Comparative diagnostic performance of contrast-enhanced ultrasound and dynamic contrast-enhanced magnetic resonance imaging for differentiating clear cell and non-clear cell renal cell carcinoma.

OBJECTIVE: To compare the diagnostic efficiency of contrast-enhanced ultrasound (CEUS) with that of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for the differential diagnosis of clear and non-clear cell renal cell carcinoma, as confirmed by subsequent pathology. METHODS: A total of 181 patients with 184 renal lesions diagnosed by both CEUS and DCE-MRI were enrolled in the study, including 136 clear cell renal cell carcinoma (ccRCC) and 48 non-clear cell renal cell carcinoma (non-ccRCC) tumors. All lesions were confirmed by histopathologic diagnosis after surgical resection. Interobserver agreement was estimated using a weighted kappa statistic. Diagnostic efficiency in evaluating ccRCC and non-ccRCC was compared between CEUS and DCE-MRI. RESULTS: The weighted kappa value for interobserver agreement was 0.746 to 0.884 for CEUS diagnosis and 0.764 to 0.895 for DCE-MRI diagnosis. Good diagnostic performance in differential diagnosis of ccRCC and non-ccRCC was displayed by both CEUS and DCE-MRI: sensitivity was 89.7% and 91.9%, respectively; specificity was 77.1% and 68.8%, respectively; and area under the receiver operating curve was 0.834 and 0.803, respectively. No statistically significant differences were present between the two methods (p = 0.54). CONCLUSIONS: Both CEUS and DCE-MRI imaging are effective for the differential diagnosis of ccRCC and non-ccRCC. Thus, CEUS could be an alternative to DCE-MRI as a first test for patients at risk of renal cancer, particularly where DCE-MRI cannot be carried out. KEY POINTS: • CEUS and DCE-MRI features can help differentiate ccRCC and non-ccRCC. • The differential diagnosis of ccRCC and non-ccRCC by CEUS is comparable to that of DCE-MRI. • Interobserver agreement is generally high using CEUS and DCE-MRI.

[Spatial and Temporal Variability of Soil C-to-N Ratio of Yugan County and Its Influencing Factors in the Past 30 Years].

The soil carbon-to-nitrogen (C/N) ratio of soils is a sensitive indicator of soil quality and an indicator for assessing the carbon and nitrogen nutrition balance of soils. Its variation is significant in reflecting the carbon and nitrogen cycling of soils. An accurate knowledge of how the C/N ratio varies spatially and temporally and the driving factors at county scale is of great significance to the extrapolation of balanced fertilization based on soil C/N ratio regulation as well as to the protection of the ecological environment. This study was based on 200 points of surface soil samples (0-20 cm) collected during the second National Soil Survey in 1982 and 423 points of surface soil samples (0-20 cm) collected during the soil test-based formulated fertilization project in 2012 in Yugan County. Combined with the soil parent material, soil type, farmland-use type, terrain factors, pH, straw incorporation pattern, and nitrogen fertilizer rate over the past 30 years, spatial and temporal variability characteristics of the soil C/N ratio were analyzed by using ordinary kriging methods, and the effects of the influencing factors were quantified by regression analysis. The results indicated that the mean value of the C/N ratio was 10.05 and 11.18 in 1982 and 2012, respectively. The coefficient of variation was 19.40% and 25.04%, respectively, which suggested the soil C/N ratio had moderate variability in the study area. The ratios of nugget to sill were 15.91% and 71.25% in 1982 and 2012, respectively. This means that the leading factor from the structural factors (parent material and soil type) into the stochastic factors (nitrogen fertilizer rate and straw incorporation pattern). In the past 30 years, most of the regional soil C/N ratio increased significantly especially the eastern region. The spatial variability of soil C/N in 1982 was mainly affected by soil parent material, soil type, terrain factor, and pH, with the degree of influence of each variable at 17.3%, 14.2%, 7.4%, and 2.3%. In 2012, the spatial variability was mainly affected by soil parent material, soil type, farmland-use type, terrain factor, straw incorporation pattern, and nitrogen fertilizer rate, with the degree of influence of each variable of 8.7%, 23.5% 28.2%, 12.2%, 12.6%, and 42.3%, respectively. To maintain the steady growth of the soil C/N ratio, it is suggested that the return of carbon be incorporated with the input of nitrogen, such as incorporating crop residues into the soil and inputting more organic fertilizers into the soil in future farming practices.

[Spatial Variability of C-to-N Ratio of Farmland Soil in Jiangxi Province].

Spatial variability of soil carbon-to-nitrogen ratio (C/N) at the provincial scale was analyzed using ordinary kriging methods. The effects of the factors influencing C/N were quantified by regression analysis based on 16,582 points of surface soil samples (0-20 cm) collected during the project of soil-test-based formulated fertilization in Jiangxi Province in 2012. The results showed that soil C/N ranged from 2.98 to 52.67, with an average of 11.72. The coefficient of variation was 25.17%, suggesting moderate variability. The nugget-to-sill ratio was 88.44%, meaning that the stochastic factors played a more important role in the spatial variability of soil C/N between the structural and stochastic factors. The spatial distribution of soil C/N was relatively smooth and the high-value areas were mainly distributed in Pengze County-Jiujiang City, Shangli County-Pingxiang City, and Lean County-Fuzhou City. The terrain factors, farmland-use type, parent material, soil type, and the level of nitrogen fertilizer had significant impacts on the spatial variability of soil C/N (P<0.05), but the degree of influence was different for each factor. Soil C/N indicated a significant positive Pearson's correlation with elevation and the slope of slope (P<0.05). The terrain factors explained 0.3% of the spatial variability of soil C/N and the farmland-use could explain 1.4%. The explanatory power of soil groups, subgroups, and soil family were 2.7%, 3.6%, and 5.5% respectively. The level of nitrogen fertilizer could explain 33.4% of the spatial variability of soil C/N, which showed that the amount of nitrogen fertilizer was the main factor that controls the spatial distribution of soil C/N.