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• Honokiol suffer from low aqueous solubility and low overall bioavailability. • Cyclodextrin inclusion techniques are strong tools to solve the solubility issues. • >The HK-HP-β-CD has excellent solubility, dissolution rate and oral bioavailability. • The HK-HP-β-CD exhibited higher antitumor activity against HepG2 than free HK. Honokiol (HK), an active compound derived from Magnolia officinalis Rehd. et Wils , possesses many beneficial biological activities for human beings. However, its poor solubility and low bioavailability severely limits its application. In this way, to improve the pharmaceutical properties, the HK was complexed in hydroxypropyl-β-cyclodextrin (HP-β-CD) and its oral bioavailability and antitumor effects were evaluated. The HK/HP-β-CD inclusion complex (1:1) was prepared by saturated aqueous solution method. The inclusion complex (HK-HP-β-CD) obtained had a higher solubility, about 1497 times that of the free HK. The dissolution rate and the oral bioavailability of HK was also significantly higher from inclusion complex than from free HK. Furthermore, the HK-HP-β-CD exhibited higher antitumor activity against Human Hepatoma Cell Line (HepG2) than free HK. More cells were arrested in the sub-G1 phase of the cell cycle and were induced to undergo late apoptosis when treated with the HK-HP-β-CD than when treated with free HK. [ABSTRACT FROM AUTHOR]

• A new ANN-based parameter estimation method of the HK distribution was proposed. • The ANN estimator took advantages of ANNs in learning and function approximation. • It had an overall better NSD and was almost one order of magnitude faster. • It yielded comparable diagnostic performance in the assessment of hepatic steatosis. • It has great potential in ultrasound tissue characterization based on HK distribution. The homodyned K (HK) distribution allows a general description of ultrasound backscatter envelope statistics with specific physical meanings. In this study, we proposed a new artificial neural network (ANN) based parameter estimation method of the HK distribution. The proposed ANN estimator took advantages of ANNs in learning and function approximation and inherited the strengths of conventional estimators through extracting five feature parameters from backscatter envelope signals as the input of the ANN: the signal-to-noise ratio (SNR), skewness, kurtosis, as well as X- and U- statistics. Computer simulations and clinical data of hepatic steatosis were used for validations of the proposed ANN estimator. The ANN estimator was compared with the RSK (the level-curve method that uses SNR, skewness, and kurtosis based on the fractional moments of the envelope) and XU (the estimation method based on X- and U- statistics) estimators. Computer simulation results showed that the relative bias was best for the XU estimator, whilst the normalized standard deviation was overall best for the ANN estimator. The ANN estimator was almost one order of magnitude faster than the RSK and XU estimators. The ANN estimator also yielded comparable diagnostic performance to state-of-the-art HK estimators in the assessment of hepatic steatosis. The proposed ANN estimator has great potential in ultrasound tissue characterization based on the HK distribution. [ABSTRACT FROM AUTHOR]

• We proposed ultrasound HK imaging with NCA for monitoring microwave ablation (MWA). • NCA HK imaging was comparable to NCA Nakagami and CED imaging for monitoring MWA. • NCA HK imaging may be used as a new method for monitoring MWA. In this paper, we proposed ultrasound homodyned K (HK) imaging based on the noise-assisted correlation algorithm (NCA) for monitoring microwave ablation of porcine liver ex vivo. The NCA-based HK (α NCA and k NCA) imaging was compared with NCA-based Nakagami (m NCA) imaging and NCA-based cumulative echo decorrelation (CED NCA) imaging. Backscattered ultrasound radiofrequency signals of porcine liver ex vivo during and after the heating of microwave ablation were collected (n = 15), which were processed for constructing B-mode imaging, NCA-based HK imaging, NCA-based Nakagami imaging, and NCA-based CED imaging. To quantitatively evaluate the final coagulation zone, the polynomial approximation (PAX) technique was applied. The accuracy of detecting coagulation area with α NCA , k NCA , m NCA , and CED NCA parametric imaging was evaluated by comparing the PAX imaging with the gross pathology. The receiver operating characteristic (ROC) curve was used to further evaluate the performance of the three quantitative ultrasound imaging methods for detecting the coagulation zone. Experimental results showed that the average accuracies of α NCA , k NCA , m NCA , and CED NCA parametric imaging combined with PAX imaging were 89.6%, 83.25%, 89.23%, and 91.6%, respectively. The average areas under the ROC curve (AUROCs) of α NCA , k NCA , m NCA , and CED NCA parametric imaging were 0.83, 0.77, 0.83, and 0.86, respectively. The proposed NCA-based HK imaging may be used as a new method for monitoring microwave ablation. [ABSTRACT FROM AUTHOR]

• We explored the feasibility of using GPD-based ultrasound Nakagami imaging to detect microwave ablation coagulation areas. • GPD algorithm was compared with MBE and WMC algorithms for parameter estimation accuracy, smoothness, resolution and CNR. • Nakagami m GPD , m MBE , and m WMC parametric imaging was compared with HK α and k parametric imaging for monitoring MWA. • GPD-based Nakagami imaging may have the potential to detect microwave ablation coagulation areas. In this paper, we explored the feasibility of using ultrasound Nakagami- m parametric imaging based on Gaussian pyramid decomposition (GPD) to detect microwave ablation coagulation areas. Monte Carlo simulation and phantom simulation results demonstrated that a 2-layer GPD model was sufficient to achieve the same m parameter estimation accuracy, smoothness and resolution as 3-layer and 4-layer. The performances of GPD, moment-based estimator (MBE) and window-modulated compounding (WMC) algorithms were compared in terms of parameter estimation, smoothness, resolution and contrast-to-noise (CNR). Results showed that the m parameter estimation obtained by GPD algorithm was better than that of MBE and WMC algorithms except the small window size (27 × 5). When using a window size of >3 pulse lengths, GPD algorithm could achieve better smoothness and CNR than MBE and WMC algorithms, but there was a certain loss of axial resolution. The computation time of GPD algorithm was less than that of WMC algorithm, while about 2.24 times that of MBE algorithm. Experimental results of porcine liver microwave ablation ex vivo (n = 20) illustrated that the average areas under the operating characteristic curve (AUCs) of Nakagami m GPD , m MBE and m WMC parametric imaging and homodyned-K (HK) α and k parametric imaging to detect coagulation areas were significantly improved by polynomial approximation (PAX). Kruskal-Wallis test showed that the accuracy of coagulation area detection obtained by PAX imaging of m GPD parameter had no significant difference with that of m MBE , m WMC , HK_ α and HK_ k parameters. This preliminary study suggested that Nakagami imaging based on GPD algorithm may have the potential to detect microwave ablation coagulation areas. [ABSTRACT FROM AUTHOR]