ORCID Profile
0000-0002-9725-0668
Current Organisation
Peter MacCallum Cancer Centre
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Publisher: ASME International
Date: 12-10-2020
DOI: 10.1115/1.4044460
Abstract: Anthropomorphic radiotherapy phantoms require tissue-equivalent materials to achieve Hounsfield units (HU) that are comparable to those of human tissue. Traditional manufacturing methods are limited by their high-cost and incompatibility with patient-specific customization. Additive manufacture (AM) provides a significant opportunity to enable manufacture of patient-specific geometries at relatively low cost. However, AM technologies are currently limited in terms of available material types, and consequently enable very little variation in achievable HU when standard manufacturing parameters are used. This work demonstrates a novel method whereby the partial volume effect (PVE) is utilized to control the HU of an AM material, in particular, enabling low HU in the range typical of lung tissue. The method enables repeatable design of lung HU and is compatible with commercial machines using standard print parameters. A custom algorithm demonstrates the clinical application of the method, whereby patient-specific computed tomography (CT) data are algorithmically calibrated according to AM print parameters and confirmed to be robust as a custom anthropomorphic radiotherapy phantoms.
Publisher: IOP Publishing
Date: 08-2019
Publisher: Wiley
Date: 2013
DOI: 10.1118/1.4771962
Publisher: Wiley
Date: 02-2023
Abstract: Proton‐to‐photon comparative treatment planning is a current requirement of Australian Government funding for patients to receive proton beam therapy (PBT) overseas, and a future requirement for Medicare funding of PBT in Australia. Because of the fundamental differences in treatment plan creation and evaluation between PBT and conventional radiation therapy with x‐rays (XRT), there is the potential for a lack of consistency in the process of comparing PBT and XRT treatment plans. This may have an impact on patient eligibility assessment for PBT. The objective of these guidelines is to provide a practical reference document for centres performing proton‐to‐photon comparative planning and thereby facilitate national uniformity.
Publisher: The American Association of Immunologists
Date: 11-2000
DOI: 10.4049/JIMMUNOL.165.9.5161
Abstract: Understanding the basic immunology of an infectious disease requires insight into the pattern of T cell reactivity and specificity. Although lymphatic filariasis is a major tropical disease, the predominant T cell Ags of filarial species such as Brugia malayi are still undefined. We have now identified a prominent T cell Ag from B. malayi microfilariae (Mf) as Bm-SPN-2, a serpin secreted exclusively by this stage. Mf-infected mice mounted strong, but short-lived, Bm-SPN-2-specific Th1 responses, measured by in vitro production of IFN-γ, but not IL-4 or IL-5, 14 days postinfection. By day 35, responsiveness to Bm-SPN-2 was lost despite enhanced reactivity to whole Mf extract. Single immunization with Mf extract also stimulated typical Th1 reactions to Bm-SPN-2, but IgG1 Ab responses dominated after repeated immunizations. Human patients displayed potent humoral responses to Bm-SPN-2 in both IgG1 and IgG4 subclasses. Thus, 100% (20 of 20) of the microfilaremic (MF+) patients bore IgG4 responses to Bm-SPN-2, while only 30% of endemic normal subjects were similarly positive. Following chemotherapy, Bm-SPN-2-specific Abs disappeared in 12 of 13 MF+ patients, although the majority remained seropositive for whole parasite extract. PBMC from most, but not all, endemic subjects were induced to secrete IFN-γ when stimulated with Bm-SPN-2. These findings demonstrate that Bm-SPN-2 is recognized by both murine and human T and B cells and indicate that their responses are under relatively stringent temporal control. This study also provides the first ex le of a stage-specific secreted molecule that acts as a major T cell Ag from filarial parasites and is a prime candidate for a serodiagnostic probe.
Publisher: IOP Publishing
Date: 08-2019
DOI: 10.1088/1742-6596/1305/1/012048
Abstract: The utility of gel dosimeters is sought to be improved upon in this study which proposes a target region of different X-ray CT contrast that is dose sensitive. The changes in the physico-chemical makeup of nPAG caused by the addition of the X-ray imaging Iodine based contrast agent Isovue are explored. The impact of this change on dose measurements is also discussed. The increase in HU as it correlates with increasing Isovue concentration is detailed, along with the dosimetric changes that occur, namely the steepness of the dose response curve and general shape of the percentage depth dose curve. It is noted that diffusion of Isovue from one gel region to another has significant dosimetric impact and the experimental method was constructed and conducted with this in mind. Further refinement and optimisation of the Isovue nPAG formulation will lead to a target region dosimeter that can be contoured on X-ray CT and used in the improvement of planning protocols, especially in cases that involve motion and deformation of target volumes.
Publisher: Elsevier BV
Date: 07-2021
Publisher: Wiley
Date: 04-2012
DOI: 10.1118/1.3694107
Abstract: Interfraction and intrafraction variation in anatomic structures is a significant challenge in contemporary radiotherapy. The objective of this work is to develop a novel tool for deformable structure dosimetry, using a tissue-equivalent deformable gel dosimeter that can reproducibly simulate targets subject to deformation. This will enable direct measurement of integrated doses delivered in different deformation states, and the verification of dose deforming algorithms. A modified version of the nPAG polymer gel has been used as a deformable 3D dosimeter and phantom to investigate doses delivered to deforming tissue-equivalent geometry. The deformable gel (DEFGEL) dosimeter hantom is comprised of polymer gel in a latex membrane, moulded (in this case) into a cylindrical geometry, and deformed with an acrylic compressor. Fifteen aluminium fiducial markers (FM) were implanted into DEFGEL phantoms and the reproducibility of deformation was determined via multiple computed tomography (CT) scans in deformed and nondeformed states before and after multiple (up to 150) deformations. Dose was delivered to the DEFGEL phantom in three arrangements: (i) without deformation, (ii) with deformation, and (iii) cumulative exposures with and without deformation, i.e., dose integration. Irradiations included both square field and a stereotactic multiple dynamic arc treatment adapted from a patient plan. Doses delivered to the DEFGEL phantom were read out using cone beam optical CT. Reproducibility was verified by observation of interscan shifts of FM locations (as determined via CT), measured from an absolute reference point and in terms of inter-FM distance. The majority (76%) of points exhibited zero shift, with others shifting by one pixel size consistent with setup error as confirmed with a control s le. Comparison of dose profiles and 2D isodose distributions from the three arrangements illustrated complex spatial redistribution of dose in all three dimensions occurring as a result of the change in shape of the target between irradiations, even for a relatively simple deformation. Discrepancies of up to 30% of the maximum dose were evident from dose difference maps for three orthogonal planes taken through the isocenter of a stereotactic field. This paper describes the first use of a tissue-equivalent, 3D dose-integrating deformable phantom that yields integrated or redistributed dosimetric information. The proposed methodology readily yields three-dimensional (3D) dosimetric data from radiation delivery to the DEFGEL phantom in deformed and undeformed states. The impacts of deformation on dose distributions were readily seen in the isodose contours and line profiles from the three arrangements. It is demonstrated that the system is potentially capable of reproducibly emulating the physical deformation of an organ, and therefore can be used to evaluate absorbed doses to deformable targets and organs at risk in three dimensions and to validate deformation algorithms applied to dose distributions.
Publisher: Elsevier BV
Date: 02-2021
Publisher: IOP Publishing
Date: 05-2017
Publisher: Wiley
Date: 13-02-2020
DOI: 10.1002/ACM2.12825
Publisher: SAGE Publications
Date: 20-05-2016
Abstract: Intrafraction organ deformation may be accounted for by inclusion of temporal information in dose calculation models. In this article, we demonstrate a quasi-4-dimensional method for improved risk estimation. Conventional 3-dimensional and quasi-4-dimensional calculations employing dose warping for dose accumulation were undertaken for patients with liver metastases planned for 42 Gy in 6 fractions of stereotactic body radiotherapy. Normal tissue complication probabilities and stochastic risks for radiation-induced carcinogenesis and cardiac complications were evaluated for healthy peripheral structures. Hypothetical assessments of other commonly employed dose/fractionation schedules on normal tissue complication probability estimates were explored. Conventional 3-dimensional dose computation may result in significant under- or overestimation of doses to organ at risk. For instance, doses differ (on average) by 17% (σ = 14%) for the left kidney, by 14% (σ = 7%) for the right kidney, by 7% (σ = 9%) for the large bowel, and by 10% (σ = 14%) for the duodenum. Discrepancies in the excess relative risk range up to about 30%. The 3-dimensional approach was shown to result in cardiac complication risks underestimated by %. For liver stereotactic body radiotherapy, we have shown that conventional 3-dimensional dose calculation may significantly over-/underestimate dose to organ at risk (90%-120% of the 4-dimensional estimate for the mean dose and 20%-150% for D 2% ). Providing dose estimates that most closely represent the actual dose delivered will provide valuable information to improve our understanding of the dose response for partial volume irradiation using hypofractionated schedules. Excess relative risks of radiocarcinogenesis were shown to range up to approximately excess relative risk = 4 and the prediction thereof depends greatly on the use of either 3-dimensional or 4-dimensional methods (with corresponding results differing by tens of percent).
Publisher: IOP Publishing
Date: 2019
Publisher: IOP Publishing
Date: 12-01-2015
Publisher: Wiley
Date: 02-08-2020
DOI: 10.1002/JMRS.417
Publisher: Elsevier BV
Date: 07-2023
Publisher: Elsevier BV
Date: 11-2012
DOI: 10.1016/J.IJROBP.2012.05.029
Abstract: Gold nanoparticles (AuNps), because of their high atomic number (Z), have been demonstrated to absorb low-energy X-rays preferentially, compared with tissue, and may be used to achieve localized radiation dose enhancement in tumors. The purpose of this study is to introduce the first ex le of a novel multicompartment radiochromic radiation dosimeter and to demonstrate its applicability for 3-dimensional (3D) dosimetry of nanoparticle-enhanced radiation therapy. A novel multicompartment phantom radiochromic dosimeter was developed. It was designed and formulated to mimic a tumor loaded with AuNps (50 nm in diameter) at a concentration of 0.5 mM, surrounded by normal tissues. The novel dosimeter is referred to as the Sensitivity Modulated Advanced Radiation Therapy (SMART) dosimeter. The dosimeters were irradiated with 100-kV and 6-MV X-ray energies. Dose enhancement produced from the interaction of X-rays with AuNps was calculated using spectrophotometric and cone-beam optical computed tomography scanning by quantitatively comparing the change in optical density and 3D datasets of the dosimetric measurements between the tissue-equivalent (TE) and TE/AuNps compartments. The interbatch and intrabatch variability and the postresponse stability of the dosimeters with AuNps were also assessed. Radiation dose enhancement factors of 1.77 and 1.11 were obtained using 100-kV and 6-MV X-ray energies, respectively. The results of this study are in good agreement with previous observations however, for the first time we provide direct experimental confirmation and 3D visualization of the radiosensitization effect of AuNps. The dosimeters with AuNps showed small (<3.5%) interbatch variability and negligible (<0.5%) intrabatch variability. The SMART dosimeter yields experimental insights concerning the spatial distributions and elevated dose in nanoparticle-enhanced radiation therapy, which cannot be performed using any of the current methods. The authors concluded that it can be used as a novel independent method for nanoparticle-enhanced radiation therapy dosimetry.
Publisher: Springer Science and Business Media LLC
Date: 27-11-2019
DOI: 10.1186/S13014-019-1392-Z
Abstract: Accurate and standardized descriptions of organs at risk (OARs) are essential in radiation therapy for treatment planning and evaluation. Traditionally, physicians have contoured patient images manually, which, is time-consuming and subject to inter-observer variability. This study aims to a) investigate whether customized, deep-learning-based auto-segmentation could overcome the limitations of manual contouring and b) compare its performance against a typical, atlas-based auto-segmentation method organ structures in liver cancer. On - contrast computer tomography image sets of 70 liver cancer patients were used, and four OARs (heart, liver, kidney, and stomach) were manually delineated by three experienced physicians as reference structures. Atlas and deep learning auto-segmentations were respectively performed with MIM Maestro 6.5 (MIM Software Inc., Cleveland, OH) and, with a deep convolution neural network (DCNN). The Hausdorff distance (HD) and, dice similarity coefficient (DSC), volume overlap error (VOE), and relative volume difference (RVD) were used to quantitatively evaluate the four different methods in the case of the reference set of the four OAR structures. The atlas-based method yielded the following average DSC and standard deviation values (SD) for the heart, liver, right kidney, left kidney, and stomach: 0.92 ± 0.04 (DSC ± SD), 0.93 ± 0.02, 0.86 ± 0.07, 0.85 ± 0.11, and 0.60 ± 0.13 respectively. The deep-learning-based method yielded corresponding values for the OARs of 0.94 ± 0.01, 0.93 ± 0.01, 0.88 ± 0.03, 0.86 ± 0.03, and 0.73 ± 0.09. The segmentation results show that the deep learning framework is superior to the atlas-based framwork except in the case of the liver. Specifically, in the case of the stomach, the DSC, VOE, and RVD showed a maximum difference of 21.67, 25.11, 28.80% respectively. In this study, we demonstrated that a deep learning framework could be used more effectively and efficiently compared to atlas-based auto-segmentation for most OARs in human liver cancer. Extended use of the deep-learning-based framework is anticipated for auto-segmentations of other body sites.
Publisher: Wiley
Date: 27-07-2012
DOI: 10.1118/1.4736534
Abstract: Strategies for dose accumulation in deforming anatomy are of interest in radiotherapy. Algorithms exist for the deformation of dose based on patient image sets, though these are sometimes contentious because not all such image calculations are constrained by physical laws. While tumor and organ motion has been a key area of study for a considerable amount of time, deformation is of increasing interest. In this work, we demonstrate a full 3D experimental validation of results from a range of dose deformation algorithms available in the public domain. We recently developed the first tissue-equivalent, full 3D deformable dosimetric phantom-"DEFGEL." To assess the accuracy of dose-warping based on deformable image registration (DIR), we have measured doses in undeformed and deformed states of the DEFGEL dosimeter and compared these to planned doses and warped doses. In this way we have directly evaluated the accuracy of dose-warping calculations for 11 different algorithms. We have done this for a range of stereotactic irradiation schemes and types and magnitudes of deformation. The original Horn and Schunck algorithm is shown to be the best performing of the 11 algorithms trialled. Comparing measured and dose-warped calculations for this method, it is found that for a 10 × 10 mm(2) square field, γ(3%∕3mm) = 99.9% for a 20 × 20 mm(2) cross-shaped field, γ(3%∕3mm) = 99.1% and for a multiple dynamic arc (0.413 cm(3) PTV) treatment adapted from a patient treatment plan, γ(3%∕3mm) = 95%. In each case, the agreement is comparable to-but consistently ∼1% less than-comparison between measured and calculated (planned) dose distributions in the absence of deformation. The magnitude of the deformation, as measured by the largest displacement experienced by any voxel in the volume, has the greatest influence on the accuracy of the warped dose distribution. Considering the square field case, the smallest deformation (∼9 mm) yields agreement of γ(3%∕3mm) = 99.9%, while the most significant deformation (∼20 mm) yields agreement of γ(3%∕3mm) = 96.7%. We have confirmed that, for a range of mass and density conserving deformations representative of those observable in anatomical targets, DIR-based dose-warping can yield accurate predictions of the dose distribution. Substantial differences can be seen between the results of different algorithms indicating that DIR performance should be scrutinized before application todose-warping. We have demonstrated that the DEFGEL deformable dosimeter can be used to evaluate DIR performance and the accuracy of dose-warping results by direct measurement.
Publisher: SAGE Publications
Date: 2019
Abstract: Additive manufacturing or 3-dimensional printing has become a widespread technology with many applications in medicine. We have conducted a systematic review of its application in radiation oncology with a particular emphasis on the creation of phantoms for image quality assessment and radiation dosimetry. Traditionally used phantoms for quality assurance in radiotherapy are often constraint by simplified geometry and homogenous nature to perform imaging analysis or pretreatment dosimetric verification. Such phantoms are limited due to their ability in only representing the average human body, not only in proportion and radiation properties but also do not accommodate pathological features. These limiting factors restrict the patient-specific quality assurance process to verify image-guided positioning accuracy and/or dose accuracy in “water-like” condition. English speaking manuscripts published since 2008 were searched in 5 databases (Google Scholar, Scopus, PubMed, IEEE Xplore, and Web of Science). A significant increase in publications over the 10 years was observed with imaging and dosimetry phantoms about the same total number (52 vs 50). Key features of additive manufacturing are the customization with creation of realistic pathology as well as the ability to vary density and as such contrast. Commonly used printing materials, such as polylactic acid, acrylonitrile butadiene styrene, high-impact polystyrene and many more, are utilized to achieve a wide range of achievable X-ray attenuation values from −1000 HU to 500 HU and higher. Not surprisingly, multimaterial printing using the polymer jetting technology is emerging as an important printing process with its ability to create heterogeneous phantoms for dosimetry in radiotherapy. Given the flexibility and increasing availability and low cost of additive manufacturing, it can be expected that its applications for radiation medicine will continue to increase.
Publisher: Elsevier BV
Date: 03-2010
DOI: 10.1016/J.BIOS.2009.11.017
Abstract: We fabricated a capacitance sensor based on an anodized aluminum oxide (AAO) nanoporous structure to detect DNA hybridization. We utilized Au film deposited on the surface of the AAO membrane and Au nanowires infiltrating the nanopores as the top and bottom electrodes, respectively. When completely complementary target DNA molecules were added to the sensor-immobilized DNA molecule probes, the capacitance was reduced with a concentration of 1pM, the capacitance decreased by approximately 10%. We measured the capacitance change for different concentrations of the target DNA solution. A linear relationship was found between the capacitance change and DNA concentration on a semi-logarithmic scale. We also investigated the possibility of detecting DNA molecules with a single-base mismatch to the probe DNA molecule. In contrast to complementary target DNA molecules, the addition of one-base mismatch DNA molecules caused no significant change in capacitance, demonstrating that DNA hybridization was detected with single nucleotide polymorphism sensitivity.
Publisher: Wiley
Date: 11-2014
Publisher: Wiley
Date: 10-09-2013
DOI: 10.1118/1.4819945
Abstract: Deformable image registration (DIR) has become a key tool for adaptive radiotherapy to account for inter- and intrafraction organ deformation. Of contemporary interest, the application to deformable dose accumulation requires accurate deformation even in low contrast regions where dose gradients may exist within near-uniform tissues. One expects high-contrast features to generally be deformed more accurately by DIR algorithms. The authors systematically assess the accuracy of 12 DIR algorithms and quantitatively examine, in particular, low-contrast regions, where accuracy has not previously been established. This work investigates DIR algorithms in three dimensions using deformable gel (DEFGEL) [U. J. Yeo, M. L. Taylor, L. Dunn, R. L. Smith, T. Kron, and R. D. Franich, "A novel methodology for 3D deformable dosimetry," Med. Phys. 39, 2203-2213 (2012)], for application to mass- and density-conserving deformations. CT images of DEFGEL phantoms with 16 fiducial markers (FMs) implanted were acquired in deformed and undeformed states for three different representative deformation geometries. Nonrigid image registration was performed using 12 common algorithms in the public domain. The optimum parameter setup was identified for each algorithm and each was tested for deformation accuracy in three scenarios: (I) original images of the DEFGEL with 16 FMs (II) images with eight of the FMs mathematically erased and (III) images with all FMs mathematically erased. The deformation vector fields obtained for scenarios II and III were then applied to the original images containing all 16 FMs. The locations of the FMs estimated by the algorithms were compared to actual locations determined by CT imaging. The accuracy of the algorithms was assessed by evaluation of three-dimensional vectors between true marker locations and predicted marker locations. The mean magnitude of 16 error vectors per s le ranged from 0.3 to 3.7, 1.0 to 6.3, and 1.3 to 7.5 mm across algorithms for scenarios I to III, respectively. The greatest accuracy was exhibited by the original Horn and Schunck optical flow algorithm. In this case, for scenario III (erased FMs not contributing to driving the DIR calculation), the mean error was half that of the modified demons algorithm (which exhibited the greatest error), across all deformations. Some algorithms failed to reproduce the geometry at all, while others accurately deformed high contrast features but not low-contrast regions-indicating poor interpolation between landmarks. The accuracy of DIR algorithms was quantitatively evaluated using a tissue equivalent, mass, and density conserving DEFGEL phantom. For the model studied, optical flow algorithms performed better than demons algorithms, with the original Horn and Schunck performing best. The degree of error is influenced more by the magnitude of displacement than the geometric complexity of the deformation. As might be expected, deformation is estimated less accurately for low-contrast regions than for high-contrast features, and the method presented here allows quantitative analysis of the differences. The evaluation of registration accuracy through observation of the same high contrast features that drive the DIR calculation is shown to be circular and hence misleading.
Publisher: Wiley
Date: 03-11-2020
DOI: 10.1002/ACM2.13076
No related grants have been discovered for Adam Yeo.