Texture analysis parameters derived from T1-and T2-weighted magnetic resonance images can reflect Ki67 index in soft tissue sarcoma

Background and objectives: 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. Methods: 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. Results: 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. Conclusion: 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.