Image-based personalization of computational models for predicting response of high-grade glioma to chemoradiation
Abstract High-grade gliomas are an aggressive and invasive malignancy which are susceptible to treatment resistance due to heterogeneity in intratumoral properties such as cell proliferation and density and perfusion. Non-invasive imaging approaches can measure these properties, which can then be us...
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Auteurs principaux: | David A. Hormuth, Karine A. Al Feghali, Andrew M. Elliott, Thomas E. Yankeelov, Caroline Chung |
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Format: | article |
Langue: | EN |
Publié: |
Nature Portfolio
2021
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Accès en ligne: | https://doaj.org/article/55eb86d0b3a0467cb8f80d1460fdead2 |
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