Health and Medical Physics Commons^™

Investigation Of Autosegmentation Techniques On T2-Weighted Mri For Off-Line Dose Reconstruction In Mr-Linac Workflow For Head And Neck Cancers, Brigid A Mcdonald, Carlos E Cardenas, Nicolette O'Connell, Sara Ahmed, Mohamed A Naser, Kareem A Wahid, Jiaofeng Xu, Dan Thill, Raed J Zuhour, Shane Mesko, Alexander Augustyn, Samantha M Buszek, Stephen Grant, Bhavana V Chapman, Alexander F Bagley, Renjie He, Abdallah S R Mohamed, John Christodouleas, Kristy K Brock, Clifton D Fuller

Faculty, Staff and Student Publications

Background: In order to accurately accumulate delivered dose for head and neck cancer patients treated with the Adapt to Position workflow on the 1.5T magnetic resonance imaging (MRI)-linear accelerator (MR-linac), the low-resolution T2-weighted MRIs used for daily setup must be segmented to enable reconstruction of the delivered dose at each fraction.

Purpose: In this pilot study, we evaluate various autosegmentation methods for head and neck organs at risk (OARs) on on-board setup MRIs from the MR-linac for off-line reconstruction of delivered dose.

Methods: Seven OARs (parotid glands, submandibular glands, mandible, spinal cord, and brainstem) were contoured on 43 images by …

Identifying The Optimal Deep Learning Architecture And Parameters For Automatic Beam Aperture Definition In 3d Radiotherapy, Skylar S Gay, Kelly D Kisling, Brian M Anderson, Lifei Zhang, Dong Joo Rhee, Callistus Nguyen, Tucker Netherton, Jinzhong Yang, Kristy Brock, Anuja Jhingran, Hannah Simonds, Ann Klopp, Beth M Beadle, Laurence E Court, Carlos E Cardenas

Faculty, Staff and Student Publications

PURPOSE: Two-dimensional radiotherapy is often used to treat cervical cancer in low- and middle-income countries, but treatment planning can be challenging and time-consuming. Neural networks offer the potential to greatly decrease planning time through automation, but the impact of the wide range of hyperparameters to be set during training on model accuracy has not been exhaustively investigated. In the current study, we evaluated the effect of several convolutional neural network architectures and hyperparameters on 2D radiotherapy treatment field delineation.

METHODS: Six commonly used deep learning architectures were trained to delineate four-field box apertures on digitally reconstructed radiographs for cervical cancer …

Quantitative Dual-Energy Computed Tomography With Cesium As A Novel Contrast Agent For Localization Of Thermochemical Ablation In Phantoms And Ex Vivo Models, Emily A Thompson, Megan C Jacobsen, David T Fuentes, Rick R Layman, Erik N K Cressman

Faculty, Staff and Student Publications

Background: Thermochemical ablation (TCA) is a minimally invasive therapy under development for hepatocellular carcinoma. TCA simultaneously delivers an acid (acetic acid, AcOH) and base (sodium hydroxide, NaOH) directly into the tumor, where the acid/base chemical reaction produces an exotherm that induces local ablation. However, AcOH and NaOH are not radiopaque, making monitoring TCA delivery difficult.

Purpose: We address the issue of image guidance for TCA by utilizing cesium hydroxide (CsOH) as a novel theranostic component of TCA that is detectable and quantifiable with dual-energy CT (DECT).

Materials and methods: To quantify the minimum concentration of CsOH that can be positively …

Deep Learning-Based Dose Prediction To Improve The Plan Quality Of Volumetric Modulated Arc Therapy For Gynecologic Cancers, Mary P Gronberg, Anuja Jhingran, Tucker J Netherton, Skylar S Gay, Carlos E Cardenas, Christine Chung, David Fuentes, Clifton D Fuller, Rebecca M Howell, Meena Khan, Tze Yee Lim, Barbara Marquez, Adenike M Olanrewaju, Christine B Peterson, Ivan Vazquez, Thomas J Whitaker, Zachary Wooten, Ming Yang, Laurence E Court

Faculty, Staff and Student Publications

Background: In recent years, deep‐learning models have been used to predict entire three‐dimensional dose distributions. However, the usability of dose predictions to improve plan quality should be further investigated.

Purpose: To develop a deep‐learning model to predict high‐quality dose distributions for volumetric modulated arc therapy (VMAT) plans for patients with gynecologic cancer and to evaluate their usability in driving plan quality improvements.

Methods: A total of 79 VMAT plans for the female pelvis were used to train (47 plans), validate (16 plans), and test (16 plans) 3D dense dilated U‐Net models to predict 3D dose distributions. The models received the …

Comprehensive Evaluation And New Recommendations In The Use Of Gafchromic Ebt3 Film, Kevin Liu, Patrik Gonçalves Jorge, Ramesh Tailor, Raphaël Moeckli, Emil Schüler

Faculty, Staff and Student Publications

BACKGROUND: Gafchromic film's unique properties of tissue-equivalence, dose-rate independence, and high spatial resolution make it an attractive choice for many dosimetric applications. However, complicated calibration processes and film handling limits its routine use.

PURPOSE: We evaluated the performance of Gafchromic EBT3 film after irradiation under a variety of measurement conditions to identify aspects of film handling and analysis for simplified but robust film dosimetry.

METHODS: The short- (from 5 min to 100 h) and long-term (months) film response was evaluated for clinically relevant doses of up to 50 Gy for accuracy in dose determination and relative dose distributions. The dependence …

Outcomes Of Breakthrough Covid-19 Infections In Patients With Hematologic Malignancies, Kelly S Chien, Christine B Peterson, Elliana Young, Dai Chihara, Elizabet E Manasanch, Jeremy L Ramdial, Philip A Thompson

Faculty, Staff and Student Publications

Patients with hematologic malignancies have both an increased risk for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections and higher morbidity/mortality. They have lower seroconversion rates after vaccination, potentially leading to inferior coronavirus disease 2019 (COVID-19) outcomes, despite vaccination. We consequently evaluated the clinical outcomes of COVID-19 infections in 243 vaccinated and 175 unvaccinated patients with hematologic malignancies. Hospitalization rates were lower in the vaccinated group when compared with the unvaccinated group (31.3% vs 52.6%). However, the rates of COVID-19-associated death were similar at 7.0% and 8.6% in vaccinated and unvaccinated patients, respectively. By univariate logistic regression, females, older patients, …

Mpla Case: How Do You Lead As A Lead Physicist?, Patricia Sansourekidou, Leonard Kim, Lee Xu, Mary Gronberg, Cassandra Stambaugh, Dongxu Wang

Faculty, Staff and Student Publications

This work of fiction is part of a case study series developed by the Medical Physics Leadership Academy (MPLA). It is intended to facilitate the discussion of the managerial and leadership challenges faced by a clinical medical physicist. In this case, a physicist David used to work in a clinic where he thrived and felt like a leader, despite not having the title. After a job change, he is now officially the "Lead Physicist" at a hospital newly affiliated with a large academic healthcare system. He believes he will be equally successful. Yet he struggles to bring about changes and …

Interrogations Of The Tumor Microenvironment Using Magnetic Resonance Imaging, Tianzhe Li

Dissertations and Theses (Open Access)

Both tumor acidosis and tumor hypoxia are characteristics commonly found in the microenvironment of solid malignant tumors. Accurate characterization of the two phenomena could provide important information to clinicians for devising suitable treatment plans. Tumor acidosis and hypoxia are closely linked to each other. Tumor acidosis is caused by the inclination of cancer cells towards anaerobic respiration, and one of the main contributing factors for the avoidance of aerobic respiration is tumor hypoxia. Both phenomena can indicate the high metastatic potential of cancers and can also cause resistance of the cancer systems against anti-cancer therapies. Therefore, developing novel molecular imaging …

Hazard Testing To Reduce Risk In The Development Of Automated Planning Tools, Kelly A Nealon, Raphael J Douglas, Eun Young Han, Stephen F Kry, Valerie K Reed, Samantha J Simiele, Laurence E Court

Faculty, Staff and Student Publications

PURPOSE: Hazard scenarios were created to assess and reduce the risk of planning errors in automated planning processes. This was accomplished through iterative testing and improvement of examined user interfaces.

METHODS: Automated planning requires three user inputs: a computed tomography (CT), a prescription document, known as the service request, and contours. We investigated the ability of users to catch errors that were intentionally introduced into each of these three stages, according to an FMEA analysis. Five radiation therapists each reviewed 15 patient CTs, containing three errors: inappropriate field of view, incorrect superior border, and incorrect identification of isocenter. Four radiation …

Multi-Parametric Mri For Radiotherapy Simulation, Tian Li, Jihong Wang, Yingli Yang, Carri K Glide-Hurst, Ning Wen, Jing Cai

Faculty, Staff and Student Publications

Magnetic resonance imaging (MRI) has become an important imaging modality in the field of radiotherapy (RT) in the past decade, especially with the development of various novel MRI and image-guidance techniques. In this review article, we will describe recent developments and discuss the applications of multi-parametric MRI (mpMRI) in RT simulation. In this review, mpMRI refers to a general and loose definition which includes various multi-contrast MRI techniques. Specifically, we will focus on the implementation, challenges, and future directions of mpMRI techniques for RT simulation.

Mpla Case: I Didn't Realize Those Were The Expectations!, Samantha J Simiele, Serdar Charyyev, Liyong Lin, Leonard Kim, Dongxu Wang, Mary P Gronberg

Faculty, Staff and Student Publications

This work of fiction is part of a case study series developed by the Medical Physics Leadership Academy (MPLA). It is intended to facilitate the discussion of how students and advisors can better communicate expectations and navigate difficult conversations. In this case, a fourth-year Ph.D. student Emma learns that her advisor Dr. So is leaving the institution and has not arranged to bring any students with him. As Emma and Dr. So meet to discuss Emma's next steps, the conversation reveals misunderstandings and miscommunications of expectations, including a specific publication requirement for graduation from Dr. So. Having just learned of …

Analysis Of Performance And Failure Modes Of The Iroc Proton Liver Phantom, Hunter Mehrens, Paige Taylor, Paola Alvarez, Stephen Kry

Faculty, Staff and Student Publications

Purpose: To analyze trends in institutional performance and failure modes for the Imaging and Radiation Oncology Core’s (IROC’s) proton liver phantom.

Materials and Methods: Results of 66 phantom irradiations from 28 institutions between 2015 and 2020 were retrospectively analyzed. Univariate analysis and random forest models were used to associate irradiation conditions with phantom results. Phantom results included pass/fail classification, average thermoluminescent dosimeter (TLD) ratio of both targets, and percentage of pixels passing gamma of both targets. The following categories were evaluated in terms of how they predicted these outcomes: irradiation year, treatment planning system (TPS), TPS algorithm, treatment machine, number …

Parametric Delineation Uncertainties Contouring (Pduc) Modeling On Ct Scans Of Prostate Cancer Patients, Vi Ly, Lizhong Liu, Carlos Cardenas, Sean Maroongroge, Brian De, Daniel El Basha, Laurence Court, Xi Luo

Faculty, Staff and Student Publications

PURPOSE: Variability in contouring contributes to large variations in radiation therapy planning and treatment outcomes. The development and testing of tools to automatically detect contouring errors require a source of contours that includes well-understood and realistic errors. The purpose of this work was to develop a simulation algorithm that intentionally injects errors of varying magnitudes into clinically accepted contours and produces realistic contours with different levels of variability.

METHODS: We used a dataset of CT scans from 14 prostate cancer patients with clinician-drawn contours of the regions of interest (ROI) of the prostate, bladder, and rectum. Using our newly developed …

Intensity Modulated Proton Arc Therapy Via Geometry-Based Energy Selection For Ependymoma, Wenhua Cao, Yupeng Li, Xiaodong Zhang, Falk Poenisch, Pablo Yepes, Narayan Sahoo, David Grosshans, Susan Mcgovern, G Brandon Gunn, Steven J Frank, Xiaorong R Zhu

Faculty, Staff and Student Publications

PURPOSE: We developed and tested a novel method of creating intensity modulated proton arc therapy (IMPAT) plans that uses computing resources similar to those for regular intensity-modulated proton therapy (IMPT) plans and may offer a dosimetric benefit for patients with ependymoma or similar tumor geometries.

METHODS: Our IMPAT planning method consists of a geometry-based energy selection step with major scanning spot contributions as inputs computed using ray-tracing and single-Gaussian approximation of lateral spot profiles. Based on the geometric relation of scanning spots and dose voxels, our energy selection module selects a minimum set of energy layers at each gantry angle …

Resection Cavity Auto-Contouring For Patients With Pediatric Medulloblastoma Using Only Ct Information, Soleil Hernandez, Callistus Nguyen, Skylar Gay, Jack Duryea, Rebecca Howell, David Fuentes, Jeannette Parkes, Hester Burger, Carlos Cardenas, Arnold C Paulino, Julianne Pollard-Larkin, Laurence Court

Faculty, Staff and Student Publications

PURPOSE: Target delineation for radiation therapy is a time-consuming and complex task. Autocontouring gross tumor volumes (GTVs) has been shown to increase efficiency. However, there is limited literature on post-operative target delineation, particularly for CT-based studies. To this end, we trained a CT-based autocontouring model to contour the post-operative GTV of pediatric patients with medulloblastoma.

METHODS: One hundred four retrospective pediatric CT scans were used to train a GTV auto-contouring model. Eighty patients were then preselected for contour visibility, continuity, and location to train an additional model. Each GTV was manually annotated with a visibility score based on the number …

Monte Carlo-Derived 99m Tc Uptake Quantification With Commercial Planar Mbi: Tumor And Breast Activity Concentrations, Benjamin P Lopez, S Cheenu Kappadath

Faculty, Staff and Student Publications

BACKGROUND: Current molecular breast imaging (MBI) images are limited to qualitative evaluation, not absolute measurement, of

PURPOSE: This work assesses the accuracy of previously-published and newly-proposed tumor and normal breast tissue

METHODS: Quantification techniques were tested in over 4000 simulated acquisitions of spherical and ellipsoid tumors with clinically relevant uptake conditions using a validated Monte Carlo application of the GE Discovery NM750b system. The evaluated techniques consisted of four tumor total activity methodologies (two single-detector-based and two geometric-mean-based), two tumor MBI volume methodologies (diameter-based and ROI-based), and two normal tissue activity concentration methodologies (single-detector-based and geometric-mean-based). The most accurate of …

Compensation Cycle Consistent Generative Adversarial Networks (Comp-Gan) For Synthetic Ct Generation From Mr Scans With Truncated Anatomy, Yao Zhao, He Wang, Cenji Yu, Laurence E Court, Xin Wang, Qianxia Wang, Tinsu Pan, Yao Ding, Jack Phan, Jinzhong Yang

Faculty, Staff and Student Publications

BACKGROUND: MR scans used in radiotherapy can be partially truncated due to the limited field of view (FOV), affecting dose calculation accuracy in MR-based radiation treatment planning.

PURPOSE: We proposed a novel Compensation-cycleGAN (Comp-cycleGAN) by modifying the cycle-consistent generative adversarial network (cycleGAN), to simultaneously create synthetic CT (sCT) images and compensate the missing anatomy from the truncated MR images.

METHODS: Computed tomography (CT) and T1 MR images with complete anatomy of 79 head-and-neck patients were used for this study. The original MR images were manually cropped 10-25 mm off at the posterior head to simulate clinically truncated MR images. Fifteen …

Ai-Enabled Online Plan Adaptation For Mr-Guided Stereotactic Ablative Radiotherapy (Sabr) Of Head And Neck Cancer, Yao Zhao

Dissertations and Theses (Open Access)

Head and neck cancer (HNC) is a prevalent cancer type worldwide. Stereotactic ablative radiotherapy (SABR) has emerged as an effective treatment for HNC, delivering highly conformal doses to the tumor target while sparing surrounding normal tissues with a sharp dose gradient. However, the accuracy of the treatment delivery is limited by setup errors, anatomical changes, and intra-/inter-fraction organ motion. The emergence of MR-guided adaptive radiotherapy (ART) has the potential to further improve the SABR of HNC, by providing superior visualization of soft tissue and enabling real-time plan adaptation based on the daily anatomical changes of patients. This novel technology has …

A Virtual Audit System For Intensity-Modulated Radiation Therapy Credentialing In Japan Clinical Oncology Group Clinical Trials: A Pilot Study, Mitsuhiro Nakamura, Dejun Zhou, Toshiyuki Minemura, Satoshi Kito, Hiroyuki Okamoto, Naoki Tohyama, Masahiko Kurooka, Yu Kumazaki, Masayori Ishikawa, Catharine H Clark, Elizabeth Miles, Joerg Lehmann, Nicolaus Andratschke, Stephen Kry, Satoshi Ishikura, Takashi Mizowaki, Teiji Nishio

Faculty, Staff and Student Publications

Purpose: The Medical Physics Working Group of the Radiation Therapy Study Group at the Japan Clinical Oncology Group is currently developing a virtual audit system for intensity-modulated radiation therapy dosimetry credentialing. The target dosimeters include films and array detectors, such as ArcCHECK (Sun Nuclear Corporation, Melbourne, Florida, USA) and Delta4 (ScandiDos, Uppsala, Sweden). This pilot study investigated the feasibility of our virtual audit system using previously acquired data.

Methods: We analyzed 46 films (32 and 14 in the axial and coronal planes, respectively) from 29 institutions. Global gamma analysis between measured and planned dose distributions used the following settings: 3%/3 …

Aapm Task Group Report 305: Guidance For Standardization Of Vendor-Neutral Reject Analysis In Radiography, Kevin Little, Ingrid Reiser, Bruce Apgar, Poonam Dalal, Jaydev Dave, Ryan Fisher, Katie Hulme, Mary Ellen Jafari, Emily Marshall, Stephen Meyer, Quentin Moore, Nicole Murphy, Thomas Nishino, Katelyn Nye, Kevin O'Donnell, John Sabol, Adrian Sanchez, William Sensakovic, Lawrence Tarbox, Robert Uzenoff, Alisa Walz-Flannigan, Charles Willis, Jie Zhang

Faculty, Staff and Student Publications

Reject rate analysis is considered an integral part of a diagnostic radiography quality control (QC) program. A rejected image is a patient radiograph that was not presented to a radiologist for diagnosis and that contributes unnecessary radiation dose to the patient. Reject rates that are either too high or too low may suggest systemic department shortcomings in QC mechanisms. Due to the lack of standardization, reject data often cannot be easily compared between radiography systems from different vendors. The purpose of this report is to provide guidance to help standardize data elements that are required for comprehensive reject analysis and …

Monte Carlo-Derived 99m Tc Uptake Quantification With Commercial Planar Mbi: Absolute Tumor Activity, Benjamin P Lopez, Srinivas Cheenu Kappadath

Faculty, Staff and Student Publications

BACKGROUND: Molecular breast imaging (MBI) of 99mTc-sestamibi is an emerging adjunct qualitative tool in the detection and diagnosis of breast cancer.

PURPOSE: This work outlines the development and performance evaluation of a methodology to absolutely quantify tumor 99mTc activity uptake using a commercially available dual-headed MBI system by implementing corrections for background, scatter, attenuation, and detector characteristics.

METHODS: A validated Monte Carlo application of a commercial MBI system was used to simulate over 7000 unique acquisitions of spherical and ellipsoidal tumors in breast tissue. Tumor absolute activity was calculated following background, scatter, and attenuation corrections of tumor region of interest …

Treatment Planning Automation For Rectal Cancer Radiotherapy, Kai Huang

Dissertations and Theses (Open Access)

Background

Rectal cancer is a common type of cancer. There is an acute health disparity across the globe where a significant population of the world lack adequate access to radiotherapy treatments which is a part of the standard of care for rectal cancers. Safe radiotherapy treatments require specialized planning expertise and are time-consuming and labor-intensive to produce.

Purpose:

To alleviate the health disparity and promote the safe and quality use of radiotherapy in treating rectal cancers, the entire treatment planning process needs to be automated. The purpose of this project is to develop automated solutions for the treatment planning process …

A Model For Gastrointestinal Tract Motility In A 4d Imaging Phantom Of Human Anatomy, Ergys Subashi, Paul Segars, Harini Veeraraghavan, Joseph Deasy, Neelam Tyagi

Faculty, Staff and Student Publications

BACKGROUND: Gastrointestinal (GI) tract motility is one of the main sources for intra/inter-fraction variability and uncertainty in radiation therapy for abdominal targets. Models for GI motility can improve the assessment of delivered dose and contribute to the development, testing, and validation of deformable image registration (DIR) and dose-accumulation algorithms.

PURPOSE: To implement GI tract motion in the 4D extended cardiac-torso (XCAT) digital phantom of human anatomy.

MATERIALS AND METHODS: Motility modes that exhibit large amplitude changes in the diameter of the GI tract and may persist over timescales comparable to online adaptive planning and radiotherapy delivery were identified based on …

Combining Physics-Based Models With Deep Learning Image Synthesis And Uncertainty In Intraoperative Cone-Beam Ct Of The Brain, Xiaoxuan Zhang, Alejandro Sisniega, Wojciech B Zbijewski, Junghoon Lee, Craig K Jones, Pengwei Wu, Runze Han, Ali Uneri, Prasad Vagdargi, Patrick A Helm, Mark Luciano, William S Anderson, Jeffrey H Siewerdsen

Faculty, Staff and Student Publications

BACKGROUND: Image-guided neurosurgery requires high localization and registration accuracy to enable effective treatment and avoid complications. However, accurate neuronavigation based on preoperative magnetic resonance (MR) or computed tomography (CT) images is challenged by brain deformation occurring during the surgical intervention.

PURPOSE: To facilitate intraoperative visualization of brain tissues and deformable registration with preoperative images, a 3D deep learning (DL) reconstruction framework (termed DL-Recon) was proposed for improved intraoperative cone-beam CT (CBCT) image quality.

METHODS: The DL-Recon framework combines physics-based models with deep learning CT synthesis and leverages uncertainty information to promote robustness to unseen features. A 3D generative adversarial network …

Quality Assurance Assessment Of Intra-Acquisition Diffusion-Weighted And T2-Weighted Magnetic Resonance Imaging Registration And Contour Propagation For Head And Neck Cancer Radiotherapy, Mohamed A Naser, Kareem A Wahid, Sara Ahmed, Vivian Salama, Cem Dede, Benjamin W Edwards, Ruitao Lin, Brigid Mcdonald, Travis C Salzillo, Renjie He, Yao Ding, Moamen Abobakr Abdelaal, Daniel Thill, Nicolette O'Connell, Virgil Willcut, John P Christodouleas, Stephen Y Lai, Clifton D Fuller, Abdallah S R Mohamed

Faculty, Staff and Student Publications

BACKGROUND/PURPOSE: Adequate image registration of anatomical and functional magnetic resonance imaging (MRI) scans is necessary for MR-guided head and neck cancer (HNC) adaptive radiotherapy planning. Despite the quantitative capabilities of diffusion-weighted imaging (DWI) MRI for treatment plan adaptation, geometric distortion remains a considerable limitation. Therefore, we systematically investigated various deformable image registration (DIR) methods to co-register DWI and T2-weighted (T2W) images.

MATERIALS/METHODS: We compared three commercial (ADMIRE, Velocity, Raystation) and three open-source (Elastix with default settings [Elastix Default], Elastix with parameter set 23 [Elastix 23], Demons) post-acquisition DIR methods applied to T2W and DWI MRI images acquired during the same …

Quantification Of The Role Of Lead Foil In Flattening Filter Free Beam Reference Dosimetry, Song Gao, Christopher Nelson, Congjun Wang, Vindu Kathriarachchi, Michael Choi, Rishik Saxena, Robin Kendall, Peter Balter

Faculty, Staff and Student Publications

PURPOSE: To quantify the potential error in outputs for flattening filter free (FFF) beams associated with use of a lead foil in beam quality determination per the addendum protocol for TG-51, we examined differences in measurements of the beam quality conversion factor k

METHODS: Two FFF beams, a 6 MV FFF and a 10 MV FFF, were calibrated on eight Varian TrueBeams and two Elekta Versa HD linear accelerators (linacs) according to the TG-51 addendum protocol by using Farmer ionization chambers [TN 30013 (PTW) and SNC600c (Sun Nuclear)] with traceable absorbed dose-to-water calibrations. In determining k

RESULTS: Differences in %dd(10)x …

Impact Of Dose Calculation Accuracy On Inverse Linear Energy Transfer Optimization For Intensity-Modulated Proton Therapy, Mei Chen, Wenhua Cao, Pablo Yepes, Fada Guan, Falk Poenisch, Cheng Xu, Jiayi Chen, Yupeng Li, Ivan Vazquez, Ming Yang, X Ronald Zhu, Xiaodong Zhang

Faculty, Staff and Student Publications

Objective: To determine the effect of dose calculation accuracy on inverse linear energy transfer (LET) optimization for intensity-modulated proton therapy, and to determine whether adding more beams would improve the plan robustness to different dose calculation engines.

Methods: Two sets of intensity-modulated proton therapy plans using two, four, six, and nine beams were created for 10 prostate cancer patients: one set was optimized with dose constraints (DoseOpt) using the pencil beam (PB) algorithm, and the other set was optimized with additional LET constraints (LETOpt) using the Monte Carlo (MC) algorithm. Dose distributions of DoseOpt plans were then recalculated using the …

Aapm Medical Physics Practice Guideline 13a: Hdr Brachytherapy, Part A, Susan L Richardson, Ivan M Buzurovic, Gil'ad N Cohen, Wesley S Culberson, Claire Dempsey, Bruce Libby, Christopher S Melhus, Robin A Miller, Daniel J Scanderbeg, Samantha J Simiele

Faculty, Staff and Student Publications

The American Association of Physicists in Medicine (AAPM) is a nonprofit professional society whose primary purposes are to advance the science, education, and professional practice of medical physics. The AAPM has more than 8000 members and is the principal organization of medical physicists in the United States. The AAPM will periodically define new practice guidelines for medical physics practice to help advance the science of medical physics and to improve the quality of service to patients throughout the United States. Existing medical physics practice guidelines (MPPGs) will be reviewed for the purpose of revision or renewal, as appropriate, on their …

Risk Analysis Of The Unity 15 T Mr-Linac Adapt-To-Position Workflow, Jiayi Liang, Paola Godoy Scripes, Neelam Tyagi, Ergys Subashi, Theresa Wunner, Nicolas Cote, Ching-Yun Chan, Angela Ng, Victoria Brennan, Kaveh Zakeri, Cassandra Wildberger, James Mechalakos

Faculty, Staff and Student Publications

BACKGROUND AND PURPOSE: Newer technologies allow for daily treatment adaptation, providing the ability to account for setup variations and organ motion but comes at the cost of increasing the treatment workflow complexity. One such technology is the adapt-to-position (ATP) workflow on the Unity MR-Linac. Prospective risk assessment of a new workflow allows clinics to catch errors before they occur, especially for processes that include novel and unfamiliar steps.

METHODS: As part of a quality management program, failure modes and effects analysis was performed on the ATP treatment workflow following the recommendations of AAPM's Task Group 100. A multidisciplinary team was …

Customizable Landmark-Based Field Aperture Design For Automated Whole-Brain Radiotherapy Treatment Planning, Yao Xiao, Carlos Cardenas, Dong Joo Rhee, Tucker Netherton, Lifei Zhang, Callistus Nguyen, Raphael Douglas, Raymond Mumme, Stephen Skett, Tina Patel, Chris Trauernicht, Caroline Chung, Hannah Simonds, Ajay Aggarwal, Laurence Court

Faculty, Staff and Student Publications

Purpose: To develop and evaluate an automated whole-brain radiotherapy (WBRT) treatment planning pipeline with a deep learning-based auto-contouring and customizable landmark-based field aperture design.

Methods: The pipeline consisted of the following steps: (1) Auto-contour normal structures on computed tomography scans and digitally reconstructed radiographs using deep learning techniques, (2) locate the landmark structures using the beam's-eye-view, (3) generate field apertures based on eight different landmark rules addressing different clinical purposes and physician preferences. Two parallel approaches for generating field apertures were developed for quality control. The performance of the generated field shapes and dose distributions were compared with the original …