Standardizing and improving dose predictions for head and neck cancers using complete sets of OAR contours.

Background: Radiotherapy dose predictions have been trained with data from previously treated patients of similar sites and prescriptions. However, clinical datasets are often inconsistent and do not contain the same number of organ at risk (OAR) structures. The effects of missing contour data in deep learning-based dose prediction models have not been studied.

Dosimetric characterization of a new surface-conforming electron MLC prototype.

The purpose is to reduce normal tissue radiation toxicity for electron therapy through the creation of a surface-conforming electron multileaf collimator (SCEM). The SCEM combines the benefits of skin collimation, electron conformal radiotherapy, and modulated electron radiotherapy. An early concept for the SCEM was constructed.

Unique approaches for testicular shielding during total-body irradiation for pediatric patients.

Total-body irradiation (TBI) has been used as a part of the conditioning regimen for patients undergoing hematopoietic stem cell transplantation for certain nonmalignant conditions such as sickle cell disease. Although effective, TBI can cause lasting side effects for pediatric patients. One of these potential side effects includes oligospermia or even permanent azoospermia.

AAPM Report 373: The content, structure, and value of the Professional Doctorate in Medical Physics (DMP).

The Professional Doctorate in Medical Physics (DMP) was originally conceived as a solution to the shortage of medical physics residency training positions. While this shortage has now been largely satisfied through conventional residency training positions, the DMP has expanded to multiple institutions and grown into an educational pathway that provides specialized clinical training and extends well beyond the creation of additional training spots. As such, it is important to reevaluate the purpose and the value of the DMP.

Monte Carlo modeling of the Elekta Versa HD and patient dose calculation with EGSnrc/BEAMnrc.

Introduction: Numerous studies have proven the Monte Carlo method to be an accurate means of dose calculation. Although there are several commercial Monte Carlo treatment planning systems (TPSs), some clinics may not have access to these resources. We present a method for routine, independent patient dose calculations from treatment plans generated in a commercial TPS with our own Monte Carlo model using free, open-source software.

Microdosimetric and radiobiological effects of gold nanoparticles at therapeutic radiation energies.

Purpose: The purpose of this study was to quantify the microscopic dose distribution surrounding gold nanoparticles (GNPs) irradiated at therapeutic energies and to measure the changes in cell survival in vitro caused by this dose enhancement.

Methods: The dose distributions from secondary electrons surrounding a single gold nanosphere and single gold nanocube of equal volume were both simulated using MCNP6. Dose enhancement factors (DEFs) in the 1 μm volume surrounding a GNP were calculated and compared between a nanosphere and nanocube and between 6 and 18 MV energies.

Machine learning models to predict the delivered positions of Elekta multileaf collimator leaves for volumetric modulated arc therapy.

Purpose: Accurate positioning of multileaf collimator (MLC) leaves during volumetric modulated arc therapy (VMAT) is essential for accurate treatment delivery. We developed a linear regression, support vector machine, random forest, extreme gradient boosting (XGBoost), and an artificial neural network (ANN) for predicting the delivered leaf positions for VMAT plans.

Methods: For this study, 160 MLC log files from 80 VMAT plans were obtained from a single institution treated on 3 Elekta Versa HD linear accelerators.

Effects of varying statistical uncertainty using a Monte Carlo based treatment planning system for VMAT.

Purpose: To determine the severity of the effects on VMAT dose calculations caused by varying statistical uncertainties (SU) per control point in a Monte Carlo based treatment planning system (TPS) and to assess the impact of the uncertainty during dose volume histogram (DVH) evaluation.

Methods: For this study, 13 archived patient plans were selected for recalculation. Treatment sites included prostate, lung, and head and neck.

Using an implementation science approach to build leader facilitation capability in healthcare: a novel approach for enhancing action learning set facilitation.

Purpose: The study describes the implementation of a novel strategy, entitled the Action Learning Set Facilitation Model, to develop internal facilitation capability to lead change. The Model incorporated the Novice-Experienced-Expert pathway, a facilitation development approach underpinning the integrated-Promoting Action on Research Implementation in Health Services Implementation Framework, with action learning methodology.

Design/methodology/approach: A mixed-methods descriptive approach reports the results of 22 interviews, 182 Action Learning Sets and 159 post program survey data sets to explore facilitator experiences, strengths and potential application of the Model.

A customizable aluminum compensator system for total body irradiation.

Purpose: To develop a simplified aluminum compensator system for total body irradiation (TBI) that is easy to assemble and modify in a short period of time for customized patient treatments.

Methods: The compensator is composed of a combination of 0.3 cm thick aluminum bars, two aluminum T-tracks, spacers, and metal bolts.

Latent space arc therapy optimization.

Volumetric modulated arc therapy planning is a challenging problem in high-dimensional, non-convex optimization. Traditionally, heuristics such as fluence-map-optimization-informed segment initialization use locally optimal solutions to begin the search of the full arc therapy plan space from a reasonable starting point. These routines facilitate arc therapy optimization such that clinically satisfactory radiation treatment plans can be created in a reasonable time frame.

Variability of Breast Surface Positioning Using an Active Breathing Coordinator for a Deep Inspiration Breath Hold Technique.

Purpose The Elekta Active Breathing Coordinator (ABC) is used to control breathing and guide deep inspiration breath hold (DIBH). It has been shown to be accurate in lung cancers, but limited analysis has been performed on the spatial accuracy and reproducibility of the breast surface. The use of optical surface-image guidance for patient positioning has grown in popularity and is an alternative solution for breast DIBH.

A sensitivity analysis of probability maps in deep-learning-based anatomical segmentation.

Purpose: Deep-learning-based segmentation models implicitly learn to predict the presence of a structure based on its overall prominence in the training dataset. This phenomenon is observed and accounted for in deep-learning applications such as natural language processing but is often neglected in segmentation literature. The purpose of this work is to demonstrate the significance of class imbalance in deep-learning-based segmentation and recommend tuning of the neural network optimization objective.

On the evaluation of mobile target trajectory between four-dimensional computer tomography and four-dimensional cone-beam computer tomography.

Purpose: For mobile lung tumors, four-dimensional computer tomography (4D CT) is often used for simulation and treatment planning. Localization accuracy remains a challenge in lung stereotactic body radiation therapy (SBRT) treatments. An attractive image guidance method to increase localization accuracy is 4D cone-beam CT (CBCT) as it allows for visualization of tumor motion with reduced motion artifacts.

Is veterinary work more than satisfying? A critical review of the literature.

Despite the rise of positive psychology in recent times, research continues to emphasise the risks and negative outcomes associated with veterinary work. Understanding these challenges and risks is imperative in helping those affected and preventing or limiting exposure for future veterinarians. However, it is vital that positive factors associated with their well-being are concomitantly addressed.

Managing tumor changes during radiotherapy using a deep learning model.

Purpose: We propose a treatment planning framework that accounts for weekly lung tumor shrinkage using cone beam computed tomography (CBCT) images with a deep learning-based model.

Methods: Sixteen patients with non-small-cell lung cancer (NSCLC) were selected with one planning CT and six weekly CBCTs each. A deep learning-based model was applied to predict the weekly deformation of the primary tumor based on the spatial and temporal features extracted from previous weekly CBCTs.

Quantifying false positional corrections due to facial motion using SGRT with open-face Masks.

Purpose: Studies have evaluated the viability of using open-face masks as an immobilization technique to treat intracranial and head and neck cancers. This method offers less stress to the patient with comparable accuracy to closed-face masks. Open-face masks permit implementation of surface guided radiation therapy (SGRT) to assist in positioning and motion management.

A detailed experimental and Monte Carlo analysis of gold nanoparticle dose enhancement using 6 MV and 18 MV external beam energies in a macroscopic scale.

Dose enhancement due to gold nanoparticles (GNPs) has been quantified experimentally and through Monte Carlo simulations for external beam radiation therapy energies of 6 and 18 MV. The highest enhancement was observed for the 18 MV beam at the highest GNP concentration tested, amounting to a DEF of 1.02.

Objective Assessment of the Quality and Accuracy of Deformable Image Registration.

Background: The increased use of deformable registration algorithms in clinical practice has also increased the need for their validation.

Aims And Objectives: The purpose of the study was to investigate the quality, accuracy, and plausibility of three commercial image registration algorithms for 4-dimensional computed tomography (4DCT) datasets using various similarity measures.

Materials And Methods: 4DCT datasets were acquired for 10 lung cancer patients.

Dose Calculation Comparisons between Three Modern Treatment Planning Systems.

Purpose: Monaco treatment planning system (TPS) version 5.1 uses a Monte-Carlo (MC)-based dose calculation engine. The aim of this study is to verify and compare the Monaco-based dose calculations with both Pinnacle collapsed cone convolution superposition (CCCS) and Eclipse anisotropic analytical algorithm (AAA) calculations.

An evaluation of Pencil Beam vs Monte Carlo calculations for intracranial stereotactic radiosurgery.

Purpose: To compare the accuracy of two separate models when calculating dose distributions in patients undergoing stereotactic radiosurgery (SRS) treatment for brain cancer.

Methods: For this comparison, two dose calculation algorithms were evaluated on two different treatment planning systems (TPS): Elekta's Monaco Version 5.11.

Characterization and comparison of imaging contrast enhancement with PEG-functionalized gold nanoparticles in kV cone beam computed tomography and computed tomography imaging.

The purpose of this study is to define a simplified method to accurately predict and characterize kV cone beam computed tomography (kV CBCT) and computed tomography (CT) image contrast enhancement from gold nanoparticles (GNPs). Parameters of the kV CBCT of a Varian Novalis Tx linear accelerator and of a GE LightSpeed 4 Big Bore CT machine were modeled using the MCNP 6.2 Monte Carlo code.

DNA Dosimeter Measurement of Relative Biological Effectiveness for 160 kVp and 6 MV X Rays.

In this work, we developed a DNA dosimeter, consisting of 4-kb DNA strands attached to magnetic streptavidin beads and labeled with fluorescein, to detect double-strand breaks (DSBs). The purpose here was to evaluate whether the DNA dosimeter readings reflect the relative biological effects of 160 kVp and 6 MV X rays. AVarian 600 C/D linac (6 MV) and a Faxitron cabinet X-ray system (160 kVp), both calibrated using traceable methods, were used to deliver high- and low-energy photons, respectively, to DNA dosimeters and multiple cell lines (mNs-5, HT-22 and Daoy).

An open-source tool to visualize potential cone collisions while planning SRS cases.

Purpose: To create an open-source visualization program that allows one to find potential cone collisions while planning intracranial stereotactic radiosurgery cases.

Methods: Measurements of physical components in the treatment room (gantry, cone, table, localization stereotactic radiation surgery frame, etc.) were incorporated into a script in MATLAB (MathWorks, Natick, MA) that produces three-dimensional visualizations of the components.