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Results for "extracted notes": 11 found

A Radiomic Quantification Framework for Hyperparameter Optimization in Texture Characterization

Authors: Yuli Lu, Chendong Ni, Cheng Qian, Kun Qian, Weiwei Sang, Chunhao Wang, Fan Xia, Zhenyu Yang, Fang-Fang Yin, Rihui Zhang, Haiming Zhu

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

Abstract Preview: Purpose: To develop a radiomic quantification framework to evaluate the effects of radiomic image preprocessing hyperparameters (i.e., image resampling and discretization) on texture characterization ...

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 ...

An Automated Approach to Monitoring Clinical Protocols Against a Master Protocol

Authors: Jeremy Christophel, Zhihua Qi

Affiliation: Henry Ford Health

Abstract Preview: Purpose: To demonstrate a method to compare DICOM metadata from clinical scanners with institutional protocols as validation that clinical use matches the master protocol.
Methods: DICOM metadata i...

Breast Fascial Ligament Characterization Using Cryo-Fluorescence Tomography Imaging

Authors: Taylor A Beal, Kari J. Brewer Savannah, Kristy K. Brock, Alejandro Contreras, Natalie W Fowlkes, Megan Kalambo, Gregory P Reece, Erin P Snoddy, Tien T Tang

Affiliation: The University of Texas MD Anderson Cancer Center, Baylor College of Medicine

Abstract Preview: Purpose: Current anatomical and surgical research does not adequately detail the breast fascial systemโ€™s ligaments and connective tissues. Most available information stems from cadaver dissections, wh...

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 ...

Feasibility of Extracting Diagnosis and Staging at Scale from Clinical Notes Via a Real-World Data Warehouse

Authors: Melissa Bronson, Elizabeth L. Covington, Robert T. Dess, Joseph R. Evans, William C. Jackson, Charles S. Mayo, Michelle L. Mierzwa, Benjamin S. Rosen, VG Vinod Vydiswaran, Grant Weyburne, Zheng Zhang, Henry Zocher

Affiliation: PCORnetยฎ, The National Patient-Centered Clinical Research Network, University of Michigan

Abstract Preview: Purpose: Diagnosis and staging are an integral part of cancer care, but this information is often scattered across various electronic medical records. The fragmentation increases overall documentation...

Improved Setup Accuracy for Dibh Whole Breast Radiotherapy with Surface-Guided Radiation Therapy

Authors: CheukKai Becket Hui, Goldie M. Klein, Yildirim D. Mutaf, Amir Pourmoghaddas

Affiliation: UC Health, Kaiser Permanente

Abstract Preview: Purpose:
In this study, we investigated the effect of SGRT (Align-RT) implementation on patient setup accuracy for DIBH breast radiotherapy treatments.
Methods:
We extracted vertical post-ima...

Lymphocytic Feature Characterization Using a Deep Learning Algorithm on Post-Radiation Lymph Nodes

Authors: Rico Castillo, Katherine Gonzalez, Casey C. Heirman, Kyle J. Lafata, Casey Y. Lee, Xiang Li, Yvonne M Mowery, Yvonne M Mowery, Daniel Murphy, Allison Pittman, Ashlyn G. Rickard

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

Abstract Preview: Purpose: To evaluate the ability of a deep learning model to identify pathomic features in lymph nodes of preclinical head and neck squamous cell carcinoma (HNSCC) models as surrogates for predicting ...

Prediction of Metastasis-Free Survival in Patients with Prostate Adenocarcinoma Using Primary Tumor and Lymph Node Radiomics from Pre-Treatment PSMA PET/CT Scans.

Authors: Ozan Cem Guler, William Silva Mendes, Sangbo Oh, Cem Onal, Lei Ren, Apurva Singh, Phuoc Tran

Affiliation: University of Maryland School of Medicine, Baskent University Faculty of Medicine, Department of Radiation Oncology, Department of Radiation Oncology, University of Maryland School of Medicine

Abstract Preview: Purpose: To predict metastasis-free survival (MFS) for patients with prostate adenocarcinoma treated with androgen deprivation therapy and external radiotherapy using clinical factors and radiomics ex...

Quality Assurance for Prior Radiotherapy Using a Large Language Model

Authors: Douglas John Moseley, David M. Routman, Satomi Shiraishi, Donald C Smith, Mark R. Waddle

Affiliation: University of Denver, Mayo Clinic

Abstract Preview: Purpose: About 6% of patients treated for the first time in our department have received radiotherapy previously at an outside institution. We aim to provide an automatic quality assurance of identify...

Quantitative Fluorescence Imaging and Spatial Transcriptomics Reveal Compartment-Specific Immune Dynamics in HPV+ Oropharyngeal Cancer

Authors: Casey C. Heirman, Kyle J. Lafata, Xiang Li, Breylon Riley, Jack B Stevens, Tammara Watts

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

Abstract Preview: Purpose: To leverage quantitative fluorescence imaging and spatial transcriptomics for characterizing the spatial and molecular heterogeneity of the tumor microenvironment (TME) in HPV+ head and neck ...