Authors: Todd A Aguilera, Gaurav Khatri, Jiaqi Liu, Hao Peng, Nina N. Sanford, Robert Timmerman, Haozhao Zhang
Affiliation: Department of Radiation Oncology, UT Southwestern Medical Center, UT southwestern medical center, UT Southwestern Medical Center, Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center
Abstract Preview: Purpose:
This study first integrates 3D topological data analysis with radiomics from local advanced rectal cancer T2-weighted MRI to evaluate therapeutic responses and quantify treatment-induced c...
Authors: Gary Y. Ge, Charles Mike Weaver, Jie Zhang
Affiliation: University of Kentucky
Abstract Preview: Purpose: The recently introduced CMS regulation on CT dose and image quality mandates the use of global noise as the metric for image quality assessment. The regulation cites two methods for calculati...
Authors: Mubasheer Chombakkadath, Tara E. Tyson, Iris Z. Wang
Affiliation: Roswell Park Comprehensive Cancer Center, University at Buffalo (SUNY)
Abstract Preview: Purpose: Deformable image registration (DIR) is critical in adaptive radiation therapy (ART). Existing DIR phantoms either simulate tumor shape or volume changes but lack comprehensive motion simulati...
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: Lavsen Dahal, Francesco Ria, Ehsan Samei, Justin B. Solomon, Liesbeth Vancoillie, Yakun Zhang
Affiliation: Duke University, Carilion Clinic, Clinical Imaging Physics Group, Department of Radiology, Duke University Health System
Abstract Preview: Purpose: Clinical diagnostic task-based optimization of CT procedures require precise and organ-specific assessments. This study investigates inter-organ noise variability to highlight the limitations...
Authors: Yile Fang, Leslie Lamb, Nathaniel David Mercaldo, Kai Yang
Affiliation: Massachusetts General Hospital
Abstract Preview: Purpose: To quantitatively evaluate power-law exponent β as a potential image-based breast cancer risk factor.
Methods: Two groups of breast cancer screening cohorts (target vs. control, 20 sub...
Authors: Rami M. Shorti, Gary R. Stinnett
Affiliation: Intermountain Health, Radiation Oncology, Intermountain Health, Advanced Visualization Engineering Department
Abstract Preview: Purpose: In this work we present the workflow, materials analysis, and lessons learned from leveraging advanced 3D printing Polyjet Technology to print conformal bolus for radiation therapy.
Method...
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: Kyle J. Lafata, Xiang Li, Megan K. Russ, Zion Sheng
Affiliation: Duke University, Department of Radiation Oncology, Duke University, Clinical Imaging Physics Group, Department of Radiology, Duke University Health System
Abstract Preview: Purpose: To adapt Vision-Language Foundational Models (VLFM) to perform HNSCC tumor grading on H&E whole slide images (WSI) via attention-based multiple instance learning (ABMIL).
Methods: We utili...
Authors: David L. Barbee, David Byun, Matt Long, Jose R. Teruel Antolin, Michael J Zelefsky
Affiliation: NYU Langone Health
Abstract Preview: Purpose:
Online adaptive MR-Linac therapy requires contour adaptation, often adding 20 minutes to treatment time and reducing machine throughput. This study introduces a fully automated MR contour ...
Authors: Matthew R. Hoerner, Maryam Naseri, Mena Shenouda
Affiliation: Yale University School of Medicine, Yale University
Abstract Preview: Purpose: To evaluate acquisition parameters of computed tomography (CT) scanner protocols across different machines to provide patients and clinicians consistent care and image quality, respectively.<...
Authors: Krystal M. Kirby, Aliasghar Rohani, Christopher W. Schneider, Sotirios Stathakis
Affiliation: Mary Bird Perkins Cancer Center, Louisiana State University, Baton Rouge, Louisiana
Abstract Preview: Purpose: Accurate treatment delivery in MR-guided radiotherapy (MRgRT) systems requires consistent imaging quality assurance (QA) to assess MR image quality. However, standard QA phantoms have limited...
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: Magdalena Bazalova-Carter, James Day, Xinchen Deng
Affiliation: University of Victoria
Abstract Preview: Purpose:
Ring artifacts in Photon-Counting Computed Tomography (PCCT) images can degrade image quality. this study aims to suppress ring artifacts with a novel autoencoder-based framework that leve...
Authors: Jacqueline M. Andreozzi, Tess Armstrong, Shiva Bhandari, John M Bryant, Jessica M Frakes, David J. Gladstone, Sarah E Hoffe, Kujtim Latifi, Arash Naghavi, Steven Nichols, Ibrahim M. Oraiqat, Russell Palm, Gage H. Redler, Stephen A Rosenberg, Joseph Weygand
Affiliation: Department of Radiation Oncology and Applied Science, Dartmouth Health, Thayer School of Engineering, Dartmouth College, Department of Radiation Oncology, Ohio State University, Moffitt Cancer Center, Department of Radiation Oncology, Moffitt Cancer Center
Abstract Preview: Purpose: The MR-linac provides unique opportunities for integrating advanced imaging into radiotherapy workflows, but the lower sensitivity of systems like the 0.35T model can pose challenges for diff...
Authors: Chloe Duncan, Andrew Kanawati, Peter Malek, Tess Reynolds
Affiliation: University of Sydney, Westmead Hospital, Image X Institute, Faculty of Medicine and Health, The University of Sydney
Abstract Preview: Purpose: Pedicle screw fixation, a standard spinal surgery procedure, has high misplacement rates (~40%) which decrease with surgeon experience. However, opportunities for surgical rehearsal, training...
Authors: Edward Robert Criscuolo, Chenlu Qin, Deshan Yang, Zhendong Zhang
Affiliation: Duke University, Department of Radiation Oncology, Duke University
Abstract Preview: Purpose:
Low-dose CT (LDCT) imaging minimizes radiation exposure but introduces significant noise, compromising image quality. While deep learning-based denoising models such as HFormer achieve sta...
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: Mengqi Shen, Meghna Trivedi, Tony J.C. Wang, Andy (Yuanguang) Xu, Yading Yuan
Affiliation: Columbia University Medical Center, Dept of Med Hematology & Oncology, Data Science Institute at Columbia University, Columbia University Irving Medical Center, Department of Radiation Oncology, Columbia University Irving Medical Center
Abstract Preview: Purpose: T2-weighted (T2w) images are critical for identifying pathological changes due to their superior contrast in differentiating tissue types. However, they often lack detailed anatomical resolut...
Authors: Nebi Demez, Michael Kasper, Noufal Manthala Padannayil, Shyam Pokharel, Suresh Rana, Lauren A. Rigsby, Tino Romaguera, Nishan Shrestha, Somol Sunny
Affiliation: Lynn Cancer Institute, Boca Raton Regional Hospital, Baptist Health South Florida
Abstract Preview: Purpose: Accurate delineation of the urethra is critical for optimizing tumor control and minimizing urethral toxicity in prostate stereotactic body radiation therapy (SBRT). The purpose of this study...
Authors: Diana Cardona, Casey C. Heirman, William Jeck, Kyle J. Lafata, Xiang Li, Lauren M. Neldner, Jeffrey S. Nelson, Megan K. Russ, Ehsan Samei
Affiliation: Duke University, Department of Radiation Oncology, Duke University, Department of Pathology, Duke University, Clinical Imaging Physics Group, Department of Radiology, Duke University Health System
Abstract Preview: Purpose: Medical physicists traditionally support radiation-based medicine, but their expertise is translatable to image-based fields like pathology. As pathology transitions to digital practices, phy...
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: Olubunmi Odunola Aregbe, Clara Ferreira, Margaret Reynolds, David A. Sterling, Jianling Yuan
Affiliation: University of Minnesota, University of Minnesota Physicians, Department of Radiation Oncology, University of Minnesota, Minneapolis
Abstract Preview: Purpose: To analyze volume changes in the high-risk clinical target volume (HR-CTV) during high-dose rate (HDR) brachytherapy for cervical cancer patients. The study aims to evaluate the trend and cor...
Authors: Michael Evan Chaga, Timothy Chen, Darra M. Conti, Jing Feng, Wenzheng Feng, Joseph Hanley, Jeff Stainsby, Tingyu Wang
Affiliation: Synaptive Medical, Hackensack Meridian Health, Jersey Shore University Medical Center
Abstract Preview: Purpose:
The Synaptive MRI is a 0.5T superconducting head only system (first US install 2023). This is the first study that evaluates the geometric accuracy using a Sun Nuclear MR Distortion and Im...
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: Manju Liu, Weiwei Sang, Yanyan Shi, Zhenyu Yang, Fang-Fang Yin, Chulong Zhang, Lihua Zhang, Rihui Zhang
Affiliation: Jiahui International Hospital, Jiahui International Hospital, Radiation Oncology, Duke Kunshan University, Medical Physics Graduate Program, Duke Kunshan University
Abstract Preview: Purpose: This study aims to transform cone-beam computed tomography (CBCT) images acquired from deep inspiration breath-hold (DIBH) breast cancer patients into high-fidelity synthetic CT (sCT) images....
Authors: Xinhua Li, Jie Zhang, Yifang (Jimmy) Zhou
Affiliation: University of Kentucky, Cedars-Sinai Medical Center
Abstract Preview: Purpose: Fat volume fraction (FVF) is an important biomarker for non-alcoholic fatty liver disease. CT can be a good modality for FVF assessment if the accuracy is adequate. We aimed to study the impa...
Authors: Olubunmi Odunola Aregbe, Clara Ferreira, Margaret Reynolds, David A. Sterling
Affiliation: University of Minnesota, University of Minnesota Physicians, Department of Radiation Oncology, University of Minnesota, Minneapolis
Abstract Preview: Purpose: Current best practices recommend daily imaging and planning for Tandem and Ring (T&R) HDR patient plans. Accurate target delineation is a critical, yet time consuming step in this process. Th...
Authors: Matthew R. Hoerner, Allison Shields
Affiliation: Yale University School of Medicine, Yale University
Abstract Preview: Purpose: To investigate the quality and clinical utility of chest x-rays synthesized from CT scans (sCXR).
Methods: Five helical chest CT exams were chosen for evaluation: this cohort represented a...
Authors: Yasaman Anbari, Srinivas Cheenu Kappadath, Benjamin P. Lopez
Affiliation: University of Houston, UT MD Anderson Cancer Center
Abstract Preview: Purpose: To improve lung dosimetry for 90Y-radioembolization planning, CT-based techniques have been proposed for patient-specific lung mass estimation instead of assuming nominal 1 kg lung masses. He...
Authors: Rico Castillo, Katherine Gonzalez, Casey C. Heirman, Kyle J. Lafata, Casey Y. Lee, Xiang Li, Yvonne M Mowery, Yvonne M Mowery, Daniel Murphy, Allison Pittman, Ashlyn G. Rickard
Affiliation: Duke University, Department of Radiation Oncology, Duke University, University of Pittsburgh
Abstract Preview: Purpose: To evaluate the ability of a deep learning model to identify pathomic features in lymph nodes of preclinical head and neck squamous cell carcinoma (HNSCC) models as surrogates for predicting ...
Authors: Ali Ajdari, Alice Bondi, Thomas R. Bortfeld, Gregory Buti, Xinru Chen, Zhongxing Liao, Antony John Lomax, Ting Xu
Affiliation: The University of Texas MD Anderson Cancer Center, Department Of Radiation Oncology, Massachusetts General Hospital (MGH), Massachusetts General Hospital & Harvard Medical School, Paul Scherrer Institut, ETH Zurich
Abstract Preview: Title: Addressing Imaging and Biomarker-driven Uncertainty in Machine Learning-based Radiotherapy Outcome Prediction
Alice Bondi, Gregory Buti, Antony Lomax, Thomas Bortfeld, Xinru Chen, Ting Xu, Z...
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: 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: Yeona Cho, Chloe Min Seo Choi, Joseph O. Deasy, Jue Jiang, Jihun Kim, Jin Sung Kim, Nikhil Mankuzhy, Aneesh Rangnekar, Andreas Rimner, Maria Thor, Harini Veeraraghavan, Abraham Wu
Affiliation: University of Freibrug, Department of Medical Physics, Memorial Sloan Kettering Cancer Center, 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, Memorial Sloan Kettering Cancer Center, Yonsei University
Abstract Preview: Purpose: We hypothesized that combining clinical, imaging, and radiotherapy dose-distribution features could increase predictive model accuracy in radiation-induced severe acute esophagitis (SAE) in e...
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: Amy Fitzpatrick, Kim Howard, Julius G. Ojwang, Neelu Soni
Affiliation: Mercy Hospital Springfield
Abstract Preview: Purpose: This study evaluates the dosimetric advantages and workflow improvements of the CyberKnife S7 Precision Treatment Planning System (TPS) with the VOLO optimizer for stereotactic radiosurgery (...
Authors: Manju Liu, Ning Wen, Fuhua Yan, Yanzhao Yang, Zhenyu Yang, Haoran Zhang, Lei Zhang, Yajiao Zhang
Affiliation: Department of Radiology, Ruijin Hospital Shanghai Jiaotong University School of Medicine, Duke Kunshan University, Medical Physics Graduate Program, Duke Kunshan University
Abstract Preview: Purpose: Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy where precise segmentation of tumors and adjacent vessels is crucial for effective treatment planning. This study dev...
Authors: Njood Alsaihati, Francesco Ria, Ehsan Samei, Justin B. Solomon, Martina Talarico, Jered Wells
Affiliation: Duke University, Clinical Imaging Physics Group, Department of Radiology, Duke University Health System
Abstract Preview: Purpose: Radiation dose and associated risk in X-ray imaging is principally informed by patient size, further used in Computed Tomography (CT) to achieve prescribed image quality levels through tube c...
Authors: Matthew S Brown, John M. Hoffman, William Hsu, Grace Hyun Kim, Michael F. McNitt-Gray, Spencer Harrison Welland, Anil Yadav
Affiliation: Department of Bioengineering, UCLA, David Geffen School of Medicine at UCLA, UCLA Department of Radiology
Abstract Preview: Purpose: Non-contrast CT (NCCT) is frequently used in initial evaluation of suspected stroke to rule out intracerebral hemorrhage. Quantitative scoring systems like the Alberta Stroke Program Early CT...
Authors: Annie Cooney, Kenneth L. Homann, Somayeh Taghizadehghahremanloo, Adam D. Yock, Hong Zhang
Affiliation: Assistant Professor, Vanderbilt University Medical Center
Abstract Preview: Purpose:
Digital radiotherapy data has been standardized using the DICOM format. However, different radiotherapy software environments interpret identical data differently due to inherent software ...
Authors: Aditya P. Apte, Joseph O. Deasy, Yusuf Emre Erdi, Anqi Fu, Johannes Hertrich, Andrew Jackson, Usman Mahmood, Jason Ocana, Trahan Sean, Amita Shukla-Dave
Affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center
Abstract Preview: Purpose: Automated AI-based quantitative CT tools hold immense promise for advancing clinical decision-making, yet their reproducibility and generalizability remain vulnerable to variability in imagin...
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...