Authors: Ryan Andosca, Rojine T. Ariani, Peter Boyle, Minji Victoria Kim, Michael Vincent Lauria, Daniel A. Low, Claudia R. Miller, Drew Moghanaki, Louise Naumann, Dylan P. O'Connell, Ricky R Savjani
Affiliation: Department of Radiation Oncology, University of California, Los Angeles, University of California, Los Angeles, UCLA Radiation Oncology
Abstract Preview: Purpose: To demonstrate that 5DCT can provide an accurate internal tumor volume (ITV) while 4DCT cannot.
Methods: The 5DCT imaging protocol uses a motion model and 25 deformably registered free-bre...
Authors: Steven DiBiase, Gurtej S. Gill, Haohua Billy Huang, Nicholas J. Lavini, Luxshan Shanmugarajah, Salar Souri, Samantha Wong
Affiliation: Stony Brook University, Northwell Health, Cornell University, NewYork-Presbyterian, New York-Presbyterian
Abstract Preview: Purpose: Clinical applications of deep learning-based algorithms have come to the radiation oncology field as organ at risk (OAR) auto contouring programs. We evaluated two of these algorithmsā (Radfo...
Authors: Theodore Higgins Arsenault, Kenneth W. Gregg, Beatriz Guevara, Lauren E Henke, Angela Jia, Rojano Kashani, Kyle O'Carroll, Alex T. Price, Adithya Reddy, Atefeh Rezaei, Daniel E Spratt, Runyon C. Woods
Affiliation: University Hospitals Seidman Cancer Center
Abstract Preview: Purpose: To evaluate the effect of unedited AI-generated contours used for online adaptive radiotherapy (FLOW-ART) on the plan quality of prostate treatments as compared to non-adaptive (non-ART) proc...
Authors: Mubasheer Chombakkadath, Tara E. Tyson, Iris Z. Wang
Affiliation: Roswell Park Comprehensive Cancer Center, University at Buffalo (SUNY)
Abstract Preview: Purpose: Deformable image registration (DIR) is critical in adaptive radiation therapy (ART). Existing DIR phantoms either simulate tumor shape or volume changes but lack comprehensive motion simulati...
Authors: Jiayi Chen, Manju Liu, Ning Wen, Haoran Zhang, Yibin Zhang
Affiliation: Department of Radiation Oncology, Ruijin Hospital, Department of Radiology, Ruijin Hospital Shanghai Jiaotong University School of Medicine, Duke Kunshan University, Department of Radiation Oncology,Ruijin Hospital, Shanghai Jiao Tong University School of Medicine
Abstract Preview: Purpose: This study introduces a novel Dual Energy CT (DECT)-Guided Intelligent Radiation Therapy (DEIT) platform designed to streamline and optimize the radiotherapy process. The DEIT system combines...
Authors: Wenfeng He, Tian Liu, Pretesh Patel, Richard L.J. Qiu, Keyur Shah, Tonghe Wang, Xiaofeng Yang, Chulong Zhang
Affiliation: Icahn School of Medicine at Mount Sinai, Emory University, Medical Physics Graduate Program, Duke Kunshan University, Memorial Sloan Kettering Cancer Center, Department of Radiation Oncology and Winship Cancer Institute, Emory University
Abstract Preview: Purpose: This study introduces a tracking-free approach to reconstruct 3D ultrasound (US) volumes from 2D freehand US scans. By eliminating the reliance on external tracking systems, this method aims ...
Authors: Beth M. Beadle, Adrian Celaya, Laurence Edward Court, David Fuentes, Anna Lee, Tze Yee Lim, Dragan Mirkovic, Amy Moreno, Raymond Mumme, Tucker J. Netherton, Callistus M. Nguyen, Jaganathan A Parameshwaran, Jack Phan, Carlos Sjogreen, Sara L. Thrower, Congjun Wang, He C. Wang, Xin Wang
Affiliation: Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center; The University of Texas MD Anderson Cancer Center UTHealth Houston Graduate School of Biomedical Sciences, Department of Radiation Oncology, Stanford University, The University of Texas MD Anderson Cancer Center, MD Anderson Cancer Center, MD Anderson, Rice University, Department of Radiation Physics, The University of Texas MD Anderson Cancer Center
Abstract Preview: Purpose: Quality assurance of target volumes from radiotherapy clinical trials is a labor and resource intensive task. The purpose of this work is to quantify the accuracy of a tool that automatically...
Authors: Shari Damast, Svetlana Kuznetsova, Christopher J. Tien
Affiliation: Yale University School of Medicine, Department of Therapeutic Radiology, Yale University School of Medicine
Abstract Preview: Purpose: Current contour similarity evaluation approaches (Dice Similarity Coefficient, Mean Distance to Agreement) are limited to geometric agreement without assessment of ultimate dosimetric impact....
Authors: Weiguo Lu, Hua-Chieh Shao, Guoping Xu, You Zhang
Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, Medical Artificial Intelligence and Automation (MAIA) Laboratory, Department of Radiation Oncology, UT Southwestern Medical Center
Abstract Preview: Purpose:
Neural network-based lesion segmentation remains a significant challenge due to the low contrast between lesions and surrounding tissues (high ambiguity) and the variability of lesion shap...
Authors: Asma Amjad, Renae Conlin, Beth A. Erickson, William Hall, Eric S. Paulson, Christina M. Sarosiek
Affiliation: Department of Radiation Oncology, Medical College of Wisconsin
Abstract Preview: Purpose: The adapt-to-shape (ATS) workflow on the MR-Linac involves manual contour edits followed by treatment plan reoptimization on daily pre-beam MRIs. A verification image is acquired after plan o...
Authors: Penghao Gao, Zejun Jiang
Affiliation: Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Artificial Intelligence Laboratory, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences
Abstract Preview: Purpose: Real-time tumor tracking can effectively compensate for the impact of respiratory motion on dose distribution. We propose a patient-specific external-internal correlation model driven by opti...
Authors: Indrin J. Chetty, Jing Cui, Mitchell Kamrava, Tiffany M. Phillips, Jennifer M. Steers, Brad Stiehl
Affiliation: Department of Radiation Oncology,Cedars-Sinai Medical Center, Cedars-Sinai Medical Center
Abstract Preview: Purpose: Auto-contouring for HDR interstitial brachytherapy can be confounded by large deformation in anatomy and image quality. Here we evaluated the performance of an AI-based auto-contouring softwa...
Authors: Robert K Chin, Klea Hoxha, Erika Jank, Jesus Juarez, Eulanca Yuka Liu, Dylan P. O'Connell, X. Sharon Qi, Ricky R Savjani
Affiliation: Department of Radiation Oncology, University of California, Los Angeles, University of California, Los Angeles, UCLA Radiation Oncology
Abstract Preview: Purpose:
Daily cone beam CT (CBCT) images are acquired prior to each radiotherapy treatment for verifying patient positioning. HyperSight is an advanced imaging solution that replaces standard CBCT...
Authors: Shae Gans, Carri K. Glide-Hurst, Mark Pankuch, Chase Ruff, Niek Schreuder, Nicholas R. Summerfield, Yuhao Yan
Affiliation: Departments of Human Oncology and Medical Physics, University of Wisconsin-Madison, Northwestern Medicine Proton Center, Northwestern Medicine Chicago Proton Center, Leo Cancer Care
Abstract Preview: Purpose: Novel upright patient positioners coupled with diagnostic-quality vertical CT at treatment isocenter introduce a significant opportunity for improved image-guided particle therapy. Treating p...
Authors: Cem Altunbas, Farhang Bayat, Roy Bliley, Rupesh Dotel, Brian Kavanagh, Uttam Pyakurel, Tyler Robin, Ryan Sabounchi
Affiliation: Department of Radiation Oncology, University of Colorado School of Medicine, Taussig Cancer Center, Cleveland Clinic, University of Colorado Anschutz Medical Campus
Abstract Preview: Purpose: Automatic segmentation of anatomical structures in CBCT images is key to enabling dose delivery monitoring and online plan modifications in radiotherapy. However, poor image quality can degra...
Authors: Silambarasan Anbumani, Nicolette O'Connell, Eenas A. Omari, Amanda Pan, Eric S. Paulson, Lindsay Puckett, Monica E. Shukla, Dan Thill, Jiaofeng Xu
Affiliation: Elekta Inc, Elekta Limited, Linac House, Department of Radiation Oncology, Medical College of Wisconsin
Abstract Preview: Purpose: Accurate electron density information from on-board imaging is essential for direct dose calculations in adaptive radiotherapy (ART). This study evaluates a deep learning model for thoracic s...
Authors: Jingyun Chen, Yading Yuan
Affiliation: Columbia University Irving Medical Center, Department of Radiation Oncology
Abstract Preview: Purpose: To develop and evaluate the Scale-attention network (SANet) for automated pancreas segmentation on MR images.
Methods: To develop SANet, we extended the classic U-Net design with a dynamic...
Authors: Phillip Cuculich, Geoffrey D. Hugo, Xiwen Li, Michael T. Prusator, Clifford Robinson, Pamela Samson, Xue Wu
Affiliation: Washington University School of Medicine in St Louis, Washington University School of Medicine in St. Louis, University of Utah, WashU Medicine
Abstract Preview: Purpose: Stereotactic arrhythmia radiotherapy (STAR) requires compensation for both respiratory and cardiac motions of the heart. Respiratory 4DCT scans implicitly include cardiac motion and cycle-to-...
Authors: Mylinh Dang, Laila A Gharzai, Xinlei Mi, Poonam Yadav
Affiliation: Northwestern Feinberg School of Medicine, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, Northwestern Medicine
Abstract Preview: Purpose: Delineation of organs at risk (OAR) in the head/neck region requires substantial physician time. Many artificial intelligence (AI) based auto-contouring software are commercially available. T...
Authors: Mehdi Amini, Minerva Becker, Simina Chiriac, Alexandre Cusin, Dimitrios Daskalou, Ghasem Hajianfar, Sophie Neveu, Marcella Pucci, Yazdan Salimi, Pascal Senn, Habib Zaidi
Affiliation: Geneva University Hospital, Division of Radiology, Diagnostic Department, Geneva University Hospitals, Service of Otorhinolaryngology-Head and Neck Surgery, Department of Clinical Neurosciences, Geneva University Hospitals
Abstract Preview: Purpose: Personalized prediction of vestibular schwannoma (VS) tumour growth is crucial for guiding patient management decisions toward observation versus intervention. This study proposes an automate...
Authors: Austin Castelo, Xinru Chen, Caroline Chung, Laurence Edward Court, Jaganathan A Parameshwaran, Zhan Xu, Jinzhong Yang, Yao Zhao
Affiliation: The University of Texas MD Anderson Cancer Center, Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Department of Imaging Physics, The University of Texas MD Anderson Cancer Center
Abstract Preview: Purpose:
To develop a deep learning-based segmentation model to automatically delineate tumors from full-body PET/CT images.
Methods:
PET/CT image pairs of 91 patients were collected for this...
Authors: Majd Antaki, Rohini Bhatia, Gayoung Kim, Yosef Landman, Junghoon Lee, Akila N. Viswanathan
Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Physics and Advanced Development Elekta
Abstract Preview: Purpose: Brachytherapy is a standard radiation therapy approach for cervical cancer, which directly delivers radiation source to the tumor using catheters. Treatment planning requires identification o...
Authors: Debarghya China, Junghoon Lee, Ali Uneri
Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Department of Biomedical Engineering, Johns Hopkins University, Johns Hopkins Univ
Abstract Preview: Purpose: This study aims to develop a population-based cardio-respiratory motion model and apply it to patient-specific 3D CTA to simulate 4D CTA and 2D+t fluoroscopy sequences. The developed motion m...
Authors: Xianjin Dai, PhD, Zhuoran Jiang, Lei Ren, Lei Xing, Zhendong Zhang
Affiliation: University of Maryland School of Medicine, Department of Radiation Oncology, Stanford University, Duke University, Stanford University
Abstract Preview: Purpose: Unsupervised deep learning has shown great promise in deformable image registration (DIR). These methods update model weights to optimize image similarity without necessitating ground truth d...
Authors: Kristen A. Duke, Samer Jabor, Neil A. Kirby, Parker New, Niko Papanikolaou, Arkajyoti Roy, Yuqing Xia
Affiliation: St. Mary's University, The University of Texas San Antonio, UT Health San Antonio
Abstract Preview: Purpose:
The Segment Anything Model (SAM) is a foundational box-prompt-based model for natural image segmentation. However, its applicability to zero-shot 3D medical image segmentation, particularl...
Authors: Sahaja Acharya, Matthew Ladra, Junghoon Lee, Lina Mekki
Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Department of Biomedical Engineering, Johns Hopkins University
Abstract Preview: Purpose: Multi-parametric MRI (mpMRI) is widely used for deep learning (DL)-based automatic segmentation of brain tumors. While multi-contrast images concatenated as channels are typically input to ne...
Authors: Alexander Choi, William Ross Green, Christine Hill-Kayser, Gary D. Kao, Michael LaRiviere, Rafe A. McBeth, Steven Philbrook
Affiliation: Department of Radiation Oncology, University of Pennsylvania
Abstract Preview: Purpose: To validate the potential of clinical deployment of an in-house AI-driven auto-segmentation tool for pediatric craniospinal irradiation (CSI) in proton therapy, with goals of reducing manual ...
Authors: Aditya P. Apte, Joseph O. Deasy, Jue Jiang, Nancy Lee, Sudharsan Madhavan, Nishant Nadkarni, Lopamudra Nayak, Harini Veeraraghavan, Wei Zhao
Affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Memorial Sloan Kettering Cancer Center
Abstract Preview: Purpose: To track early response to radiotherapy using digital twins, it is crucial to quantify tumor volume and mass changes. Traditional tumor detection methods, particularly in image registration, ...
Authors: Jingyun Chen, Yading Yuan
Affiliation: Columbia University Irving Medical Center, Department of Radiation Oncology
Abstract Preview: Purpose: To evaluate centralized and decentralized strategies for federated head and neck tumor segmentation on PET/CT.
Methods: We utilized training data from the HEad and neCK TumOR segmentation ...
Authors: Zhaoyang Fan, Eric Nguyen, Dan Ruan, Jiayu Xiao
Affiliation: Department of Radiation Oncology, University of California, Los Angeles, Department of Radiology, University of Southern California, University of Southern California
Abstract Preview: Purpose: MR vessel wall imaging (VWI) has been shown to be effective for evaluating intracranial atherosclerosis disease. However, VWI typically also requires an MR angiography (MRA) in the same imagi...
Authors: Kota Hirose, Daisuke Kawahara, Jokichi Kawazoe, Yuji Murakami
Affiliation: Department of Radiation Oncology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Graduate School of Biomedical and Health Sciences, Hiroshima University
Abstract Preview: Purpose: Synthesizing medical images can address the lack of or unscanned medical images, reducing scanner time and costs. However, paired image scarcity remains a challenge for image synthesis. We pr...
Authors: Xu Chen, Jun Lian, Yunkui Pang, Pew-Thian Yap
Affiliation: University of North Carolina at Chapel Hill, Huaqiao University
Abstract Preview: Purpose: Unsupervised CBCT-to-CT translation in the pelvic region is essential for accurate radiotherapy delivery and adaptive image-guided interventions. However, current models for cross-modality tr...
Authors: Derek Tang, Susu Yan
Affiliation: Massachusetts General Hospital
Abstract Preview: Purpose: To evaluate the performance of a multi-task automated-segmentation and synthetic CT generation model (sCT) and investigate its application in an adaptive proton therapy workflow.
Methods: ...
Authors: Gayoung Kim, Junghoon Lee
Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University
Abstract Preview: Purpose: 3D time-of-flight magnetic resonance angiography (TOF-MRA) is widely used for visualizing cerebrovascular structures. Accurate segmentation of cerebrovascular structures is critical for relia...
Authors: Laila A Gharzai, Bharat B Mittal, Poonam Yadav
Affiliation: Northwestern Feinberg School of Medicine, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, Northwestern University Feinberg School of Medicine
Abstract Preview: Purpose: Multiple studies have shown the increasing role of deep learning in segmenting regions of interest. This work presents the feasibility of auto-segmenting the critical structures for head and ...
Authors: Benjamin Haibe-Kains, Ruiyan Ni, Alexandra Rink
Affiliation: Department of Medical Biophysics, University of Toronto, University Health Network
Abstract Preview: Purpose: Accurate auto-segmentation for targets and organs-at-risk (OARs) using deep learning reduces the delineating time in radiotherapy. In high-dose-rate brachytherapy, specific clinical criteria ...
Authors: Chih-Wei Chang, Runyu Jiang, Mark Korpics, Yuan Shao, Aranee Sivananthan, Zhen Tian, Ralph Weichselbaum, Xiaofeng Yang, Aubrey Zhang, Xiaoman Zhang
Affiliation: Department of Radiation & Cellular Oncology, University of Chicago, University of Chicago, Department of Physics, University of Chicago, Emory University, Department of Radiation Oncology and Winship Cancer Institute, Emory University, School of Public Health, University of Illinois Chicago
Abstract Preview: Purpose: Gamma Knife (GK) plan quality can vary significantly among planners, even for cases handled by the same planner. Although plan quality metrics such as coverage, selectivity, and gradient inde...
Authors: Sang Hee Ahn, Nalee Kim, Do Hoon Lim
Affiliation: Samsung Medical Center, Department of Radiation Oncology, Samsung Medical Center, Sungkyunkwan University School of Medicine
Abstract Preview: Purpose: MRI offers superior soft-tissue contrast, aiding tumor localization and segmentation in radiation therapy, which traditionally relies on oncologists' expertise. This study compares CNN-based ...
Authors: Gregory T. Armstrong, James E. Bates, Kristy K. Brock, Laurence Edward Court, Matt Ehrhardt, Danielle Friedman, Aashish C. Gupta, Donald Hancock, Rebecca M. Howell, Cindy Im, Tera S Jones, Choonsik Lee, Wendy Leisenring, Taylor Meyers, Lindsay Morton, Chaya Moskowitz, Joe Neglia, Vikki Nolan, Caleb O'Connor, Kevin C. Oeffinger, Constance A. Owens, Arnold C. Paulino, Chelsea C. Pinnix, Sander Roberti, Cecile Ronckers, Susan A. Smith, Kumar Srivastava, Lucie Turcotte
Affiliation: Department of Medicine, Duke University School of Medicine, Department of Epidemiology and Cancer Control, St. Jude Childrenās Research Hospital, The University of Texas MD Anderson Cancer Center, Department of Oncology, St. Jude Childrenās Research Hospital, Department of Pediatrics, Memorial Sloan Kettering Cancer Center, Division of Pediatric Epidemiology and Clinical Research, University of Minnesota, Division of Childhood Cancer Epidemiology, University Medicine at Johannes Gutenberg University Mainz, Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Department of Pediatrics, University of Minnesota, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Department of Biostatistics, St. Jude Childrenās Research Hospital, Clinical Research Division, Fred Hutchinson Cancer Center, Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Department of Radiation Oncology and Winship Cancer Institute, Emory University, The University of Texas MD Anderson Cancer Center UTHealth Houston Graduate School of Biomedical Sciences
Abstract Preview: Purpose: To (1) develop and validate a novel anatomically realistic pediatric/adolescent population-based breast model, (2) incorporate model into an age-scalable female reference phantom, and (3) dem...
Authors: Henry Szu-Meng Chen, Mu-Lan Jen, Vinodh A. Kumar, Ho-Ling Anthony Liu, Jian Ming Teo
Affiliation: School of Medicine, University of Colorado Denver, Department of Neuroradiology, The University of Texas MD Anderson Cancer Center, Department of Imaging Physics, The University of Texas MD Anderson Cancer Center
Abstract Preview: Purpose: Resting-state (rs-) fMRI detects functional networks by measuring synchronization of low-frequency oscillations in blood-oxygenation-level-dependent (BOLD) signals between brain regions. Stan...
Authors: Penghao Gao, Zejun Jiang, Huazhong Shu, Linlin Wang, Gongsen Zhang, Jian Zhu
Affiliation: Laboratory of Image Science and Technology, Key Laboratory of Computer Network and Information Integration, Southeast University, Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Artificial Intelligence Laboratory, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences
Abstract Preview: Purpose: We propose a cascading framework for time-varying anatomical volumetric reconstruction and tumor-tracking, guided by onboard orthogonal-view X-ray projections.
Methods: We employe multiple...
Authors: Gregory T. Armstrong, James E. Bates, Christine V. Chung, Lei Dong, Ralph Ermoian, Jie Fu, Christine Hill-Kayser, Rebecca M. Howell, Meena S. Khan, Sharareh Koufigar, John T. Lucas, Thomas E. Merchant, Taylor Meyers, Tucker J. Netherton, Constance A. Owens, Arnold C. Paulino, Sogand Sadeghi
Affiliation: Department of Radiation Oncology, University of Washington and Fred Hutchinson Cancer Center, Department of Epidemiology and Cancer Control, St. Jude Childrenās Research Hospital, St. Jude Children's Research Hospital, Department of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, Department of Radiation Oncology, St. Jude Childrenās Research Hospital, Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Department of Radiation Oncology, University of Washington/ Fred Hutchinson Cancer Center, Department of Radiation Oncology, University of Pennsylvania, University of Pennsylvania, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Department of Radiation Oncology and Winship Cancer Institute, Emory University, The University of Texas MD Anderson Cancer Center UTHealth Houston Graduate School of Biomedical Sciences
Abstract Preview: Purpose: Clinical workflows often rely on auto-segmentation tools trained on adult data, which may exhibit suboptimal performance in pediatric imaging due to inherent anatomical variations and smaller...
Authors: Kathryn J. Dess, Martha M. Matuszak, Dan Polan
Affiliation: University of Michigan
Abstract Preview: Purpose: A recent survey demonstrated 18 of 20 top academic institutions have implemented auto-segmentation. Studies to date have focused on geometric contour changes and dosimetric differences using ...
Authors: Yang Lei, Tian Liu, Ren-Dih Sheu, Meysam Tavakoli, Jing Wang, Kaida Yang, Jiahan Zhang
Affiliation: Icahn School of Medicine at Mount Sinai, Department of Radiation Oncology, Emory University
Abstract Preview: Purpose:
The study aimed to improve target and organ at risk (OAR) segmentation in low-dose-rate brachytherapy (LDR-BT) for prostate cancer treatment, by integrating clinical guidelines into deep l...
Authors: Jennifer L. Dolan, Chengyin Li, Parag Parikh, Doris N. Rusu, Kundan S Thind
Affiliation: Henry Ford Health, Cedars-Sinai Medical Center
Abstract Preview: Purpose: The time and resource demands of online Adaptive Radiation Therapy (ART) can limit its widespread clinical adoption and potentially impact patient throughput. To address this, we developed a ...
Authors: Yang Lei, Haibo Lin, Tian Liu, Charles B. Simone, Shouyi Wei, Ajay Zheng
Affiliation: Icahn School of Medicine at Mount Sinai, New York Proton Center
Abstract Preview: Purpose: Radiation-induced lung injury (RILI), encompassing pneumonitis and fibrosis, represents a critical dose-limiting factor in lung cancer radiation therapy. Variability in treatment outcomes is ...
Authors: Wookjin Choi, Jun Li
Affiliation: Thomas Jefferson University
Abstract Preview: Purpose: Resin Yttrium-90 (Y-90) selective internal radiation therapy (SIRT) is a radioembolization procedure which uses Y-90 microspheres to treat metastatic liver cancer. In the procedure, liver vol...
Authors: Gregory T. Armstrong, James E. Bates, Lei Dong, Ralph Ermoian, Jie Fu, Christine Hill-Kayser, Rebecca M. Howell, Sharareh Koufigar, John T. Lucas, Thomas E. Merchant, Tucker J. Netherton, Sogand Sadeghi
Affiliation: Department of Radiation Oncology, University of Washington and Fred Hutchinson Cancer Center, Department of Epidemiology and Cancer Control, St. Jude Childrenās Research Hospital, St. Jude Children's Research Hospital, Department of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, Department of Radiation Oncology, St. Jude Childrenās Research Hospital, Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Department of Radiation Oncology, University of Washington/ Fred Hutchinson Cancer Center, Department of Radiation Oncology, University of Pennsylvania, University of Pennsylvania, Department of Radiation Oncology and Winship Cancer Institute, Emory University
Abstract Preview: Purpose: This study evaluates the adaptability and limitations of commercially available (MIM, RayStation) tools trained on predominately adult datasets (ages 20ā60+ years) for delineating organs at r...
Authors: Asma Amjad, Renae Conlin, Eric S. Paulson, Christina M. Sarosiek
Affiliation: Department of Radiation Oncology, Medical College of Wisconsin
Abstract Preview: Purpose: In an effort to improve contouring accuracy for abdominal MR guided online adaptive radiotherapy (MRgOART), patient-specific deep learning-based auto-segmentation (PS-DLAS) has been proposed....
Authors: Ali Ammar, Quan Chen, Yi Rong, Libing Zhu
Affiliation: Mayo Clinic Arizona
Abstract Preview: Purpose: To investigate how defacing algorithms, essential for patient privacy in data sharing, impact AI-based segmentation performance in CT imaging for radiation therapy. This study evaluates wheth...
Authors: Fei Han, James M. Lamb, Michael Vincent Lauria, Daniel A. Low, Tessa Elizabeth Maurer, Danilo Maziero, Claudia R. Miller, Drew Moghanaki, Louise Naumann, Nicolas Viot
Affiliation: Department of Radiation Oncology, University of California, Los Angeles, Siemens Healthineers, UCLA, University of California Los Angeles
Abstract Preview: Purpose: Patients with lung disease outside radiotherapy are barred from high dose protocols used for motion modeling, but MRI could offer no-dose alternatives. Image-based ventilation is a promising ...
Authors: Christian Fiandra, Marco Fusella, Gianfranco Loi, Silvia Pesente, Lorenzo Placidi, Claudio Vecchi, Orlando Zaccaria, Stefania Zara
Affiliation: Abano Terme Hospital, University of Turin, Maggiore della CaritĆ , Tecnologie Avanzate Srl, Fondazione Policlinico Universitario Agostino Gemelli IRCCS
Abstract Preview: Purpose: Deformable-image-registration (DIR) is essential in modern radiotherapy for adaptive RT, re-irradiation, and other clinical applications. Multimodal DIR is especially important in MRI-only wo...
Authors: Stephen R. Bowen, Richard Cheng, Kylie Kang, Janice Kim, Ana Paula Santos Lima, Dominic A. Maes, Juergen Meyer, Karen Ordovas, Kerry Reding
Affiliation: Department of Radiation Oncology, University of Washington, Department of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, Department of Radiology, University of Washington, Division of Cardiology, University of Washington, Department of Biobehavioral Nursing and Health Informatics, School of Nursing, University of Washington
Abstract Preview: Purpose: Artificial intelligence (AI)-based auto-segmentation tools can increase the efficacy and reproducibility of radiotherapy (RT) treatment planning. This study evaluates the quality of AI-genera...
Authors: Claus Belka, Stefanie Corradini, George Dedes, Nikolaos Delopoulos, Christopher Kurz, Guillaume Landry, Ahmad Neishabouri, Domagoj Radonic, Adrian Thummerer, Niklas Wahl, Fan Xiao
Affiliation: Department of Radiation Oncology, LMU University Hospital, LMU Munich, Department of Medical Physics, LMU Munich, Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), National Center for Radiation Oncology (NCRO), Heidelberg Institute for Radiation Oncology (HIRO)
Abstract Preview: Purpose: In MR-guided online adaptive radiotherapy, MRI lacks tissue attenuation information necessary for accurate dose calculations. Instead of using deep learning methods to generate synthetic CT i...
Authors: Xianjin Dai, PhD, Michael Gensheimer, Praveenbalaji Rajendran, Lei Xing, Yong Yang
Affiliation: Department of Radiation Oncology, Stanford University, Massachusetts General Hospital, Harvard Medical School
Abstract Preview: Purpose: Recent advances in the automatic delineation of radiotherapy treatment targets, which incorporate linguistic clinical data extracted by large language models (LLMs) into traditional visual-on...
Authors: Chloe Min Seo Choi, Nikhil Mankuzhy, Aneesh Rangnekar, Andreas Rimner, Maria Thor, Harini Veeraraghavan, Abraham Wu
Affiliation: Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Memorial Sloan Kettering Cancer Center
Abstract Preview: Purpose: Cardiac substructure irradiation predisposes patients for poor outcomes in thoracic radiation therapy. A deep learning model was developed to segment the cardiac substructures invariant to co...
Authors: Elizabeth L. Covington, Robert T. Dess, Charles S. Mayo, Michelle L. Mierzwa, Dan Polan, Jennifer Shah, Claire Zhang
Affiliation: University of Michigan, Department of Radiation Oncology, University of Michigan
Abstract Preview: Purpose: Auto-segmentation improves contour consistency and standardization in radiation therapy but may introduce variations from current practices, potentially impacting treatment outcomes and toxic...
Authors: Jihun Kim, Jin Sung Kim, Jun Won Kim, Yong Tae Kim, Chanwoong Lee, Jihyn Pyo, Young Hun Yoon
Affiliation: Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Department of Radiation Oncology, Gangnam Severance Hospital, Yonsei University College of Medicine
Abstract Preview: Purpose: Although segmentation foundation models have recently demonstrated promising zero-shot performance on natural images, its clinical application to magnetic resonance (MR) images still requires...
Authors: Cheng-En Hsieh, Shen-Hao Li, Hsin-Hon Lin, Shu-Wei Wu, An-Ci Yang
Affiliation: Department of Medical Imaging and Radiological Sciences, Chang Gung University, Proton and Radiation Therapy Center, Chang Gung Memorial Hospital, Proton and Radiation Therapy Center, Chang Gung Memorial Hospital Linkou
Abstract Preview: Purpose:
The aim of this study is to develop a framework of generating patient-specific phantom tailored for head and neck proton therapy. From these phantoms, digital reference objects based on th...
Authors: Daria Gaykalova, Ranee Mehra, Jason K Molitoris, Hajar Moradmand, Lei Ren, Amit Sawant, Phuoc Tran
Affiliation: University of Maryland School of Medicine, Maryland University Baltimore, University of Maryland, Department of Radiation Oncology, University of Maryland School of Medicine
Abstract Preview: Purpose: Radiomics extracts quantitative imaging biomarkers from medical images. However, maintaining the reproducibility and stability of selected features across institutions and parameter settings ...
Authors: Cheng-Chieh Cheng, Jeffrey P Guenette, Yajun Li, Bruno Madore, Lei Qin
Affiliation: Brigham and Women's Hospital, National Sun Yat-sen University, Dana-Farber Cancer Institute
Abstract Preview: Purpose: Pilot tone (PT), a compact RF sensor, has been integrated into clinical practice for motion detection. Prior studies proposed mapping PT signals to head positions using a calibration step tha...
Authors: Seungryong Cho, Donghyeok Choi, Joonil Hwang, Byung-Hee Kang, Jin Sung Kim, Eungman Lee, Younghee Park
Affiliation: Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, KAIST, Department of Radiation Oncology, Yonsei Cancer Center, Yonsei University College of Medicine, Ewha Womans University of Medicine
Abstract Preview: Purpose: Radiation therapy (RT) is critical for cancer treatment, but changes in tumor size and shape during therapy challenge precise dose delivery. Adaptive radiation therapy (ART) addresses these v...
Authors: Omar Awad, Alfredo Enrique Echeverria, Issam M. El Naqa, Daniel Allan Hamstra, Yiding Han, Ryan Lafratta, Abdallah Sherif Radwan Mohamed, Piyush Pathak, Zaid Ali Siddiqui, Baozhou Sun, Vincent Ugarte
Affiliation: H. Lee Moffitt Cancer Center, Harris Health, Baylor College of Medicine
Abstract Preview: Purpose:
Accurate detection and segmentation of brain metastases are critical for diagnosis, treatment planning, and follow-up imaging but are challenging due to labor-intensive manual assessments ...
Authors: Asma Amjad, Renae Conlin, Eric S. Paulson, Christina M. Sarosiek
Affiliation: Department of Radiation Oncology, Medical College of Wisconsin
Abstract Preview: Purpose:
MR-guided adaptive radiation therapy (MRgART) is transforming clinical workflows, requiring fast, accurate organs-at-risk (OARs) contouring. While deep learning auto-segmentation (DLAS) of...
Authors: Karyn A Goodman, Yang Lei, Tian Liu, Pretesh Patel, Jing Wang, Kaida Yang, Jiahan Zhang
Affiliation: Icahn School of Medicine at Mount Sinai, Department of Radiation Oncology and Winship Cancer Institute, Emory University
Abstract Preview: Purpose: This study aims to improve organ-at-risk (OAR) segmentation in pancreatic cancer stereotactic body radiotherapy (SBRT) by integrating clinical guidelines into deep learning workflows. We use ...
Authors: Xuezhen Feng, Li-Sheng Geng, Haoze Li, Xi Liu, Tianyu Xiong, Ruijie Yang
Affiliation: Department of Health Technology and Informatics, The Hong Kong Polytechnic University, School of Physics, Beihang University, School of Nuclear Science and Technology, University of South China, Department of Radiation Oncology, Peking University Third Hospital
Abstract Preview: Purpose: This study aimed to develop a deep learning-based algorithm for automatically delineate gross tumor volume (GTV) for lung cancer patients, alleviating the workload of radiologists and improvi...
Authors: Jue Jiang, Aneesh Rangnekar, Shiqin Tan, Harini Veeraraghavan
Affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Weill Cornell Graduate School of Medical Sciences
Abstract Preview: Purpose: Clinicians often use information from FDG-PET and CT to interpret and delineate gross tumor (GTVp) and nodal (GTVn) volumes for radiotherapy planning in head and neck (HN) cancer patients. He...
Authors: Ali Ajdari, Thomas R. Bortfeld, Christopher Bridge, Gregory Buti, Marcela Giovenco, Fredrik Lofman, Gregory C. Sharp, Helen A Shih, Tugba Yilmaz
Affiliation: Massachusetts General Hospital, RaySearch Laboratories, Department Of Radiation Oncology, Massachusetts General Hospital (MGH), Massachusetts General Hospital & Harvard Medical School, Massachusetts General Hospital and Harvard Medical School
Abstract Preview: Purpose: Defining radiation target volumes with accurate integration of the neuroanatomy is one of the major difficulties in designing glioma treatments. We developed a deep learning network for norma...
Authors: Olubunmi Odunola Aregbe, Clara Ferreira, Margaret Reynolds, David A. Sterling
Affiliation: University of Minnesota, University of Minnesota Physicians, Department of Radiation Oncology, University of Minnesota, Minneapolis
Abstract Preview: Purpose: Current best practices recommend daily imaging and planning for Tandem and Ring (T&R) HDR patient plans. Accurate target delineation is a critical, yet time consuming step in this process. Th...
Authors: Chloe Min Seo Choi, Joseph O. Deasy, Jue Jiang, Sudharsan Madhavan, Nikhil Mankuzhy, Nishant Nadkarni, Andreas Rimner, Maria Thor, Harini Veeraraghavan, Abraham Wu
Affiliation: University of Freibrug, Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Memorial Sloan Kettering Cancer Center
Abstract Preview: Purpose: Voxel-based analysis (VBA) requires accurate topology-preserving inter-patient deformable image registration (DIR). This study assessed whether guiding a DIR method with geometric priors of t...
Authors: Ming Dong, Carri K. Glide-Hurst, Qisheng He, Anudeep Kumar, Alex Singleton Kuo, Joshua Pan, Chase Ruff, Nicholas R. Summerfield
Affiliation: Department of Computer Science, Wayne State University, Departments of Human Oncology and Medical Physics, University of Wisconsin-Madison, Department of Human Oncology, University of Wisconsin-Madison
Abstract Preview: Purpose: Recent evidence highlights the importance of incorporating cardiac substructures (CS) into treatment planning for thoracic cancers, however current segmentation methods are limited to a singl...
Authors: Ming Chao, Thomas Chum, Tenzin Kunkyab, Yang Lei, Tian Liu, Richard G Stock, Hasan Wazir, Junyi Xia, Jiahan Zhang
Affiliation: Icahn School of Medicine at Mount Sinai
Abstract Preview: Purpose:
This study aims to develop effective strategies for multi-organ segmentation of pelvic cone-beam computed tomography (CBCT) images based on transformer models to facilitate adaptive radiat...
Authors: Mingli Chen, Xuejun Gu, Hao Jiang, Mahdieh Kazemimoghadam, Weiguo Lu, Qingying Wang, Kangning Zhang
Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, UT Southwestern Medical Center, Department of Radiation Oncology, Stanford University School of Medicine
Abstract Preview: Purpose:
Deep learning-based automatic medical image segmentation is increasingly employed in clinical practice, significantly reducing manual workload. However, verifying segmentation results rema...
Authors: Samuel L. Brady, Shruti Hegde, Alexander Knapp, Usman Mahmood, Joseph G. Meier, Elanchezhian Somasundaram, Zachary Taylor
Affiliation: Cincinnati Children's Hospital Medical Ctr, Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Cincinnati Children's Hospital Medical Center, Cincinnati Childrens Hospital Med Ctr
Abstract Preview: Purpose:
To assess how two benchmark multi-organ CT segmentation models respond to varying image noise levels.
Methods:
This study utilized the pediatric CT dataset from The Cancer Imaging Ar...
Authors: David P. Adam, William T. Hrinivich, Taoran Li, Alexander Lu, Michael Salerno, Alejandro Sisniega, Boon-Keng Kevin Teo
Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Johns Hopkins University, University of Pennsylvania
Abstract Preview: Purpose: Cone beam CT (CBCT)-guided online adaptive radiotherapy (ART) is of growing interest, with recent improvements in image quality provided through larger detector panels and fast gantry rotatio...
Authors: Zayne Belal, Rachel Drummey, Clifton David Fuller, Stephen Y. Lai, Brigid A. McDonald, Setareh Sharafi, Sonja Stieb, Kareem Abdul Wahid
Affiliation: Department of Head and Neck Surgery, The University of Texas MD Anderson Cancer Center, Department of Radiation Oncology, Hospital of the University of Pennsylvania, Department of Radiology, Johns Hopkins University, KSA-KSB, Cantonal Hospital Aarau, College Of Osteopathic Medicine, NOVA Southeastern University, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center
Abstract Preview: Purpose:
Radiotherapy-induced dysphagia can significantly impair head and neck (H&N) cancer patientsā quality of life. Despite the dose-dependent relationship between radiotherapy and dysphagia, sw...
Authors: B. Gino Fallone, Gawon Han, Keith D. Wachowicz, Mark G. Wright, Eugene Yip, Jihyun Yun
Affiliation: Medical Physics Division, Department of Oncology, University of Alberta, Dept. of Medical Physics, Cross Cancer Institute and Dept. of Oncology, University of Alberta, Medical Physics Division, Department of Oncology, University of Alberta and Department of Medical Physics, Cross Cancer Institute, Dept. of Medical Physics, Cross Cancer Institute and Dept. of Oncology, University of Alberta; MagnetTx Oncology Solutions, www.magnetTX.com
Abstract Preview: Purpose: MRI-radiotherapy hybrid systems can guide the therapeutic beam, dynamically adjusting to a moving tumor in real-time. However, there is a time delay from imaging and beam control, requiring p...
Authors: Manju Liu, Ning Wen, Fuhua Yan, Yanzhao Yang, Zhenyu Yang, Haoran Zhang, Lei Zhang, Yajiao Zhang
Affiliation: Department of Radiology, Ruijin Hospital Shanghai Jiaotong University School of Medicine, Duke Kunshan University, Medical Physics Graduate Program, Duke Kunshan University
Abstract Preview: Purpose: Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy where precise segmentation of tumors and adjacent vessels is crucial for effective treatment planning. This study dev...
Authors: Blessing Akinro, Soumyanil Banerjee, Ming Dong, Carri K. Glide-Hurst, Prashant Nagpal, Chase Ruff, Nicholas R. Summerfield, Timothy P. Szczykutowicz
Affiliation: Departments of Human Oncology and Medical Physics, University of Wisconsin-Madison, Departments of Radiology and Medical Physics, University Wisconsin-Madison, Department of Radiology, University of Wisconsin-Madison, Department of Computer Science, Wayne State University, Department of Human Oncology
Abstract Preview: Purpose: Radiation dose to coronary arteries (CAs) during thoracic radiotherapy (RT) is linked to cardiotoxicity. However, precise CA delineation for avoidance is limited by image quality and CA compl...
Authors: James M. Balter, Lando S. Bosma, Jorge Tapias Gomez, Nishant Nadkarni, Mert R Sanbuncu, William Paul Segars, Ergys D. Subashi, Neelam Tyagi, Harini Veeraraghavan
Affiliation: University of Michigan, The University of Texas MD Anderson Cancer Center, Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Carl E. Ravin Advanced Imaging Laboratories and Center for Virtual Imaging Trials, Duke University Medical Center, Cornell University, University Medical Center Utrecht, Memorial Sloan Kettering Cancer Center
Abstract Preview: Purpose: Develop patient-specific virtual digital twin (VDT) cohorts modeling physically realistic spatio-temporal gastrointestinal (GI) organs (stomach and duodenum) digestive motion.
Methods: Pat...
Authors: Ali Ammar, Quan Chen, Jingwei Duan, Yi Rong, Nathan Y. Yu, Libing Zhu
Affiliation: Mayo Clinic Arizona, University of Alabama at Birmingham
Abstract Preview: Purpose: Clinical performance of deep learning-based auto-segmentation (DLAS) can degrade over time due to AI āagingā from unseen data input compared to the initial model training data. This study aim...
Authors: Daming LI, Jinsen Xie, Zhe Zhang
Affiliation: Peking University Shenzhen Hospital Radiotherapy Department, School of Nuclear Science and Technology, University of South China
Abstract Preview: Purpose: To analyze the actual doses received during radiotherapy for head and neck cancers (HNC) using Velocity, providing insights for adaptive radiotherapy decision-making.
Methods: Thirty-three...
Authors: Diandra Ayala-Peacock, Junzo Chino, Oana I. Craciunescu, Allison Jones, Kyle J. Lafata, Kim Light, Sheridan G. Meltsner, Jack B Stevens
Affiliation: Duke University, Department of Radiation Oncology, Duke University, Duke University Medical Center
Abstract Preview: Purpose: This study aims to develop an MR-based method that retrospectively correlates longitudinal changes in morphology and physiology for the bulboclitoris and vaginal canal with dose received duri...
Authors: Tommaso Frigerio, Joshua Genender, John M. Hoffman, Catherine (Caffi) Meyer
Affiliation: UCLA, David Geffen School of Medicine at UCLA
Abstract Preview: Purpose: Accurate bone marrow segmentation is required for bone marrow dosimetry to monitor for dangers in PSMA-Lu177 radioligand therapy. We introduce a hybrid (AI/semantic knowledge) segmentation pi...
Authors: Li-Sheng Geng, David Huang, Haoze Li, Xi Liu, Meng Wang, Tianyu Xiong, Ruijie Yang, Weifang Zhang, Meixin Zhao
Affiliation: School of Physics, Beihang University, Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Department of Radiation Oncology, Peking University Third Hospital, Department of Nuclear Medicine, Peking University Third Hospital, Medical Physics Graduate Program, Duke Kunshan University
Abstract Preview: Purpose: This study aimed to develop a deep learning-based framework for simultaneously generating lung perfusion and ventilation images from three-dimensional computed tomography (3D CT) images.
M...
Authors: Ming Dong, Carri K. Glide-Hurst, Joshua Pan, Nicholas R. Summerfield
Affiliation: Department of Computer Science, Wayne State University, Departments of Human Oncology and Medical Physics, University of Wisconsin-Madison, Department of Human Oncology, University of Wisconsin-Madison
Abstract Preview: Purpose: Radiation dose to the cardiac nodes is more strongly associated with conduction disorders and arrythmias than whole heart (WH) metrics. However, node segmentation is challenging due to comple...
Authors: Bryan Bednarz, Laura Bennett, Abby E. Besemer, Tyler J Bradshaw, Steve Y Cho, John M. Floberg, Joseph Grudzinski, Elissa Khoudary, Michael J. Lawless
Affiliation: Department of Radiology, University of Wisconsin, University of Wisconsin-Madison Department of Medical Physics, Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin - Madison, Department of Human Oncology, University of Wisconsin School of Medicine and Public Health, Voximetry, Inc, University of Pennsylvania, Department of Radiology, University of Wisconsin - Madison, Department of Human Oncology, University of Wisconsin-Madison
Abstract Preview: Purpose: To assess the impact of using a standardized immobilization setup for multi-time-point SPECT/CT imaging on radiopharmaceutical therapy (RPT) dosimetry image registration.
Methods: Ten ...
Authors: Samuel Kadoury, Redha Touati
Affiliation: Polytechnique MontrƩal
Abstract Preview: Purpose:
Generating synthetic CT images from MR acquisitions for radiotherapy planning allows to integrate soft tissue contrast alongside density information stemming from CT, thus improving tumor ...
Authors: Gong Vincent Hao, Daisuke Kawahara, Jokichi Kawazoe, Yuji Murakami, Ikuno Nishibuchi, Peiying Colleen Ruan, Daguang Xu, Dong Yang
Affiliation: Department of Radiation Oncology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Graduate School of Biomedical and Health Sciences, Hiroshima University, NVIDIA
Abstract Preview: Purpose:
Accurate tumor segmentation in head and neck cancer is critical for effective treatment planning, but variability in practices across medical facilities poses challenges for standardizatio...
Authors: Cem Altunbas, Adam Avant, Farhang Bayat, Roy Bliley, Ian Boor, Brian Kavanagh, Uttam Pyakurel, Tyler Robin, Ryan Sabounchi
Affiliation: Department of Radiation Oncology, University of Colorado School of Medicine, Taussig Cancer Center, Cleveland Clinic
Abstract Preview: Purpose: Improved soft tissue visualization plays an important role in target localization and treatment plan adaptation in CBCT-guided radiotherapy. In this work, a novel CBCT approach, 2D antiscatte...
Authors: Nuraddeen Nasiru Garba, Kalpana M Kanal, Abdullahi Mohammed, Rabiu Nasiru, Muhammad SHAFIU Shehu, Daniel Vergara, Joseph Everett Wishart
Affiliation: AHMADU BELLO UNIVERSITY, ZARIA, University of Washington
Abstract Preview: Purpose: To establish local Diagnostic Reference Levels (DRLs) for head and neck computed tomography (CT) exams in Abuja, Nigeria, and to investigate the performance of brain metastasis (BM) and brain...
Authors: Michael Cummings, Olga M. Dona Lemus, Hana Mekdash, Tyler Moran, Alexander R Podgorsak, Sean M. Tanny, Matthew J. Webster, Lexiang Yang, Dandan Zheng, Yuwei Zhou, Xiaofeng Zhu
Affiliation: Department of Radiation Oncology, University of Rochester, University of Miami, Inova Schar Cancer Institute, University of Rochester
Abstract Preview: Purpose: oART is revolutionizing radiotherapy by allowing treatment plans to be adjusted based on daily imaging, improving targeting precision and potentially enhancing patient outcomes. However, its ...
Authors: Stephen R. Bowen, Shijun Chen, Chunyan Duan, Daniel S. Hippe, Qiantuo Liu, Qianqian Tong, Jiajie Wang, Shouyi Wang, Faisal Yaseen
Affiliation: The University of Texas at Austin, Tongji University, University of Washington, Department of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, Fred Hutchinson Cancer Center, University of Texas at Arlington
Abstract Preview: Purpose: Tumor subregion clustering and prediction of region-specific response can augment assessments and adaptive treatment decisions. A modeling framework was constructed to predict chemoradiation ...
Authors: Ming Dong, Carri K. Glide-Hurst, Behzad Hejrati, Joshua Pan, Yuhao Yan
Affiliation: Department of Computer Science, Wayne State University, Departments of Human Oncology and Medical Physics, University of Wisconsin-Madison, Department of Human Oncology, University of Wisconsin-Madison
Abstract Preview: Purpose: Upright patient positioners and vertical CT reduce tumor motion and stabilize internal anatomy during treatment delivery. Yet, to fully exploit the advantages of upright, translation of stand...
Authors: Michael Baine, Yang Lei, Yu Lei, Ruirui Liu, Tian Liu, Jing Wang
Affiliation: Icahn School of Medicine at Mount Sinai, University of Nebraska Medical Center
Abstract Preview: Purpose: Accurate 3D deformable registration of MRI and ultrasound (US) is essential for real-time image guidance during high-dose-rate (HDR) prostate brachytherapy. However, MRI-US registration of th...