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Objective To explore the association of renal surface nodularity (RSN) with the increased adverse vascular event (AVE) risk in patients with arterial hypertension. Methods This cross-sectional study included patients with arterial hypertension aged 18–60 years who underwent contrasted computed tomography (CT) of kidney from January 2012 to December 2020. The subjects were classified into AVE or not (non-AVE) matched with age (≤5 years) and sex. Their CT images were analyzed using both qualitative (semiRSN) and quantitative RSN (qRSN) methods, respectively. Their clinical characteristics included age, sex, systolic blood pressure (SBP), diastolic blood pressure, hypertension course, diabetes history, hyperlipidemia, and estimated glomerular filtration rate (eGFR). Results Compared with non-AVE group (n = 91), AVE (n = 91) was at lower age, higher SBP, and fewer rate of diabetes and hyperlipidemia history (all P

Background. This study sought to explore the association between quantitative classification of renal surface nodularity (qRSN) based on computed tomography (CT) imaging and early renal injury (ERI) in patients with arterial hypertension. Methods. A total of 143 patients with a history of hypertension were retrospectively enrolled; clinical information (age, sex, hypertension grade, and hypertension course), laboratory tests, and qRSN were collected or assessed. The subjects were divided into an ERI group (n = 60) or a control group (CP, n = 83) according to ERI diagnosis based on the following criteria: cystatin C > 1.02 mg/L. Univariate analysis and multiple logistic regression were used to assess the association between ERI and qRSN. A receiver operating characteristic curve (ROC) was performed to compare multiple logistic regression models with or without qRSN for differentiating the ERI group from the control group. Results. In univariate analysis, hypertension grade, hypertension course, triglycerides (TG), and qRSN were related to ERI in patients with arterial hypertension (all P

PURPOSE:To investigate the profile and determinants of retinal optical intensity in normal subjects using 3D spectral domain optical coherence tomography (SD OCT). METHODS:A total of 231 eyes from 231 healthy subjects ranging in age from 18 to 80 years were included and underwent a 3D OCT scan. Forty-four eyes were randomly chosen to be scanned by two operators for reproducibility analysis. Distribution of optical intensity of each layer and regions specified by the Early Treatment of Diabetic Retinopathy Study (ETDRS) were investigated by analyzing the OCT raw data with our automatic graph-based algorithm. Univariate and multivariate analyses were performed between retinal optical intensity and sex, age, height, weight, spherical equivalent (SE), axial length, image quality, disc area and rim/disc area ratio (R/D area ratio). RESULTS:For optical intensity measurements, the intraclass correlation coefficient of each layer ranged from 0.815 to 0.941, indicating good reproducibility. Optical intensity was lowest in the central area of retinal nerve fiber layer, ganglion cell layer, inner plexiform layer, inner nuclear layer, outer plexiform layer and photoreceptor layer, except for the retinal pigment epithelium (RPE). Optical intensity was positively correlated with image quality in all retinal layers (0.5530.05). There was no relationship between retinal optical intensity and sex, height, weight, SE, axial length, disc area and R/D area ratio. CONCLUSIONS:There was a specific pattern of distribution of retinal optical intensity in different regions. The optical intensity was affected by image quality and age. Image quality can be used as a reference for normalization. The effect of age needs to be taken into consideration when using OCT for diagnosis.

To assess the correlation and agreement between the Topcon built-in algorithm and our graph-based algorithm in measuring the total and regional macular thickness for normal and glaucoma subjects.A total of 228 normal eyes and 93 glaucomatous eyes were enrolled in our study. All patients underwent comprehensive ophthalmic examination and Topcon 3D-OCT 2000 scan. One eye was randomly selected for each subject. The thickness of each layer and the total and regional macular thickness on an Early Treatment of Diabetic Retinopathy Study (ETDRS) chart were measured using the Topcon algorithm and our three-dimensional graph-based algorithm. Correlation and agreement analyses between these two algorithms were performed.Our graph search algorithm exhibited a strong correlation with Topcon algorithm. The macular GCC thickness values for normal and glaucoma subjects ranged from 0.86 to 0.91 and from 0.78 to 0.90, and the regional macular thickness values ranged from 0.79 to 0.96 and 0.70 to 0.95, respectively. Small differences were observed between the Topcon algorithm and our graph-based algorithm. The span of 95% limits of agreement of macular GCC thickness was less than 28 μm in both normal and glaucoma subjects, respectively. These limits of total and regional macular thickness were 15.5 μm and 23.1 μm for normal subjects and 29.1 μm and 46.4 μm for glaucoma subjects, respectively.Our graph-based algorithm exhibited a high degree of agreement with the Topcon algorithm with respect to thickness measurements in normal and glaucoma subjects. Moreover, our graph-based algorithm can segment the retina into more layers than the Topcon algorithm does.

Empirical mode decomposition (EMD) is an adaptive method for nonlinear, non-stationary signal analysis. However, the upper and lower envelopes fitted by cubic spline interpolation (CSI) may often occur overshoots. In this paper, a new envelope fitting method based on the flattest constrained interpolation is proposed. The proposed method effectively integrates the difference between extremes into the cost function, and applies a chaos particle swarm optimization method to optimize the derivatives of the interpolation nodes. The proposed method was tested on three different types of data: ascertain signal, random signals and real electrocardiogram signals. The experimental results show that: (1) The proposed flattest envelope effectively solves the overshoots caused by CSI method and the artificial bends caused by piecewise parabola interpolation (PPI) method. (2) The index of orthogonality of the intrinsic mode functions (IMFs) based on the proposed method is 0.04054, 0.02222 ± 0.01468 and 0.04013 ± 0.03953 for the ascertain signal, random signals and electrocardiogram signals, respectively, which is lower than the CSI method and the PPI method, and means the IMFs are more orthogonal. (3) The index of energy conversation of the IMFs based on the proposed method is 0.96193, 0.93501 ± 0.03290 and 0.93041 ± 0.00429 for the ascertain signal, random signals and electrocardiogram signals, respectively, which is closer to 1 than the other two methods and indicates the total energy deviation amongst the components is smaller. (4) The comparisons of the Hilbert spectrums show that the proposed method overcomes the mode mixing problems very well, and make the instantaneous frequency more physically meaningful.