OBJECTIVES: Microvascular invasion (MVI) is an important predictor of postoperative recurrence or poor outcomes of hepatocellular carcinoma (HCC). Radiomics is able to predict MVI in HCC preoperatively. This study aims to investigate the influence of different region of interest (ROI) sizes on CT-based radiomics model for MVI prediction in HCC. METHODS: Patients with HCC with or without MVI confirmed by pathology and those who underwent preoperative plain or enhanced abdominal CT scans in the Third Xiangya Hospital of Central South University from January 2010 to December 2020 were retrospectively and consecutively included. According to the ratio of 7 to 3, the patients were randomly assigned into a training set and a validation set. Clinical data were collected from medical records, and radiomics features were extracted from the arterial phase (AP) and portal venous phase (PVP) of preoperatively acquired CT in all patients. Six different ROI sizes were employed. The original ROI (OROI) was manually delineated along the visible borders of the tumor layer-by-layer. The OROI was expanded out by 1-5 mm. The OROI was combined with 5 different peritumoral regions to generate the other 5 ROIs, named Plus1-Plus5. Feature extraction, dimension reduction, and model development were conducted in 6 different ROIs separately. Supporter vector machine (SVM) was used for model construction. Model performance was assessed via receiver operating characteristic (ROC) curve. RESULTS: A total of 172 HCC patients were included, in which 83 (48.3%) were MVI positive, and 89 (51.7%) were MVI negative. Three hundred and ninety-six features based on AP or PVP images were extracted from each ROI. After feature selection and dimension reduction, 4, 5, 15, 11, 6, and 3 features of OROI, Plus1, Plus2, Plus 3, Plus4, and Plus5 were selected for model construction, respectively. In the training set, the sensitivity, specificity, and area under the curve (AUC) of OROI were 0.759, 0.806, and 0.855, respectively. The AUC values of Plus2 (0.979) and Plus3 (0.954) were higher than that of OROI. The AUC values of Plus1 (0.802), Plus4 (0.792), and Plus5 (0.774) were not significantly different from those of OROI. In the validation set, the sensitivity, specificity, and AUC value of OROI were 0.640, 0.630, and 0.664, respectively. The AUC value of Plus3 was 0.903, which was higher than that of OROI. The AUC values of Plus1 (0.679), Plus2 (0.536), Plus4 (0.708), and Plus5 (0.757) were not significantly different from that of OROI (P>0.05). CONCLUSIONS The size of ROI significantly inflluences on the performance of CT-based radiomics model for MVI prediction in HCC. Including appropriate area around the tumor into ROI could improve the predictive performance of the model, and 3 mm might be appropriate distance.
Carcinoma, Hepatocellular/pathology* ; Humans ; Liver Neoplasms/pathology* ; Predictive Value of Tests ; Retrospective Studies ; Tomography, X-Ray Computed/methods*

OBJECTIVE: To examine the level of occupational exposure to whole body vibration( WBV) in a hydroelectric power station,and evaluate its effects on workers' health. METHODS: A hydroelectric power station in Hangzhou City was chosen as study subject by using judgment sampling method. The level of WBV exposure to workers and high vibration level areas were measured,and the vibration frequency was analyzed. The comfort and allowing duration of occupational exposure in WBV exposed workers was evaluated. RESULTS: The median root-mean-square of accelerometer acceleration of WBV exposure in generator floor,turbines-floor,middle-floor,hydraulic floor of the hydroelectric power station were 0. 894,0. 995,1. 095 and 0. 904 m/s~2,respectively. The central frequency of WBV in this station was 1. 25 Hz. Among the 105 monitoring spots,8. 6% of WBV exposed workers of the spots did not perceive or feel uncomfortable,but 91. 4%of them felt uncomfortable or very uncomfortable. Only 12. 4% of the WBV exposed workers tolerated more than 8 hours of WBV occupational exposure. CONCLUSION: There is an occupational hazard of WBV in this hydroelectric power station.The low frequency vibration with central frequency below 1. 25 Hz is the key control point of the WBV of this hydroelectric power station.

Blue space is an important place for physical activity and provides physical and mental health benefits to residents. However, little is known about the mechanism of association between blue space and physical activity. Based on China National Knowledge Infrastructure and Web of Science Core Collection, the Chinese and English literature on the correlation between blue space and physical activity were selected and analyzed. The research field has the following characteristics so far: there are few studies on blue space in inland cities, developing countries, and vulnerable populations, and it is an emerging research field. Most included studies demonstrate positive effects of blue space exposure on physical activity, while studies conducted in different populations demonstrate population differences. The combination of multi-source data and multidisciplinary approaches should be an important foundation of this research field. Based on this, a research framework was proposed in this paper to analyze the complex association between them from a perspective of multi-dimensional characteristics, and blue physical activity was modeled as ecosystem services to explore the relationship between blue space and physical activity from a perspective of ecosystem service supply-demand and flow.