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Results for "multi modality": 26 found

A Semi-Automated Landmark Identification Framework for Liver MR-CT Image Pairs: Towards a Multi-Modality DIR Benchmark Dataset

Authors: Deshan Yang, Zhendong Zhang

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

Abstract Preview: Purpose:
The evaluation of deformable image registration (DIR) algorithms is crucial for improving accuracy and clinical adoption. However, reliable benchmarks, especially for inter-modality regist...

Assessment of the Impact of CT Respiratory Motion on PET SUV Quantification through Virtual Imaging

Authors: Ehsan Abadi, Darrin Byrd, Paul E. Kinahan, Katie Marie Olivas, Ehsan Samei

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

Abstract Preview: Purpose: To evaluate the impact of respiratory motion during CT acquisitions on PET image quantification using an integrated PET-CT simulation pipeline.
Methods: A validated CT simulator (DukeSim) ...

Automated Multimodal Image Registration for Prostate Bed Radiation Treatment

Authors: Quan Chen, Xue Feng, Chunhui Han, Gaofeng Huang, Trevor Ketcherside, Yi Lao, Yun Rose Li, An Liu, Bo Liu, Kun Qing, William T. Watkins

Affiliation: Graduate Program in Bioengineering, University of California San Francisco-UC Berkeley, Department of Radiation Oncology, City of Hope National Medical Center, Mayo Clinic Arizona, Carina Medical LLC

Abstract Preview: Purpose: New treatment platforms such as Ethos (Varian Medical Systems) allow the introduction of multi-modal imaging into adaptive radiotherapy workflow to facilitate an up-to-date view of patients’ ...

BEST IN PHYSICS MULTI-DISCIPLINARY: Building a Cross-Modality Model to Integrate Bio-Clinical Features, Anatomical MRI, and White-Matter Pathlength Mapping for Personalized Glioblastoma RT Planning

Authors: Steve Braunstein, Angela Jakary, Hui Lin, Bo Liu, Janine Lupo, Tiffany Ngan, Ke Sheng, Nate Tran

Affiliation: Radiation Oncology, University of California San Francisco, Graduate Program in Bioengineering, University of California San Francisco-UC Berkeley, Department of Radiation Oncology, University of California San Francisco, Department of Radiology and Biomedical Imaging, University of California San Francisco, Department of Radiation Oncology, University of California, San Francisco

Abstract Preview: Purpose: Current RT clinical target volumes (CTVs) for Glioblastoma (GBM) employ 2cm isotropic expansions of gross tumor volumes. However, studies showed patients still experience progression beyond t...

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...

Biomechanically Guided Deep Learning for Deformable Multimodality Liver Registration Framework

Authors: Yunfei Dong, Dongyang Guo, Zhenyu Yang, Fang-Fang Yin, Zeyu Zhang

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

Abstract Preview: Purpose:
To develop a Biomechanically Guided Deep Learning Registration Network (BG-DRNet) that improves both accuracy and physiological plausibility in liver image registration. While cone-beam CT...

Design and Use of a Modified Commercial Phantom for Gamma Knife End-to-End Testing

Authors: Edward A. Opalko, Matthew B. Podgorsak, Dheerendra Prasad

Affiliation: Roswell Park Comprehensive Cancer Center

Abstract Preview: Purpose: To design a 3D printed insert for Varian’s SRS Head Phantom that allows for multi-planar film dosimetry and to evaluate its ability in end-to-end testing for Gamma Knife treatments.
Method...

Efficient Denoising of Low-Statistic Influence Matrices Using a Diffusion Transformer-Based Framework for Adaptive Proton Therapy

Authors: Yuzhen Ding, Hongying Feng, Jason Michael Holmes, Baoxin Li, Wei Liu, Daniel Ma, Lisa McGee, Samir H. Patel, Jean Claude M. Rwigema, Sujay A. Vora

Affiliation: Arizona State University, Department of Radiation Oncology, Mayo Clinic, Mayo Clinic Arizona, Mayo Clinic

Abstract Preview: Purpose:
Intensity-modulated proton therapy (IMPT) is a preferred treatment modality for head and neck (H&N) cancer patients, offering precise tumor targeting while sparing surrounding organs at ri...

Enhanced Prognostic Modeling for Clear Cell Renal Cell Carcinoma Via Multi-Omics Model and Computational Pathology Foundation Model Integration

Authors: James Brugarolas, Meixu Chen, Raquibul Hannan, Payal Kapur, Jing Wang, Kai Wang

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

Abstract Preview: Purpose: Accurate prognosis of clear cell renal cell carcinoma (ccRCC) is essential for guiding personalized treatment planning. In this study, we present a multi-modal ensemble model (MMEM) that inte...

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...

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...

Implementing a Learning-to-Optimize Machine Learning Framework to Accelerate VMAT Treatment Planning Optimization for Prostate Cancer

Authors: Ara Alexandrian, Sadiki Daniel

Affiliation: Louisiana State University, Mary Bird Perkins Cancer Center

Abstract Preview: Purpose: To develop a learning-to-optimize machine learning model that accelerates optimization in VMAT treatment planning by training on prostate patient data.
Methods: A treatment plan dataset of...

Integrating SPECT and Compton Imaging for Multi-Energy Photon Reconstruction

Authors: Qihui Lyu, Javier Caravaca Rodriguez, Youngho Seo, Ke Sheng, Jingjie Yu

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

Abstract Preview: Purpose:
Simultaneous broad-energy imaging is critical for many theragnostic applications, but the current Single-Photon Emission Computed Tomography (SPECT) can only image low energy photons with ...

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...

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

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

Affiliation: Duke University, Duke Kunshan University

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

LLM-Enhanced Multi-Modal Framework for Predicting Pain Relief of Stereotactic Body Radiotherapy for Spine Metastases Using Clinical Factors and Imaging Reports

Authors: John Byun, Steven D Chang, Mingli Chen, Cynthia Chuang, Xuejun Gu, Melanie Hayden Gephart, Yusuke Hori, Hao Jiang, Mahdieh Kazemimoghadam, Fred Lam, Gordon Li, Lianli Liu, Weiguo Lu, David Park, Erqi Pollom, Elham Rahimy, Deyaaldeen Abu Reesh, Scott Soltys, Gregory Szalkowski, Lei Wang, Qingying Wang, Zi Yang, Xianghua Ye, Kangning Zhang

Affiliation: Department of Radiation Oncology, Stanford University, 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: Accurate prediction of pain relief is crucial in determining the clinical effectiveness of Stereotactic body radiotherapy (SBRT) regimen for spine metastases. We propose a deep-learning frame...

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-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-Organ Segmentation of Pelvic Cone-Beam Computed Tomography (CBCT) with Transformer Models to Enhance Adaptive Radiotherapy for Prostate Cancer

Authors: Ming Chao, Thomas Chum, Tenzin Kunkyab, Yang Lei, Tian Liu, Richard G Stock, Hasan Wazir, Junyi Xia, Jiahan Zhang

Affiliation: Icahn School of Medicine at Mount Sinai

Abstract Preview: Purpose:
This study aims to develop effective strategies for multi-organ segmentation of pelvic cone-beam computed tomography (CBCT) images based on transformer models to facilitate adaptive radiat...

Multimodal Attention Fusion Model Leveraging Structured and Unstructured EHR Data for Hospital Readmission Prediction in Head and Neck Cancer

Authors: Shreyas Anil, Jason Chan, Arushi Gulati, Yannet Interian, Hui Lin, Benedict Neo, Andrea Park, Bhumika Srinivas

Affiliation: Department of Otolaryngology Head and Neck Surgery, University of California San Francisco, Department of Data Science, University of San Francisco, Department of Radiation Oncology, University of California San Francisco

Abstract Preview: Purpose: Hospital readmission prediction models often rely on structured Electronic Health Record (EHR) data, overlooking critical insights from unstructured clinical notes. This study presents a mult...

Patient-Specific Imaging Modality Agnostic Virtual Digital Twins Modeling Temporally Varying Digestive Motion

Authors: James M. Balter, Lando S. Bosma, Jorge Tapias Gomez, Nishant Nadkarni, Mert R Sanbuncu, William Paul Segars, Ergys D. Subashi, Neelam Tyagi, Harini Veeraraghavan

Affiliation: University of Michigan, The University of Texas MD Anderson Cancer Center, Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Carl E. Ravin Advanced Imaging Laboratories and Center for Virtual Imaging Trials, Duke University Medical Center, Cornell University, University Medical Center Utrecht, Memorial Sloan Kettering Cancer Center

Abstract Preview: Purpose: Develop patient-specific virtual digital twin (VDT) cohorts modeling physically realistic spatio-temporal gastrointestinal (GI) organs (stomach and duodenum) digestive motion.
Methods: Pat...

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 ...

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...

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...

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

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

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

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