Development of optimised tissue-equivalent materials for proton therapy

Cook, H.; Simard, Mikaël; Niemann, Nathan; Gillies, Callum; Osborne, Mark; Hussein, Mohammad; Rompokos, V.; Bouchard, Hugo; Royle, Gary; Pettingell, J.; Lourenço, Ana

doi:10.1088/1361-6560/acb637

Cited by 4 publications

(6 citation statements)

References 32 publications

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“…However, production limitations made high-density cortical bone and bone structures of more than one density infeasible. Unlike in a recent publication by Cook et al [6], the goal was not to find materials performing closer to tabulated human tissues [1] than current solutions but rather to reach the level of performance of the tissue surrogates currently used for Hounsfield unit (HU) curve calibration.…”

Section: Discussionmentioning

confidence: 99%

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Dosimetric characteristics of 3D-printed and epoxy-based materials for particle therapy phantoms

Brunner,

Langgartner,

Danhel

et al. 2024

Front. Phys.

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Objective3D printing has seen use in many fields of imaging and radiation oncology, but applications in (anthropomorphic) phantoms, especially for particle therapy, are still lacking. The aim of this work was to characterize various available 3D printing methods and epoxy-based materials with the specific goal of identifying suitable tissue surrogates for dosimetry applications in particle therapy.Methods3D-printed and epoxy-based mixtures of varying ratios combining epoxy resin, bone meal, and polyethylene powder were scanned in a single-energy computed tomography (CT), a dual-energy CT, and a µCT scanner. Their CT-predicted attenuation was compared to measurements in a 148.2 MeV proton and 284.7 MeV/u carbon ion beam. The sample homogeneity was evaluated in the respective CT images and in the carbon beam, additionally via widening of the Bragg peak. To assess long-term stability attenuation, size and weight measurements were repeated after 6–12 months.ResultsFour 3D-printed materials, acrylonitrile butadiene styrene polylactic acid, fused deposition modeling printed nylon, and selective laser sintering printed nylon, and various ratios of epoxy-based mixtures were found to be suitable tissue surrogates. The materials’ predicted stopping power ratio matched the measured stopping power ratio within 3% for all investigated CT machines and protocols, except for µCT scans employing cone beam CT technology. The heterogeneity of the suitable surrogate samples was adequate, with a maximum Bragg peak width increase of 11.5 ± 2.5%. The repeat measurements showed no signs of degradation after 6–12 months.ConclusionWe identified surrogates for soft tissue and low- to medium-density bone among the investigated materials. This allows low-cost, adaptable phantoms to be built for quality assurance and end-to-end tests for particle therapy.

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Section: Discussionmentioning

confidence: 99%

“…A comprehensive characterization of the elemental composition of human tissues [1] and the ICRU report 44 on "Tissue Substitutes in Radiation Dosimetry" are the foundation of modern surrogates [2]. Potential candidates to expand or improve the material library are investigated to this day [3][4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Dosimetric characteristics of 3D-printed and epoxy-based materials for particle therapy phantoms

Brunner,

Langgartner,

Danhel

et al. 2024

Front. Phys.

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“…[7][8][9] Furthermore, the accuracy of the predicted SPRs is limited to how well the tissue surrogate materials in the calibration phantom mimic real human tissue interaction properties for both diagnostic x-rays (50-150 kV) and therapeutic protons (3-300 MeV). 10 The direct translation from CT numbers to SPR is problematic as there is no univocal one-to-one relationship between CT numbers and SPRs for tissues in the human body. 11,12 It has recently been shown that stoichiometric calibration using SECT with the most commonly used set of reference tissues 13,14 can cause systematic range errors in pediatric tissues, 15 partly due to a larger fraction of oxygen in pediatric tissue compared to adults.…”

Section: Introductionmentioning

confidence: 99%

“…The calibration requires a considerable amount of effort during the commissioning of each individual scanner, as the CT numbers differ between CT scanner models, scan protocol settings (e.g., tube voltage, beam filtration and reconstruction kernel), patient size, 2–5 positioning in the CT scanner, 6 as well as image noise 7–9 . Furthermore, the accuracy of the predicted SPRs is limited to how well the tissue surrogate materials in the calibration phantom mimic real human tissue interaction properties for both diagnostic x‐rays (50–150 kV) and therapeutic protons (3–300 MeV) 10 . The direct translation from CT numbers to SPR is problematic as there is no univocal one‐to‐one relationship between CT numbers and SPRs for tissues in the human body 11,12 .…”

Section: Introductionmentioning

confidence: 99%

Prediction of proton stopping power ratios using dual‐energy CT basis material decomposition

Pettersson,

Thilander‐Klang,

Bäck

2024

Medical Physics

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BackgroundProton radiotherapy treatment plans are currently restricted by the range uncertainties originating from the stopping power ratio (SPR) prediction based on single‐energy computed tomography (SECT). Various studies have shown that multi‐energy CT (MECT) can reduce the range uncertainties due to medical implant materials and age‐related variations in tissue composition. None of these has directly applied the basis material density (MD) images produced by projection‐based MECT systems for SPR prediction.PurposeTo present and evaluate a novel proton SPR prediction method based on MD images from dual‐energy CT (DECT), which could reduce the range uncertainties currently associated with proton radiotherapy.MethodsA theoretical basis material decomposition into water and iodine material densities was performed for various pediatric and adult human reference tissues, as well as other non‐tissue materials, by minimizing the root‐mean‐square relative attenuation error in the energy interval from 40 to 140 keV. A model (here called MD‐SPR) mapping predicted MDs to theoretically calculated reference SPRs was created with locally weighted scatterplot smoothing (LOWESS) data‐fitting. The goodness of fit of the MD‐SPR model was evaluated for the included reference tissues. MD images of two electron density phantoms, combined to form a head‐ and an abdomen‐sized phantom setup, were acquired with a clinical projection‐based fast‐kV switching DECT scanner. The MD images were compared to the theoretically predicted MDs of the tissue surrogates and other non‐tissue materials in the phantoms, as well as used for input to the MD‐SPR model for generation of SPR images. The SPR images were subsequently compared to theoretical reference SPRs of the materials in the phantoms, as well as to SPR images from a commercial algorithm (DirectSPR, Siemens Healthineers, Forchheim, Germany) using image‐based consecutive scan DECT for the same phantom setups.ResultsThe predicted SPRs of the tissue surrogates were similar for MD‐SPR and DirectSPR, where the adipose and bone tissue surrogates were within 1% difference to the reference SPRs, while other non‐adipose soft tissue surrogates (breast, brain, liver, muscle) were all underestimated by between −0.7% and −1.8%. The SPRs of the non‐tissue materials (polymethyl methacrylate (PMMA), polyether ether ketone (PEEK), graphite and Teflon) were within 2.8% for MD‐SPR images, compared to 6.8% for DirectSPR.ConclusionsThe MD‐SPR model performed similar compared to other published methods for the human reference tissues. The SPR prediction for tissue surrogates was similar to DirectSPR and showed potential to improve SPR prediction for non‐tissue materials.

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“…Phantom materials may be used for patient‐specific quality assurance (QA), 1 machine QA and routine output checks, 2 and anthropomorphic phantoms 3 . Most of these phantom materials have been tested extensively for tissue‐ or water‐equivalence in a photon beam, but several of these validated materials are not tissue‐equivalent in a proton beam 4,5 . Less is known about the dosimetric characteristics of these materials in a therapeutic carbon ion beam.…”

Section: Introductionmentioning

confidence: 99%

Technical note: Radiological clinical equivalence for phantom materials in carbon ion therapy

Taylor,

Mirandola,

Ciocca

et al. 2024

Medical Physics

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PurposeAs carbon ion radiotherapy increases in use, there are limited phantom materials for heterogeneous or anthropomorphic phantom measurements. This work characterized the radiological clinical equivalence of several phantom materials in a therapeutic carbon ion beam.MethodsEight materials were tested for radiological material‐equivalence in a carbon ion beam. The materials were computed tomography (CT)‐scanned to obtain Hounsfield unit (HU) values, then irradiated in a monoenergetic carbon ion beam to determine relative linear stopping power (RLSP). The corresponding HU and RLSP for each phantom material were compared to clinical carbon ion calibration curves. For absorbed dose comparison, ion chamber measurements were made in the center of a carbon ion spread‐out Bragg peak (SOBP) in water and in the phantom material, evaluating whether the material perturbed the absorbed dose measurement beyond what was predicted by the HU‐RLSP relationship.ResultsPolyethylene, solid water (Gammex and Sun Nuclear), Blue Water (Standard Imaging), and Techtron HPV had measured RLSP values that agreed within ±4.2% of RLSP values predicted by the clinical calibration curve. Measured RLSP for acrylic was 7.2% different from predicted. The agreement for balsa wood and cork varied between samples. Ion chamber measurements in the phantom materials were within 0.1% of ion chamber measurements in water for most materials (solid water, Blue Water, polyethylene, and acrylic), and within 1.9% for the rest of the materials (balsa wood, cork, and Techtron HPV).ConclusionsSeveral phantom materials (Blue Water, polyethylene, solid water [Gammex and Sun Nuclear], and Techtron HPV) are suitable for heterogeneous phantom measurements for carbon ion therapy. Low density materials should be carefully characterized due to inconsistencies between samples.

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Development of optimised tissue-equivalent materials for proton therapy

Cited by 4 publications

References 32 publications

Dosimetric characteristics of 3D-printed and epoxy-based materials for particle therapy phantoms

Dosimetric characteristics of 3D-printed and epoxy-based materials for particle therapy phantoms

Prediction of proton stopping power ratios using dual‐energy CT basis material decomposition

Technical note: Radiological clinical equivalence for phantom materials in carbon ion therapy

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