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From Average to Individual: Transforming Cancer Care With Single-Subject Clinical Trials

With Digital Twins of Brain Tumors, Computational Scientists are Personalizing Cancer Care

Published in the journal Frontiers in Artificial Intelligence, Oden Institute researchers show how methods developed for digital twins in aerospace engineering can be used for high-grade glioma patients undergoing radiotherapy.  

Researchers in Texas Continue Collaboration on Oncological Data and Computational Science

Researchers in Texas Continue Collaboration on Oncological Data and Computational Science
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New Technique Predicts Response of Brain Tumors to Chemoradiation

Date Time New Technique Predicts Response of Brain Tumors to Chemoradiation AUSTIN, Texas – A team studying malignant brain tumors has developed a new technique for predicting how individual patients will respond to chemoradiation, a major step forward in efforts to personalize cancer treatment. Researchers at The University of Texas at Austin’s Oden Institute for Computational Engineering and Sciences, Texas Advanced Computing Center (TACC) and The University of Texas MD Anderson Cancer Center have merged various quantitative imaging measurements with computational simulations to create an accurate model for calculating the progression of high-grade glioma. High-grade gliomas are the most common cancerous primary brain tumors found in adults. Current treatments involve surgical resection of the tumor followed by radiation therapy and chemotherapy. Despite this aggressive treatment, prognosis for patients who undergo this approach is generally poor. The growth and behavior of

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