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Results for "kaplan meier": 7 found

A Framework for Automated Selection of Dose-Volume Objectives to Improve Radiation-Induced Immune Suppression (RIIS)-Related Overall Survival (OS) Following Chemo-Radiotherapy

Authors: Gabriel Lucas Andrade de Sousa, Einsley-Marie Janowski, Cam Nguyen, Krishni Wijesooriya

Affiliation: Department of Radiation Oncology, University of Virginia, Department of Physics, University of Virginia

Abstract Preview: Purpose: Optimizing radiation therapy (RT) to spare the immune system may improve Overall Survival (OS) in cancer patients. This study develops a computational algorithm to identify optimal dose-volum...

A Topological Technique to Unify Image Texture and Morphology to Enhance Radiomic Feature Representations

Authors: David Brizel, Kyle J. Lafata, Jian-Guo Liu, Yvonne M Mowery, Yvonne M Mowery, William Paul Segars, Jack B Stevens

Affiliation: Department of Physics, Duke University, Carl E. Ravin Advanced Imaging Laboratories and Center for Virtual Imaging Trials, Duke University Medical Center, Duke University, Department of Radiation Oncology, Duke University, University of Pittsburgh

Abstract Preview: Purpose: To develop a technique to quantify tumor topology using a unifying mathematical framework that integrates texture and morphology and to evaluate its feasibility as a prognostic biomarker for ...

AI-Driven Drug Discovery through an Interactive Analysis of Radiomics and Biological Insights in Glioblastoma

Authors: Nobuki Imano, Yuzuha Kadooka, Daisuke Kawahara, Misato Kishi, Yuji Murakami, Shumpei Onishi

Affiliation: Department of Radiation Oncology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Graduate School of Biomedical and Health Sciences, Hiroshima University, Department of Neurosurgery, Hiroshima University Hospital

Abstract Preview: Purpose: Radiomics has proven useful in predicting overall survival in glioblastoma (GBM) patients, but consistent molecular correlations remain unidentified, leaving its biological basis unclear. Thi...

Assessment of Alpha-Fetoprotein As a Prognostic Factor of Overall Survival for HCC Patients Undergoing 90Y-Glass Trans-Arterial Radioembolization

Authors: Srinivas Cheenu Kappadath, James Long, Armeen Mahvash, Anna Marks, Ajalaya Teyateeti

Affiliation: Mahidol University, The University of Texas MD Anderson Cancer Center, UT MD Anderson Cancer Center

Abstract Preview: Purpose:
Alpha-fetoprotein (AFP) has been implicated as prognostic factor of overall survival (OS) for hepatocellular carcinoma (HCC). We present a statistical approach to determine optimal AFP-cut...

Exploring NSCLC Microenvironments: Multi-Score Survival Models Integrationg Radiomics-Based Regional Imaging Features and Genomics

Authors: Nobuki Imano, Daisuke Kawahara, Misato Kishi, Yuji Murakami

Affiliation: Department of Radiation Oncology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Graduate School of Biomedical and Health Sciences, Hiroshima University

Abstract Preview: Purpose: This study aims to develop a comprehensive Multi-score by integrating Radiomics-score (Rad-score), Gene-score derived from gene expression levels, and tumor environment Rad-score (TE-Rad-scor...

In-Silico Clinical Trials Enabled By Digital Twin Approach Can Accurately and Prospectively Predict Outcomes of Clinical Trials Combining Radiation and Systemic Therapy

Authors: Clemens Grassberger, David (Bo) McClatchy, Harald Paganetti

Affiliation: Department of Radiation Oncology, University of Washington and Fred Hutchinson Cancer Center, Massachusetts General Hospital

Abstract Preview: Purpose: While randomized controlled trials (RCTs) are the gold standard for demonstrating efficacy, nearly 50% of late-stage clinical trials fail to meet their endpoint. Tools to study the design of ...

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 ...