Wormald BW, et al. - In view of the information that prognostic information beyond volume is potentially offered by textural features derived from MRI, to influence the surgical treatment of cervical cancer, researchers investigated textural features that vary between cervical tumors above and below the volume threshold of eligibility for trachelectomy. Whether these hold value in predicting recurrence in patients with low-volume tumors was also investigated. They compared textural features, depended on grey-level co-occurrence matrices, between tumors greater (n = 46) or less (n = 79) than 4.19 cm³. Indicators of predicting recurrence in low-volume tumors were Dissimilarity, Energy [ADC (apparent diffusion co-efficient)-radiomics, AUC = 0.864); Dissimilarity, ClusterProminence, InverseVariance (T2-W-radiomics, AUC = 0.808); Volume, Depth of Invasion, LymphoVascular Space Invasion (clinico-pathological features, AUC = 0.794). Between high- and low-volume tumors, a difference was evident in textural features (Dissimilarity, Energy, ClusterProminence, ClusterShade, InverseVariance, Autocorrelation) from ADC maps and T2-W images, and recurrence in low-volume tumors could potentially be predicted by textural features.