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Machine learning identifies multi-parametric functional PET/MR imaging cluster to predict radiation resistance in preclinical head and neck cancer models.

Simon BoekeRené M WinterSara LeibfarthMarcel A KruegerGregory BowdenJonathan CottonBernd J PichlerDaniel ZipsDaniela Thorwarth
Published in: European journal of nuclear medicine and molecular imaging (2023)
A quantitative imaging metric was described in a preclinical study indicating that radiation-resistant subvolumes in HNC may be detected by clusters of ADC and FMISO using combined PET/MRI which are potential targets for future functional image-guided RT dose-painting approaches and require clinical validation.
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