Authors: Gabriel Lucas Andrade de Sousa, Einsley-Marie Janowski, Cam Nguyen, Krishni Wijesooriya
Affiliation: Department of Radiation Oncology, University of Virginia, Department of Physics, University of Virginia
Abstract Preview: Purpose: Optimizing radiation therapy (RT) to spare the immune system may improve Overall Survival (OS) in cancer patients. This study develops a computational algorithm to identify optimal dose-volum...
Authors: Christos Ilioudis, Marios Myronakis, Sotirios Raptis, Kyriaki Theodorou
Affiliation: Medical Physics Department, Medical School, University of Thessaly, Department of Information and Electronic Engineering, International Hellenic University (IHU)
Abstract Preview: Purpose: This study presents a radiomics-driven, machine learning framework developed to predict the possibility of Radiation Pneumonitis (RP), as a side effect of radiation therapy in lung cancer pat...
Authors: Eric Chang, Nguyen Phuong Dang, Andrew Lim, Lauren Lukas, Lijun Ma, Yutaka Natsuaki, Zhengzheng Xu, Hualin Zhang
Affiliation: Radiation Oncology, Keck School of Medicine of USC
Abstract Preview: Purpose: Harnessed the power of AI and Deep Learning (DL), Generalized Neural Network models for medical image transformation are trained to predict target images from reference images, often requirin...
Authors: Katelyn M. Atkins, Indrin J. Chetty, Elizabeth M. McKenzie, Taman Upadhaya, Samuel C. Zhang
Affiliation: Department of Radiation Oncology,Cedars-Sinai Medical Center, Cedars-Sinai Medical Center
Abstract Preview: Purpose:
We explored a multi-regional and multi-omics approach to extract CT-based radiomics and 3D dosiomics features to predict radiation pneumonitis (RP) in patients with locally advanced Non-Sm...
Authors: Christopher Colyer, Leon F Dunn, Jonathan Dunning, Simon Goodall, Andy Schofield
Affiliation: GenesisCare
Abstract Preview: Purpose: Modern radiotherapy is characterized by complex treatment plans utilizing dynamic MLCs, gantry positions and recently, collimator rotations. The purpose of this work was to compare the plan c...
Authors: Zachary Buchwald, Chih-Wei Chang, Richard L.J. Qiu, Mojtaba Safari, Hui-Kuo Shu, Lisa Sudmeier, Xiaofeng Yang, David Yu, Xiaohan Yuan
Affiliation: Emory University and Winship Cancer Institute, Emory University, Georgia Institute of Technology, Department of Radiation Oncology and Winship Cancer Institute, Emory University
Abstract Preview: Purpose: This study proposes a novel vision-language model (VLM) to predict survival outcomes in glioblastoma (GBM) patients. By integrating multimodal MRI data and clinical information, the proposed ...
Authors: Mojtaba Behzadipour, Siyong Kim, Mitchell Polizzi, Richard R. Wargo, Lulin Yuan
Affiliation: VCU Health - Department of Radiology, Virginia Commonwealth University
Abstract Preview: Purpose:
The purpose of this study is to develop a method for generating missing tissue in CT scans of patients with large body sizes, where the field of view (FOV) of the scanner fails to capture ...
Authors: Yasin Abdulkadir, Justin Hink, James M. Lamb, Jack Neylon
Affiliation: Department of Radiation Oncology, University of California, Los Angeles
Abstract Preview: Purpose: Curation remains a significant barrier to the use of ‘big data’ radiotherapy planning databases of 100,000 patients or more. Anatomic site of treatment is an important stratification for almo...
Authors: Lavsen Dahal, Francesco Ria, Ehsan Samei, Justin B. Solomon, Liesbeth Vancoillie, Yakun Zhang
Affiliation: Duke University, Carilion Clinic, Clinical Imaging Physics Group, Department of Radiology, Duke University Health System
Abstract Preview: Purpose: Clinical diagnostic task-based optimization of CT procedures require precise and organ-specific assessments. This study investigates inter-organ noise variability to highlight the limitations...
Authors: Klea Hoxha, Dylan P. O'Connell, Ricky R Savjani
Affiliation: Department of Radiation Oncology, University of California, Los Angeles, UCLA Radiation Oncology
Abstract Preview: Purpose: Ambiguities in physician simulation orders lead to workflow disruptions during CT simulation. Often, information that could provide
helpful context to simulation therapists and planners is...
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: Wilfred R Furtado, Gary Y. Ge, Jie Zhang
Affiliation: Department of Radiology, University of Kentucky, University of Kentucky
Abstract Preview: Purpose: The United Kingdom and several other countries already have well-established diagnostic reference levels (DRLs) for gastrointestinal fluoroscopic procedures, whereas the United States does no...
Authors: Michael Dohopolski, Xuejun Gu, Hao Jiang, Steve B. Jiang, Christopher Kabat, Jingying Lin, Weiguo Lu, Michael Tang
Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center, Neuralrad LLC, 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: To streamline access to clinical data stored in Oncology Information Systems such as MOSAIQ or ARIA, we developed an AI-powered chatbot capable of querying, summarizing, and interactively ans...
Authors: Xuelian Chen, John Ginn, Zhuhong Li, Kaizhong Shi, Chunhao Wang, Jianliang Wang, Chuan Wu, Zhenyu Yang, Fang-Fang Yin, Jingtong Zhao
Affiliation: The First People's Hospital of Kunshan, Duke University, Medical Physics Graduate Program, Duke Kunshan University, Duke Kunshan University, Department of Radiation Oncology, Duke Kunshan University
Abstract Preview: Purpose: Developing deep learning-based models for accurate automated breast cancer diagnosis from mammography presents significant challenges due to the small size and subtle nature of breast lesions...
Authors: Kimberly Chan, Anke Henning, Mahrshi Jani, Andrew Wright, Xinyu Zhang
Affiliation: Advanced Imaging Research Center (AIRC), UT Southwestern Medical Center
Abstract Preview: Purpose: To evaluate the performance of multiple deep learning architectures for MRSI reconstruction and determine their effectiveness in maintaining high-resolution metabolite mapping while reducing ...
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: Jared Baggett, Wesley E. Bolch, Lukas M. Carter, Robert Joseph Dawson, Laura Dinwiddie, Adam Leon Kesner, Cameron B. Kofler, Juan Camilo Ocampo Ramos, Yitian Wang, Stefan Wehmeier
Affiliation: University of Chicago, Department of Medical Physics, Memorial Sloan Kettering Cancer Center, University of Florida, MD Anderson
Abstract Preview: Purpose: To develop a slice-specific computed tomography (CT) organ dose library using Monte Carlo radiation transport simulations on a newly created set of newborn, infant, and toddler computational ...
Authors: Fangfen Dong, Jiaming Li, Xiaobo Li, Weipei Wang, Zhixin Wang, Bing Wu, Benhua Xu, Yong Yang, Yifa Zhao
Affiliation: Department of Radiation Oncology, Fujian Medical University Union Hospital/Fujian Key Laboratory of Intelligent Imaging and Precision Radiotherapy for Tumors/Clinical Research Center for Radiology and Radiotherapy of Fujian Province (Digestive, Hematologi, Zhangpu County Hospital, School of Medical Imaging, Fujian Medical University
Abstract Preview: Purpose: To explore the construction and clinical application value of a deep learning-based positioning error prediction model, providing a reference for optimizing iSCOUT system-guided precision rad...
Authors: Stephen Balter, Haegin Han, Cari M Kitahara, Taeeun Kwon, Choonsik Lee, Martha S Linet, Donald L. Miller
Affiliation: Columbia University Medical Center, National Cancer Institute, Food and Drug Administration
Abstract Preview: Purpose: Staff in fluoroscopically guided interventional (FGI) procedures are exposed to radiation. Inhomogeneous radiation fields and variability in procedural conditions make it challenging to deriv...
Authors: Carri K. Glide-Hurst, Thomas M Grist, Kevin M. Johnson, Prashant Nagpal, Tarun Naren, Chase Ruff, Oliver Wieben, Jiwei Zhao
Affiliation: Department of Biostatistics and Medical Informatics, University of Wisconsin - Madison, Department of Radiology, University of Wisconsin-Madison, Department of Medical Physics, University of Wisconsin-Madison, Departments of Human Oncology and Medical Physics, University of Wisconsin-Madison
Abstract Preview: Purpose: Cardiotoxicity is a devastating side effect for thoracic radiotherapy (RT). Currently, standard RT imaging is insufficient to decouple cardiorespiratory motion, limiting substructure-specific...
Authors: Anke Henning, Mahrshi Jani, Tianyu Wang, Andrew Wright, Xinyu Zhang
Affiliation: Advanced Imaging Research Center (AIRC), UT Southwestern Medical Center
Abstract Preview: Purpose: Proton MRSI offers critical metabolic insights into diseased brain processes but is prone to artifacts, and current post-processing methods are often insufficient, resulting in low-quality da...
Authors: Xinhui Duan, Roderick W. McColl, Mi-Ae Park, Liqiang Ren, Gary Xu, Kuan Zhang, Yue Zhang
Affiliation: UT Southwestern Medical Center, Department of Radiology, UT Southwestern Medical Center, Imaging Services, UT Southwestern Medical Center
Abstract Preview: Purpose:
Image-based deep-learning noise-reduction techniques have been developed for photon-counting CT (PCCT) to improve image quality with reduced radiation dose. The denoising strength is typic...
Authors: Chibawanye I. Ene, Sherise D. Ferguson, Ping Hou, Vinodh A. Kumar, Ho-Ling Anthony Liu, Kyle R. Noll, Sujit S. Prabhu, Jian Ming Teo, Max Wintermark
Affiliation: Department of Neuro-Oncology, The University of Texas MD Anderson Cancer Center, Department of Neuroradiology, The University of Texas MD Anderson Cancer Center, Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Department of Imaging Physics, The University of Texas MD Anderson Cancer Center
Abstract Preview: Purpose:
Functional brain atlases are used to guide clinical functional MRI (fMRI) analyses. Imprecise assertions may introduce the ecological fallacy as atlases are reflective of the constituent c...
Authors: Morgan A. Daly, David J. Goodenough, Andrew M. Hernandez, John M. Hoffman, Joshua Levy, Michael F. McNitt-Gray, Ali Uneri, Bino Varghese
Affiliation: University of California, George Washington University, David Geffen School of Medicine at UCLA, Johns Hopkins Univ, University of Southern California, The Phantom Laboratory
Abstract Preview: Purpose: Quantitative imaging is affected by CT acquisition and reconstruction conditions, limiting robustness in multi-site or -scanner studies. This work aimed to develop a dataset that will enable ...
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: Lian Duan, Stephen F. Kry, Hunter S. Mehrens, Christine Peterson, Paige A. Taylor
Affiliation: The University of Texas MD Anderson Cancer Center, UT MD Anderson Cancer Center
Abstract Preview: Purpose: To develop predictive models for IROC SRS head phantom audits and to identify important factors influencing institutional performance.
Methods: The IROC SRS head phantom includes two TLDs ...
Authors: Minbin Chen, Ke Lu, Kaizhong Shi, Chunhao Wang, Chuan Wu, Zhenyu Yang, Fang-Fang Yin, Jingtong Zhao
Affiliation: The First People's Hospital of Kunshan, Duke University, Medical Physics Graduate Program, Duke Kunshan University, Duke Kunshan University, Department of Radiation Oncology, Duke Kunshan University
Abstract Preview: Purpose: MRI-based automatic detection of brain metastases is often challenged by the small size and subtle nature of metastases. This study aimed to develop a novel deep learning-based brain metastas...
Authors: Jadon Buller, Zhuoran Jiang, Yankun Lang, Lei Ren, Leshan Sun, Liangzhong Xiang, Yifei Xu
Affiliation: University of Maryland School of Medicine, University of California, Irvine, University of California, Stanford University
Abstract Preview: Purpose: Electroacoustic tomography (EAT) and Protoacoustic (PA) imaging are novel modalities for treatment verification of electroporation and proton therapy. However, the limited acquisition angle i...
Authors: Hassan Bagher-Ebadian, Justine M. Cunningham, Anthony J. Doemer, Mohammad M. Ghassemi, Joshua P. Kim, Benjamin Movsas, Kundan S Thind
Affiliation: Michigan State University, Henry Ford Health
Abstract Preview: Purpose: Reduction of noise in medical images critically enables improved accuracy in delineating tumors and organs at risk, leading to more precise treatment planning and safer image-guided radiation...
Authors: Rashmi Bhaskara, Oluwaseyi Oderinde
Affiliation: Purdue University
Abstract Preview: Purpose: This study proposes a novel approach to overcoming CBCT image quality limitations by developing an improved synthetic CT (sCT) generation method based on a CycleGAN architecture using Vision ...
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 Carità, 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: Chia-Ho Hua, Jirapat Likitlersuang, Jinsoo Uh
Affiliation: St. Jude Children's Research Hospital
Abstract Preview: Purpose: AI-based fast MRI, which reconstructs images from undersampled k-space data, has not yet been tailored for RT planning. This study aims to evaluate the fast MRI performance of our recently pr...
Authors: Xiangli Cui, Chunyan Fu, Man Hu, Wanli Huo, Jingyu Liu, Jianguang Zhang, Yingying Zhang, Shanyang Zhao
Affiliation: Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, the Zhejiang-New Zealand Joint Vision-Based Intelligent Metrology Laboratory, College of Information Engineering, China Jiliang University, Departments of Radiation Oncology, Zibo Wanjie Cancer Hospital, Key Laboratory of Electromagnetic Wave Information Technology and Metrology of Zhejiang Province, College of Information Engineering, China Jiliang University, Department of Oncology, Xiangya Hospital, Central South University, College of Information Engineering, China Jiliang University, Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University, Shandong Academy of Medical Sciences
Abstract Preview: Purpose: To quantify the impact of fine-tuning strategies for pre-trained AI image generation models on glioma MRI image quality and observer performance, and to determine the optimal fine-tuning conf...
Authors: Mingli Chen, Xuejun Gu, Mahdieh Kazemimoghadam, Weiguo Lu, Qingying Wang
Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, Department of Radiation Oncology, Stanford University School of Medicine
Abstract Preview: Purpose: This study introduces a novel template-guided deep learning framework for primary gross tumor volume (GTVp) segmentation, addressing challenges posed by diverse tumor types and enabling a uni...
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: Ling Chen, Alexei V. Trofimov, Yi Wang, Dufan Wu
Affiliation: Massachusetts General Hospital, MGH
Abstract Preview: Purpose:
Selecting gaze angles of the eye is an important part of set-up of proton therapy for ocular tumors, ensuring that the treatment beam could irradiate the tumor while maximally sparing impo...
Authors: Yu Gao, Lei Xing, Siqi Ye
Affiliation: Department of Radiation Oncology, Stanford University
Abstract Preview: Purpose:
Limited-angle CBCT (LA-CBCT) scans are often the only option for non-coplanar radiation therapy to prevent potential mechanical collisions. However, the consecutive angular occlusion of pr...
Authors: Mark Ashamalla, Renee Farrell, Jinkoo Kim, Kartik Mani, Xin Qian, Samuel Ryu, Yizhou Zhao
Affiliation: Stony Brook Medicine, Stony Brook University Hospital
Abstract Preview: Purpose: Adaptive planning is increasingly used in head and neck radiation therapy due to factors like tumor response or changes in patient anatomy. However, methods such as resimulation or offline re...
Authors: Andreea Dimofte, Maksym Sharma, Weibing Yang, Timothy C. Zhu
Affiliation: Department of Radiation Oncology, University of Pennsylvania, University of Pennsylvania
Abstract Preview: Purpose:
To assess the effectiveness and dosimetric impact of utilizing a knowledge-based planning model for GI site-specific plans.
Methods:
Six knowledge-based planning models were develope...
Authors: Ibtisam Almajnooni, Elisabeth Weiss, Lulin Yuan
Affiliation: Virginia Commonwealth University
Abstract Preview: Purpose: We developed a deep learning neural network (DLNN) to predict the risk of radiation-induced esophagitis (RE) during lung cancer radiation therapy based on the spatial dose distribution, for t...
Authors: Zong Fan, Fan Lam, Hua Li, Rita Huan-Ting Peng, Yuan Yang
Affiliation: University of Illinois at Urbana Champaign, University of Illinois at Urbana-Champaign, Washington University School of Medicine, University of Illinois Urbana-Champaign
Abstract Preview: Purpose: Accurate lesion segmentation in MRI is critical for early diagnosis, treatment planning, and monitoring disease progression in various neurological disorders. Cross-site MRI data can alleviat...
Authors: Guha Balakrishnan, Osama R. Mawlawi, Yiran Sun, Ashok Veeraraghavan
Affiliation: RICE University, UT MD Anderson Cancer Center
Abstract Preview: Purpose:
Previous deep learning (DL) techniques such as X2CT-GAN [1] has shown great promise in reconstructing realistic CT volume from biplanar X-rays, however they introduce numerous artifacts in...
Authors: Yunfei Dong, Dongyang Guo, Jiongli Pan, Tao Peng, Caiyin Tang, Zhenyu Yang, Fang-Fang Yin, Lei Zhang, Tianyi Zhang, Yaogong Zhang
Affiliation: Duke Kunshan University, Department of Radiology, Taizhou People’s Hospital Affiliated to Nanjing Medical University, School of Future Science and Engineering, Soochow University, Medical Physics Graduate Program, Duke Kunshan University
Abstract Preview: Purpose: This study aims to improve the accuracy of CT-based diagnosis of thyroid cancer by developing a hybrid model that integrates Convolutional Neural Networks (CNNs) with Long Short-Term Memory (...
Authors: Steve B. Jiang, Mu-Han Lin, Yu-Chen Lin, Austen Matthew Maniscalco, Dan Nguyen, David Sher, Xinran Zhong
Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center, Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, UT Southwestern Medical Center, Department of Radiation Oncology, UT Southwestern Medical Center, UT Dallas
Abstract Preview: Purpose:
Sequential boost radiotherapy (RT) poses a challenge in allocating dose across multiple plans while protecting organs at risk (OARs). Clinicians must decide whether OAR sparing should occu...
Authors: Hassan Bagher-Ebadian, Ahmed I Ghanem, Joshua P. Kim, Chengyin Li, Rafi Ibn Sultan, Kundan S Thind, Dongxiao Zhu
Affiliation: Wayne State University, Department of Radiation Oncology, Henry Ford Health-Cancer, Detroit, MI and Alexandria Department of Clinical Oncology, Faculty of Medicine, Alexandria University, Henry Ford Health
Abstract Preview: Purpose: Accurate segmentation of the Left Anterior Descending (LAD) artery in free-breathing 3D treatment planning CT is crucial for radiotherapy but remains challenging due to its small size, comple...
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: Kristina Bjegovic, Yong Chen, Gilberto Gonzalez, Yankun Lang, Lei Ren, Leshan Sun, Liangzhong Xiang, Yifei Xu
Affiliation: University of Maryland School of Medicine, University of California, Irvine, University of Oklahoma Health Sciences Center, University of Oklahoma Health Science Center
Abstract Preview: Purpose: Proton therapy is becoming an increasingly popular choice for cancer treatment due to its precision, reduced side effects, and effectiveness. While dosimetry is fundamental to the success of ...
Authors: Ahmad K. Al-Basheer, Andrew Clarke Grice, Kelly E. Hosier, Mark Logsdon, Evan A. Silverstein, Chris Tunnicliff, Chuan Wu
Affiliation: Sutter Medical Foundation, Sutter Health
Abstract Preview: Purpose: For Prostate SBRT Boost treatments, determine whether a uniform 2mm CTV to PTV margin is sufficient to give 95% dose coverage to the CTV in 90% of patients via a modified Van Herk Margin Form...
Authors: Hyejoo Kang, Andrew Keeler, Mathias Lehmann, Jason Patrick Luce, Ha Nguyen, John C. Roeske
Affiliation: Varian Imaging Laboratory, Department of Radiation Oncology, Stritch School of Medicine, Loyola University Chicago, Stritch School of Medicine Loyola University Chicago, Cardinal Bernardin Cancer Center, Loyola University Chicago
Abstract Preview: Purpose: Markerless tumor tracking (MTT) using dual-energy (DE) subtraction imaging is being considered as a non-invasive method to track tumors during lung cancer treatment. Prior to clinical impleme...
Authors: Xiangli Cui, Chi Han, Man Hu, Wanli Huo, Xunan Wang, Jianguang Zhang, Yingying Zhang
Affiliation: Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Departments of Radiation Oncology, Zibo Wanjie Cancer Hospital, Department of Oncology, Xiangya Hospital, Central South University, China Jiliang University, the Zhejiang-New Zealand Joint Vision-Based Intelligent Metrology Laboratory, College of Information Engineering, China Jiliang University, Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University, Shandong Academy of Medical Sciences, China Jiliang University,
Abstract Preview: Purpose:
Medical image generation has broad application prospects in deep learning, but the model training effect is often limited due to the lack of real image data. This study aims to explore the...
Authors: Rituparna Basak, Maede Boroji, Renee F Cattell, Vahid Danesh, Imin Kao, Kartik Mani, Xin Qian, Samuel Ryu, Tiezhi Zhang
Affiliation: Stony Brook Medicine, Stony Brook University, Washington University in St. Louis, Stony Brook University Hospital
Abstract Preview: Purpose: Fundamental qualitative characteristics physicians use to differentiate skin lesion subtypes include asymmetry, border irregularity, and color. Radiomic features have potential to quantify th...
Authors: Curtiland Deville, Rachel B. Ger, Elaina Hales, Heng Li, Todd R. McNutt
Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Johns Hopkins University
Abstract Preview: Purpose: Lack of specialized coding knowledge limits the use of data from large SQL repositories. We aimed to develop intuitive user interfaces for a registry that allows users to visualize the relati...
Authors: Eric C. Ford, Yulun He, Minsun Kim, Dustin Melancon, Juergen Meyer, Dong Joo Rhee, Yinghua Tao
Affiliation: Department of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, MD Anderson Cancer Center, University of Washington
Abstract Preview: Purpose: To develop and evaluate an automated-planning technique capable of generating high-quality treatment plans for hippocampal-sparing-whole-brain radiation therapy.
Methods: An auto-planning ...
Authors: Hoyeon Lee
Affiliation: University of Hong Kong
Abstract Preview: Purpose: Deep-learning approaches are widely investigated for Cone-Beam CT (CBCT) scatter correction to improve the quality of the linear-accelerator mounted CBCT. This study aims to optimize the deep...
Authors: Annie Cooney, Kenneth L. Homann, Somayeh Taghizadehghahremanloo, Adam D. Yock, Hong Zhang
Affiliation: Assistant Professor, Vanderbilt University Medical Center
Abstract Preview: Purpose:
Digital radiotherapy data has been standardized using the DICOM format. However, different radiotherapy software environments interpret identical data differently due to inherent software ...
Authors: Kevin Peter Risolo
Affiliation: University of Pennsylvania
Abstract Preview: Purpose: To quantify the improved efficiency of checking patient treatment plan MU by utilizing RadFormation’s ClearCalc script-based program.
Methods: A total of 58 patients planned for treatment ...
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: Ibtisam Almajnooni, Siyong Kim, Nathaniel Miller, Elisabeth Weiss, Lulin Yuan
Affiliation: Virginia Commonwealth University
Abstract Preview: Purpose: Radiation-induced esophagitis (RE) is a common concern in lung cancer IMRT. Recent studies have indicated that the risk of radiation side effects varies greatly with patients’ baseline clinic...
Authors: Jiankui Yuan, Dandan Zheng, Tingliang Zhuang
Affiliation: Medical Artificial Intelligence and Automation (MAIA) Laboratory, Department of Radiation Oncology, UT Southwestern Medical Center, University of Rochester, Varian Medical Systems, Advanced Oncology Solutions
Abstract Preview: Purpose: In Monte Carlo (MC) radiation therapy dose calculations, latent variance exists when directly applying phase-space files (PSF) with a finite number of source particles, while the latter is pr...
Authors: Sagine Berry-Tony, Lasya Daggumati, James R Duncan, Melak Senay, Allan Thomas
Affiliation: University of Missouri-Kansas City School of Medicine, Mallinckrodt Institute of Radiology, Washington University School of Medicine, Washington University in St. Louis
Abstract Preview: Purpose: Most acquired images in FGIs are not permanently archived. In the context of modern computational prowess, novel improvements to FGI practice likely sit just under the surface of large-scale ...
Authors: Caiden Atienza, Daniel E. Hyer, Samuel D. Rusu, Blake R. Smith, Joel J. St-Aubin
Affiliation: Iowa Health Care, University of Iowa
Abstract Preview: Purpose: Pinnacle3 TPS (Philips Radiation Oncology Systems, Fitchburg, WI, USA) support is set to end by December 31, 2026. This work presents a validated method to archive Pinnacle data, which may be...