Authors: Lorenzo Arsini, Andrea Ciardiello, Fabio Massimo D'Amore, Stefano Giagu, Federico Giove, Carlo Mancini-Terracciano, Cecilia Voena
Affiliation: Istituto Superiore di Sanità, Sapienza University of Rome, Università 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 disease—such as ...
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: Zachary Buchwald, Chih-Wei Chang, Richard L.J. Qiu, Mojtaba Safari, Hui-Kuo Shu, Lisa Sudmeier, Xiaofeng Yang, David Yu, Xiaohan Yuan
Affiliation: Emory University and Winship Cancer Institute, Emory University, Georgia Institute of Technology, Department of Radiation Oncology and Winship Cancer Institute, Emory University
Abstract Preview: Purpose: This study proposes a novel vision-language model (VLM) to predict survival outcomes in glioblastoma (GBM) patients. By integrating multimodal MRI data and clinical information, the proposed ...
Authors: 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: Ivan L. Cordrey, Dharmin D. Desai, Ellis Lee Johnson
Affiliation: Cumberland Medical Center - Cancer Center, University of Kentucky, Varian Advanced Oncology Solutions
Abstract Preview: Purpose: HyperArc (HA) is known to produce a high quality SRS plan. Adding Surface Area Informed Optimization (SAIO) to HA has been shown to improve plan quality metrics R50% and the Conformality Inde...
Authors: Arjit K. Baghwala, Sunan Cui, Jessica Fagerstrom, Eric C. Ford, Kristi Rae Gayle Hendrickson, Sharareh Koufigar, Samuel Ming Ho Luk, Bishwambhar Sengupta, Afua A. Yorke
Affiliation: University of Washington, Department of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, Department of Radiation Oncology, University of Vermont Medical Center, University of Washington and Fred Hutchinson Cancer Center, Houston Methodist Hospital
Abstract Preview: Purpose: The global burden of cancer continues to rise, leading to an increased workload in radiation oncology clinics. This surge is not only due to the growing demand for treatment machines and moda...
Authors: Aditya P. Apte, Joseph O. Deasy, Sharif F. 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 publicly shareable applications (apps) for AI-based radiotherapy segmentation workflows with pyCERR on Seven Bridges Cancer Genomics Cloud-based platform (CGC-SB)
Methods: Runni...
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: Alan H. Baydush, Sarah Cummings, Jeffrey Michael Fenoli, Christy Hickerson, Lalith Kumaraswamy, Philmo Oh, Sarah B. Wisnoskie
Affiliation: Novant Health Cancer Institute, Novant Health
Abstract Preview: Purpose: To develop, validate, and commission a VMAT Total Body Irradiation (TBI) workflow by integrating publicly available resources, commercial solutions, and in-house testing to enhance treatment ...
Authors: Yunfeng Cui, Will Giles, Xinyi Li, Ke Lu, Jennifer C. O'Daniel, Anna E. Rodrigues, Chunhao Wang, Lana Wang, Yibo Xie, Sua Yoo, Jingtong Zhao
Affiliation: Duke University, Duke University Medical Center
Abstract Preview: Purpose:
To establish quantitative measurement of plan modulation for SRS/SBRT treated with Volumetric Modulated Arc Therapy (VMAT) on C-arm LINACs.
Methods:
A total of 461 plans were analyze...
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: John Byun, Juan J Cardona, Steven D Chang, Cynthia Fu-Yu Chuang, Xuejun Gu, Yusuke Hori, Hao Jiang, Fred Lam, Lianli Liu, Weiguo Lu, David Park, Erqi Pollom, Elham Rahimy, Deyaaldeen Abu Reesh, Scott Soltys, Gregory Szalkowski, Lei Wang
Affiliation: Department of Radiation Oncology, Stanford University, Department of Neurosurgery, Stanford School of Medicine, Department of Neurosurgery, Stanford University, 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:
Intraventricular tumors pose significant challenges in neurosurgery due to their complex location. Therefore, brain SRS could be a better treatment option. At our institution, some patient...
Authors: John Byun, Steven D Chang, Cynthia Fu-Yu Chuang, Xuejun Gu, Melanie Hayden Gephart, Yusuke Hori, Fred Lam, Gordon Li, Lianli Liu, Weiguo Lu, David Park, Erqi Pollom, Elham Rahimy, Deyaaldeen Abu Reesh, Scott Soltys, Gregory Szalkowski, Lei Wang, Xianghua Ye, Kangning Zhang
Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, Department of Neurosurgery, Stanford University, Department of Radiation Oncology, Stanford University, Department of Radiation Oncology, Stanford University School of Medicine
Abstract Preview: Purpose: Accurate and automated delineation of vestibular schwannoma (VS) volume is crucial for disease management, as both treatment approaches (stereotactic radiosurgery and invasive surgery) and mo...
Authors: Ahmad Algohary, Adrian Breto, Quadre Emery, Radka Stoyanova
Affiliation: University of Miami, Department of Radiation Oncology, University of Miami
Abstract Preview: Purpose:
To develop a foundation model (U-Found) for multiparametric MRI (mpMRI) of the prostate by using self-supervised learning to prove the feasibility of a prostate-oriented foundation model u...
Authors: Beth Reed, Justin B. Solomon
Affiliation: Duke University, Clinical Imaging Physics Group, Department of Radiology, Duke University Health System
Abstract Preview: Purpose: The purpose of this study was to compare image quality between CT images of variable slice thickness reconstructed directly at the scanner verses reformatted at a PACS workstation.
Methods...
Authors: Chunhui Han, An Liu, Anthony Magliari, Lesley Rosa
Affiliation: Office of Medical Affairs, Varian, A Siemens Healthineers Company, Department of Radiation Oncology, City of Hope National Medical Center
Abstract Preview: Purpose: To evaluate the performance of a knowledge-based planning (KBP) optimization model for total marrow and lymphoid irradiation (TMLI) on a ring-gantry linac with a dual-layer MLC and to evaluat...
Authors: Jihun Kim, Jin Sung Kim, Jun Won Kim, Yong Tae Kim, Chanwoong Lee, Jihyn Pyo, Young Hun Yoon
Affiliation: Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Department of Radiation Oncology, Gangnam Severance Hospital, Yonsei University College of Medicine
Abstract Preview: Purpose: Although segmentation foundation models have recently demonstrated promising zero-shot performance on natural images, its clinical application to magnetic resonance (MR) images still requires...
Authors: Md Tauhidul Islam, Junyan Liu, Lei Xing
Affiliation: Department of Radiation Oncology, Stanford University
Abstract Preview: Purpose: Radiation-induced lung injury (RILI) is a common complication in patients receiving radiotherapy for lung cancer, with approximately 16%–28% developing pulmonary fibrosis. The exact mechanism...
Authors: Oluyemi Bright Aboyewa, KyungPyo Hong, Daniel Kim
Affiliation: Department of Radiology, Northwestern University
Abstract Preview: Purpose: While non-Cartesian MRI is desirable for fast imaging with high spatial resolution and robustness to motion, it requires long post-processing times. Preconditioning with an adequate density c...
Authors: John Ginn, Chenlu Qin, Deshan Yang
Affiliation: Duke University, Department of Radiation Oncology, Duke University
Abstract Preview: Purpose: Clinical implementation of auto-segmentation tools has been hindered by poor interpretability and generalizability of AI models, necessitating the development of automated contour quality ass...
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: Casey C. Heirman, Kyle J. Lafata, Xiang Li, Breylon Riley, Jack B Stevens, Tammara Watts
Affiliation: Duke University, Department of Radiation Oncology, Duke University
Abstract Preview: Purpose: To leverage quantitative fluorescence imaging and spatial transcriptomics for characterizing the spatial and molecular heterogeneity of the tumor microenvironment (TME) in HPV+ head and neck ...
Authors: Tatsuya Fujisaki, Hiraku Fuse, Shin Miyakawa, Hiroki Nosaka, Masato Takahashi, Kenji Yasue
Affiliation: Ibaraki Prefectural University of Health Sciences
Abstract Preview: Purpose: This study aimed to evaluate the robustness of Jacobian-based and HUchange-based CT ventilation imaging (CTVI) against respiratory amplitude variations using a custom-designed alveolar phanto...
Authors: Yizheng Chen, Michael Gensheimer, Mingjie Li, Lei Xing
Affiliation: Department of Radiation Oncology, Stanford University
Abstract Preview: Purpose: Automatically translating non-contrast to contrast-enhanced computed tomography (CT) images is critical for improving clinical workflow, reducing heathcare cost, minimizing radiation exposure...