Authors: Lorenzo Arsini, Andrea Ciardiello, Fabio Massimo D'Amore, Stefano Giagu, Federico Giove, Carlo Mancini-Terracciano, Cecilia Voena
Affiliation: Istituto Superiore di SanitĂ , Sapienza University of Rome, UniversitĂ Sapienza Roma, Magnetic Resonance for Brain Investigation Laboratory, Museo Storico della Fisica e Centro di Studi e Ricerche Enrico Fermi
Abstract Preview: Purpose: To leverage newly developed heteronuclear magnetic resonance imaging (MRI) techniques, particularly sodium (23Na) imaging, for identifying potential biomarkers of Alzheimer's diseaseâsuch as ...
Authors: Ross I. Berbeco, Vera Birrer, Raphael Bruegger, Pablo Corral Arroyo, Roshanak Etemadpour, Dianne M. Ferguson, Rony Fueglistaller, Thomas C. Harris, Yue-Houng Hu, Matthew W. Jacobson, Mathias Lehmann, Nicholas Lowther, Daniel Morf, Marios Myronakis
Affiliation: Brigham and Women's Hospital, Harvard Medial School, Dana-Farber Cancer Institute, Department of Radiation Oncology, Dana Farber/Brigham and Women's Cancer Center, Department of Radiation Oncology, Brigham and Womenâs Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Brigham and Womens Hospital, Dana Farber Cancer Institute, Harvard Medical School, Brigham and Women's Hospital, Varian Imaging Laboratory, Dana-Farber Cancer Institute
Abstract Preview: Purpose: A challenge for dual energy CBCT is that noise and residual errors in material decomposition steps can become amplified when forming low energy, high contrast virtual mono-energetic images (V...
Authors: Suman Gautam, Tianjun Ma, William Song
Affiliation: Virginia Commonwealth University
Abstract Preview: Purpose: We propose an artificial intelligence (AI)-based method to rapidly predict the patient-speciïŹc quality assurance (PSQA) results for magnetic resonance (MR)-guided online adaptive radiation th...
Authors: Yu Chang, Mei Chen
Affiliation: Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Department of Radiation Oncology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine
Abstract Preview: Purpose: Spot weights optimization, as a critical step in the proton therapy, is often time-consuming and labor-intensive. Deep learning, with its powerful learning and computational efficiency, can e...
Authors: Mingli Chen, Xuejun Gu, Hao Jiang, Mahdieh Kazemimoghadam, Weiguo Lu, Gregory Szalkowski, 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: Respiratory motion management is crucial for accurate radiation delivery to moving targets while protecting healthy tissue, relying on time-resolved volumetric imaging and continuous deformab...
Authors: Benito De Celis Alonso, Braian Adair Maldonado Luna, Gerardo Uriel Perez Rojas, RenĂ© Eduardo RodrĂguez-PĂ©rez, Kamal Singhrao
Affiliation: Department of Radiation Oncology, Brigham and Women's Hospital, Dana Farber Cancer Institute, Harvard Medical School, Faculty of Physics and Mathematics, Benemérita Universidad Autónoma de Puebla
Abstract Preview: Purpose: Artificial Intelligence (AI)-generated synthetic CT (sCT) images can be used to provide electron densities for dose calculation for online adaptive MRI-guided stereotactic body radiotherapy (...
Authors: Drexell Hunter Boggs, Carlos E. Cardenas, Allison Dalton, John B Fiveash, Joel A. Pogue, Richard A. Popple, Farnaz Rahim Li
Affiliation: The University of Alabama at Birmingham, University of Alabama at Birmingham
Abstract Preview: Purpose: External-beam Accelerated Partial Breast Irradiation (APBI) using stereotactic-body radiotherapy (SBRT) is increasingly adopted as an alternative to whole-breast radiation, offering targeted ...
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: Matthew S Brown, Joshua Genender, John M. Hoffman, Gabriel Melendez-Corres, Muhammad W. Wahi-Anwar
Affiliation: David Geffen School of Medicine at UCLA, UCLA Department of Radiology
Abstract Preview: Purpose: Renal lesions are evaluated using scoring systems based on visual assessments and manual measurements. The purpose of this work is to develop a multi-agent system for automated anatomic landm...
Authors: Courtney R. Buckey, Jay W. Burmeister, Minsong Cao, Grace Chang, Yu Kuang, Yixiang Liao, Yi Rong, Dandan Zheng
Affiliation: Mayo Clinic, Mayo Clinic Arizona, Karmanos Cancer Center, Gershenson ROC, Wayne State University School of Medicine, Department of Radiation Oncology, University of California, Los Angeles, Medical Physics Program, University of Nevada, Rush University Medical Center, University of Rochester
Abstract Preview: Purpose: Investigate the adequacy of training for therapeutic medical physics residents in select special procedures.
Methods: After a review of existing literature, a multi-institutional group dev...
Authors: Dequan Chen, Jason Michael Holmes, Tianming Liu, Wei Liu, Zhengliang Liu, Jiajian Shen, Peilong Wang
Affiliation: Department of Radiology, Mayo Clinic, Department of Radiation Oncology, Mayo Clinic, School of Computing, University of Georgia
Abstract Preview: Purpose:
We present a study to evaluate the performance of large language models (LLMs) in answering radiation oncology physics questions, focusing on the recently released models.
Methods:
A...
Authors: Rani Anne', Wenchao Cao, Yingxuan Chen, Wookjin Choi, Firas Mourtada, Yevgeniy Vinogradskiy
Affiliation: Thomas Jefferson University
Abstract Preview: Purpose: In-room mobile cone-beam CT (CBCT) is emerging to enhance high-dose-rate (HDR) brachytherapy workflow using on-demand imaging. However, metal artifacts from X-ray markers inside gynecological...
Authors: Yankun Lang, Lei Ren, Leshan Sun, Liangzhong Xiang, Yifei Xu, Jie Zhang
Affiliation: University of Maryland School of Medicine, University of California, Irvine
Abstract Preview: Purpose: To achieve the full-view image from a single-view sinogram using a two-stage deep learning model for electroacoustic-tomography (EAT), which is an emerging imaging technique with significant ...
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: Zachary Buchwald, Zach Eidex, Richard L.J. Qiu, Justin R. Roper, Mojtaba Safari, Hui-Kuo Shu, Xiaofeng Yang, David Yu
Affiliation: Emory University and Winship Cancer Institute, Emory University, Department of Radiation Oncology and Winship Cancer Institute, Emory University
Abstract Preview: Purpose: Gadolinium-based contrast agents (GBCA) are commonly used for patients with gliomas to delineate and characterize the brain tumors using T1-weighted (T1W) MRI. However, there is a rising conc...
Authors: Hilary P Bagshaw, Mark K Buyyounouski, Cynthia Fu-Yu Chuang, Yu Gao, Dimitre Hristov, Lianli Liu, Lawrie Skinner, Lei Xing
Affiliation: Department of Radiation Oncology, Department of Radiation Oncology, Stanford University
Abstract Preview: Purpose:
MR-guided radiation therapy has introduced a significant leap in cancer treatment by allowing adaptive treatment. The low-field MR-guided system predominantly uses the TrueFISP sequence, w...
Authors: Pradeep Bhetwal, Wookjin Choi, Adam Dicker, Rupesh Ghimire, Yingcui Jia, Lauren Nkwonta, Yevgeniy Vinogradskiy, Wentao Wang, Maria Werner-Wasik
Affiliation: Thomas Jefferson University
Abstract Preview: Purpose: Multi-disciplinary clinics are becoming standard of care for patients with lung cancer treated with SBRT. To improve clinical decision support in a multi-disciplinary clinic, it would be bene...
Authors: Giovanni Iacca, Gloria Miori, Laura Orsingher, Daniele Ravanelli, Annalisa Trianni
Affiliation: Department of Information Engineering and Computer Science, University of Trento, Medical Physics Department, S.Chiara Hospital, APSS
Abstract Preview: Purpose: This study aims to leverage artificial intelligence (AI) to predict and identify performance degradation in Digital Radiography (DR) systems, enabling proactive maintenance and minimizing cli...
Authors: Sean P. Devan, Cory S. Knill, Charles K. Matrosic, Zheng Zhang
Affiliation: University of Michigan
Abstract Preview: Purpose: Physicists troubleshooting machine issues during patient treatments often face high-pressure situations, balancing error codes, resource constraints, and time-sensitive decisions. To streamli...
Authors: Adayabalam Balajee, Elijah Berberette, Maria Escalona, Dray Gentry, Chester R. Ramsey, Terri Ryan
Affiliation: ORAU, Thompson Proton Center, University of Tennessee
Abstract Preview: Purpose:
Dicentric chromosomes, characterized by two centromeres on a single chromosome, are key biomarkers in biological dosimetry for quantifying ionizing radiation exposure. However, manual dete...
Authors: Kyle Cuneo, Issam M. El Naqa, Dale W. Litzenberg, Yiming Liu, Xueding Wang, Lise Wei, Wei Zhang, Jiaren Zou
Affiliation: University of Michigan, H. Lee Moffitt Cancer Center
Abstract Preview: Purpose: To quantitatively map 3D dose deposition during radiotherapy, empowering real-time adaptive radiation treatment.
Methods: The research features reconstructing dose deposition from acou...
Authors: Zachary Buchwald, Chih-Wei Chang, Zach Eidex, Richard L.J. Qiu, Mojtaba Safari, Shansong Wang, Xiaofeng Yang, David Yu
Affiliation: Emory University and Winship Cancer Institute, Emory University, Department of Radiation Oncology and Winship Cancer Institute, Emory University
Abstract Preview: Purpose: MRI offers excellent soft tissue contrast for diagnosis and treatment but suffers from long acquisition times, causing patient discomfort and motion artifacts. To accelerate MRI, supervised d...
Authors: Meixu Chen, Jing Wang
Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, UT Southwestern Medical Center
Abstract Preview: Purpose: Cancer treatment outcome prediction plays a pivotal role in guiding therapeutic decisions and optimizing patient care. Traditionally, binary prediction models have been widely used for risk s...
Authors: Jie Hu, Zhengdong Jiang, Nan Li, Tie Lv, Yuqing Xia, Shouping Xu, Gaolong Zhang, Wei Zhao, Changyou Zhong
Affiliation: School of Physics, Beihang University, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Radiotherapy Department of Meizhou Peopleâs Hospital (Huangtang Hospital), UT Health San Antonio, National Cancer Center/ National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, PeopleÊŒs Republic of China, Department of Radiation Oncology
Abstract Preview: Purpose: Patients usually undergo cone-beam computed tomography (CBCT) scans which are used for patient set-up before radiotherapy. However, the low image quality of CBCT hinders its use in adaptive r...
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: Chuangxin Chu, Haotian Huang, Tianhao Li, Jingyu Lu, Zhenyu Yang, Fang-Fang Yin, Tianyu Zeng, Chulong Zhang, Yujia Zheng
Affiliation: The Hong Kong Polytechnic University, Nanyang Technological University, Australian National University, Medical Physics Graduate Program, Duke Kunshan University, North China University of Technology, Duke Kunshan University
Abstract Preview: Purpose: Deep learning segmentation models, such as U-Net, rely on high-quality image-segmentation pairs for accurate predictions. However, the recent increasing use of generative networks for creatin...
Authors: Kyle J. Lafata, Xiang Li, Megan K. Russ, Zion Sheng
Affiliation: Duke University, Department of Radiation Oncology, Duke University, Clinical Imaging Physics Group, Department of Radiology, Duke University Health System
Abstract Preview: Purpose: To adapt Vision-Language Foundational Models (VLFM) to perform HNSCC tumor grading on H&E whole slide images (WSI) via attention-based multiple instance learning (ABMIL).
Methods: We utili...
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: David L. Barbee, David Byun, Matt Long, Jose R. Teruel Antolin, Michael J Zelefsky
Affiliation: NYU Langone Health
Abstract Preview: Purpose:
Online adaptive MR-Linac therapy requires contour adaptation, often adding 20 minutes to treatment time and reducing machine throughput. This study introduces a fully automated MR contour ...
Authors: Chase Cochran, Shane McCarthy, Damodar Pokhrel, William St Clair
Affiliation: University of Kentucky, Department of Radiation Medicine, University of Kentucky, Radiation Medicine
Abstract Preview: Purpose: Manually generating intraocular stereotactic radiosurgery (SRS) plans involves significant challenges, including lengthy planning times and inter-planner variability. Knowledge-based SRS plan...
Authors: Hongyi Jiang, Fang-Fang Yin
Affiliation: Duke University, Medical Physics Graduate Program, Duke Kunshan University
Abstract Preview: Purpose:
Imaging moving tissues using PET-CT can be difficult. Separating signal into phases during construction reduces signal count and increases influence of noise. Algorithms that use signal fr...
Authors: Laurence Edward Court, Raphael Douglas, David Fuentes, Anuja Jhingran, Barbara Marquez, Raymond Mumme, Christine Peterson, Julianne M. Pollard-Larkin, Surendra Prajapati, Dong Joo Rhee, Thomas J. Whitaker
Affiliation: MD Anderson Cancer Center, The University of Texas MD Anderson Cancer Center, MD Anderson, Department of Radiation Physics, The University of Texas MD Anderson Cancer Center
Abstract Preview: Purpose: Safe deployment of auto-contouring models requires the inclusion of automated quality assurance (QA). One approach is to use an independent auto-contouring model and compare the contours geom...
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: Hua-Chieh Shao, Chenyang Shen, Jiacheng Xie, Shunyu Yan, You Zhang
Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, UT Southwestern Medical Center, Medical Artificial Intelligence and Automation (MAIA) Laboratory, Department of Radiation Oncology, UT Southwestern Medical Center, Medical Artificial Intelligence and Automation (MAIA) Laboratory, Department of Radiation Oncology, UT Southwestern Medical Center, The University of Texas at Dallas
Abstract Preview: Purpose: Motion-resolved CBCT imaging, which reconstructs a dynamic sequence of CBCTs reflecting intra-scan motion (one CBCT per x-ray projection), is highly desired for regular/irregular motion chara...
Authors: Liyuan Chen, Steve Jiang, Chenyang Shen
Affiliation: Department of Radiation Oncology, UT Southwestern Medical Center, UT Southwestern Medical Center
Abstract Preview: Purpose: Delays in radiation therapy (RT) initiation caused by conventional CT simulation processes can hinder timely treatment delivery and patient outcomes. This study proposes a Virtual Treatment S...
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: Evan Calabrese, Edward Robert Criscuolo, Deshan Yang
Affiliation: Duke University, Department of Radiation Oncology, Duke University
Abstract Preview: Purpose: Glioblastoma (GBM) is the most common and aggressive form of brain cancer. Deformable image registration (DIR) is a powerful tool to compute anatomical changes in longitudinal MRI scans, whic...
Authors: Sam Beddar, Jason Michael Holmes, Daniel G. Robertson, James J. Sohn, Ethan D. Stolen
Affiliation: Department of Radiation Oncology, Mayo Clinic, MD Anderson Cancer Center, Department of Radiation & Cellular Oncology, University of Chicago, Department of Radiation and Cellular Oncology, University of Chicago
Abstract Preview: Purpose: Camera-based scintillation dosimetry incorporating large volumes have shown promise for fast and comprehensive evaluation of external beam treatment fields. While some efforts have been made ...
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:
PET is used in radiotherapy workflows for accurate target delineation. However, a separate CT scan is typically required for attenuation correction in PET imaging and for registering PET-d...
Authors: Sahaja Acharya, Matthew Ladra, Junghoon Lee, Lina Mekki, Bohua Wan
Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Department of Biomedical Engineering, Johns Hopkins University, Department of Computer Science, Johns Hopkins University
Abstract Preview: Purpose: Cerebellar mutism syndrome (CMS) is the most frequently observed complication in children undergoing surgical resection of posterior fossa tumors. Previous work explored lesion to symptom map...
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: Haijian Chen, Katja M. Langen, William Andrew LePain, Claire Tran, Mingyao Zhu
Affiliation: Emory Healthcare, Emory University, Georgia Institute of Technology
Abstract Preview: Purpose: To validate the performance of a commercial deep-learning segmentation (DLS) tool for head and neck cancer (HNC) and thoracic and abdominal cancer (TAC) by comparing it to manual segmentation...
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: Theodore Higgins Arsenault, Beatriz Guevara, Rojano Kashani, Raymond F. Muzic, Gisele Castro Pereira, Alex T. Price
Affiliation: University Hospitals Seidman Cancer Center, Case Western Reserve University Department of Biomedical Engineering
Abstract Preview: Purpose: Accurate dose prediction in radiotherapy is essential for treatment planning. This study evaluates four nnUnet-based models using the OpenKBP head and neck dataset: a baseline model (Model 1)...
Authors: Eric N Carver, Julia Marks
Affiliation: Brown University
Abstract Preview: Purpose: The clinical applicability of radiomic features is hindered by challenges in stability and reproducibility. To address this, researchers are establishing image and feature standardizations an...
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: 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: Mauro Carrara, Olivera Ciraj Bjelac, John E. Damilakis, Andre L. Dekker, Serafina Di Gioia, Renato Padovani, Egor Titovich, Qingrong Jackie Wu
Affiliation: University of Crete, Duke University Medical Center, Maastro Clinic, Dosimetry and Medical Radiation Physics Section, Division of Human Health, International Atomic Energy Agency, International Centre for Theoretical Physics
Abstract Preview: Purpose: The purpose of this work is to present the International Atomic Energy Agency (IAEA) activity in providing medical physicists (MPs) with knowledge, skills, and competencies to support the saf...
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: 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: Hector Andrade-Loarca, Ines Butz, Chiara Gianoli, Prof. Gitta Kutyniok, Jianfei Li, Katia Parodi, Prof. Vincenzo Patera, Angelo Schiavi, Prof. Ozan Ăktem
Affiliation: Sapienza University of Rome, Department of Mathematics, Royal Institute of Technology, School of Computation, Information and Technology, Technische Universitaet Muenchen, Department of Medical Physics, Ludwig-Maximilians-UniversitĂ€t MĂŒnchen (LMU Munich), Department of Mathematics, Ludwig-Maximilians-UniversitĂ€t (LMU) MĂŒnchen, Department of Medical Physics, Ludwig-Maximilians-UniversitĂ€t (LMU) MĂŒnchen
Abstract Preview: Purpose: To explore and demonstrate the feasibility of accurate and fast prediction of the water equivalent thickness (WET) distribution of tissue traversed by a proton imaging pencil beam, aiming at ...
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: Zixu Guan, Takahiro Iwai, Takashi Mizowaki, Mitsuhiro Nakamura, Michio Yoshimura
Affiliation: Kyoto University, Department of Radiation Oncology and Image-applied Therapy, Graduate School of Medicine, Kyoto University
Abstract Preview: Purpose:
The goal of this study is to develop a fully automated treatment planning approach for VMAT in pancreatic cancer that can convert patient anatomy into LINAC machine parameters. In this wor...
Authors: Fumiaki Komatsu, Shunsuke Moriya, Ryosuke Nakamura, Takeji Sakae, Toshiyuki Terunuma, Tetsuya Tomita
Affiliation: Graduate School of Comprehensive Human Sciences, University of Tsukuba, Institute of Medicine, University of Tsukuba, Proton Medical Research Center, University of Tsukuba, Department of Radiology, University of Tsukuba Hospital
Abstract Preview: Purpose: To develop a deep learning (DL) model capable of accurately tracking lung tumors independent of beam angle variations.
Methods: A thoracic dynamic phantom simulating lung motion in the sup...
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: Xiaoyu Duan, Xiang Li, Wenbo Wan, Lei Zhang, Yiwen Zhang
Affiliation: Duke University, Medical Physics Graduate Program, Duke Kunshan University
Abstract Preview: Purpose: Breast screening has been proved to reduce breast cancer mortality by early detection and treatment for patients. Mammography is the most common and widely used technique for breast cancer sc...
Authors: Maryellen L. Giger, Fahd Hatoum, Robert Tomek, Heather M. Whitney
Affiliation: The University of Chicago
Abstract Preview: Purpose: To assess the importance of applying stratified sampling across demographic attributes (including age, sex, race, and ethnicity) when constructing training and testing datasets for ML-based d...
Authors: Jean Dessureault, Malcolm R. McEwen, Bryan R. Muir, James Renaud
Affiliation: National Research Council
Abstract Preview: Purpose: To develop and commission a mailable calorimeter that enables clinical medical physicists to quickly and efficiently address innovative dosimetry challenges directly at the point of use.
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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: Lucy Jiang, Chengyu Shi
Affiliation: Department of Radiation Oncology, City of Hope Orange County, Amity Regional High School (10th Grade)
Abstract Preview: Purpose: Early-stage breast cancer is common among females, with typically high local tumor control rates (LCR). Brachytherapy is a common way to achieve LCR following surgery. However, the patients m...
Authors: Michael Burke, David J. Carlson, Yiu-Hsin Chang, Huixiao Chen, Zhe (Jay) Chen, Emily A. Draeger, Dae Yup Han, Vanessa Hill, Ann-Teresa Jasman, John Kim, Svetlana Kuznetsova, MinYoung Lee, Daniel Longo, Henry S. Park, Adam Shulman, Lauren Tressel, Weili Zhong
Affiliation: Department of Therapeutic Radiology, Yale University School of Medicine
Abstract Preview: Purpose:
The complexity of biology-guided radiotherapy (BgRT), particularly with systems like RefleXion X1, necessitates robust pre-treatment quality assurance (QA) to ensure patient safety, treatm...
Authors: Abid Khan, Chad Klochko, Michael J Kovalchick, Hyeok Jun Lee, Hani Nasr, Krishnan Shyamkumar, Kundan S Thind
Affiliation: Henry Ford Radiology, Wayne State University, Henry Ford Health, HFHS
Abstract Preview: Purpose: Automated vascular segmentation in interventional angiography is challenged by contrast kinetics, vessel variations, and 2D projections, limiting the effectiveness of single-model approaches....
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 Childrenâs Research Hospital, The University of Texas MD Anderson Cancer Center, Department of Oncology, St. Jude Childrenâs 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 Childrenâs 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: Parker Anderson, Elizabeth L. Bossart, Jonathan Cyriac, Nesrin Dogan, Robert Kaderka, Yihang Xu
Affiliation: University of Miami, University of Miami, Sylvester Comprehensive Cancer Center, University of Miami Sylvester Comprehensive Cancer Center
Abstract Preview: Purpose:
Knowledge-based planning (KBP) can enhance the treatment planning process in cancer radiotherapy (RT). By training a KBP model with high-quality treatment plans developed by experts, dose-...
Authors: Ming Chao, Hao Guo, Tenzin Kunkyab, Yang Lei, Tian Liu, Kenneth Rosenzweig, Robert Samstein, James Tam, Junyi Xia, Jiahan Zhang
Affiliation: Icahn School of Medicine at Mount Sinai
Abstract Preview: Purpose:
The aim of the study is to develop a trade-off prediction model to efficiently guide the treatment planning process for patients with stage III non-small cell lung cancer (NSCLC).
Metho...
Authors: Rafe A. McBeth, Ayoola Okuribido, Rodney D. Wiersma
Affiliation: Department of Radiation Oncology, University of Pennsylvania, University of Pennsylvania, UCLA
Abstract Preview: Purpose: To develop a method for standardizing data collected during quality assurance checks across institutions using language models.
Background: QA procedures and data management can vary widel...
Authors: Rafe A. McBeth, Ayoola Okuribido, Rodney D. Wiersma
Affiliation: Department of Radiation Oncology, University of Pennsylvania, University of Pennsylvania, UCLA
Abstract Preview: Purpose: To develop a method for standardizing data collected during quality assurance checks across institutions using language models.
Background: QA procedures and data management can vary widel...
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 Childrenâs 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 Childrenâs 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: James E. Bates, Benjamin Hopkins, Kirk Luca, Shadab Momin, Justin R. Roper, Soumon Rudra, Eduard Schreibmann, Bill Stokes, Tu Thi, Xiaofeng Yang
Affiliation: Emory University, Department of Radiation Oncology and Winship Cancer Institute, Emory University
Abstract Preview: Purpose: Swallowing dysfunctions after radiotherapy are caused by multiple factors yet are strongly associated with the irradiation of pharyngeal musculature due to its role in the initiation and comp...
Authors: Lei Ren, Jie Zhang
Affiliation: University of Maryland School of Medicine
Abstract Preview: Purpose: 4D-CBCT is valuable for imaging anatomy affected by respiratory motions to guide radiotherapy delivery. However, 4D-CBCT often has undersampled projections acquired in each respiratory phase ...
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: Ameer Elaimy, Theodore Lawrence, Charles S. Mayo, Seyyedeh Azar Oliaei Motlagh, Benjamin S. Rosen
Affiliation: University of Michigan
Abstract Preview: Purpose: To analyze the impact of clinical features on short-term survival, toxicity, and poor outcomes in HCC patients treated with SBRT,using automated data aggregation and enhanced algorithms with ...
Authors: Ruth Afanador, Daniela Branco, John M Bryant, John Campbell, Clement Chaphuka, Samuel A. Einstein, David B. Flint, Jeffrey R. Kemp, Mussa Kumwembe, Daniel J Mollura, Joseph Weygand
Affiliation: RAD-AID International, The University of Texas MD Anderson Cancer Center, Department of Radiation Oncology and Applied Science, Dartmouth Health, UNC Health, Malawi National Cancer Center, Kamuzu Central Hospital, Penn State College of Medicine, Sutter Health, New York University, University of California San Diego / California Protons, Department of Radiation Oncology, Moffitt Cancer Center
Abstract Preview: Purpose: Malawi, a landlocked country in southeastern Africa with a population of over 20 million, ranks among the worldâs least-developed nations and has the fourth-lowest gross domestic product per ...
Authors: Rajeev Gupta, Shriram Ashok Rajurkar, Teerthraj Verma
Affiliation: King George's Medical University, King George's Medical University, UP
Abstract Preview: Purpose:
The volunteer deep inspiration breath hold (vDIBH) technique is used to reduce the heart dose in left breast cancer radiotherapy. Many times, it is faced that despite rigorous exercise and...
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: Louis Archambault, Nicolas Drouin, Alexis Horik, Simon Thibault
Affiliation: Département de Physique, de Génie Physique et D'optique, et Centre de Recherche sur le Cancer, Université Laval, Département de Physique, de Génie Physique et D'optique, et Centre d'optique, photonique et laser, Université Laval
Abstract Preview: Purpose: To develop a novel type of real-time 3D dosimeter for the quality assurance of linear accelerators used in external beam radiotherapy.
Methods: An experimental setup was constructed using ...
Authors: Sofia Beer, Menal Bhandari, Alec Block, Nader Darwish, Joseph Dingillo, Sebastien A. Gros, Hyejoo Kang, Andrew Keeler, Rajkumar Kettimuthu, Jason Patrick Luce, Ha Nguyen, John C. Roeske, George K. Thiruvathukal, Austin Yunker
Affiliation: Data Science and Learning Division, Argonne National 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, Department of Computer Science, Loyola University of Chicago
Abstract Preview: Purpose: Artificial intelligence (AI) generated synthetic medical images are seeing increased use in radiology and radiation oncology. Physician observer studies are an ideal way to evaluate the usabi...
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: 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: 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: Pouya Azarbar, Nima Kasraie, Mahsa Shahrbabki Mofrad, Peyman Sheikhzadeh
Affiliation: UT Southwestern Medical Center, Shahid Beheshti University of Medical science, Imam Khomeini Hospital Complex,Tehran University of Medical Sciences, Tehran University of Medical Science
Abstract Preview: Purpose: PET imaging become crucial in diagnosing and managing various diseases, but its key limitation is the lack of detailed anatomical information. Integrating CT-scans with PET images enhances cl...
Authors: Rashmi Bhaskara, Shravan Bhavsar, Ananth Grama, Oluwaseyi Oderinde, Shourya Verma
Affiliation: Purdue University
Abstract Preview: Generating Synthetic Positron Emission Tomography from Computed Tomography using Lightweight Diffusion Model for Head and Neck Cancer
Purpose: To generate synthetic PET tumor avidity segments direc...
Authors: Pouya Azarbar, Nima Kasraie, Peyman Sheikhzadeh
Affiliation: UT Southwestern Medical Center, Shahid Beheshti University of Medical science, Imam Khomeini Hospital Complex,Tehran University of Medical Sciences
Abstract Preview: Purpose: Positron Emission Tomography (PET) is crucial for diagnosing and monitoring diseases due to its functional imaging capabilities. However, its high cost, significant radiation exposure, and li...
Authors: Seth Amofa, Erli Chen, Samuel A. Einstein, Ekinadoese Imudia Frias, Nupur Karmaker, Yinus Kawthara, Dulguun Myagmarsuren, Travis C. Salzillo, Joseph Weygand, Afua A. Yorke
Affiliation: Department of Radiation Oncology and Applied Science, Dartmouth Health, University of Washington, Federal University Oye-Ekiti, Cheshire Medical Center, Dartmouth College, Penn State College of Medicine, Dept. of Medical Physics and Biomedical Engineering, Gono Bishwabidyalay, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Virginia Tech Carilion School of Medicine
Abstract Preview: Purpose: Recent developments in the medical physics job market have made it increasingly difficult for radiotherapy centers, particularly in rural areas, to recruit qualified therapeutic medical physi...
Authors: Stephen M. Avery, Izabella L. Barreto, Oi-Wai Chau, Cesar Della Biancia, Beata Gontova Bernat, Amanda M. Jackson, Rao Khan, Eugene P. Lief, Osama R. Mawlawi, Wilfred F. Ngwa, Christopher F. Njeh, Peter Allan Sandwall, William Swanson, Joseph Weygand, Afua A. Yorke
Affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center, VA Medical Center, Johns Hopkins University, Mayo Clinic, Champion Cancer Center, Howard University, UT MD Anderson Cancer Center, Department of Radiation Oncology and Applied Science, Dartmouth Health, University of Washington, University of Florida College of Medicine, Washington University in St Louis, Emory University, University of Pennsylvania, OhioHealth, Indiana University School of Medicine, Department of Radiation Oncology
Abstract Preview: Purpose: To assess needs of medical physicists working in low-and-middle-income countries (LMICs)
Methods: A survey was developed by AAPMâs Global Needs Assessment Committee (GNAC) in partnership w...
Authors: Enhui Chang, Yunfei Dong, Yifei Hao, Chengliang Jin, Shengsheng Lai, Yi Long, Mengni Wu, Yulu Wu, Ruimeng Yang, Zhenyu Yang, Yue Yuan, Lei Zhang, Wanli Zhang, Yaogong Zhang
Affiliation: Duke Kunshan University, Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Medical Physics Graduate Program, Duke Kunshan University
Abstract Preview: Purpose: Macrotrabecular-Massive Hepatocellular Carcinoma (MTM-HCC) is one type of liver cancer showed minimum image signature for accurate non-invasive diagnosis. This study aims to develop and evalu...
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: Manju Liu, Weiwei Sang, Yanyan Shi, Zhenyu Yang, Fang-Fang Yin, Chulong Zhang, Lihua Zhang, Rihui Zhang
Affiliation: Jiahui International Hospital, Jiahui International Hospital, Radiation Oncology, Duke Kunshan University, Medical Physics Graduate Program, Duke Kunshan University
Abstract Preview: Purpose: This study aims to transform cone-beam computed tomography (CBCT) images acquired from deep inspiration breath-hold (DIBH) breast cancer patients into high-fidelity synthetic CT (sCT) images....
Authors: Drexell Hunter Boggs, Carlos E. Cardenas, Jingwei Duan, Joseph Harms, Joel A. Pogue, Richard A. Popple, Courtney Bosse Stanley, Dennis N. Stanley, Sean Xavier Sullivan, Natalie N. Viscariello
Affiliation: Washington University in St. Louis, The University of Alabama at Birmingham, University of Alabama at Birmingham
Abstract Preview: Purpose: CBCT-guided online adaptive radiation therapy (OART) with Ethos for stereotactic accelerated partial breast irradiation (APBI) can mitigate inter-fraction variation, leading to dosimetric adv...
Authors: So Hyun Ahn, Chris Beltran, Byongsu Choi, Jeong Heon Kim, Jin Sung Kim, Bo Lu, Justin Chunjoo Park, Bongyong Song, Jun Tan
Affiliation: Mayo Clinic, Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Ewha Medical Research Institute, Ewha Womans University College of Medicine, UC San Diego, Yonsei University College of Medicine
Abstract Preview: Purpose:
Cone-beam computed tomography (CBCT) is widely used in IGRT for patient positioning but suffers from low resolution and poor soft tissue contrast. Synthetic CT (sCT) generated from CBCT ad...
Authors: Renee Farrell, Jinkoo Kim, Xin Qian, Ziyu Shu, Zhaozheng Yin, Tiezhi Zhang
Affiliation: Stony Brook Medicine, Washington University in St. Louis, Stony Brook University, Stony Brook University Hospital
Abstract Preview: Purpose: Ultra-short CT scan allows fast imaging speed, dose reduction, and compact system design. We developed a deep image prior (DIP) based reconstruction method named Hybrid Prior-Enhanced Deep Im...
Authors: James M. Lamb, Dishane Chand Luximon, Jack Neylon, Rachel Petragallo, Moritz Ritter, Timothy Ritter
Affiliation: Department of Radiation Oncology, University of California, Los Angeles, ETH Zurich, VCU Health System, Department of Radiation Oncology, University of Colorado
Abstract Preview: Purpose: Anomalies in cone beam computed tomography (CBCT) radiotherapy image guidance can signal treatment deviations. Repetitive review of setup image registrations by humans is inefficient, prone t...
Authors: Hilary P Bagshaw, Mark K Buyyounouski, Serdar Charyyev, Xianjin Dai, PhD, Yu Gao, Thomas R. Niedermayr, Lei Xing
Affiliation: Department of Radiation Oncology, Stanford University
Abstract Preview: Purpose: Real-time transrectal ultrasound imaging is the gold standard for needle placement and treatment planning of real-time based-ultrasound-based high dose-rate (HDR) prostate brachytherapy. Cumu...
Authors: Marissa Brown, Geoffrey D. Clarke, Luke Norton
Affiliation: University of Texas Health Science Center at San Antonio
Abstract Preview: Purpose: To evaluate how different learning strategies affect convolutional neural network (CNN) estimates of the liver's intravoxel incoherent motion (IVIM) parameters.
Methods: A 3-stage U-Net wa...
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: Mahya Ahmadzadeh, Nagarajan Kandasamy, Keyur Shah, Gregory C. Sharp, Santhosh Vadivel, John MacLaren Walsh
Affiliation: Electrical and Computer Engineering Department, Massachusetts General Hospital, Emory University, Drexel University
Abstract Preview: Purpose: In image-guided radiotherapy (IGRT), cone beam CTs (CBCTs) suffer from distortions that degrade registration with planning CTs. While CycleGANs can generate synthetic CTs (sCTs) from CBCTs, e...
Authors: Minbin Chen, Xiaoyi Dai, Xiaoyu Duan, Chunhao Wang, Fan Xia, Zhenyu Yang, Fang-Fang Yin, Chulong Zhang, Rihui Zhang
Affiliation: Duke University, Duke Kunshan University, Medical Physics Graduate Program, Duke Kunshan University, The First People's Hospital of Kunshan
Abstract Preview: Purpose: Deep learning (DL)-based mammography diagnosis presents unique challenges, as accurate interpretation requires both global breast condition analysis and local lesion structural information. E...
Authors: Fang-Fang Yin, Lei Zhang, Yaogong Zhang
Affiliation: Medical Physics Graduate Program, Duke Kunshan University
Abstract Preview: Purpose: Rotational symmetry is an inherent property of many tomography systems (e.g., CT, PET, SPECT), arising from the circular arrangement or rotation of detectors. This study revisits the image re...
Authors: Steve B. Jiang, Chien-Yi Liao, Dan Nguyen, Daniel Yang, Hengrui Zhao
Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center
Abstract Preview: Purpose:
Post-operative radiotherapy for prostate cancer requires precise contouring of the clinical target volume (CTV) to account for microscopic disease that is invisible in the image. However, ...
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: 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: Mark Anastasio, Hua Li, Zhuchen Shao
Affiliation: Washington University School of Medicine, University of Illinois Urbana-Champaign
Abstract Preview: Purpose: Ill-conditioned reconstruction problems in medical imaging, such as those arising from undersampled k-space data in MRI, can result in degraded image quality and clinical task-orientated perf...
Authors: Amanda J. Deisher, Andrew YK Foong, Witold Matysiak, Jing Qian, Xueyan Tang, Erik J. Tryggestad, Mi Zhou
Affiliation: Mayo Clinic
Abstract Preview: Purpose: Phase gating is commonly employed to mitigate the impact of tumor motion in radiotherapy. Due to the machine-specific time delay between triggering and radiation delivery, the triggering sign...
Authors: Xiangli Cui, Zilei Fu, Man Hu, Wanli Huo, Xiaoqing Wu, Jianguang Zhang, Yingying Zhang
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, Department of Oncology, Xiangya Hospital, Central South University, Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University, Shandong Academy of Medical Sciences
Abstract Preview: Purpose:
Using Stable Diffusion to generate images of the knee in different disease states can enrich the medical imaging database and inject new vitality into the field of medical imaging analysis...
Authors: Justus Adamson, John Ginn, Yongbok Kim, Ke Lu, Trey Mullikin, Xiwen Shu, Chunhao Wang, Zhenyu Yang, Jingtong Zhao
Affiliation: Duke University, Duke Kunshan University
Abstract Preview: Purpose:
To develop a knowledge-based deep model for synthetic CT (sCT) generation from a single MR volume in frameless radiosurgery (SRS), eliminating the need for CT simulation prior to the SRS d...
Authors: Gregory A Azzam, Michael Butkus, Nesrin Dogan, Robert Kaderka, Nhan Vu, Yihang Xu
Affiliation: University of Miami, Department of Radiation Oncology, University of Miami, University of Miami Sylvester Comprehensive Cancer Center, University of Miami, Sylvester Comprehensive Cancer Center
Abstract Preview: Purpose: Knowledge-based planning (KBP) has demonstrated potential for improving planning quality and efficiency. Adoption of KBP in particle therapy has been slow due to limited number of plans to tr...
Authors: Mojtaba Behzadipour, Suman Gautam, Tianjun Ma, Ikchit Singh Sangha, Bongyong Song, William Song, Kumari Sunidhi
Affiliation: UC San Diego, Virginia Commonwealth University
Abstract Preview: Purpose: This study aims to develop a knowledge-based voxel-wise dose prediction system using a convolutional neural network (CNN) for high-dose-rate (HDR) prostate brachytherapy and to evaluate its p...
Authors: Victoria Susan Ainsworth, Stephen M. Avery, Serhii Brovchuk, Thomas Brown, Sean A. Dresser, Matthew D. Goss, Viktor M. Iakovenko, Kelly Kisling, Nataliya Kovalchuk, Robert F. Krauss, Wilfred F. Ngwa, Jatinder R. Palta, Julie A. Raffi, Peter Allan Sandwall, Natalka Suchowerska, William Swanson, Shada J. Wadi-Ramahi, Ruslan Zelinskyi
Affiliation: Allegheny Hospital, Johns Hopkins University, Virginia Commonwealth University, Stanford University, O.O. Shalimov National Institute of Surgery and Transplantology, Department of Radiation Oncology, UT Southwestern Medical Center, School of Physics, The University of Sydney, MaineHealth, University of California, San Diego, Duke University, Emory University, University of Pennsylvania, University of Pittsburgh Medical Center, Medical Physics Department, Medical center of Yuriy Spizhenko, OhioHealth, University of Massachusetts Lowell, St. Francis Hospital
Abstract Preview: Purpose: The AAPM International Council, in collaboration with Help Ukraine Group (HUG) and Ukrainian Association of Medical Physicists (UAMP), developed a novel hybrid year-long training course to as...
Authors: Yan Dai, Jie Deng, Christopher Kabat, Weiguo Lu, Ying Zhang, Hengrui Zhao
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, Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center
Abstract Preview: Purpose:
MRI-guided adaptive radiotherapy (MRgART) using MR-LINAC systems offers significant advantages for liver cancer, enabling superior tumor delineation and online plan adaptation. However, ma...
Authors: Ryan Gentzler, Xin He, James Larner, J.T. Morgan, Cam Nguyen, Wendy Stewart, Krishni Wijesooriya, Grant Williams
Affiliation: Department of Physics, University of Virginia, Department of Radiation Oncology, University of Virginia, Division of Hematology & Oncology, Department of Medicine, University of Virginia
Abstract Preview: Purpose: Some recent studies have shown Overall Survival (OS) of advanced-stage lung cancer patients treated with chemo-radiation therapy (CRT) is correlated with heart dose [1-5], while in other stud...
Authors: Andrew R. Godley, Steve B. Jiang, Mu-Han Lin, Austen Matthew Maniscalco, Dan Nguyen, Yang Kyun Park
Affiliation: 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, Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center
Abstract Preview: Purpose:
Preparing DICOM datasets for research and education is challenging due to the complexity of the format and the necessity for patient-specific handling. Existing workflows demand substantia...
Authors: Abdullah A. Alshreef, Elizabeth L. Bossart, Ashley Cetnar, Leonard H. Kim, Neil A. Kirby, Anna E. Rodrigues, Xin Wang, You Zhang
Affiliation: University of Miami, The University of Texas MD Anderson Cancer Center, Loma Linda University Medical Center, MD Anderson Cancer Center at Cooper, Cooper Medical School of Rowan University, The Ohio State University - James Cancer Hospital, UT Health San Antonio, Duke University, 5940 forest park road
Abstract Preview: Purpose: AAPM TG-298 reported several concerns regarding the training and education of alternative pathway candidates. Medical physics postdoctoral research, though not part of the certification pathw...
Authors: Dilli Banjade, Ajeet Mishra, Shiaw Juen (Eugene) Tan
Affiliation: District Radiation Oncology Service WNW Health
Abstract Preview: Purpose: A shortage of qualified Radiation Oncology Medical Physicists (ROMPs) poses a critical challenge to providing advanced treatments in regional Australia. Training and retaining medical physici...
Authors: Junwen Liu, Mengzhen Wang, Ning Wen, Jifeng Xiao, Fuhua Yan, Yanzhao Yang, Xuekun Zhang, Zheyu Zhang
Affiliation: Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Department of Radiology, Ruijin Hospital Shanghai Jiaotong University School of Medicine, Shanghai Jiaotong University, The SJTU-Ruijin-UIH Institute for Medical Imaging Technology, Shanghai Jiaotong University Schoo of Medicine
Abstract Preview: Purpose:This study aims to develop and evaluate a large language model (LLM) fine-tuned to generate consistent and accurate impressions from imaging findings. Additionally, the study investigates the ...
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: 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: 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: Keyi Bian, Marco Caballo, Wenxiu Guo, Haijie Li, Jiao Li, Aidi Liu, Yue Ma, Ioannis Sechopoulos, Yafei Wang, Yaopan Wu, Zhaoxiang Ye, Yuwei Zhang, Yueqiang Zhu, Daan van den Oever
Affiliation: Radboud University Medical Center, Tianjin Medical University Cancer Institute & Hospital, Sun Yat-Sen University Cancer Center
Abstract Preview: Purpose: To develop and validate a nomogram integrating intra- and peritumoral radiomics of contrast-enhanced cone-beam breast CT (CE-CBBCT) and clinicopathologic features for predicting fluorescence ...
Authors: Wenchao Cao, Yingxuan Chen, Haisong Liu, Richard A. Popple, Wenyin Shi, Rodney J. Sullivan, Wentao Wang, Lydia J. Wilson, Zhenghao Xiao
Affiliation: Thomas Jefferson University, The University of Alabama at Birmingham, University of Alabama at Birmingham
Abstract Preview: Purpose: Objectively evaluating brain sparing as a plan-quality indicator for patients receiving stereotactic radiosurgery (SRS) to multiple metastases (multi-met) is complicated by variability in tar...
Authors: Mingyang Han, Jia Jing, Chongming Li, Hui Lin, Zhenyu Xiong
Affiliation: School of Physics, Hefei University of Technology, Rutgers Cancer Institute of New Jersey
Abstract Preview: Purpose: To enrich the teaching case library of Computational Physics course, one of the basic courses in undergraduates majoring in physics. It is an excellent application case of Medical Physics for...
Authors: Kevin M Brom, Josep Chorro Bas, RosaAnna Chorro Bas, Andres Climent Rubio, Jaydev K. Dave, Tobias Kummer, Larissa Shiue, Donald J Tradup
Affiliation: Mayo Clinic, Prehospital Critical Care Training Group
Abstract Preview: Purpose: To design and evaluate the functionality of a vascular flow phantom for contrast-enhanced ultrasound imaging (CEUS).
Methods: A microcontroller-generated signal was amplified by a cust...
Authors: Mary Gronberg, Kelly Kisling, Ana Maria Marques da Silva
Affiliation: University of California, San Diego, The University of Texas Southwestern Medical Center, Pontifical Catholic University of Rio Grande do Sul
Abstract Preview: Purpose: To evaluate the current status of online teaching in medical physics and identify effective active learning strategies for global medical physics education.
Methods: A scoping review was c...
Authors: Ibtisam Almajnooni, Victor Cobilean, Milos Manic, Harindra Sandun Mavikumbure, Elisabeth Weiss, Lulin Yuan
Affiliation: Virginia Commonwealth University
Abstract Preview: Purpose: This study aims to optimize the 3D U-Net architecture for dose prediction in lung cancer radiation therapy (RT) plans, particularly in scenarios with limited clinical data, as well as to quan...
Authors: Wookjin Choi, Michael Dichmann, Adam Dicker, Nilanjan Haldar, Yingcui Jia, Nicole L Simone, Eugene Storozynsky, Yevgeniy Vinogradskiy, Maria Werner-Wasik
Affiliation: Thomas Jefferson University, 9Department of Radiation Oncology, Thomas Jefferson University
Abstract Preview: Purpose: Cardiotoxicity remains a significant limitation for lung cancer patients treated with radiotherapy. Pre-radiotherapy cardiac conditions increase the probability of patients developing cardiot...
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: Wouter Crijns, Frederik Maes, Loes Vandenbroucke, Liesbeth Vandewinckele
Affiliation: Department of Oncology, Laboratory of Experimental Radiotherapy, KU Leuven; Department of Radiation Oncology, UZ Leuven, Department ESAT/PSI, KU Leuven; Medical Imaging Research Center, UZ Leuven, Department of Oncology, Laboratory of Experimental Radiotherapy, KU Leuven
Abstract Preview: Purpose: To explore intentional deep overfit learning (IDOL) to exploit the initial treatment plan to predict an adaptive radiotherapy plan.
Methods: A conditional generative adversarial network is...
Authors: Vasiliki Chatzipavlidou, Ilias Gatos, George C. Kagadis, Theodoros Kalathas, Paraskevi Katsakiori, Anna Makridou, Dimitris N. Mihailidis, Nikos Papathanasiou, Ioanna Stamouli, Stavros Tsantis
Affiliation: Theageneio Hospital, University of Pennsylvania, University of Patras
Abstract Preview: Purpose: To compare the performance of multiple deep learning (DL) networks, including DenseNet201, InceptionV3, MobileNetV3, EfficientNetB2, NASNetMobile, VGG19, ResNet50, and Xception, in classifyin...
Authors: Osama R. Mawlawi, Yiran Sun
Affiliation: RICE University, UT MD Anderson Cancer Center
Abstract Preview: Purpose: Conventional PET reconstruction methods often produce noisy images with artifacts due to data/model mismatches and inconsistencies. Recently, deep learning-based conditional denoising diffusi...
Authors: John Ginn, Zhuoyun Huang, Yongbok Kim, Ke Lu, Chunhao Wang, Yibo Xie, Zhenyu Yang, Jingtong Zhao
Affiliation: Duke University, Duke Kunshan University
Abstract Preview: Purpose: This study aims to develop and validate a machine learning model for predicting V60%, a critical dosimetric metric in LINAC-based Single-Isocenter-Multiple-Targets (SIMT) stereotactic radiosu...
Authors: Leslie Harrell, Sanjay Maraboyina, Romy Megahed, Maida Ranjbar, Xenia Ray, Pouya Sabouri
Affiliation: Department of Radiation Oncology, University of Arkansas for Medical Sciences (UAMS), University of California San Diego
Abstract Preview: Purpose: Real-time adaptive radiation therapy (ART) dynamically modifies patientsâ treatment plan during delivery to account for anatomical and physiological variations. Addressing ART planning time v...
Authors: Abdullah Hidayat, Wazir Muhammad
Affiliation: Florida Atlantic University
Abstract Preview: Purpose: This study aims to predict Head and Neck cancer using an artificial neural network (ANN) through readily available basic health data. The goal is to uncover hidden patterns and predictors in ...
Authors: Ozan Cem Guler, William Silva Mendes, Sangbo Oh, Cem Onal, Lei Ren, Apurva Singh, Phuoc Tran
Affiliation: University of Maryland School of Medicine, Baskent University Faculty of Medicine, Department of Radiation Oncology, Department of Radiation Oncology, University of Maryland School of Medicine
Abstract Preview: Purpose: To predict metastasis-free survival (MFS) for patients with prostate adenocarcinoma treated with androgen deprivation therapy and external radiotherapy using clinical factors and radiomics ex...
Authors: Hua-Chieh Shao, You Zhang, Ruizhi Zuo
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: Cone-beam CT (CBCT) provides on-board patient anatomy for image guidance and treatment adaptation in radiotherapy. However, to compensate for respiration-induced anatomical motion, motion-res...
Authors: Aditya P. Apte, Joseph O. Deasy, Sharif Elguindi, Aditi Iyer, Jue Jiang, Eve Marie LoCastro, Jung Hun Oh, Amita Shukla-Dave, Harini Veeraraghavan
Affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Memorial Sloan Kettering Cancer Center
Abstract Preview: Purpose: We present port of popular Computational Environment for Radiological Research software platform to Python programming language to cater to cloud-based analyses.
Methods: The components of...
Authors: Mary Feng, Yi Lao, Hui Lin, Hengjie Liu, Xin Miao, Michael Ohliger
Affiliation: University of California, Los Angeles, Department of Radiation Oncology, University of California San Francisco, Department of Radiation Oncology, City of Hope National Medical Center, University of California San Francisco, Siemens Medical Solutions USA Inc.
Abstract Preview: Purpose: 4D MRI with high spatiotemporal resolution is vital to characterize the tumor/tumor motion for liver radiotherapy. However, high-quality 4D MRI requires an impractically long scanning time fo...
Authors: Steve B. Jiang, Dan Nguyen, Chenyang Shen, Fan-Chi F. Su, Jiacheng Xie, Shunyu Yan, Daniel Yang, Ying Zhang, You Zhang
Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, UT Southwestern Medical Center, 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, The University of Texas at Dallas
Abstract Preview: Purpose: Fast dose verification is essential for the safety and efficiency of MR-guided adaptive radiotherapy (ART) as patients anxiously waiting on the treatment couch. Conventional tools often requi...
Authors: Steve B. Jiang, Austen Matthew Maniscalco, Dan Nguyen, Chenyang Shen, Jiacheng Xie, Shunyu Yan, Ying Zhang, You Zhang
Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, UT Southwestern Medical Center, 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, The University of Texas at Dallas
Abstract Preview: Purpose: Although treatment planning systems (TPSs) can handle dose calculation and plan optimization automatically, planning for radiotherapy still requires extensive efforts and expertise from a mul...
Authors: Daniel A. Alexander, Jonathan Baron, Brook Kennedy Byrd, William Ross Green, Bolin Li, Rafe A. McBeth, Abigail Pepin, Steven Philbrook
Affiliation: Department of Radiation Oncology and Applied Sciences, Department of Radiation Oncology, University of Pennsylvania, Thayer School of Engineering, University of Pennsylvania
Abstract Preview: Purpose: As accelerated partial breast irradiation (APBI) gains traction, the prospect of a rapid sim-to-completion of treatment workflow is an attractive option for patients. While OAR autocontouring...
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: Jiali Gong, Yi Guo, Chi Han, Wanli Huo, Hongdong Liu, Zhao Peng, Yaping Qi, Zhaojuan Zhang
Affiliation: Department of Radiotherapy, cancer center, The First Affiliated Hospital of Fujian Medical University, Department of Oncology, Xiangya Hospital, Central South University, State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, China Jiliang University, Division of lonizing Radiation Metrology, National Institute of Metrology, Key Laboratory of Electromagnetic Wave Information Technology and Metrology of Zhejiang Province, College of Information Engineering, China Jiliang University, the Zhejiang-New Zealand Joint Vision-Based Intelligent Metrology Laboratory, College of Information Engineering, China Jiliang University
Abstract Preview: Purpose: To address overfitting from limited training data in multi-organ segmentation, an efficient transfer learning framework is proposed. It reduces reliance on training samples, enabling a single...
Authors: Geoffrey D. Hugo, Eric Laugeman, Thomas R. Mazur, Pamela Samson, Kim A. Selting, Zhehao Zhang
Affiliation: University of Illinois, Washington University in St. Louis School of Medicine, WashU Medicine
Abstract Preview: Purpose: To investigate the robustness of a deep learning (DL)-based 4D-CBCT motion-compensated (MoCo) reconstruction method to out-of-distribution data.
Methods: Our developed 4D-CBCT reconstructi...
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: Hengjie Liu, Dan Ruan, Ke Sheng, DI Xu
Affiliation: Physics and Biology in Medicine, University of California, Los Angeles, Department of Radiation Oncology, University of California, San Francisco, Department of Radiation Oncology, University of California at San Francisco, Department of Radiation Oncology, University of California, Los Angeles
Abstract Preview: Purpose:
State-of-the-art deep learning-based deformable image registration often uses large, complex models directly adapted from computer vision tasks but achieves only comparable performance to ...
Authors: Ke Lu, Chunhao Wang, Ruoxu Xia, Zhenyu Yang, Fang-Fang Yin, Chulong Zhang, Lei Zhang, Rihui Zhang, Jingtong Zhao, Haiming Zhu
Affiliation: Duke University, Duke Kunshan University, Medical Physics Graduate Program, Duke Kunshan University, The First People's Hospital of Kunshan
Abstract Preview: Purpose: The human brainâs spherical geometry offers unique opportunities for improving the segmentation of tiny and irregular anatomical structures. We hypothesize that representing the brain in sphe...
Authors: Lori Buchholtz, Alison Garda, Chris L. Hallemeier, Kathryn L. Kolsky, Han Liu, Joseph John Lucido, Marisa Schinter, Andrew J. Veres, Sara Walerak
Affiliation: Mayo Clinic
Abstract Preview: Purpose: The C_START initiative aims to streamline and simplify the Direct-to-Unit (DtU) clinical setup and treatment planning process for photon radiation therapy, particularly for emergent cases suc...
Authors: Samuel Kadoury, Redha Touati
Affiliation: Polytechnique Montréal
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: Serhii Brovchuk, Viktor M. Iakovenko, Nataliya Kovalchuk, Yuliia Lozko, Zoia Shepil, Natalka Suchowerska, Ruslan Zelinskyi
Affiliation: Kyiv Regional Oncology Dispensary, Stanford University, O.O. Shalimov National Institute of Surgery and Transplantology, School of Physics, The University of Sydney, Medical Physics Department, Medical center of Yuriy Spizhenko, Department of Radiation Oncology, UT Southwestern Medical Center, Stanford Cancer Center
Abstract Preview: Purpose: The full-scale russian invasion of Ukraine has caused the largest humanitarian disaster in Europe since World War II. This study identifies gaps in RT services caused by the war and outlines ...
Authors: Michael Baine, Charles Enke, Yang Lei, Yu Lei, Ruirui Liu, Su-Min Zhou
Affiliation: Icahn School of Medicine at Mount Sinai, University of Nebraska Medical Center, Department of Radiation Oncology, University of Nebraska Medical Center
Abstract Preview: Purpose: This study presents a framework for generating synthetic CT images using a Cycle Diffusion model, which can be utilized to enhance needle conspicuity in ultrasound-guided prostate HDR brachyt...
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: Isaac J. Bailey, Lindsay S. DeWeese, Anna M. Mench, Celeste Winters
Affiliation: Oregon Health & Science University, Department of Diagnostic Radiology, Oregon Health & Science University
Abstract Preview: Purpose: The emergence and recent FDA approval of several new radiopharmaceutical therapies have increased demand for physicists to provide specialized support. However, these topics are not yet inclu...
Authors: Jing Qian, Brandon Reber, David M. Routman, Satomi Shiraishi
Affiliation: Mayo Clinic
Abstract Preview: Purpose: The dose distribution in proton radiotherapy (PRT) is characterized by sharp gradients, posing a challenge for machine learning-based dose prediction. While denoising with diffusion processes...
Authors: Guangjun Li, Ying Song, Huanan Tang, Tianxiong Wu, Qiuyi Ye, Wei Zhang
Affiliation: West China Second Hospital of Sichuan University, United Imaging Healthcare, West China Hospital of Sichuan University
Abstract Preview: Purpose:
To propose a general low-dose reconstruction model for ultra-sparse-view cone-beam CT (CBCT) and evaluate its clinical application in improving image quality and reducing radiation dose fo...
Authors: Yunxiang Li, Weiguo Lu, Xiaoxue Qian, Hua-Chieh Shao, 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:
Curating high-quality, labeled data for medical image segmentation can be challenging and costly, considering the existence of various image domains with differing modalities/protocols. Cr...
Authors: Mingli Chen, Xuejun Gu, Hao Jiang, Mahdieh Kazemimoghadam, Weiguo Lu, Qingying Wang, Zi Yang, 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: Dose prediction (DP) is essential in guiding radiotherapy planning. However, current DP models for intensity-modulated radiation therapy (IMRT) primarily rely on fixed-beam orientations and a...
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:
Converting MR images to synthetic CT (MR2sCT) is highly desirable as it streamlines the radiotherapy treatment planning workflow. This approach leverages the superior soft tissue visibilit...
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 patientsâ 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: Avinash Mudireddy, Nathan Shaffer, Joel J. St-Aubin
Affiliation: University of Iowa
Abstract Preview: Purpose: This work demonstrates preliminary results in training a reinforcement learning (RL) network to perform VMAT machine parameter optimization.
Methods: We implemented a policy gradient RL al...