Authors: Jenghwa Chang, Kuan Huang, Lyu Huang, Jason Lima, Jian Liu, Farzin Motamedi
Affiliation: Northwell, Department of Computer Science and Technology, Kean University, Physics and Astronomy, Hofstra University, Hofstra University Medical Physics Program
Abstract Preview: Title: A Deep Learning Approach to the Prediction of Gamma Passing Rates in VMAT Radiotherapy Plans for Adaptive Treatment.
Purpose: This study aims to develop a deep learning algorithm to predict ...
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: Xiaoying Pan, X. Sharon Qi
Affiliation: Department of Radiation Oncology, University of California, Los Angeles, School of Computer Science and technology,Xi'an University of Posts and Telecommunications
Abstract Preview: Purpose:
Survival prediction for cancer presents a substantial hurdle in personalized oncology, due to intricate, high-dimensional medical data. Our study introduces an innovative feature selection...
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: Zachery Colbert, Matthew Foote, Michael Huo, Mark Pinkham, Prabhakar Ramachandran, Mihir Shanker
Affiliation: Radiation Oncology, Princess Alexandra Hospital, Ipswich Road, Princess Alexandra Hospital
Abstract Preview: Purpose: The study aimed to develop and implement deep learning-based autosegmentation models for the autosegmentation of four key tumor types: brain metastasis, pituitary adenoma, vestibular schwanno...
Authors: Hui-Shan Jian, Yu-Ying Lin
Affiliation: Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou
Abstract Preview: Purpose: The image quality assurance of mammographic images is crucial for correct diagnosis. To develop and validate an explainable deep-learning classifier for phantom image quality assessment of di...
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: 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: Katja M. Langen, William Andrew LePain, Robert Muiruri, Vivi Nguyen, Mosa Pasha, Roelf L. Slopsema, Alexander Stanforth, Yinan Wang, Mingyao Zhu
Affiliation: Emory Healthcare, Emory University, Department of Radiation Oncology and Winship Cancer Institute, Emory University
Abstract Preview: Purpose: Intensity modulated proton therapy (IMPT) treatment planning for craniospinal irradiation (CSI) is complex and requires extensive effort from the planner. This study aims to enhance planning ...
Authors: Xiaoda Cong, Rohan Deraniyagala, Xuanfeng Ding, Xiaoqiang Li, Jian Liang, Peilin Liu, Craig Stevens, Xiangkun Xu, Weili Zheng
Affiliation: Corewell Health William Beaumont University Hospital, Corewellhealth William Beaumont University Hospital, William Beaumont University Hospital, Corewellhealth William Beaumont Hospital, Department of Radiation Oncology, Corewell Health William Beaumont University Hospital
Abstract Preview: Purpose:
Commission a step-and-shoot arc therapy(SPArc-step&shoot) for treating head-neck cancer patients as a desired interim milestone toward full dynamic treatment.
Methods:
An in-house de...
Authors: Serdar Charyyev, Cynthia Fu-Yu Chuang, Veng Jean Heng, Lianli Liu, Lei Xing, Yong Yang
Affiliation: Department of Radiation Oncology, Stanford University
Abstract Preview: Purpose: To replace large finite-size photon phase space files with a compact neural network capable of generating an infinite number of particles.
Methods: Three separate models were developed to ...
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: Aditya P. Apte, Joseph O. Deasy, Jue Jiang, Nancy Lee, Sudharsan Madhavan, Nishant Nadkarni, Lopamudra Nayak, Harini Veeraraghavan, Wei Zhao
Affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Memorial Sloan Kettering Cancer Center
Abstract Preview: Purpose: To track early response to radiotherapy using digital twins, it is crucial to quantify tumor volume and mass changes. Traditional tumor detection methods, particularly in image registration, ...
Authors: Justus Adamson, Mu Chen, Ke Lu, Zhenyu Yang, Fang-Fang Yin, Rihui Zhang, Yaogong Zhang, Haipeng Zhao, Haiming Zhu, Yuchun Zhu
Affiliation: Shanghai Dacheng Medical Technology, Duke University, Medical Physics Graduate Program, Duke Kunshan University, Duke Kunshan University, The First People's Hospital of Kunshan
Abstract Preview: Purpose: In filtered back-projection (FBP) reconstruction, conventional filters often reduce noise at the expense of high-frequency details, leading to structural details loss. To address this limitat...
Authors: Yaspal Badyal, Rabten Datsang, Tianjun Ma, William Song
Affiliation: MVision AI, Virginia Commonwealth University
Abstract Preview: Purpose: Deep learning (DL)-based dose distribution predictions for prostate cancer show significant potential for OAR sparing compared to manually optimized treatment plans. We aim to generate clinic...
Authors: Alexander Bookbinder, Matthew Tivnan, Xiangyi Wu, Wei Zhao
Affiliation: Stony Brook Medicine, Massachusetts General Hospital
Abstract Preview: Purpose: To investigate and benchmark a system-adaptive diffusion-based digital breast tomosynthesis (DBT) denoising model for a direct-indirect dual-layer flat panel detector (DI-DLFPD) with a k-edge...
Authors: Xiance Jin
Affiliation: 1st Affiliated Hospital of Wenzhou Medical University
Abstract Preview: Purpose:
Deep learning deformable registration models was proposed to predict optimal dose distributions a with a few of optimal planned doses using a few-shot learning for cervical cancer.
Meth...
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: 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: Nan Li, Yaoying Liu, Shouping Xu, Xinlei Xu, Gaolong Zhang
Affiliation: School of Physics, Beihang University, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, School of physics, Beihang University, Beihang University, Department of Radiation Oncology
Abstract Preview: Purpose:
CT simulation is essential for radiation therapy preparation but has limitations in distinguishing lesions. Contrast-enhanced CT (CECT) improves lesion detection and characterization, but ...
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: Claus Belka, Stefanie Corradini, George Dedes, Nikolaos Delopoulos, Christopher Kurz, Guillaume Landry, Ahmad Neishabouri, Domagoj Radonic, Adrian Thummerer, Niklas Wahl, Fan Xiao
Affiliation: Department of Radiation Oncology, LMU University Hospital, LMU Munich, Department of Medical Physics, LMU Munich, Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), National Center for Radiation Oncology (NCRO), Heidelberg Institute for Radiation Oncology (HIRO)
Abstract Preview: Purpose: In MR-guided online adaptive radiotherapy, MRI lacks tissue attenuation information necessary for accurate dose calculations. Instead of using deep learning methods to generate synthetic CT i...
Authors: Xianjin Dai, PhD, Michael Gensheimer, Praveenbalaji Rajendran, Lei Xing, Yong Yang
Affiliation: Department of Radiation Oncology, Stanford University, Massachusetts General Hospital, Harvard Medical School
Abstract Preview: Purpose: Recent advances in the automatic delineation of radiotherapy treatment targets, which incorporate linguistic clinical data extracted by large language models (LLMs) into traditional visual-on...
Authors: 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: Wilfred R Furtado, Gary Y. Ge, James Lee, Jie Zhang
Affiliation: University of Kentucky
Abstract Preview: Purpose: Despite advancements in Artificial Intelligence (AI) and its growing role in clinical practices like radiology, formal AI education remains limited in medical training. This gap contributes t...
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: Rex A. Cardan, Carlos E. Cardenas, Udbhav S. Ram
Affiliation: The University of Alabama at Birmingham, University of Alabama at Birmingham
Abstract Preview: Purpose: The AAPM TG-263 report provides nomenclature guidelines for target and normal tissue structures used in radiation oncology. Adherence to these guidelines is challenging for targets, as there ...
Authors: Andres Portocarrero Bonifaz, Ian Schreiber
Affiliation: CARTI Cancer Center
Abstract Preview: Purpose: To explore how calculation grid resolution, along with other planning factors, affects head and neck dose calculation accuracy and contributes to potential discrepancies in the Eclipse Treatm...
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: Yunfei Dong, Dongyang Guo, Jiongli Pan, Tao Peng, Caiyin Tang, Zhenyu Yang, Fang-Fang Yin, Lei Zhang, Tianyi Zhang, Yaogong Zhang
Affiliation: Duke Kunshan University, Department of Radiology, Taizhou People’s Hospital Affiliated to Nanjing Medical University, School of Future Science and Engineering, Soochow University, Medical Physics Graduate Program, Duke Kunshan University
Abstract Preview: Purpose: This study aims to improve the accuracy of CT-based diagnosis of thyroid cancer by developing a hybrid model that integrates Convolutional Neural Networks (CNNs) with Long Short-Term Memory (...
Authors: Martin Frank, Oliver Jäkel, Niklas Wahl
Affiliation: Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), Karlsruhe Institute of Technology (KIT)
Abstract Preview: Purpose: Machine learning (ML) models on normal tissue complication and tumor control probability ((N)TCP) exploiting e.g. dosiomic and radiomic features are playing an increasingly important role in ...
Authors: Charles D. Bloch, Stephen R. Bowen, Bing-Hao Chiang, Alex Egan, Eric C. Ford, Sharareh Koufigar, Dominic A. Maes, Juergen Meyer, Sharon Pai, Frank Rafie, Rajesh Regmi, Jatinder Saini, George A. Sandison, Marco Schwarz, Bishwambhar Sengupta, Tony P. Wong
Affiliation: Department of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, Department of Physics, University of Washington
Abstract Preview: Purpose: This study aimed to optimize the strategy and timing of physics consults for proton prostate patients to improve the patient experience and resource utilization in our radiation oncology depa...
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: Bowen Jing, Jing Wang
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: Medical images acquired at multiple time points during neoadjuvant chemotherapy allow physicians to assess patients’ responses and personalize treatment plans accordingly. Studies from the I-...
Authors: Ramesh Boggula, Jay W. Burmeister, Michael Joiner
Affiliation: Wayne State University, Karmanos Cancer Center, Gershenson ROC, Wayne State University School of Medicine
Abstract Preview: Purpose: Recent advances in large language models such as ChatGPT offer new possibilities for supplementing traditional teaching methods. In this study, we developed a custom GPT-powered tool freely a...
Authors: William T. Hrinivich, Junghoon Lee, Lina Mekki
Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Department of Biomedical Engineering, Johns Hopkins University, Johns Hopkins University
Abstract Preview: Purpose: Volumetric modulated arc therapy (VMAT) planning is a computationally expensive process. In this work, we propose a reinforcement learning (RL) framework to automatically optimize dose rate a...
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: Lu Jiang, Ke Sheng
Affiliation: Department of Radiation Oncology, University of California at San Francisco, Department of Radiation Oncology, University of California, San Francisco
Abstract Preview: Purpose:
Conventional radiotherapy treatment planning is guided by a set of generic objectives that are unspecific to patient anatomy. Treatment planning thus heavily relies on the planner’s experi...