Differentiation of Hepatocellular Carcinoma from Hepatic Hemangioma and Focal Nodular Hyperplasia using Computed Tomographic Spectral Imaging

Background and Aims:Hepatocellular carcinoma(HCC)is the most common primary hepatic malignancy.This study was designed to investigate the value of computed tomography(CT)spectral imaging in differentiating HCC from hepatic hemangioma(HH)and focal nodular hyperplasia(FNH).Methods:This was a retrospective study of 51 patients who underwent spectral multiple-phase CT at 40–140 keV during the arterial phase(AP)and portal venous phase(PP).Slopes of the spectral curves,iodine density,water density derived from iodine-and water-based material decomposition images,iodine uptake ratio(IUR),normalized iodine concentration,and the ratio of iodine concentration in liver lesions between AP and PP were measured or calculated.Results:As energy level decreased,the CT values of HCC(n=31),HH(n=17),and FNH(n=7)increased in both AP and PP.There were significant differences in IUR in the AP,IUR in the PP,normalized iodine concentration in the AP,slope in the AP,and slope in the PP among HCC,HH,and FNH.The CT values in AP,IUR in the AP and PP,normalized iodine concentration in the AP,slope in the AP and PP had high sensitivity and specificity in differentiating HH and HCC from FNH.Quantitative CT spectral data had higher sensitivity and specificity than conventional qualitative CT image analysis during the combined phases.Conclusions:Mean CT values at low energy(40–90 keV)and quantitative analysis of CT spectral data(IUR in the AP)could be helpful in the differentiation of HCC,HH,and FNH.

Robust image-based coordinated control for spacecraft formation flying

This paper addresses a coordinated control problem for Spacecraft Formation Flying(SFF). The distributed followers are required to track and synchronize with the leader spacecraft.By using the feature points in the two-dimensional image space, an integrated 6-degree-of-freedom dynamic model is formulated for spacecraft relative motion. Without sophisticated threedimensional reconstruction, image features are directly utilized for the controller design. The proposed image-based controller can drive the follower spacecraft in the desired configuration with respect to the leader when the real-time captured images match their reference counterparts. To improve the precision of the formation configuration, the proposed controller employs a coordinated term to reduce the relative distance errors between followers. The uncertainties in the system dynamics are handled by integrating the adaptive technique into the controller, which increases the robustness of the SFF system. The closed-loop system stability is analyzed using the Lyapunov method and algebraic graph theory. A numerical simulation for a given SFF scenario is performed to evaluate the performance of the controller.

Distributed adaptive prescribed-time orbit containment control for satellite cluster flight

The distributed prescribed-time orbit containment control for the satellite cluster flight with multiple dynamic leaders is investigated.The directed information communication topology between followers is taken into account in the overall paper.When the satellite mass is assumed to be constant,a distributed prescribed-time orbit containment controller is,firstly,presented to drive the followers into the dynamic convex hull produced by multiple leaders.Then,the parameter uncertainty is considered,and a prescribed-time sliding mode estimator is introduced to estimate the desired velocity of each follower.Based on the estimated state,a novel distributed adaptive prescribed-time orbit containment control scheme is proposed.The Lyapunov stability theory is utilized to prove the prescribed-time stability of the closed-loop system.Finally,several numerical simulations and comparison of different control methods are provided to verify the effectiveness and superiority of the proposed control method.