Publications by authors named "Scott N Penfold"

14 Publications

  • Page 1 of 1

A novel TPS toolkit to assess correlation between transit fluence dosimetry and DVH metrics for adaptive head and neck radiotherapy.

Phys Eng Sci Med 2021 Aug 31. Epub 2021 Aug 31.

Department of Physics, The University of Adelaide, Adelaide, SA, 5005, Australia.

Inter-fractional anatomical variations in head and neck (H&N) cancer patients can lead to clinically significant dosimetric changes. Adaptive re-planning should thus commence to negate any potential over-dosage to organs-at-risk (OAR), as well as potential under-dosage to target lesions. The aim of this study is to explore the correlation between transit fluence, as measured at an electronic portal imaging device (EPID), and dose volume histogram (DVH) metrics to target and OAR structures in a simulated environment. Planning data of eight patients that have previously undergone adaptive radiotherapy for H&N cancer using volumetric modulated arc therapy (VMAT) at the Royal Adelaide Hospital were selected for this study. Through delivering the original treatment plan to both the planning and rescan CTs of these eight patients, predicted electronic portal images (EPIs) and DVH metrics corresponding to each data set were extracted using a novel RayStation script. A weighted projection mask was developed for target and OAR structures through considering the intra-angle overlap between fluence and structure contours projected onto the EPIs. The correlation between change in transit fluence and planning target volume (PTV) D98 and spinal cord D0.03cc with and without the weighting mask applied was investigated. PTV D98 was strongly correlated with mean fluence percentage difference both with and without the weighting mask applied (R = 0.69, R = 0.79, N = 14, p < 0.05), where spinal cord D0.03cc exhibited a weak correlation (R = 0.35, R = 0.53, N = 7, p > 0.05) however this result was not statistically significant. The simulation toolkit developed in this work provided a useful means to investigate the relationship between change in transit fluence and change in key dosimetric parameters for H&N cancer patients.
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http://dx.doi.org/10.1007/s13246-021-01048-5DOI Listing
August 2021

Estimating the second primary cancer risk due to proton therapy compared to hybrid IMRT for left sided breast cancer.

Acta Oncol 2021 Mar 21;60(3):300-304. Epub 2020 Dec 21.

School for Physical Sciences, University of Adelaide, Adelaide, Australia.

Background And Purpose: Proton therapy has been proposed as a technique to improve the long-term quality of life of breast cancer patients. This is due to its ability to reduce the dose to healthy tissue compared to conventional X-ray therapy. The aim of this study was to investigate the risk of secondary carcinogenesis due to proton therapy compared to hybrid IMRT for breast treatments.

Material And Methods: In this study, the Pinnacle treatment planning system was used to simulate treatment plans for 15 female left-sided whole breast cancer patients with deep inspiration breath hold scans. Two treatment plans were generated for each patient: hybrid intensity modulated radiotherapy (h-IMRT) and intensity modulated proton therapy (IMPT). Using the dose-volume histograms (DVHs) from these plans, the mean lifetime attributed risk (LAR) for both lungs and the contralateral breast were evaluated using the BEIR VII and Schneider full risk models.

Results: The results from both risk models show lower LAR estimates for the IMPT treatment plan compared to the h-IMRT treatment plan. This result was observed for all organs of interest and was consistent amongst the two separate risk models. For both treatment plans, the organs from most to least at risk were: ipsilateral lung, contralateral breast, and contralateral lung. In all cases, the risk estimated via the BEIR VII model was higher that the Schneider full risk model.

Conclusion: The use of proton therapy for breast treatments leads to reduced risk estimates for secondary carcinogenesis. Therefore, proton therapy shows promise in improving the long term treatment outcome of breast patients.
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http://dx.doi.org/10.1080/0284186X.2020.1862421DOI Listing
March 2021

Individualised selection of left-sided breast cancer patients for proton therapy based on cost-effectiveness.

J Med Radiat Sci 2021 Mar 7;68(1):44-51. Epub 2020 Jul 7.

Department of Physics, University of Adelaide, Adelaide, SA, Australia.

Introduction: The significantly greater cost of proton therapy compared with X-ray therapy is frequently justified by the expected reduction in normal tissue toxicity. This is often true for indications such as paediatric and skull base cancers. However, the benefit is less clear for other more common indications such as breast cancer, and it is possible that the degree of benefit may vary widely between these patients. The aim of this work was to demonstrate a method of individualised selection of left-sided breast cancer patients for proton therapy based on cost-effectiveness of treatment.

Methods: 16 left-sided breast cancer patients had a treatment plan generated for the delivery of intensity-modulated proton therapy (IMPT) and of intensity-modulated photon therapy (IMRT) with the deep inspiration breath-hold (DIBH) technique. The resulting dosimetric data was used to predict probabilities of tumour control and toxicities for each patient. These probabilities were used in a Markov model to predict costs and the number of quality-adjusted life years expected as a result of each of the two treatments.

Results: IMPT was not cost-effective for the majority of patients but was cost-effective where there was a greater risk reduction of second malignancies with IMPT.

Conclusion: The Markov model predicted that IMPT with DIBH was only cost-effective for selected left-sided breast cancer patients where IMRT resulted in a significantly greater dose to normal tissue. The presented model may serve as a means of evaluating the cost-effectiveness of IMPT on an individual patient basis.
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http://dx.doi.org/10.1002/jmrs.416DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7890920PMC
March 2021

Patient selection for proton therapy: a radiobiological fuzzy Markov model incorporating robust plan analysis.

Phys Eng Sci Med 2020 Jun 10;43(2):493-503. Epub 2020 Feb 10.

Department of Physics, University of Adelaide, Adelaide, SA, 5005, Australia.

While proton therapy can offer increased sparing of healthy tissue compared with X-ray therapy, it can be difficult to predict whether a benefit can be expected for an individual patient. Predictive modelling may aid in this respect. However, the predictions of these models can be affected by uncertainties in radiobiological model parameters and in planned dose. The aim of this work is to present a Markov model that incorporates these uncertainties to compare clinical outcomes for individualised proton and X-ray therapy treatments. A time-inhomogeneous fuzzy Markov model was developed which estimates the response of a patient to a given treatment plan in terms of quality adjusted life years. These are calculated using the dose-dependent probabilities of tumour control and toxicities as transition probabilities in the model. Dose-volume data representing multiple isotropic patient set-up uncertainties and range uncertainties (for proton therapy) are included to model dose delivery uncertainties. The model was retrospectively applied to an example patient as a demonstration. When uncertainty in the radiobiological model parameter was considered, the model predicted that proton therapy would result in an improved clinical outcome compared with X-ray therapy. However, when dose delivery uncertainty was included, there was no difference between the two treatments. By incorporating uncertainties in the predictive modelling calculations, the fuzzy Markov concept was found to be well suited to providing a more holistic comparison of individualised treatment outcomes for proton and X-ray therapy. This may prove to be useful in model-based patient selection strategies.
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http://dx.doi.org/10.1007/s13246-020-00849-4DOI Listing
June 2020

Comparative proton versus photon treatment planning for the Medicare Medical Treatment Overseas Program: The Royal Adelaide Hospital experience.

J Med Imaging Radiat Oncol 2020 Oct 3;64(5):682-688. Epub 2020 Apr 3.

Department of Radiation Oncology, Royal Adelaide Hospital, Adelaide, South Australia, Australia.

Introduction: Australia's first proton beam therapy (PBT) service, The Australian Bragg Centre for Proton Therapy and Research, is scheduled to open in the near future providing PBT for patients closer to home. Patients currently access Commonwealth funding for PBT via the Medicare Medical Treatment Overseas Program (MTOP). Proton versus photon treatment planning is a pre-requisite for the MTOP application. The Royal Adelaide Hospital (RAH) Department of Radiation Oncology has been providing this since 2016. We aim to provide a descriptive overview of our proton versus photon treatment planning process, presenting a summary of the comparative planning results and the treatment pathways selected for the patients referred.

Methods: All patients referred to the RAH for comparative planning between January 2016 and December 2018 were included in the analysis. Comparative plans were generated for each case using Pinnacle or Eclipse treatment planning systems. The planning techniques used and plan quality metrics were reported.

Results: Forty three patients were referred for comparative planning. The age range was 1-63 years, with the majority (72%) being paediatric patients (age ≤18 years). Of the 19 cases that have been submitted to MTOP, 16 have been accepted and 3 denied. Two of the accepted cases chose not to travel abroad for PBT. The other 14 cases have received PBT overseas.

Conclusions: The RAH has provided an important service to demonstrate the dosimetric difference between PBT and photon therapy for Australian patients, an important step in supporting the funding of patients for treatment overseas.
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http://dx.doi.org/10.1111/1754-9485.13018DOI Listing
October 2020

An inhomogeneous most likely path formalism for proton computed tomography.

Phys Med 2020 Feb 7;70:184-195. Epub 2020 Feb 7.

Department of Physics, University of Adelaide, Adelaide, South Australia 5005, Australia; Department of Medical Physics, Royal Adelaide Hospital, Adelaide, South Australia 5000, Australia.

Purpose: Multiple Coulomb scattering (MCS) poses a challenge in proton CT (pCT) image reconstruction. The assumption of straight paths is replaced with Bayesian models of the most likely path (MLP). Current MLP-based pCT reconstruction approaches assume a water scattering environment. We propose an MLP formalism based on accurate determination of scattering moments in inhomogeneous media.

Methods: Scattering power relative to water (RScP) was calculated for a range of human tissues and investigated against relative stopping power (RStP). Monte Carlo simulation was used to compare the new inhomogeneous MLP formalism to the water approach in a slab geometry and a human head phantom. An MLP-Spline-Hybrid method was investigated for improved computational efficiency.

Results: A piecewise-linear correlation between RStP and RScP was shown, which may assist in iterative pCT reconstruction. The inhomogeneous formalism predicted Monte Carlo proton paths through a water cube with thick bone inserts to within 1.0 mm for beams ranging from 210 to 230 MeV incident energy. Improvement in accuracy over the conventional MLP ranged from 5% for a 230 MeV beam to 17% for 210 MeV. There was no noticeable gain in accuracy when predicting 200 MeV proton paths through a clinically relevant human head phantom. The MLP-Spline-Hybrid method reduced computation time by half while suffering negligible loss of accuracy.

Conclusions: We have presented an MLP formalism that accounts for material composition. In most clinical cases a water scattering environment can be assumed, however in certain cases of significant heterogeneity the proposed algorithm may improve proton path estimation.
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http://dx.doi.org/10.1016/j.ejmp.2020.01.025DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7026699PMC
February 2020

Cost-effectiveness of proton therapy in treating base of skull chordoma.

Australas Phys Eng Sci Med 2019 Dec 23;42(4):1091-1098. Epub 2019 Oct 23.

Department of Physics, University of Adelaide, North Terrace, Adelaide, SA, Australia.

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.
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http://dx.doi.org/10.1007/s13246-019-00810-0DOI Listing
December 2019

A radiobiological Markov simulation tool for aiding decision making in proton therapy referral.

Phys Med 2017 Dec 23;44:72-82. Epub 2017 Nov 23.

Department of Physics, University of Adelaide, Adelaide, SA 5005, Australia; Department of Medical Physics, Royal Adelaide Hospital, Adelaide, SA 5000, Australia. Electronic address:

Purpose: 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 individual 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.

Methods: 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.

Results: The model was successfully developed to compare clinical outcomes for proton and X-ray treatment plans. For the example 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.

Conclusions: The functionality of the model was demonstrated using the example patient. The proposed Markov method may be a useful tool for deciding on a treatment strategy for individual patients.
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http://dx.doi.org/10.1016/j.ejmp.2017.11.013DOI Listing
December 2017

Europium-155 as a source for dual energy cone beam computed tomography in adaptive proton therapy: A simulation study.

Med Phys 2017 Oct 4;44(10):5143-5152. Epub 2017 Aug 4.

Department of Physics, University of Adelaide, Adelaide, SA, 5005, Australia.

Purpose: To investigate the feasibility of a 3D imaging system utilizing a Eu source and pixelated cadmium-zinc-telluride (CZT) detector for applications in adaptive radiotherapy. Specifically, to compare the reconstructed stopping power ratio (SPR) values of a head phantom obtained with the proposed imaging technique with theoretical SPR values.

Method: A Geant4 Monte Carlo simulation was performed with the novel imaging system. The simulation was repeated with a typical 120 kV X-ray tube spectrum while maintaining all other parameters. Dual energy Eu source cone beam computed tomography (CBCT) images were reconstructed with an iterative projection algorithm known as total variation superiorization with diagonally relaxed orthogonal projections (TVS-DROP). Single energy 120 kV source CBCT images were also reconstructed with TVS-DROP. Reconstructed images were converted to SPR with stoichiometric calibration techniques based on ICRU 44 tissues. Quantitative accuracy of reconstructed attenuation coefficient images as well as SPR images were compared.

Results: Images generated by gamma emissions of Eu showed superior contrast resolution to those generated by the 120 kV spectrum. Quantitatively, all reconstructed images correlated with reference attenuation coefficients of the head phantom within 1 standard deviation. Images generated with the Eu source showed a smaller standard deviation of pixel values. Use of a dual energy conversion into SPR resulted in superior SPR accuracy with the Eu source.

Conclusion: Eu was found to display desirable qualities when used as a source for dual energy CBCT. Further work is required to demonstrate whether the simulation results presented here can be translated into an experimental prototype.
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http://dx.doi.org/10.1002/mp.12450DOI Listing
October 2017

Dosimetric comparison of stopping power calibration with dual-energy CT and single-energy CT in proton therapy treatment planning.

Med Phys 2016 Jun;43(6):2845-2854

Department of Physics, University of Adelaide, Adelaide, SA 5005, Australia and Department of Medical Physics, Royal Adelaide Hospital, Adelaide, SA 5000, Australia.

Purpose: The accuracy of proton dose calculation is dependent on the ability to correctly characterize patient tissues with medical imaging. The most common method is to correlate computed tomography (CT) numbers obtained via single-energy CT (SECT) with proton stopping power ratio (SPR). CT numbers, however, cannot discriminate between a change in mass density and change in chemical composition of patient tissues. This limitation can have consequences on SPR calibration accuracy. Dual-energy CT (DECT) is receiving increasing interest as an alternative imaging modality for proton therapy treatment planning due to its ability to discriminate between changes in patient density and chemical composition. In the current work we use a phantom of known composition to demonstrate the dosimetric advantages of proton therapy treatment planning with DECT over SECT.

Methods: A phantom of known composition was scanned with a clinical SECT radiotherapy CT-simulator. The phantom was rescanned at a lower X-ray tube potential to generate a complimentary DECT image set. A set of reference materials similar in composition to the phantom was used to perform a stoichiometric calibration of SECT CT number to proton SPRs. The same set of reference materials was used to perform a DECT stoichiometric calibration based on effective atomic number. The known composition of the phantom was used to assess the accuracy of SPR calibration with SECT and DECT. Intensity modulated proton therapy (IMPT) treatment plans were generated with the SECT and DECT image sets to assess the dosimetric effect of the imaging modality. Isodose difference maps and root mean square (RMS) error calculations were used to assess dose calculation accuracy.

Results: SPR calculation accuracy was found to be superior, on average, with DECT relative to SECT. Maximum errors of 12.8% and 2.2% were found for SECT and DECT, respectively. Qualitative examination of dose difference maps clearly showed the dosimetric advantages of DECT imaging, compared to SECT imaging for IMPT dose calculation for the case investigated. Quantitatively, the maximum dose calculation error in the SECT plan was 7.8%, compared to a value of 1.4% in the DECT plan. When considering the high dose target region, the root mean square (RMS) error in dose calculation was 2.1% and 0.4% for SECT and DECT, respectively.

Conclusions: DECT-based proton treatment planning in a commercial treatment planning system was successfully demonstrated for the first time. DECT is an attractive imaging modality for proton therapy treatment planning owing to its ability to characterize density and chemical composition of patient tissues. SECT and DECT scans of a phantom of known composition have been used to demonstrate the dosimetric advantages obtainable in proton therapy treatment planning with DECT over the current approach based on SECT.
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http://dx.doi.org/10.1118/1.4948683DOI Listing
June 2016

Review of 3D image data calibration for heterogeneity correction in proton therapy treatment planning.

Australas Phys Eng Sci Med 2016 Jun 26;39(2):379-90. Epub 2016 Apr 26.

Department of Physics, University of Adelaide, Adelaide, SA, 5005, Australia.

Correct modelling of the interaction parameters of patient tissues is of vital importance in proton therapy treatment planning because of the large dose gradients associated with the Bragg peak. Different 3D imaging techniques yield different information regarding these interaction parameters. Given the rapidly expanding interest in proton therapy, this review is written to make readers aware of the current challenges in accounting for tissue heterogeneities and the imaging systems that are proposed to tackle these challenges. A summary of the interaction parameters of interest in proton therapy and the current and developmental 3D imaging techniques used in proton therapy treatment planning is given. The different methods to translate the imaging data to the interaction parameters of interest are reviewed and a summary of the implementations in several commercial treatment planning systems is presented.
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http://dx.doi.org/10.1007/s13246-016-0447-9DOI Listing
June 2016

Monte Carlo simulations of dose distributions with necrotic tumor targeted radioimmunotherapy.

Appl Radiat Isot 2014 Aug 12;90:40-5. Epub 2014 Mar 12.

Department of Medical Physics, Royal Adelaide Hospital, Adelaide, SA 5000, Australia; School of Chemistry and Physics, University of Adelaide, Adelaide, SA 5005, Australia.

Radio-resistant hypoxic tumor cells are significant contributors to the locoregional recurrences and distant metastases that mark failure of radiotherapy. Due to restricted tissue oxygenation, chronically hypoxic tumor cells frequently become necrotic and thus there is often an association between chronically hypoxic and necrotic tumor regions. This simulation study is the first in a series to determine the feasibility of hypoxic cell killing after first targeting adjacent areas of necrosis with either an α- or β-emitting radioimmunoconjugate.
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http://dx.doi.org/10.1016/j.apradiso.2014.03.006DOI Listing
August 2014

Proton CT for Improved Stopping Power Determination in Proton Therapy, invited.

Trans Am Nucl Soc 2012 ;106:55-58

Royal Adelaide Hospital, Adelaide, SA 5000, Australia.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3999915PMC
January 2012
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