Authors: Sean L. Berry, Hsiang-Chi Kuo, Seng Boh Gary Lim, Ingrid Valencia Lozano, Laszlo Voros
Affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center
Abstract Preview: Purpose:
To quantify the impact of target degradation on 6FFF beam output by analyzing the output trends and adjustment frequencies at our clinic on a flattening filter-free (6FFF) and a flattened ...
Authors: Yunxiang Li, Hua-Chieh Shao, Chenyang Shen, Jing Wang, Jiacheng Xie, Shunyu Yan, 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) Laboratory, 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 liver deformable motion tracking is essential in image-guided radiotherapy to enable precise tumor targeting during treatment. We developed a conditional point cloud diffusion model ...
Authors: Chuxiong Ding, Xuejun Gu, Heejung Kim, Weiguo Lu, Yang Kyun Park, Yulong Yan
Affiliation: 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, Stanford University School of Medicine
Abstract Preview: Purpose: The purpose of this study was to develop and evaluate a Monte Carlo (MC) dose calculation software (DosemanCK) for secondary dose verification of CyberKnife (CK) treatment plans. Unlike tradi...
Authors: Weiguo Lu, Jax Luo, Xiaoxue Qian, 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, Harvard Medical School
Abstract Preview: Purpose:
Semi-supervised segmentation leverages sparse annotation information to learn rich representations from combined labeled and label-less data for segmentation tasks. This study leverages th...
Authors: Stephen R. Bowen, Chunyan Duan, Daniel S. Hippe, Qiantuo Liu, Jing Sun, Jiajie Wang, Shouyi Wang, Faisal Yaseen, Xiaojing Zhu
Affiliation: Tongji University, University of Washington, Department of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, Shanghai University of Electric Power, Fred Hutchinson Cancer Center, University of Texas at Arlington
Abstract Preview: Purpose: Accurate prediction of patient response to radiotherapy plays a crucial role in monitoring disease progression and assessing treatment efficacy, enabling clinicians to develop personalized th...
Authors: Xiaolong Fu, Runping Hou, Md Tauhidul Islam, Lei Xing
Affiliation: Department of Radiation Oncology, Stanford University, Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine
Abstract Preview: Purpose: To introduce a novel schematic image representation of radiomics data, called OmicsMap, for high-performance deep radiomics analysis. OmicsMap transforms tabular radiomics data into an image ...
Authors: Juan-Francisco Calvo-Ortega, Andrew Cousins, Ashley Cullen, Andrew Dipulia, Peter B. Greer, Seng Boh Gary Lim, Shih-Chi Lin, D. Michael Lovelock, Conor McGarry, Victoria Robinson, Cameron Stanton, Baozhou Sun, Ching-Ling Teng, Gemma Warner, Benjamin J. Zwan
Affiliation: Northern Ireland Cancer Centre, Baylor College of Medicine, Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Christchurch Hospital, Northwell, Central Coast Cancer Centre, Calvary Mater Hospital, Hospital Quironsalud Barcelona, Icahn School of Medicine at Mount Sinai, Chris O'Brien Lifehouse, University of Newcastle
Abstract Preview: Purpose: This multi-institution Electronic Silicon-based Remote Survey of Small-field Output (ESPRESSO) study aims to develop the remote audit process to evaluate the safety of single-isocenter multi-...
Authors: Hua-Chieh Shao, Chenyang Shen, Jiacheng Xie, Shunyu Yan, 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) Laboratory, 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: Motion-resolved CBCT imaging, which reconstructs a dynamic sequence of CBCTs reflecting intra-scan motion (one CBCT per x-ray projection), is highly desired for regular/irregular motion chara...
Authors: Ashok Bhandari, Kurtis Johnson, Yu Lei, Tianzhe Li, Kyuhak Oh, Shuo Wang, Chi Zhang, Su-Min Zhou
Affiliation: University of Nebraska Medical Center
Abstract Preview: Purpose: The purpose of this study was to leverage neural network visualization tools to detect high-attention areas indicative of treatment failure in lung SBRT by examining correlation matrices betw...
Authors: Mingli Chen, Xuejun Gu, Hao Jiang, Mahdieh Kazemimoghadam, Weiguo Lu, Qingying Wang, 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:
PET is used in radiotherapy workflows for accurate target delineation. However, a separate CT scan is typically required for attenuation correction in PET imaging and for registering PET-d...
Authors: Wesley A. Belcher, Aidan Burke, Matthew Green, Taylor Stamey
Affiliation: ECU Health, East Carolina University Brody School of Medicine
Abstract Preview: Purpose: The purpose of this study was to determine the effect of using deep inhalation breath hold (DIBH) vs. free breathing (FB) and intensity-modulated radiation therapy (IMRT) vs. 3D for right-sid...
Authors: Laura I. Cervino, Karen Episcopia, Hsiang-Chi Kuo, Sangkyu Lee, Seng Boh Gary Lim, Shih-Chi Lin, Grace Tang
Affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center
Abstract Preview: Purpose: This study evaluated the performance of the HyperSight Cone-Beam Computed Tomography (CBCT) system on a TrueBeam C-arm LINAC (TB) and two Ethos ring-gantry LINACs (ES) for adaptive radiation ...
Authors: Nrusingh C. Biswal, Sally Cheston, Sung-Woo Lee, Weiguang Yao, Baoshe Zhang
Affiliation: Department of Radiation Oncology, University of Maryland School of Medicine
Abstract Preview: Purpose: The deep inspiration breath-hold (DIBH) technique in left breast radiation reduces doses to critical organs such as the heart, left lung, and left anterior descending artery (LAD). With the a...
Authors: Sorour Hosseini, YuHuei Jessica Huang, Jeremy Kunz, Nicholas Pierre Nelson, Ryan G. Price, Prema Rassiah, Hui Zhao
Affiliation: University of Utah, Department of Radiation Oncology, Huntsman Cancer Institute, University of Utah
Abstract Preview: Purpose: To investigate the feasibility and clinical implications of creating customized workflows in a new SGRT system: LUNA 3D (LAP, Florida).
Methods: Three clinical SGRT workflows were designed...
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: Carlos E. Cardenas, Udbhav S. Ram, Marcin Wierzbicki
Affiliation: The University of Alabama at Birmingham, University of Alabama at Birmingham, Juravinski Cancer Centre
Abstract Preview: Purpose:
This study aims to systematically evaluate the dosimetric properties and delivery efficiency of 6X-FFF and 10X-FFF beams for lung SBRT on the Varian TrueBeam STx using the Eclipse TPS 16.1...
Authors: James Brugarolas, Meixu Chen, Raquibul Hannan, Payal Kapur, Jing Wang, Kai Wang
Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, UT Southwestern Medical Center, Department of Radiation Oncology, University of Maryland Medical Center
Abstract Preview: Purpose: Accurate prognosis of clear cell renal cell carcinoma (ccRCC) is essential for guiding personalized treatment planning. In this study, we present a multi-modal ensemble model (MMEM) that inte...
Authors: Fei Han, James M. Lamb, Michael Vincent Lauria, Daniel A. Low, Tessa Elizabeth Maurer, Danilo Maziero, Claudia R. Miller, Drew Moghanaki, Louise Naumann, Nicolas Viot
Affiliation: Department of Radiation Oncology, University of California, Los Angeles, Siemens Healthineers, UCLA, University of California Los Angeles
Abstract Preview: Purpose: Patients with lung disease outside radiotherapy are barred from high dose protocols used for motion modeling, but MRI could offer no-dose alternatives. Image-based ventilation is a promising ...
Authors: Stephen R. Bowen, Richard Cheng, Kylie Kang, Janice Kim, Ana Paula Santos Lima, Dominic A. Maes, Juergen Meyer, Karen Ordovas, Kerry Reding
Affiliation: Department of Radiation Oncology, University of Washington, Department of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, Department of Radiology, University of Washington, Division of Cardiology, University of Washington, Department of Biobehavioral Nursing and Health Informatics, School of Nursing, University of Washington
Abstract Preview: Purpose: Artificial intelligence (AI)-based auto-segmentation tools can increase the efficacy and reproducibility of radiotherapy (RT) treatment planning. This study evaluates the quality of AI-genera...
Authors: Yu Gao, Lei Xing, Siqi Ye
Affiliation: Department of Radiation Oncology, Stanford University
Abstract Preview: Purpose:
Limited-angle CBCT (LA-CBCT) scans are often the only option for non-coplanar radiation therapy to prevent potential mechanical collisions. However, the consecutive angular occlusion of pr...
Authors: Clemens Grassberger, David (Bo) McClatchy, Harald Paganetti
Affiliation: Department of Radiation Oncology, University of Washington and Fred Hutchinson Cancer Center, Massachusetts General Hospital
Abstract Preview: Purpose: While randomized controlled trials (RCTs) are the gold standard for demonstrating efficacy, nearly 50% of late-stage clinical trials fail to meet their endpoint. Tools to study the design of ...
Authors: John Byun, Steven D Chang, Mingli Chen, Cynthia Chuang, Xuejun Gu, Melanie Hayden Gephart, Yusuke Hori, Hao Jiang, Mahdieh Kazemimoghadam, Fred Lam, Gordon Li, Lianli Liu, Weiguo Lu, David Park, Erqi Pollom, Elham Rahimy, Deyaaldeen Abu Reesh, Scott Soltys, Gregory Szalkowski, Lei Wang, Qingying Wang, Zi Yang, Xianghua Ye, Kangning Zhang
Affiliation: Department of Radiation Oncology, Stanford University, 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: Accurate prediction of pain relief is crucial in determining the clinical effectiveness of Stereotactic body radiotherapy (SBRT) regimen for spine metastases. We propose a deep-learning frame...
Authors: Yang Sheng, Qingrong Jackie Wu, Qiuwen Wu, Xin Wu, Dongrong Yang
Affiliation: Duke University Medical Center
Abstract Preview: Purpose:
This study aims to leverage large language model (LLMs) to develop a human-in-the-loop agentic framework, enhancing the efficiency of treatment planning in radiotherapy.
Methods:
A L...
Authors: Stephen R. Bowen, Chunyan Duan, Daniel S. Hippe, Qiantuo Liu, Jiajie Wang, Shouyi Wang, Faisal Yaseen, Han Zhou
Affiliation: Tongji University, University of Washington, Department of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, Fred Hutchinson Cancer Center, University of Texas at Arlington
Abstract Preview: Purpose: Predicting the effects of the spatial-temporal tumor response to chemoradiation can assist in adjusting radiation dose and support clinical decision-making in radiotherapy. A multi-instance l...
Authors: Hassan Bagher-Ebadian, Ahmed I Ghanem, Joshua P. Kim, Chengyin Li, Rafi Ibn Sultan, Kundan S Thind, Dongxiao Zhu
Affiliation: Wayne State University, Department of Radiation Oncology, Henry Ford Health-Cancer, Detroit, MI and Alexandria Department of Clinical Oncology, Faculty of Medicine, Alexandria University, Henry Ford Health
Abstract Preview: Purpose: Accurate segmentation of the Left Anterior Descending (LAD) artery in free-breathing 3D treatment planning CT is crucial for radiotherapy but remains challenging due to its small size, comple...
Authors: Victor B. Kassey, Maciej M. Kmiec, Periannan Kuppusamy, Ryan C. O'Connell, Sergey V. Petryakov, Conner Ubert
Affiliation: Dartmouth College
Abstract Preview: Purpose: High-resolution magnetic field uniformity is essential for quantitative and pre-clinical MRI research. Imaging uniformity is affected by the B0 field, which can be corrected using manual or a...
Authors: Hua-Chieh Shao, Guoping Xu, You Zhang, Tingliang Zhuang
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:
Advancements in onboard X-ray hardware allow high-quality CBCT imaging with a short scan time (~6s for Varian HyperSight), enabling CBCT-based dose calculation and treatment planning. Howe...
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: Hua-Chieh Shao, Shanshan Tang, Jing Wang, Kai Wang, 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, Medical Artificial Intelligence and Automation (MAIA) Laboratory, Department of Radiation Oncology, UT Southwestern Medical Center, Department of Radiation Oncology, University of Maryland Medical Center
Abstract Preview: Purpose: Artifacts caused by gas bubble movement in the gastrointestinal tract can severely degrade the image quality of on-board abdominal cone-beam computed tomography (CBCT), impacting its utility ...
Authors: Mingli Chen, Xuejun Gu, Hao Jiang, Mahdieh Kazemimoghadam, Weiguo Lu, Qingying Wang, 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:
This work demonstrates how existing software, when creatively adapted, can address a wide range of clinical challenges. By focusing on data exploration and application-specific modificatio...
Authors: Stephen R. Bowen, Shijun Chen, Chunyan Duan, Daniel S. Hippe, Qiantuo Liu, Qianqian Tong, Jiajie Wang, Shouyi Wang, Faisal Yaseen
Affiliation: The University of Texas at Austin, Tongji University, University of Washington, Department of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, Fred Hutchinson Cancer Center, University of Texas at Arlington
Abstract Preview: Purpose: Tumor subregion clustering and prediction of region-specific response can augment assessments and adaptive treatment decisions. A modeling framework was constructed to predict chemoradiation ...
Authors: Yunxiang Li, Weiguo Lu, 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:
Curating high-quality, labeled data for medical image segmentation can be challenging and costly, considering the existence of various image domains with differing modalities/protocols. Cr...
Authors: Muhammad Ramish Ashraf, Kerriann Casey, Suparna Dutt, Jie Fu, Edward Elliot Graves, Xuejun Gu, Hao Jiang, Brianna Caroline Lau, Billy W Loo, Weiguo Lu, Rakesh Manjappa, Stavros Melemenidis, Erinn Bruno Rankin, Lawrie Skinner, Luis Armando Soto, Murat Surucu, Vignesh Viswanathan, Zi Yang, Amy Shu-Jung Yu
Affiliation: Department of Radiation Oncology, University of Washington and Fred Hutchinson Cancer Center, 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, Department of Comparative Medicine, Stanford University School of Medicine, Department of Radiation Oncology, Stanford University Cancer Center
Abstract Preview: Purpose: The intestine is a classical preclinical model for studying radiation injury, and histological quantification of intestinal crypts is a key assay for assessing this response. However, substan...