Predicting the Malignancy Grade of Soft Tissue Sarcomas on MRI Using Conventional Image Reading and Radiomics
Fabian Schmitz,
Hendrik Voigtländer,
Hyungseok Jang
et al.
Abstract:Objectives: This study aims to investigate MRI features predicting the grade of STS malignancy using conventional image reading and radiomics. Methods: Pretherapeutic imaging data regarding size, tissue heterogeneity, peritumoral changes, necrosis, hemorrhage, and cystic degeneration were evaluated in conventional image reading. Furthermore, the tumors’ apparent diffusion coefficient (ADC) values and radiomics features were extracted and analyzed. A random forest machine learning algorithm was trained and eval… Show more
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