Authors: Jiayi Chen, Manju Liu, Ning Wen, Haoran Zhang, Yibin Zhang
Affiliation: Department of Radiation Oncology, Ruijin Hospital, Department of Radiology, Ruijin Hospital Shanghai Jiaotong University School of Medicine, Duke Kunshan University, Department of Radiation Oncology,Ruijin Hospital, Shanghai Jiao Tong University School of Medicine
Abstract Preview: Purpose: This study introduces a novel Dual Energy CT (DECT)-Guided Intelligent Radiation Therapy (DEIT) platform designed to streamline and optimize the radiotherapy process. The DEIT system combines...
Authors: Shahed Badiyan, Bin Cai, Tu Dan, Michael Dohopolski, Steve B. Jiang, Deepkumar Mistry, Arnold Pompos, Robert Timmerman, Jing Wang
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, University of Texas Southwestern Medical Center, Department of Radiation Oncology, UT Southwestern Medical Center
Abstract Preview: Purpose: Biology-guided radiotherapy (BGRT) offers significant potential for personalized and adaptive cancer treatment, with clinically available systems such as SCINTIX from Reflexion now being intr...
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: Chih-Wei Chang, Runyu Jiang, Mark Korpics, Yuan Shao, Aranee Sivananthan, Zhen Tian, Ralph Weichselbaum, Xiaofeng Yang, Aubrey Zhang, Xiaoman Zhang
Affiliation: Department of Radiation & Cellular Oncology, University of Chicago, University of Chicago, Department of Physics, University of Chicago, Emory University, Department of Radiation Oncology and Winship Cancer Institute, Emory University, School of Public Health, University of Illinois Chicago
Abstract Preview: Purpose: Gamma Knife (GK) plan quality can vary significantly among planners, even for cases handled by the same planner. Although plan quality metrics such as coverage, selectivity, and gradient inde...
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: Jeonghoon Park, Amritha Praveen, Siddhant Sen, James J. Sohn, Ethan D. Stolen
Affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Department of Radiation & Cellular Oncology, University of Chicago, Department of Radiation and Cellular Oncology, The University of Chicago, Department of Radiation and Cellular Oncology, University of Chicago, Department of Psychology, University of Illinois Urbana-Champaign
Abstract Preview: Purpose: Accurate fabrication of custom boluses is essential in radiation therapy to enhance dose delivery to superficial tumors, especially in anatomically complex regions. This study introduces a no...
Authors: Michael Bowers, Patrik Brodin, Madhur Garg, Rafi Kabarriti, William P. Martin, Todd R. McNutt, Julie Shade, Wolfgang A. Tomé, Christian Velten
Affiliation: Johns Hopkins University, Oncospace, Inc., Montefiore Medical Center
Abstract Preview: Purpose: Development of an automated planning tool utilizing AI generated patient-specific dose-volume histogram predictions for rapid H&N plan generation.
Methods: Planning best-practices were dev...