Health and Medical Physics Commons^™

Landmark-Based Auto-Contouring Of Clinical Target Volumes For Radiotherapy Of Nasopharyngeal Cancer, Carlos Sjogreen, Tucker J Netherton, Anna Lee, Moaaz Soliman, Skylar S Gay, Callistus Nguyen, Raymond Mumme, Ivan Vazquez, Dong Joo Rhee, Carlos E Cardenas, Mary K Martel, Beth M Beadle, Laurence Edward Court

Faculty, Staff and Student Publications

Background: The delineation of clinical target volumes (CTVs) for radiotherapy for nasopharyngeal cancer is complex and varies based on the location and extent of disease.

Purpose: The current study aimed to develop an auto-contouring solution following one protocol guidelines (NRG-HN001) that can be adjusted to meet other guidelines, such as RTOG-0225 and the 2018 International guidelines.

Methods: The study used 2-channel 3-dimensional U-Net and nnU-Net framework to auto-contour 27 normal structures in the head and neck (H&N) region that are used to define CTVs in the protocol. To define the CTV-Expansion (CTV1 and CTV2) and CTV-Overall (the outer envelope of …

Correcting Ct Misregistration In Data-Driven Gated (Ddg) Pet With Pet Self-Gating And Deformable Image Registration, Peng Sun, M Allan Thomas, Dershan Luo, Tinsu Pan

Faculty, Staff and Student Publications

Background: Misregistration between CT and PET data can result in mis-localization and inaccurate quantification of functional uptake in whole body PET/CT imaging. This problem is exacerbated when an abnormal inspiration occurs during the free-breathing helical CT (FB CT) used for attenuation correction of PET data. In data-driven gated (DDG) PET, the data selected for reconstruction is typically derived from the end-expiration (EE) phase of the breathing cycle, making this potential issue worse.

Purpose: The objective of this study is to develop a deformable image registration (DIR)-based respiratory motion model to improve the registration and quantification between misregistered FB CT and …

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 …

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 …

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 …

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 …

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 …

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 …

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 …

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 …