Objective To investigate the expressions of estrogen receptor (ER) subtypes and c-met proto-oncogene in human endometrial carcinomas and to assess the clinical significance of ER and c-met in this carcinoma. Methods Reverse transcription PCR (RT-PCR) was used to detect the expressions of ERα, ERβ and c-met proto-oncogene mRNA in 30 samples of endometrial carcinoma and 11 samples of normal endometrium. Results The expression of ERα in endometrial carcinoma (0.70±0.40) was significantly reduced in comparison to that in normal endometrium (1.14±0.56, P<0.05). A similar finding was made for the expression of ERβ in carcinoma (0.24±0.18) versus normal tissues (0.48±0.20, P<0.05). In contrast, c-met mRNA expression was increased in endometrial carcinoma (1.45±0.72) compared to that in normal endometrium (0.42±0.31, P<0.01). A decrease tendency of the expression of ERα was also found from Stage Ⅰ (0.82±0.41) to a more severe Stag Ⅱ-Ⅲ of endometrial carcinoma (0.42±0.17, P<0.05). The analysis of ERα and ERβ mRNA revealed a decrease tendency from shallow to deep invasion of the uterine muscles (P<0.05). We found that the expressions of ERα and ERβ were negatively correlated with c-met proto-oncogene with a coefficient correlation of -0.63 (P<0.01) and -0.32 (P<0.05), respectively. Conclusion ERα and ERβ are both involved in mutagenic action of carcinogen. C-met proto-oncogene plays an important role in the carcinogenesis and development of endometrial carcinoma. C-met and ER expressions show a negative correlation in the development of endometrial carcinoma.

Objective To discuss the correlation between molecular subtypes of early stage breast cancer patients with positive sentinel lymph nodes and the metastasis of non-sentinel lymph nodes, and find out the factors predicting the metastasis of non-sentinel lymph nodes. Methods The clinical data of 124 female breast cancer patients with sentinel lymph node positive were retrospectively analyzed, and the patients were treated with axillary lymph node dissection. And the correlations were analyzed by single factor analysis and multiple factor Logistic regression analysis. Results Among the 124 patients,non-sentinel lymph node metastasis was in 45 cases (36.3%), and only sentinel lymph node positive was in 79 cases (63.7%). The single factor analysis result showed that the age≤35 years, number of sentinel lymph node positive≥2, macrometastasis of sentinel lymph node had correlation with the metastasis of non-sentinel lymph node (P<0.05 or<0.01);but the molecular type, operation method, maximum tumor diameter had no correlation with the metastasis of non-sentinel lymph node (P>0.05). The multiple factor Logistic regression analysis result showed that the number of sentinel lymph node positive and circumstance of sentinel lymph node positive lesions were the independent risk factors of the non-sentinel lymph node metastasis in patients with sentinel lymph node positive (OR = 4.589 and 2.948; P<0.01 or <0.05). Conclusions The circumstance of sentinel lymph node positive lesions and number of sentinel lymph node positive are the independent risk factors of the non-sentinel lymph node metastasis, but the molecular type is not correlated with the metastasis of non-sentinel lymph node. Predicting non-sentinel lymph node metastasis should be combined with clinical and pathological factors.

Objective: To investigate the feasibility of contrast-enhanced computer tomography (CT) texture analysis in predicting early recurrence after transarterial chemoembolization (TACE) in patients with liver cancer. Methods: A retrospective analysis was performed for 47 patients with liver cancer confirmed by liver biopsy and digital subtraction angiography who underwent upper abdominal contrast-enhanced CT scan before TACE, and according to the presence or absence of focal recurrence within half a year, these patients were divided into early recurrence (ER) group and non-early recurrence (NER) group. The texture analysis was used to delineate tumor boundary layer by layer on the axial contrast-enhanced CT image before liver cancer surgery, and related parameters of tumor heterogeneity, including entropy, mean, non-uniformity, skewness, and kurtosis, were obtained. The independent samples t-test was used for comparison of texture parameters between the two groups. The receiver operating characteristic (ROC) curve was used for the analysis of entropy, mean, and non-uniformity, and the area under the ROC curve (ROC), optical cut-off value, sensitivity, and specificity were calculated to evaluate the efficiency of texture analysis in predicting early focal recurrence after TACE. Results: There were 20 patients in the ER group and 27 in the NER group. The ER group had a maximum major axis length of 88.2±36.3 mm and a maximum minor axis length of 41.4±21.4 mm, and the NER group had a maximum major axis length of 66.9±30.2 mm and a maximum minor axis length of 29.3±19.8 mm; the ER group had significantly higher maximum major and minor axis lengths than the NER group (t = 4.89 and 4.62, P < 0.001). The ER group had significantly higher entropy and non-uniformity values than the NER group, and there were no significant differences in skewness and kurtosis between the two groups. Entropy, non-uniformity, and mean had high efficiency in predicting early recurrence after TACE, and the optimal cut-off value of entropy was 4.135. Conclusion Volumetric texture analysis of contrast-enhanced CT images before liver cancer surgery has a high value in predicting early recurrence after TACE.

Objective: To investigate the value of radiomics in image quality control with low-dose CT examination of solid pulmonary nodules. Methods: Images were acquired on CT750 HD scanner, and chest pulmonary nodules phantom were scanned at different tube voltage and tube current. The radiation dose CTDI_vol under different scanning conditions were recorded, as well as CNR and SNR of each scanning sequence. The variation of radiation dose, noise, tube voltage and tube current were analyzed. All data were analyzed by radiomics analysis software. R language statistics software was adopted to analyze the extracted features by principal component analysis (PCA), and the characteristic parameters with the largest contribution rate to image quality were selected for analysis. One-way ANOVA was used to analyze all the important characteristic parameters to reveal the difference of characteristic parameters under different tube voltages. Finally, the post-test method was used to find out the differences among different tube voltage groups. Results: Radiation dose rised linearly with the increase of tube current and tube voltage. Although the overall change trend of SNR and CNR in pulmonary nodules was linearly related to the change of tube voltage and tube current, there was no clear change trend threshold at low dose, which could not accurately evaluate the image quality under low radiation. Both CNR and SNR cannot evaluate the image quality effectively, and have no practiced value for optimizing the low dose scanning parameters. There main components including Uniformity, Voxel Value Sum, and Haralick Correlation extracted by radiomics analysis software were proved to play a critical role in image quality control. The cumulative contribution rate of variance was 89.20% and the eigen values were greater than 1. Uniformity curve of characteristic parameter showed that the trend of change was correlated with the change of tube voltage and tube current, and the stability and consistency were good. Uniformity one-way ANOVA analysis showed that when the tube voltage reduced from 140 to 120 kVp, there was no difference (P=0.117) in the uniformity, while from 120 to 80 kVp, significant differences revealed (P<0.001). Considering tube current, no significant variation was observed in uniformity when current was greater than 90 mA, which indicated that tube current of 90 mA could lead to better image quality. Conclusion Radiomics analysis can effectively evaluate and control the CT image quality of low dose solid pulmonary nodules.