An evaluation of consumer smartphones for generating bolus and surface mould applicators for radiation oncology.

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.

Radiation Oncology Training in the Philippines: Bridging Gaps for Improved Cancer Care in Low- and Middle-Income Countries.

PURPOSE: Radiation oncology in the Philippines, a large lower- and middle-income country in Southeast Asia, is facing a critical shortage in manpower, with only 113 radiation oncologists (ROs) over 55 radiotherapy (RT) centers serving 100 million population. Paramount to workforce expansion is ensuring that training programs can produce adequately trained specialists. In this study, we describe the current state of radiation oncology training programs in the Philippines. METHODS: This is a cross-sectional observational analysis of the nine radiation oncology residency training programs in the Philippines. Data were collected from a survey of the program directors, the Philippine Radiation Oncology Society database, and a PubMed literature search. RESULTS: Eight of the nine programs are in the National Capital Region. Since program standardization in 2005, there have been 82 four-year residency graduates, with up to 18 new graduates annually. Faculty-to-trainee ratio ranges from 0.5 to 2.67. In terms of technology, all programs have intensity-modulated RT and high-dose-rate brachytherapy, but only six are equipped with computed tomography-based image guidance and stereotactic capabilities. Clinical education schemes vary per institution regarding curriculum implementation, resident activities, and methods of evaluation. Required resident case logs are not met for lung, GI, genitourinary, bone and soft tissue, and hematologic malignancies. In total, there are only 22 resident-led publications from 10 unique individuals in two training programs. CONCLUSION: Program expansions are warranted to meet the projected demand for ROs in the Philippines, but training programs must first improve key aspects of staffing, technology, clinical education, and research. Addressing training challenges related to resource limitations necessitates local and international collaborations with higher-capacity centers to bridge gaps for continued quality improvement with the aim of ultimately delivering better overall cancer care.

A survey on brachytherapy training of gynecological cancer focusing on the competence of residents in China.

BACKGROUND: The brachytherapy is an indispensable treatment for gynecological tumors, but the quality and efficiency of brachytherapy training for residents is still unclear. METHODS: An anonymous questionnaire was designed to collect information on gynecological brachytherapy (GBT) training for radiation oncology residents from 28 training bases in China. The questionnaire content was designed based on the principle of competency based medical education (CBME). The Likert scale was employed to evaluate self-reported competence and comprehension regarding GBT. A total of 132 senior residents were included in the final analysis. RESULTS: 53.79% (71/132) of senior residents had experience in performing image-guided GBT, whereas 76.52% (101/132) had observed the procedure during their standardized residency training. The proportion of senior residents who reported having the self-reported competence to independently complete the GBT was 78.03% for intracavity GBT, 75.00% for vaginal stump GBT, and 50.03% for interstitial GBT, respectively. The number of successful completion of Interstitial, intracavity and vaginal GBT was correlated with the self- confidence of trainees after standardized training. In particular, the independent completion of interstitial GBT for more than 20 cases was an independent factor for the self-reported competence of senior residents. During the training period, 50.76% and 56.82% of the residents had not participated in the specialized examinations and professional GBT courses. CONCLUSIONS: The study revealed that the self-confidence of residents to independently complete brachytherapy was relatively high, and the specialized curriculum setting and training process assessment for brachytherapy training still need to be strengthened in the future.

Deformable registration of magnetic resonance images using unsupervised deep learning in neuro-/radiation oncology.

PURPOSE: Accurate deformable registration of magnetic resonance imaging (MRI) scans containing pathologies is challenging due to changes in tissue appearance. In this paper, we developed a novel automated three-dimensional (3D) convolutional U-Net based deformable image registration (ConvUNet-DIR) method using unsupervised learning to establish correspondence between baseline pre-operative and follow-up MRI scans of patients with brain glioma. METHODS: This study involved multi-parametric brain MRI scans (T1, T1-contrast enhanced, T2, FLAIR) acquired at pre-operative and follow-up time for 160 patients diagnosed with glioma, representing the BraTS-Reg 2022 challenge dataset. ConvUNet-DIR, a deep learning-based deformable registration workflow using 3D U-Net style architecture as a core, was developed to establish correspondence between the MRI scans. The workflow consists of three components: (1) the U-Net learns features from pairs of MRI scans and estimates a mapping between them, (2) the grid generator computes the sampling grid based on the derived transformation parameters, and (3) the spatial transformation layer generates a warped image by applying the sampling operation using interpolation. A similarity measure was used as a loss function for the network with a regularization parameter limiting the deformation. The model was trained via unsupervised learning using pairs of MRI scans on a training data set (n = 102) and validated on a validation data set (n = 26) to assess its generalizability. Its performance was evaluated on a test set (n = 32) by computing the Dice score and structural similarity index (SSIM) quantitative metrics. The model's performance also was compared with the baseline state-of-the-art VoxelMorph (VM1 and VM2) learning-based algorithms. RESULTS: The ConvUNet-DIR model showed promising competency in performing accurate 3D deformable registration. It achieved a mean Dice score of 0.975 ± 0.003 and SSIM of 0.908 ± 0.011 on the test set (n = 32). Experimental results also demonstrated that ConvUNet-DIR outperformed the VoxelMorph algorithms concerning Dice (VM1: 0.969 ± 0.006 and VM2: 0.957 ± 0.008) and SSIM (VM1: 0.893 ± 0.012 and VM2: 0.857 ± 0.017) metrics. The time required to perform a registration for a pair of MRI scans is about 1 s on the CPU. CONCLUSIONS: The developed deep learning-based model can perform an end-to-end deformable registration of a pair of 3D MRI scans for glioma patients without human intervention. The model could provide accurate, efficient, and robust deformable registration without needing pre-alignment and labeling. It outperformed the state-of-the-art VoxelMorph learning-based deformable registration algorithms and other supervised/unsupervised deep learning-based methods reported in the literature.

[Clinical research in radiation oncology]. / La recherche clinique en oncologie-radiothérapie : acquis et perspectives.

Clinical research is summarizing scientific trials performed in human aiming to improve biological and medical knowledges. The management of such an activity has to be conducted in a secured environment in terms of expertise, competency and professionalism of involved actors. In the field of cancer, multidisciplinarity is key in the treatment of malignant disease and plays a major role sequentially or concomitantly. In the 90s, clinical research in radiation oncology obtained historical successes, which remain validated guidelines for national societies in a significant number of clinical situations. They concern not only technological improvements but also combined modality treatments with chemotherapy, hormonal therapy and potentially new targeted agents. Radiotherapy, in a palliative or in a curative setting, benefited from dramatic technological improvements aiming to address patient quality of life after radiation therapy. Actually, the emergence of artificial intelligence is willing to modify our current practice historically based on old concepts of clinical evaluation.

La recherche clinique correspond aux études scientifiques réalisées sur la personne humaine en vue du développement des connaissances biologiques et médicales. Sa conduite doit désormais être assurée dans des environnements garantissant l'expertise, la compétence et le professionnalisme des acteurs impliqués. Dans le traitement du cancer, la pluridisciplinarité, garante de la meilleure prise en charge des tumeurs malignes, fait intervenir, de manière séquentielle ou concomitante, de nombreuses spécialités. La recherche clinique en oncologie-radiothérapie a permis d'obtenir des acquis historiques qui restent, dans leur grande majorité, des référentiels de la prise en charge de la maladie reconnus par les sociétés nationales. Elles portent sur la validation des acquis technologiques, mais également sur des associations avec la chimiothérapie, l'hormonothérapie et, demain, les nouveaux agents de thérapie ciblée. La radiothérapie à visée palliative ou curative a considérablement bénéficié des évolutions technologiques et informatiques pour améliorer la qualité de vie des patients après traitement. L'émergence de l'intelligence artificielle permet d'envisager d'améliorer les pratiques basées sur une appréciation du bénéfice-risque. On peut espérer que l'intelligence artificielle devienne supérieure à l'appréciation clinique établie sur les anciens critères retenus au cours de l'histoire.

[Diversity, equity and inclusion in radiation oncology : where do we stand ?] / Diversité, équité et inclusion en radiothérapie-oncologie : où en sommes-nous ?

INTRODUCTION: The promotion of diversity, equity and inclusion (DEI) is increasingly sought after in healthcare, which is why we wanted to draw up a picture of DEI in radiation oncology and give some ideas on how to contribute to its dissemination. METHOD: This article proposes a non-exhaustive review of the international literature on DEI in radiation oncology, both among health professionals and patients. In addition, this review identifies some implicit cognitive biases and proposes strategies to address them. RESULTS: Most of the proposed publications identify a lack of DEI among radiation oncology staff and document inequities in access to high-quality radiotherapy affecting patients belonging to minority groups. CONCLUSION: Significant disparities exist between genders and ethnic groups within the radiotherapy teams, and in the radiotherapy treatment of patients. Nevertheless, DEI is gaining importance, and a range of initiatives and instruments are being developed to address these disparities.

INTRODUCTION: La promotion de l'équité, de la diversité et de l'inclusion (EDI) est de plus en plus recherchée dans les soins de santé, raison pour laquelle nous avons voulu dresser un tableau de l'EDI en radiothérapie et donner des pistes pour contribuer à sa diffusion. Méthode : Cet article propose une revue non exhaustive de la littérature internationale sur l'EDI en radiothérapie, tant chez les professionnels de la santé que chez les patients. En outre, cette revue relève des biais cognitifs implicites et propose des stratégies pour y remédier. Résultats : La majorité des publications proposées identifient un manque d'EDI parmi les professionnels en radiothérapie, et documentent également des iniquités dans l'accès à une radiothérapie de haute qualité touchant les patients issus de groupes minoritaires. CONCLUSION: D'importantes disparités existent entre genres et groupes ethniques au sein des équipes de radiothérapie ainsi que dans le traitement des patients par radiothérapie. Néanmoins, l'EDI gagne en importance et toute une série d'initiatives et d'instruments pour remédier à ces disparités se développent.

[Network science. Part 2 : in radiotherapy]. / La science des réseaux. Partie 2 : en radiothérapie.

In a former publication, we summarized basic principles of network science in order to understand its potential, especially within the field of oncology. This rather young science offers, for example, the opportunity to identify new systemic treatment options. However, these are not the only therapeutic options within the arsenal devoted to the battle against cancer. The two other main pillars of treatment are surgery and radiotherapy. It is our purpose to highlight some applications - rather limited nowadays - of network science in radiotherapy. Data are not so abundant compared to the field of systemic treatments.

Dans un article précédent, les préceptes de base de la science des réseaux ont été sommairement abordés, afin d'en illustrer l'intérêt en cancérologie, en général. Nous avons pu faire le point - de façon non exhaustive - sur l'utilité de cette science assez jeune, en montrant, par exemple, son apport en matière d'identification de moyens systémiques de traitement. Les traitements systémiques font partie de l'arsenal thérapeutique, tout comme d'ailleurs la chirurgie et la radiothérapie. Nous voulons décrire brièvement certaines applications de la science des réseaux quand il s'agit du domaine particulier des radiations ionisantes, même si leur nombre est somme toute plus limité par rapport à ce qui est publié dans le domaine des traitements systémiques.

Addressing challenges in low-income and middle-income countries through novel radiotherapy research opportunities.

Although radiotherapy continues to evolve as a mainstay of the oncological armamentarium, research and innovation in radiotherapy in low-income and middle-income countries (LMICs) faces challenges. This third Series paper examines the current state of LMIC radiotherapy research and provides new data from a 2022 survey undertaken by the International Atomic Energy Agency and new data on funding. In the context of LMIC-related challenges and impediments, we explore several developments and advances-such as deep phenotyping, real-time targeting, and artificial intelligence-to flag specific opportunities with applicability and relevance for resource-constrained settings. Given the pressing nature of cancer in LMICs, we also highlight some best practices and address the broader need to develop the research workforce of the future. This Series paper thereby serves as a resource for radiation professionals.

Implementation of a programmatic assessment model in radiation oncology medical physics training.

PURPOSE: In 2019, a formal review and update of the current training program for medical physics residents/registrars in Australasia was conducted. The purpose of this was to ensure the program met current local clinical and technological requirements, to improve standardization of training across Australia and New Zealand and generate a dynamic curriculum and programmatic assessment model. METHODS: A four-phase project was initiated, including a consultant desktop review of the current program and stakeholder consultation. Overarching program outcomes on which to base the training model were developed, with content experts used to update the scientific content. Finally, assessment specialists reviewed a range of assessment models to determine appropriate assessment methods for each learning outcome, creating a model of programmatic assessment. RESULTS: The first phase identified a need for increased standardized assessment incorporating programmatic assessment. Seven clear program outcome statements were generated and used to guide and underpin the new curriculum framework. The curriculum was expanded from the previous version to include emerging technologies, while removing previous duplication. Finally, a range of proposed assessments for learning outcomes in the curriculum were generated into the programmatic assessment model. These new assessment methods were structured to incorporate rubric scoring to provide meaningful feedback. CONCLUSIONS: An updated training program for Radiation Oncology Medial Physics registrars/residents was released in Australasia. Scientific content from a previous program was used as a foundation and revised for currency with the ability to accommodate a dynamic curriculum model. A programmatic model of assessment was created after comprehensive review and consultation. This new model of assessment provides more structured, ongoing assessment throughout the training period. It contains allowances for local bespoke assessment, and guidance for supervisors by the provision of marking templates and rubrics.

Integration of Telemedicine Consultation Into a Tertiary Radiation Oncology Department: Predictors of Use, Treatment Yield, and Effects on Patient Population.

PURPOSE: The COVID-19 pandemic led to rapid expansion of telemedicine. The implications of telemedicine have not been rigorously studied in radiation oncology, a procedural specialty. This study aimed to evaluate the characteristics of in-person patients (IPPs) and virtual patients (VPs) who presented to a large cancer center before and during the pandemic and to understand variables affecting likelihood of receiving radiotherapy (yield) at our institution. METHODS: A total of 17,915 patients presenting for new consultation between 2019 and 2021 were included, stratified by prepandemic and pandemic periods starting March 24, 2020. Telemedicine visits included video and telephone calls. Area deprivation indices (ADIs) were also compared. RESULTS: The overall population was 56% male and 93% White with mean age of 63 years. During the pandemic, VPs accounted for 21% of visits, were on average younger than their in-person (IP) counterparts (63.3 years IP v 62.4 VP), and lived further away from clinic (215 miles IP v 402 VP). Among treated VPs, living closer to clinic was associated with higher yield (odds ratio [OR], 0.95; P < .001). This was also seen among IPPs who received treatment (OR, 0.96; P < .001); however, the average distance from clinic was significantly lower for IPPs than VPs (205 miles IP v 349 VP). Specialized radiotherapy (proton and brachytherapy) was used more in VPs. IPPs had higher ADI than VPs. Among VPs, those treated had higher ADI (P < .001). CONCLUSION: Patient characteristics and yield were significantly different between IPPs and VPs. Telemedicine increased reach to patients further away from clinic, including from rural or health care-deprived areas, allowing access to specialized radiation oncology care. Telemedicine has the potential to increase the reach of other technical and procedural specialties.

Ferroptosis: Frenemy of Radiotherapy.

Recently, it was established that ferroptosis, a type of iron-dependent regulated cell death, plays a prominent role in radiotherapy-triggered cell death. Accordingly, ferroptosis inducers attracted a lot of interest as potential radio-synergizing drugs, ultimately enhancing radioresponses and patient outcomes. Nevertheless, the tumor microenvironment seems to have a major impact on ferroptosis induction. The influence of hypoxic conditions is an area of interest, as it remains the principal hurdle in the field of radiotherapy. In this review, we focus on the implications of hypoxic conditions on ferroptosis, contemplating the plausibility of using ferroptosis inducers as clinical radiosensitizers. Furthermore, we dive into the prospects of drug repurposing in the domain of ferroptosis inducers and radiosensitizers. Lastly, the potential adverse effects of ferroptosis inducers on normal tissue were discussed in detail. This review will provide an important framework for subsequent ferroptosis research, ascertaining the feasibility of ferroptosis inducers as clinical radiosensitizers.

Quality of Large Language Model Responses to Radiation Oncology Patient Care Questions.

Importance: Artificial intelligence (AI) large language models (LLMs) demonstrate potential in simulating human-like dialogue. Their efficacy in accurate patient-clinician communication within radiation oncology has yet to be explored. Objective: To determine an LLM's quality of responses to radiation oncology patient care questions using both domain-specific expertise and domain-agnostic metrics. Design, Setting, and Participants: This cross-sectional study retrieved questions and answers from websites (accessed February 1 to March 20, 2023) affiliated with the National Cancer Institute and the Radiological Society of North America. These questions were used as queries for an AI LLM, ChatGPT version 3.5 (accessed February 20 to April 20, 2023), to prompt LLM-generated responses. Three radiation oncologists and 3 radiation physicists ranked the LLM-generated responses for relative factual correctness, relative completeness, and relative conciseness compared with online expert answers. Statistical analysis was performed from July to October 2023. Main Outcomes and Measures: The LLM's responses were ranked by experts using domain-specific metrics such as relative correctness, conciseness, completeness, and potential harm compared with online expert answers on a 5-point Likert scale. Domain-agnostic metrics encompassing cosine similarity scores, readability scores, word count, lexicon, and syllable counts were computed as independent quality checks for LLM-generated responses. Results: Of the 115 radiation oncology questions retrieved from 4 professional society websites, the LLM performed the same or better in 108 responses (94%) for relative correctness, 89 responses (77%) for completeness, and 105 responses (91%) for conciseness compared with expert answers. Only 2 LLM responses were ranked as having potential harm. The mean (SD) readability consensus score for expert answers was 10.63 (3.17) vs 13.64 (2.22) for LLM answers (P < .001), indicating 10th grade and college reading levels, respectively. The mean (SD) number of syllables was 327.35 (277.15) for expert vs 376.21 (107.89) for LLM answers (P = .07), the mean (SD) word count was 226.33 (191.92) for expert vs 246.26 (69.36) for LLM answers (P = .27), and the mean (SD) lexicon score was 200.15 (171.28) for expert vs 219.10 (61.59) for LLM answers (P = .24). Conclusions and Relevance: In this cross-sectional study, the LLM generated accurate, comprehensive, and concise responses with minimal risk of harm, using language similar to human experts but at a higher reading level. These findings suggest the LLM's potential, with some retraining, as a valuable resource for patient queries in radiation oncology and other medical fields.

Serious game for radiotherapy training.

BACKGROUND: Cancer patients are often treated with radiation, therefore increasing their exposure to high energy emissions. In such cases, medical errors may be threatening or fatal, inducing the need to innovate new methods for maximum reduction of irreversible events. Training is an efficient and methodical tool to subject professionals to the real world and heavily educate them on how to perform with minimal errors. An evolving technique for this is Serious Gaming that can fulfill this purpose, especially with the rise of COVID-19 and the shift to the online world, by realistic and visual simulations built to present engaging scenarios. This paper presents the first Serious Game for Lung Cancer Radiotherapy training that embodies Biomedical Engineering principles and clinical experience to create a realistic and precise platform for coherent training. METHODS: To develop the game, thorough 3D modeling, animation, and gaming fundamentals were utilized to represent the whole clinical process of treatment, along with the scores and progress of every player. The model's goal is to output coherency and organization for students' ease of use and progress tracking, and to provide a beneficial educational experience supplementary to the users' training. It aims to also expand their knowledge and use of skills in critical cases where they must perform crucial decision-making and procedures on patients of different cases. RESULTS: At the end of this research, one of the accomplished goals consists of building a realistic model of the different equipment and tools accompanied with the radiotherapy process received by the patient on Maya 2018, including the true beam table, gantry, X-ray tube, CT Scanner, and so on. The serious game itself was then implemented on Unity Scenes with the built models to create a gamified authentic environment that incorporates the 5 main series of steps; Screening, Contouring, External Beam Planning, Plan Evaluation, Treatment, to simulate the practical workflow of an actual Oncology treatment delivery for lung cancer patients. CONCLUSION: This serious game provides an educational and empirical space for training and practice that can be used by students, trainees, and professionals to expand their knowledge and skills in the aim of reducing potential errors.

Effect of radiotherapy on the surface roughness and microhardness of contemporary bioactive restorative materials.

OBJECTIVE: The aim of this in vitro study was to evaluate the effect of radiotherapy on the surface microhardness and roughness of different bioactive restorative materials. MATERIALS AND METHODS: A total of 60-disc specimens (5 mm × 2 mm) were performed in four groups (n = 15 each) from Equia Forte HT, Cention N, Activa Bioactive Restorative, and Beautifil II. Following the polishing procedure (600, 1000, 1200 grit silicon carbide papers), all specimens were irradiated at 2 Gy per fraction, five times a week for a total dose of 70 Gy in 30 fractions over 7 weeks. Before and after the irradiation, the specimens were analyzed regarding the surface roughness and microhardness. Surface morphology was also analyzed by scanning electron microscopy. Kruskal-Wallis test, Wilcoxon test, and paired sample t-test were used for statistical analysis. RESULTS: Significant differences were found after radiation with increased mean roughness of both Cention N (p = 0.001) and Beautifil II (p < 0.001) groups. In terms of microhardness, only the Beautifil II group showed significant differences with decreased values after radiation. There were statistically significant differences among the groups' roughness and microhardness data before and after radiotherapy (p < 0.05). CONCLUSION: The effect of radiotherapy might differ according to the type of the restorative material. Although results may differ for other tested materials, giomer tends to exhibit worse behaviour in terms of both surface roughness and microhardness. CLINICAL RELEVANCE: In patients undergoing head and neck radiotherapy, it should be taken into consideration that the treatment process may also have negative effects on the surface properties of anti-caries restorative materials.

AAPM WGVRTO report 390: A survey of veterinary radiation oncology equipment and infrastructure in 2022.

Since 2010, there has been little published data on the state of equipment and infrastructure in veterinary radiation oncology clinical practice. These data are important not only to identify the status and use of technology within the veterinary radiation oncology community but also to help identify the extent of medical physics support. The purpose of our study is to report findings from a survey of veterinary radiation oncologists in the USA, Canada, and select centers outside of North America in 2022. A 40-question survey covering topics such as type of radiotherapy equipment, techniques offered, treatment planning systems and dose calculation algorithms, special techniques, board-certified radiation oncologists and residents, and extent of medical physics support was distributed through an online survey tool. Results from 40 veterinary radiation oncology institutions, with equipment explicitly used for veterinary care, suggest that the current state of practice is not dissimilar to what currently exists in human radiation oncology facilities; techniques and technologies commonly employed include flattening filter-free mode megavoltage beams, volumetric arc therapy, daily cone-beam computed tomography, image-guided radiation therapy, and sophisticated dose calculation algorithms. These findings suggest the need for modern radiation oncology acceptance testing, commissioning, and quality assurance programs within the veterinary community. The increase in veterinary radiation oncology residency positions and increasing sophistication of equipment suggests that increased levels of standardized medical physics support would benefit the veterinary radiation oncology community.