Lunch supply in public primary school canteens in Zhejiang Province / 中国学校卫生

Objective@#To investigate lunch supply of public primary school canteens in Zhejiang Province, and to provide a basis for the scientific guidance of school lunch.@*Methods@#During May to Jun. and Sept. to Oct. in 2019, lunch food supply was weighed and recorded and the number of diners in 44 public primary school canteens were summarized. Each investigation lasted for one week.@*Results@#Food was mainly based on the taste of the students (40.91%) in the school canteen. About 45.45% of the schools referred to the Nutrition Guidelines of School Meals for students meals when making recipes in the school canteen. The supplies of cereals, vegetables, fruits, livestock and poultry meat, fish and shrimp, eggs, milk, soybean nuts, vegetable oil and salt were 109.05, 118.01, 0, 63.96, 9.25, 11.31, 0, 10.68, 10.47, 2.54 g. The supply of vegetable oil was basically the same as the recommended amount ( P >0.05). The supplies of energy, protein, calcium, iron, zinc, vitamin A, vitamin B 1, vitamin B 2, vitamin C, dietary fiber were 820.84 kcal, 32.79 g, 164.18 mg, 7.84 mg, 4.71 mg, 23.07 μgRAE, 0.41 mg, 0.35 mg, 20.47 mg, 2.34 g, 37.56% of energy from fat and 48.47% of energy from carbohydrate. The supply of vitamin B 1 was basically the same as the recommended amount ( P >0.05). There were no significant differences in all kinds of food and nutrients between urban and rural primary schools ( P >0.05).@*Conclusion@#Lunch supply is not optimistic in public primary school canteens in Zhejiang Province, with unreasonable structure and fails to agree with current nutritional recommendations. It is suggested that the scientific guidance of students meals should be carried out according to the survey results combined with the characteristics of local diet.

Clinical value of MRI texture analysis for preoperative grading of meningiomas based on conventional MRI images / 中华放射学杂志

Objective To explore the efficacy and clinical value of texture analysis of conventional MRI image for the preoperative classification of meningiomas. Methods The MR images of 101 meningioma cases were retrospectively analyzed, all of them underwent routine MRI before operation, and confirmed by surgery and pathology,of whom 81 cases in WHO Ⅰ,19 cases in Ⅱand 1 case in Ⅲ.The maximum diameter of the tumor in MRI images was outlined as ROI by the Image J software.The histograms and grey-level co-occurrence matrix(GLCM)were used to measure the texture parameters,such as maximum value,minimum value,standard deviation(SD),skewness,kurtosis,angular second moment,contrast,inverse different moment, entropy, correlation and so on, and compared with postoperative pathological grading results.The independent sample t test or the Mann-Whitney U test was used to compare the difference of the histogram and the gray level co-occurrence matrix parameter of the MRI images between low-grade and high-grade meningiomas. ROC curves for statistically significant parameters were used to confirm their efficacy in predicting the preoperative grade of meningiomas.Results (1)In histogram parameters,the SDs of T2WI,FLAIR,ADC(SDT2WI,SDFLAIR,SDADC)of low grade meningioma were 14.764(10.928,17.932),9.753 (7.385,13.618) and 12.171 (9.138,19.691), the high grade meningiomas were 19.252 (13.580,25.715), 13.568 (8.936,17.108) and 16.636 (13.166,21.498), respectively. The difference between the two groups was statistically significant(Z values were-2.863,-2.250,-2.247,P respectively 0.004,0.024,0.025).The skewness values (SkeADC, SkeFLAIR) of ADC sequence and FLAIR sequence of low-grade meningiomas were 1.377 ± 1.172 and-1.327 ± 0.930, respectively, and the high-grade meningiomas were 2.503 ± 1.613 and-0.827±0.834,respectively.The differences between the two groups were statistically significant (t values were-2.196,-3.129, P values were 0.002,0.030, respectively). (2) In the GLCM parameters, entropy (EntT1WI, EntT2WI, EntFLAIR, EntADC) of the enhanced T1WI, T2WI, FLAIR and ADC sequences of low grade meningiomas were 6.881(6.174,7.305),6.534±0.598,6.019±0.588,6.040±0.588,high-grade meningiomas were 7.079 (6.742,7.739), 7.014 ± 0.514,6.370 ± 0.703,6.576 ± 0.450, respectively. And the difference between the two groups was statistically significant (Z=-2.007, t values were-3.294,-2.327,-3.245, P values were 0.045,0.001,0.022,0.002,respectively).(3)The ROC curves of EntADCand SkeADCwere plotted, and the area under the curve(AUC)was 0.768 and 0.710,respectively.Combined EntADC,SkeADCand EntT2WI were the best for the classification of meningiomas,and AUC was 0.799.Conclusion Texture analysis can provide more quantification information, which can be more accurately distinguishing high grade meningiomas and low grade meningiomas before surgery.

Subtype discrimination of lung adenocarcinoma manifesting as ground glass nodule based on radiomics / 中华放射学杂志

Objective To develop and validate the radiomics nomogram on the discrimination of lung invasive adenocarcinoma from'non-invasive'lesion manifesting as ground glass nodule(GGN)and compare it with morphological features and quantitative imaging. Methods One hundred and sixty pathologically confirmed lung adenocarcinomas from November 2011 to December 2014 were included as primary cohort. Seventy-six lung adenocarcinomas from November 2014 to December 2015 were set as an independent validation cohort. Lasso regression analysis was used for feature selection and radiomics signature building. Radiomics score was calculated by the linear fusion of selected features. Multivariable logistic regression analysis was performed to develop models. The prediction performances were evaluated with ROC analysis and AUC,and the different prediction performance between different models and mean CT value were compared with Delong test. The generalization ability was evaluated with the leave-one-out cross-validation method. The performance of the nomogram was evaluated in terms of its calibration. The Hosmer-Lemeshow test was used to evaluate the significance between the predictive and observe values.Results Four hundred and eighty-five 3D features were extracted and reduced to 2 features as the most important discriminators to build the radiomics signatures. The individualized prediction model was developed with age, radiomics signature, spiculation and pleural indentation, which had the best discrimination performance(AUC=0.934)in comparison with other models and mean CT value(P<0.05)and showed better performance compared with the clinical model(AUC=0.743,P<0.001).The radiomics-based nomogram demonstrated good calibration in the primary and validation cohort, and showed improved differential diagnosis performance with an AUC of 0.956 in the independent validation cohort. Conclusion Individualized prediction model incorporating with age, radiomics signature, spiculation and pleural indentation, presenting with radiomics nomogram, could differentiate IAC from'non-invasive'lesion manifesting as GGN with the best performance in comparison with morphological features and quantitative imaging.

An integrated segmentation method for 3D ultrasound carotid artery / 中国医疗器械杂志

An integrated segmentation method for 3D ultrasound carotid artery was proposed. 3D ultrasound image was sliced into transverse, coronal and sagittal 2D images on the carotid bifurcation point. Then, the three images were processed respectively, and the carotid artery contours and thickness were obtained finally. This paper tries to overcome the disadvantages of current computer aided diagnosis method, such as high computational complexity, easily introduced subjective errors et al. The proposed method could get the carotid artery overall information rapidly, accurately and completely. It could be transplanted into clinical usage for atherosclerosis diagnosis and prevention.