Authors: John J. DeMarco, Farideh Pak, Olivia Grahm C Valadie
Affiliation: Cedars Sinai, Cedars-Sinai, Cedars-Sinai Medical Center
Abstract Preview: Purpose: To investigate the performance of the Integral Quality Monitor (IQM) device for patient-specific QA, focusing on segment-by-segment signal evaluation compared to cumulative signal evaluation....
Authors: Weiguo Lu, 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
Abstract Preview: Purpose:
Neural network-based lesion segmentation remains a significant challenge due to the low contrast between lesions and surrounding tissues (high ambiguity) and the variability of lesion shap...
Authors: Penghao Gao, Zejun Jiang
Affiliation: 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: Real-time tumor tracking can effectively compensate for the impact of respiratory motion on dose distribution. We propose a patient-specific external-internal correlation model driven by opti...
Authors: Pradeep Bhetwal, Wookjin Choi, Adam Dicker, Rupesh Ghimire, Yingcui Jia, Lauren Nkwonta, Yevgeniy Vinogradskiy, Wentao Wang, Maria Werner-Wasik
Affiliation: Thomas Jefferson University
Abstract Preview: Purpose: Multi-disciplinary clinics are becoming standard of care for patients with lung cancer treated with SBRT. To improve clinical decision support in a multi-disciplinary clinic, it would be bene...
Authors: Deepak Agrawal, Subhash Gupta, Shashanksharad Kale, Gopishankar Natanasabapathi, Manoj Phalak, Dhanabalan Rajasekaran, Surendra Kumar Saini, Subramani Vellaiyan
Affiliation: All India Institute of Medical Sciences (AIIMS), All India Institute of Medical Sciences
Abstract Preview: Purpose:
To evaluate planning strategy for uveal melanoma tumor (UM) in gamma knife stereotactic radiosurgery (GKSRS) using Lightning inverse planning software for treatment planning.
Methods:
Authors: Hongjing Sun, Timothy C. Zhu
Affiliation: University of Pennsylvania
Abstract Preview: Purpose: This study aims to develop a model of singlet oxygen distribution in pleural photodynamic therapy (PDT) by combining standardized anatomical coordinates with CT-validated geometry reconstruct...
Authors: Shae Gans, Carri K. Glide-Hurst, Mark Pankuch, Chase Ruff, Niek Schreuder, Nicholas R. Summerfield, Yuhao Yan
Affiliation: Departments of Human Oncology and Medical Physics, University of Wisconsin-Madison, Northwestern Medicine Proton Center, Northwestern Medicine Chicago Proton Center, Leo Cancer Care
Abstract Preview: Purpose: Novel upright patient positioners coupled with diagnostic-quality vertical CT at treatment isocenter introduce a significant opportunity for improved image-guided particle therapy. Treating p...
Authors: Sarah A. Ashmeg, Travis James McCaw, Joseph Shields, Matthew Spector, Christopher Tyerech, Christopher T Wilke
Affiliation: UPMC Hillman Cancer Center, UPMC Hillman Cancer Center and University of Pittsburgh School of Medicine, Department of Radiation Oncology, UPMC Hillman Cancer Center, Department of Radiation Oncology, University of Pennsylvania, UPMC
Abstract Preview: Purpose: Patients with oral cavity cancer often undergo surgical extirpation prior to radiation, and surgical implants are utilized to reconstruct the resulting defect. This study dosimetrically evalu...
Authors: Hao-Wen Cheng, Jonathan G. Li, Chihray Liu, Wen-Chih Tseng, Guanghua Yan
Affiliation: University of Florida
Abstract Preview: Purpose: This study develops and evaluates deep learning (DL) models for predicting 3D dose distributions in simultaneous integrated boost (SIB) prostate cancer treatment using the Elekta Unity MR-Lin...
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: Sam Beddar, Jason Michael Holmes, Daniel G. Robertson, James J. Sohn, Ethan D. Stolen
Affiliation: Department of Radiation Oncology, Mayo Clinic, MD Anderson Cancer Center, Department of Radiation & Cellular Oncology, University of Chicago, Department of Radiation and Cellular Oncology, University of Chicago
Abstract Preview: Purpose: Camera-based scintillation dosimetry incorporating large volumes have shown promise for fast and comprehensive evaluation of external beam treatment fields. While some efforts have been made ...
Authors: Theodore Higgins Arsenault, Beatriz Guevara, Rojano Kashani, Raymond F. Muzic, Gisele Castro Pereira, Alex T. Price
Affiliation: University Hospitals Seidman Cancer Center, Case Western Reserve University Department of Biomedical Engineering
Abstract Preview: Purpose: Accurate dose prediction in radiotherapy is essential for treatment planning. This study evaluates four nnUnet-based models using the OpenKBP head and neck dataset: a baseline model (Model 1)...
Authors: Hector Andrade-Loarca, Ines Butz, Chiara Gianoli, Prof. Gitta Kutyniok, Jianfei Li, Katia Parodi, Prof. Vincenzo Patera, Angelo Schiavi, Prof. Ozan Öktem
Affiliation: Sapienza University of Rome, Department of Mathematics, Royal Institute of Technology, School of Computation, Information and Technology, Technische Universitaet Muenchen, Department of Medical Physics, Ludwig-Maximilians-Universität München (LMU Munich), Department of Mathematics, Ludwig-Maximilians-Universität (LMU) München, Department of Medical Physics, Ludwig-Maximilians-Universität (LMU) München
Abstract Preview: Purpose: To explore and demonstrate the feasibility of accurate and fast prediction of the water equivalent thickness (WET) distribution of tissue traversed by a proton imaging pencil beam, aiming at ...
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: 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: Zixu Guan, Takahiro Iwai, Takashi Mizowaki, Mitsuhiro Nakamura, Michio Yoshimura
Affiliation: Kyoto University, Department of Radiation Oncology and Image-applied Therapy, Graduate School of Medicine, Kyoto University
Abstract Preview: Purpose:
The goal of this study is to develop a fully automated treatment planning approach for VMAT in pancreatic cancer that can convert patient anatomy into LINAC machine parameters. In this wor...
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: Ahssan Balawi, Peter Jermain, Timothy Kearney, Sonali Rudra, Michael H. Shang, Markus Wells, Mohammad Zarenia
Affiliation: Department of Radiation Medicine, MedStar Georgetown University Hospital
Abstract Preview: Purpose: To investigate the applicability and accuracy of a deep learning (DL) model in predicting radiation dose distribution for breast cancer patients treated with pencil-beam-scanning proton radio...
Authors: Julia Bauer, Tianxue Du, Katia Parodi, Marco Pinto, Thomas Tessonnier
Affiliation: Department of Medical Physics, Ludwig-Maximilians-Universität (LMU) München, Heidelberg Ion Beam Therapy Center (HIT), Department of Radiation Oncology, Heidelberg University Hospital, Department of Medical Physics, Ludwig-Maximilians-Universität München (LMU Munich)
Abstract Preview: Purpose:
Carbon ion therapy could benefit from range verification due to its sensitivity to range uncertainties. Positron emission tomography (PET) aids in this and comparing irradiation-induced PE...
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: Dennis A. Cheek, Wei Luo, Cameron Thayer-Freeman, Brien Timothy Washington
Affiliation: UT Southwestern Medical Center, University of Kentucky, Department of Radiation Medicine, University of Kentucky
Abstract Preview: Purpose: To investigate the effect of variation in the α/β of cervical cancer on clinical outcome for cervix cancer patients treated with radiation therapy.
Methods: A distribution of experimentall...
Authors: Chieh-Ya Chiu, Shen-Hao Li, Hsin-Hon Lin, Shu-Wei Wu
Affiliation: Department of Medical Imaging and Radiological Sciences, Chang Gung University, Proton and Radiation Therapy Center, Chang Gung Memorial Hospital Linkou
Abstract Preview: Purpose: Monte Carlo simulation enables precise calculation of dose distribution in proton therapy through tracing the radiation particles with patient tissues. However, achieving clinical-level preci...
Authors: Zakaria Aboulbanine, Greeshma A. Agasthya, Paul Inman, Anuj J. Kapadia, Anthony Hong Cheol Lim, Jayasai Ram Rajagopal, Chris C. Wang
Affiliation: Oak Ridge National Laboratory, Georgia Institute of Technology
Abstract Preview: Purpose: Radiobiological simulation via TOPAS-nBio requires significant computational resources and time to provide meaningful results. This study aims to decrease simulation time and computational re...
Authors: Li Chen, Shouliang Ding, Xiaoyan Huang, Lecheng Jia, Hua Li, Hongdong Liu, Yanfei Liu, Zun Piao, Guangyu Wang
Affiliation: 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, Shenzhen United Imaging Research Institute of Innovative Medical Equipment
Abstract Preview: Purpose: Optimal radiotherapy planning is challenging, influenced by anatomical factors such as surrounding organs and tumor characteristics, which complicate dose distribution and target coverage. Wh...
Authors: Jacob S. Buatti, Kristen A. Duke, Malena Fassnacht, Neil A. Kirby, Parker New, Niko Papanikolaou, Arkajyoti Roy, Yuqing Xia, Michelle de Oliveira
Affiliation: The University of Texas San Antonio, UT Southwestern Medical Center, UT Health San Antonio
Abstract Preview: Purpose:
Quantifying and visualizing uncertainty is critical for building clinical trust in AI-generated dose distributions. This study evaluates Monte Carlo Dropout (MCD), Snapshot Ensemble (SE), ...
Authors: Yang Sheng, Qingrong Jackie Wu, Qiuwen Wu, Xin Wu, Dongrong Yang
Affiliation: Duke University Medical Center
Abstract Preview: Purpose:
Treatment planning for intensity-modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) relies on inverse planning, an iterative and non-intuitive process of adjust...
Authors: Mojtaba Behzadipour, Suman Gautam, Tianjun Ma, Ikchit Singh Sangha, Bongyong Song, William Song, Kumari Sunidhi
Affiliation: UC San Diego, Virginia Commonwealth University
Abstract Preview: Purpose: This study aims to develop a knowledge-based voxel-wise dose prediction system using a convolutional neural network (CNN) for high-dose-rate (HDR) prostate brachytherapy and to evaluate its p...
Authors: Christopher Ackerman, Chang Chang, Yan-Cheng Huang, Robert Kaderka, Che Lin, Hsin-Chih Lo, Iain MacEwan, Yi-Chin Tu, James Urbanic
Affiliation: University of California San DIego, Taiwan AI Labs, National Taiwan University, California Protons Cancer Therapy Center, University of Miami, Sylvester Comprehensive Cancer Center
Abstract Preview: Purpose: To investigate the performance of an existing AI beam angle prediction model on external patient datasets for liver proton treatments. The AI model was trained on datasets exclusively from on...
Authors: Smith Apisarnthanarax, Stephen R. Bowen, Sunan Cui, Jie Fu, Clemens Grassberger, Yulun He, Yejin Kim, Matthew J. Nyflot, Sharon Pai
Affiliation: Department of Radiation Oncology, University of Washington and Fred Hutchinson Cancer Center, Department of Radiation Oncology, University of Washington, University of Washington, Department of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, Department of Physics, University of Washington, University of Washington and Fred Hutchinson Cancer Center
Abstract Preview: Purpose: 99mTc-sulfur colloid SPECT imaging enables quantitative assessment of voxel-wise liver function in patients with hepatocellular carcinoma (HCC). Accurately predicting post-radiotherapy (RT) l...
Authors: Ibtisam Almajnooni, Victor Cobilean, Milos Manic, Harindra Sandun Mavikumbure, Elisabeth Weiss, Lulin Yuan
Affiliation: Virginia Commonwealth University
Abstract Preview: Purpose: This study aims to optimize the 3D U-Net architecture for dose prediction in lung cancer radiation therapy (RT) plans, particularly in scenarios with limited clinical data, as well as to quan...
Authors: Seungtaek Choi, Laurence Edward Court, Eun Young Han, Yusung Kim, Hunter S. Mehrens, Tucker J. Netherton, Shiqin Su
Affiliation: The University of Texas MD Anderson Cancer Center, Department of Radiation Physics, The University of Texas MD Anderson Cancer Center
Abstract Preview: Purpose: Automated treatment planning is gaining traction for its enhanced consistency and efficiency. A key challenge, however, lies in the inability of neural network dose predictions directly trans...
Authors: Ricardo Garcia Santiago, Narges Miri, Daryl P. Nazareth, Ankit Pant, Mukund Seshadri
Affiliation: Roswell Park Comprehensive Cancer Center
Abstract Preview: Purpose: To develop a transformer-based deep learning network framework for predicting VMAT dose distributions. This can provide fast and efficient calculations with accuracies potentially comparable ...
Authors: Leslie Harrell, Sanjay Maraboyina, Romy Megahed, Maida Ranjbar, Xenia Ray, Pouya Sabouri
Affiliation: Department of Radiation Oncology, University of Arkansas for Medical Sciences (UAMS), University of California San Diego
Abstract Preview: Purpose: Real-time adaptive radiation therapy (ART) dynamically modifies patients’ treatment plan during delivery to account for anatomical and physiological variations. Addressing ART planning time v...
Authors: Katja M. Langen, Mark McDonald, Bill Stokes, Yinan Wang, Suk Whan (Paul) Yoon
Affiliation: Emory University, Department of Radiation Oncology and Winship Cancer Institute, Emory University
Abstract Preview: Purpose: Effective dose management in high-risk re-irradiation (ReRT) patients entails early, detailed special physics consultation (SPC) to mitigate risks from cumulative radiation dose. SPCs have tr...
Authors: Daisuke Kawahara, Takaaki Matsuura, Yuji Murakami, Ryunosuke Yanagida
Affiliation: Hiroshima High-Precision Radiotherapy Cancer Center, Department of Radiation Oncology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Department of Radiation Oncology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima
Abstract Preview: Purpose: In recent years, automation in radiation therapy planning using AI has gained significant attention to reduce the workload of treatment planners. Adaptive Radiation Therapy (ART), as a new fo...
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: Mingli Chen, Xuejun Gu, Hao Jiang, Mahdieh Kazemimoghadam, Weiguo Lu, Qingying Wang, Zi Yang, 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: Dose prediction (DP) is essential in guiding radiotherapy planning. However, current DP models for intensity-modulated radiation therapy (IMRT) primarily rely on fixed-beam orientations and a...