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Results for "novel multi": 48 found

A Combination of Radiomics and Dosiomics for Gross Tumor Volume Regression in Personalized Ultra-Fractionated Stereotactic Adaptive Radiotherapy (PULSAR)

Authors: Hao Peng, Yajun Yu

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

Abstract Preview: Purpose: Personalized ultra-fractionated stereotactic adaptive radiotherapy (PULSAR) is a novel ablative radiation dosing scheme developed by our institution. This study aims to establish a regression...

A Dual Energy CT-Guided Intelligent Radiation Therapy Platform

Authors: Jiayi Chen, Manju Liu, Ning Wen, Haoran Zhang, Yibin Zhang

Affiliation: Department of Radiation Oncology, Ruijin Hospital, Department of Radiology, Ruijin Hospital Shanghai Jiaotong University School of Medicine, Duke Kunshan University, Department of Radiation Oncology,Ruijin Hospital, Shanghai Jiao Tong University School of Medicine

Abstract Preview: Purpose: This study introduces a novel Dual Energy CT (DECT)-Guided Intelligent Radiation Therapy (DEIT) platform designed to streamline and optimize the radiotherapy process. The DEIT system combines...

A Novel Multi-Material Decomposition Algorithm for Improved Material Quantification Using Dual-Energy CT

Authors: Dale Black, David Clymer, Huanjun Ding, Hamidreza Khodajou Chokami, Sabee Molloi, Christine Vy Nguyen, Tim Sananikone, Alireza Shojazadeh, Randy Wang

Affiliation: Department of Radiological Sciences, University of California, University of California, Department of Radiological Sciences, University of California, Irvine, Department of Radiological Sciences, University of California, Irvine

Abstract Preview: Purpose: We present a novel multi-material decomposition (MMD) algorithm for accurate quantification of material concentration in reconstructed dual-energy CT images. This method addresses limitations...

Automated Treatment Planning for Linac-Based Stereotactic Radiosurgery of Intraocular Malignancies Via Hyperarc Knowledge-Based Planning

Authors: Chase Cochran, Shane McCarthy, Damodar Pokhrel, William St Clair

Affiliation: University of Kentucky, Department of Radiation Medicine, University of Kentucky, Radiation Medicine

Abstract Preview: Purpose: Manually generating intraocular stereotactic radiosurgery (SRS) plans involves significant challenges, including lengthy planning times and inter-planner variability. Knowledge-based SRS plan...

BEST IN PHYSICS MULTI-DISCIPLINARY: Foundation Model-Empowered Unsupervised 3D Deformable Medical Image Registration

Authors: Xianjin Dai, PhD, Zhuoran Jiang, Lei Ren, Lei Xing, Zhendong Zhang

Affiliation: University of Maryland School of Medicine, Department of Radiation Oncology, Stanford University, Duke University, Stanford University

Abstract Preview: Purpose: Unsupervised deep learning has shown great promise in deformable image registration (DIR). These methods update model weights to optimize image similarity without necessitating ground truth d...

Beyond Correlation: An Ultra-Large Physics-Driven Vascularized Tumor Model to Bridge Feature Formation with Underlying Biology

Authors: Jiayi Du, Lihua Jin, Ke Sheng, Yu Zhou

Affiliation: Harvard University, University of California, San Francisco, UCLA, Department of Radiation Oncology, University of California, San Francisco

Abstract Preview: Purpose: Radiomics enables powerful insights into tumor biology through non-invasive imaging, excelling in diagnostic and prognostic predictions. However, due to a lack of mechanistic connections, que...

Characterization of Linear Energy Transfer Spectra in Mini Beam Spatially Fractionated Proton Therapy

Authors: Serdar Charyyev, Kaan Dere, Edgar Gelover, Mohammad Khurram Khan, Liyong Lin, Mark McDonald, Cristina Oancea, Alexander Stanforth, Sibo Tian, Suk Whan (Paul) Yoon, Mingyao Zhu

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

Abstract Preview: Purpose: The conventional implementation of proton spatially fractionated radiotherapy (SFRT) utilizes physical collimators with apertures to generate minibeams, creating alternating regions of high-d...

Comprehensive Commissioning of an O-Ring-Shaped Image-Guided Radiotherapy System with a Gimbal-Mounted Linear Accelerator

Authors: Tetsuo Fukuda, Hideaki Hirashima, Kohei Kawata, Yukako Kishigami, Takashi Mizowaki, Mitsuhiro Nakamura, Yohei Sawada, Maika Urago

Affiliation: Kyoto University, kyotoUnivercity, Hitachi high-tech, Department of Radiation Oncology and Image-applied Therapy, Graduate School of Medicine, Kyoto University

Abstract Preview: Purpose: To present the comprehensive commissioning results of the O-ring shaped linac, OXRAY.
Materials and Methods: OXRAY enables a novel three-dimensional unicursal noncoplanar irradiation metho...

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 ...

Development and Validation of Novel Two-Stage Vascular Segmentation Model for Interventional Angiography

Authors: Abid Khan, Chad Klochko, Michael J Kovalchick, Hyeok Jun Lee, Hani Nasr, Krishnan Shyamkumar, Kundan S Thind

Affiliation: Henry Ford Radiology, Wayne State University, Henry Ford Health, HFHS

Abstract Preview: Purpose: Automated vascular segmentation in interventional angiography is challenged by contrast kinetics, vessel variations, and 2D projections, limiting the effectiveness of single-model approaches....

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 Ultrafast MR Technique to Detect Linac Radiation Pulses for Biological Imaging on a Clinical 0.35T MR-Linac

Authors: Pierre Gardair, Johnathan E Leeman, Claire Keun Sun Park, Atchar Sudhyadhom

Affiliation: Brigham and Women’s Hospital, Dana Farber Cancer Institute, Harvard Medical School, Brigham and Women’s Hospital and Dana Farber Cancer Institute, Harvard Medical School,, Brigham and Women’s Hospital and Dana Farber Cancer Institute, Harvard Medical School, Harvard Medical School

Abstract Preview: Purpose: Dose is a poor surrogate for radiobiological damage but no in vivo technology exists to directly measure damage such as DNA strand breaks and free radical generation (FRG). Recent advances in...

Dosimetric Comparison of 6X and 10X Flattening Filter-Free Photon Beams on a Truebeam Linac Using the Eclipse TPS

Authors: Carlos E. Cardenas, Udbhav S. Ram, Marcin Wierzbicki

Affiliation: The University of Alabama at Birmingham, University of Alabama at Birmingham, Juravinski Cancer Centre

Abstract Preview: Purpose:
This study aims to systematically evaluate the dosimetric properties and delivery efficiency of 6X-FFF and 10X-FFF beams for lung SBRT on the Varian TrueBeam STx using the Eclipse TPS 16.1...

Feasibility Study of Group Sparse-Based Beam Angle Optimization for Multi-Field Carbon Ion Radiotherapy

Authors: Min Cheol Han, Hojin Kim, Jin Sung Kim, Hyejin Lee, Sac Lee, Yongdo Yun

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

Abstract Preview: Purpose: Carbon ion radiotherapy (CIRT) is characterized by high relative biological effectiveness (RBE), which must be integrated into the treatment planning process. This study aims to develop a nov...

First Phantom Testing of Biology-Guided Radiotherapy for Sequential Integrated Boost Radiotherapy

Authors: Girish Bal, David J. Carlson, Huixiao Chen, Zhe (Jay) Chen, Emily A. Draeger, Dae Yup Han, Henry S. Park

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

Abstract Preview: Purpose: This study explores the feasibility, accuracy, and dosimetric performance of hybrid biology-guided radiotherapy (BgRT) combined with image-guided radiotherapy (IGRT) for delivering sequential...

First in-Vivo Application of a Novel Precision Small Animal Irradiation Platform with Proton IMPT Delivery and Advanced on-Board Image-Guidance

Authors: Niels Bassler, Jonathan Bortfeldt, Davide Boscaini, Francesco Evangelista, Guyue Hu, Ze Huang, Margarita Kozak, Julie Lascaud, Giulio Lovatti, Eero Lönnqvist, Jasper Nijkamp, Munetaka Nitta, Prasannakumar Palaniappan, Katia Parodi, Marco Pinto, Per R. Poulsen, Marco Riboldi, Babak Sharifi, Brita Singers SÞrensen, Peter Thirolf

Affiliation: Department of Medical Physics, Ludwig-Maximilians-UniversitĂ€t MĂŒnchen (LMU Munich), Ludwig-Maximilians UniversitĂ€t, Danish Centre for Particle Therapy, Aarhus University Hospital, Department of Medical Physics, Ludwig-Maximilians-UniversitĂ€t (LMU) MĂŒnchen, Department of Experimental Clinical Oncology, Aarhus University, Department of Oncology, Aarhus University Hospital

Abstract Preview: Purpose: To perform the first in vivo application of a novel small animal radiation research platform combining on-board image-guidance with multi-field intensity modulated spot scanning delivery [1] ...

From Noisy Signals to Accurate Maps: Transforming Look-Locker MRI with an Intelligent T₁ Estimation

Authors: Prabhu C. Acharya, Hassan Bagher-Ebadian, Stephen L. Brown, James R. Ewing, Mohammad M. Ghassemi, Benjamin Movsas, Farzan Siddiqui, Kundan S Thind

Affiliation: Michigan State University, Oakland University, Henry Ford Health

Abstract Preview: Purpose: Accurate T1 quantification using T One by Multiple Read Out Pulse (TOMROP) sequences is essential for physiological assessments in dynamic-contrast-enhanced (DCE) MRI and T1 mapping studies. ...

Fully Automated Review of Prostate Radiotherapy Treatment Plan Quality

Authors: Yasin Abdulkadir, John Charters, Melissa Ghafarian, James M. Lamb, Dishane Chand Luximon, Jack Neylon

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

Abstract Preview: Purpose:
Assessment of radiotherapy treatment quality in large-scale multi-institutional contexts remains an outstanding challenge. Retrospective human review of treatment plans is labor intensive ...

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...

High-Temporal Dynamic CBCT Imaging Via Gaussian Neural Representation

Authors: Weixing Cai, Laura I. Cervino, Yabo Fu, Licheng Kuo, Tianfang Li, Xiang Li, Jean M. Moran, Huiqiao Xie, Hao Zhang

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

Abstract Preview: Purpose: This study introduces a novel spatiotemporal Gaussian neural representation framework to reconstruct high-temporal dynamic CBCT images from 1-minute acquisition, preserving motion dynamics an...

Improvement of Spine Phantom for MR Imaging of the Spine

Authors: Richard Dortch, Thammathida Ketsiri, Zhiqiang Li, Shiv P. Srivastava

Affiliation: Barrow Neurological Institute, Dignity Health Cancer Institute, St. Joseph's Hospital & Medical Center

Abstract Preview: Purpose: Imaging the spinal cord post-surgery is challenging due to metal surgical implants, which induce signal loss and geometric distortions. Together, this hinders the visualization of the spinal ...

Improving Mammography Diagnosis Accuracy through Global Context and Local Lesion Integration

Authors: Minbin Chen, Xiaoyi Dai, Xiaoyu Duan, Chunhao Wang, Fan Xia, Zhenyu Yang, Fang-Fang Yin, Chulong Zhang, Rihui Zhang

Affiliation: Duke University, Duke Kunshan University, Medical Physics Graduate Program, Duke Kunshan University, The First People's Hospital of Kunshan

Abstract Preview: Purpose: Deep learning (DL)-based mammography diagnosis presents unique challenges, as accurate interpretation requires both global breast condition analysis and local lesion structural information. E...

Interpretable Deep Learning Predicts Metastasis-Free Survival (MFS) from Conventional Imaging for Oligometastatic Castration-Sensitive Prostate Cancer (omCSPC) Using Multi-Modality PSMA PET and CT Imaging.

Authors: Yufeng Cao, Luigi Marchionni, William Silva Mendes, Cem Onal, Lei Ren, Amit Sawant, Nicole L Simone, Philip Sutera, Phuoc Tran

Affiliation: University of Maryland School of Medicine, 9Department of Radiation Oncology, Thomas Jefferson University, Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins Medicine, University of Maryland, Baltimore, Baskent University Faculty of Medicine, Department of Radiation Oncology, Department of Radiation Oncology, University of Maryland School of Medicine, Maryland University Baltimore, 8Department of Pathology and Laboratory Medicine, Weill Cornell Medicine

Abstract Preview: Purpose: This study aims to predict 2-yr Metastasis-free survival (MFS) for oligometastatic castration-sensitive prostate cancer (omCSPC) patients treated by metastasis-directed therapy (MDT) by devel...

Joint Optimization of Patient-Specific Range Modulators and Beam Intensities for Conformal Flash Proton Therapy

Authors: Hao Gao, Jiayue Han, Wangyao Li, Yuting Lin, Jufri Setianegara, Aoxiang Wang, Yanan Zhu

Affiliation: Department of Biomedical Engineering, Huazhong University of Science and Technology, Department of Radiation Oncology, University of Kansas Medical Center

Abstract Preview: Purpose: Proton therapy leverages Bragg-peak-based dose delivery to achieve ultra-high-dose-rate FLASH with patient-specific range modulators (PSRM). Current proton FLASH (pFLASH) planning typically i...

Latent Diffusion Model-Driven Semi-Supervised Semantic Segmentation of Cell Nuclei

Authors: Mark Anastasio, Hua Li, Zhuchen Shao

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

Abstract Preview: Purpose: Automated semantic segmentation of cell nuclei in microscopic images is vital for disease diagnosis and tissue microenvironment analysis. However, obtaining large annotated datasets for train...

Liver Tumor Auto-Contouring Using Recurrent Neural Networks on MRI-Linac for Adaptive Radiation Therapy

Authors: Yan Dai, Jie Deng, Christopher Kabat, Weiguo Lu, Ying Zhang, Hengrui Zhao

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

Abstract Preview: Purpose:
MRI-guided adaptive radiotherapy (MRgART) using MR-LINAC systems offers significant advantages for liver cancer, enabling superior tumor delineation and online plan adaptation. However, ma...

Mapping Dosimetry, Excision Probability, and Mpmri Pixel Data to Core-Needle Biopsy Tissue from HDR Prostate Brachytherapy

Authors: Jeffrey Andrews, Nathan E. Becker, Juanita Crook, Andrew Jirasek, Matthew Jonathan Muscat

Affiliation: UBC, BC Cancer Agency, BC Cancer

Abstract Preview: Purpose: To map dosimetry and imaging information to ultrasound and multi-parametric magnetic resonance (mpMR) guided trans-perineal core-needle biopsies, performed during two-fraction prostate high-d...

Memory-Efficient Deep Learning for Volumetric Cone-Beam CT Image Reconstruction

Authors: Ziqi Gao, Lei Xing, Siqi Ye, S. Kevin Zhou

Affiliation: Department of Radiation Oncology, Stanford University, University of Science and Technology of China (USTC)

Abstract Preview: Purpose: To address the challenge of high memory usage in volumetric cone-beam CT (CBCT) imaging, we propose a method that combines joint reconstruction and super-resolution for sparsely sampled CBCT ...

Micro-Ultrasound Guided Focal Prostate Radiotherapy: Development and Testing of a Novel Device.

Authors: Kevin Barker, David Jeffrey Contella, Chandima Edirisinghe, Aaron Fenster, Douglas A Hoover, Elizabeth Huynh

Affiliation: Robarts Research Institute, University of Western Ontario, London Health Sciences Center, Department of Radiation Oncology, London Health Sciences Centre

Abstract Preview: Purpose: We aim to develop a system that integrates micro-ultrasound into focal prostate cancer radiotherapy. This requires developing a mechatronic stepper capable of performing motorized rotation of...

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-Criteria Optimization in Medical Physics Resource Allocation: Design of an Efficient and Equitable Scheduling System

Authors: Dalton Griner, Kathryn L. Kolsky, Joseph John Lucido, Andrew J. Veres

Affiliation: Mayo Clinic

Abstract Preview: Purpose: This project aimed to automate a complex and time-consuming employee scheduling process. By replacing the traditional manual method with a multi-criteria optimization-based system (MCO), the ...

Multi-Modality Artificial Intelligence for Involved-Site Radiation Therapy: Clinical Target Volume Delineation in High-Risk Pediatric Hodgkin Lymphoma

Authors: Tyler J Bradshaw, Sharon M Castellino, Steve Y Cho, David Hodgson, Bradford S Hoppe, Kara M Kelly, Andrea Lo, Sarah Milgrom, Xin Tie

Affiliation: Department of Radiation Oncology, University of Toronto, Department of Radiology, University of Wisconsin, University of Colorado Anschutz, Department of Medical Physics, University of Wisconsin, Department of Radiation Oncology, Mayo Clinic, Department of Radiation Oncology, BC Cancer, Vancouver Center, Department of Radiology, University of Wisconsin - Madison, Roswell Park Comprehensive Cancer Center, Emory University School of Medicine

Abstract Preview: Purpose: Clinical target volume (CTV) delineation for involved-site radiation therapy (ISRT) in Hodgkin lymphoma (HL) is time-consuming due to the need to analyze multi-time-point PET/CT scans co-regi...

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...

NA-Unetr: A Neighborhood Attention Transformer Network for Enhanced 3D Segmentation of the Left Anterior Descending Artery

Authors: Hassan Bagher-Ebadian, Ahmed I Ghanem, Joshua P. Kim, Chengyin Li, Rafi Ibn Sultan, Kundan S Thind, Dongxiao Zhu

Affiliation: Wayne State University, Department of Radiation Oncology, Henry Ford Health-Cancer, Detroit, MI and Alexandria Department of Clinical Oncology, Faculty of Medicine, Alexandria University, Henry Ford Health

Abstract Preview: Purpose: Accurate segmentation of the Left Anterior Descending (LAD) artery in free-breathing 3D treatment planning CT is crucial for radiotherapy but remains challenging due to its small size, comple...

Novel AI-Powered Tool to Objectively Evaluate Brain Dose for Multi-Met Stereotactic Radiosurgery Optimization

Authors: Wenchao Cao, Yingxuan Chen, Haisong Liu, Richard A. Popple, Wenyin Shi, Rodney J. Sullivan, Wentao Wang, Lydia J. Wilson, Zhenghao Xiao

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

Abstract Preview: Purpose: Objectively evaluating brain sparing as a plan-quality indicator for patients receiving stereotactic radiosurgery (SRS) to multiple metastases (multi-met) is complicated by variability in tar...

Novel Approach to Improve Treatment Planning Process for Mixed Fractionation Schemes on ZAP-X

Authors: Michael Evan Chaga, Timothy Chen, Darra M. Conti, Shabbar Danish, Jing Feng, Wenzheng Feng, Joseph Hanley, Tingyu Wang

Affiliation: Hackensack Meridian Health, Jersey Shore University Medical Center

Abstract Preview: Purpose: Using mixed fractionation schemes is a common technique in treating CNS lesions. This article describes an innovative plan-and-split approach for more efficient planning on the ZAP-X and thus...

Optimizing Design to Enhance the Energy Separation in a Kv Dual-Layer Imager (DLI)

Authors: Ross I. Berbeco, Vera Birrer, Raphael Bruegger, Pablo Corral Arroyo, Roshanak Etemadpour, Dianne M. Ferguson, Rony Fueglistaller, Thomas C. Harris, Yue-Houng Hu, Matthew W. Jacobson, Mathias Lehmann, Nicholas Lowther, Daniel Morf, Marios Myronakis

Affiliation: Brigham and Women's Hospital, Harvard Medial School, Dana-Farber Cancer Institute, Department of Radiation Oncology, Dana Farber/Brigham and Women's Cancer Center, Department of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Brigham and Womens Hospital, Dana Farber Cancer Institute, Harvard Medical School, Brigham and Women's Hospital, Varian Imaging Laboratory, Dana-Farber Cancer Institute

Abstract Preview: Purpose: Multi-layer flat-panel imagers can improve for clinical image-guided radiotherapy applications, including the enhanced visualization of soft tissue and a reduction in image artifacts. Each im...

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, ...

Plastic Scintillating Detector Assisted Spot Mapping for Patient Specific Quality Assurance in Proton Beam Therapy

Authors: Saad Bin Saeed Ahmed, Marcos Feijoo, Wazir Muhammad, Charles Shang, Naseem Ud Din

Affiliation: South Florida Proton Therapy Institute, Miami Cancer Institute, Blue Physics LLC, Florida Atlantic University

Abstract Preview: Purpose: This study introduces a novel approach for patient-specific quality assurance in proton beam therapy, utilizing new plastic scintillator detectors with high temporal resolutions to create det...

Real-Time 3D Dose Verification for MR-Guided Online Adaptive Radiotherapy (ART) Via Geometry-Encoded Deep Learning Framework

Authors: Steve B. Jiang, Dan Nguyen, Chenyang Shen, Fan-Chi F. Su, Jiacheng Xie, Shunyu Yan, Daniel Yang, Ying Zhang, You Zhang

Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, UT Southwestern Medical Center, Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center, Medical Artificial Intelligence and Automation (MAIA) Laboratory, Department of Radiation Oncology, UT Southwestern Medical Center, The University of Texas at Dallas

Abstract Preview: Purpose: Fast dose verification is essential for the safety and efficiency of MR-guided adaptive radiotherapy (ART) as patients anxiously waiting on the treatment couch. Conventional tools often requi...

Real-Time Automatic Treatment Planning System (RT-AutoTPS) for Volumetric Modulated Arc Radiotherapy (VMAT)

Authors: Steve B. Jiang, Austen Matthew Maniscalco, Dan Nguyen, Chenyang Shen, Jiacheng Xie, Shunyu Yan, Ying Zhang, You Zhang

Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, UT Southwestern Medical Center, Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center, Medical Artificial Intelligence and Automation (MAIA) Laboratory, Department of Radiation Oncology, UT Southwestern Medical Center, The University of Texas at Dallas

Abstract Preview: Purpose: Although treatment planning systems (TPSs) can handle dose calculation and plan optimization automatically, planning for radiotherapy still requires extensive efforts and expertise from a mul...

Redefining the Down-Sampling Scheme of U-Net for Precision Biomedical Image Segmentation

Authors: Yizheng Chen, Md Tauhidul Islam, Mingjie Li, Lei Xing

Affiliation: Department of Radiation Oncology, Stanford University

Abstract Preview: Purpose:
Biomedical image segmentation (BIS) is a cornerstone of medical physics, enabling accurate delineation of anatomical structures and abnormalities, which is critical for diagnosis, treatmen...

Spherical Slicing and Convolutions for Accurate Glioma Tumor Segmentation Using Multi-Parametric MRI

Authors: Ke Lu, Chunhao Wang, Ruoxu Xia, Zhenyu Yang, Fang-Fang Yin, Chulong Zhang, Lei Zhang, Rihui Zhang, Jingtong Zhao, Haiming Zhu

Affiliation: Duke University, Duke Kunshan University, Medical Physics Graduate Program, Duke Kunshan University, The First People's Hospital of Kunshan

Abstract Preview: Purpose: The human brain’s spherical geometry offers unique opportunities for improving the segmentation of tiny and irregular anatomical structures. We hypothesize that representing the brain in sphe...

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...

The Development of a Novel Biomechanical Model for Accurate Contour Deformation during Online Adaptative Metastatic Bone Cancer Radiotherapy Planning.

Authors: Jeremy S. Bredfeldt, Benito De Celis Alonso, Braian Adair Maldonado Luna, Kevin M. Moerman, Gerardo Uriel Perez Rojas, René Eduardo Rodríguez-Pérez, Kamal Singhrao

Affiliation: Department of Radiation Oncology, Brigham and Women's Hospital, Harvard Medical School, Department of Radiation Oncology, Brigham and Women's Hospital, Dana Farber Cancer Institute, Harvard Medical School, Department of Mechanical Engineering, University of Galway, Faculty of Physics and Mathematics, Benemérita Universidad Autónoma de Puebla

Abstract Preview: Purpose: Online adaptive radiotherapy replanning for single-isocenter bone cancer metastasis treatment reduces on-table treatment time and patient discomfort compared to the multi-isocenter standard-o...

Toward Harmonized AI-Based Quantitative CT: A Voxel-Printed, Patient Specific Phantom for Cross-Platform Harmonization

Authors: Aditya P. Apte, Joseph O. Deasy, Yusuf Emre Erdi, Anqi Fu, Johannes Hertrich, Andrew Jackson, Usman Mahmood, Jason Ocana, Trahan Sean, Amita Shukla-Dave

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

Abstract Preview: Purpose: Automated AI-based quantitative CT tools hold immense promise for advancing clinical decision-making, yet their reproducibility and generalizability remain vulnerable to variability in imagin...

Universal Range Modulators for Flash Proton Therapy: 3D Printing of Stackable Variable Density Units

Authors: Eric S. Diffenderfer, Lei Dong, Alejandro Garcia, Wenbo Gu, Michele M. Kim, Alexander Lin, Kai Mei, Peter B. Noël, Boon-Keng Kevin Teo, Lingshu Yin, Jennifer Wei Zou

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

Abstract Preview: Purpose: We present a novel 3D-printed range-modulating devices with spatially modulated density for FLASH particle therapy. By varying density distributions, spread-out Bragg peaks(SOBPs) can be gene...

Validation of 3D Pseudo-Dose Map Reconstructed from Multi-View Cherenkov Images in Total Skin Electron Therapy

Authors: Brook Byrd, Lisha Chen, Michael LaRiviere, Baozhu Lu, John Plastaras, Brian W Pogue, Emily Xiong, Timothy C. Zhu, Yifeng Zhu

Affiliation: Department of Radiation Oncology, University of Pennsylvania, University of Pennsylvania, University of Wisconsin - Madison

Abstract Preview: Purpose: For total skin electron therapy (TSET), achieving optimal dose distribution depends on precise patient positioning, which is often influenced by daily variability. Cherenkov imaging offers a ...