Differentiation between metastatic and tumour-free cervical lymph nodes in patients with papillary thyroid carcinoma by grey-scale sonographic texture analysis

Purpose: Papillary thyroid carcinoma (PTC) is the most common thyroid cancer, and cervical lymph nodes (LNs) are the most common extrathyroid metastatic involvement. Early detection and reliable diagnosis of LNs can lead to improved cure rates and management costs. This study explored the potential of texture analysis for texture-based classification of tumour-free and metastatic cervical LNs of PTC in ultrasound imaging. Material and methods: A total of 274 LNs (137 tumour-free and 137 metastatic) were explored using the texture analysis (TA) method. Up to 300 features were extracted for texture analysis in three normalisations (default, 3sigma, and 1-99). Linear discriminant analysis was employed to transform raw data to lower-dimensional spaces and increase discriminative power. The features were classified by the first nearest neighbour classifier. Results: Normalisation reflected improvement on the performance of the classifier; hence, the features under 3sigma normalisation schemes through FFPA (fusion Fisher plus the probability of classification error POE + average correlation coefficients ACC) features indicated high performance in classifying tumour-free and metastatic LNs with a sensitivity of 99.27%, specificity of 98.54%, accuracy of 98.90%, positive predictive value of 98.55%, and negative predictive value of 99.26%. The area under the receiver operating characteristic curve was 0.996. Conclusions: TA was determined to be a reliable method with the potential for characterisation. This method can be applied by physicians to differentiate between tumour-free and metastatic LNs in patients with PTC in conventional ultrasound imaging. © Pol J Radiol

Differentiation between metastatic and tumour-free cervical lymph nodes in patients with papillary thyroid carcinoma by grey-scale sonographic texture analysis

Purpose: Papillary thyroid carcinoma (PTC) is the most common thyroid cancer, and cervical lymph nodes (LNs) are the most common extrathyroid metastatic involvement. Early detection and reliable diagnosis of LNs can lead to improved cure rates and management costs. This study explored the potential of texture analysis for texture-based classification of tumour-free and metastatic cervical LNs of PTC in ultrasound imaging. Material and methods: A total of 274 LNs (137 tumour-free and 137 metastatic) were explored using the texture analysis (TA) method. Up to 300 features were extracted for texture analysis in three normalisations (default, 3sigma, and 1-99). Linear discriminant analysis was employed to transform raw data to lower-dimensional spaces and increase discriminative power. The features were classified by the first nearest neighbour classifier. Results: Normalisation reflected improvement on the performance of the classifier; hence, the features under 3sigma normalisation schemes through FFPA (fusion Fisher plus the probability of classification error POE + average correlation coefficients ACC) features indicated high performance in classifying tumour-free and metastatic LNs with a sensitivity of 99.27%, specificity of 98.54%, accuracy of 98.90%, positive predictive value of 98.55%, and negative predictive value of 99.26%. The area under the receiver operating characteristic curve was 0.996. Conclusions: TA was determined to be a reliable method with the potential for characterisation. This method can be applied by physicians to differentiate between tumour-free and metastatic LNs in patients with PTC in conventional ultrasound imaging. © Pol J Radiol

Application of deep learning technique to manage COVID-19 in routine clinical practice using CT images: Results of 10 convolutional neural networks

Fast diagnostic methods can control and prevent the spread of pandemic diseases like coronavirus disease 2019 (COVID-19) and assist physicians to better manage patients in high workload conditions. Although a laboratory test is the current routine diagnostic tool, it is time-consuming, imposing a high cost and requiring a well-equipped laboratory for analysis. Computed tomography (CT) has thus far become a fast method to diagnose patients with COVID-19. However, the performance of radiologists in diagnosis of COVID-19 was moderate. Accordingly, additional investigations are needed to improve the performance in diagnosing COVID-19. In this study is suggested a rapid and valid method for COVID-19 diagnosis using an artificial intelligence technique based. 1020 CT slices from 108 patients with laboratory proven COVID-19 (the COVID-19 group) and 86 patients with other atypical and viral pneumonia diseases (the non-COVID-19 group) were included. Ten well-known convolutional neural networks were used to distinguish infection of COVID-19 from non-COVID-19 groups: AlexNet, VGG-16, VGG-19, SqueezeNet, GoogleNet, MobileNet-V2, ResNet-18, ResNet-50, ResNet-101, and Xception. Among all networks, the best performance was achieved by ResNet-101 and Xception. ResNet-101 could distinguish COVID-19 from non-COVID-19 cases with an AUC of 0.994 (sensitivity, 100; specificity, 99.02; accuracy, 99.51). Xception achieved an AUC of 0.994 (sensitivity, 98.04; specificity, 100; accuracy, 99.02). However, the performance of the radiologist was moderate with an AUC of 0.873 (sensitivity, 89.21; specificity, 83.33; accuracy, 86.27). ResNet-101 can be considered as a high sensitivity model to characterize and diagnose COVID-19 infections, and can be used as an adjuvant tool in radiology departments. © 2020 Elsevier Lt

Impact of integrated multimodal traveler information on auto commuter's mode switching propensity

Aim: Real-time traveler information affects auto commuter’s travel behavior. Method: An ordered probit model is used to analyze auto commuter’s mode switching propensity under influence of simulated real-time multimodal traveler information. A travel preference survey is administered to car drivers to gather individual commuter’s travel decisions under integrated multimodal traveler information. Result: It is shown that integrated multimodal traveler information can influence willingness of car drivers to switch mode of travel, while socio-economic characteristics also influence the mode choice decision

FcγRIIB engagement drives agonistic activity of Fc-engineered αOX40 antibody to stimulate human tumor-infiltrating T cells

Background OX40 (CD134) is a costimulatory molecule of the tumor necrosis factor receptor superfamily that is currently being investigated as a target for cancer immunotherapy. However, despite promising results in murine tumor models, the clinical efficacy of agonistic αOX40 antibodies in the treatment of patients with cancer has fallen short of the high expectation in earlier-stage trials. Methods Using lymphocytes from resected tumor, tumorfree (TF) tissue and peripheral blood mononuclear cells (PBMC) of 96 patients with hepatocellular and colorectal cancers, we determined OX40 expression and the in vitro T-cell agonistic activity of OX40-targeting compounds. RNA-Seq was used to evaluate OX40-mediated transcriptional changes in CD4+ and CD8+

Effect of Plant Spacing and Plant Density on Yield and Yield Components of Two White Bean (Phaseolus vulgaris L.) Promising Lines in Presence and Absence of Weeds

Abstract\ud Crop genotype with high potential in weed competition is one of the main factors affecting competition against weeds . This experiment was conducted in a split– factorial plot design with four replications in base based on randomize complete block design in National Research Institute of Bean (Khomein) in 2004. The main plot comprised of with and without weed control and sub plot comprised of the plant densities (30, 40 and 50 plant /m2 or 60, 50 and 40 cm row spacing, respectively) and two lines of the white bean (KS41105 and KS41124). The evaluated characteristics were: plant height, branches number, pod number/plant, seed number/pod, seed number/plant, 100seed weight and grain yield. Results of the this experiment showed that decrease of row spacing caused increasing of the grain yield in both weed free and weed infest conditions. The maximum grain yield in KS41105 line with and without weed control obtained in 40 and 50 cm row spacing, respectively. In KS41124 line, maximum grain yield with and without weed control obtained in 50 and 40 cm row spacing, respectively. In two lines weed infested condition caused decreasing of the pod number/plant, seed number/plant and 100seed weight, but there were not any effect on seed number/pod. \ud \ud Keywords: White bean, Weeds, Row spacing, Yield component

船の静復原力の実測

Purpose: Early detection and monitoring of kidney function during the post-transplantation period is one of the most important issues for improving the accuracy of an initial diagnosis. The aim of this study was to evaluate texture analysis (TA) in scintigraphic imaging to detect changes in kidney status after transplantation. Material and methods: Scintigraphic images were used for TA from a total of 94 kidney allografts (39 rejected and 55 non-rejected). Images corresponding to the frames at the 2nd, 5th, and 20th minute of the study were used to determine the optimum time point for analysis of differences in texture features between the rejected and non-rejected allografts. Results: Linear discriminant analysis indicated the best performance at the fifth minute frame for classification of the rejected and non-rejected allografts with receiver operating characteristic curve (Az) of 0.982, corresponding to 91.89 sensitivity, 96.49 specificity, and 94.68 accuracy. Also, TA can differentiate acute tubular necrosis from acute rejection with Az of 0.953 corresponding to 88 sensitivity, 92.31 specificity, and 90.62 accuracy at the 5th minute frame. The best correlation between texture feature and kidney function was achieved at the 20th minute frame (r = -0.396) for glomerular filtration rate. Conclusions: TA has good potential for the characterisation of kidney failure after transplantation and can improve clinical diagnosis. © Pol J Radiol

電波波形の説明

Background: Early detection and reliable diagnosis of breast cancer could lead to improved cure rates and reduce mortality and management costs. Objectives: To explore the potential of texture analysis based on run-length matrix features for classifying benign and malignant breast tumors in ultrasound imaging. Methods: A total of 70 breast tumors (38 benign and 32 malignant) have used in the proposed computer-aided diagnosis system. Twenty run-length matrix features have extracted for texture analysis in three normalizations (default, 3sigma, and 1 - 99). Linear discriminant analysis and principal component analysis have employed to transform raw data to lower-dimensional spaces and increase discriminative power. The features have classified by the first nearest neighbor classifier. Results: The features under 3sigma normalization have designed via Linear discriminant analysis indicated high performance in classifying benign and malignant breast tumors with a sensitivity of 96.87, specificity of 100, accuracy of 98.57, positive predictive value of 100, and negative predictive value of 97.43. The area under receiver operating characteristic curve was 0.992. Conclusions: Run-length matrix features had a high potential to characterize and could help radiologist to diagnosis breast tumors. © 2017, International Journal of Cancer Management

Optimization and kinetic evaluation of acid blue 193 degradation by UV/peroxydisulfate oxidation using response surface methodology

The optimization of process conditions for the degradation of Acid Blue 193 by UV/peroxydisulfate was investigated using response surface methodology (RSM). The effects of four parameters namely initial K2S2O8 concentration, UV irradiation, temperature, and initial dye concentration on two process responses, color removal and the rate constants of the first-order kinetic equations, were investigated using a second-order polynomial multiple regression model. The analysis of variance (ANOVA) explained a high determination coefficient (R2) value of 0.927-0.967, which ensures a good fit of the first-order regression model with the experimental data. The central composite design (CCD) was used to optimize the process conditions, which showed that an initial K2S2O8 concentration of 5 mM, UV irradiation of 250 W, temperature of 50 °C, and the initial dye concentration of 40 mg/L were the best conditions. Under optimum conditions, the maximum color removal from the wastewater and the rate constants of the first-order kinetic equation were 100% and 0.086 min--1, respectively

Radioprotective effects of selenium and vitamin-E against 6MV X-rays in human blood lymphocytes by micronucleus assay

Background: Critical macromolecules of cells such as DNA are in exposure to damage of free radicals that induced from the interaction of ionizing radiation with biological systems. Selenium and vitamin-E are natural compounds that have been shown to be a direct free radical scavenger. The aim of this study was to investigate the radioprotective effect of selenium and vitamin-E separately and synergistically against genotoxicity induced by 6MV x-rays irradiation in blood lymphocytes. Methods: Fifteen volunteers were divided into three groups include A, B and C. These groups were given selenium (800IU), vitamin-E (100mg) and selenium (400IU) + vitamin-E (50mg), respectively. Peripheral blood samples were collected from each group before (0hr) and 1, 2 and 3hr after selenium and vitamin-E administration (separately and synergistically). Then the blood samples were irradiated to 200cGy of 6MV x-rays. After that lymphocyte samples were cultured with mitogenic stimulation to determine the chromosomal aberrations with micronucleus assay in cytokinesis-blocked binucleated cells. Results: The lymphocytes in the blood samples collected at one hr after ingestion selenium and vitamin-E, exposed in vitro to x-rays exhibited a significant decrease in the incidence of micronuclei, compared with control group at 0hr. The maximum protection and decrease in frequency of micronuclei (50) were observed at one hr after administration of selenium and vitamin-E synergistically. Conclusion: The data suggest that ingestion of selenium and vitamin-E as a radioprotector substance before exposures may reduce genetic damage caused by x-rays irradiation