Authors: Ishika Bhaumik, John M. Boone, Michael T Corwin, Eric S Diaz, Ahmadreza Ghasemiesfe, Andrew M. Hernandez, Sarah E. McKenney, Misagh Piran, Ali Uneri, Eric L White
Affiliation: UC Davis, UC Davis Health, University of California, Johns Hopkins Univ
Abstract Preview: Purpose: A new model CT scanner (Canon Aquilion One Insight) was recently installed at our institution, and it included a 3D Landmark (3DLM) scan for automatic scan planning, a new deep learning recon...
Authors: Tina Ehtiati, Grace Jianan Gang, Limei Ma, Oleg Shekhtman, Visish M. Srinivasan
Affiliation: Siemens Medical Solutions USA, Inc., University of Pennsylvania
Abstract Preview: Purpose: Saccular aneurysms are the most common type of intracranial aneurysm and are typically treated by endovascular embolization. The procedure requires approximately orthogonal fluoroscopy images...
Authors: Weiguo Lu, Jax Luo, Xiaoxue Qian, Hua-Chieh Shao, Guoping Xu, You Zhang
Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, Medical Artificial Intelligence and Automation (MAIA) Laboratory, Department of Radiation Oncology, UT Southwestern Medical Center, Harvard Medical School
Abstract Preview: Purpose:
Semi-supervised segmentation leverages sparse annotation information to learn rich representations from combined labeled and label-less data for segmentation tasks. This study leverages th...
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: Deshan Yang, Zhendong Zhang
Affiliation: Duke University, Department of Radiation Oncology, Duke University
Abstract Preview: Purpose:
The evaluation of deformable image registration (DIR) algorithms is crucial for improving accuracy and clinical adoption. However, reliable benchmarks, especially for inter-modality regist...
Authors: Cem Altunbas, Farhang Bayat, Roy Bliley, Rupesh Dotel, Brian Kavanagh, Uttam Pyakurel, Tyler Robin, Ryan Sabounchi
Affiliation: Department of Radiation Oncology, University of Colorado School of Medicine, Taussig Cancer Center, Cleveland Clinic, University of Colorado Anschutz Medical Campus
Abstract Preview: Purpose: Automatic segmentation of anatomical structures in CBCT images is key to enabling dose delivery monitoring and online plan modifications in radiotherapy. However, poor image quality can degra...
Authors: Beth Bradshaw Ghavidel, Benyamin Khajetash, Yang Lei, Meysam Tavakoli
Affiliation: Icahn School of Medicine at Mount Sinai, Department of Medical Physics, School of Medicine, Iran University of Medical Sciences, Emory University, Department of Radiation Oncology, Emory University
Abstract Preview: Purpose: Pancreatic cancer is among the most aggressive types of cancer, with a five-year survival rate of approximately 10%. Recent studies show that radiomics and deep learning (DL)-based methods ar...
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: Yankun Lang, Lei Ren, Dario B. Rodrigues
Affiliation: University of Maryland School of Medicine, Department of Radiation Oncology, University of Maryland School of Medicine
Abstract Preview: Purpose:
HTP of microwave (MW) phased-array systems determine MW antenna settings to maximize energy absorption (SAR in W/kg) in tumor. Conventional HTP algorithms calculate SAR based on electromag...
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: Sahaja Acharya, Matthew Ladra, Junghoon Lee, Lina Mekki
Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Department of Biomedical Engineering, Johns Hopkins University
Abstract Preview: Purpose: Multi-parametric MRI (mpMRI) is widely used for deep learning (DL)-based automatic segmentation of brain tumors. While multi-contrast images concatenated as channels are typically input to ne...
Authors: Sara Endo, Takeshi Fujisawa, Hidehiro Hojo, Masaki Nakamura, Hidenobu Tachibana
Affiliation: Department of Radiation Oncology, National Cancer Center Hospital East, Radiation Safety and Quality Assurance Division, National Cancer Center Hospital East
Abstract Preview: Purpose: To assess the clinical feasibility of deep learning (DL)-based automated contouring through qualitative and quantitative assessments.
Methods: Sixty cases were chosen, including 3 OARs...
Authors: Gayoung Kim, Junghoon Lee
Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University
Abstract Preview: Purpose: 3D time-of-flight magnetic resonance angiography (TOF-MRA) is widely used for visualizing cerebrovascular structures. Accurate segmentation of cerebrovascular structures is critical for relia...
Authors: 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: Hania A. Al-Hallaq, Xuxin Chen, Anees H. Dhabaan, Elahheh (Ella) Salari, Xiaofeng Yang
Affiliation: Emory University, Department of Radiation Oncology and Winship Cancer Institute, Emory University
Abstract Preview: Purpose:
Radiomics image analysis could lead to the development of predictive signatures and personalized radiotherapy treatments. However, variations in delineation are known to affect hand-crafte...
Authors: Jeffrey D. Bradley, Steven J. Feigenberg, Cole Friedes, Yin Gao, Xun Jia, Kevin Teo, Lingshu Yin, Jennifer Wei Zou
Affiliation: Department of Radiation Oncology, University of Pennsylvania, Johns Hopkins University
Abstract Preview: Purpose: Understanding how physicians evaluate plans is critical for automatic planning and ensuring consistent, high-quality care. While deep-learning models excel in complex decision-making, the lac...
Authors: Xianjin Dai, PhD, Michael Gensheimer, Praveenbalaji Rajendran, Lei Xing, Yong Yang
Affiliation: Department of Radiation Oncology, Stanford University, Massachusetts General Hospital, Harvard Medical School
Abstract Preview: Purpose: Recent advances in the automatic delineation of radiotherapy treatment targets, which incorporate linguistic clinical data extracted by large language models (LLMs) into traditional visual-on...
Authors: Thomas L. Hayes, Nicholas C. Koch, Han Liu, Qingyang (Grace) Shang, Benjamin J. Sintay, Caroline Vanderstraeten, David B. Wiant
Affiliation: Fuse Oncology, Cone Health, Cone Health Cancer Center
Abstract Preview: Purpose:
This study evaluates the accuracy of a deep learning-based automatic breast planning script in predicting beam energy for breast cancer treatments. The script was validated and implemented...
Authors: Adnan Jafar, Xun Jia, An Qin
Affiliation: Johns Hopkins University
Abstract Preview: Purpose: 3D whole-brain radiotherapy (WBRT) is widely used due to its simplicity and effectiveness. While modern treatment planning systems, like RayStation, offer automated Field-in-Field planning, p...
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: Karyn A Goodman, Yang Lei, Tian Liu, Pretesh Patel, Jing Wang, Kaida Yang, Jiahan Zhang
Affiliation: Icahn School of Medicine at Mount Sinai, Department of Radiation Oncology and Winship Cancer Institute, Emory University
Abstract Preview: Purpose: This study aims to improve organ-at-risk (OAR) segmentation in pancreatic cancer stereotactic body radiotherapy (SBRT) by integrating clinical guidelines into deep learning workflows. We use ...
Authors: Xuezhen Feng, Li-Sheng Geng, Haoze Li, Xi Liu, Tianyu Xiong, Ruijie Yang
Affiliation: Department of Health Technology and Informatics, The Hong Kong Polytechnic University, School of Physics, Beihang University, School of Nuclear Science and Technology, University of South China, Department of Radiation Oncology, Peking University Third Hospital
Abstract Preview: Purpose: This study aimed to develop a deep learning-based algorithm for automatically delineate gross tumor volume (GTV) for lung cancer patients, alleviating the workload of radiologists and improvi...
Authors: 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: 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: Mavlonbek Khomidov, Jong-Ha Lee
Affiliation: Department of Biomedical Engineering, Keimyung University, Department of Computer Engineering, Keimyung University
Abstract Preview: Purpose: In this research, we aim to estimate blood pressure using remote photoplethysmography (rPPG) signal extracted from facial video. This method provides non-invasive and contactless, continuous ...
Authors: Malvern Madondo, Mark McDonald, Zhen Tian, Christopher Valdes, Ralph Weichselbaum, Xiaofeng Yang, David Yu, Jun Zhou
Affiliation: Department of Radiation & Cellular Oncology, University of Chicago, University of Chicago, Emory University, Department of Radiology, University of Chicago, Department of Radiation Oncology and Winship Cancer Institute, Emory University
Abstract Preview: Purpose: Head-and-neck (HN) cancer patients often experience significant anatomical changes during treatment course. Proton therapy, particularly intensity-modulated proton therapy (IMPT), is sensitiv...
Authors: Keiichi Jingu, Noriyuki Kadoya, Takafumi Komiyama, Takeru Nakajima, Hikaru Nemoto, Hiroshi Onishi, Masahide Saito, Ryota Tozuka
Affiliation: Department of Radiology, University of Yamanashi, Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Department of Advanced Biomedical Imaging, University of Yamanashi
Abstract Preview: Purpose: We evaluated the accuracy of a new AI-based fully automated planning software in stereotactic body radiotherapy (SBRT) for early-stage lung cancer.
Methods: We collected data from 125 pati...
Authors: Ming Dong, Carri K. Glide-Hurst, Joshua Pan, Nicholas R. Summerfield
Affiliation: Department of Computer Science, Wayne State University, Departments of Human Oncology and Medical Physics, University of Wisconsin-Madison, Department of Human Oncology, University of Wisconsin-Madison
Abstract Preview: Purpose: Radiation dose to the cardiac nodes is more strongly associated with conduction disorders and arrythmias than whole heart (WH) metrics. However, node segmentation is challenging due to comple...
Authors: Petr Bruza, Yao Chen, David J. Gladstone, Lesley A Jarvis, Brian W Pogue, Kimberley S Samkoe, Yucheng Tang, Shiru Wang, Rongxiao Zhang
Affiliation: NVIDIA Corp, Dartmouth College, Thayer School of Engineering, Dartmouth College, Dartmouth Cancer Center, University of Missouri, University of Wisconsin - Madison
Abstract Preview: Purpose: Cherenkov imaging provides real-time visualization of megavoltage radiation beam delivery during radiotherapy. Patient-specific bio-morphological features, such as vasculature, captured in th...