Gradient-Based Radiomics for Outcome Prediction and Decision-Making in PULSAR: A Preliminary Study.

Haozhao Zhang^1,2, Jiaqi Liu^1,2, Michael Dohopolski^1,2, Zabi Wardak¹, Robert Timmerman¹, Hao Peng^1,2

¹Department of Radiation Oncology, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.

²Medical Artificial Intelligence and Automation Laboratory, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA.

PubMed PMC DOI PDF

Abstract

PURPOSE: Personalized ultrafractionated stereotactic adaptive radiation therapy (PULSAR) has emerged as an innovative method for delivering high-dose radiation over extended intervals, adapting treatment based on the patient's response. However, current adaptation largely relies on physicians' experience and tumor size assessment, underscoring the need for a data-driven approach to improve outcome…

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