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Results for "survival mfs": 7 found

An Image Representation of Radiomics Data for Enhanced Deep Radiomics Analysis with Consideration of Feature Interactions

Authors: Xiaolong Fu, Runping Hou, Md Tauhidul Islam, Lei Xing

Affiliation: Department of Radiation Oncology, Stanford University, Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine

Abstract Preview: Purpose: To introduce a novel schematic image representation of radiomics data, called OmicsMap, for high-performance deep radiomics analysis. OmicsMap transforms tabular radiomics data into an image ...

Efficient Monte Carlo Simulation of Radiation-Induced Double Strand Break Production and Repair Kinetics

Authors: Zakaria Aboulbanine, Greeshma A. Agasthya, Paul Inman, Anuj J. Kapadia, Anthony Hong Cheol Lim, Jayasai Ram Rajagopal, Chris C. Wang

Affiliation: Oak Ridge National Laboratory, Georgia Institute of Technology

Abstract Preview: Purpose: Radiobiological simulation via TOPAS-nBio requires significant computational resources and time to provide meaningful results. This study aims to decrease simulation time and computational re...

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...

Graph-Based Feature Selection to Improve Stability and Reproducibility of CT-Based Radiomics in Head and Neck Squamous Cell Carcinoma: A Cross-Institutional Study

Authors: Daria Gaykalova, Ranee Mehra, Jason K Molitoris, Hajar Moradmand, Lei Ren, Amit Sawant, Phuoc Tran

Affiliation: University of Maryland School of Medicine, Maryland University Baltimore, University of Maryland, Department of Radiation Oncology, University of Maryland School of Medicine

Abstract Preview: Purpose: Radiomics extracts quantitative imaging biomarkers from medical images. However, maintaining the reproducibility and stability of selected features across institutions and parameter settings ...

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 ...

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...

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...