Radiotherapy

Thrilled to share that our work has been selected for an Oral Scientific Presentation in the BEST of Physics session at the American Society for Radiation Oncology (ASTRO) 2026 Annual Meeting, September 26–30 in Boston, MA. Out of ~2,700 abstracts submitted to ASTRO this year, only 300 were chosen for oral presentation, and BEST of Physics gathers the highest-rated physics work of the meeting. Presentation details Abstract # 75557 Title Early Adaptive Interventions in Lung Cancer: Leveraging Fusion of Longitudinal CBCT Trajectories and Clinical Variables for Robust Survival Prediction Session SS 19 — BEST of Physics Date / Time September 28, 2026 · 10:45 AM – 12:00 PM ET Venue Thomas M. Menino Convention & Exhibition Center, Boston, MA Format 7-min oral + 3-min Q&A Publication Red Journal supplement Authors Wookjin Choi, Pradeep Bhetwal, Michael Dichmann, Yingcui Jia, Wenchao Cao, Danfu Liang, Yingxuan Chen, Adam Dicker, Yevgeniy Vinogradskiy ...

I’m excited to share a new collaborative study I had the privilege of co-authoring, which was recently published in Nutrients. Led by Jefferson medical student Julia Logan, this work explores how large language models (LLMs) like ChatGPT and Gemini can deliver accessible, culturally sensitive dietary advice to cancer patients—many of whom lack access to professional nutritional counseling due to insurance limitations or socioeconomic barriers. ...

We’re excited to share our latest work published in Technology in Cancer Research & Treatment: “Deep Learning-Based Auto-Segmentation for Liver Yttrium-90 Selective Internal Radiation Therapy” — a collaboration between Jun Li, Rani Anne, and myself. This study introduces a deep learning (DL) model built on the 3D U-Net architecture, developed to automatically segment the liver in CT scans for patients undergoing Y-90 Selective Internal Radiation Therapy (SIRT). Accurate liver segmentation is a critical step for calculating Y-90 dosage, traditionally done manually — a time-consuming and subjective process. ...

Jefferson Investigates: Artificial Intelligence and Heart Disease — The Nexus https://medicalxpress.com/news/2024-06-machine-lung-cancer-scans-heart.html

Our study on cardiac toxicity in lung cancer treatment is now featured in a JCO CCI editorial. Discoveries that could change patient care are on the horizon. Stay tuned! #CardiacToxicity#LungCancer#Innovation Shining a Light: Unveiling Cardiac Risks Using Positron Emission Tomography Imaging in Lung Cancer Radiotherapy

AAPM 2023, ASTRO 2023

Our paper “Novel Functional Radiomics for Prediction of Cardiac Positron Emission Tomography Avidity in Lung Cancer Radiotherapy” has been published in JCO CCI. This research work delves into an innovative approach to predict clinical cardiac assessment using functional imaging. Abstract: Traditional methods for evaluating cardiotoxicity primarily focus on radiation doses to the heart. However, functional imaging offers the potential to enhance early prediction of cardiotoxicity in lung cancer patients undergoing radiotherapy. In this context, Fluorine-18 (18F) fluorodeoxyglucose (FDG)-positron emission tomography (PET)/computed tomography (CT) imaging plays a crucial role. This study aims to develop a radiomics model that predicts clinical cardiac assessment using 18F-FDG PET/CT scans before thoracic radiation therapy. ...

AAPM Annual Meeting (Houston, TX • July 23 ‒ 27, 2023) Novel Functional Delta-Radiomics for Predicting Overall Survival in Lung Cancer Radiotherapy Using Cardiac FDG-PET Uptake Wookjin Choi, Yevgeniy Vinogradskiy Interactive ePoster Discussions: Sunday, July 23, 2023: 3:00 PM - 3:30 PM, GRBCC, Exhibit Hall | Forum 6 SU-300-IePD-F6-4 Novel Functional Delta-Radiomics for Predicting Overall Survival in Lung Cancer Radiotherapy Using Cardiac FDG-PET Uptake Deep Learning Segmentation for Accurate GTV and OAR Segmentation in MR-Guided Adaptive Radiotherapy for Pancreatic Cancer Patients Wookjin Choi, Hamidreza Nourzadeh, Yingxuan Chen, Christopher G. Ainsley, Vimal K. Desai, Alexander A. Kubli, Yevgeniy Vinogradskiy, Maria Werner-Wasik, Adam Mueller, and Karen E. Mooney PO-GePV-D-50 Deep Learning Segmentation for Accurate GTV and OAR Segmentation in MR-Guided Adaptive Radiotherapy for Pancreatic Cancer Patients ...

Varian will support my research project entitled “Longitudinal CBCT radiomics analysis for lung cancer radiotherapy response and prognosis prediction” with $230,000 over 2 years. This is the first research grant from Varian to the Department of Radiation Oncology, Sidney Kimmel Medical College at Thomas Jefferson University. This project can potentially impact the clinical practice of lung cancer patients by using standard imaging modalities (CBCT and 4D-CBCT) to provide early prediction of prognosis and toxicity. ...