Texture analysis of multiparametric MRI: interobserver variability of texture features and associations with nodal status.

Texture analysis of pre-treatment multiparametric MRI (mpMRI) consisting of diffusion-weighted MRI (DWI) and T2-weighted (T2W) texture features could be a promising and reproducible quantitative approach in assessing tumor heterogeneity in cervical cancer. We retrospectively studied forty treatment-naïve patients who had mpMRI examinations. We observed that around 30% of texture features had low interobserver variability, and that most of these features were from the Gray-Level Co-occurrence Matrix (GLCM) and Gray-Level Run Length Matrix (GLRLM). Furthermore, T2W features had moderate associations with pelvic lymph node (PLN) status.