Radiation Medicine Commons^™

Safety Of Concurrent Radiation Therapy With Brentuximab Vedotin In The Treatment Of Lymphoma, Susan Y Wu, Penny Q Fang, Ethan B Wang, Sairah Ahmed, Madeleine Duvic, Preetesh Jain, Luis E Malpica Castillo, Ranjit Nair, Raphael E Steiner, Paolo Strati, Auris O Huen, Swaminathan P Iyer, Chelsea C Pinnix, Bouthaina S Dabaja, Jillian R Gunther

Faculty, Staff and Student Publications

PURPOSE: Purpose: Radiation therapy (RT) and the antibody-drug conjugate brentuximab vedotin (BV) are standard-of-care treatment options for patients with certain B and T-cell lymphomas; however, there are limited data exploring the safety of concurrent BV and RT (BVRT).

METHODS AND MATERIALS: We performed a single institutional retrospective review of 44 patients who received BVRT.

RESULTS: Twenty percent of patients (9/44) developed new grade 2 or higher (G2+) hematologic toxicity (HT) after BVRT, which was associated with radiation dose (median dose of 35 Gy in those with new G2+ HT compared with 15 Gy in those without;

CONCLUSIONS: Our analysis demonstrates …

Deep Learning-Based Dose Prediction For Automated, Individualized Quality Assurance Of Head And Neck Radiation Therapy Plans, Mary P Gronberg, Beth M Beadle, Adam S Garden, Heath Skinner, Skylar Gay, Tucker Netherton, Wenhua Cao, Carlos E Cardenas, Christine Chung, David T Fuentes, Clifton D Fuller, Rebecca M Howell, Anuja Jhingran, Tze Yee Lim, Barbara Marquez, Raymond Mumme, Adenike M Olanrewaju, Christine B Peterson, Ivan Vazquez, Thomas J Whitaker, Zachary Wooten, Ming Yang, Laurence E Court

Faculty, Staff and Student Publications

PURPOSE: This study aimed to use deep learning-based dose prediction to assess head and neck (HN) plan quality and identify suboptimal plans.

METHODS AND MATERIALS: A total of 245 volumetric modulated arc therapy HN plans were created using RapidPlan knowledge-based planning (KBP). A subset of 112 high-quality plans was selected under the supervision of an HN radiation oncologist. We trained a 3D Dense Dilated U-Net architecture to predict 3-dimensional dose distributions using 3-fold cross-validation on 90 plans. Model inputs included computed tomography images, target prescriptions, and contours for targets and organs at risk (OARs). The model's performance was assessed on …

Validation Of An Automated Contouring And Treatment Planning Tool For Pediatric Craniospinal Radiation Therapy, Soleil Hernandez, Hester Burger, Callistus Nguyen, Arnold C Paulino, John T Lucas, Austin M Faught, Jack Duryea, Tucker Netherton, Dong Joo Rhee, Carlos Cardenas, Rebecca Howell, David Fuentes, Julianne Pollard-Larkin, Laurence Court, Jeannette Parkes

Faculty, Staff and Student Publications

PURPOSE: Treatment planning for craniospinal irradiation (CSI) is complex and time-consuming, especially for resource-constrained centers. To alleviate demanding workflows, we successfully automated the pediatric CSI planning pipeline in previous work. In this work, we validated our CSI autosegmentation and autoplanning tool on a large dataset from St. Jude Children's Research Hospital.

METHODS: Sixty-three CSI patient CT scans were involved in the study. Pre-planning scripts were used to automatically verify anatomical compatibility with the autoplanning tool. The autoplanning pipeline generated 15 contours and a composite CSI treatment plan for each of the compatible test patients (n=51). Plan quality was evaluated quantitatively …

Effectiveness Without Efficacy: Cautionary Tale From A Landmark Breast Cancer Randomized Controlled Trial, Yu Shen, Jing Ning, Heather Y Lin, Simona F Shaitelman, Henry M Kuerer, Isabelle Bedrosian

Faculty, Staff and Student Publications

Background: “Old” randomized controlled trials established breast conserving therapy (BCT) and total mastectomy (TM) equivalence for treating early breast cancer, whereas recent literature report improved survival with BCT. To reconcile this, we performed a simulation study and re-analyzed B-06 trial data.

Methods: We estimated the distributions for overall survival (OS), cumulative incidence functions for breast-cancer-specific death (BCSD) and other causes-specific death (OCSD) by BCT and TM. The restricted mean survival time (RMST) difference and hazard ratio between the two arms were estimated. Given the estimated distributions, we simulated cause-specific death times from each arm, evaluating the power to test treatment …

Stereotactic Body Proton Therapy For Early Stage Non-Small Cell Lung Cancer – Technical Challenges And Solutions: The Md Anderson Experience, X Ronald Zhu, Yuting Li, Ming Yang, Thomas J Whitaker, Paige A Taylor, Xiaodong Zhang, Falk Poenisch, Narayan Sahoo, Zhongxing Liao, Joe Y Chang

Faculty, Staff and Student Publications

Our randomized clinical study comparing stereotactic body radiotherapy (SBRT) and stereotactic body proton therapy (SBPT) for early stage non-small cell lung cancer (NSCLC) was closed prematurely owing to poor enrollment, largely because of lack of volumetric imaging and difficulty in obtaining insurance coverage for the SBPT group. In this article, we describe technology improvements in our new proton therapy center, particularly in image guidance with cone beam CT (CBCT) and CT on rail (CTOR), as well as motion management with real-time gated proton therapy (RGPT) and optical surface imaging. In addition, we have a treatment planning system that provides better …

Characterization Of A Solid-State Detector For Dosimetry In The Diagnostic Energy Range With Verification Via Monte Carlo Estimation Of Average Breast Dose In Mammography, Areej Aljabal

Theses and Dissertations

This dissertation aims to develop a simplified QA metric for estimating radiation dose in mammography. This metric, the Mid-Breast Dose (MDB) Index, maybe be proposed as an alternative dose index, consistent with average glandular dose (AGD), for routine QA. MBD was obtained using “Phantom mid-point Air Kerma (AK) measurement” for conventional mammography. The advantage of this method is that MBD can be measured directly without requiring multiple conversion factors. The accuracy of clinical measurements in computing the MBD was assessed by comparing it with the AGD estimated by the Dance formalism experimentally and Monte Carlo simulation.

MBD methodology relies on …

Characterization And Investigation Of Cold Atmospheric Plasma And Its Effects On Cancer Cell Biology, Thomas M. Ritrosky

Theses and Dissertations

Modern cancer treatment uses radiation therapy in over 50% of patient cases. It is an e↵ective way of treating tumors because the mechanisms of cell killing are well known through the damage that ionizing radiation does to DNA. The amount of radiation can be tracked through measuring the dose of the clinical photon or electron beam used. However, there are limitations in the usage of radiation therapy, for example, a tumor can create hypoxic areas that become radioresistant leading to complete ine↵ectiveness of further radiation treatment. This project looks into the application of cold atmospheric plasma as an adjuvant therapy …

A Learning Health System For Radiation Oncology, Rishabh Kapoor

Theses and Dissertations

The proposed research aims to address the challenges faced by clinical data science researchers in radiation oncology accessing, integrating, and analyzing heterogeneous data from various sources. The research presents a scalable intelligent infrastructure, called the Health Information Gateway and Exchange (HINGE), which captures and structures data from multiple sources into a knowledge base with semantically interlinked entities. This infrastructure enables researchers to mine novel associations and gather relevant knowledge for personalized clinical outcomes.

The dissertation discusses the design framework and implementation of HINGE, which abstracts structured data from treatment planning systems, treatment management systems, and electronic health records. It utilizes …

Comparison Of Machine-Learning And Deep-Learning Methods For The Prediction Of Osteoradionecrosis Resulting From Head And Neck Cancer Radiation Therapy, Brandon Reber, Lisanne Van Dijk, Brian Anderson, Abdallah Sherif Radwan Mohamed, Clifton Fuller, Stephen Lai, Kristy Brock

Faculty, Staff and Student Publications

PURPOSE: Deep-learning (DL) techniques have been successful in disease-prediction tasks and could improve the prediction of mandible osteoradionecrosis (ORN) resulting from head and neck cancer (HNC) radiation therapy. In this study, we retrospectively compared the performance of DL algorithms and traditional machine-learning (ML) techniques to predict mandible ORN binary outcome in an extensive cohort of patients with HNC.

METHODS AND MATERIALS: Patients who received HNC radiation therapy at the University of Texas MD Anderson Cancer Center from 2005 to 2015 were identified for the ML (n = 1259) and DL (n = 1236) studies. The subjects were followed for ORN …

Multiomics Characterization Of Methicillin-Resistant Staphylococcus Aureus (Mrsa) Isolates With Heterogeneous Intermediate Resistance To Vancomycin (Hvisa) In Latin America, Betsy E Castro, Rafael Rios, Lina P Carvajal, Mónica L Vargas, Mónica P Cala, Lizeth León, Blake Hanson, An Q Dinh, Oscar Ortega-Recalde, Carlos Seas, Jose M Munita, Cesar A Arias, Sandra Rincon, Jinnethe Reyes, Lorena Diaz

Faculty, Staff and Student Publications

BACKGROUND: Heterogeneous vancomycin-intermediate Staphylococcus aureus (hVISA) compromise the clinical efficacy of vancomycin. The hVISA isolates spontaneously produce vancomycin-intermediate Staphylococcus aureus (VISA) cells generated by diverse and intriguing mechanisms.

OBJECTIVE: To characterize the biomolecular profile of clinical hVISA applying genomic, transcriptomic and metabolomic approaches.

METHODS: 39 hVISA and 305 VSSA and their genomes were included. Core genome-based Bayesian phylogenetic reconstructions were built and alterations in predicted proteins in VISA/hVISA were interrogated. Linear discriminant analysis and a Genome-Wide Association Study were performed. Differentially expressed genes were identified in hVISA-VSSA by RNA-sequencing. The undirected profiles of metabolites were determined by liquid chromatography and …

Using Patient Flow Analysis With Real-Time Patient Tracking To Optimize Radiation Oncology Consultation Visits, Shane Mesko, Julius Weng, Prajnan Das, Albert C Koong, Joseph M Herman, Dorothy Elrod-Joplin, Ashley Kerr, Thomas Aloia, John Frenzel, Katy E French, Wendi Martinez, Iris Recinos, Abdulaziz Alshaikh, Utpala Daftary, Amy C Moreno, Quynh-Nhu Nguyen

Faculty, Staff and Student Publications

PURPOSE: Clinical efficiency is a key component of the value-based care model and a driver of patient satisfaction. The purpose of this study was to identify and address inefficiencies at a high-volume radiation oncology clinic.

METHODS AND MATERIALS: Patient flow analysis (PFA) was used to create process maps and optimize the workflow of consultation visits in a gastrointestinal radiation oncology clinic at a large academic cancer center. Metrics such as cycle times, waiting times, and rooming times were assessed by using a real-time patient status function in the electronic medical record for 556 consults and compared between before vs after …

Federated Learning Enables Big Data For Rare Cancer Boundary Detection, Sarthak Pati, Ujjwal Baid, Brandon Edwards, Micah Sheller, Shih-Han Wang, G. Anthony Reina, Patrick Foley, Alexey Gruzdev, Deepthi Karkada, Christos Davatzikos, Chiharu Sako, Satyam Ghodasara, Michel Bilello, Suyash Mohan, Philipp Vollmuth, Gianluca Brugnara, Chandrakanth J. Preetha, Felix Sahm, Klaus Maier-Hein, Maximilian Zenk, Martin Bendszus, Wolfgang Wick, Evan Calabrese, Jeffrey Rudie, Javier Villanueva-Meyer, Soonmee Cha, Madhura Ingalhalikar, Manali Jadhav, Umang Pandey, Jitender Saini, John Garrett, Matthew Larson, Robert Jeraj, Stuart Currie, Russell Frood, Kavi Fatania, Raymond Y. Huang, Ken Chang, Carmen Balaña, Jaume Capellades, Josep Puig, Johannes Trenkler, Josef Pichler, Georg Necker, Andreas Haunschmidt, Stephan Meckel, Gaurav Shukla, Spencer Liem, Gregory S Alexander, Joseph Lombardo, Joshua D. Palmer, Adam E. Flanders, Adam P. Dicker, Haris I. Sair, Craig K. Jones, Archana Venkataraman, Meirui Jiang, Tiffany Y. So, Cheng Chen, Pheng Ann Heng, Qi Dou, Michal Kozubek, Filip Lux, Jan Michálek, Petr Matula, Miloš Keřkovský, Tereza Kopřivová, Marek Dostál, Václav Vybíhal, Michael A. Vogelbaum, J. Ross Mitchell, Joaquim Farinhas, Joseph A. Maldjian, Chandan Ganesh Bangalore Yogananda, Marco C. Pinho, Divya Reddy, James Holcomb, Benjamin C. Wagner, Benjamin M. Ellingson, Timothy F. Cloughesy, Catalina Raymond, Talia Oughourlian, Akifumi Hagiwara, Chencai Wang, Minh-Son To, Sargam Bhardwaj, Chee Chong, Marc Agzarian, Alexandre Xavier Falcão, Samuel B. Martins, Bernardo C. A. Teixeira, Flávia Sprenger, David Menotti, Diego R. Lucio, Pamela Lamontagne, Daniel Marcus, Benedikt Wiestler, Florian Kofler, Ivan Ezhov, Marie Metz, Rajan Jain, Matthew Lee, Yvonne W. Lui, Richard Mckinley, Johannes Slotboom, Piotr Radojewski, Raphael Meier, Roland Wiest, Derrick Murcia, Eric Fu, Rourke Haas, John Thompson, David Ryan Ormond, Chaitra Badve, Andrew E. Sloan, Vachan Vadmal, Kristin Waite, Rivka R. Colen, Linmin Pei, Murat Ak, Ashok Srinivasan, J. Rajiv Bapuraj, Arvind Rao, Nicholas Wang, Ota Yoshiaki, Toshio Moritani, Sevcan Turk, Joonsang Lee, Snehal Prabhudesai, Fanny Morón, Jacob Mandel, Konstantinos Kamnitsas, Ben Glocker, Luke V. M. Dixon, Matthew Williams, Peter Zampakis, Vasileios Panagiotopoulos, Panagiotis Tsiganos, Sotiris Alexiou, Ilias Haliassos, Evangelia I Zacharaki, Konstantinos Moustakas, Christina Kalogeropoulou, Dimitrios M. Kardamakis, Yoon Seong Choi, Seung-Koo Lee, Jong Hee Chang, Sung Soo Ahn, Bing Luo, Laila Poisson, Ning Wen, Pallavi Tiwari, Ruchika Verma, Rohan Bareja, Ipsa Yadav, Jonathan Chen, Neeraj Kumar, Marion Smits, Sebastian R. Van Der Voort, Ahmed Alafandi, Fatih Incekara, Maarten M. J. Wijnenga, Georgios Kapsas, Renske Gahrmann, Joost W Schouten, Hendrikus J. Dubbink, Arnaud J. P. E. Vincent, Martin J. Van Den Bent, Pim J. French, Stefan Klein, Yading Yuan, Sonam Sharma, Tzu-Chi Tseng, Saba Adabi, Simone P. Niclou, Olivier Keunen, Ann-Christin Hau, Martin Vallières, David Fortin, Martin Lepage, Bennett Landman, Karthik Ramadass, Kaiwen Xu, Silky Chotai, Lola B. Chambless, Akshitkumar Mistry, Reid C. Thompson, Yuriy Gusev, Krithika Bhuvaneshwar, Anousheh Sayah, Camelia Bencheqroun, Anas Belouali, Subha Madhavan, Thomas C. Booth, Alysha Chelliah, Marc Modat, Haris Shuaib, Carmen Dragos, Aly Abayazeed, Kenneth Kolodziej, Michael Hill, Ahmed Abbassy, Shady Gamal, Mahmoud Mekhaimar, Mohamed Qayati, Mauricio Reyes, Ji Eun Park, Jihye Yun, Ho Sung Kim, Abhishek Mahajan, Mark Muzi, Sean Benson, Regina G. H. Beets-Tan, Jonas Teuwen, Alejandro Herrera-Trujillo, Maria Trujillo, William Escobar, Ana Abello, Jose Bernal, Jhon Gómez, Joseph Choi, Stephen Baek, Yusung Kim, Heba Ismael, Bryan Allen, John M. Buatti, Aikaterini Kotrotsou, Hongwei Li, Tobias Weiss, Michael Weller, Andrea Bink, Bertrand Pouymayou, Hassan F. Shaykh, Joel Saltz, Prateek Prasanna, Sampurna Shrestha, Kartik M. Mani, David Payne, Tahsin Kurc, Enrique Pelaez, Heydy Franco-Maldonado, Francis Loayza, Sebastian Quevedo, Pamela Guevara, Esteban Torche, Cristobal Mendoza, Franco Vera, Elvis Ríos, Eduardo López, Sergio A. Velastin, Godwin Ogbole, Mayowa Soneye, Dotun Oyekunle, Olubunmi Odafe-Oyibotha, Babatunde Osobu, Mustapha Shu'aibu, Adeleye Dorcas, Farouk Dako, Amber L. Simpson, Mohammad Hamghalam, Jacob J. Peoples, Ricky Hu, Anh Tran, Danielle Cutler, Fabio Y. Moraes, Michael A. Boss, James Gimpel, Deepak Kattil Veettil, Kendall Schmidt, Brian Bialecki, Sailaja Marella, Cynthia Price, Lisa Cimino, Charles Apgar, Prashant Shah, Bjoern Menze, Jill S. Barnholtz-Sloan, Jason Martin, Spyridon Bakas

Department of Radiation Oncology Faculty Papers

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically …

Quantifying The Magnitude Of To Tal Dose Deviation Caused By Various Sources Of Error Among Iroc Phantom Irradiation Results, Sharbacha S. Edward

Dissertations and Theses (Open Access)

The Imaging and Radiation Oncology Core (IROC) phantoms are used as an end-to-end test of an institution’s radiotherapy processes, and for clinical trial credentialing. Phantoms are treated like patients, and evaluation of the doses received by the thermoluminescent dosimeters (TLDs) inside the phantom, reflects the accuracy with which an institution can image, plan and irradiate a phantom or patient. Recent phantom results show that among the hundreds of various IROC phantoms irradiated annually, 8-17% of institutions fail this test. The purpose of this work was to investigate the various types of errors that may occur during the treatment process and …

Infrastructure Development For Personalized Risk Prediction To Reduce Cardiovascular Disease In Childhood Cancer Survivors, Suman Shrestha

Dissertations and Theses (Open Access)

Although childhood cancer survivors have lengthy life expectancies, they run the risk of experiencing long-term health issues as a result of their treatment. The most frequent non-cancerous cause of morbidity and mortality for these survivors is cardiac disease. Radiation therapy (RT) has been linked in numerous cohort studies to a higher chance of developing a late cardiac disease in these survivors, and this risk rises with higher mean heart doses and increased RT exposure to larger cardiac volumes. Since, the heart is a heterogeneous organ made up of several distinct substructures, RT dose received by the entire heart does not …

High Local Control And Low Ocular Toxicity Using Ultra-Low-Dose “Boom-Boom” Radiotherapy For Indolent Orbital Lymphoma, Sanjna Shelukar, Christian Fernandez, Zeynep Bas, Lydia Komarnicky, Sara E. Lally, Carol L Shields, Adam Binder, Pierluigi Porcu, Onder Alpdogan, Ubaldo Martinez-Outschoorn, Wenyin Shi

Department of Medical Oncology Faculty Papers

Background: The first line definitive treatment for early-stage indolent B-cell lymphoma is radiation therapy (RT). Due to the sensitivity of orbital structures to radiation, ultra-low-dose RT (4 Gy in 2 fractions, "boom-boom") has and been utilized as an attractive option for orbital lymphoma. In this retrospective study, we evaluated the outcome and toxicity of "boom-boom" RT for indolent orbital lymphoma with an emphasis on ophthalmologic toxicity.

Methods: This is a retrospective case series with 17 patients with orbital lymphoma who received boom-boom RT at a single tertiary referral center between January 2017 and June 2022. Medical records, imaging and radiation …

Quantitative Apparent Diffusion Coefficients From Peritumoral Regions As Early Predictors Of Response To Neoadjuvant Systemic Therapy In Triple-Negative Breast Cancer, Benjamin C Musall, Beatriz E Adrada, Rosalind P Candelaria, Rania M M Mohamed, Abeer H Abdelhafez, Jong Bum Son, Jia Sun, Lumarie Santiago, Gary J Whitman, Tanya W Moseley, Marion E Scoggins, Hagar S Mahmoud, Jason B White, Ken-Pin Hwang, Nabil A Elshafeey, Medine Boge, Shu Zhang, Jennifer K Litton, Vicente Valero, Debu Tripathy, Alastair M Thompson, Clinton Yam, Peng Wei, Stacy L Moulder, Mark D Pagel, Wei T Yang, Jingfei Ma, Gaiane M Rauch

Faculty, Staff and Student Publications

BACKGROUND: Pathologic complete response (pCR) to neoadjuvant systemic therapy (NAST) in triple-negative breast cancer (TNBC) is a strong predictor of patient survival. Edema in the peritumoral region (PTR) has been reported to be a negative prognostic factor in TNBC.

PURPOSE: To determine whether quantitative apparent diffusion coefficient (ADC) features from PTRs on reduced field-of-view (rFOV) diffusion-weighted imaging (DWI) predict the response to NAST in TNBC.

STUDY TYPE: Prospective.

POPULATION/SUBJECTS: A total of 108 patients with biopsy-proven TNBC who underwent NAST and definitive surgery during 2015-2020.

FIELD STRENGTH/SEQUENCE: A 3.0 T/rFOV single-shot diffusion-weighted echo-planar imaging sequence (DWI).

ASSESSMENT: Three scans were …

Spinal Metastases And The Evolving Role Of Molecular Targeted Therapy, Chemotherapy, And Immunotherapy, Elena I Fomchenko, James C Bayley, Christopher Alvarez-Breckenridge, Laurence D Rhines, Claudio E Tatsui

Faculty, Staff and Student Publications

Metastatic involvement of the spine is a common complication of systemic cancer progression. Surgery and external beam radiotherapy are palliative treatment modalities aiming to preserve neurological function, control pain and maintain functional status. More recently, with development of image guidance and stereotactic delivery of high doses of conformal radiation, local tumor control has improved; however recurrent or radiation refractory disease remains a significant clinical problem with limited treatment options. This manuscript represents a narrative overview of novel targeted molecular therapies, chemotherapies, and immunotherapy treatments for patients with breast, lung, melanoma, renal cell, prostate, and thyroid cancers, which resulted in improved …

Expansion Of The Detrusor Muscular Ring Surrounding The Bladder Neck On Mri: Moving Beyond The Prostate As An Etiology Of Lower Urinary Tract Symptoms Due To Benign Prostatic Hyperplasia, Kiran Nandalur, David Walker, Hong Ye, Sayf A. Al-Katib, Brian Seifman, David Gangwish, Abhay Dhaliwal, Connor Ervin, Kayla Dobies, Channing Sesoko, Sirisha Nandalur, Bernadette Zwaans, Jennifer Nguyen, Jason Hafron

Conference Presentation Abstracts

Purpose: The etiology of lower urinary tract symptoms secondary to benign prostatic hyperplasia (LUTS/BPH) remains uncertain. The purpose of our study was to quantitatively analyze pelvic anatomic characteristics on magnetic resonance imaging (MRI) to assess for independent factors for symptoms.
*Methods and Materials: This retrospective single-institution study evaluated treatment-naïve men who underwent prostate MRI within 3 months of International Prostate Symptom Score (IPSS) from June 2021 to February 2022. Factors measured on MRI included: detrusor muscular ring surrounding the bladder neck measured as area and alternatively diameter, central gland (CG) mean apparent diffusion coefficient (ADC), levator hiatus (LH) volume, intrapelvic …

Characterizing Pulmonary Function Test Changes For Patients With Lung Cancer Treated On A 2-Institution, 4-Dimensional Computed Tomography-Ventilation Functional Avoidance Prospective Clinical Trial, Ryan C. Miller, Richard Castillo, Edward Castillo, Bernard L Jones, Moyed Miften, Brian Kavanagh, Bo Lu, Maria Werner-Wasik, Nader Ghassemi, Joseph Lombardo, Julie Barta, Inga Grills, Chad G Rusthoven, Thomas Guerrero, Yevgeniy Vinogradskiy

Department of Radiation Oncology Faculty Papers

Purpose: Four-dimensional computed tomography (4DCT)-ventilation-based functional avoidance uses 4DCT images to generate plans that avoid functional regions of the lung with the goal of reducing pulmonary toxic effects. A phase 2, multicenter, prospective study was completed to evaluate 4DCT-ventilation functional avoidance radiation therapy. The purpose of this study was to report the results for pretreatment to posttreatment pulmonary function test (PFT) changes for patients treated with functional avoidance radiation therapy.

Methods and materials: Patients with locally advanced lung cancer receiving chemoradiation were accrued. Functional avoidance plans based on 4DCT-ventilation images were generated. PFTs were obtained at baseline and 3 months …

Multi-Organ Segmentation Of Abdominal Structures From Non-Contrast And Contrast Enhanced Ct Images, Cenji Yu, Chidinma P Anakwenze, Yao Zhao, Rachael M Martin, Ethan B Ludmir, Joshua S Niedzielski, Asad Qureshi, Prajnan Das, Emma B Holliday, Ann C Raldow, Callistus M Nguyen, Raymond P Mumme, Tucker J Netherton, Dong Joo Rhee, Skylar S Gay, Jinzhong Yang, Laurence E Court, Carlos E Cardenas

Faculty, Staff and Student Publications

Manually delineating upper abdominal organs at risk (OARs) is a time-consuming task. To develop a deep-learning-based tool for accurate and robust auto-segmentation of these OARs, forty pancreatic cancer patients with contrast-enhanced breath-hold computed tomographic (CT) images were selected. We trained a three-dimensional (3D) U-Net ensemble that automatically segments all organ contours concurrently with the self-configuring nnU-Net framework. Our tool's performance was assessed on a held-out test set of 30 patients quantitatively. Five radiation oncologists from three different institutions assessed the performance of the tool using a 5-point Likert scale on an additional 75 randomly selected test patients. The mean (± …