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Highlights: ► Twelve entropy indices were systematically compared in monitoring depth of anesthesia and detecting burst suppression.► Renyi permutation entropy performed best in tracking EEG changes associated with different anesthesia states.► Approximate Entropy and Sample Entropy performed best in detecting burst suppression.Objective: Entropy algorithms have been widely used in analyzing EEG signals during anesthesia. However, a systematic comparison of these entropy algorithms in assessing anesthesia drugs' effect is lacking. In this study, we compare the capability of 12 entropy indices for monitoring depth of anesthesia (DoA) and detecting the burst suppression pattern (BSP), in anesthesia induced by GABAergic agents.Methods: Twelve indices were investigated, namely Response Entropy (RE) and State entropy (SE), three wavelet entropy (WE) measures [Shannon WE (SWE), Tsallis WE (TWE), and Renyi WE (RWE)], Hilbert-Huang spectral entropy (HHSE), approximate entropy (ApEn), sample entropy (SampEn), Fuzzy entropy, and three permutation entropy (PE) measures [Shannon PE (SPE), Tsallis PE (TPE) and Renyi PE (RPE)]. Two EEG data sets from sevoflurane-induced and isoflurane-induced anesthesia respectively were selected to assess the capability of each entropy index in DoA monitoring and BSP detection. To validate the effectiveness of these entropy algorithms, pharmacokinetic/pharmacodynamic (PK/PD) modeling and prediction probability (Pk) analysis were applied. The multifractal detrended fluctuation analysis (MDFA) as a non-entropy measure was compared.Results: All the entropy and MDFA indices could track the changes in EEG pattern during different anesthesia states. Three PE measures outperformed the other entropy indices, with less baseline variability, higher coefficient of determination (R2) and prediction probability, and RPE performed best; ApEn and SampEn discriminated BSP best. Additionally, these entropy measures showed an advantage in computation efficiency compared with MDFA.Conclusion: Each entropy index has its advantages and disadvantages in estimating DoA. Overall, it is suggested that the RPE index was a superior measure. Investigating the advantages and disadvantages of these entropy indices could help improve current clinical indices for monitoring DoA.

Achieving rapid and effective hemostasis on irregularly shaped, non‐compressible visceral, and high‐pressure arterial bleeding wounds remains a critical clinical challenge. Herein, an ultrafast self‐gelling and wet adhesive polyethyleneimine/polyacrylic acid/quaternized chitosan (PEI/PAA/QCS) powder is reported as the hemostatic material and wound dressing. PEI/PAA/QCS powder deposited on bleeding wounds can rapidly absorb a large amount of blood to concentrate coagulation factors. Meanwhile, the powder can form an adhesive hydrogel in situ within 4 s upon hydration to form a pressure‐resistant physical barrier. Furthermore, PEI/PAA/QCS hydrogels can aggregate blood cells and platelets to enhance hemostasis. Depositing PEI/PAA/QCS powder on various bleeding wounds, including at the liver and heart, high‐pressure femoral artery and tail vein of rats, arrests the bleeding around 10 s with no rebleeding after ten minutes. Excellent hemostasis of PEI/PAA/QCS powder is further demonstrated against massive hemorrhage in porcine spleen and liver in vivo, which are non‐compressible organs with abundant blood supply. In addition, the powder can be used as a wound dressing to promote the healing of the full‐thickness skin wounds. The advantages of PEI/PAA/QCS powder including rapid and effective hemostasis, effective wound healing, easy usage, low cost, and adaptability to fit complex target sites make it a promising biomaterial for surgical applications.

Electroencephalogram (EEG) monitoring of the effect of anesthetic drugs on the central nervous system has long been used in anesthesia research. Several methods based on nonlinear dynamics, such as permutation entropy (PE), have been proposed to analyze EEG series during anesthesia. However, these measures are still single-scale based and may not completely describe the dynamical characteristics of complex EEG series. In this paper, a novel measure combining multiscale PE information, called CMSPE (composite multi-scale permutation entropy), was proposed for quantifying the anesthetic drug effect on EEG recordings during sevoflurane anesthesia. Three sets of simulated EEG series during awake, light and deep anesthesia were used to select the parameters for the multiscale PE analysis: embedding dimension m, lag tau and scales to be integrated into the CMSPE index. Then, the CMSPE index and raw single-scale PE index were applied to EEG recordings from 18 patients who received sevoflurane anesthesia. Pharmacokinetic/pharmacodynamic (PKPD) modeling was used to relate the measured EEG indices and the anesthetic drug concentration. Prediction probability (P(k)) statistics and correlation analysis with the response entropy (RE) index, derived from the spectral entropy (M-entropy module; GE Healthcare, Helsinki, Finland), were investigated to evaluate the effectiveness of the new proposed measure. It was found that raw single-scale PE was blind to subtle transitions between light and deep anesthesia, while the CMSPE index tracked these changes accurately. Around the time of loss of consciousness, CMSPE responded significantly more rapidly than the raw PE, with the absolute slopes of linearly fitted response versus time plots of 0.12 (0.09-0.15) and 0.10 (0.06-0.13), respectively. The prediction probability P(k) of 0.86 (0.85-0.88) and 0.85 (0.80-0.86) for CMSPE and raw PE indicated that the CMSPE index correlated well with the underlying anesthetic effect. The correlation coefficient for the comparison between the CMSPE index and RE index of 0.84 (0.80-0.88) was significantly higher than the raw PE index of 0.75 (0.66-0.84). The results show that the CMSPE outperforms the raw single-scale PE in reflecting the sevoflurane drug effect on the central nervous system.

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OBJECTIVE Nearly 25% of solid renal tumors are indolent cancer or benign and can be managed conservatively in selected patients. This prospective study was performed to determine whether preoperative IV microbubble contrast-enhanced ultrasound can be used to differentiate indolent and benign renal tumors from more aggressive clear cell carcinoma. SUBJECTS AND METHODS Thirty-four patients with renal tumors underwent preoperative gray-scale, color, power Doppler, and octafluoropropane microbubble IV contrast-enhanced ultrasound. Three blinded radiologists reading in consensus compared rate of contrast wash-in, grade and pattern of enhancement, and contrast washout compared with adjacent parenchyma. Contrast ultrasound findings were compared with surgical histopathologic findings for all patients. RESULTS The 34 patients had 23 clear cell carcinomas, three type 1 papillary carcinomas, one chromophobe carcinoma, one clear rare multilocular low-grade malignant tumor, two unclassified lesions, three oncocytomas, and one benign angiomyolipoma. The combination of heterogeneous lesion echotexture and delayed lesion washout had 85% positive predictive value, 43% negative predictive value, 48% sensitivity, and 82% specificity for predicting whether a lesion was conventional clear cell carcinoma or another tumor. Diminished lesion enhancement grade had 75% positive predictive value, 81% negative predictive value, 55% sensitivity, and 91% specificity for non–clear cell histologic features, either benign or low-grade malignant. Combining delayed washout with quantitative lesion peak intensity of at least 20% of kidney peak intensity had 91% positive predictive value, 40% negative predictive value, 63% sensitivity, and 80% specificity in the prediction of clear cell histologic features. CONCLUSION Ultrasound features of gray-scale heterogeneity, lesion washout, grade of contrast enhancement, and quantitative measure of peak intensity may be useful for differentiating clear cell carcinoma and non–clear cell renal tumors.

Our study illustrates a method to evaluate the standard of practice for thyroid nodule assessment among radiologists within an ultrasound group. Application of a 5-point malignancy rating scale to select nodules for biopsy is feasible and shows good diagnostic accuracy.