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Results for "paired 120": 58 found

A Comparison of the Impact to Mean Doses to Organs at Risk of Small Versus Large Spot Sizes in Pelvic Proton Therapy

Authors: Jamie s Baker, Sam Beddar, Mahsa Dehghanpour, Ariel MT Hoang, Emma Holliday, Rachael M. Martin Paulpeter, Joshua S. Niedzielski, Luis Augusto Perles, Josie S Ruzek, Gabriel O. Sawakuchi

Affiliation: MD Anderson Cancer Center, The University of Texas MD Anderson Cancer Center, UT MD Anderson Cancer Center, niversity of Texas MD Anderson Cancer Center School of Health Professions, Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, University of Texas MD Anderson Cancer Center School of Health Professions

Abstract Preview: Purpose: This study aims to evaluate the dosimetric impact on organs at risk (OAR) of small versus large spot sizes when treating pelvic cancer patients with pencil beam scanning (PBS) proton therapy....

A Deep Learning Approach to the Prediction of Gamma Passing Rates in VMAT Radiotherapy Plans for Adaptive Treatment.

Authors: Jenghwa Chang, Kuan Huang, Lyu Huang, Jason Lima, Jian Liu, Farzin Motamedi

Affiliation: Northwell, Department of Computer Science and Technology, Kean University, Physics and Astronomy, Hofstra University, Hofstra University Medical Physics Program

Abstract Preview: Title: A Deep Learning Approach to the Prediction of Gamma Passing Rates in VMAT Radiotherapy Plans for Adaptive Treatment.
Purpose: This study aims to develop a deep learning algorithm to predict ...

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 Modular Approach to Reversible and Stackable Medical Imaging Translation Models: CBCT-Based Synthetic MRI with Multiple U-Nets in Series (MUNETs)

Authors: Eric Chang, Nguyen Phuong Dang, Andrew Lim, Lauren Lukas, Lijun Ma, Yutaka Natsuaki, Zhengzheng Xu, Hualin Zhang

Affiliation: Radiation Oncology, Keck School of Medicine of USC

Abstract Preview: Purpose: Harnessed the power of AI and Deep Learning (DL), Generalized Neural Network models for medical image transformation are trained to predict target images from reference images, often requirin...

A Self-Supervised Deep Learning Approach for Automatic Identification and Metal Artifact Reduction in Cone-Beam CT for Brachytherapy

Authors: Rani Anne', Wenchao Cao, Yingxuan Chen, Wookjin Choi, Firas Mourtada, Yevgeniy Vinogradskiy

Affiliation: Thomas Jefferson University

Abstract Preview: Purpose: In-room mobile cone-beam CT (CBCT) is emerging to enhance high-dose-rate (HDR) brachytherapy workflow using on-demand imaging. However, metal artifacts from X-ray markers inside gynecological...

A Tumor Tracking Method in Surface-Guided Radiotherapy

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...

Advancing Cardiac Sparing with Upright Patient Geometry and Deep Learning

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...

Advancing Flash Radiotherapy: Intercomparison of Parameters between Two Institutions to Optimize Clinical Applications.

Authors: Amir Abdollahi, Celine Karle, Michele M. Kim, Constantinos Koumenis, Andrea Mairani, Erato Stylianou Markidou

Affiliation: Heidelberg Ion-Beam Therapy Center - Department of Radiation Oncology, German Cancer Research Centre(DKFZ), University of Pennsylvania, Physics Dep. University of Cyprus

Abstract Preview: Purpose: The aim is to compare FLASH dose-rate RT generated with protons and carbon (HIT) and compare to protons (UPenn) to provide evidence for equipotency of FLASH vs. standard RT to tumor growth co...

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...

Adversarial Diffusion-Based Self-Supervised Learning for High-Resolution MR Imaging

Authors: Zachary Buchwald, Chih-Wei Chang, Zach Eidex, Richard L.J. Qiu, Mojtaba Safari, Shansong Wang, Xiaofeng Yang, David Yu

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

Abstract Preview: Purpose: MRI offers excellent soft tissue contrast for diagnosis and treatment but suffers from long acquisition times, causing patient discomfort and motion artifacts. To accelerate MRI, supervised d...

Anatomical Noise Power Exponent (β) As an Image-Based Risk Factor for Breast Cancer

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...

Application of a Conditional Diffusion Model to Improve Real-Time MR Imaging in Online Adaptive MR-Guided Radiotherapy

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...

Artificial Intelligence-Powered Conventional Energy Integrating Detector-Based Coronary CT Angiography: Learning High-Resolution and Multi-Energy Imaging from Photon-Counting Detector CT

Authors: Shaojie Chang, Thomas A. Foley, Hao Gong, Emily Koons, Shuai Leng, Cynthia H. McCollough, Eric E. Williamson

Affiliation: Mayo Clinic

Abstract Preview: Purpose: To enhance coronary CT angiography (cCTA) capabilities on conventional energy integrating detector CT (EID-CT) using artificial intelligence (AI). The AI framework incorporates high-resolutio...

Assessing the Risks of Synthetic MRI Data in Deep Learning: A Study on U-Net Segmentation Accuracy

Authors: Chuangxin Chu, Haotian Huang, Tianhao Li, Jingyu Lu, Zhenyu Yang, Fang-Fang Yin, Tianyu Zeng, Chulong Zhang, Yujia Zheng

Affiliation: The Hong Kong Polytechnic University, Nanyang Technological University, Australian National University, Medical Physics Graduate Program, Duke Kunshan University, North China University of Technology, Duke Kunshan University

Abstract Preview: Purpose: Deep learning segmentation models, such as U-Net, rely on high-quality image-segmentation pairs for accurate predictions. However, the recent increasing use of generative networks for creatin...

Assessment of Image Quality and Dose in Dual-Energy X-Ray Imaging for Lung Tumor Tracking

Authors: Nawal Alqethami, Felix Ginzinger, Prasannakumar Palaniappan, Marco Riboldi, Philipp Steininger, Wentao Xie

Affiliation: Research & Development, medPhoton GmbH, Department of Medical Physics, Ludwig-Maximilians-Universität (LMU) München, Department of Medical Physics, Ludwig-Maximilians-Universität München (LMU Munich)

Abstract Preview: Purpose:
This study evaluates the image quality of Dual-Energy (DE) X-ray imaging for lung tumor tracking across various sizes and protocols, comparing its imaging dose to Single-Energy (SE) imagin...

Biologically Guided Deep Learning for MRI-Based Brain Metastasis Outcome Prediction after Stereotactic Radiosurgery

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...

Brain Tumor Segmentation from Multi-Parametric MRI with Integrated Evidential Uncertainty Estimation

Authors: Sahaja Acharya, Matthew Ladra, Junghoon Lee, Lina Mekki

Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Department of Biomedical Engineering, Johns Hopkins University

Abstract Preview: Purpose: Multi-parametric MRI (mpMRI) is widely used for deep learning (DL)-based automatic segmentation of brain tumors. While multi-contrast images concatenated as channels are typically input to ne...

CBCT Dose Measurement for Common Protocols on Elekta Versahd and Varian Truebeam

Authors: Yingxuan Chen, Jun Li, Alexis N. Webb

Affiliation: Thomas Jefferson University

Abstract Preview: Purpose: Cone-beam computed-tomography (CBCT) is widely used for image-guided therapy. Cumulative dose from repeated CBCT might be a concern. This study aims to measure and compare the CBCT dose for c...

Characterizing a VMAT Optimization Algorithm with Integrated Static-Angle Modulated Ports for Esophageal Cancer Treatment

Authors: Lei Dong, Yin Gao, Taoran Li, Michael Salerno, Boon-Keng Kevin Teo, Melissa Vila

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

Abstract Preview: Purpose: A novel solution, RapidArc Dynamic-RAD (Varian Medical Systems, Palo Alto, USA) has been implemented to integrate VMAT with modulation of IMRT-like static-angle ports, including use of a dyna...

Comparison of Cine Cardiac Magnetic Resonance (CMR) Imaging Performance: 0.6 T Versus 1.5 T, Is 0.6 T Fit for Purpose?

Authors: Jacinta E. Browne, Tzu Cheng Chao, Ajit Deveraj, Ece Ercan, Tim Leiner, Alessio Perazzolo, Michal Povazan, Jouke Smink, Camilla Vita, Spencer Waddle, Dinghui Wang

Affiliation: Università Cattolica del Sacro Cuore, Philips Healthcare, Mayo Clinic

Abstract Preview: Purpose:
In recent years, mid-field MRI has shown promise to meet the technical demands of cardiac imaging1. Mid-field strengths offer advantages to CMR due to shorter T1-relaxation times, lower sp...

Comparison of Portal Dosimetry and Delta4® for Pretreatment QA of Sfrt-VMAT Plans

Authors: Tianyuan Dai, Zejun Jiang, Xiangyue Kong

Affiliation: Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Department of Radiation Oncology Physics and Technology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences

Abstract Preview: Purpose:
This study aims to evaluate the reliability of SFRT-VMAT plan verification by comparing two QA methods: Portal Dosimetry (PD) and Delta4®.
Methods:
Preteatment QA was conducted for 1...

Contrast-Free Enhancement of Coronary Artery Stenosis: Synthetic Ccta from Non-Contrast CT Using Diffusion Model

Authors: Abdusalam Abdukerim

Affiliation: Institute for Medical Imaging Technology, Ruijin Hospital

Abstract Preview: Purpose:
Coronary computed tomography angiography (CCTA) is the gold-standard non-invasive test for coronary artery disease (CAD), but iodine contrast agents (ICA) pose limitations in specific popu...

Deep Learning Aided Oropharyngeal Cancer Autoplanning

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...

Deep Learning-Based Segmentation Using Cine Epid Images for Real-Time Tumor Monitoring

Authors: Fumiaki Komatsu, Shunsuke Moriya, Ryosuke Nakamura, Takeji Sakae, Toshiyuki Terunuma, Tetsuya Tomita

Affiliation: Graduate School of Comprehensive Human Sciences, University of Tsukuba, Institute of Medicine, University of Tsukuba, Proton Medical Research Center, University of Tsukuba, Department of Radiology, University of Tsukuba Hospital

Abstract Preview: Purpose: To develop a deep learning (DL) model capable of accurately tracking lung tumors independent of beam angle variations.
Methods: A thoracic dynamic phantom simulating lung motion in the sup...

Deep Learning-Based Ventricular Auto-Segmentation for Dosimetric Analysis in Intraventricular Tumor SRS

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...

Deep-Dive Comparative Assessment between Digitally Reconstructed Radiographs and X-Ray Digital Radiographs from Lung CT Scans

Authors: Xinyi Fu, Dan Ruan, Ke Sheng

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:
Digitally reconstructed radiographs (DRRs) are easy to generate and widely used to establish research protocols in pulmonary diagnosis and image-guided radiotherapy tasks. A question remai...

Deep-Learning Based Spectral Artifact Removal with In Vivo 7T Proton MRSI Data

Authors: Anke Henning, Mahrshi Jani, Tianyu Wang, Andrew Wright, Xinyu Zhang

Affiliation: Advanced Imaging Research Center (AIRC), UT Southwestern Medical Center

Abstract Preview: Purpose: Proton MRSI offers critical metabolic insights into diseased brain processes but is prone to artifacts, and current post-processing methods are often insufficient, resulting in low-quality da...

Developing Patient-Specific Functional Atlases with Inverse Distance Weighting of MR Images

Authors: Chibawanye I. Ene, Sherise D. Ferguson, Ping Hou, Vinodh A. Kumar, Ho-Ling Anthony Liu, Kyle R. Noll, Sujit S. Prabhu, Jian Ming Teo, Max Wintermark

Affiliation: Department of Neuro-Oncology, The University of Texas MD Anderson Cancer Center, Department of Neuroradiology, The University of Texas MD Anderson Cancer Center, Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Department of Imaging Physics, The University of Texas MD Anderson Cancer Center

Abstract Preview: Purpose:
Functional brain atlases are used to guide clinical functional MRI (fMRI) analyses. Imprecise assertions may introduce the ecological fallacy as atlases are reflective of the constituent c...

Developing a Dataset for Investigations into the Impact of CT Acquisition and Reconstruction Conditions on Quantitative Imaging Using Paired Image Quality and Radiomics Phantom Data

Authors: Morgan A. Daly, David J. Goodenough, Andrew M. Hernandez, John M. Hoffman, Joshua Levy, Michael F. McNitt-Gray, Ali Uneri, Bino Varghese

Affiliation: University of California, George Washington University, David Geffen School of Medicine at UCLA, Johns Hopkins Univ, University of Southern California, The Phantom Laboratory

Abstract Preview: Purpose: Quantitative imaging is affected by CT acquisition and reconstruction conditions, limiting robustness in multi-site or -scanner studies. This work aimed to develop a dataset that will enable ...

Dosimetric Comparative Analysis of Modulated and Non Modulated Electron Bolus in Nasal Electron Therapy

Authors: Stephen D. Davis, Alonso N. Gutierrez, Noah S. Kalman, Michael Leyva, Alejandro Rene Llanes Lopez, William Romaguera, Ranjini P. Tolakanahalli, Deborah Wang

Affiliation: Miami Cancer Institute, Baptist Health South Florida, Miami Cancer Institute, Miami Cancer Institute, Baptist Health

Abstract Preview: Purpose: To evaluate whether a modulated electron bolus (MEB) technique improves both nominal and shifted dose distributions in nasal electron therapy as compared to a non‑modulated, uniform‑thickness...

Dosimetric Evaluation of Clinical Venezia Hybrid Applicator Plans Using a TG-186 Model-Based Dose Calculation Algorithm

Authors: Davide Brivio, Ivan M. Buzurovic, Thomas C. Harris, Desmond A. O'Farrell

Affiliation: Department of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Brigham and Women's Hospital, Harvard Medial School, Dana-Farber Cancer Institute, Department of Radiation Oncology

Abstract Preview: Purpose: Cervical cancer can be treated with a brachytherapy boost following external beam radiotherapy. One applicator option is the Advanced Gynecological Applicator "Venezia" (Elekta) hybrid, consi...

Dual-Domain Neural Network Cone-Beam CT Correction for Online Adaptive Proton Therapy

Authors: Daniel H. Bushe, Arthur Lalonde, Hoyeon Lee, Harald Paganetti, Brian Winey

Affiliation: Universite de Montreal, Massachusetts General Hospital, Massachusetts General Hospital and Harvard Medical School, University of Hong Kong

Abstract Preview: Purpose: Improving the precision and fidelity of daily volumetric imaging is essential for enabling adaptive proton therapy (APT). While cone-beam CT (CBCT) provides daily volumetric imaging, their ut...

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 Proton Treatment and Mitigating Radiation-Induced Lung Injury Using a Novel Cycle Diffusion Approach for Lung Ventilation Estimation

Authors: Yang Lei, Haibo Lin, Tian Liu, Charles B. Simone, Shouyi Wei, Ajay Zheng

Affiliation: Icahn School of Medicine at Mount Sinai, New York Proton Center

Abstract Preview: Purpose: Radiation-induced lung injury (RILI), encompassing pneumonitis and fibrosis, represents a critical dose-limiting factor in lung cancer radiation therapy. Variability in treatment outcomes is ...

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 ...

Evaluation of Hybrid Dynamic Conformal Arc Planning for SRS and SBRT Treatment

Authors: Pat Esposito, Ashley Klein, Carmine Verna, Ling Zhuang

Affiliation: Northwestern Medicine

Abstract Preview: Purpose: To evaluate dosimetric parameters and treatment delivery efficiency between volumetric modulated arc therapy (VMAT) and hybrid dynamic conformal arc (HDCA) on SRS and SBRT planning through st...

Evaluation of Treatment Planning Feasibility and Dosimetric Quality of the Reflexion™ X1 System for Complex Spinal Targets

Authors: Thomas I. Banks, Bin Cai, Andrew R. Godley, Yang Kyun Park, Hao Peng, Rameshwar Prasad, Chenyang Shen, Shunyu Yan, Haozhao Zhang

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

Abstract Preview: Purpose:
The RefleXion® X1 (RefleXion Medical, Inc., Hayward, CA) uniquely integrates KVCT and PET as on-board image guidance for radiotherapy. It has been installed and commissioned for clinical u...

Evaluation of the Dosimetric Characteristics of Multi-Layers of Brass Mesh Bolus for Electron Treatment

Authors: Yunzhi Ma, Ling Zhuang

Affiliation: Northwestern Medicine

Abstract Preview: Purpose: Multiple layers of brass mesh bolus (RPD, Inc., Albertville, MN) may be needed to provide better body conformity and sufficient dose build up on patient surface during electron treatment. Thi...

Eye-Tracking Analysis of Radiologist Preferences in PET Imaging: Comparing 5-Ring and 6-Ring Detector Configurations

Authors: Samuel L. Brady, Joseph G. Meier, Elanchezhian Somasundaram, Andrew T Trout

Affiliation: Cincinnati Children's Hospital Medical Ctr, Cincinnati Childrens Hospital Med Ctr

Abstract Preview: Purpose:
To analyze eye-tracker gaze data for insights into radiologists’ areas of focus in an observer study of whole-body PET images.
Methods:
For a comparative study of dose matched PET im...

Feasibility of Rapidarc Dynamic for Lattice Radiation Therapy of Bulky Liver Tumors

Authors: Christine V. Chung, Laurence Edward Court, Meena S. Khan, Ethan B. Ludmir, Rachael M. Martin Paulpeter, Saurabh Shashikumar Nair, Callistus M. Nguyen, Joshua S. Niedzielski, Luis Augusto Perles

Affiliation: MD Anderson Cancer Center, 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: Spatially Fractionated Radiation Therapy (SFRT) has re-emerged as an efficacious treatment approach for bulky solid tumors. RapidArc Dynamic (RAD) has unique beam delivery capabilities that m...

Feasibility of X-Ray Based Online Adaptive Dynamic Optimization with Integrated Knowledge-Based Planning for Head and Neck Cancer

Authors: Jacob S. Buatti, Mu-Han Lin, Dominic Moon, David D.M. Parsons, David Sher, Justin D. Visak, Hui Ju Wang

Affiliation: Department of Radiation Oncology, UT Southwestern Medical Center, Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, UT Southwestern Medical Center, Department of Radiation Oncology, UT Southwestern Medical Center, Dallas, TX

Abstract Preview: Purpose: Most current adaptive treatment planning systems (TPS) natively utilize static planning goals from the reference plan for online adaptive re-optimization. In complex head-and-neck cancer (HNC...

Foundation Model-Augmented Learning for Automatic Delineation in Precision Radiotherapy

Authors: Xianjin Dai, PhD, Michael Gensheimer, Praveenbalaji Rajendran, Lei Xing, Yong Yang

Affiliation: Department of Radiation Oncology, Stanford University, Massachusetts General Hospital, Harvard Medical School

Abstract Preview: Purpose: Recent advances in the automatic delineation of radiotherapy treatment targets, which incorporate linguistic clinical data extracted by large language models (LLMs) into traditional visual-on...

Generating Brain Pseudo-CT from PET-Only Images Using Deep Learning Method

Authors: Pouya Azarbar, Nima Kasraie, Mahsa Shahrbabki Mofrad, Peyman Sheikhzadeh

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

Abstract Preview: Purpose: PET imaging become crucial in diagnosing and managing various diseases, but its key limitation is the lack of detailed anatomical information. Integrating CT-scans with PET images enhances cl...

High-Fidelity Treatment Optimization for Online Adaptive Stereotactic Partial Breast Irradiation: Integrating Dose and Treatment Time Considerations

Authors: Drexell Hunter Boggs, Carlos E. Cardenas, Jingwei Duan, Joseph Harms, Joel A. Pogue, Richard A. Popple, Courtney Bosse Stanley, Dennis N. Stanley, Sean Xavier Sullivan, Natalie N. Viscariello

Affiliation: Washington University in St. Louis, The University of Alabama at Birmingham, University of Alabama at Birmingham

Abstract Preview: Purpose: CBCT-guided online adaptive radiation therapy (OART) with Ethos for stereotactic accelerated partial breast irradiation (APBI) can mitigate inter-fraction variation, leading to dosimetric adv...

Knowledge-Based Planning for Chest Wall with Lymph Nodes Irradiation VMAT

Authors: Nesrin Dogan, Panagiota Galanakou, Robert Kaderka

Affiliation: University of Miami, Sylvester Comprehensive Cancer Center, University of Miami Sylvester Comprehensive Cancer Center

Abstract Preview: Purpose:
To develop knowledge-based treatment planning (KBP) for volumetric modulated arc therapy (VMAT) in chest wall treatments with regional nodal involvement. Given the challenges posed due to ...

Knowledge-Based Planning in Proton Therapy: Validation and Model Size Considerations with Limited Data

Authors: Gregory A Azzam, Michael Butkus, Nesrin Dogan, Robert Kaderka, Nhan Vu, Yihang Xu

Affiliation: University of Miami, Department of Radiation Oncology, University of Miami, University of Miami Sylvester Comprehensive Cancer Center, University of Miami, Sylvester Comprehensive Cancer Center

Abstract Preview: Purpose: Knowledge-based planning (KBP) has demonstrated potential for improving planning quality and efficiency. Adoption of KBP in particle therapy has been slow due to limited number of plans to tr...

Latent Diffusion for 3D CT Reconstruction from Biplanar X-Rays

Authors: Guha Balakrishnan, Osama R. Mawlawi, Yiran Sun, Ashok Veeraraghavan

Affiliation: RICE University, UT MD Anderson Cancer Center

Abstract Preview: Purpose:
Previous deep learning (DL) techniques such as X2CT-GAN [1] has shown great promise in reconstructing realistic CT volume from biplanar X-rays, however they introduce numerous artifacts in...

Log File-Based Patient-Specific QA As a Viable Alternative to Measurement-Based QA in IMPT

Authors: Sina Mossahebi, Pouya Sabouri, Kayla Schneider, James W Snider

Affiliation: University of Maryland School of Medicine, Proton International, Department of Radiation Oncology, University of Arkansas for Medical Sciences (UAMS), Department of Radiation Oncology, University of Arkansas for Medical Sciences

Abstract Preview: Purpose:
Conventional patient-specific QA (PSQA) for intensity-modulated proton therapy (IMPT) requires extensive measurements, straining resources in single-room proton centers. This study evaluat...

Modality-Agnostic Image Cascade (MAGIC) for Multi-Modality Cardiac Substructure Segmentation

Authors: Ming Dong, Carri K. Glide-Hurst, Qisheng He, Anudeep Kumar, Alex Singleton Kuo, Joshua Pan, Chase Ruff, Nicholas R. Summerfield

Affiliation: Department of Computer Science, Wayne State University, Departments of Human Oncology and Medical Physics, University of Wisconsin-Madison, Department of Human Oncology, University of Wisconsin-Madison

Abstract Preview: Purpose: Recent evidence highlights the importance of incorporating cardiac substructures (CS) into treatment planning for thoracic cancers, however current segmentation methods are limited to a singl...

Multi-Region Multiomic Features Improve Random Forest Toxicity Modeling of Radiation Pneumonitis

Authors: Laurence Edward Court, Alexandra Olivia Leone, Zhongxing Liao, Saurabh Shashikumar Nair, Joshua S. Niedzielski, Ramon Maurilio Salazar, Ting Xu

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

Abstract Preview: Purpose: Radiation Pneumonitis (RP) predictive models often rely on clinical and DVH parameters, but multiomic features from CT imaging and 3D dose distributions from various regions could provide add...

Optimization-Based Image Reconstruction Regularized with Inter-Spectral Structural Similarity for Limited-Angle Dual-Energy Cone-Beam CT

Authors: Chih-Wei Chang, Junbo Peng, Richard L.J. Qiu, Justin Roper, Xiangyang Tang, Tonghe Wang, Huiqiao Xie, Xiaofeng Yang, David Yu

Affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Emory Univ, Emory University, Memorial Sloan Kettering Cancer Center, Department of Radiation Oncology and Winship Cancer Institute, Emory University

Abstract Preview: Purpose: Limited-angle dual-energy (DE) cone-beam CT (CBCT) is considered a promising solution to achieve fast and low-dose DE imaging on current CBCT scanners without hardware modification. However, ...

Posterior-Mean Diffusion Model for Realistic PET Image Reconstruction

Authors: Osama R. Mawlawi, Yiran Sun

Affiliation: RICE University, UT MD Anderson Cancer Center

Abstract Preview: Purpose: Conventional PET reconstruction methods often produce noisy images with artifacts due to data/model mismatches and inconsistencies. Recently, deep learning-based conditional denoising diffusi...

Predicting and Monitoring Response to Head and Neck Cancer Radiotherapy Using Multi-Modality Imaging and Radiobiological Digital Twin Simulations

Authors: Eric Aliotta, Michalis Aristophanous, Joseph O. Deasy, Bill Diplas, Milan Grkovski, James Han, Vaios Hatzoglou, Jeho Jeong, Nancy Y Lee, Ramesh Paudyal, Nadeem Riaz, Heiko Schoder, Amita Shukla-Dave

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

Abstract Preview: Purpose: To forecast radiotherapy treatment response for head and neck cancer (HNC) using multimodality imaging and personalized radiobiological modeling.
Methods: Multi-modality imaging data from ...

Quantifying the Impact of Tissue Inhomogeneities on Calculated Dosimetry within LDR Brachytherapy

Authors: Fatemeh Akbari, Deidre Batchelar, Luc Beaulieu, Nathan E. Becker, Juanita Crook, Dakota Mckeown, Matthew Jonathan Muscat, Rowan M. Thomson

Affiliation: Département de physique, de génie physique et d'optique, Université Laval, BC Cancer Agency, UBC, Carleton University, BC Cancer - Kelowna, BC Cancer

Abstract Preview: Purpose:
To study the effects of inter-seed attenuation and tissue inhomogeneities on dose-volume metrics of critical structures in prostate low-dose-rate (LDR) permanent seed implant brachytherapy...

Streamlining Orthovoltage QA: Feasibility of IC Profiler Dosimetry and Workflow Optimization

Authors: Huixiao Chen, Zhe (Jay) Chen, MinYoung Lee, Sameer Taneja

Affiliation: Yale School of Medicine, Department of Therapeutic Radiology, Yale University School of Medicine

Abstract Preview: Purpose: Superficial radiation therapy uses low-energy x-rays to treat various types of cancers, including non-melanoma skin cancers, and dermatological conditions such as keloid scars, mycosis fungoi...

Streamlining Quality Control for Radiographic and Fluoroscopic Systems

Authors: Caroline Cheney, Patricia G Collins, Allen R. Goode, Preston Le, Andrew M. Polemi, Angela Snyder

Affiliation: UVA Health, Atirix Medical Systems

Abstract Preview: Purpose: Optimize ongoing quality control (QC) for radiographic (DR) and fluoroscopic (FL) systems by identifying metrics most sensitive to hardware disruptions among regional noise, pooled noise, sig...

Ultra-Sparse-View Cone-Beam CT Reconstruction Based Strictly-Structure-Preserved Deep Neural Network in Image-Guided Radiation Therapy

Authors: Guangjun Li, Ying Song, Huanan Tang, Tianxiong Wu, Qiuyi Ye, Wei Zhang

Affiliation: West China Second Hospital of Sichuan University, United Imaging Healthcare, West China Hospital of Sichuan University

Abstract Preview: Purpose:
To propose a general low-dose reconstruction model for ultra-sparse-view cone-beam CT (CBCT) and evaluate its clinical application in improving image quality and reducing radiation dose fo...

Universal MR-to-Synthetic CT: A Streamlined Framework for MR-Only Radiotherapy 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:
Converting MR images to synthetic CT (MR2sCT) is highly desirable as it streamlines the radiotherapy treatment planning workflow. This approach leverages the superior soft tissue visibilit...