Background: Accurate measurement and reconstruction of orbital soft tissue is important to diagnosis and treatment of orbital diseases. This study applied an interactive graph cut method to orbital soft tissue precise segmentation and calculation in computerized tomography (CT) images, and to estimate its application in orbital reconstruction. Methods: The interactive graph cut method was introduced to segment extraocular muscle and intraorbital fat in CT images. Intra-and inter-observer variability of tissue volume measured by graph cut segmentation was validated. Accuracy and reliability of the method was accessed by comparing with manual delineation and commercial medical image software. Intraorbital structure of 10 patients after enucleation surgery was reconstructed based on graph cut segmentation and soft tissue volume were compared within two different surgical techniques. Results: Both muscle and fat tissue segmentation results of graph cut method showed good consistency with ground truth in phantom data. There were no significant differences in muscle calculations between observers or segmental methods (p > 0.05). Graph cut results of fat tissue had coincidental variable trend with ground truth which could identify 0.1cm 3 variation. The mean performance time of graph cut segmentation was significantly shorter than manual delineation and commercial software (p < 0.001). Jaccard similarity and Dice coefficient of graph cut method were 0.767 ± 0.045 and 0.836 ± 0.032 for human normal extraocular muscle segmentation. The measurements of fat tissue were significantly better in graph cut than those in commercial software (p < 0.05). Orbital soft tissue volume was decreased in post-enucleation orbit than that in normal orbit (p < 0.05). Conclusion: The graph cut method was validated to have good accuracy, reliability and efficiency in orbit soft tissue segmentation. It could discern minor volume changes of soft tissue. The interactive segmenting technique would be a valuable tool for dynamic analysis and prediction of therapeutic effect and orbital reconstruction.

Most real-world systems evolve over time in which entities and the interactions between entities are added and removed---new entities or relationships appear and old entities or relationships vanish. While most network evolutionary models can provide an iterative process for constructing global properties, they cannot capture the evolutionary mechanisms of real systems. Link prediction is hence proposed to predict future links which also can help us understand the evolution law of real systems. The aim of link prediction is to uncover missing links from known parts of the network or quantify the likelihood of the emergence of future links from current structures of the network. However, almost all existing studies ignored that old nodes tend to disappear and new nodes appear over time in real networks, especially in social networks. It is more challenging for link prediction since the new nodes do not have pre-existing structure information. To solve the temporal link prediction problems with new nodes, here we take into account nodal Attribute Similarity and the Shortest Path Length, namely, $ASSPL$, to predict future links with new nodes. The results tested on scholar social network and academic funding networks show that it is highly effective and applicable for $ASSPL$ in funding networks with time-evolving. Meanwhile, we make full use of an efficient parameter to exploit how network structure or nodal attribute has an impact on the performance of temporal link prediction. Finally, we find that nodal attributes and network structure complement each other well for predicting future links with new nodes in funding networks.

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ObjectiveThe research objective was to evaluate the predicting role of the vascular endothelial growth factor to CBP/P300-interacting transactivator with Glu/Asp-rich C-terminal domain 2 Ratio (VEGF/CITED2) from peripheral blood mononuclear cells (PBMCs) in the collateral circulation of acute ischemic stroke (AIS).MethodsIn an observational study of patients with AIS, the western blot was applied to test the protein expression of VEGF and CITED2. Then, we calculated the VEGF/CITED2 and collected other clinical data. Binary logistic regression analysis between collateral circulation and clinical data was performed. Finally, receiver operating characteristic (ROC) curve analysis was used to explore the predictive value of VEGF/CITED2.ResultsA total of 67 patients with AIS were included in the study. Binary logistic regression analysis indicated the VEGF/CITED2 (OR 165.79, 95%CI 7.25–3,791.54, P = 0.001) was an independent protective factor. The ROC analyses showed an area under the ROC curve of the VEGF/CITED2 was 0.861 (95%CI 0.761–0.961). The optimal cutoff value of 1.013 for VEGF/CITED2 had a sensitivity of 89.1% and a specificity of 85.7%.ConclusionIn patients with AIS, the VEGF/CITED2 was related to the establishment of collateral circulation. The VEGF/CITED2 is a potentially valuable biomarker for predicting collateral circulation.Clinical trial registrationClinicalTrials.gov, identifier: NCT05345366.