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Title: TU-H-CAMPUS-TeP1-05: Fast Processed 3D Printing-Aided Urethane Resin (PUR) Bolus in Radiation Therapy

Abstract

Purpose: 3D printed custom bolus is regularly used in radiation therapy clinic as a compensator. However, usual method of bolus printing with 100% filling is very time-consuming. The purpose of this study is to evaluate the feasibility and benefit of 3D printed bolus filled with UR. Methods: Two boluses were designed on nose (9e electrons) and ear (6× photons) for a head phantom in treatment planning system (TPS) to achieve dose coverage to the skin. The bolus structures (56–167cc) were converted to STereoLithographic (STL) model using an in-house developed algorithm and sent to a commercial fused deposition modeling (FDM) printer. Only shells were printed with polylactic acid (PLA) material. Liquid UR was then placed in a vacuum pump and slowly poured into the hollow bolus from its top opening. Liquid UR hardened in around half an hour. The phantom was rescanned with custom boluses attached and the dosimetry was compared with original design in TPS. Basic CT and dose properties were investigated. GaF films were irradiated to measure dose profile and output of several open photon and electron beams under solid water and UR slabs of same thicknesses. Results: CT number was 11.2±7.3 and 65.4±7.8, respectively for solid water(∼1.04g/cc) andmore » UR(∼1.08g/cc). The output measurement at dmax for 6× was within 2% for the two materials. The relative dose profiles of the two materials above dmax show 94–99% Gamma analysis passing rates for both photons and electrons. Dose distributions with 3D PUR boluses maintained great coverage on the intended skin regions and resembled that with computer generated boluses. Manufacturing 3D PUR boluses was 3–4 times faster than 100% printed boluses. The efficiency significantly improves for larger boluses. Conclusion: The study suggests UR has similar dose responses as solid water. Making custom bolus with UR greatly increases clinical workflow efficiency.« less

Authors:
; ; ; ; ;  [1]
  1. UT Southwestern Medical Center, Dallas, TX (United States)
Publication Date:
OSTI Identifier:
22654056
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:
60 APPLIED LIFE SCIENCES; 61 RADIATION PROTECTION AND DOSIMETRY; ELECTRON BEAMS; MATERIALS; PHOTONS; RADIATION DOSE DISTRIBUTIONS; RADIOTHERAPY; WATER

Citation Formats

Zhao, B, Chiu, T, Gu, X, Lee, H, Nedzi, L, and Jiang, S. TU-H-CAMPUS-TeP1-05: Fast Processed 3D Printing-Aided Urethane Resin (PUR) Bolus in Radiation Therapy. United States: N. p., 2016. Web. doi:10.1118/1.4957678.
Zhao, B, Chiu, T, Gu, X, Lee, H, Nedzi, L, & Jiang, S. TU-H-CAMPUS-TeP1-05: Fast Processed 3D Printing-Aided Urethane Resin (PUR) Bolus in Radiation Therapy. United States. doi:10.1118/1.4957678.
Zhao, B, Chiu, T, Gu, X, Lee, H, Nedzi, L, and Jiang, S. 2016. "TU-H-CAMPUS-TeP1-05: Fast Processed 3D Printing-Aided Urethane Resin (PUR) Bolus in Radiation Therapy". United States. doi:10.1118/1.4957678.
@article{osti_22654056,
title = {TU-H-CAMPUS-TeP1-05: Fast Processed 3D Printing-Aided Urethane Resin (PUR) Bolus in Radiation Therapy},
author = {Zhao, B and Chiu, T and Gu, X and Lee, H and Nedzi, L and Jiang, S},
abstractNote = {Purpose: 3D printed custom bolus is regularly used in radiation therapy clinic as a compensator. However, usual method of bolus printing with 100% filling is very time-consuming. The purpose of this study is to evaluate the feasibility and benefit of 3D printed bolus filled with UR. Methods: Two boluses were designed on nose (9e electrons) and ear (6× photons) for a head phantom in treatment planning system (TPS) to achieve dose coverage to the skin. The bolus structures (56–167cc) were converted to STereoLithographic (STL) model using an in-house developed algorithm and sent to a commercial fused deposition modeling (FDM) printer. Only shells were printed with polylactic acid (PLA) material. Liquid UR was then placed in a vacuum pump and slowly poured into the hollow bolus from its top opening. Liquid UR hardened in around half an hour. The phantom was rescanned with custom boluses attached and the dosimetry was compared with original design in TPS. Basic CT and dose properties were investigated. GaF films were irradiated to measure dose profile and output of several open photon and electron beams under solid water and UR slabs of same thicknesses. Results: CT number was 11.2±7.3 and 65.4±7.8, respectively for solid water(∼1.04g/cc) and UR(∼1.08g/cc). The output measurement at dmax for 6× was within 2% for the two materials. The relative dose profiles of the two materials above dmax show 94–99% Gamma analysis passing rates for both photons and electrons. Dose distributions with 3D PUR boluses maintained great coverage on the intended skin regions and resembled that with computer generated boluses. Manufacturing 3D PUR boluses was 3–4 times faster than 100% printed boluses. The efficiency significantly improves for larger boluses. Conclusion: The study suggests UR has similar dose responses as solid water. Making custom bolus with UR greatly increases clinical workflow efficiency.},
doi = {10.1118/1.4957678},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = 2016,
month = 6
}
  • Purpose: To demonstrate the feasibility of fast Monte Carlo (MC) treatment planning and verification using four-dimensional CT (4DCT) for adaptive IMPT for lung cancer patients. Methods: A validated GPU MC code, gPMC, has been linked to the patient database at our institution and employed to compute the dose-influence matrices (Dij) on the planning CT (pCT). The pCT is an average of the respiratory motion of the patient. The Dijs and patient structures were fed to the optimizer to calculate a treatment plan. To validate the plan against motion, a 4D dose distribution averaged over the possible starting phases is calculatedmore » using the 4DCT and a model of the time structure of the delivered spot map. The dose is accumulated using vector maps created by a GPU-accelerated deformable image registration program (DIR) from each phase of the 4DCT to the reference phase using the B-spline method. Calculation of the Dij matrices and the DIR are performed on a cluster, with each field and vector map calculated in parallel. Results: The Dij production takes ∼3.5s per beamlet for 10e6 protons, depending on the energy and the CT size. Generating a plan with 4D simulation of 1000 spots in 4 fields takes approximately 1h. To test the framework, IMPT plans for 10 lung cancer patients were generated for validation. Differences between the planned and the delivered dose of 19% in dose to some organs at risk and 1.4/21.1% in target mean dose/homogeneity with respect to the plan were observed, suggesting potential for improvement if adaptation is considered. Conclusion: A fast MC treatment planning framework has been developed that allows reliable plan design and verification for mobile targets and adaptation of treatment plans. This will significantly impact treatments for lung tumors, as 4D-MC dose calculations can now become part of planning strategies.« less
  • Purpose: To demonstrate an efficient and clinically relevant patient specific QA method by reconstructing 3D patient dose from 2D EPID images for IMRT plans. Also to determine the usefulness of 2D QA metrics when assessing 3D patient dose deviations. Methods: Using the method developed by King et al (Med Phys 39(5),2839–2847), EPID images of IMRT fields were acquired in air and converted to dose at 10 cm depth (SAD setup) in a flat virtual water phantom. Each EPID measured dose map was then divided by the corresponding treatment planning system (TPS) dose map calculated with an identical setup, to derivemore » a 2D “error matrix”. For each field, the error matrix was used to adjust the doses along the respective ray lines in the original patient 3D dose. All field doses were combined to derive a reconstructed 3D patient dose for quantitative analysis. A software tool was developed to efficiently implement the entire process and was tested with a variety of IMRT plans for 2D (virtual flat phantom) and 3D (in-patient) QA analysis. Results: The method was tested on 60 IMRT plans. The mean (± standard deviation) 2D gamma (2%,2mm) pass rate (2D-GPR) was 97.4±3.0% and the mean 2D gamma index (2D-GI) was 0.35±0.06. The 3D PTV mean dose deviation was 1.8±0.8%. The analysis showed very weak correlations between both the 2D-GPR and 2D-GI when compared with PTV mean dose deviations (R2=0.3561 and 0.3632 respectively). Conclusion: Our method efficiently calculates 3D patient dose from 2D EPID images, utilising all of the advantages of an EPID-based dosimetry system. In this study, the 2D QA metrics did not predict the 3D patient dose deviation. This tool allows reporting of the 3D volumetric dose parameters thus providing more clinically relevant patient specific QA.« less
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  • Purpose: EPID-based patient-specific quality assurance provides verification of the planning setup and delivery process that phantomless QA and log-file based virtual dosimetry methods cannot achieve. We present a method for EPID-based QA utilizing spatially-variant EPID response kernels that allows for direct calculation of the entrance fluence and 3D phantom dose. Methods: An EPID dosimetry system was utilized for 3D dose reconstruction in a cylindrical phantom for the purposes of end-to-end QA. Monte Carlo (MC) methods were used to generate pixel-specific point-spread functions (PSFs) characterizing the spatially non-uniform EPID portal response in the presence of phantom scatter. The spatially-variant PSFs weremore » decomposed into spatially-invariant basis PSFs with the symmetric central-axis kernel as the primary basis kernel and off-axis representing orthogonal perturbations in pixel-space. This compact and accurate characterization enables the use of a modified Richardson-Lucy deconvolution algorithm to directly reconstruct entrance fluence from EPID images without iterative scatter subtraction. High-resolution phantom dose kernels were cogenerated in MC with the PSFs enabling direct recalculation of the resulting phantom dose by rapid forward convolution once the entrance fluence was calculated. A Delta4 QA phantom was used to validate the dose reconstructed in this approach. Results: The spatially-invariant representation of the EPID response accurately reproduced the entrance fluence with >99.5% fidelity with a simultaneous reduction of >60% in computational overhead. 3D dose for 10{sub 6} voxels was reconstructed for the entire phantom geometry. A 3D global gamma analysis demonstrated a >95% pass rate at 3%/3mm. Conclusion: Our approach demonstrates the capabilities of an EPID-based end-to-end QA methodology that is more efficient than traditional EPID dosimetry methods. Displacing the point of measurement external to the QA phantom reduces the necessary complexity of the phantom itself while offering a method that is highly scalable and inherently generalizable to rotational and trajectory based deliveries. This research was partially supported by Varian.« less