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• W2951784311 abstract "Texture analysis derived from morphological magnetic resonance (MR) images might be associated with histopathology in tumors. The present study sought to elucidate possible associations between texture features derived from T1-and T2-weighted images with proliferation index Ki67 in soft tissue sarcomas. Overall, 29 patients (n = 13, 44.8% female) with a median age of 52 years were included into this retrospective study. Several soft tissue sarcomas were investigated. Texture analysis was performed on pre-contrast T1-weighted and T2-weighted images using the free available Mazda software. The best correlation coefficients with Ki67 index were identified for the following parameters: T1-weighted images “45dgr_RLNonUni (p = 0.50, P = 0.006), T2-weighted images “S (4,0)SumAverg” (p = −0.45, P = 0.02). A ROC analysis was performed for Ki67-index with a threshold of 10%. The highest area under the curve (AUC) was found for the parameter “T1_WavEnHL_s-7” with an AUC of 0.90. For the threshold of Ki67 = 20% the highest AUC was identified for the parameter „T2_S (1,1)Entropy” with an AUC of 0.77. Several texture features derived from T1-and T2-weighted images correlated with proliferation index Ki67 and might be used as valuable novel biomarkers in soft tissue sarcomas." @default.
• W2951784311 created "2019-06-27" @default.
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• W2951784311 date "2019-09-01" @default.
• W2951784311 modified "2023-10-14" @default.
• W2951784311 title "Texture analysis parameters derived from T1-and T2-weighted magnetic resonance images can reflect Ki67 index in soft tissue sarcoma" @default.
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• W2951784311 doi "https://doi.org/10.1016/j.suronc.2019.06.006" @default.
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