This work introduces BreastWatch, a Varian Eclipse script tool designed to help medical physicists, dosimetrists, and radiation oncologists easily inspect and improve External Beam Breast Treatment (EBBT) plans using automatic evaluation of protocol dose-constraints enhanced by a Community-Based approach.

As medical linear accelerator technology advances, enabling higher dose rate deliveries, hypofractionation regimens has increased. This necessitates respiratory gating systems that synchronize radiation delivery with tumor position, requiring simple rigorous quality assurance (QA) to ensure treatment accuracy and patient safety.

Volumetric-modulated arc therapy (VMAT) treatment planning allows a compromise between a sufficient coverage of the planning target volume (PTV) and a simultaneous sparing of organs-at-risk (OARs). Particularly in the case of lung tumors, deciding whether it is possible or worth spending more time on further improvements of a treatment plan is difficult. Therefore, this work aims to develop a knowledge-based, structure-dependent, automated dose volume histogram (DVH) prediction module for lung tumors.

Breast cancer is a neoplastic disease with high prevalence among women. Radiotherapy is one of the principal treatment modalities for this disease, but it poses significant challenges. This study aimed to compare and evaluate the technical and dosimetric performance of conventional C-arm linac systems and a new design, Halcyon, in the context of breast radiotherapy.

Medical physics is a fulfilling profession where physics is applied to advance human health. However, many are uninformed of the role of physicists in medicine, and students are unaware of this career pathway. This study presents a pilot 1-year program for science teachers to learn about physics in medicine and share with students and teachers.

The use of deep learning-based auto-contouring algorithms in various treatment planning services is increasingly common. There is a notable deficit of commercially or publicly available models trained on large or diverse datasets containing high-dose-rate (HDR) brachytherapy treatment scans, leading to poor performance on images that include HDR implants.

In linear accelerators, deviations in the x-ray focal spot position significantly affect the accuracy of radiation therapy. However, as the focal spot position in bore-type linac systems such as the Radixact system, cannot be assessed using conventional methods, a new evaluation method is required. This study aimed to develop a novel method to measure the focal spot position of Radixact and evaluate any deviations from the ideal x-ray focal spot position.

FLASH has been shown to spare normal tissue toxicity while maintaining tumor control. However, existing irradiation platforms and dosimetry are not compatible. Consequently, an abundance of FLASH delivery devices and new dosimetry across all modalities has been created. Many review articles concluded that dosimetry is modality-dependent. Focusing on electrons, researchers have modified clinical LINACs to enable FLASH dose rates. Modified LINACs caused the development of unique control systems that have yet to be characterized. Improvement could be made when considering the organization of reviews.

Methods have been developed that apply image processing to 4DCTs to generate 4DCT-ventilation/perfusion lung imaging. Traditional methods for 4DCT-ventilation rely on Hounsfield-Unit (HU) density-change methods and suffer from poor numerical robustness while not providing 4DCT-perfusion data. The purpose of this work was to evaluate the clinical differences between classic HU-based 4DCT-ventilation approaches and novel 4DCT-ventilation/perfusion approaches.

The study evaluates rapid linear accelerator (Linac) single isocenter stereotactic radiosurgery (SRS) with Hyperarc for large target numbers. We compared to Gamma Knife (GK), which suffers from long treatment times and investigated causes of differences.

Balancing quality and efficiency has been a challenge for online adaptive therapy. Most systems start the online re-optimization with the original planning goals. While some systems allow planners to modify the planning goals, achieving a high-quality plan within time constraints remains a common barrier. This study aims to bolster plan quality by leveraging a deep-learning dose prediction model to predict new planning goals that account for inter-fractional anatomical changes.

This study quantitatively evaluates bladder changes and their dosimetric impact during the on-couch adaptive process on a commercial CBCT-based online adaptive radiotherapy (CT-gART) platform.

This study aims to evaluate the accuracy of the frameless linear accelerator-based stereotactic radiosurgery (FSRS) system incorporating cone-beam CT (CBCT), six degrees of freedom (6-DoF) couch, room laser, and surface image-guided (SG) systems. It focuses on assessing the FSRS system's accuracy and ability to detect position errors using head phantoms at different couch angles. Turntables were used to simulate the couch rotation to overcome the limitation of the available couch rotation angles for a 360° CBCT scan.

This study evaluates the dosimetric and geometric precision of a virtual cone technique using CBCT-based polymer gel dosimetry, enabling radiation delivery, and imaging readout within an identical spatial coordinate system.

The dose-averaged linear energy transfer (LET) in proton therapy (PT) has in pre-clinical studies been linked to the relative biological effectiveness (RBE) of protons. Until recently, the most common PT delivery method in prostate cancer has been double-scattered PT, with LET only available through dedicated Monte Carlo (MC) simulations. However, as most studies of the relationship between LET and RBE in double scattered PT have been focused on the head and neck region, existing MC implementations have not been capable of calculating LET for the longer field ranges used, for example, in the pelvic region.

Due to the tight curvature in their design, ring applicators are usually associated with large positioning errors. The standard practice to correct for these deviations based on global offsets may not be sufficient to comply with the recommended tolerance. In this work, we investigate two methods for applicator reconstruction that implement position-dependent source offset corrections.

Many artificial intelligence (AI) solutions have been proposed to enhance the radiotherapy (RT) workflow, but limited applications have been implemented to date, suggesting an implementation gap. One contributing factor to this gap is a misalignment between AI systems and their users. To address the AI implementation gap, we propose a human-centric methodology, novel in RT, for an interface design of an AI-driven RT treatment error detection system.

This study aimed to develop and validate a method for characterizing the spatial resolution of clinical chest computed tomography (CT) sequence images.

In vivo transit dosimetry using an electronic portal imaging device (EPID-IVTD) is an important tool for verifying the accuracy of radiation therapy treatments. Despite its potential, the implementation of EPID-IVTD in breast intensity modulated radiation therapy (IMRT) treatments has not yet been standardized, limiting its clinical adoption. A standardized EPID-IVTD method could enhance treatment accuracy and improve patient safety in routine clinical practice.

Current radiotherapy practices rely on manual contouring of CT scans, which is time-consuming, prone to variability, and requires highly trained experts. There is a need for more efficient and consistent contouring methods. This study evaluated the performance of the Varian Ethos AI auto-contouring tool to assess its potential integration into clinical workflows. This retrospective study included 223 patients with treatment sites in the pelvis, abdomen, thorax, and head and neck regions. The Ethos AI tool generated auto-contours on each patients' pre-treatment planning CT, and 45 unique structures were included across the study cohort. Multiple measures of geometric similarity were computed, including surface Dice Similarity Coefficient (sDSC) and mean distance to agreement (MDA). Dosimetric concordance was evaluated by comparing mean dose and maximum 2 cm dose (D) between manual and AI contours. Ethos AI demonstrated high geometric accuracy for well-defined structures like the bladder, lungs, and femoral heads. Smaller structures and those with less defined boundaries, such as optic nerves and duodenum, showed lower agreement. Over 70% of auto-contours demonstrated a sDSC > 0.8, and 74% had MDA < 2.5 mm. Geometric accuracy generally correlated with dosimetric concordance, however differences in contour definitions did result in some structures exhibiting dose deviations. The Ethos AI auto-contouring tool offers promising accuracy and reliability for many anatomical structures, supporting its use in planning workflows. Auto-contouring errors, although rare, highlight the importance of ongoing QA and expert manual oversight.

The use of radioactive materials in the United States has been tightly regulated by the Nuclear Regulatory Commission and other entities for many decades. In 2015, however, the Joint Commission began to require hospital-based nuclear medicine departments to conduct shielding designs and evaluations for radioactive material areas, mirroring established x-ray practices. NCRP Report No. 147 guides diagnostic medical x-ray shielding, but obviously cannot be used alone for nuclear medicine applications. The rising demand for theranostic nuclear medicine shielding evaluations particularly necessitates updated focused guidance, the aim of this report.