Extraction of radiomic features has to be repeatable in order to be clinically useful. We investigated the repeatability of radiomic feature extraction on a unique dataset consisting of a double baseline MRI scans in 48 patients diagnosed with glioblastoma. Size and shape features which are mostly governed by tumor segmentation showed on average higher repeatability than intensity and texture-based features which are more dependent on image acquisition and preprocessing. More research on the influence of image acquisition and preprocessing on the repeatability and reliability of radiomic features has to be undertaken to make radiomics a safe image-analysis tool.
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