ORCID Profile
0000-0002-3862-2644
Current Organisation
University of Adelaide
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Publisher: Wiley
Date: 29-05-2012
DOI: 10.1118/1.4719963
Abstract: The objective of the current work was to develop an algorithm for growing a macroscopic tumor volume from in idual randomized quasi-realistic cells. The major physical and chemical components of the cell need to be modeled. It is intended to import the tumor volume into GEANT4 (and potentially other Monte Carlo packages) to simulate ionization events within the cell regions. A MATLAB© code was developed to produce a tumor coordinate system consisting of in idual ellipsoidal cells randomized in their spatial coordinates, sizes, and rotations. An eigenvalue method using a mathematical equation to represent in idual cells was used to detect overlapping cells. GEANT4 code was then developed to import the coordinate system into GEANT4 and populate it with in idual cells of varying sizes and composed of the membrane, cytoplasm, reticulum, nucleus, and nucleolus. Each region is composed of chemically realistic materials. The in-house developed MATLAB© code was able to grow semi-realistic cell distributions (~2 × 10(8) cells in 1 cm(3)) in under 36 h. The cell distribution can be used in any number of Monte Carlo particle tracking toolkits including GEANT4, which has been demonstrated in this work. Using the cell distribution and GEANT4, the authors were able to simulate ionization events in the in idual cell components resulting from 80 keV gamma radiation (the code is applicable to other particles and a wide range of energies). This virtual microdosimetry tool will allow for a more complete picture of cell damage to be developed.
Publisher: Springer Science and Business Media LLC
Date: 12-08-2020
Publisher: Springer Science and Business Media LLC
Date: 30-08-2018
Publisher: Wiley
Date: 26-12-2019
DOI: 10.1002/MP.13332
Abstract: Indirect biological damage due to reactive species produced in water radiolysis reactions is responsible for the majority of biological effect for low linear energy transfer (LET) radiation. Modeling water radiolysis and the subsequent interactions of reactive species, as well as track structures, is essential to model radiobiology on the microscale. Recently, chemistry models have been developed for Geant4-DNA to be used in combination with the comprehensive existing physics models. In the current work, the first detailed, independent, in silico validation of all species yields with published experimental observations and comparison with other radiobiological simulations is presented. Additionally, the effect of LET of protons and heavier ions on reactive species yield in the model was examined, as well as the completeness of the chemical reactions following the radiolysis within the time after physical interactions simulated in the model. Yields over time of reactive species were simulated for water radiolysis by incident electrons, protons, alpha particles, and ions with various LETs using Geant4 and RITRACKS simulation tools. Water dissociation and recombination was simulated using Geant4 to determine the completeness of chemical reactions at the end of the simulation. Yield validation was performed by comparing yields simulated using Geant4 with experimental observations and other simulations. Validation was performed for all species for low LET radiation and the solvated electron and hydroxyl radical for high LET ions. It was found that the Geant4-DNA chemistry yields were generally in good agreement with experimental observations and other simulations. However, the Geant4-DNA yields for the hydroxyl radical and hydrogen peroxide at the end of the chemistry stage were found to be respectively considerably higher and lower than the experimentally observed yields. Increasing the LET of incident hadrons increased the yield of secondary species and decreased the yield of primary species. The effect of LET on the yield of the hydroxyl radical at 100 ns simulated with Geant4 was in good agreement with experimental measurements. Additionally, by the end of the simulation only 40% of dissociated water molecules had been recombined and the rate of recombination was slowing. The yields simulated using Geant4 are within reasonable agreement with experimental observations. Higher LET radiation corresponds with increased yields of secondary species and decreased yields of primary species. These trends combined with the LET having similar effects on the 100 ns hydroxyl radical yield for Geant4 and experimental measurements indicate that Geant4 accurately models the effect of LET on radiolysis yields. The limited recombination within the modeled chemistry stage and the slowing rate of recombination at the end of the stage indicate potential long-range indirect biological damage.
Publisher: Elsevier BV
Date: 12-2017
DOI: 10.1016/J.EJMP.2017.11.013
Abstract: Proton therapy can be a highly effective strategy for the treatment of tumours. However, compared with X-ray therapy it is more expensive and has limited availability. In addition, it is not always clear whether it will benefit an in idual patient more than a course of traditional X-ray therapy. Basing a treatment decision on outcomes of clinical trials can be difficult due to a shortage of data. Predictive modelling studies are becoming an attractive alternative to supplement clinical decisions. The aim of the current work is to present a Markov framework that compares clinical outcomes for proton and X-ray therapy. A Markov model has been developed which estimates the radiobiological effect of a given treatment plan. This radiobiological effect is estimated using the tumour control probability (TCP), normal tissue complication probability (NTCP) and second primary cancer induction probability (SPCIP). These metrics are used as transition probabilities in the Markov chain. The clinical outcome is quantified by the quality adjusted life expectancy. To demonstrate functionality, the model was applied to a 6-year-old patient presenting with skull base chordoma. The model was successfully developed to compare clinical outcomes for proton and X-ray treatment plans. For the ex le patient considered, it was predicted that proton therapy would offer a significant advantage compared with volumetric modulated arc therapy in terms of survival and mitigating injuries. The functionality of the model was demonstrated using the ex le patient. The proposed Markov method may be a useful tool for deciding on a treatment strategy for in idual patients.
Publisher: Wiley
Date: 07-07-2020
DOI: 10.1002/JMRS.416
Publisher: Wiley
Date: 16-03-2021
DOI: 10.1002/MP.14780
Publisher: Springer Science and Business Media LLC
Date: 11-12-2019
DOI: 10.1038/S41598-019-54941-1
Abstract: The repair or misrepair of DNA double-strand breaks (DSBs) largely determines whether a cell will survive radiation insult or die. A new computational model of multicellular, track structure-based and pO 2 -dependent radiation-induced cell death was developed and used to investigate the contribution to cell killing by the mechanism of DNA free-end misrejoining for low-LET radiation. A simulated tumor of 1224 squamous cells was irradiated with 6 MV x-rays using the Monte Carlo toolkit Geant4 with low-energy Geant4-DNA physics and chemistry modules up to a uniform dose of 1 Gy. DNA damage including DSBs were simulated from ionizations, excitations and hydroxyl radical interactions along track segments through cell nuclei, with a higher cellular pO 2 enhancing the conversion of DNA radicals to strand breaks. DNA free-ends produced by complex DSBs (cDSBs) were able to misrejoin and produce exchange-type chromosome aberrations, some of which were asymmetric and lethal. A sensitivity analysis was performed and conditions of full oxia and anoxia were simulated. The linear component of cell killing from misrejoining was consistently small compared to values in the literature for the linear component of cell killing for head and neck squamous cell carcinoma (HNSCC). This indicated that misrejoinings involving DSBs from the same x-ray (including all associated secondary electrons) were rare and that other mechanisms (e.g. unrejoined ends) may be important. Ignoring the contribution by the indirect effect toward DNA damage caused the DSB yield to drop to a third of its original value and the cDSB yield to drop to a tenth of its original value. Track structure-based cell killing was simulated in all 135306 viable cells of a 1 mm 3 hypoxic HNSCC tumor for a uniform dose of 1 Gy.
Publisher: Wiley
Date: 02-04-2022
DOI: 10.1002/JMRS.579
Publisher: Informa UK Limited
Date: 04-2017
DOI: 10.2147/HP.S133231
Publisher: Springer Science and Business Media LLC
Date: 10-02-2020
Publisher: American Chemical Society (ACS)
Date: 22-04-2019
Publisher: Springer Science and Business Media LLC
Date: 17-05-2021
Publisher: Elsevier BV
Date: 09-2021
Publisher: Hindawi Limited
Date: 2015
DOI: 10.1155/2015/968429
Abstract: The major differences between the physics models in Geant4-DNA and RITRACKS Monte Carlo packages are investigated. Proton and electron ionisation interactions and electron excitation interactions in water are investigated in the current work. While these packages use similar semiempirical physics models for inelastic cross-sections, the implementation of these models is demonstrated to be significantly different. This is demonstrated in a simple Monte Carlo simulation designed to identify differences in interaction cross-sections.
Publisher: MDPI AG
Date: 22-06-2020
DOI: 10.3390/IJMS21124431
Abstract: Gold nanoparticle (GNP) enhanced proton therapy is a promising treatment concept offering increased therapeutic effect. It has been demonstrated in experiments which provided indications that reactive species play a major role. Simulations of the radiolysis yield from GNPs within a cell model were performed using the Geant4 toolkit. The effect of GNP cluster size, distribution and number, cell and nuclear membrane absorption and intercellular yields were evaluated. It was found that clusters distributed near the nucleus increased the nucleus yield by 91% while reducing the cytoplasm yield by 7% relative to a disperse distribution. Smaller cluster sizes increased the yield, 200 nm clusters had nucleus and cytoplasm yields 117% and 35% greater than 500 nm clusters. Nuclear membrane absorption reduced the cytoplasm and nucleus yields by 8% and 35% respectively to a permeable membrane. Intercellular enhancement was negligible. Smaller GNP clusters delivered near sub-cellular targets maximise radiosensitisation. Nuclear membrane absorption reduces the nucleus yield, but can damage the membrane providing another potential pathway for biological effect. The minimal effect on adjacent cells demonstrates that GNPs provide a targeted enhancement for proton therapy, only effecting cells with GNPs internalised. The provided quantitative data will aid further experiments and clinical trials.
Publisher: Wiley
Date: 14-10-2023
DOI: 10.1002/ACM2.14182
Publisher: Wiley
Date: 12-06-2013
DOI: 10.1118/1.4808150
Abstract: Investigation of increased radiation dose deposition due to gold nanoparticles (GNPs) using a 3D computational cell model during x-ray radiotherapy. Two GNP simulation scenarios were set up in Geant4 a single 400 nm diameter gold cluster randomly positioned in the cytoplasm and a 300 nm gold layer around the nucleus of the cell. Using an 80 kVp photon beam, the effect of GNP on the dose deposition in five modeled regions of the cell including cytoplasm, membrane, and nucleus was simulated. Two Geant4 physics lists were tested: the default Livermore and custom built Livermore/DNA hybrid physics list. 10(6) particles were simulated at 840 cells in the simulation. Each cell was randomly placed with random orientation and a diameter varying between 9 and 13 μm. A mathematical algorithm was used to ensure that none of the 840 cells overlapped. The energy dependence of the GNP physical dose enhancement effect was calculated by simulating the dose deposition in the cells with two energy spectra of 80 kVp and 6 MV. The contribution from Auger electrons was investigated by comparing the two GNP simulation scenarios while activating and deactivating atomic de-excitation processes in Geant4. The physical dose enhancement ratio (DER) of GNP was calculated using the Monte Carlo model. The model has demonstrated that the DER depends on the amount of gold and the position of the gold cluster within the cell. In idual cell regions experienced statistically significant (p < 0.05) change in absorbed dose (DER between 1 and 10) depending on the type of gold geometry used. The DER resulting from gold clusters attached to the cell nucleus had the more significant effect of the two cases (DER ≈ 55). The DER value calculated at 6 MV was shown to be at least an order of magnitude smaller than the DER values calculated for the 80 kVp spectrum. Based on simulations, when 80 kVp photons are used, Auger electrons have a statistically insignificant (p < 0.05) effect on the overall dose increase in the cell. The low energy of the Auger electrons produced prevents them from propagating more than 250-500 nm from the gold cluster and, therefore, has a negligible effect on the overall dose increase due to GNP. The results presented in the current work show that the primary dose enhancement is due to the production of additional photoelectrons.
Publisher: Springer Science and Business Media LLC
Date: 08-02-2023
DOI: 10.1007/S13246-023-01229-4
Abstract: Optical scanning technologies are increasingly being utilised to supplement treatment workflows in radiation oncology, such as surface-guided radiotherapy or 3D printing custom bolus. One limitation of optical scanning devices is the absence of internal anatomical information of the patient being scanned. As a result, conventional radiation therapy treatment planning using this imaging modality is not feasible. Deep learning is useful for automating various manual tasks in radiation oncology, most notably, organ segmentation and treatment planning. Deep learning models have also been used to transform MRI datasets into synthetic CT datasets, facilitating the development of MRI-only radiation therapy planning. To train a pix2pix generative adversarial network to transform 3D optical scan data into estimated MRI datasets for a given patient to provide additional anatomical data for a select few radiation therapy treatment sites. The proposed network may provide useful anatomical information for treatment planning of surface mould brachytherapy, total body irradiation, and total skin electron therapy, for ex le, without delivering any imaging dose. A 2D pix2pix GAN was trained on 15,000 axial MRI slices of healthy adult brains paired with corresponding external mask slices. The model was validated on a further 5000 previously unseen external mask slices. The predictions were compared with the “ground-truth” MRI slices using the multi-scale structural similarity index (MSSI) metric. A certified neuro-radiologist was subsequently consulted to provide an independent review of the model’s performance in terms of anatomical accuracy and consistency. The network was then applied to a 3D photogrammetry scan of a test subject to demonstrate the feasibility of this novel technique. The trained pix2pix network predicted MRI slices with a mean MSSI of 0.831 ± 0.057 for the 5000 validation images indicating that it is possible to estimate a significant proportion of a patient’s gross cranial anatomy from a patient’s exterior contour. When independently reviewed by a certified neuro-radiologist, the model’s performance was described as “quite amazing, but there are limitations in the regions where there is wide variation within the normal population.” When the trained network was applied to a 3D model of a human subject acquired using optical photogrammetry, the network could estimate the corresponding MRI volume for that subject with good qualitative accuracy. However, a ground-truth MRI baseline was not available for quantitative comparison. A deep learning model was developed, to transform 3D optical scan data of a patient into an estimated MRI volume, potentially increasing the usefulness of optical scanning in radiation therapy planning. This work has demonstrated that much of the human cranial anatomy can be predicted from the external shape of the head and may provide an additional source of valuable imaging data. Further research is required to investigate the feasibility of this approach for use in a clinical setting and further improve the model’s accuracy.
Publisher: MDPI AG
Date: 09-2019
DOI: 10.3390/IJMS20174280
Abstract: Gold nanoparticles (GNPs) are promising radiosensitizers with the potential to enhance radiotherapy. Experiments have shown GNP enhancement of proton therapy and indicated that chemical damage by reactive species plays a major role. Simulations of the distribution and yield of reactive species from 10 ps to 1 µs produced by a single GNP, two GNPs in proximity and a GNP cluster irradiated with a proton beam were performed using the Geant4 Monte Carlo toolkit. It was found that the reactive species distribution at 1 µs extended a few hundred nm from a GNP and that the largest enhancement occurred over 50 nm from the nanoparticle. Additionally, the yield for two GNPs in proximity and a GNP cluster was reduced by up to 17% and 60% respectively from increased absorption. The extended range of action from the diffusion of the reactive species may enable simulations to model GNP enhanced proton therapy. The high levels of absorption for a large GNP cluster suggest that smaller clusters and diffuse GNP distributions maximize the total radiolysis yield within a cell. However, this must be balanced against the high local yields near a cluster particularly if the cluster is located adjacent to a biological target.
Publisher: American Chemical Society (ACS)
Date: 16-10-2015
DOI: 10.1021/ACS.ANALCHEM.5B03183
Abstract: Internalized gold nanoparticles were quantified in large numbers of in idual prostate cancer cells using large area synchrotron X-ray fluorescence microscopy. Cells were also irradiated with a 6 MV linear accelerator to assess the biological consequence of radiosensitization with gold nanoparticles. A large degree of heterogeneity in nanoparticle uptake between cells resulted in influenced biological effect.
Publisher: Wiley
Date: 02-12-2019
DOI: 10.1002/MP.13923
Abstract: Radiosensitizer enhanced radiotherapy provides the possibility of improved treatment outcomes by preferentially increasing the effectiveness of radiation within the tumor. Proton therapy offers improved sparing of tissue distal of the tumor along the beam path and reduced integral dose compared to conventional photon therapy. The combination of proton therapy with radiosensitizers offers the potential for an enhanced therapy with increased effect within the tumor and low integral dose. The simulations performed in this work determine the effect of nanoparticle characteristics and proton energy on the nanoscale dose and radiolysis yield enhancement for a single gold nanoparticle irradiated with a proton beam. This data can be used to determine optimal nanoparticle characteristics to enhance proton therapy. A two-stage Monte Carlo simulation was performed using Geant4. In the first stage of the simulation, the physical interactions of protons within a gold nanoparticle were modeled and the secondary electrons escaping the nanoparticle's surface were scored in a phase space file. In the second stage of the simulation, the phase space file was used as an input to model the physical interactions of the secondary electrons in water and the resulting production and chemical interactions of reactive species. By comparing a gold nanoparticle with an equivalent water nanoparticle, the nanoscale enhancement of dose and radiolysis yield was calculated. A large nanoscale enhancement of both the dose and radiolysis yield of up to a factor of 11 due to gold nanoparticles was found for most simulated conditions. For 50 nm gold nanoparticles, a large enhancement factor of 9-11 was observed for high proton energies however, the enhancement was reduced for proton energies below 10 MeV. For 5 MeV incident protons, it was found that the enhancement factor was approximately 9 for gold nanoparticles of sizes 5-25 nm with a reduction in enhancement observed for nanoparticle sizes outside this range. Additionally, it was found that larger nanoparticle sizes resulted in greater total energy deposition and radiolysis yields per proton flux but with reduced efficiency per nanoparticle mass. It was observed that a large loss of enhancement occurred for thick nanoparticle coatings. However, for polyethylene glycol (PEG) coatings, coating density had a minimal effect on enhancement. A large enhancement in dose and radiolysis yield was observed. However, the low-energy secondary electrons produced within the gold for lower energy protons are susceptible to self-absorption and result in the loss of enhancement observed for larger nanoparticles and thicker coatings. The radiolysis yield and dose increase with nanoparticle size however, the yield and dose per gold mass decrease due to self-absorption. Therefore, an intermediate nanoparticle size of approximately 10-25 nm maximizes both the radiolysis yield and dose as well as the enhancement. Coatings should be kept to the minimum effective thickness to limit the loss of enhancement. For molecular coatings such as PEG, coating density should be maximized as this increases the coating's effectiveness with only a minimal effect on enhancement.
Publisher: Springer Science and Business Media LLC
Date: 08-09-2017
DOI: 10.1038/S41598-017-11444-1
Abstract: Tumor oxygenation has been correlated with treatment outcome for radiotherapy. In this work, the dependence of tumor oxygenation on tumor vascularity and blood oxygenation was determined quantitatively in a 4D stochastic computational model of head and neck squamous cell carcinoma (HNSCC) tumor growth and angiogenesis. Additionally, the impacts of the tumor oxygenation and the cancer stem cell (CSC) symmetric ision probability on the tumor volume doubling time and the proportion of CSCs in the tumor were also quantified. Clinically relevant vascularities and blood oxygenations for HNSCC yielded tumor oxygenations in agreement with clinical data for HNSCC. The doubling time varied by a factor of 3 from well oxygenated tumors to the most severely hypoxic tumors of HNSCC. To obtain the doubling times and CSC proportions clinically observed in HNSCC, the model predicts a CSC symmetric ision probability of approximately 2% before treatment. To obtain the doubling times clinically observed during treatment when accelerated repopulation is occurring, the model predicts a CSC symmetric ision probability of approximately 50%, which also results in CSC proportions of 30–35% during this time.
Publisher: Elsevier BV
Date: 03-2018
DOI: 10.1016/J.EJMP.2018.03.004
Abstract: The use of gold nanoparticle (GNP) and other metal nanoparticle (MNP) radiosensitisers to enhance radiotherapy offers the potential of improved treatment outcomes. Originally intended for use with X-ray therapy, the possibility of enhanced hadron therapy is desirable due to the superior sparing of healthy tissue in hadron therapy compared to conventional X-ray therapy. While MNPs were not expected to be effective radiosensitisers for hadron therapy due to the limited Z dependence of interactions, recent experimental measurements have contradicted this expectation. Key experimental measurements and Monte Carlo simulations of MNP radiosensitisation for hadron irradiation are reviewed in the current work. Numerous experimental measurements have found a large radiosensitisation effect due to MNPs for proton and carbon ion irradiation. Experiments have also indicated that the radiosensitisation is due in large part to enhanced reactive oxygen species (ROS) production. Simulations have found a large radial dose and ROS enhancement on the nanoscale around a single MNP. However, the short range of the dose enhancement is insufficient for a large macroscale dose enhancement or enhanced biological effect in a cell model considering dose to the nucleus from GNPs in the cytoplasm (a distribution observed in most experiments).
Publisher: Elsevier BV
Date: 09-2019
DOI: 10.1016/J.BRACHY.2019.05.006
Abstract: We propose a novel method of designing surface mold brachytherapy applicators using optical photogrammetry. The accuracy of this technique for the purpose of 3D-printing surface mold brachytherapy applicators is investigated. Photogrammetry was used to generate a 3D model of a patient's right arm. The geometric accuracy of the model was evaluated against CT in terms of volume, surface area, and the Hausdorff distance. A surface mold applicator was then 3D printed using this reconstructed model. The accuracy was evaluated by analyzing the displacement and air-gap volumes between the applicator and plaster cast on a CT image. This technique was subsequently applied to generate a 3D-printed applicator of the author's hand directly, as a proof of principle, using only photographic images. The volume and surface area of the model were within 0.1% and 2.6% of the CT-obtained values, respectively. Using the Hausdorff distance metric, it was determined that 93% of the visible vertices present in the CT-derived model had a matching vertex on the photogrammetry-derived model within 1 mm, indicating a high level of similarity. The maximum displacement between the plaster cast of the patient's arm and the photo-derived 3D-printed applicator was 1.2 mm with a total air-gap volume of approximately 0.05 cm Photogrammetry has been applied to the task of generating 3D-printed brachytherapy surface mold applicators. The current work demonstrates the feasibility and accuracy of this technique and how it may be incorporated into a 3D-printing brachytherapy workflow.
Publisher: Elsevier BV
Date: 10-2016
DOI: 10.1016/J.EJMP.2016.09.007
Abstract: Emerging radiotherapy treatments including targeted particle therapy, hadron therapy or radiosensitisation of cells by high-Z nanoparticles demand the theoretical determination of radiation track structure at the nanoscale. This is essential in order to evaluate radiation damage at the cellular and DNA level. Since 2007, Geant4 offers physics models to describe particle interactions in liquid water at the nanometre level through the Geant4-DNA Package. This package currently provides a complete set of models describing the event-by-event electromagnetic interactions of particles with liquid water, as well as developments for the modelling of water radiolysis. Since its release, Geant4-DNA has been adopted as an investigational tool in kV and MV external beam radiotherapy, hadron therapies using protons and heavy ions, targeted therapies and radiobiology studies. It has been benchmarked with respect to other track structure Monte Carlo codes and, where available, against reference experimental measurements. While Geant4-DNA physics models and radiolysis modelling functionalities have already been described in detail in the literature, this review paper summarises and discusses a selection of representative papers with the aim of providing an overview of a) geometrical descriptions of biological targets down to the DNA size, and b) the full spectrum of current micro- and nano-scale applications of Geant4-DNA.
Publisher: Wiley
Date: 22-03-2017
DOI: 10.1002/MP.12130
Abstract: A stochastic computer model of tumour growth with spatial and temporal components that includes tumour angiogenesis was developed. In the current work it was used to simulate head and neck tumour growth. The model also provides the foundation for a 4D cellular radiotherapy simulation tool. The model, developed in Matlab, contains cell positions randomised in 3D space without overlap. Blood vessels are represented by strings of blood vessel units which branch outwards to achieve the desired tumour relative vascular volume. Hypoxic cells have an increased cell cycle time and become quiescent at oxygen tensions less than 1 mmHg. Necrotic cells are resorbed. A hierarchy of stem cells, transit cells and differentiated cells is considered along with differentiated cell loss. Model parameters include the relative vascular volume (2-10%), blood oxygenation (20-100 mmHg), distance from vessels to the onset of necrosis (80-300 μm) and probability for stem cells to undergo symmetric ision (2%). Simulations were performed to observe the effects of hypoxia on tumour growth rate for head and neck cancers. Simulations were run on a supercomputer with eligible parts running in parallel on 12 cores. Using biologically plausible model parameters for head and neck cancers, the tumour volume doubling time varied from 45 ± 5 days (n = 3) for well oxygenated tumours to 87 ± 5 days (n = 3) for severely hypoxic tumours. The main achievements of the current model were randomised cell positions and the connected vasculature structure between the cells. These developments will also be beneficial when irradiating the simulated tumours using Monte Carlo track structure methods.
Publisher: EDP Sciences
Date: 2012
Publisher: Springer Science and Business Media LLC
Date: 23-10-2019
DOI: 10.1007/S13246-019-00810-0
Abstract: While proton beam therapy (PBT) can offer increased sparing of healthy tissue, it is associated with large capital costs and as such, has limited availability. Furthermore, it has not been well established whether PBT has significant clinical advantages over conventional volumetric modulated arc therapy (VMAT) for all tumour types. PBT can potentially offer improved clinical outcomes for base of skull chordoma (BOSCh) patients compared with photon (X-ray) therapy, however the cost-effectiveness of these treatments is unclear. In this study, the cost-effectiveness of PBT in the treatment of BOSCh patients is assessed, based on an analysis of comparative radiotherapy treatment plans using a radiobiological Markov model. Seven BOSCh patients had treatment plans for the delivery of intensity modulated proton therapy and VMAT retrospectively analysed. The patient outcome (in terms of tumour local control and normal tissue complications) after receiving each treatment was estimated with a radiobiological Markov model. In addition, the model estimated the cost of both the primary treatment and treating any resultant adverse events. The incremental cost-effectiveness ratio (ICER) was obtained for each patient. PBT was found to be cost-effective for 5 patients and cost-saving for 2. The mean ICER was AUD$1,990 per quality adjusted life year gained. Variation of model parameters resulted in the proton treatments remaining cost-effective for these patients. Based on this cohort, PBT is a cost-effective treatment for patients with BOSCh. This supports the inclusion of PBT for BOSCh in the Medicare Services Advisory Committee 1455 application.
Publisher: Springer Science and Business Media LLC
Date: 12-04-2021
Publisher: Radiation Research Society
Date: 28-06-2018
DOI: 10.1667/RR15050.1
Publisher: Springer Science and Business Media LLC
Date: 12-01-2022
DOI: 10.1007/S13246-021-01092-1
Abstract: In this study, we investigate whether an acceptable dosimetric plan can be obtained for a brachytherapy surface applicator designed using photogrammetry and compare the plan quality to a CT-derived applicator. The nose region of a RANDO anthropomorphic phantom was selected as the treatment site due to its high curvature. Photographs were captured using a Nikon D5600 DSLR camera and reconstructed using Agisoft Metashape while CT data was obtained using a Canon Aquillion scanner. Virtual surface applicators were designed in Blender and printed with PLA plastic. Treatment plans with a prescription dose of 3.85 Gy × 10 fractions with 100% dose to PTV on the bridge of the nose at 2 mm depth were generated separately using AcurosBV in the Varian BrachyVision TPS. PTV D
Publisher: IOP Publishing
Date: 27-03-2015
DOI: 10.1088/0031-9155/60/8/3217
Abstract: The preliminary framework of a combined radiobiological model is developed and calibrated in the current work. The model simulates the production of in idual cells forming a tumour, the spatial distribution of in idual ionization events (using Geant4-DNA) and the stochastic biochemical repair of DNA double strand breaks (DSBs) leading to the prediction of survival or death of in idual cells. In the current work, we expand upon a previously developed tumour generation and irradiation model to include a stochastic ionization damage clustering and DNA lesion repair model. The Geant4 code enabled the positions of each ionization event in the cells to be simulated and recorded for analysis. An algorithm was developed to cluster the ionization events in each cell into simple and complex double strand breaks. The two lesion kinetic (TLK) model was then adapted to predict DSB repair kinetics and the resultant cell survival curve. The parameters in the cell survival model were then calibrated using experimental cell survival data of V79 cells after low energy proton irradiation. A monolayer of V79 cells was simulated using the tumour generation code developed previously. The cells were then irradiated by protons with mean energies of 0.76 MeV and 1.9 MeV using a customized version of Geant4. By replicating the experimental parameters of a low energy proton irradiation experiment and calibrating the model with two sets of data, the model is now capable of predicting V79 cell survival after low energy (<2 MeV) proton irradiation for a custom set of input parameters. The novelty of this model is the realistic cellular geometry which can be irradiated using Geant4-DNA and the method in which the double strand breaks are predicted from clustering the spatial distribution of ionisation events. Unlike the original TLK model which calculates a tumour average cell survival probability, the cell survival probability is calculated for each cell in the geometric tumour model developed in the current work. This model uses fundamental measurable microscopic quantities such as genome length rather than macroscopic radiobiological quantities such as alpha/beta ratios. This means that the model can be theoretically used under a wide range of conditions with a single set of input parameters once calibrated for a given cell line.
Publisher: Springer Science and Business Media LLC
Date: 30-05-2023
DOI: 10.1007/S13246-023-01279-8
Abstract: In high-dose-rate (HDR) prostate brachytherapy the combined effect of uncertainties cause a range of possible dose distributions deviating from the nominal plan, and which are not considered during treatment plan evaluation. This could lead to dosimetric misses for critical structures and overdosing of organs at risk. A robust evaluation method to assess the combination of uncertainties during plan evaluation is presented and demonstrated on one HDR prostate ultrasound treatment plan retrospectively. A range of uncertainty scenarios are simulated by changing six parameters in the nominal plan and calculating the corresponding dose distribution. Two methods are employed to change the parameters, a probabilistic approach using random number s ling to evaluate the likelihood of variation in dose distributions, and a combination of the most extreme possible values to access the worst-case dosimetric outcomes. One thousand probabilistic scenarios were run on the single treatment plan with 43.2% of scenarios passing seven of the eight clinical objectives. The prostate D 90 had a standard deviation of 4.4%, with the worst case decreasing the dose by up to 27.2%. The urethra D 10 was up to 29.3% higher than planned in the worst case. All DVH metrics in the probabilistic scenarios were found to be within acceptable clinical constraints for the plan under statistical tests for significance. The clinical significance of the results from the robust evaluation method presented on any in idual treatment plan needs to be compared in the context of a historical data set that contains patient outcomes with robustness analysis data to ascertain a baseline acceptance.
Publisher: Cambridge University Press (CUP)
Date: 02-08-2017
DOI: 10.1017/S0885715617000719
Abstract: A robust analysis script was developed in MATLAB for cross-correlative quantification of internalised gold nanoparticle (AuNP) uptake in a large number of in idual cells with the corresponding number of DNA double-strand breaks (DSBs) in the same cells. The correlation of inorganic NP content with a biological marker at the single-cell level will aid in the elucidation of mechanisms of NP radiosensitisation. PC-3 cells were co-cultured with AuNPs and irradiated using an iridium-192 source. AuNP uptake was measured using synchrotron X-ray fluorescence (XRF) and DSBs imaged via confocal microscopy. MATLAB 2016a was used to develop a script to cross-correlate the two imaging modalities and quantify both DSBs and internalised AuNP content in the same cell. Various user-defined options written into the script give a high degree of versatility, which can account for a large number of variables in experimental parameters and data acquisition. The analysis procedure is flexible and robust, which gives consistent consideration to the wide spectrum of potential input image/data sets. Quantitative correlative microscopy was achieved with a custom MATLAB script used to correlate γH2AX foci (a marker of DNA DSBs) from confocal microscopy with AuNP content acquired using synchrotron XRF at the single-cell level. The script can be extended to a broad range of multi-modality imaging spectroscopies.
No related grants have been discovered for Michael Douglass.