The Impact of Different Regions of Interest on Shear Wave Elastography Assessment of the Meniscus in the Knee Joint.

RATIONALE AND OBJECTIVES: To investigate the impact of different regions of interest (ROI) on the assessment of shear wave elastography (SWE) in evaluating the meniscus of the knee joint. MATERIALS AND METHODS: After ethical approval, a total of 141 participants were enrolled in this prospective study from February to October 2023. SWE was utilized to evaluate the anterior horn of the lateral meniscus (LM) and medial meniscus (MM), using two different ROIs (ROI-Small and ROI-Trace) to measure the elastic mean value (Emean) and elastic maximum value (Emax). The differences in elasticity values between the normal menisci and torn menisci were compared, and the impact of different ROI selection methods on the diagnostic performance of elastic parameters in the torn menisci was assessed using receiver operating characteristic (ROC) curves. RESULTS: In Emean comparison, only MM in the tear group showed higher ROI-S than ROI-T. When comparing Emax, all ROI-T values were higher than the ROI-S values, and this difference was statistically significant. Different sizes of ROI did not significantly impact the diagnostic performance of Emean in LM and MM, nor the diagnostic effectiveness of Emax in LM. However, only the area under the curve (AUC) of MM for Emax in both ROI-S and ROI-T showed a statistically significant difference. CONCLUSION: The shear wave elasticity values and diagnostic performance may vary depending on the ROI settings. Therefore, it is recommended to use a 2 mm diameter ROI placed at the central position of the meniscus, with Emean as the elasticity index.

Global Burden of Lung Cancer Attributable to Household Fine Particulate Matter Pollution in 204 Countries and Territories, 1990 to 2019.

INTRODUCTION: Household particulate matter (PM) air pollution is substantially associated with lung cancer. Nevertheless, the global burden of lung cancer attributable to household PM2.5 is still uncertain. METHODS: In this study, data from the Global Burden and Disease Study 2019 are used to thoroughly assess the burden of lung cancer associated with household PM2.5. RESULTS: The number of deaths and disability-adjusted life-years (DALYs) attributable to household PM2.5 was found to be 0.08 million and 1.94 million, respectively in 2019. Nevertheless, the burden of lung cancer attributable to household PM2.5 decreased from 1990 to 2019. At the sociodemographic index (SDI) district level, the middle SDI region had the most number of lung cancer deaths and DALYs attributable to household PM2.5. Moreover, the burden of lung cancer was mainly distributed in low-SDI regions, such as Sub-Saharan Africa. Conversely, in high-SDI regions, the age-standardized mortality rate and age-standardized DALY rate of lung cancer attributable to household PM2.5 exhibit the most rapid declines. The burden of lung cancer attributable to household PM2.5 is heavier for men than for women. The sex difference is more obvious in the elderly. CONCLUSIONS: The prevalence of lung cancer attributable to household PM2.5 has exhibited a declining trend from 1990 to 2019 owing to a concurrent decline in household PM2.5 exposure.

Merging Multiphase CTA Images and Training Them Simultaneously with a Deep Learning Algorithm Could Improve the Efficacy of AI Models for Lateral Circulation Assessment in Ischemic Stroke.

We aimed to build a deep learning-based, objective, fast, and accurate collateral circulation assessment model. We included 92 patients who had suffered acute ischemic stroke (AIS) with large vessel occlusion in the anterior circulation in this study, following their admission to our hospital from June 2020 to August 2021. We analyzed their baseline whole-brain four-dimensional computed tomography angiography (4D-CTA)/CT perfusion. The images of the arterial, arteriovenous, venous, and late venous phases were extracted from 4D-CTA according to the perfusion time-density curve. The subtraction images of each phase were created by subtracting the non-contrast CT. Each patient was marked as having good or poor collateral circulation. Based on the ResNet34 classification network, we developed a single-image input and a multi-image input network for binary classification of collateral circulation. The training and test sets included 65 and 27 patients, respectively, and Monte Carlo cross-validation was employed for five iterations. The network performance was evaluated based on its precision, accuracy, recall, F1-score, and AUC. All the five performance indicators of the single-image input model were higher than those of the other model. The single-image input processing network, combining multiphase CTA images, can better classify AIS collateral circulation. This automated collateral assessment tool could help to streamline clinical workflows, and screen patients for reperfusion therapy.

[Clinical effectiveness of Subjective Global Nutritional Assessment in hospitalized children with cerebral palsy].

OBJECTIVE: To investigate the nutritional status of children with cerebral palsy (CP) and the clinical effectiveness of Subjective Global Nutritional Assessment (SGNA) in nutritional assessment of hospitalized children with CP. METHODS: A total of 208 children with CP, aged 1-5 years, who were hospitalized from April to October 2019 were enrolled as subjects. SGNA was used to investigate nutritional status, and the Z-score method recommended by the World Health Organization was used as a reference standard to validate the clinical effectiveness of SGNA. RESULTS: The detection rate of malnutrition in children with CP was 42.3% by SGNA and 39.4% by the Z-score method (P>0.05). The application of SGNA showed high consistency between different evaluators (κ=0.621, P<0.001). With the Z-score method as the reference standard, SGNA had a sensitivity of 80.5%, a specificity of 82.5%, a positive predictive value of 75.0%, and a negative predictive value of 86.7%, and high consistency was observed between the two evaluation methods (κ=0.622, P<0.001). SGNA was moderately consistent with weight-for-age Z-score and height-for-age Z-score (κ=0.495 and 0.478 respectively, P<0.001) and was poorly consistent with weight-for-height Z-score (κ=0.197, P<0.05). CONCLUSIONS: There is a relatively high incidence rate of malnutrition in children with CP. SGNA can be used as a tool to assess the nutritional status of children with CP.