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Results for "cross modality": 28 found

A Foundational Model for Medical Imaging Modality Translation in Head and Neck Radiotherapy

Authors: Jie Deng, Yunxiang Li, Xiao Liang, Weiguo Lu, Jiacheng Xie, You Zhang

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, University of Texas 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: Recently, foundational models trained on large datasets have shown remarkable performance across various tasks. Developing a foundational model for medical image modality translation in head-...

A Novel Proton Lattice Modality Using Minibeams

Authors: Hao Gao, Yuting Lin, Nimita Shinde, Weijie Zhang

Affiliation: Department of Radiation Oncology, University of Kansas Medical Center

Abstract Preview: Purpose: LATTICE, a form of spatially fractionated radiation therapy (SFRT), delivers high-dose peaks and low-dose valleys to the target volume and has been clinically used for large target volumes. H...

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...

A Vision-Language Deep Learning Model for Predicting Survival Outcomes in Glioblastoma Patients

Authors: Zachary Buchwald, Chih-Wei Chang, Richard L.J. Qiu, Mojtaba Safari, Hui-Kuo Shu, Lisa Sudmeier, Xiaofeng Yang, David Yu, Xiaohan Yuan

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

Abstract Preview: Purpose: This study proposes a novel vision-language model (VLM) to predict survival outcomes in glioblastoma (GBM) patients. By integrating multimodal MRI data and clinical information, the proposed ...

Anatomical Noise Power Exponent (Ξ²) 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 Ξ² as a potential image-based breast cancer risk factor.

Methods: Two groups of breast cancer screening cohorts (target vs. control, 20 sub...

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...

Clinically Ready Simulation Package for Monitoring Gamma Hotspot Emission, and Detection in Patient Anatomy

Authors: Ananta Raj Chalise, Matthias K Gobbert, Zhuoran Jiang, Sina Mossahebi, Stephen W. Peterson, Jerimy C. Polf, Lei Ren, Ehsan Shakeri, Vijay Raj Sharma, Jie Zhang

Affiliation: University of Maryland School of Medicine, University of Maryland Baltimore County, University of Maryland, Baltimore County, Stanford University, University of Maryland, School of Medine, Department of Physics, University of Cape Town, M3D, Inc

Abstract Preview: Purpose: Prompt gamma (PG) imaging is a promising modality for proton dose verification. Currently, there is a lack of effective tool to investigate the PG emission during proton therapy and optimize ...

Cross-Slice Attention for Unsupervised 3D Pelvic CBCT to CT Translation

Authors: Xu Chen, Jun Lian, Yunkui Pang, Pew-Thian Yap

Affiliation: University of North Carolina at Chapel Hill, Huaqiao University

Abstract Preview: Purpose: Unsupervised CBCT-to-CT translation in the pelvic region is essential for accurate radiotherapy delivery and adaptive image-guided interventions. However, current models for cross-modality tr...

Dosimetric Evaluation of a Helical Tomotherapy to L-Shaped Linac Plan Conversion Workflow

Authors: Megan E. Daly, Ryan D. Hernandez, Abriel J. Horak, Soo Kyoung Kim, Peter C. Park, Dwaine O. Spence, Payton H. Stone, Cari L. Wright

Affiliation: UC Davis Cancer Center

Abstract Preview: Purpose: To evaluate a fallback planning workflow used for cross-modality treatment planning and delivery between helical Tomotherapy and volumetric modulated arc therapy (VMAT) using conventional L-s...

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...

Enhancing Urethral Visualization for Prostate SBRT Using Post-Void T2-Weighted Imaging on a Low-Field 0.35T MR-Linac System

Authors: Nebi Demez, Michael Kasper, Noufal Manthala Padannayil, Shyam Pokharel, Suresh Rana, Lauren A. Rigsby, Tino Romaguera, Nishan Shrestha, Somol Sunny

Affiliation: Lynn Cancer Institute, Boca Raton Regional Hospital, Baptist Health South Florida

Abstract Preview: Purpose: Accurate delineation of the urethra is critical for optimizing tumor control and minimizing urethral toxicity in prostate stereotactic body radiation therapy (SBRT). The purpose of this study...

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

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

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

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

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...

Impact of Patient Size on the Choices of Dual and Single Energy CT for Accurate Liver Fat Volume Fraction Quantification

Authors: Xinhua Li, Jie Zhang, Yifang (Jimmy) Zhou

Affiliation: University of Kentucky, Cedars-Sinai Medical Center

Abstract Preview: Purpose: Fat volume fraction (FVF) is an important biomarker for non-alcoholic fatty liver disease. CT can be a good modality for FVF assessment if the accuracy is adequate. We aimed to study the impa...

Integrating Multiple Modalities with Pretrained Swin Foundation Model for Head and Neck Tumor Segmentation

Authors: Jue Jiang, Aneesh Rangnekar, Shiqin Tan, Harini Veeraraghavan

Affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Weill Cornell Graduate School of Medical Sciences

Abstract Preview: Purpose: Clinicians often use information from FDG-PET and CT to interpret and delineate gross tumor (GTVp) and nodal (GTVn) volumes for radiotherapy planning in head and neck (HN) cancer patients. He...

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...

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...

Low-Cost Image Quality Assurance Phantom Customization Via Additive Manufacturing

Authors: Sarah E. Holler, Daniel Johnson

Affiliation: Department of Radiation Oncology, University of Kansas Medical Center

Abstract Preview: Purpose: As the technological availability of modern clinical infrastructure increases in resource-restricted regions of the world, the needs to maintain quality standards of practice need not be hamp...

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...

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 ...

Quantitative Fluorescence Molecular Tomography Guide Radiation Therapy

Authors: Jiahao Chen, Yunwen Huang, Yidong Yang, Shanshan Zhang, Ning Zhao, Cheng Zheng

Affiliation: Department of Life Sciences and Medicine, 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 a molecular image-guided radiotherapy technique for accurate and effective radiation treatment using quantitative fluorescence molecular tomography (FMT).
Methods: X-ray cone be...

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...

Weekly Changes in Ventilation Response for Photon and Proton Patients during Radiotherapy

Authors: Kristy K. Brock, Austin Castelo, Yulun He, Zhongxing Liao, Rebecca Lim, Radhe Mohan, Caleb O'Connor, Tien T Tang, Uwe Titt

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

Abstract Preview: Purpose: Conformal dose distributions in proton radiotherapy promise to reduce normal tissue toxicity such as radiation-induced pneumonitis, but this has not been fully realized in clinical trials. To...