To enhance the accuracy of computer-aided diagnosis of adolescent depression based on electroencephalogram signals, this study collected signals of 32 female adolescents (16 depressed and 16 healthy, age: 16.3 ± 1.3) with eyes colsed for 4 min in a resting state. First, based on the phase synchronization between the signals, the phase-locked value (PLV) method was used to calculate brain functional connectivity in the θ and α frequency bands, respectively. Then based on the graph theory method, the network parameters, such as strength of the weighted network, average characteristic path length, and average clustering coefficient, were calculated separately (P < 0.05). Next, using the relationship between multiple thresholds and network parameters, the area under the curve (AUC) of each network parameter was extracted as new features (P < 0.05). Finally, support vector machine (SVM) was used to classify the two groups with the network parameters and their AUC as features. The study results show that with strength, average characteristic path length, and average clustering coefficient as features, the classification accuracy in the θ band is increased from 69% to 71%, 66% to 77%, and 50% to 68%, respectively. In the α band, the accuracy is increased from 72% to 79%, 69% to 82%, and 65% to 75%, respectively. And from overall view, when AUC of network parameters was used as a feature in the α band, the classification accuracy is improved compared to the network parameter feature. In the θ band, only the AUC of average clustering coefficient was applied to classification, and the accuracy is improved by 17.6%. The study proved that based on graph theory, the method of feature optimization of brain function network could provide some theoretical support for the computer-aided diagnosis of adolescent depression.
ObjectiveTo observe the safety and effectiveness of targeted navigation laser with continuous wave threshold power in the treatment of chronic central serous chorioretinopathy (CCSC).MethodsA retrospective clinical study. From November 2018 to June 2020, 28 eyes of 28 patients with CCSC diagnosed in the Eye Hospital of Nanjing Medical University were included in the study. Among them, there were 17 males with 17 eyes and 11 females with 11 eyes; all of them had a monocular disease. The average age of the patients was 36.24±5.14 years, and the average course of the diseases was 4.7±1.3 months. All affected eyes underwent best corrected visual acuity (BCVA), fluorescein fundus angiography, fundus autofluorescence, frequency domain optical coherence tomography and angiography, multifocal electroretinogram (mf-ERG) and micro field inspection. BCVA was carried out using the international standard visual acuity chart, which was converted into the logarithmic minimum angle of resolution (logMAR) visual acuity during statistics. A targeted navigation laser system was used for continuous wave power therapy under the threshold. Two weeks and 1, 3 months after treatment, the same equipment and methods as before treatment were used to perform related examinations to observe the BCVA, subfoveal choroidal thickness (SFCT), foveal retinal thickness (CMT), the mean light sensitivity (MS) in the 10° range of the macular center, and the amplitude density of P1 wave at ring 1 and 2. The t test was used to compare CMT, SFCT, retinal amplitude density and MS before and after treatment.ResultsBefore treatment and 2 weeks, 1 and 3 months after treatment, the average logMAR BCVA of the eyes were 0.74±0.16, 0.57±0.16, 0.22±0.05, 0.21±0.06, and the average CMT was 512.33±31.56, 350.40±36.61, 256.49±22.38, 253.45±23.65 μm respectively, the average SFCT was 462.82±25.38, 462.37±39.54, 461.51±29.36, 461.25±34.55 μm, the average MS was 16.32±5.41, 17.53±4.23, 19.52±4.12, 21.35±2.77 dB respectively. At different times before and after treatment, BCVA (t=6.52, 5.71, 6.01; P=0.00, 0.00, 0.00), CMT (t=3.08, 6.57, 4.90; P=0.01, 0.00, 0.00), SFCT (t=7.01, 6.54, 4.85; P=0.08, 0.07, 0.17), MS (t=6.17, 4.25, 5.46; P=0.02, 0.00, 0.00), the difference was statistically significant. The amplitude density of P1 wave at ring 1 in the affected eye was 64.37±18.25, 85.31±13.98, 98.35±14.52, 98.40±22.17 nV/deg2, and the amplitude density of P1 wave at ring2 was 36.12±18.32, 44.02±17.15, 62.35±14.85, 63.17±15.79 nV/deg2. The amplitude density of P1 wave at ring 1 (t=5.11, 9.03, 4.27; P=0.03, 0.00, 0.00) and ring 2 (t=5.11, 9.03, 4.27; P=0.03, 0.00, 0.00) before and after treatment showed statistical significance.ConclusionTargeted navigation laser continuous wave threshold power treatment for CCSC can increase the BCVA, macular retinal amplitude density and macular foveal MS, and reduce CMT and SFCT.
The construction of brain functional network based on resting-state functional magnetic resonance imaging (fMRI) is an effective method to reveal the mechanism of human brain operation, but the common brain functional network generally contains a lot of noise, which leads to wrong analysis results. In this paper, the least absolute shrinkage and selection operator (LASSO) model in compressed sensing is used to reconstruct the brain functional network. This model uses the sparsity of L1-norm penalty term to avoid over fitting problem. Then, it is solved by the fast iterative shrinkage-thresholding algorithm (FISTA), which updates the variables through a shrinkage threshold operation in each iteration to converge to the global optimal solution. The experimental results show that compared with other methods, this method can improve the accuracy of noise reduction and reconstruction of brain functional network to more than 98%, effectively suppress the noise, and help to better explore the function of human brain in noisy environment.
Central serous chorioretinopathy (CSC) is a common macular disease, mainly manifested as a plasma detachment of the macula. Photodynamic therapy (PDT) is an effective treatment for CSC, but with the shortage of the photosensitizer Verteporfin, the effective treatment of CSC has become a common concern for ophthalmologists. In this paper, based on the latest research results on the relationship between the changes in the thickness of the outer nuclear layer and the natural course of the disease and PDT therapy, we propose that patients with CSC should receive effective treatment as early as possible to prevent irreversible damage to visual function due to the thinning of the outer nuclear layer. In addition to PDT, it is recommended that laser photocoagulation or subthreshold micropulse laser treatment of the leaking spot should be considered first, depending on the presence of the leaking spot and its location in relation to the macula center. Anti-vascular endothelial growth factor therapy can be considered if there is a combination of choroidal neovascularization and/or polypoidal choroidal vasculopathy. Other treatments that have not been demonstrated to be effective in evidence-based medicine are not recommended.
A de-noising method for electrocardiogram (ECG) based on ensemble empirical mode decomposition (EEMD) and wavelet threshold de-noising theory is proposed in our school. We decomposed noised ECG signals with the proposed method using the EEMD and calculated a series of intrinsic mode functions (IMFs). Then we selected IMFs and reconstructed them to realize the de-noising for ECG. The processed ECG signals were filtered again with wavelet transform using improved threshold function. In the experiments, MIT-BIH ECG database was used for evaluating the performance of the proposed method, contrasting with de-noising method based on EEMD and wavelet transform with improved threshold function alone in parameters of signal to noise ratio (SNR) and mean square error (MSE). The results showed that the ECG waveforms de-noised with the proposed method were smooth and the amplitudes of ECG features did not attenuate. In conclusion, the method discussed in this paper can realize the ECG de-noising and meanwhile keep the characteristics of original ECG signal.
Objective To introduce the multivariate random effects model (MREM) in the meta-analysis of diagnostic tests with multiple thresholds. Methods This paper expanded and extended the bivariate random effects model (BREM) to develop the MREM, and implemented it in the SAS Proc NLMIXED procedure. Results The MREM could obtain the study specific ROC curve for each study through empirical Bayes estimation, and the summary ROC curve located in between all study specific ROC curves evenly, while the BREM couldn’t obtain the study specific ROC curve. In addition, in the aspect of parameters estimation, the MREM didn’t depend on the choice of the diagnosis threshold and the type of SROC. The MREM could get only one SROC curve and its AUC was between the AUC of the 5 types of SROC from BREM, so it could avoid overestimation or underestimation. Conclusion The MREM can fully exploit the data, obtain stable and reliable results, and have a good application value in meta-analysis of diagnostic tests with multiple thresholds.
Due to the characteristics and environmental factors, electrocardiogram (ECG) signals are usually interfered by noises in the course of signal acquisition, so it is crucial for ECG intelligent analysis to eliminate noises in ECG signals. On the basis of wavelet transform, threshold parameters were improved and a more appropriate threshold expression was proposed. The discrete wavelet coefficients were processed using the improved threshold parameters, the accurate wavelet coefficients without noises were gained through inverse discrete wavelet transform, and then more original signal coefficients could be preserved. MIT-BIH arrythmia database was used to validate the method. Simulation results showed that the improved method could achieve better denoising effect than the traditional ones.
This paper discusses the relationship between stimulating pulse width and the threshold of electrically evoked compound action potential (ECAP). Firstly, the rheobase and chronaxy from strength-duration curve of nerve fiber was computed using the shepherd's experiment results. Secondly, based on the relationship between ECAP and the action potential of nerve fiber, a mathematical expression to describe the relationship between stimulating pulse width and ECAP threshold was proposed. Thirdly, the parameters were obtained and the feasibility was proved to the expression with the results of experiment using guinea pigs. Research result showed that with ECAP compared to the action potential of nerve fiber, their threshold function relationship with stimulating pulse width was similar, and rheobase from the former was an order smaller in the magnitude than the latter, but the chronaxy was close to each other. These findings may provide meaningful guidance to clinical ECAP measurement and studying speech processing strategies of cochlear implant.
Red blood cell (RBC) transfusions are frequently used in cardiac surgery. A minority of patients assume most of the blood products transfusion during and after cardiac operations. Observational analysis of transfusion in patients undergoing cardiac surgery has uniformly demonstrated that RBC transfusion is associated with a significantly increasing risk of all-cause mortality and other serious adverse outcomes. In addition, it is an established fact that such patients can tolerate relatively low hemoglubin (Hb) levels. Consequently, it becomes widely accepted that appropriate limitation of transfusions could confer a substantial benefit to patients and decrease the use of limited resource. As a result, a restrictive threshold for blood transfusion is likely to be favored under most circumstances. However, an increasing amount of data differing from the observational analysis shows that clinical outcomes in patients who received transfusions with restrictive thresholds for Hb level are not superior to those with liberal thresholds. It has created a new uncertainty regarding the use of a restrictive threshold for transfusion during the perioperative period of cardiac surgery.
It is difficult to distinguish the inferior alveolar nerve (IAN) from other tissues inside the IAN canal due to their similar CT values in the X image which are smaller than that of the bones. The direct reconstruction, therefore, is difficult to achieve the effects. The traditional clinical treatments mainly rely on doctors' manually drawing the X images so that some subjective results could not be avoided. This paper proposes the partition reconstruction of IAN canal based on shape features. According to the anatomical features of the IAN canal, we divided the image into three parts and treated the three parts differently. For the first, the directly part of the mandibular, we used Shape-driven Level-set Algorithm Restrained by Local Information (BSLARLI) segment IAN canal. For the second part, the mandibular body, we used Space B-spline curve fitting IAN canal's center, then along the center curve established the cross section. And for the third part, the mental foramen, we used an adaptive threshold Canny algorithm to extract IAN canal's edge to find center curve, and then along it established the cross section similarly. Finally we used the Visualization Toolkit (VTK) to reconstruct the CT data as mentioned above. The VTK reconstruction result by setting a different opacity and color values of tissues CT data can perspectively display the INA canal clearly. The reconstruction result by using this method is smoother than that using the segmentation results and the anatomical structure of mental foramen position is similar to the real tissues, so it provides an effective method for locating the spatial position of the IAN canal for implant surgeries.