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Title: SU-G-TeP1-02: Analytical Stopping Power and Range Parameterization for Therapeutic Energy Intervals

Abstract

Purpose: To develop a simple, analytic parameterization of stopping power and range, which covers a wide energy interval and is applicable to many species of projectile ions and target materials, with less than 15% disagreement in linear stopping power and 1 mm in range. Methods: The new parameterization was required to be analytically integrable from stopping power to range, and continuous across the range interval of 1 µm to 50 cm. The model parameters were determined from stopping power and range data for hydrogen, carbon, iron, and uranium ions incident on water, carbon, aluminum, lead and copper. Stopping power and range data was taken from SRIM. A stochastic minimization algorithm was used to find model parameters, with 10 data points per energy decade. Additionally, fitting was performed with 2 and 26 data points per energy decade to test the model’s robustness to sparse Results: 6 free parameters were sufficient to cover the therapeutic energy range for each projectile ion species (e.g. 1 keV – 300 MeV for protons). The model agrees with stopping power and range data well, with less than 9% relative stopping power difference and 0.5 mm difference in range. As few as, 4 bins per decade weremore » required to achieve comparable fitting results to the full data set. Conclusion: This study successfully demonstrated that a simple analytic function can be used to fit the entire energy interval of therapeutic ion beams of hydrogen and heavier elements. Advantages of this model were the small number (6) of free parameters, and that the model calculates both stopping power and range. Applications of this model include GPU-based dose calculation algorithms and Monte Carlo simulations, where available memory is limited. This work was supported in part by a research agreement between United States Naval Academy and Louisiana State University: Contract No N00189-13-P-0786. In addition, this work was accepted for presentation at the American Nuclear Society Annual Meeting 2016.« less

Authors:
 [1];  [1];  [2];  [3]
  1. Louisiana State University, Baton Rouge, LA (United States)
  2. (United States)
  3. United States Naval Academy, Annapolis, MD (United States)
Publication Date:
OSTI Identifier:
22649342
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 43; Journal Issue: 6; Other Information: (c) 2016 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
61 RADIATION PROTECTION AND DOSIMETRY; COMPUTERIZED SIMULATION; EDUCATIONAL FACILITIES; ION BEAMS; KEV RANGE 01-10; MEV RANGE; MONTE CARLO METHOD; STOCHASTIC PROCESSES; STOPPING POWER

Citation Formats

Donahue, W, Newhauser, W, Mary Bird Perkins Cancer Center, Baton Rouge, LA, and Ziegler, J F. SU-G-TeP1-02: Analytical Stopping Power and Range Parameterization for Therapeutic Energy Intervals. United States: N. p., 2016. Web. doi:10.1118/1.4956992.
Donahue, W, Newhauser, W, Mary Bird Perkins Cancer Center, Baton Rouge, LA, & Ziegler, J F. SU-G-TeP1-02: Analytical Stopping Power and Range Parameterization for Therapeutic Energy Intervals. United States. doi:10.1118/1.4956992.
Donahue, W, Newhauser, W, Mary Bird Perkins Cancer Center, Baton Rouge, LA, and Ziegler, J F. Wed . "SU-G-TeP1-02: Analytical Stopping Power and Range Parameterization for Therapeutic Energy Intervals". United States. doi:10.1118/1.4956992.
@article{osti_22649342,
title = {SU-G-TeP1-02: Analytical Stopping Power and Range Parameterization for Therapeutic Energy Intervals},
author = {Donahue, W and Newhauser, W and Mary Bird Perkins Cancer Center, Baton Rouge, LA and Ziegler, J F},
abstractNote = {Purpose: To develop a simple, analytic parameterization of stopping power and range, which covers a wide energy interval and is applicable to many species of projectile ions and target materials, with less than 15% disagreement in linear stopping power and 1 mm in range. Methods: The new parameterization was required to be analytically integrable from stopping power to range, and continuous across the range interval of 1 µm to 50 cm. The model parameters were determined from stopping power and range data for hydrogen, carbon, iron, and uranium ions incident on water, carbon, aluminum, lead and copper. Stopping power and range data was taken from SRIM. A stochastic minimization algorithm was used to find model parameters, with 10 data points per energy decade. Additionally, fitting was performed with 2 and 26 data points per energy decade to test the model’s robustness to sparse Results: 6 free parameters were sufficient to cover the therapeutic energy range for each projectile ion species (e.g. 1 keV – 300 MeV for protons). The model agrees with stopping power and range data well, with less than 9% relative stopping power difference and 0.5 mm difference in range. As few as, 4 bins per decade were required to achieve comparable fitting results to the full data set. Conclusion: This study successfully demonstrated that a simple analytic function can be used to fit the entire energy interval of therapeutic ion beams of hydrogen and heavier elements. Advantages of this model were the small number (6) of free parameters, and that the model calculates both stopping power and range. Applications of this model include GPU-based dose calculation algorithms and Monte Carlo simulations, where available memory is limited. This work was supported in part by a research agreement between United States Naval Academy and Louisiana State University: Contract No N00189-13-P-0786. In addition, this work was accepted for presentation at the American Nuclear Society Annual Meeting 2016.},
doi = {10.1118/1.4956992},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = {Wed Jun 15 00:00:00 EDT 2016},
month = {Wed Jun 15 00:00:00 EDT 2016}
}
  • Purpose: We present an improved method to calculate patient-specific calibration curves to convert X-ray computed tomography (CT) Hounsfield Unit (HU) to relative stopping powers (RSP) for proton therapy treatment planning. Methods: By optimizing the HU-RSP calibration curve, the difference between a proton radiographic image and a digitally reconstructed X-ray radiography (DRR) is minimized. The feasibility of this approach has previously been demonstrated. This scenario assumes that all discrepancies between proton radiography and DRR originate from uncertainties in the HU-RSP curve. In reality, external factors cause imperfections in the proton radiography, such as misalignment compared to the DRR and unfaithful representationmore » of geometric structures (“blurring”). We analyze these effects based on synthetic datasets of anthropomorphic phantoms and suggest an extended optimization scheme which explicitly accounts for these effects. Performance of the method is been tested for various simulated irradiation parameters. The ultimate purpose of the optimization is to minimize uncertainties in the HU-RSP calibration curve. We therefore suggest and perform a thorough statistical treatment to quantify the accuracy of the optimized HU-RSP curve. Results: We demonstrate that without extending the optimization scheme, spatial blurring (equivalent to FWHM=3mm convolution) in the proton radiographies can cause up to 10% deviation between the optimized and the ground truth HU-RSP calibration curve. Instead, results obtained with our extended method reach 1% or better correspondence. We have further calculated gamma index maps for different acceptance levels. With DTA=0.5mm and RD=0.5%, a passing ratio of 100% is obtained with the extended method, while an optimization neglecting effects of spatial blurring only reach ∼90%. Conclusion: Our contribution underlines the potential of a single proton radiography to generate a patient-specific calibration curve and to improve dose delivery by optimizing the HU-RSP calibration curve as long as all sources of systematic incongruence are properly modeled.« less
  • Purpose: In prostate HDR brachytherapy dose distributions are highly sensitive to changes in prostate volume and catheter displacements. We investigate the maximum deformations in implant geometry before planning objectives are violated. Methods: A typical prostate Ir-192 HDR brachytherapy reference plan was calculated on the Oncentra planning system, which used CT images from a tissue equivalent prostate phantom (CIRS Model 053S) embedded inside a pelvis wax phantom. The prostate was deformed and catheters were displaced in simulations using a code written in MATLAB. For each deformation dose distributions were calculated, based on TG43 methods, using the MATLAB code. The calculations weremore » validated through comparison with Oncentra calculations for the reference plan, and agreed within 0.12%SD and 0.3%SD for dose and volume, respectively. Isotropic prostate volume deformations of up to +34% to −27% relative to its original volume, and longitudinal catheter displacements of 7.5 mm in superior and inferior directions were simulated. Planning objectives were based on American Brachytherapy Society guidelines for prostate and urethra volumes. A plan violated the planning objectives when less than 90% of the prostate volume received the prescribed dose or higher (V{sub 100}), or the urethral volume receiving 125% of prescribed dose or higher was more than 1 cc (U{sub 125}). Lastly, the dose homogeneity index (DHI=1-V{sub 150}/V{sub 100}) was evaluated; a plan was considered sub-optimal when the DHI fell below 0.62. Results and Conclusion: Planning objectives were violated when the prostate expanded by 10.7±0.5% or contracted by 11.0±0.2%; objectives were also violated when catheters were displaced by 4.15±0.15 mm and 3.70±0.15 mm in the superior and inferior directions, respectively. The DHI changes did not affect the plan optimality, except in the case of prostate compression. In general, catheter displacements have a significantly larger impact on plan optimality than prostate volume changes.« less
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