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Results for "sct generation": 69 found

3D Image Quality Evaluation of a New CT Scanner Employing 3D Landmark Scans, Super Resolution Reconstruction, and Ag Beam Filtration

Authors: Ishika Bhaumik, John M. Boone, Michael T Corwin, Eric S Diaz, Ahmadreza Ghasemiesfe, Andrew M. Hernandez, Sarah E. McKenney, Misagh Piran, Ali Uneri, Eric L White

Affiliation: UC Davis, UC Davis Health, University of California, Johns Hopkins Univ

Abstract Preview: Purpose: A new model CT scanner (Canon Aquilion One Insight) was recently installed at our institution, and it included a 3D Landmark (3DLM) scan for automatic scan planning, a new deep learning recon...

3D Printed Electron Block Aperture Generation

Authors: David Chighvinadze, Lisa Czaplicki, Jeremy D. Donaghue, Lama K. Muhieddine Mossolly

Affiliation: Cleveland Clinic Sandusky, Cleveland Clinic Strongsville, Cleveland Clinic Fairview

Abstract Preview: Purpose:
Current electron block generation requires manual cutting of stryofoam and placement for pouring of the block which can lead to possible miscutting of blocks, and non-accurate rotations co...

4DCT Vs 5DCT: How to Generate an Accurate Target Volume

Authors: Ryan Andosca, Rojine T. Ariani, Peter Boyle, Minji Victoria Kim, Michael Vincent Lauria, Daniel A. Low, Claudia R. Miller, Drew Moghanaki, Louise Naumann, Dylan P. O'Connell, Ricky R Savjani

Affiliation: Department of Radiation Oncology, University of California, Los Angeles, University of California, Los Angeles, UCLA Radiation Oncology

Abstract Preview: Purpose: To demonstrate that 5DCT can provide an accurate internal tumor volume (ITV) while 4DCT cannot.
Methods: The 5DCT imaging protocol uses a motion model and 25 deformably registered free-bre...

A Bayesian Model for the Detection of Local Ventilation Changes in Lung Cancer Patients

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...

A Deep Learning-Based Method for Rapid Generation of Spot Weights in Single Field Optimization for Proton Therapy in Prostate Cancer

Authors: Yu Chang, Mei Chen

Affiliation: Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Department of Radiation Oncology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine

Abstract Preview: Purpose: Spot weights optimization, as a critical step in the proton therapy, is often time-consuming and labor-intensive. Deep learning, with its powerful learning and computational efficiency, can e...

A Diffusion-Based AI Framework for Continuous Deformable Image Registration and Time-Resolved Dynamic CT Generation

Authors: Mingli Chen, Xuejun Gu, Hao Jiang, Mahdieh Kazemimoghadam, Weiguo Lu, Gregory Szalkowski, 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: Respiratory motion management is crucial for accurate radiation delivery to moving targets while protecting healthy tissue, relying on time-resolved volumetric imaging and continuous deformab...

A Ground Truth Label-Mediated Method for Improved Bone and Gas Cavity Definition for MRI-Guided Online Adaptive Radiotherapy Workflows Using Synthetic CT Images.

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 (...

A Hybrid Radiomics-Integrated Machine Learning Framework for Early Identification of Potential Radiation Pneumonitis in Lung Cancer Patients

Authors: Christos Ilioudis, Marios Myronakis, Sotirios Raptis, Kyriaki Theodorou

Affiliation: Medical Physics Department, Medical School, University of Thessaly, Department of Information and Electronic Engineering, International Hellenic University (IHU)

Abstract Preview: Purpose: This study presents a radiomics-driven, machine learning framework developed to predict the possibility of Radiation Pneumonitis (RP), as a side effect of radiation therapy in lung cancer pat...

A Novel Integrated Framework for Rapid Automatic Calculation of Organ Absorbed Dose from kV-CBCT Imaging during Radiotherapy

Authors: Marios Myronakis, Kyriaki Theodorou

Affiliation: Medical Physics Department, Medical School, University of Thessaly

Abstract Preview: Purpose: The development of an integrated application framework for rapid, seamless, and automated calculation of absorbed organ dose for individual patients undergoing kV CBCT imaging over the course...

A Novel Method for Virtual Extension of Image-Derived Vasculature Segmentations

Authors: Raneem Atta, Alejandro Bertolet, Mislav Bobić, Wesley E. Bolch, Robert Joseph Dawson, Carlos Huesa-Berral, Harald Paganetti, Eric Wehrenberg-Klee

Affiliation: Massachusetts General Hospital, University of Florida, Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Massachusetts General Hospital and Harvard Medical School, Department of Radiology, Massachusetts General Hospital and Harvard Medical School

Abstract Preview: Purpose: Representations of intra-organ vasculature have a variety of uses in the field of computational dosimetry but generally rely on models derived from population-averaged reference individuals. ...

A Study of Large Model Alignment Techniques for MRI Images of Small Sample Meningioma

Authors: Xiangli Cui, Man Hu, Wanli Huo, Da Yao, Jianguang Zhang, Yingying Zhang, Shanyang Zhao

Affiliation: Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, the Zhejiang-New Zealand Joint Vision-Based Intelligent Metrology Laboratory, College of Information Engineering, China Jiliang University, Departments of Radiation Oncology, Zibo Wanjie Cancer Hospital, Department of Oncology, Xiangya Hospital, Central South University, Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University, Shandong Academy of Medical Sciences

Abstract Preview: Purpose:
To study the fine-tuning strategy of pre-trained AI image generation model to adapt to the generation of small sample meningioma MRI images, explore its impact on observer performance, and...

A Virtual 4DCT Generator Based on a Digital Phantom with Joint Cardiac and Respiratory Motions

Authors: Phillip Cuculich, Geoffrey D. Hugo, Xiwen Li, Michael T. Prusator, Clifford Robinson, Pamela Samson, Xue Wu

Affiliation: Washington University School of Medicine in St Louis, Washington University School of Medicine in St. Louis, University of Utah, WashU Medicine

Abstract Preview: Purpose:
For development of novel motion management methods it is useful to have a digital phantom capable of realistic simulation of respiratory 4DCT acquisition of the thorax, including cycle-to-...

A Window-Level Based Approach for Generating Missing Tissue in CT Scans Using a Transformer-Gan Model

Authors: Mojtaba Behzadipour, Siyong Kim, Mitchell Polizzi, Richard R. Wargo, Lulin Yuan

Affiliation: VCU Health - Department of Radiology, Virginia Commonwealth University

Abstract Preview: Purpose:
The purpose of this study is to develop a method for generating missing tissue in CT scans of patients with large body sizes, where the field of view (FOV) of the scanner fails to capture ...

AI Auto-Contouring for CT-Based High-Dose-Rate Interstitial Brachytherapy of Cervical Cancer: Implications for Organ-at-Risk (OAR) Contouring and Dosimetric Analysis

Authors: Indrin J. Chetty, Jing Cui, Mitchell Kamrava, Tiffany M. Phillips, Jennifer M. Steers, Brad Stiehl

Affiliation: Department of Radiation Oncology,Cedars-Sinai Medical Center, Cedars-Sinai Medical Center

Abstract Preview: Purpose: Auto-contouring for HDR interstitial brachytherapy can be confounded by large deformation in anatomy and image quality. Here we evaluated the performance of an AI-based auto-contouring softwa...

AI-Assisted 3D Microscale Mesh Models of Human Lungs from Iodine-Stained Serial-Sectioned Histology Images and Their Dosimetry Applications

Authors: John P. Aris, Wesley E. Bolch, Robert Joseph Dawson, Bonnie N. C. President, Yitian Wang

Affiliation: Johns Hopkins University, University of Florida

Abstract Preview: Purpose: Generation of a mesh-based microscale lung model is essential for accurate dosimetry analysis. Lungs exchange air with the environment and may be exposed to alpha-particle-emitting radionucli...

AI-Driven Troubleshooting for Truebeam Systems: Development and Testing of a Gpt-4o Chatbot

Authors: Sean P. Devan, Cory S. Knill, Charles K. Matrosic, Zheng Zhang

Affiliation: University of Michigan

Abstract Preview: Purpose: Physicists troubleshooting machine issues during patient treatments often face high-pressure situations, balancing error codes, resource constraints, and time-sensitive decisions. To streamli...

Advanced Modeling of Singlet Oxygen Distribution in Pleural Cavity Photodynamic Therapy Using Validated Geometric Standardization

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...

Advancing Thoracic Synthetic CT Images with Enhanced Cyclegan for Adaptive Radiotherapy Applications

Authors: Silambarasan Anbumani, Nicolette O'Connell, Eenas A. Omari, Amanda Pan, Eric S. Paulson, Lindsay Puckett, Monica E. Shukla, Dan Thill, Jiaofeng Xu

Affiliation: Elekta Inc, Elekta Limited, Linac House, Department of Radiation Oncology, Medical College of Wisconsin

Abstract Preview: Purpose: Accurate electron density information from on-board imaging is essential for direct dose calculations in adaptive radiotherapy (ART). This study evaluates a deep learning model for thoracic s...

An Adaptive Radiotherapy Approach Sparing Preirradiated Critical Structures

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...

An Adaptive Radiotherapy Strategy Study Based on Segmented Synthesis and Deformational Registration

Authors: Jie Hu, Zhengdong Jiang, Nan Li, Tie Lv, Yuqing Xia, Shouping Xu, Gaolong Zhang, Wei Zhao, Changyou Zhong

Affiliation: School of Physics, Beihang University, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Radiotherapy Department of Meizhou People’s Hospital (Huangtang Hospital), UT Health San Antonio, National Cancer Center/ National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, Peopleʼs Republic of China, Department of Radiation Oncology

Abstract Preview: Purpose: Patients usually undergo cone-beam computed tomography (CBCT) scans which are used for patient set-up before radiotherapy. However, the low image quality of CBCT hinders its use in adaptive r...

Assessment of Automated Planning Templates for Genitourinary and Gastrointestinal Disease Sites for Online MR-Guided Adaptive Radiotherapy

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...

Auto-Contouring of OAR Enhances Patient Safety and Workflow in Gamma Knife Stereotactic Radiosurgery

Authors: Sven Ferguson, S. Murty Goddu, Ana Heermann, Taeho Kim, Nels C. Knutson, Hugh HC Lee, Shanti Marasini, Timothy Mitchell, Seungjong Oh, Kevin Renick

Affiliation: Washington University in St. Louis School of Medicine, Washington University School of Medicine in St. Louis, Department of Radiation Oncology, Washington University School of Medicine in St. Louis

Abstract Preview: Purpose: In the Gamma Knife stereotactic radiosurgery (GK-SRS), the delineation of organs-at-risks (OARs) was not fully automated. Due to the cumbersome nature of manual OAR contouring, dose evaluatio...

Automated IMPT Treatment Planning for CSI: Enhancing Efficiency with Auto-Segmentation and Scripting

Authors: Katja M. Langen, William Andrew LePain, Robert Muiruri, Vivi Nguyen, Mosa Pasha, Roelf L. Slopsema, Alexander Stanforth, Yinan Wang, Mingyao Zhu

Affiliation: Emory Healthcare, Emory University, Department of Radiation Oncology and Winship Cancer Institute, Emory University

Abstract Preview: Purpose: Intensity modulated proton therapy (IMPT) treatment planning for craniospinal irradiation (CSI) is complex and requires extensive effort from the planner. This study aims to enhance planning ...

Automatic Breast VMAT Planning Using Script and Rapidplan on Eclipse

Authors: Maria Jose Almada, Bruno Forti, Patricia Murina, Carlos Daniel Venencia

Affiliation: Instituto Zunino - Fundacion Marie Curie, Dra.

Abstract Preview: Purpose: The use of VMAT for the breast requires duplication of the patient's CT, several planning structures, and patient-specific dose-volume constraints depending on the patient's anatomy, fraction...

CT-Free PET Imaging: Synthetic CT Generation for Efficient and Accurate PET-Based Planning

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...

Calorimetric Measurement of Absorbed Dose By a Flash Beamline

Authors: Luke Connell, Stephen F. Kry, Malcolm R. McEwen, Bryan R. Muir, James Renaud, Emil Schueler, Hayden Scott, Paige A. Taylor

Affiliation: National Research Council, The University of Texas MD Anderson Cancer Center, UT MD Anderson Cancer Center, Department of Radiation Physics, The University of Texas MD Anderson Cancer Center

Abstract Preview: Purpose: To demonstrate the capability of a robust calorimeter to accurately determine the absorbed dose delivered by an electron FLASH beamline.

Methods: Electron FLASH beams of 6 MeV and 9 Me...

Commissioning of Elekta Leipzig and Valencia Skin Applicators

Authors: Hamid Aghdam, DJ Chen, Heather Chen, Sharad Goyal, Yonas Solomon Mekuria, Martin Ojong-Ntui, Yuan James Rao

Affiliation: The George Washington University, The George Washington University Cancer Center

Abstract Preview: Purpose: Elekta Leipzig and Valencia Skin applicators are designed to treat skin lesions. The applicators limit the irradiation to the required treatment area using a densimet shielding. Valencia uses...

Cycle-Consistent Multi-Task Automated Segmentation and Synthetic CT Generation Model for Adaptive Proton Therapy

Authors: Derek Tang, Susu Yan

Affiliation: Massachusetts General Hospital

Abstract Preview: Purpose: To evaluate the performance of a multi-task automated-segmentation and synthetic CT generation model (sCT) and investigate its application in an adaptive proton therapy workflow.
Methods: ...

Deep Learning–Based Dose Prediction for Automated Proton Radiation Therapy Planning of Breast Cancer

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...

Development and Implementation of MRI-Only Simulation, Planning and Treatment Workflow for Pelvic Radiotherapy Using Synthetic CT on MR-Linac

Authors: Peter Balter, Elaine Eunnae Cha, Seungtaek Choi, Yao Ding, Eun Young Han, Yusung Kim, Rajat J. Kudchadker, Belinda Lee, Surendra Prajapati, Reza Reiazi, Ergys D. Subashi, Sarath Vijayan, Jinzhong Yang, Yao Zhao

Affiliation: The University of Texas MD Anderson Cancer Center

Abstract Preview: Purpose: This study evaluates the feasibility of an MR-only simulation, planning, and treatment (MROSPT) workflow for pelvic cancer patients using synthetic CT generated from MRI data. By validating s...

Enhanced Pelvic Organ Segmentation Using LLM-Driven Prompts for Prostate Cancer Low-Dose-Rate Brachytherapy

Authors: Yang Lei, Tian Liu, Ren-Dih Sheu, Meysam Tavakoli, Jing Wang, Kaida Yang, Jiahan Zhang

Affiliation: Icahn School of Medicine at Mount Sinai, Department of Radiation Oncology, Emory University

Abstract Preview: Purpose:
The study aimed to improve target and organ at risk (OAR) segmentation in low-dose-rate brachytherapy (LDR-BT) for prostate cancer treatment, by integrating clinical guidelines into deep l...

Enhancing Cyberattack Resiliency through the Radiotherapy Backup and Recovery Dashboard Tool

Authors: Yasin Abdulkadir, Justin Hink, James M. Lamb, Eric Nguyen, Justin Kyle Pijanowski, Yevgeniy Vinogradskiy

Affiliation: Department of Radiation Oncology, University of California, Los Angeles, Thomas Jefferson University

Abstract Preview: Purpose: To enhance a Radiation Oncology department’s cyberattack resiliency using a novel software that backs-up critical radiotherapy treatment information. The software returns essential informatio...

Enhancing Synthetic Pelvic CT Images from CBCT Using Vision Transformer with Adaptive Fourier Neural Operators

Authors: Rashmi Bhaskara, Oluwaseyi Oderinde

Affiliation: Purdue University

Abstract Preview: Purpose: This study proposes a novel approach to overcoming CBCT image quality limitations by developing an improved synthetic CT (sCT) generation method based on a CycleGAN architecture using Vision ...

Evaluating the Performance of Using Large Language Models to Automate Summarization of CT Simulation Orders in Radiation Oncology

Authors: Meiyun Cao, Edward L. Clouser, Xiaoning Ding, Jason Michael Holmes, Shaw Hu, Linda L. Lam, Wendy S. Lindholm, Wei Liu, Samir H. Patel, Diego Santos Toesca, Jason Sharp, Sujay A. Vora, Peilong Wang

Affiliation: Department of Radiation Oncology, Mayo Clinic, Mayo Clinic Arizona, George Washington University

Abstract Preview: Purpose: In current clinical workflow of radiation oncology departments, therapists manually summarize CT simulation orders into summaries before the CT simulation for execution. This process signific...

Evaluation of a Novel Multimodal Deformable Image Registration Algorithm for Pelvic MRI-CT Fusion in Radiotherapy

Authors: Christian Fiandra, Marco Fusella, Gianfranco Loi, Silvia Pesente, Lorenzo Placidi, Claudio Vecchi, Orlando Zaccaria, Stefania Zara

Affiliation: Abano Terme Hospital, University of Turin, Maggiore della Carità, Tecnologie Avanzate Srl, Fondazione Policlinico Universitario Agostino Gemelli IRCCS

Abstract Preview: Purpose: Deformable-image-registration (DIR) is essential in modern radiotherapy for adaptive RT, re-irradiation, and other clinical applications. Multimodal DIR is especially important in MRI-only wo...

Feasibility Study of Deep Learning-Based MRI-to-PET Generation for Rectal Cancer: Overall Survival Prediction and Pathological Complete Response Assessment

Authors: Weigang Hu, Zhenhao Li, Jiazhou Wang, Xiaojie Yin, Zhen Zhang

Affiliation: Fudan University Shanghai Cancer Center

Abstract Preview: Purpose:
This study aims to develop and validate a novel deep learning method to generate synthetic PET images for rectal cancer from MRI data. By incorporating metabolic information from the synth...

Feasibility of 3D Printing for Fabricating Anthropomorphic Kidney Phantoms

Authors: Gisell Ruiz Boiset, Paulo ROBERTO Costa, Wagner Henrique Marques, Raphael Morata, Victor H.F Oliveira

Affiliation: University of São Paulo (USP), Institute of Physics

Abstract Preview: Purpose: This study investigates the feasibility of 3D printing materials in creating anthropomorphic kidney phantoms that accurately simulate the radiological properties of human tissues, for applica...

Generation of Patient-Specific Phantom for Head & Neck Proton Therapy Based on Xcat

Authors: Cheng-En Hsieh, Shen-Hao Li, Hsin-Hon Lin, Shu-Wei Wu, An-Ci Yang

Affiliation: Department of Medical Imaging and Radiological Sciences, Chang Gung University, Proton and Radiation Therapy Center, Chang Gung Memorial Hospital, Proton and Radiation Therapy Center, Chang Gung Memorial Hospital Linkou

Abstract Preview: Purpose:
The aim of this study is to develop a framework of generating patient-specific phantom tailored for head and neck proton therapy. From these phantoms, digital reference objects based on th...

Generation of Virtual Lung PET Images from CT Data Via Deep Learning for Accelerated Tumor Detection and Preliminary Diagnosis

Authors: Pouya Azarbar, Nima Kasraie, Peyman Sheikhzadeh

Affiliation: UT Southwestern Medical Center, Shahid Beheshti University of Medical science, Imam Khomeini Hospital Complex,Tehran University of Medical Sciences

Abstract Preview: Purpose: Positron Emission Tomography (PET) is crucial for diagnosing and monitoring diseases due to its functional imaging capabilities. However, its high cost, significant radiation exposure, and li...

High-Fidelity Synthetic CT Generation from CBCT for Dibh Breast Cancer Patients Using Shortest Path Regularization

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....

High-Quality Patchnet (HQ-PatchNet) for Synthetic CT Generation in Head & Neck Imaging

Authors: So Hyun Ahn, Chris Beltran, Byongsu Choi, Jeong Heon Kim, Jin Sung Kim, Bo Lu, Justin Chunjoo Park, Bongyong Song, Jun Tan

Affiliation: Mayo Clinic, Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Ewha Medical Research Institute, Ewha Womans University College of Medicine, UC San Diego, Yonsei University College of Medicine

Abstract Preview: Purpose:
Cone-beam computed tomography (CBCT) is widely used in IGRT for patient positioning but suffers from low resolution and poor soft tissue contrast. Synthetic CT (sCT) generated from CBCT ad...

Icrp Mesh-Type Reference Computational Phantoms Representing Pregnant Women and Fetuses

Authors: Wesley E. Bolch, Chansoo Choi, Chan Hyeong Kim, Suhyeon Kim, Bangho Shin, Yeon Soo Yeom

Affiliation: Hanyang University, University of Florida, 2) Department of Radiation Convergence Engineering, Yonsei University

Abstract Preview: Purpose: Task Group 103 of International Commission on Radiological Protection (ICRP) recently released new-generation adult and pediatric mesh-type reference computational phantoms (MRCPs) via ICRP P...

Improving Adversarial Approaches to Synthetic CT Image Generation with Skin Surface Masks

Authors: Mahya Ahmadzadeh, Nagarajan Kandasamy, Keyur Shah, Gregory C. Sharp, Santhosh Vadivel, John MacLaren Walsh

Affiliation: Electrical and Computer Engineering Department, Massachusetts General Hospital, Emory University, Drexel University

Abstract Preview: Purpose: In image-guided radiotherapy (IGRT), cone beam CTs (CBCTs) suffer from distortions that degrade registration with planning CTs. While CycleGANs can generate synthetic CTs (sCTs) from CBCTs, e...

Improving TG-263 Target Name Compliance Using Locally-Hosted Large Language Models

Authors: Rex A. Cardan, Carlos E. Cardenas, Udbhav S. Ram

Affiliation: The University of Alabama at Birmingham, University of Alabama at Birmingham

Abstract Preview: Purpose: The AAPM TG-263 report provides nomenclature guidelines for target and normal tissue structures used in radiation oncology. Adherence to these guidelines is challenging for targets, as there ...

Integrating Clinical Knowledge Via Llms for Precise Organ-at-Risk Segmentation in Pancreatic Cancer SBRT

Authors: Karyn A Goodman, Yang Lei, Tian Liu, Pretesh Patel, Jing Wang, Kaida Yang, Jiahan Zhang

Affiliation: Icahn School of Medicine at Mount Sinai, Department of Radiation Oncology and Winship Cancer Institute, Emory University

Abstract Preview: Purpose: This study aims to improve organ-at-risk (OAR) segmentation in pancreatic cancer stereotactic body radiotherapy (SBRT) by integrating clinical guidelines into deep learning workflows. We use ...

Knee Image Generation Based on Fine-Tuning Stable Diffusion Model

Authors: Xiangli Cui, Zilei Fu, Man Hu, Wanli Huo, Xiaoqing Wu, Jianguang Zhang, Yingying Zhang

Affiliation: Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, the Zhejiang-New Zealand Joint Vision-Based Intelligent Metrology Laboratory, College of Information Engineering, China Jiliang University, Departments of Radiation Oncology, Zibo Wanjie Cancer Hospital, Department of Oncology, Xiangya Hospital, Central South University, Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University, Shandong Academy of Medical Sciences

Abstract Preview: Purpose:
Using Stable Diffusion to generate images of the knee in different disease states can enrich the medical imaging database and inject new vitality into the field of medical imaging analysis...

Knowledge-Based Deep Residual U-Net for Synthetic CT Generation Using a Single MR Volume for Frameless Radiosurgery

Authors: Justus Adamson, John Ginn, Yongbok Kim, Ke Lu, Trey Mullikin, Xiwen Shu, Chunhao Wang, Zhenyu Yang, Jingtong Zhao

Affiliation: Duke University, Duke Kunshan University

Abstract Preview: Purpose:
To develop a knowledge-based deep model for synthetic CT (sCT) generation from a single MR volume in frameless radiosurgery (SRS), eliminating the need for CT simulation prior to the SRS d...

Mask Guided Diffusion Model for Metal Artifacts Reduction

Authors: Shusen Jing, Qihui Lyu, Dan Ruan, Ke Sheng, Qifan Xu

Affiliation: Department of Radiation Oncology, University of California, Los Angeles, University of California San Francisco, Department of Radiation Oncology, University of California, San Francisco

Abstract Preview: Purpose: Metallic implants can significantly distort sinograms, leading to severe artifacts in computed tomography (CT) reconstructions. Reconstructing CT images containing metal is fundamentally an i...

Mask-Based Synthetic Contrast-Enhanced CT Generation for Advancing Data Limited Segmentation on Cardiac Substructure

Authors: Jin Sung Kim, Chanwoong Lee, Young Hun Yoon

Affiliation: Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine

Abstract Preview: Purpose: Chest contrast-enhanced CT (CECT) serves as a valuable tool for cardiac imaging, but its lack of detailed anatomical visualization limits its utility in segmentation tasks. While CECT offers ...

Multi-Vendor Validation of a Deep Learning-Based Synthetic CT Generation Model for MR-Only Radiotherapy Planning in the Pelvis

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...

Personalized and Automated Head & Neck Radiotherapy Planning with AI-Guided Optimization

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...

Portpy: An Open-Source Python Package to Accelerate Research in Radiotherapy Treatment Planning Optimization

Authors: Qijie Huang, Gourav Jhanwar, Saad Nadeem, Vicki Trier Taasti, Mojtaba Tefagh, Seppo Tuomaala, Masoud Zarepisheh

Affiliation: Varian Medical Systems Inc, Department of Clinical Medicine - Danish Center for Particle Therapy, Aarhus University Hospital, Memorial Sloan Kettering Cancer Center, The University of Edinburgh

Abstract Preview: Purpose:
We have developed PortPy (Planning and Optimization for Radiation Therapy in Python), a first-of-its-kind open-source package designed to accelerate research and development in radiotherap...

Prompt Preset for Imaging Physics Education and Board Style Question Generation: Development and Validation

Authors: Rose Al Helo, Shengwen Deng, Sven L. Gallo, David W. Jordan

Affiliation: Department of Radiology, Radiation Safety, University Hospitals Cleveland Medical Center, University Hospitals Cleveland Medical Center, Department of Radiology, Radiation Safety, University Hospitals Cleveland Medical Center; School of Medicine, Case Western Reserve University; Department of Radiology, Louis Stokes Cleveland VA Medical Center

Abstract Preview: Purpose: From an educator perspective, preparing test questions for trainees is time-consuming and requires a lot of quality verification steps (review of stems, distractors, referencing) that can pot...

Radio-Acoustic Monitoring of Electron Flash Therapy In Vivo

Authors: Kristina Bjegovic, Luke Connell, Emil Schueler, Leshan Sun, Lucy Whitmore, Liangzhong Xiang

Affiliation: University of California, Irvine, MD Anderson, Department of Radiation Physics, The University of Texas MD Anderson Cancer Center

Abstract Preview: Purpose: The use of FLASH-RT in the clinic would greatly reduce off-target radiation toxicity in normal tissues. However, due to the hypo-fractionated delivery of prescribed doses at FLASH dose rates,...

Real-Time Fully Automated IMRT Planning without Optimization Process Using a Two-Step AI Framework

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...

Retrospective Planning Study for the Evaluation of Biological Effectiveness of Spatially Fractionated Radiation Therapy with Gamma-Knife Radiosurgery on Brain Metastases

Authors: Brankica Andelic, Young-Bin Cho, Tara M. Gray, Bingqi Guo, Andrew Robert Hadfield, Hakan Nordstrom, Jacob Scott, John Suh, Nara Yoon

Affiliation: Adelphi University, Elekta, Cleveland Clinic

Abstract Preview: Purpose: To investigate the biological effect of Spatially Fractionated Radiation Therapy (SFRT) within Gamma-Knife (GK) using retrospective planning for brain metastases patients. This study presents...

Robustness of Deep Learning-Based Motion Compensated 4D-CBCT Reconstruction to out-of-Distribution Data

Authors: Geoffrey D. Hugo, Eric Laugeman, Thomas R. Mazur, Pamela Samson, Kim A. Selting, Zhehao Zhang

Affiliation: University of Illinois, Washington University in St. Louis School of Medicine, WashU Medicine

Abstract Preview: Purpose: To investigate the robustness of a deep learning (DL)-based 4D-CBCT motion-compensated (MoCo) reconstruction method to out-of-distribution data.
Methods: Our developed 4D-CBCT reconstructi...

Simplified Method of Assessing Lung Volume Limits during the Planning Process in the Re-Treatment Environment

Authors: Sameera Kumar, Chang Ming Charlie Ma, Robert A. Price

Affiliation: Fox Chase Cancer Center

Abstract Preview: Purpose:
Difficulty assessing lung limits during treatment planning in the retreatment environment can be compounded as limits are volume-based (ie. VxGy<37%) and require a critical volume with a m...

Streamlining Hippocampal-Sparing Whole-Brain VMAT Planning: Enhancing Efficiency and Plan Quality with an Automated Workflow

Authors: Eric C. Ford, Yulun He, Minsun Kim, Dustin Melancon, Juergen Meyer, Dong Joo Rhee, Yinghua Tao

Affiliation: Department of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, MD Anderson Cancer Center, University of Washington

Abstract Preview: Purpose: To develop and evaluate an automated-planning technique capable of generating high-quality treatment plans for hippocampal-sparing-whole-brain radiation therapy.
Methods: An auto-planning ...

Synthesizing High-Quality Hepatic Vascular Tree Segmentation Datasets to Improve Segmentation Model Performance

Authors: Trevor McKeown, Deshan Yang, Zhendong Zhang

Affiliation: Duke University, Department of Radiation Oncology, Duke University

Abstract Preview: Purpose: Accurate delineation of liver blood vascular structures is crucial for planning and executing therapeutic interventions in liver-related medical procedures. However, current auto-segmentation...

Synthetic CT Generation from a Cycle Diffusion Model Based Framework for Ultrasound-Based Prostate HDR Brachytherapy

Authors: Michael Baine, Charles Enke, Yang Lei, Yu Lei, Ruirui Liu, Su-Min Zhou

Affiliation: Icahn School of Medicine at Mount Sinai, University of Nebraska Medical Center, Department of Radiation Oncology, University of Nebraska Medical Center

Abstract Preview: Purpose: This study presents a framework for generating synthetic CT images using a Cycle Diffusion model, which can be utilized to enhance needle conspicuity in ultrasound-guided prostate HDR brachyt...

Synthetic Vs. Conventional Planar Imaging: Performance and Clinical Feasibility

Authors: Jennifer Kwak, Chelsea Manica, Justin K. Mikell, Michael Silosky, Wendy Siman

Affiliation: Washington University School of Medicine in St. Louis, University of Colorado Anschutz Medical Campus, School of Medicine, Rocky Vista University

Abstract Preview: Purpose:
This study evaluates synthetic planar imaging (synP) from SPECT projections against conventional planar imaging, focusing on detectability, spatial resolution, and feasibility. SynP allows...

Teaching an Old Dog New Tricks: Unlocking Hidden Potential in Existing Frameworks for Versatile Radiotherapy Applications

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...

Text-Conditioned Latent Diffusion Model for Synthesis of Contrast-Enhanced CT from Non-Contrast CT

Authors: Yizheng Chen, Michael Gensheimer, Mingjie Li, Lei Xing

Affiliation: Department of Radiation Oncology, Stanford University

Abstract Preview: Purpose: Automatically translating non-contrast to contrast-enhanced computed tomography (CT) images is critical for improving clinical workflow, reducing heathcare cost, minimizing radiation exposure...

Tumor Density on Time-Weighted Mid-Position Images for Thoracic Tumors

Authors: Katrinus Keijnemans, Eric S. Paulson, An Tai

Affiliation: Department of Radiotherapy, University Medical Center Utrecht, Department of Radiation Oncology, Medical College of Wisconsin

Abstract Preview: Purpose: Time-weighted mid-position images (MidPs), derived from four-dimensional computed tomography (4DCT) via deformable image registration (DIR), are frequently selected for treatment planning due...

Uncertainties on Synthetic-CT Generation from CBCT: Another Layer of Complexity in Abdominal Adaptive Radiotherapy

Authors: Laura I. Cervino, Wendy B. Harris, Paulo Quintero, Hao Zhang

Affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center

Abstract Preview: Purpose: To evaluate the impact of the prediction uncertainty from CBCT-based synthetic CT (sCT) generation in abdominal adaptive radiotherapy.

Methods: CT and CBCT images from 65 abdominal pat...

Using a Generative Adversarial Network (GAN) for Source Particle Generation in Monte Carlo Radiation Therapy Simulations

Authors: Jiankui Yuan, Dandan Zheng, Tingliang Zhuang

Affiliation: Medical Artificial Intelligence and Automation (MAIA) Laboratory, Department of Radiation Oncology, UT Southwestern Medical Center, University of Rochester, Varian Medical Systems, Advanced Oncology Solutions

Abstract Preview: Purpose: In Monte Carlo (MC) radiation therapy dose calculations, latent variance exists when directly applying phase-space files (PSF) with a finite number of source particles, while the latter is pr...

Validation of Updated CT-to-SPR Calibration Method with Icrp-145 Data for Carbon-Ion Radiotherapy

Authors: Min Cheol Han, Soorim Han, Chan Hyeong Kim, Jin Sung Kim, Seok-Ho Lee, Gahee Son, Yongdo Yun

Affiliation: Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Hanyang University, Department of Integrative Medicine, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine

Abstract Preview: Purpose: The stoichiometric calibration method proposed by Kanematsu et al. (2016) has been widely adopted for CT number to stopping-power ratio (SPR) conversion in carbon-ion radiotherapy. With the r...

Virtual Monoenergetic Imaging for Radiotherapy: A Single CT Acquisition for Both Target Delineation and Dose Calculation

Authors: Harold Y Hu, Yanle Hu, Shuai Leng, Maryam Sadeghian, Joe Swicklik

Affiliation: Mayo Clinic Arizona, Basis Scottsdale, Mayo Clinic

Abstract Preview: Purpose: Radiotherapy CT simulation often requires two scans: a non-contrast scan for dose calculation and a contrast-enhanced scan for target delineation. Photon-counting-detector (PCD) CT allows the...