SS 41 - Radiation and Cancer Physics 7: AI-Driven Imaging and Predictive Modeling

Presentations

• 02:30pm - 03:45pm PT

  Radiation and Cancer Physics 7: AI-Driven Imaging and Predictive Modeling

  Speaker: Ke Sheng, PhD - University of California, San Francisco, San Francisco
• 02:30pm - 02:40pm PT

  Validation of a Poissonian LQ-Based Population TCP Model for Breast Cancer Radiotherapy

  Speaker: Sergejs Unterkirhers, DSc, PhD, MS, BS - Radiotherapy Hirslanden, Zurich
• 02:40pm - 02:50pm PT

  Predicting Voxel-Level Local Progression for Locally Advanced NSCLC following Chemoradiation Using Multi-Task Deep Learning

  Speaker: Jie Fu, PhD - University of Washington, Seattle
• 02:50pm - 03:00pm PT

  An Explainable Deep Model for Risk Scoring and Accurate Radionecrosis Identification Following Brain Metastasis Stereotactic Radiosurgery

  Speaker: Jingtong Zhao, MS, BS - Duke University, Durham
• 03:00pm - 03:10pm PT

  Independent External Validation of Radiation-Induced Esophagitis Prediction during Chemoradiation Therapy for NSCLC Using RTOG 0617 Trial Data

  Speaker: Laura Cella, PhD - National Research Council (IBB), Napoli
• 03:10pm - 03:20pm PT

  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

  Speaker: Yufeng Cao, PhD - University of Maryland Central Maryland Radiation Oncology, Columbia
• 03:20pm - 03:30pm PT

  3D Topological Analysis for Assessing Therapeutic Responses to Radiation and Chemotherapy with and without Anti-CD40 Immunotherapy in Local Advanced Rectal Cancer

  Speaker: Hao Peng, PhD - UT Southwestern Medical Center, Dallas
• 03:30pm - 03:40pm PT

  Radiotherapy-Induced Acute Lymphopenia for Low and Intermediate Risk Prostate Cancer

  Speaker: Maryam Moteabbed, PhD - Massachusetts General Hospital, Boston