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A new beam line facility dedicated to investigations into the radiobiology of biological single cells has been constructed at the Centre for Ion Beam Applications, National University of Singapore. This facility, which has a horizontal layout, has some novel features including post lens magnetic ion deflection and scanning and provision for a diamond exit window and confocal fluorescence microscope for high performance online investigations. The radiobiology facility uses a system of Oxford Microbeam compact magnetic quadrupole lenses enabling high demagnifications (up to 123 × 51) at the cell plane, and a relatively short lens to cell distances (22.5 cm). Beam optics and SRIM calculations have indicated a theoretical design performance of up to 450 nm for the proton spot size at the cell surface. To measure the spatial resolution of the proton beam at the cell position, we positioned a gold calibration grid inside the external cell chamber at a position normally occupied by cells. Preliminary results were obtained by scanning a 2 MeV focused beam over a grid and using a surface barrier detector to construct a STIM image of the grid we have measured an in-air spot size of sub-500 nm at the cell position. In this paper, the design of the new radiobiology beam line, preliminary results of resolution tests, as well as presenting first investigations into the damage caused by focused proton beam irradiation of human liver cancer cells by detecting DNA damage markers gamma-H2AX and 53BP1.

An automated dose accumulation and contour propagation workflow using daily cone beam computed tomography (CBCTs) images for prostate cases that require pelvic lymph nodes irradiation (PLNs) was developed. This workflow was constructed using MIM® software with the intention to provide accurate dose transformations for plans with two different isocentres, whereby two sequential treatment phases were prescribed. The pre‐processing steps for data extractions from treatment plans, CBCTs, determination of couch shift information and management of missing CBCTs are described. To ensure that the imported translational couch shifts were in the correct orientation and readable in MIM, phantom commissioning was performed. For dose transformation, rigid registration with corrected setup shifts and scaled fractional dose was performed for pCT to daily CBCTs, which were then deformed onto CBCT1. Fractional dose summation resulted in the final accumulated dose for the patient allowing differences in dosimetry between the planned and accumulated dose to be analysed. Contour propagations of the prostate, bladder and rectum were performed within the same workflow. Transformed contours were then deformed onto daily CBCTs to generate trending reports for analysis, including Dice Similarity Coefficient (DSC) and Mean Distance to Agreement (MDA). Results obtained from phantom commissioning (DSC = 0.96, MDA = 0.89 mm) and geometrical analysis of the propagated contours for twenty patients; prostate (DSC: 0.9 ± 0.0, MDA: 1.0 ± 0.3 mm), rectum (DSC: 0.8 ± 0.1, mm, MDA: 1.7 ± 0.6 mm) and bladder (DSC: 0.8 ± 0.1, MDA: 2.8 ± 1.0 mm) were within clinically accepted tolerances for both DSC (>0.8) and MDA (< 0.3 mm). The developed workflow is being performed on a larger patient cohort for predictive model building, with the goal of correlating observed toxicity with the actual accumulated dose received by the patient., An automated dose accumulation and contour propagation workflow using daily cone beam computed tomography images for prostate cancer was developed.

There is an increasing number of radiobiological experiments being conducted with low energy protons (less than 5 MeV) for radiobiological studies due to availability of sub-millimetre focused beam. However, low energy proton has broad microdosimetric spectra which can introduce dosimetric uncertainty. In this work, we quantify the impact of this dosimetric uncertainties on the cell survival curve and how it affects the estimation of the alpha and beta parameters in the LQ formalism. Monte Carlo simulation is used to generate the microdosimetric spectra in a micrometer-sized water sphere under proton irradiation. This is modelled using radiobiological experiment set-up at the Centre of Ion Beam Application (CIBA) in National University of Singapore. Our results show that the microdosimetric spectra can introduce both systematic and random shifts in dose and cell survival; this effect is most pronounced with low energy protons. The alpha and beta uncertainties can be up to 10% and above 30%, respectively for low energy protons passing through thin cell target (about 10 microns). These uncertainties are non-negligible and show that care must be taken in using the cell survival curve and its derived parameters for radiobiological models.

Objective: Dose-averaged linear energy transfer (LETD) is one of the factors which determines relative biological effectiveness (RBE) for treatment planning in proton therapy. It is usually determined from Monte Carlo (MC) simulation. However, no standard simulation protocols were established for sampling of LETD. Simulation parameters like maximum step length and range cut will affect secondary electrons production and have an impact on the accuracy of dose distribution and LETD. We aim to show how different combinations of step length and range cut in GEANT4 will affect the result in sampling of LETD using different MC scoring methods. Methods: In this work, different step length and range cut value in a clinically relevant voxel geometry were used for comparison. Different LETD scoring methods were established and the concept of covariance between energy deposition per step and step length is used to explain the differences between them. Results: We recommend a maximum step length of 0.05 mm and a range cut of 0.01 mm in MC simulation as this yields the most consistent LETD value across different scoring methods. Different LETD scoring methods are also compared and variation up to 200% can be observed at the plateau of 80 MeV proton beam. Scoring Method one has one of the lowest percentage differences compared across all simulation parameters. Conclusion: We have determined a set of maximum step length and range cut parameters to be used for LETD scoring in a 1 mm voxelized geometry. LETD scoring method should also be clearly defined and standardized to facilitate cross-institutional studies. Advances in knowledge: Establishing a standard simulation protocol for sampling LETD would reduce the discrepancy when comparing data across different centres, and this can improve the calculation for RBE.

In anticipation of the new Proton Therapy Centre in Singapore at 2020, the medical physicists and physicists in NCCS and NUS have come together to do several preparation/preliminary works. Of which, one of the most important programme is to develop the Monte Carlo simulation capability using GEANT4 toolkit. We simulated the entire beam delivery and nozzle based on specifications given by Hitachi. The results of the Energy-Range curves in water phantom together with spot size in air agrees well with measurement data provided by Hitachi. We will show the complete methodology of simulation leading up to the comparison with measurement data. There were 3 main aspects we focused on—(1) The choice of physics models, (2) The determination of initial proton phase space based on Twiss parameters from beam profile measurement and (3) The choice of cut-off energy and step size. This simulation is important for the commissioning of the Proton Therapy System and the methodology presented will be helpful for other upcoming centers who are interested in doing the same.

It is known that high energy protons in proton therapy generate secondary particles. Of which, secondary neutrons are a main concern as they deposit out-of-field doses and can have long-term health effects on cancer patients. In this paper, the energy, 3-D spatial and angular distribution of the production yield of neutrons is scored along the proton beam path in different types of tissue medium. The degree of biological damage is then quantified through factoring in the relative biological effectiveness of neutrons. This systematic study involved simulating 70, 150 and 200 MeV proton beam transport in various tissue compositions with the GEANT4 code. System specifications of the Hitachi proton therapy system were used in this study. Simulation results showed that the neutrons are forward facing and are generally emitted at a preferential angle. With considerations on the RBE variation with neutron’s energy, the spatial and angular distribution of the production of lethal neutrons were identified along the proton track. Non-trivial relations between biological damage in different tissue medium were observed. Such comprehensive simulation studies have not been reported and this input information can be useful for treatment planning in reducing out-of-field neutron dose in sensitive organs.

We present a simple and universal approach to calculate the total ionization cross section (TICS) for electron impact ionization in DNA bases and other biomaterials in the condensed phase. Evaluating the electron impact TICS plays a vital role in ion-beam radiobiology simulation at the cellular level, as secondary electrons are the main cause of DNA damage in particle cancer therapy. Our method is based on extending the dielectric formalism. The calculated results agree well with experimental data and show a good comparison with other theoretical calculations. This method only requires information of the chemical composition and density and an estimate of the mean binding energy to produce reasonably accurate TICS of complex biomolecules. Because of its simplicity and great predictive effectiveness, this method could be helpful in situations where the experimental TICS data are absent or scarce, such as in particle cancer therapy.

Objective: Radiomics pipelines have been developed to extract novel information from radiological images, which may help in phenotypic profiling of tumours that would correlate to prognosis. Here, we compared two publicly available pipelines for radiomics analyses on head and neck CT and MRI in nasopharynx cancer (NPC). Methods and materials: 100 biopsy-proven NPC cases stratified by T- and N-categories were enrolled in this study. Two radiomics pipeline, Moddicom (v. 0.51) and Pyradiomics (v. 2.1.2) were used to extract radiomics features of CT and MRI. Segmentation of primary gross tumour volume was performed using Velocity v. 4.0 by consensus agreement between three radiation oncologists. Intraclass correlation between common features of the two pipelines was analysed by Spearman’s rank correlation. Unsupervised hierarchical clustering was used to determine association between radiomics features and clinical parameters. Results: We observed a high proportion of correlated features in the CT data set, but not for MRI; 76.1% (51 of 67 common between Moddicom and Pyradiomics) of CT features and 28.6% (20 of 70 common) of MRI features were significantly correlated. Of these, 100% were shape-related for both CT and MRI, 100 and 23.5% were first-order-related, 61.9 and 19.0% were texture-related, respectively. This interpipeline heterogeneity affected the downstream clustering with known prognostic clinical parameters of cTN-status and GTVp. Nonetheless, shape features were the most reproducible predictors of clinical parameters among the different radiomics modules. Conclusion: Here, we highlighted significant heterogeneity between two publicly available radiomics pipelines that could affect the downstream association with prognostic clinical factors in NPC Advances in knowledge: The present study emphasized the broader importance of selecting stable radiomics features for disease phenotyping, and it is necessary prior to any investigation of multicentre imaging datasets to validate the stability of CT-related radiomics features for clinical prognostication.

Biological uncertainty remains one of the main sources of uncertainties in proton therapy, and is encapsulated in a scalar quantity known as relative biological effective (RBE). It is currently recognised that a constant RBE of 1.1 is not consistent with radiobiological experiment and may lead to sub-optimal exploitation of the benefits of proton therapy. To overcome this problem, several RBE models have been developed, and in most of these models, there is a dependence of RBE on dose-averaged linear energy transfer (LET), [Formula: see text]. In this work, we show that the [Formula: see text] estimation in these models during the data-fitting (or parameter estimation) phase could be subjected to a huge uncertainty due to not taking into account cellular materials during simulation, and this uncertainty can propagate down to the resulting RBE models. The dosimetric impact of this [Formula: see text] uncertainty is then evaluated on a simple clinical spread out Bragg peak (SOBP) and a prostate example. Our simulation shows that [Formula: see text] uncertainty due to the use of water as cellular material is non-negligible under low [Formula: see text] and low dose (2 Gy), and can be neglected otherwise. Thus, this study indicates that further dose and range margins may be required for low [Formula: see text] target under low dose. This is due to greater uncertainties in RBE model associated with incomplete knowledge of cellular composition for [Formula: see text] computation.