Aims: Ultrasonography is the preferred technique to evaluate the status of maternal and fetal health during pregnancy. Non-obstetric acute or chronic conditions occurring during pregnancy must be diagnosed as early as possible to permit timely and necessary treatment for the sake of maternal and fetal health. The purpose of this study was to evaluate the safety and value of contrast-enhanced ultrasonography (CEUS) during pregnancy.Materials and methods: This prospective study included 14 pregnant women requiring pregnancy termination and six healthy pregnant women. The 14 pregnant women requiring pregnancy termination underwent CEUS prior to surgery to investigate the pattern of contrast agent diffusion. The six healthy pregnant women did not undergo CEUS. The structure of placentae with and without contrast agent injection were also compared by light microscopy.Results: CEUS analysis failed to identify any signs of contrast agents in the umbilical cord blood and fetus. There were no obvious changes in the morphology of placentae with and without contrast agent injection under light microscope. CEUS identified the need for early treatment in one pregnant woman with an ovarian tumor.Conclusions: Due to the protective effect of the placental barrier on the fetus, CEUS during pregnancy may represent a safe form of imaging technology that can provide valuable information for the diagnosis of non-obstetric acute or chronic disorders and to guide thefuture treatment of pregnant women.
This paper introduces a simulated annealing algorithm for solving the linear constrained optimization problems. The performance of this algorithm is demonstrated with Rosenbrock function global optimal problem. Then the design of cooling schedule and the influence of various controlling parameters are discussed. From the results, it is evident that the quality of the obtained optimal solution is closely related to the iterative times. There are three parameters related to the iterative times, and the most important influence parameter is markov chain.
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