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Results for "loss function": 62 found

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 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 Novel Feature Selection Method for Survival Prediction of Head-and-Neck Following Radiation Therapy

Authors: Xiaoying Pan, X. Sharon Qi

Affiliation: Department of Radiation Oncology, University of California, Los Angeles, School of Computer Science and technology,Xi'an University of Posts and Telecommunications

Abstract Preview: Purpose:
Survival prediction for cancer presents a substantial hurdle in personalized oncology, due to intricate, high-dimensional medical data. Our study introduces an innovative feature selection...

A Novel Semi-Analytic Approach for Dose Calculation in Proton Minibeam Radiotherapy

Authors: Hao Gao, Wangyao Li, Yuting Lin, Chao Wang, Wei Wu

Affiliation: Institute of Modern Physics, Chinese Academy of Sciences, Department of Radiation Oncology, University of Kansas Medical Center

Abstract Preview: Purpose: Proton minibeam radiation therapy (pMBRT) delivers a unique peak-and-valley dose pattern using collimators with narrow slits, offering improved normal tissue sparing compared to conventional ...

A Retrospective Analysis of Automatic Exposure Control (AEC) Tracking Failure Rates in Radiographic Systems

Authors: Benjamin W. Maloney, Ashley E. Rubinstein, Colin Schaeffer, Justin Yu

Affiliation: Henry Ford Health

Abstract Preview: Purpose: Radiography AEC systems ensure correctly exposed images for varied kVp and patient thicknesses. The specific kVp and PMMA thicknesses selected for testing AEC tracking may affect passing rate...

A Simple and Reliable Method to Determine Patients Eligible for Treatment on the Novel Biological Guided Radiotherapy (BgRT) System Based on FDG Uptake in Nearby Non-Treatment Regions.

Authors: Brett Lewis, Roland Teboh

Affiliation: HUMC, Hackensack University Medical Center

Abstract Preview: Purpose: The novel RefleXion SCINTIX BgRT system relies on the FDG uptake distribution from a PET study to plan and deliver dose. One of the patient eligibility criteria is that any uptake outside the...

Accuracy Analysis of "Sphere-Mask" Optical Positioning System in Radiotherapy of Breast Cancer

Authors: Xiu tong Lin, Tao Sun

Affiliation: Department of Radiation physics and technology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Department of Radiation physics and technology, Shandong Second Provincial General Hospital

Abstract Preview: Purpose: To compare the positioning accuracy and time efficiency of "Sphere-Mask" Optical Positioning System (OPS) and traditional laser light positioning method in breast cancer radiotherapy, and to ...

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...

Analytical Approach to Calculate Normal Tissue Complication Probability and Tumor Control Probability for Ultra-High Dose Rate Radiation (FLASH) Based on Linear-Quadratic Model

Authors: Santosh K. Agarwalla, Nrusingh C. Biswal, Shree C, Harikrishnan Suresh Kumar, Jajati K. Nayak, Prema P., Sarath K S, Tamil Selvan S, Hem D. Shukla

Affiliation: Variable Energy Cyclotron Centre, Department of Physics, Fakir Mohan University, Department of Radiation Oncology, University of Maryland School of Medicine, Department of Sciences, Amrita Vishwa Vidyapeetham

Abstract Preview: Purpose: The rapid oxygen depletion in tissues during irradiation is the most accepted mechanism of the FLASH effect. However, the Normal Tissue Complication Probability (NTCP) and Tumor Control Proba...

Analyzer-Less X-Ray Interferometry with Super-Resolution Methods

Authors: Joyoni Dey, Hunter Cole Meyer, Murtuza Taqi

Affiliation: Louisiana State University

Abstract Preview: Purpose: We propose using super-resolution methods for X-ray grating interferometry without an analyzer with detectors that fail to meet the Nyquist sampling rate needed for traditional image recovery...

BEST IN PHYSICS IMAGING: Volumetric Sampling Properties of Longitudinal Multiple X-Ray-Source Array Computed Tomography (MXA-CT)

Authors: Craig K Abbey, John M. Boone, Richard E. Colbeth, Andrew M. Hernandez, Vance Robinson, Paul Schwoebel, Jeffrey H. Siewerdsen, Alejandro Sisniega, Wojciech B. Zbijewski, Huanyi Zhou

Affiliation: UC Santa Barbara, University of California, UT MD Anderson Cancer Center, Johns Hopkins University, University of New Mexico Albuquerque, UC Davis Health, Varex Imaging Corporation

Abstract Preview: Purpose: A new CT configuration utilizing a multiple X-ray-source array (MXA) is under development to mitigate cone-beam (CB) artifacts in single-rotation wide coverage imaging. We investigate the sam...

Biomechanically Informed Diagnostic-to-Synthetic CT Transformation for Expedited Radiation Therapy Planning

Authors: Liyuan Chen, Steve Jiang, Chenyang Shen

Affiliation: Department of Radiation Oncology, UT Southwestern Medical Center, UT Southwestern Medical Center

Abstract Preview: Purpose: Delays in radiation therapy (RT) initiation caused by conventional CT simulation processes can hinder timely treatment delivery and patient outcomes. This study proposes a Virtual Treatment S...

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...

Characterisation of Breathing Volumes and Surface Motion for Upright and Supine Treatment Positions

Authors: Sophie Boisbouvier, David Cobben, Anthony L Criscuolo, Michael W. Kissick, Mark Ramtohul, Gordon Sands, Tracy Underwood

Affiliation: University of Surrey, Department of Medical Physics, Queen Elizabeth Hospital, Lung Cancer and Sarcoma Radiotherapy, The Clatterbridge Cancer Centre, Leo Cancer Care, Radiotherapy department, Centre Léon Bérard

Abstract Preview: Purpose:
Pulmonary function tests (PFTs) help assess treatment options for lung cancer patients. Conventionally, these are undertaken upright, whereas radiotherapy is administered supine. This stud...

Characterization, Commissioning, and Clinical Evaluation of a Commercial Beo Optically Stimulated Luminescence (OSL) System

Authors: Brett G Erickson, Joseph P. Kowalski, Xinyi Li, Qiuwen Wu, Sua Yoo

Affiliation: Duke University, Mayo Clinic - Department of Radiation Oncology, Duke University Medical Center

Abstract Preview: Purpose: Characterization and commissioning of the BeO-based myOSLchip system was performed (per TG191) to assess its feasibility as a full replacement for the recalled Landauer aluminum oxide OSL in ...

Comparative Evaluation of Nn-Unet Models for Radiotherapy Dose Prediction Using the Head and Neck Cancer Patients

Authors: Theodore Higgins Arsenault, Beatriz Guevara, Rojano Kashani, Raymond F. Muzic, Gisele Castro Pereira, Alex T. Price

Affiliation: University Hospitals Seidman Cancer Center, Case Western Reserve University Department of Biomedical Engineering

Abstract Preview: Purpose: Accurate dose prediction in radiotherapy is essential for treatment planning. This study evaluates four nnUnet-based models using the OpenKBP head and neck dataset: a baseline model (Model 1)...

Contrast-Dependent Loss of Edge Sharpness in Low-Contrast Targets with Increasing Iterative Reconstruction Strength

Authors: Emi Ai Eastman, Christina Lee, Xinhua Li, Alexander W. Scott, Yifang (Jimmy) Zhou

Affiliation: Cedars-Sinai Medical Center

Abstract Preview: Purpose: Iterative reconstruction (IR) methods are valuable for reducing dose in modern CT; however, IR methods have the effect of reducing spatial resolution and hence the lesion edge sharpness. Furt...

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 Autoencoder for Ring Artifact Denoising in Photon-Counting CT

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...

Deep Learning-Based Auto-Segmentation in Cervical High-Dose-Rate Brachytherapy with Clinical Considerations

Authors: Benjamin Haibe-Kains, Ruiyan Ni, Alexandra Rink

Affiliation: Department of Medical Biophysics, University of Toronto, University Health Network

Abstract Preview: Purpose: Accurate auto-segmentation for targets and organs-at-risk (OARs) using deep learning reduces the delineating time in radiotherapy. In high-dose-rate brachytherapy, specific clinical criteria ...

Deep Learning-Based Plan Quality Prediction for Gamma Knife Radiosurgery of Brain Metastases

Authors: Chih-Wei Chang, Runyu Jiang, Mark Korpics, Yuan Shao, Aranee Sivananthan, Zhen Tian, Ralph Weichselbaum, Xiaofeng Yang, Aubrey Zhang, Xiaoman Zhang

Affiliation: Department of Radiation & Cellular Oncology, University of Chicago, University of Chicago, Department of Physics, University of Chicago, Emory University, Department of Radiation Oncology and Winship Cancer Institute, Emory University, School of Public Health, University of Illinois Chicago

Abstract Preview: Purpose: Gamma Knife (GK) plan quality can vary significantly among planners, even for cases handled by the same planner. Although plan quality metrics such as coverage, selectivity, and gradient inde...

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...

Deep-Learning Convolutional Neural Network-Based Breast Cancer Localization for Mammographic Images: A Study on Simulated and Clinical Images

Authors: Xiaoyu Duan, Xiang Li, Wenbo Wan, Lei Zhang, Yiwen Zhang

Affiliation: Duke University, Medical Physics Graduate Program, Duke Kunshan University

Abstract Preview: Purpose: Breast screening has been proved to reduce breast cancer mortality by early detection and treatment for patients. Mammography is the most common and widely used technique for breast cancer sc...

Development of a Deep Learning Model for Accurate Brain Dose Prediction in Multi-Target Stereotactic Radiosurgery Plan Evaluation

Authors: Wenchao Cao, Yingxuan Chen, Haisong Liu, Wenyin Shi, Wentao Wang, Lydia J. Wilson, Zhenghao Xiao

Affiliation: Thomas Jefferson University

Abstract Preview: Purpose: Multi-target stereotactic radiosurgery (SRS) planning poses challenges due to complex geometries, small target volumes, and steep dose gradients. Achieving a balance between target coverage a...

Development of an Inverse Treatment Planning System for Precision Small Animal Radiotherapy

Authors: Zihao Liu, Qiwei Wu, Yanfei Xiong, Yidong Yang, Ning Zhao

Affiliation: Department of Engineering and Applied Physics, School of Physical Sciences, University of Science and Technology of China, Department of Engineering and Applied Physics, University of Science and Technology of China, University of Science and Technology of China

Abstract Preview: Purpose: To develop an inverse planning framework that optimizes beam angles and intensities for small animal radiotherapy and to validate its accuracy and effectiveness.
Methods: The inverse plann...

Does the Method Matter? How in Hominum, In Vivo, in silico, and in Phantasma Measures Compare and Contrast Is Assessing the Utility of Photon Counting CT?

Authors: Ehsan Abadi, Njood Alsaihati, Steven T. Bache, Mridul Bhattarai, Cindy Marie McCabe, Francesco Ria, Ehsan Samei

Affiliation: Duke University, Center for Virtual Imaging Trials, Duke University, Duke University Health System, Clinical Imaging Physics Group, Department of Radiology, Duke University Health System

Abstract Preview: Purpose: To compare and contrast alternative methods including reader (in hominum), phantom (in phantasma), in vivo, and in silico methods deployed to assess the performance of photon counting (PCCT) ...

Dosimetric Evaluation of the Aldo Function for Multiple Brain Metastases in Automated Stereotactic Radiosurgery Treatment Planning

Authors: Hsiao-Mei Fu, Shih-Ming Hsu, Chia-Ting Lee, Shih-Hua Liu, Tsung-Yu Yen

Affiliation: National Yang Ming Chiao Tung University, Mackay Memorial Hospital

Abstract Preview: Purpose: The Automatic Lower Dose Objective (ALDO) is a unique function designed to achieve 98% relative coverage across all targets in automated SRS treatment planning (HyperArc planning). This study...

Dual-Energy CT Derived Perfusion Blood Volume and 4D-CT Derived Ventilation Changes in Lung Cancer Patients 6-Months Post Radiation Therapy

Authors: Daniel A. Alexander, Jeffrey D. Bradley, Steven J. Feigenberg, Cole Friedes, Casey Hollawell, William Levin, Maksym Sharma, Boon-Keng Kevin Teo, Ying Xiao, Nikhil Yegya-Raman, Jennifer Wei Zou

Affiliation: Department of Radiation Oncology and Applied Sciences, Department of Radiation Oncology, University of Pennsylvania, University of Pennsylvania

Abstract Preview: Purpose: To investigate lung function changes following definitive chemoradiation dose using CT-derived measurements in patients with locally advanced NSCLC at 6-months post-treatment compared to pre-...

Efficient Robustness Optimization in Intensity Modulated Proton Therapy for Head and Neck Cancer Via Visual State Space Attention Generative Adversarial Networks (VSSA-GAN)

Authors: Nan Li, Yaoying Liu, Shouping Xu, Gaolong Zhang

Affiliation: Department of Radiation Oncology, School of Physics, Beihang University, School of physics, Beihang University, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College

Abstract Preview: Purpose: In intensity-modulated proton therapy (IMPT) for head and neck cancer, CBCT registration ensures accurate setup, minimizing dose errors. Unlike IMRT, IMPT plans directly define tumor volumes ...

Evaluation of Color Display Performance of Pathology Relevant Colors Using the Macbeth Colorchecker

Authors: Diana Cardona, Casey C. Heirman, William Jeck, Kyle J. Lafata, 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: Display image accuracy is critical for digital diagnostic fields, such as radiology and digital pathology. While the AAPM TG-18 test patterns are established for grayscale radiology monitor Q...

Evaluation of Deformable Image Registration Accuracy Used in MR-Only Ventilation Mapping

Authors: Fei Han, James M. Lamb, Michael Vincent Lauria, Daniel A. Low, Tessa Elizabeth Maurer, Danilo Maziero, Claudia R. Miller, Drew Moghanaki, Louise Naumann, Nicolas Viot

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

Abstract Preview: Purpose: Patients with lung disease outside radiotherapy are barred from high dose protocols used for motion modeling, but MRI could offer no-dose alternatives. Image-based ventilation is a promising ...

Generating 3D Brain in Volume (BRAVO) Images Using Attention-Gated Conditional Gan (AGC-GAN)

Authors: Nan Li, Shouping Xu, Gaolong Zhang, Xuerong Zhang

Affiliation: Department of Radiation Oncology, HeBei YiZhou proton center, School of Physics, Beihang University, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College

Abstract Preview: Purpose:
The 3D BRAVO sequence is an advanced magnetic resonance (MR) technique that allows for image reconstruction at any angle. It offers 1 mm gapless scanning and has a high signal-to-noise rat...

Graph Neural Network with Long Short-Term Memory for CT-Based Macrotrabecular-Massive Hepatocellular Carcinoma Diagnosis

Authors: Enhui Chang, Yunfei Dong, Yifei Hao, Chengliang Jin, Shengsheng Lai, Yi Long, Mengni Wu, Yulu Wu, Ruimeng Yang, Zhenyu Yang, Yue Yuan, Lei Zhang, Wanli Zhang, Yaogong Zhang

Affiliation: Duke Kunshan University, Department of Radiology, The Second Affiliated Hospital, School of Medicine, South China University of Technology, Medical Physics Graduate Program, Duke Kunshan University

Abstract Preview: Purpose: Macrotrabecular-Massive Hepatocellular Carcinoma (MTM-HCC) is one type of liver cancer showed minimum image signature for accurate non-invasive diagnosis. This study aims to develop and evalu...

Impact of Six Degrees of Freedom Intrafraction Motion on Target Coverage for Single-Isocenter Multi-Target Stereotactic Radiosurgery

Authors: Anupama Chundury, Hyejoo Kang, John C. Roeske, Iris A. Rusu

Affiliation: Loyola University Medical Center, Department of Radiation Oncology, Stritch School of Medicine, Loyola University Chicago, Stritch School of Medicine Loyola University Chicago, Cardinal Bernardin Cancer Center, Loyola University Chicago

Abstract Preview: Purpose: To quantify the dosimetric impact of six degrees of freedom (6DoF) intrafractional errors on gross tumor volume (GTV) and planning target volumes (PTV) for single-isocenter multi-target stere...

Impact of Transfer Learning on Estimation of Intravoxel Incoherent Motion Parameters in the Liver

Authors: Marissa Brown, Geoffrey D. Clarke, Luke Norton

Affiliation: University of Texas Health Science Center at San Antonio

Abstract Preview: Purpose: To evaluate how different learning strategies affect convolutional neural network (CNN) estimates of the liver's intravoxel incoherent motion (IVIM) parameters.
Methods: A 3-stage U-Net wa...

Improving the Robustness of AI-Based Detection and Segmentation for Brain Metastasis By Optimizing Loss Function and Multi-Dataset Training

Authors: Omar Awad, Alfredo Enrique Echeverria, Issam M. El Naqa, Daniel Allan Hamstra, Yiding Han, Ryan Lafratta, Abdallah Sherif Radwan Mohamed, Piyush Pathak, Zaid Ali Siddiqui, Baozhou Sun, Vincent Ugarte

Affiliation: H. Lee Moffitt Cancer Center, Harris Health, Baylor College of Medicine

Abstract Preview: Purpose:
Accurate detection and segmentation of brain metastases are critical for diagnosis, treatment planning, and follow-up imaging but are challenging due to labor-intensive manual assessments ...

Investigate Deep-Learned MRI Reconstruction with Data Consistency Mechanism and Task-Informed Loss

Authors: Mark Anastasio, Hua Li, Zhuchen Shao

Affiliation: Washington University School of Medicine, University of Illinois Urbana-Champaign

Abstract Preview: Purpose: Ill-conditioned reconstruction problems in medical imaging, such as those arising from undersampled k-space data in MRI, can result in degraded image quality and clinical task-orientated perf...

Investigating X-Ray Flash Effect on Plasmid DNA with Combined Microscopic Monte Carlo and Analytical Simulations

Authors: Xun Jia, Youfang Lai

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

Abstract Preview: Purpose: Ultrahigh dose rate FLASH (>40 Gy/s) radiotherapy (RT) has attracted significant attention. The mechanism remains unclear, hindering clinical translation. This study investigated the behavior...

Knowledge-Informed Deep Learning for Accurate and Interpretable Extracapsular Extension Detection in Head and Neck Squamous Cell Carcinoma

Authors: William N. Duggar, Amirhossein Eskorouchi, Haifeng Wang

Affiliation: Mississippi State University, University of Mississippi Medical Center

Abstract Preview: Purpose:
Extracapsular extension (ECE) in lymph nodes represents a critical prognostic factor in head and neck squamous cell carcinoma (HNSCC), bearing important implications for staging, treatment...

Large Language Model-Driven Agentic System for Collaborative Decision-Making in Radiotherapy Treatment Planning

Authors: Yang Sheng, Qingrong Jackie Wu, Qiuwen Wu, Xin Wu, Dongrong Yang

Affiliation: Duke University Medical Center

Abstract Preview: Purpose:
This study aims to leverage large language model (LLMs) to develop a human-in-the-loop agentic framework, enhancing the efficiency of treatment planning in radiotherapy.
Methods:
A L...

Log-Based Predictive Modeling of the Dynamic Collimation System (DCS) Trimmer Dynamics for Efficient Proton Pbs Delivery

Authors: Wesley S. Culberson, Albert Du, Ryan T. Flynn, Ryan Gardner, Alonso N. Gutierrez, Patrick M Hill, Daniel E. Hyer, Eric Jensen, Kaustubh A. Patwardhan, Blake R. Smith, Nhan Vu, Karsten K. Wake

Affiliation: University of Wisconsin, Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin - Madison, Miami Cancer Institute, Baptist Health South Florida, Department of Human Oncology, University of Wisconsin School of Medicine and Public Health, Ion Beam Applications (IBA), University of Iowa, Iowa Health Care

Abstract Preview: Purpose: To develop an accurate predictive temporal model for the movement of Dynamic Collimation System (DCS) trimmers during collimated proton pencil beam scanning (PBS) deliveries using log data. T...

MR-Based Functional Liver Imaging and Dosimetry to Predict Albi Change Post-SBRT

Authors: Madhava Aryal, James M. Balter, Yue Cao, Daniel T Chang, Kyle Cuneo, Joseph R. Evans, Theodore Lawrence, John Rice, Randall K. Ten Haken, Lise Wei

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

Abstract Preview: Purpose: This study aims to identify predictors of global liver function change measured by albumin-bilirubin (ALBI) score following stereotactic body radiation therapy (SBRT) in hepatocellular carcin...

Minimizing Abscopal Effects in Normal Tissues with Flash-RT: Mechanisms of Action and Potential Clinical Applications

Authors: Liang Cui, Xingyu Lu, Hang Shang, LingHong Zhou

Affiliation: Southern Medical University

Abstract Preview: Purpose: This study examines how varying dose rates of radiotherapy impact normal tissues outside the target area and analyzes the protective effects and regulatory mechanisms of ultra-high dose rate ...

Multi-Path Deep Learning Model for Predicting Post-Radiotherapy Functional Liver Imaging in Patients with Hepatocellular Carcinoma

Authors: Smith Apisarnthanarax, Stephen R. Bowen, Sunan Cui, Jie Fu, Clemens Grassberger, Yulun He, Yejin Kim, Matthew J. Nyflot, Sharon Pai

Affiliation: Department of Radiation Oncology, University of Washington and Fred Hutchinson Cancer Center, Department of Radiation Oncology, University of Washington, University of Washington, Department of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, Department of Physics, University of Washington, University of Washington and Fred Hutchinson Cancer Center

Abstract Preview: Purpose: 99mTc-sulfur colloid SPECT imaging enables quantitative assessment of voxel-wise liver function in patients with hepatocellular carcinoma (HCC). Accurately predicting post-radiotherapy (RT) l...

Neural Network Based Differentiable Optimization for Volumetric Modulated Arc Therapy (VMAT)

Authors: Peng Dong, Lei Xing

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

Abstract Preview: Purpose: Volumetric Modulated Arc Therapy (VMAT) optimization is a complex, non-convex problem with numerous variables and intricate constraints. Traditional optimization methods often lack efficiency...

Optimization of the U-Net Model for the Radiation Dose Prediction in Lung Cancer RT Plans and Its Uncertainty Quantification

Authors: Ibtisam Almajnooni, Victor Cobilean, Milos Manic, Harindra Sandun Mavikumbure, Elisabeth Weiss, Lulin Yuan

Affiliation: Virginia Commonwealth University

Abstract Preview: Purpose: This study aims to optimize the 3D U-Net architecture for dose prediction in lung cancer radiation therapy (RT) plans, particularly in scenarios with limited clinical data, as well as to quan...

Performance Evaluation of an Upright, Short-Scan, Cone-Beam, Dedicated Breast CT System.

Authors: Stephen Araujo, Jing-Tzyh Alan Chiang, Cynthia E. Davis, Eri Haneda, Andrew Karellas, Thomas C Larsen, William Ross, Hsin Wu Tseng, Srinivasan Vedantham, Pengwei Wu

Affiliation: Department of Biomedical Engineering, The University of Arizona, GE Aerospace Research, Department of Medical Imaging, The University of Arizona, GE HealthCare Technology & Innovation Center

Abstract Preview: Purpose: The purpose of this work is to describe the design and development of a newly developed upright-geometry dedicated breast CT system and to quantitatively and qualitatively evaluate its imagin...

Personalized Radiotherapy: A Novel Approach to Multi-Criteria Optimization with Patient-Specific Risk Integration

Authors: Ali Ajdari, Thomas R. Bortfeld, Zhongxing Liao, Mara Schubert, Katrin Teichert

Affiliation: The University of Texas MD Anderson Cancer Center, Department Of Radiation Oncology, Massachusetts General Hospital (MGH), Massachusetts General Hospital & Harvard Medical School, Fraunhofer ITWM

Abstract Preview: Purpose: Radiotherapy (RT) treatment planning often involves solving a multi-criteria optimization (MCO) problem. Conventionally, MCO considers a set of generic (population-wide) dosimetric criteria, ...

Prior-Model-Free Dynamic CBCT Reconstruction Via Combined Optical Surface and X-Ray Imaging

Authors: Hua-Chieh Shao, Guoping Xu, You Zhang, Tingliang Zhuang

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

Abstract Preview: Purpose:
Advancements in onboard X-ray hardware allow high-quality CBCT imaging with a short scan time (~6s for Varian HyperSight), enabling CBCT-based dose calculation and treatment planning. Howe...

Quality and Performance Advantages of a Machine Learning-Assisted Framework for IMRT Fluence Map Optimization

Authors: Yang Sheng, Qingrong Jackie Wu, Qiuwen Wu, Xin Wu, Dongrong Yang

Affiliation: Duke University Medical Center

Abstract Preview: Purpose: Gradient-based optimization is the standard approach for IMRT fluence map optimization (FMO). Recently, a machine learning (ML)-assisted framework using a one-layer neural network was propose...

Recovery Factor Comparisons for Reirradiation Overlapping the Spinal Cord

Authors: Xinxin Deng, Issam M. El Naqa, Jimm Grimm, Lijun Ma, Vitali Moiseenko, Timothy E. Schultheiss, Gopal Subedi, Wolfgang A. Tomé, Ellen D. Yorke, Albert van der Kogel

Affiliation: Montefiore Medical Center, Wellstar Kennestone Hospital Cancer Center, H. Lee Moffitt Cancer Center, Department of Human Oncology, University of Wisconsin–Madison, Department of Radiation Oncology, Wellstar Health System, Radiation Oncology, Keck School of Medicine of USC, Georgia Institute of Technology, University of California San Diego, City Of Hope National Medical Centre, Memorial Sloan Kettering Cancer Center

Abstract Preview: Purpose: Reirradiation is increasingly utilized in clinical practice but dose-time recovery factors for human subjects remain uncertain. We constructed a reirradiation recovery model for spinal cord e...

Reduction of the Charge Build-up Effect on the Beam Current Transformers for Real-Time Monitoring of Ultra-High Dose per-Pulse Electron Beams

Authors: Wesley S. Culberson, Miguel Angel Flores Mancera, Jeff Radtke

Affiliation: Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin - Madison

Abstract Preview: Purpose: Beam current transformers (BCTs) are a promising alternative to ion chambers for real-time monitoring of ultra-high dose per-pulse (UHDPP) beams. The signal of the BCT is insensitive to ion r...

Serial PET-CT Activity Concentration during Small Target Lung Tumor SBRT

Authors: Joseph Barbiere, Joseph Hanley, Brett Lewis, Jay Mistry, Alois M. Ndlovu, Roland Teboh

Affiliation: Hackensack University Medical Center, HUMC, Jersey Shore University Medical Center

Abstract Preview: Purpose:
Quantitative PET-CT can evaluate clinical response to radiotherapy. For tumors less than approximately 3cm partial volume effects due to the poor PET resolution makes accurate measurement ...

Spatial Resolution Degradation in Weekly Computed Tomography Quality Control and Implications for X-Ray Tube Replacement

Authors: Hadley Anna DeBrosse, Kevin J. Little

Affiliation: The Ohio State University

Abstract Preview: Purpose: This work examines the consistency and pattern of spatial resolution degradation in weekly quality control (QC) testing prior to CT tube failure and replacement and investigates potential cor...

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...

Towards Penile Small Vessel Imaging with Ferumoxytol-Enhanced MRI

Authors: Darren Fang, Amar Kishan, Justin McWilliams, Dan Ruan, Xiaodong Zhong

Affiliation: Department of Radiation Oncology, University of California, Los Angeles, Department of Radiology, University of California, Los Angeles, Department of Radiological Sciences, University of California, Los Angeles

Abstract Preview: Purpose: Prostate radiotherapy can malform penile vasculature, contributing to erectile dysfunction and compromising quality of life. To detect, quantify, and preferably avoid such occurrences, this p...

Unidose: A Universal Framework for IMRT Dose Prediction

Authors: Mingli Chen, Xuejun Gu, Hao Jiang, Mahdieh Kazemimoghadam, Weiguo Lu, Qingying Wang, Zi Yang, Kangning Zhang

Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, UT Southwestern Medical Center, Department of Radiation Oncology, Stanford University School of Medicine

Abstract Preview: Purpose: Dose prediction (DP) is essential in guiding radiotherapy planning. However, current DP models for intensity-modulated radiation therapy (IMRT) primarily rely on fixed-beam orientations and a...

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...

Uprightvision: A Deep-Learning Toolkit for Transforming Supine Anatomy to Upright

Authors: Ming Dong, Carri K. Glide-Hurst, Behzad Hejrati, Joshua Pan, Yuhao Yan

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: Upright patient positioners and vertical CT reduce tumor motion and stabilize internal anatomy during treatment delivery. Yet, to fully exploit the advantages of upright, translation of stand...

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...

VMAT Machine Parameter Optimization Using Policy Gradient Reinforcement Learning

Authors: Avinash Mudireddy, Nathan Shaffer, Joel J. St-Aubin

Affiliation: University of Iowa

Abstract Preview: Purpose: This work demonstrates preliminary results in training a reinforcement learning (RL) network to perform VMAT machine parameter optimization.
Methods: We implemented a policy gradient RL al...

Weak-to-Strong Generalization for Interpretable Deep Learning-Based Histological Image Classification Guided By Hand-Crafted Features

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...