Authors: Xiaoying Pan, X. Sharon Qi
Affiliation: Department of Radiation Oncology, University of California, Los Angeles, School of Computer Science and technology,Xi'an University of Posts and Telecommunications
Abstract Preview: Purpose:
Survival prediction for cancer presents a substantial hurdle in personalized oncology, due to intricate, high-dimensional medical data. Our study introduces an innovative feature selection...
Authors: Jiayi Du, Lihua Jin, Ke Sheng, Yu Zhou
Affiliation: Harvard University, University of California, San Francisco, UCLA, Department of Radiation Oncology, University of California, San Francisco
Abstract Preview: Purpose: Radiomics enables powerful insights into tumor biology through non-invasive imaging, excelling in diagnostic and prognostic predictions. However, due to a lack of mechanistic connections, que...
Authors: Eric N Carver, Julia Marks
Affiliation: Brown University
Abstract Preview: Purpose: The clinical applicability of radiomic features is hindered by challenges in stability and reproducibility. To address this, researchers are establishing image and feature standardizations an...
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...
Authors: Rex A. Cardan, Carlos E. Cardenas, John B Fiveash, Joel A. Pogue, Richard A. Popple, Farnaz Rahim Li, Rodney J. Sullivan, Natalie N. Viscariello, Christopher Willey
Affiliation: The University of Alabama at Birmingham, University of Alabama at Birmingham
Abstract Preview: Purpose: vBrain radiosurgery toxicity-rate is estimated via clinically-relevant isodose volume (IDV) thresholds according to HyTEC (e.g., V12Gy≤10cc). HyperArcTM (HA) automated planning allows accurat...
Authors: Michael Ashenafi, Nicholas Becerra Espinosa, Mario Ramos Gallardo, Matthew Pacella, Sean M. Tanny
Affiliation: Department of Radiation Oncology, University of Rochester
Abstract Preview: Purpose: A new multileaf collimator (MLC) model has been introduced in Varian Eclipse v18.0, with the treatment planning system (TPS) explicitly modeling the leaf end effects. The vendor recommends a ...
Authors: Caroline Esposito, Keith T Griffin, Jae Won Jung, Choonik Lee, Choonsik Lee, Matthew Mille, Harald Paganetti, Sergio Morato Rafet, Jan PO Schuemann, Jungwook Shin, Torunn I Yock
Affiliation: East Carolina University, University of Michigan, Massachusetts General Hospital, National Cancer Institute, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Massachusetts General Hospital and Harvard Medical School
Abstract Preview: Purpose: The National Cancer Institute’s Pediatric Proton and Photon Therapy Comparison Cohort aims to collect and analyze data from cancer centers across the United States and Canada to quantify diff...
Authors: Issam M. El Naqa, Kurukulasuriya Ruwani Fernando, Himani Himani, Vivek Kumar, Arun Oinam, Manju Sharma
Affiliation: Panjab University, Moffitt Cancer Center, H. Lee Moffitt Cancer Center, Post Graduate Institute of Medical Sciences, University of California San Francisco
Abstract Preview: Purpose: To investigate the utility of Magnetic Resonance Imaging (MRI)-based radiomics for predicting tumor response and adverse effects, specifically gastrointestinal (GI) toxicity, in cervical canc...