397 total cell line/LET combinations). We characterized how radiosensitivity metrics of the form DSF%, (the dose required to achieve survival fraction [SF], e.g., D10%) varied with proton LET, and calculated the Bayesian information criteria associated with different LET-dependent functions to determine which functions best described the underlying trends. This allowed us to construct a six-parameter model that predicts cells’ proton survival curves based on the LET dependence of their radiosensitivity, rather than the LET dependence of the LQM parameters themselves. We compared the accuracy of our model to previously established empirical proton RBE models, and implemented our model within a clinical treatment plan evaluation workflow to demonstrate its feasibility in a clinical setting. Results Our analyses of the trends in the data show that DSF% is linearly correlated between x-rays and protons, regardless of the choice of the survival level (e.g., D10%, D37%, or D50% are similarly correlated), and that the slope and intercept of these correlations vary with proton LET. The model we constructed based on these trends predicts proton RBE within 15%–30% at the 68.3% confidence level and offers a more accurate general description of the experimental data than previously published empirical models. In the context of a clinical treatment plan, our model generally predicted higher RBE-weighted doses than the other empirical models, with RBE-weighted doses in the distal portion of the field being up to 50.7% higher than the planned RBE-weighted doses (RBE = 1.1) to the tumor. Conclusions We established a new empirical proton RBE model that is more accurate than previous empirical models, and that predicts much higher RBE values in the distal edge of clinical proton beams.Item Benchmark measurements and simulations of dose perturbations due to metallic spheres in proton beams(Elsevier, 2013) Newhauser, Wayne D.; Rechner, Laura; Mirkovic, Dragan; Yepes, Pablo; Koch, Nicholas C.; Titt, Uwe; Fontenot, Jonas D.; Zhang, RuiMonte Carlo simulations are increasingly used for dose calculations in proton therapy due to its inherent accuracy. However, dosimetric deviations have been found using Monte Carlo code when high density materials are present in the proton beamline. The purpose of this work was to quantify the magnitude of dose perturbation caused by metal objects. We did this by comparing measurements and Monte Carlo predictions of dose perturbations caused by the presence of small metal spheres in several clinical proton therapy beams as functions of proton beam range and drift space. Monte Carlo codes MCNPX, GEANT4 and Fast Dose Calculator (FDC) were used. Generally good agreement was found between measurements and Monte Carlo predictions, with the average difference within 5% and maximum difference within 17%. The modification of multiple Coulomb scattering model in MCNPX code yielded improvement in accuracy and provided the best overall agreement with measurements. Our results confirmed that Monte Carlo codes are well suited for predicting multiple Coulomb scattering in proton therapy beams when short drift spaces are involved.Item Brain Radiation Necrosis Outside the Target Volume After Proton Radiation Therapy: Analyses of Multiparametric Imaging and Proton Biologic Effectiveness(Elsevier, 2022) Bronk, Julianna K.; Amer, Ahmad; Khose, Swapnil; Flint, David; Adair, Antony; Yepes, Pablo; Grosshans, David; Johnson, Jason; Chung, CarolinePurpose We present the case of a 48-year-old patient with recurrent World Health Organization grade II meningioma in the left occipital region who underwent a subtotal resection, followed by postoperative proton therapy to residual disease and the resection cavity. Fourteen months after radiation treatment completion, surveillance imaging revealed numerous ring-enhancing infratentorial lesions, both within and outside of the high-dose field, of concern for viable tumor. We describe the use of advanced imaging and proton biologic effectiveness analyses to enable the diagnosis of radiation necrosis (RN) and ascertain intrinsic physical factors contributing to the development of RN in this patient. Methods and Materials Multiparametric magnetic resonance imaging (MRI) and Monte Carlo predictions of linear energy transfer (LET) and variable relative biologic effectiveness dose were performed. Results The dosimetric analysis revealed that of the 10 lesions, 9 were located outside of the clinical treatment volume and 6 received a dose of <60 Gy relative biologic effectiveness to 95% of the volume. However, increased proton LET values were found in lesions that received lower radiation doses. Dynamic susceptibility contrast and contrast-enhanced, as well as arterial spin labeling-perfusion MRI findings were consistent with RN. Subsequent follow-up imaging revealed no further progression, and the patient was disease-free at the time of this report. Conclusions We describe a case of brain RN after proton beam radiation outside of the high-dose radiation therapy volume. On initial radiographic detection of these lesions, the distant relationship between their anatomic location with respect to the patient's treatment history reduced the suspicion of RN. However, on closer examination of intrinsic physical variables, RN lesions were present in regions that received a lower dose but higher LETs. Although conventional multisequence MRI was inadequate to distinguish between RN and tumor progression, characterization of tissue physiology allowed for the correct diagnosis, highlighting the utility of advanced brain tumor imaging in the follow-up setting.Item Fixed- versus Variable-RBE Computations for Intensity Modulated Proton Therapy(Elsevier, 2019) Yepes, Pablo; Adair, Antony; Frank, Steven J.; Grosshans, David R.; Liao, Zhongxing; Liu, Amy; Mirkovic, Dragan; Poenisch, Falk; Titt, Uwe; Wang, Qianxia; Mohan, RadhePurpose: To evaluate how using models of proton therapy that incorporate variable relative biological effectiveness (RBE) versus the current practice of using a fixed RBE of 1.1 affects dosimetric indices on treatment plans for large cohorts of patients treated with intensity modulated proton therapy (IMPT). Methods and Materials: Treatment plans for 4 groups of patients who received IMPT for brain, head-and-neck, thoracic, or prostate cancer were selected. Dose distributions were recalculated in 4 ways: 1 with a fast-dose Monte Carlo calculator with fixed RBE and 3 with RBE calculated to 3 different models—McNamara, Wedenberg, and repair-misrepair-fixation. Differences among dosimetric indices (D02, D50, D98, and mean dose) for target volumes and organs at risk (OARs) on each plan were compared between the fixed-RBE and variable-RBE calculations. Results: In analyses of all target volumes, for which the main concern is underprediction or RBE less than 1.1, none of the models predicted an RBE less than 1.05 for any of the cohorts. For OARs, the 2 models based on linear energy transfer, McNamara and Wedenberg, systematically predicted RBE >1.1 for most structures. For the mean dose of 25% of the plans for 2 OARs, they predict RBE equal to or larger than 1.4, 1.3, 1.3, and 1.2 for brain, head-and-neck, thorax, and prostate, respectively. Systematically lower increases in RBE are predicted by repair-misrepair-fixation, with a few cases (eg, femur) in which the RBE is less than 1.1 for all plans. Conclusions: The variable-RBE models predict increased doses to various OARs, suggesting that strategies to reduce high-dose linear energy transfer in critical structures should be developed to minimize possible toxicity associated with IMPT.Item Impact of dose calculation accuracy on inverse linear energy transfer optimization for intensity-modulated proton therapy(Wiley, 2023) Chen, Mei; Cao, Wenhua; Yepes, Pablo; Guan, Fada; Poenisch, Falk; Xu, Cheng; Chen, Jiayi; Li, Yupeng; Vazquez, Ivan; Yang, Ming; Zhu, X. Ronald; Zhang, XiaodongObjective To determine the effect of dose calculation accuracy on inverse linear energy transfer (LET) optimization for intensity-modulated proton therapy, and to determine whether adding more beams would improve the plan robustness to different dose calculation engines. Methods Two sets of intensity-modulated proton therapy plans using two, four, six, and nine beams were created for 10 prostate cancer patients: one set was optimized with dose constraints (DoseOpt) using the pencil beam (PB) algorithm, and the other set was optimized with additional LET constraints (LETOpt) using the Monte Carlo (MC) algorithm. Dose distributions of DoseOpt plans were then recalculated using the MC algorithm, and the LETOpt plans were recalculated using the PB algorithm. Dosimetric indices of targets and critical organs were compared between the PB and MC algorithms for both sets of plans. Results For DoseOpt plans, dose differences between the PB and MC algorithms were minimal. However, the maximum dose differences in LETOpt plans were 11.11% and 15.85% in the dose covering 98% and 2% (D2) of the clinical target volume, respectively. Furthermore, the dose to 1 cc of the bladder differed by 11.42 Gy (relative biological effectiveness). Adding more beams reduced the discrepancy in target coverage, but the errors in D2 of the structure were increased with the number of beams. Conclusion High modulation of LET requires high dose calculation accuracy during the optimization and final dose calculation in the inverse treatment planning for intensity-modulated proton therapy, and adding more beams did not improve the plan robustness to different dose calculation algorithms.Item Intensity modulated proton arc therapy via geometry-based energy selection for ependymoma(Wiley, 2023) Cao, Wenhua; Li, Yupeng; Zhang, Xiaodong; Poenisch, Falk; Yepes, Pablo; Sahoo, Narayan; Grosshans, David; McGovern, Susan; Gunn, G. Brandon; Frank, Steven J.; Zhu, Xiaorong R.Purpose We developed and tested a novel method of creating intensity modulated proton arc therapy (IMPAT) plans that uses computing resources similar to those for regular intensity-modulated proton therapy (IMPT) plans and may offer a dosimetric benefit for patients with ependymoma or similar tumor geometries. Methods Our IMPAT planning method consists of a geometry-based energy selection step with major scanning spot contributions as inputs computed using ray-tracing and single-Gaussian approximation of lateral spot profiles. Based on the geometric relation of scanning spots and dose voxels, our energy selection module selects a minimum set of energy layers at each gantry angle such that each target voxel is covered by sufficient scanning spots as specified by the planner, with dose contributions above the specified threshold. Finally, IMPAT plans are generated by robustly optimizing scanning spots of the selected energy layers using a commercial proton treatment planning system (TPS). The IMPAT plan quality was assessed for four ependymoma patients. Reference three-field IMPT plans were created with similar planning objective functions and compared with the IMPAT plans. Results In all plans, the prescribed dose covered 95% of the clinical target volume (CTV) while maintaining similar maximum doses for the brainstem. While IMPAT and IMPT achieved comparable plan robustness, the IMPAT plans achieved better homogeneity and conformity than the IMPT plans. The IMPAT plans also exhibited higher relative biological effectiveness (RBE) enhancement than did the corresponding reference IMPT plans for the CTV in all four patients and brainstem in three of them. Conclusions The proposed method demonstrated potential as an efficient technique for IMPAT planning and may offer a dosimetric benefit for patients with ependymoma or tumors in close proximity to critical organs. IMPAT plans created using this method had elevated RBE enhancement associated with increased linear energy transfer (LET) in both targets and abutting critical organs.Item Mixed Effect Modeling of Dose and Linear Energy Transfer Correlations With Brain Image Changes After Intensity Modulated Proton Therapy for Skull Base Head and Neck Cancer(Elsevier, 2021) Engeseth, Grete May; He, Renjie; Mirkovic, Dragan; Yepes, Pablo; Mohamed, Abdallah Sherif Radwan; Stieb, Sonja; Fuller, Clifton Dave; Wu, Richard; Zhang, Xiadong; Hysing, Liv Bolstad; Pettersen, Helge Egil Seime; Stokkevåg, Camilla Hanquist; Mohan, Radhe; Frank, Steven Jay; Gunn, Gary BrandonPurpose: Intensity modulated proton therapy (IMPT) could yield high linear energy transfer (LET) in critical structures and increased biological effect. For head and neck cancers at the skull base this could potentially result in radiation-associated brain image change (RAIC). The purpose of the current study was to investigate voxel-wise dose and LET correlations with RAIC after IMPT. Methods and Materials: For 15 patients with RAIC after IMPT, contrast enhancement observed on T1-weighted magnetic resonance imaging was contoured and coregistered to the planning computed tomography. Monte Carlo calculated dose and dose-averaged LET (LETd) distributions were extracted at voxel level and associations with RAIC were modelled using uni- and multivariate mixed effect logistic regression. Model performance was evaluated using the area under the receiver operating characteristic curve and precision-recall curve. Results: An overall statistically significant RAIC association with dose and LETd was found in both the uni- and multivariate analysis. Patient heterogeneity was considerable, with standard deviation of the random effects of 1.81 (1.30-2.72) for dose and 2.68 (1.93-4.93) for LETd, respectively. Area under the receiver operating characteristic curve was 0.93 and 0.95 for the univariate dose-response model and multivariate model, respectively. Analysis of the LETd effect demonstrated increased risk of RAIC with increasing LETd for the majority of patients. Estimated probability of RAIC with LETd = 1 keV/µm was 4% (95% confidence interval, 0%, 0.44%) and 29% (95% confidence interval, 0.01%, 0.92%) for 60 and 70 Gy, respectively. The TD15 were estimated to be 63.6 and 50.1 Gy with LETd equal to 2 and 5 keV/µm, respectively. Conclusions: Our results suggest that the LETd effect could be of clinical significance for some patients; LETd assessment in clinical treatment plans should therefore be taken into consideration.Item Monte-Carlo Simulation and Measurements of Electrons, Positrons, and Gamma-rays Generated by Laser-Solid Interactions(2015-04-20) Henderson, Alexander Hastings; Liang, Edison P.; Yepes, Pablo; Cox, DennisLasers have grown more powerful in recent years, opening up new frontiers in physics. From early intensities of less than 1010 W/cm2, lasers can now achieve intensities over 1021 W/cm2. Ultraintense laser can become powerful new tools to produce relativistic electrons, positron-electron pairs, and gamma-rays. The pair production efficiency is equal to or greater than that of linear accelerators, the most common method of antimatter generation in the past. The gamma-rays and electrons produced can be highly collimated, making these interactions of interest for beam generation. Monte-Carlo particle transport simulation has long been used in physics for simulating various particle and radiation processes, and is well-suited to simulating both electromagnetic cascades resulting from laser-solid interactions and the response of electron/positron spectrometers and gamma-ray detectors. We have used GEANT4 Monte-Carlo particle transport simulation to design and calibrate charged-particle spectrometers using permanent magnets as well as a Forward Compton Electron Spectrometer to measure gamma-rays of higher energies than have previously been achieved. We have had some success simulating and measuring high positron and gamma-rays yields from laser-solid interactions using gold target at the Texas Petawatt Laser (TPW). While similar spectrometers have been developed in the past, we are to our knowledge the first to successfully use permanent magnet spectrometers to detect positrons originating from laser-solid interactions in this energy range. We believe we are also the first to successfully detect multi-MeV gamma rays using a permanent magnet Forward Compton Electron Spectrometer. Monte-Carlo particle transport simulation has been used by other groups to model positron production from laser-solid ineraction, but at the time that we began we were, as far as we know, the first to have a significant amount of empirical data to work with. We were thus at liberty to estimate the initial conditions, compare simulation results to data, and adjust as needed to obtain a better estimate of the actual initial conditions. We have also developed a new method for measuring the yield and angular distribution of gamma-rays using a two-dimensional dosimeter array. In this work, we examine the experimental and simulation results as well as the physical processes behind them. In addition, the gamma-rays produced by our experiments could be useful for photo-nuclear reactors and homeland security purposes. In our experiments, we measured narrow energy-band positrons and electrons which have potential medical uses.Item Optimization of FLASH proton beams using a track-repeating algorithm(Wiley, 2022) Wang, Qianxia; Titt, Uwe; Mohan, Radhe; Guan, Fada; Zhao, Yao; Yang, Ming; Yepes, PabloBackground: Radiation with high dose rate (FLASH) has shown to reduce toxicities to normal tissues around the target and maintain tumor control with the same amount of dose compared to conventional radiation. This phenomenon has been widely studied in electron therapy, which is often used for shallow tumor treatment. Proton therapy is considered a more suitable treatment modality for deep-seated tumors. The feasibility of FLASH proton therapy has recently been demonstrated by a series of pre- and clinical trials. One of the challenges is to efficiently generate wide enough dose distributions in both lateral and longitudinal directions to cover the entire tumor volume. The goal of this paper is to introduce a set of automatic FLASH proton beam optimization algorithms developed recently. Purpose: To develop a fast and efficient optimizer for the design of a passive scattering proton FLASH radiotherapy delivery at The University of Texas MD Anderson Proton Therapy Center, based on the fast dose calculator (FDC). Methods: A track-repeating algorithm, FDC, was validated versus Geant4 simulations and applied to calculate dose distributions in various beamline setups. The design of the components was optimized to deliver homogeneous fields with well-defined diameters between 11.0 and 20.5 mm, as well as a spread-out Bragg peak (SOBP) with modulations between 8.5 and 39.0 mm. A ridge filter, a high-Z material scatterer, and a collimator with range compensator were inserted in the beam path, and their shapes and sizes were optimized to spread out the Bragg peak, widen the beam, and reduce the penumbra. The optimizer was developed and tested using two proton energies (87.0 and 159.5 MeV) in a variety of beamline arrangements. Dose rates of the optimized beams were estimated by scaling their doses to those of unmodified beams. Results: The optimized 87.0-MeV beams, with a distance from the beam pipe window to the phantom surface (window-to-surface distance [WSD]) of 550 mm, produced an 8.5-mm-wide SOBP (proximal 90% to distal 90% of the maximum dose); 14.5, 12.0, and 11.0-mm lateral widths at the 50%, 80%, and 90% dose location, respectively; and a 2.5-mm penumbra from 80% to 20% in the lateral profile. The 159.5-MeV beam had an SOBP of 39.0 mm and lateral widths of 20.5, 15.0, and 12.5 mm at 50%, 80%, and 90% dose location, respectively, when the WSD was 550 mm. Wider lateral widths were obtained with increased WSD. The SOBP modulations changed when the ridge filters with different characteristics were inserted. Dose rates on the beam central axis for all optimized beams (other than the 87.0-MeV beam with 2000-mm WSD) were above that needed for the FLASH effect threshold (40 Gy/s) except at the very end of the depth dose profile scaling with a dose rate of 1400 Gy/s at the Bragg peak in the unmodified beams. The optimizer was able to instantly design the individual beamline components for each of the beamline setups, without the need of time intensive iterative simulations. Conclusion: An efficient system, consisting of an optimizer and an FDC have been developed and validated in a variety of beamline setups, comprising two proton energies, several WSDs, and SOBPs. The set of automatic optimization algorithms produces beam shaping element designs efficiently and with excellent quality.Item Study and implementation of a high-level trigger for the STAR experiment(2002) DeMello, Martin J.; Yepes, PabloWe have designed and implemented various components of the STAR Level 3 trigger, including a Sector Level 3, a Global Level 3 and a Sector Broker. In addition, we have implemented and studied a small prototype of the STAR tracking farm, using Intel dual Pentiums connected via an ethernet ring.