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Background: The use of Computed Tomography (CT) imaging data to create 3D printable patient-specific devices for radiation oncology purposes is already well established in the literature and has shown to have superior conformity than conventional methods. Using non-ionizing radiation imaging techniques such as photogrammetry or laser scanners in-lieu of a CT scanner presents many desirable benefits including reduced imaging dose and fabrication of the device can be completed prior to simulation. With recent advancements in smartphone-based technology, photographic and LiDAR-based technologies are more readily available than ever before and to a high level of quality. As a result, these non-ionizing radiation imaging methods are now able to generate patient-specific devices that can be acceptable for clinical use., Purpose: In this work, we aim to determine if smartphones can be used by radiation oncologists or other radiation oncology staff to generate bolus or brachytherapy surface moulds instead of conventional CT with equivalent or comparable accuracy., Methods: This work involved two separate studies: a phantom and participant study. For the phantom study, a RANDO anthropomorphic phantom (limited to the nose region) was used to generate 3D models based on three different imaging techniques: conventional CT, photogrammetry & LiDAR which were both acquired on a smartphone. Virtual boli were designed in Blender and 3D printed from PLA plastic material. The conformity of each printed boli was assessed by measuring the air gap volume and approximate thickness between the phantom & bolus acquired together on a CT. For the participant study, photographs, and a LiDAR scan of four volunteers were captured using an iPhone 13 Pro™ to assess their feasibility for generating human models. Each virtual 3D model was visually assessed to identify any issues in their reconstruction. The LiDAR models were registered to the photogrammetry models where a distance to agreement analysis was performed to assess their level of similarity. Additionally, a 3D virtual bolus was designed and printed using ABS material from all models to assess their conformity onto the participants skin surface using a verbal feedback method., Results: The photogrammetry derived bolus showed comparable conformity to the CT derived bolus while the LiDAR derived bolus showed poorer conformity as shown by their respective air gap volume and thickness measurements. The reconstruction quality of both the photogrammetry and LiDAR models of the volunteers was inadequate in regions of facial hair and occlusion, which may lead to clinically unacceptable patient-specific device that are created from these areas. All participants found the photogrammetry 3D printed bolus to conform to their nose region with minimal room to move while three of the four participants found the LiDAR was acceptable and could be positioned comfortably over their entire nose., Conclusions: Smartphone-based photogrammetry and LiDAR software show great potential for future use in generating 3D reference models for radiation oncology purposes. Further investigations into whether they can be used to fabricate clinically acceptable patient-specific devices on a larger and more diverse cohort of participants and anatomical locations is required for a thorough validation of their clinical usefulness., (© 2024 The Authors. Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine.)

Background: Uncertainties in radiotherapy cause deviation from the planned dose distribution and may result in delivering a treatment that fails to meet clinical objectives. The impact of uncertainties is unique to the patient anatomy and the needle locations in HDR prostate brachytherapy. Evaluating this impact during treatment planning is not common practice, relying on margins around the target or organs-at-risk to account for uncertainties., Purpose: A robust evaluation framework for HDR prostate brachytherapy treatment plans was evaluated on 49 patient plans, measuring the range of possible dosimetric outcomes to the patient due to 14 major uncertainties., Methods: Patient plans were evaluated for their robustness to uncertainties by simulating probable uncertainty scenarios. Five-thousand probabilistic and 1943 worst-case scenarios per patient were simulated by changing the position and size of structures and length of dwell times from their nominal values. For each uncertainty scenario, the prostate D 90 and maximum doses to the urethra, D 0.01cc , and rectum, D 0.1cc , were calculated., Results: The D 90 was an average 1.16 ± 0.51% (mean ± SD) below nominal values for the probabilistic scenarios; the D 0.01cc metric was 2.24 ± 0.90% higher; and D 0.1cc was greater by 0.48 ± 0.30%. The D 0.01cc and D 90 metrics were more sensitive to uncertainties than D 0.1cc , with a median of 79.0% and 84.9% of probabilistic scenarios passing the constraints, compared to 96.5%. The median pass-rate for scenarios that passed all three metrics simultaneously was 63.4%., Conclusions: Assessing treatment plan robustness improves plan quality assurance, is achievable in less than 1-min, and identifies treatment plans with poor robustness, allowing re-optimization before delivery., (© 2023 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, LLC on behalf of The American Association of Physicists in Medicine.)

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 sampling 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 individual 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., (© 2023. The Author(s).)

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 98% , D 90% and V 100% , and OAR D 0.1cc , D 2cc and V 50% dose metrics and dwell times were evaluated, with the applicator fit assessed by air-gap volume measurements. Both types of surface applicators were printed with minimal defects and visually fitted well to the target area. The measured air-gap volume between the photogrammetry applicator and phantom surface was 44% larger than the CT-designed applicator, with a mean air gap thickness of 3.24 and 2.88 mm, respectively. The largest difference in the dose metric observed for the PTV and OAR was the PTV V 100% of - 1.27% and skin D 0.1cc of - 0.28%. PTV D 98% and D 90% and OAR D 2cc and V 50% for the photogrammetry based plan were all within 0.5% of the CT based plan. Total dwell times were also within 5%. A 3D printed surface applicator for the nose was successfully constructed using photogrammetry techniques. Although it produced a larger air gap between the surface applicator and phantom surface, a clinically acceptable dose plan was created with similar PTV and OAR dose metrics to the CT-designed applicator. Additional future work is required to comprehensively evaluate its suitability in a clinically environment., (© 2022. Australasian College of Physical Scientists and Engineers in Medicine.)

Radiation therapy requires clinical linear accelerators to be mechanically and dosimetrically calibrated to a high standard. One important quality assurance test is the Winston-Lutz test which localises the radiation isocentre of the linac. In the current work we demonstrate a novel method of analysing EPID based Winston-Lutz QA images using a deep learning model trained only on synthetic image data. In addition, we propose a novel method of generating the synthetic WL images and associated 'ground-truth' masks using an optical path-tracing engine to 'fake' mega-voltage EPID images. The model called DeepWL was trained on 1500 synthetic WL images using data augmentation techniques for 180 epochs. The model was built using Keras with a TensorFlow backend on an Intel Core i5-6500T CPU and trained in approximately 15 h. DeepWL was shown to produce ball bearing and multi-leaf collimator field segmentations with a mean dice coefficient of 0.964 and 0.994 respectively on previously unseen synthetic testing data. When DeepWL was applied to WL data measured on an EPID, the predicted mean displacements were shown to be statistically similar to the Canny Edge detection method. However, the DeepWL predictions for the ball bearing locations were shown to correlate better with manual annotations compared with the Canny edge detection algorithm. DeepWL was demonstrated to analyse Winston-Lutz images with an accuracy suitable for routine linac quality assurance with some statistical evidence that it may outperform Canny Edge detection methods in terms of segmentation robustness and the resultant displacement predictions., (Copyright © 2021 Associazione Italiana di Fisica Medica. All rights reserved.)

The fabrication of brachytherapy surface moulds is considered laborious and time consuming that often result in repeated attempts due to incorrect catheter positioning or the presence of air gaps. 3-dimensional printing using low-cost and reliable materials has allowed the rapid creation of patient-specific surface mould applicators to be achieved using patient imaging data obtained via CT scan. In this study we investigate whether an alternative approach using photogrammetry techniques can improve this process and how camera settings and object texture affect the reconstructions. Two humanoid phantoms, an anthropomorphic RANDO phantom and a Laerdal Little Anne CPR training manikin were used in this study. Both were imaged using a Nikon D5600 DSLR and Nokia 3.1 smartphone camera and reconstructed using Agisoft Metashape software. CT scans of both phantoms were taken as references for comparing the photogrammetry reconstructions. Models were reconstructed from different photo sets and assessed by distance to agreement with the CT models. Both phantoms were effectively reconstructed for most experiments. Increasing the number of photos used produced the better reconstructions while in general, reconstructions using video data were poor. The two phantoms were reconstructed at a similar quality. Background light that caused undesirable reflections significantly reduced reconstruction quality. Applying a non-reflective tape to the affected regions provided a suitable method for reducing their effects. Photogrammetry techniques were effectively able to reconstruct 3-dimensional models of both phantom. The camera settings and lighting did have a profound effect on the reconstruction quality and should be chosen appropriately depending on the scene.

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., (© 2020 The Authors. Journal of Medical Radiation Sciences published by John Wiley & Sons Australia, Ltd on behalf of Australian Society of Medical Imaging and Radiation Therapy and New Zealand Institute of Medical Radiation Technology.)

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.

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.

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.

Purpose: 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., Methods and Materials: 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., Results: 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 3 ., Conclusions: 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., (Crown Copyright © 2019. Published by Elsevier Inc. All rights reserved.)

DNA damage induced by ionizing radiation exposure is enhanced in the presence of oxygen (the "oxygen effect"). Despite its practical importance in radiotherapy, the oxygen effect has largely been excluded from models that predict DNA damage from radiation tracks. A Monte Carlo-based algorithm was developed in MATLAB software to predict DNA damage from physical and chemical tracks through a cell nucleus simulated in Geant4-DNA, taking into account the effects of cellular oxygenation (pO 2 ) on DNA radical chemistry processes. An initial spatial distribution of DNA base and sugar radicals was determined by spatially clustering direct events (that deposited at least 10.79 eV) and hydroxyl radical ( • OH) interactions. The oxygen effect was modeled by increasing the efficiency with which sugar radicals from direct-type effects were converted to strand breaks from 0.6 to 1, the efficiency with which sugar radicals from the indirect effect were converted to strand breaks from 0.28 to 1 and the efficiency of base-to-sugar radical transfer from • OH-mediated base radicals from 0 to 0.03 with increasing pO 2 from 0 to 760 mmHg. The DNA damage induction algorithm was applied to tracks from electrons, protons and alphas with LET values from 0.2 to 150 keV/μm under different pO 2 conditions. The oxygen enhancement ratio for double-strand break induction was 3.0 for low-LET radiation up to approximately 15 keV/μm, after which it gradually decreased to a value of 1.3 at 150 keV/μm. These values were consistent with a range of experimental data published in the literature. The DNA damage yields were verified using experimental data in the literature and results from other theoretical models. The spatial clustering approach developed in this work has low memory requirements and may be suitable for particle tracking simulations with a large number of cells.

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., (Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.)

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 division 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 division 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 division probability of approximately 50%, which also results in CSC proportions of 30-35% during this time.