Background: To ascertain if analysis of lung density histograms in thin-section CT was more reproducible than visual assessment of lung changes in systemic sclerosis (SSc), and if such density histogram parameters as mean lung attenuation (MLA), skewness, and kurtosis could more closely reflect pulmonary function as well as exercise and quality of life impairment.
Methods: The intraoperator and interoperator reproducibility of visual and densitometric lung CT analysis in 48 SSc patients examined with CT were evaluated by means of weighted kappa statistics. Univariate and multivariate regression analyses were applied to evaluate the relationship of visual and densitometric CT measurements with functional parameters including functional residual capacity (FRC), FVC, FEV(1), diffusion capacity of the lung for carbon monoxide (Dlco), 6-min walking testing (6MWT), and health-related quality of life questionnaire (QLQ) parameters.
Results: The intraoperator and interoperator reproducibility of MLA (intraobserver weighted kappa = 0.97; interobserver weighted kappa = 0.96), skewness (intraobserver weighted kappa = 0.89; interobserver weighted kappa = 0.88), and kurtosis (intraobserver weighted kappa = 0.89; interobserver weighted kappa = 0.88) were higher than those of visual assessment (intraobserver weighted kappa = 0.71; interobserver weighted kappa = 0.69). In univariate analysis, only densitometric measurements were correlated with some exercise and QLQ parameters. In multivariate analysis, MLA (square regression coefficient corrected [R(2)c] = 0.70), skewness (R(2)c = 0.78), and kurtosis (R(2)c = 0.77) were predicted by FRC, FVC, Dlco, 6MWT, and QLQ parameters, while visual assessment was associated only with FRC and FVC (R(2)c = 0.40).
Conclusions: In SSc, densitometric analysis is more reproducible than visual assessment of lung changes in thin-section CT and more closely correlated to pulmonary function testing, 6MWT, and QLQ. Density histogram parameters may be useful for cross-sectional and longitudinal studies of lung involvement in SSc.
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http://dx.doi.org/10.1378/chest.06-1401 | DOI Listing |
Vet Res Commun
January 2025
Genetics and Biotechnology, Department of Aquaculture, Faculty of Fish Resources, Suez University, Suez, 43221, Egypt.
Selective breeding is a potent method for developing strains with enhanced traits. This study compared the growth performance and stress responses of the genetically improved Abbassa Nile tilapia strain (G9; GIANT-G9) with a local commercial strain over 12 weeks, followed by exposure to stressors including high ammonia (10 mg TAN/L), elevated temperature (37 °C), and both for three days. The GIANT-G9 showed superior growth, including greater weight gain, final weight, length gain, specific growth rate, and protein efficiency ratio, as well as a lower feed conversion ratio and condition factor compared to the commercial strain.
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January 2025
From the Department of Radiology, Shenzhen Nanshan People's Hospital, Shenzhen University, Taoyuan Rd No. 89, Nanshan District, Shenzhen 518000, Guangdong, China (H.H., Z.D., Y.Q.); Medical AI Laboratory and Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University Medical School, Shenzhen University, Shenzhen, China (J.M., R.L., B.H.); Department of Medical Imaging, People's Hospital of Longhua, Shenzhen, Guangdong, China (X.P., Y.Z.); and Department of Radiology, Shenzhen People's Hospital, Shenzhen, Guangdong, China (D.Z., G.H.).
Background Multiparametric MRI, including contrast-enhanced sequences, is recommended for evaluating suspected prostate cancer, but concerns have been raised regarding potential contrast agent accumulation and toxicity. Purpose To evaluate the feasibility of generating simulated contrast-enhanced MRI from noncontrast MRI sequences using deep learning and to explore their potential value for assessing clinically significant prostate cancer using Prostate Imaging Reporting and Data System (PI-RADS) version 2.1.
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January 2025
Department of Magnetic Resonance Imaging, The First Affiliated Hospital, Zhengzhou University, Zhengzhou, 450052, China.
Background: Conventional hip joint MRI scans necessitate lengthy scan durations, posing challenges for patient comfort and clinical efficiency. Previously, accelerated imaging techniques were constrained by a trade-off between noise and resolution. Leveraging deep learning-based reconstruction (DLR) holds the potential to mitigate scan time without compromising image quality.
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December 2024
School of Pharmacy, Shandong University of Traditional Chinese Medicine Ji'nan 250355, China State Key Laboratory of Integration and Innovation of Classic Formula and Modern Chinese Medicine, Lunan Pharmaceutical Group Co., Ltd. Linyi 276005, China.
This study aims to investigate the protective effect and potential mechanism of Jingfang Granules(JF) on the mouse model of chronic fatigue syndrome(CFS). Mice were randomized into normal, model, and low-, medium-, and high-dose(0.9, 1.
View Article and Find Full Text PDFPLoS One
January 2025
School of Resources and Environment, Inner Mongolia University of Technology, Hohhot, China.
The aim of this study is to address the limitations of convolutional networks in recognizing modulation patterns. These networks are unable to utilize temporal information effectively for feature extraction and modulation pattern recognition, resulting in inefficient modulation pattern recognition. To address this issue, a signal modulation recognition method based on a two-way interactive temporal attention network algorithm has been developed.
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