Authors: Ziheng Deng, Yao Hao, Runping Hou, Deshan Yang, Jun Zhao, Yufu Zhou
Affiliation: Department of Radiation Oncology, Duke University, School of Biomedical Engineering, Shanghai Jiao Tong University, Washington University School of Medicine, Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine
Abstract Preview: Purpose: 4D CBCT has been developed to provide dynamic images for image-guided radiation therapy. However, as projection data are sorted into sparse and clustered phase-specific bins, 4D CBCT images a...
Authors: Bas W. Raaymakers, Mario Ries, Paris Tzitzimpasis, Cornel Zachiu
Affiliation: Department of Radiotherapy, University Medical Center Utrecht, University Medical Center Utrecht, UMC Utrecht
Abstract Preview: Purpose: Radiation pneumonitis affects approximately 10-30% of lung cancer patients treated with radiation therapy (RT), posing a significant dose-limiting factor. Recently developed CT-ventilation me...
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-specific quality assurance (PSQA) results for magnetic resonance (MR)-guided online adaptive radiation th...
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: Jie Deng, 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: Based on a 3D pre-treatment MRI scan, we developed DREME-MR to jointly reconstruct the reference patient anatomy and a data-driven, patient-specific cardiorespiratory motion model. Via a moti...
Authors: Benito De Celis Alonso, Braian Adair Maldonado Luna, Gerardo Uriel Perez Rojas, René Eduardo Rodríguez-Pérez, 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: 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: Denisa R. Goia, M. Saiful Huq, Ronald John Lalonde, Fang Li, Noor Mail, Joseph Shields, Christopher Tyerech
Affiliation: UPMC Hillman Cancer Center, UPMC Hillman Cancer Center and University of Pittsburgh School of Medicine, Department of Radiation Oncology, University of Pennsylvania, UPMC
Abstract Preview: Purpose: HyperSight is a new platform for image-guided radiation therapy, offering advanced reconstruction algorithms, a large field-of-view, and rapid acquisition times. To validate the performance o...
Authors: Grant Evans, Maxwell Arthur Kassel, Charles Shang, Stephen Shang
Affiliation: South Florida Proton Therapy Institute, SFPRF
Abstract Preview: Purpose: Proton pencil beam scanning therapy is particularly sensitive to field translational shifts and beam range variations, which can degradation of dose distribution and compromise the treatment....
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: Neelam Tyagi
Affiliation: Memorial Sloan Kettering Cancer Center
Abstract Preview: N/A...
Authors: Mohamed Bahaaeldin Mohamed Afifi, Lili Chen, Xiaoming Chen, Ahmed A. Eldib, Chang Ming Charlie Ma, Robert A. Price
Affiliation: Fox Chase Cancer Center, Radiological Sciences and Medical Imaging Department, College of Applied Medical Sciences, Prince Sattam bin Abdulaziz University.
Abstract Preview: Purpose: Reirradiation of recurrent cancer or a newly developed lesion in a proximal location poses a challenge for radiation treatments. This is occasionally encountered in many modern clinics and ef...
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: Hideaki Hirashima, Haruo Inokuchi, Nobutaka Mukumoto, Naruki Murahashi, Mitsuhiro Nakamura, Megumi Nakao, Keiko Shibuya, Linna Zhang
Affiliation: Kyoto University, Osaka Metropolitan University
Abstract Preview: Purpose:
To transform the quality of 2D cine MR images acquired during online adaptive MR-guided radiotherapy (OA-MRgRT) by utilizing a conditional diffusion model to achieve image quality comparab...
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: Accurate delineation of treatment targets and organs-at-risk is crucial for radiotherapy. Despite significant progress in artificial intelligence (AI)-based automatic segmentation tools, effi...
Authors: Shahed Badiyan, Tsuicheng D. Chiu, Viktor M. Iakovenko, Steve Jiang, Christopher Kabat, Mu-Han Lin, Roberto Pellegrini, Arnold Pompos, Edoardo Salmeri, David Sher, Sruthi Sivabhaskar, Justin D. Visak
Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center, Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, TX, Global Clinical Science, Elekta AB, UT Southwestern Medical Center, Department of Radiation Oncology, UT Southwestern Medical Center
Abstract Preview: Purpose: Adaptive treatment planning requires robust strategies to enable streamlined on-couch processes, creating a significant barrier for planners transitioning from conventional to adaptive planni...
Authors: Nebi Demez, Michael Kasper, Noufal Manthala Padannayil, Haley Park, Shyam Pokharel, Suresh Rana, Lauren A. Rigsby, Tino Romaguera, Hina Saeed, Nishan Shrestha, Somol Sunny
Affiliation: Florida Atlantic University, Lynn Cancer Institute, Boca Raton Regional Hospital, Baptist Health South Florida
Abstract Preview: Purpose:
Pancreatic cancer poses therapeutic challenges due to the proximity of critical organs, requiring precise radiotherapy. Magnetic resonance (MR)-guided linear accelerators provide daily ima...
Authors: Evan Calabrese, Hangjie Ji, Kyle J. Lafata, Casey Y. Lee, Eugene Vaios, Chunhao Wang, Lana Wang, Zhenyu Yang, Jingtong Zhao
Affiliation: Duke University, Department of Radiation Oncology, Duke University, Duke Kunshan University, North Carolina State University
Abstract Preview: Purpose: To develop a biologically guided deep learning (DL) model for predicting brain metastasis(BM) local control outcomes following stereotactic radiosurgery (SRS). By integrating pre-SRS MR image...
Authors: Xu Chen, Jun Lian, Yunkui Pang, Pew-Thian Yap
Affiliation: University of North Carolina at Chapel Hill, Huaqiao University
Abstract Preview: Purpose: Unsupervised CBCT-to-CT translation in the pelvic region is essential for accurate radiotherapy delivery and adaptive image-guided interventions. However, current models for cross-modality tr...
Authors: Robbie Beckert, Austen N. Curcuru, Farnoush Forghani, Yi Huang, Geoffrey D. Hugo, Hyun Kim, Eric Laugeman, Luke Christian Marut, Thomas R. Mazur, Allen Mo, Emily Sigmund
Affiliation: Washington University in St. Louis School of Medicine, WashU Medicine, Washington University School of Medicine in St. Louis, Wash U Medicine, Washington University in St. Louis, Department of Radiation Oncology, Washington University School of Medicine in St. Louis
Abstract Preview: Purpose: Adaptive SBRT is resource intensive, requiring additional personnel for online planning, and should be reserved for cases where it is most beneficial. The purpose of this research is to creat...
Authors: Mark Bowers, Gabriel Carrizo, Jimmy Caudell, Vladimir Feygelman, Kevin Greco, Christian Hahn, Jihye Koo, Kujtim Latifi, Fredrik Lofman, Jacopo Parvizi, Muqeem Qayyum, Caleb Sawyer
Affiliation: RaySearch Laboratories, Moffitt Cancer Center
Abstract Preview: Purpose: Head and neck (H&N) radiotherapy planning is complex, with multiple competing objectives. We endeavored to improve efficiency of planning by developing a deep learning (DL) model trained to p...
Authors: Tsuicheng D. Chiu, Weiguo Lu, Aaron Thomlinson, You Zhang
Affiliation: Department of Radiation Oncology, UT Southwestern Medical Center, Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, University of Texas Southwestern Medical Center
Abstract Preview: Purpose: To develop and validate an MR-compatible anthropomorphic motion phantom to assess liver motion, real-time dosimetry, and gating system performance under controlled and reproducible respirator...
Authors: Kaelyn Becker, Xenia Ray
Affiliation: University of California, San Diego, University of California San Diego
Abstract Preview: Purpose: Ethos 2.0 with HyperSight (Varian Medical Systems) imaging enables nearly fully automated offline adaptive radiotherapy including automated deformation of targets and recalculation on the Hou...
Authors: Penghao Gao, Zejun Jiang, Huazhong Shu, Linlin Wang, Gongsen Zhang, Jian Zhu
Affiliation: Laboratory of Image Science and Technology, Key Laboratory of Computer Network and Information Integration, Southeast University, 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: We propose a cascading framework for time-varying anatomical volumetric reconstruction and tumor-tracking, guided by onboard orthogonal-view X-ray projections.
Methods: We employe multiple...
Authors: Amar Kishan, Jun Lian, Yunkui Pang, Jonathan Pham, X. Sharon Qi, Michael Steinberg, Luca F Valle, Pew-Thian Yap
Affiliation: Department of Radiation Oncology, University of California, Los Angeles, University of North Carolina at Chapel Hill
Abstract Preview: Purpose: Stereotactic body radiotherapy (SBRT) is a highly effective treatment for prostate cancer, yet predicting genitourinary (GU) toxicity has primarily relied on planned dosimetry. This study inv...
Authors: Jennifer L. Dolan, Chengyin Li, Parag Parikh, Doris N. Rusu, Kundan S Thind
Affiliation: Henry Ford Health, Cedars-Sinai Medical Center
Abstract Preview: Purpose: The time and resource demands of online Adaptive Radiation Therapy (ART) can limit its widespread clinical adoption and potentially impact patient throughput. To address this, we developed a ...
Authors: Christopher G. Ainsley, Pradeep Bhetwal, Yingxuan Chen, Wookjin Choi, Vimal K. Desai, Karen E. Mooney, Adam Mueller, Hamidreza Nourzadeh, Yevgeniy Vinogradskiy, Maria Werner-Wasik
Affiliation: Thomas Jefferson University
Abstract Preview: Purpose: MR-guided adaptive radiotherapy (MRgART) has demonstrated improved outcomes for patients with pancreatic cancer. However, the time-consuming re-segmentation of targets and organs-at-risk (OAR...
Authors: Asma Amjad, Renae Conlin, Eric S. Paulson, Christina M. Sarosiek
Affiliation: Department of Radiation Oncology, Medical College of Wisconsin
Abstract Preview: Purpose: In an effort to improve contouring accuracy for abdominal MR guided online adaptive radiotherapy (MRgOART), patient-specific deep learning-based auto-segmentation (PS-DLAS) has been proposed....
Authors: Chunhui Han, An Liu, William T. Watkins, Qiuyun Xu
Affiliation: Department of Radiation Oncology, City of Hope National Medical Center
Abstract Preview: Purpose: To evaluate the RefleXion X1 imaging system as a standalone positron emission tomography and computed tomography (PET/CT) simulator for radiotherapy treatment planning and adaptive re-plannin...
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: Zachary Buchwald, Chih-Wei Chang, Zach Eidex, Hui Mao, 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, Emory University School of Medicine
Abstract Preview: Purpose: MRI-guided radiation therapy (MRgRT) benefits significantly from enhanced soft-tissue contrast and spatial resolution, which aid in accurately delineating tumors and organs at risk. Although ...
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: Philip Blumenfeld, Jon Feldman, Yair Hillman, Michael Marash, Aron Popovtzer, Alexander Pryanichnikov, Shimshon Winograd, Marc Wygoda, Vered Zivan
Affiliation: Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), P-Cure Ltd./Inc., Sharett Institute of Oncology, Hadassah Medical Center, Hebrew University of Jerusalem
Abstract Preview: Purpose:
Image-guided adaptive proton therapy (IGAPT) allows tailored dose adjustments to account for anatomical and physiological changes during treatment. Recent efforts have developed a cost-eff...
Authors: Kin Yin Cheung, Chen-Yu Huang, Chi Wa Kong, Pei-Xiong Li, Pak Hang Nam, Bin Yang, Siu Ki Yu, Chi To Yung
Affiliation: Medical Physics Department, Hong Kong Sanatorium and Hospital
Abstract Preview: Purpose:
The Elekta Unity system facilitates daily adaptive radiotherapy using MRI-based treatment planning. However, MR images are prone to motion artefacts caused by respiratory motion, potential...
Authors: Anthony J. Doemer, Aharon Feldman, Ian Gallagher, Yimei Huang, Brett M. Miller, Benjamin Movsas, Kundan S Thind
Affiliation: Henry Ford Health
Abstract Preview: Purpose: CT-guided adaptive radiation therapy (CTgART) is a technical, resource intensive, procedure that involves many different radiation oncology team members. To ensure consistent, high-quality CT...
Authors: Min-Sig Hwang, Danny K. Lee, Daniel C. Pavord, Kyung Lim Yun
Affiliation: Allegheny Health Network
Abstract Preview: Purpose: Ensuring the quality of treatment plans through patient-specific pre-treatment quality assurance (QA) is essential. However, the use of physical phantom-based QA devices is not feasible for o...
Authors: Asma Amjad, Renae Conlin, Eric S. Paulson, Christina M. Sarosiek
Affiliation: Department of Radiation Oncology, Medical College of Wisconsin
Abstract Preview: Purpose:
MR-guided adaptive radiation therapy (MRgART) is transforming clinical workflows, requiring fast, accurate organs-at-risk (OARs) contouring. While deep learning auto-segmentation (DLAS) of...
Authors: Shahed Badiyan, Chien-Yi Liao, Mu-Han Lin, Dan Nguyen, Justin D. Visak, Hui Ju Wang, Brien Timothy Washington, Kenneth Westover, Yuanyuan Zhang
Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center, Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, TX, 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
Abstract Preview: Purpose: Knowledge-based planning (KBP) plays a crucial role in improving treatment plans by leveraging previous clinical data to guide new cases. KBP is applied to the Ethos 2.0 Intelligent Optimizat...
Authors: Eyub Y. Akdemir, Gregory A Azzam, Rupesh Kotecha, Gregory J. Kubicek, Natalia Lutsik, Eric Mellon, Siamak P. Nejad-Davarani, Parag Parikh, Karen C. Snyder
Affiliation: Miami Cancer Institute, Baptist Health South Florida, Department of Radiation Oncology, University of Miami, Henry Ford Health
Abstract Preview: Purpose: Resection cavity volumes shrink gradually over time after surgical resection of brain metastases. Fractionated stereotactic radiosurgery (fSRS) is often delivered to the cavity to prevent rec...
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: Gregory Bolard, Rabten Datsang, Sarah Ghandour, Timo Kiljunen, Pauliina Paavilainen, Sami Suilamo, Katlin Tiigi
Affiliation: Turku University Hospital, Virginia Commonwealth University, MVision AI, North Estonia Medical Centre, Docrates Cancer Center, Hopital Riviera-Chablais
Abstract Preview: Purpose: To verify the performance of a vendor-neutral deep learning model for synthetic CT generation from T2-weighted and balanced steady-state MR sequences to support both MR-only simulation and MR...
Authors: David P. Adam, William T. Hrinivich, Taoran Li, Alexander Lu, Michael Salerno, Alejandro Sisniega, Boon-Keng Kevin Teo
Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Johns Hopkins University, University of Pennsylvania
Abstract Preview: Purpose: Cone beam CT (CBCT)-guided online adaptive radiotherapy (ART) is of growing interest, with recent improvements in image quality provided through larger detector panels and fast gantry rotatio...
Authors: Sarah Dumont, Trevor Ketcherside, An Liu, William T. Watkins, Qiuyun Xu
Affiliation: RefleXion Medical, Department of Radiation Oncology, City of Hope National Medical Center
Abstract Preview: Purpose:
The RefleXion X1 SCINTIX algorithm convolves beam fluence with real-time PET distributions for tracking and plan adaptation, but radiotherapy Planning Target Volumes (PTVs) are often signi...
Authors: Ali Hosni, Oleksii Semeniuk, Andrea Shessel, Teo Stanescu
Affiliation: Princess Margaret Hospital, Princess Margaret Cancer Centre, Brown University Health
Abstract Preview: Purpose: To report on early clinical experience with a two-phase radiotherapy approach for esophageal cancer patients, utilizing CBCT-based conventional C-arm linear accelerator radiotherapy and MR-gu...
Authors: Liangzhong Xiang
Affiliation: University of California, Irvine
Abstract Preview: N/A...
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: Lili Chen, Xiaoming Chen, Chang Ming Charlie Ma, Joshua Meyer
Affiliation: Fox Chase Cancer Center
Abstract Preview: Purpose: Fast CBCT (HyperSight) acquisition technique together with a surface-guided breath-hold (SGBH) would allow a better image quality for accurate target/organ delineation. It facilitates breath-...
Authors: Rafe A. McBeth, Kuancheng Wang, Ledi Wang
Affiliation: Department of Radiation Oncology, University of Pennsylvania, Georgia Institute of Technology, University of Pennsylvania
Abstract Preview: Purpose:
The integration of AI in clinical workflows presents unprecedented opportunities to enhance treatment quality in radiation oncology, yet it also demands innovative approaches to address th...
Authors: Lando S. Bosma, Victoria Brennan, Nicolas Cote, ChengCheng Gui, Nima Hassan Rezaeian, Jue Jiang, Sudharsan Madhavan, Josiah Simeth, Neelam Tyagi, Harini Veeraraghavan, Michael J Zelefsky
Affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, NYU Langone Health, University Medical Center Utrecht, Memorial Sloan Kettering Cancer Center
Abstract Preview: Purpose: Deep learning-based deformable image registration (DIR) models often lack robustness when applied to datasets with differing imaging characteristics. We aimed to (1) improve registration netw...
Authors: Kim Creach, Kim Howard, Julius G. Ojwang, Richard A. Shaw, Neelu Soni
Affiliation: Mercy Hospital Springfield
Abstract Preview: Purpose: To present a standardized MRI-CT hybrid workflow for High-Dose-Rate (HDR) Image-Guided Adaptive Brachytherapy (IGBT) in cervical cancer, aligned with AAPM TG-303, as a model to assist with im...
Authors: David Byun, Ting Chen, Paulina E. Galavis, Allison McCarthy, Hesheng Wang, Michael J Zelefsky
Affiliation: NYU Langone Health
Abstract Preview: Purpose: To summarize a MR guided adaptive workflow developed for pelvic lymph nodes (PLN) stereotactic radiotherapy using large field size on Elekta Unity© MR Linac system, and to quantitatively anal...
Authors: Michael Cummings, Olga M. Dona Lemus, Hana Mekdash, Tyler Moran, Alexander R Podgorsak, Sean M. Tanny, Matthew J. Webster, Lexiang Yang, Dandan Zheng, Yuwei Zhou, Xiaofeng Zhu
Affiliation: Department of Radiation Oncology, University of Rochester, University of Miami, Inova Schar Cancer Institute, University of Rochester
Abstract Preview: Purpose: oART is revolutionizing radiotherapy by allowing treatment plans to be adjusted based on daily imaging, improving targeting precision and potentially enhancing patient outcomes. However, its ...
Authors: Anthony J. Doemer, Bing Luo, Benjamin Movsas, Humza Nusrat, Farzan Siddiqui, Chadd Smith, Kundan S Thind, Kyle Verdecchia
Affiliation: Department of Physics, Toronto Metropolitan University, Henry Ford Health
Abstract Preview: Purpose: Large-vision models (LVMs) are rapidly emerging, yet their application in radiation oncology remains largely unexplored. This study investigates the potential of LVMs for offline adaptive rad...
Authors: Daniel Ball, Alex Dresner, Geoffrey S. Ibbott, Leonard H. Kim, Christopher Tyerech, Sebastián Vega
Affiliation: MD Anderson Cancer Center at Cooper, Cooper Medical School of Rowan University, The American Board of Radiology, Department of Radiation Oncology, University of Pennsylvania, Rowan University, Philips Healthcare MR Oncology
Abstract Preview: Purpose:
In vivo dosimetry is valuable to radiation therapy for its ability to report the actual dose received by patients but is currently limited to surface and intracavitary measurements, leavin...
Authors: Bin Cai
Affiliation: University of Texas Southwestern Medical Center
Abstract Preview: N/A...
Authors: Jie Deng, Yunxiang Li, 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: Magnetic Resonance Imaging (MRI) has exceptional soft tissue contrast and an essential role in radiotherapy. The introduction of clinical MR-LINACs has enabled adaptive radiotherapy (ART) usi...
Authors: Min Geon Choi, Sean J. Domal, Ruiqi Li, Taoran Li, Mu-Han Lin, Yang Kyun Park, David D.M. Parsons, Justin D. Visak
Affiliation: Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, TX, UT Southwestern Medical Center, University of Texas Southwestern Medical Center, University of Pennsylvania, Department of Radiation Oncology, UT Southwestern Medical Center
Abstract Preview: Purpose: Ethos X-ray-guided online adaptive radiotherapy (ART) enables precise, daily adaptive treatments but requires significant resources, limiting widespread adoption. Many treatment sites do not ...
Authors: Mark Anastasio, Zong Fan, Hua Li, Changjie Lu, Lulu Sun, Xiaowei Wang, Zhimin Wang, Michael Wu
Affiliation: University of Illinois at Urbana-Champaign, University of Illinois at Chicago, Washington University School of Medicine, University of Illinois Urbana-Champaign, Washington University in St. Louis, University Laboratory High School
Abstract Preview: Purpose: Histological whole slide images (WSIs) are vital in clinical diagnosis. Although deep learning (DL) methods have achieved great success in this task, they often lack interpretability. Traditi...