Background: Accurate characterization of small (3 cm) hepatocellular carcinoma (sHCC) and dysplastic nodules (DNs) in cirrhotic liver is challenging. We aimed to investigate whether texture analysis (TA) based on T2-weighted images (T2WI) is superior to qualitative diagnosis using gadoxetic acid-enhanced MR imaging (Gd-EOB-MRI) and diffusion-weighted imaging (DWI) for distinguishing sHCC from DNs in cirrhosis. Materials and methods: Sixty-eight patients with 73 liver nodules (46 HCCs, 27 DNs) pathologically confirmed by operation were included. For imaging diagnosis, three sets of images were reviewed by two experienced radiologists in consensus: a Gd-EOB-MRI set, a DWI set, and a combined set (combination of Gd-EOB-MRI and DWI). For TA, 279 texture features resulting from T2WI were extracted for each lesion. The performance of each approach was evaluated by a receiver operating characteristic analysis. The area under the receiver operating characteristic curve (A z), sensitivity, specificity, and accuracy were determined. Results: The performance of TA (A z = 0.96) was significantly higher than that of imaging diagnosis using Gd-EOB-MRI set (A z = 0.86) or DWI set (A z = 0.80) alone in differentiation of sHCC from DNs (P = 0.008 and 0.025, respectively). The combination of Gd-EOB-MRI and DWI showed a greater sensitivity (95.6%) but reduced specificity (66.7%). The specificity of TA (92.6%) was significantly higher than that of the combined set (P < 0.001), but no significant difference was observed in sensitivity (97.8 vs. 95.6%, P = 0.559). Zhong et al. Differentiation of Small HCC From DNs Conclusion: TA-based T2WI showed a better classification performance than that of qualitative diagnosis using Gd-EOB-MRI and DW imaging in differentiation of sHCCs from DNs in cirrhotic liver. TA-based MRI may become a potential imaging biomarker for the early differentiation HCCs from DNs in cirrhosis.

Sheet flow featured with shallow depth on vegetated slopes plays a key role on the dynamics of soil and water loss, yet the hydrodynamic characteristics of sheet flow pasting a vegetation stem simplified by an emergent cylinder have not been revealed. Laboratory flume experiments were conducted to investigate potential effects of a vegetation stem on velocity components, flow vortexes, and shear stress from time-averaged and time-resolved perspectives. Flow fields on the upstream flow of the cylinder at the symmetry plane were captured by using a high precision Particle Image Velocimetry (PIV, 63 pixel/mm) system. Four flow conditions with flow depths from 0.4 to 0.57 cm and cylinder Reynolds number from 2440 to 3806 were selected to fully evaluate the sheet flow condition. Time-averaged hydrodynamic features were analyzed in terms of streamlines, streamwise velocity, wall-normal velocity, and vorticity. Time-resolved features of two velocity components were then analyzed. Joint probability density functions of the two velocity components exhibited asymmetrical bimodal, indicating two preferred flow states occurred frequently, namely, backflow event and downflow event. Subsequently, analyses by linear stochastic estimation showed that the backflow event was induced by a reverse upstream flow starting from the leading edge of the cylinder and penetrating primary horseshoe vortex, which was motivated by the intermediate-flow mode proposed in previous open channel flow. Meanwhile, the downflow event was induced by a portion of fluid that was unable to penetrate the primary horseshoe vortex and then vertically impinged the flume bed, which was motivated by the downflow mode proposed in this study. As the critical hydrodynamic parameter for local scouring, shear stress was finally sketched. It was suggested that soil control measures should be implemented around the vegetation stem with a radius of 0.1D (D is the cylinder diameter), where the maximum shear stress mostly occurs. The newly defined flow mode could provide deeper insights into the mechanisms of sheet flow and promote the practice of soil erosion control on vegetated hillslopes.