Our proposed method is fully automatic without any user interaction. Quantitative results also indicate that our method is so efficient and accurate that it can be good enough to replace the time-consuming and tedious manual segmentation approach, demonstrating the potential clinical applications.

Our study indicated that heat stress increased the quantity of doxorubicin-containing exosomes from tumour cells, and enhanced the anti-tumour effect of exosomes from the doxorubicin-treated tumour cells. Our findings may aid in designing new strategies for cancer therapy by combination of chemotherapy and hyperthermia.

PurposeTo evaluate the accuracy of shear wave elastography (SWE) in the quantitative diagnosis of liver fibrosis severity.MethodsThe published literatures were systematically retrieved from PubMed, Embase, Web of science and Scopus up to May 13th, 2016. Included studies reported the pooled sensitivity, specificity, positive and negative predictive values, as well as the diagnostic odds ratio of SWE in populations with liver fibrosis. A bivariate mixed-effects regression model was used, which was estimated by the I2 statistics. The quality of articles was evaluated by quality assessment of diagnostic accuracy studies (QUADAS).ResultsThirteen articles including 2303 patients were qualified for the study. The pooled sensitivity and specificity of SWE for the diagnosis of liver fibrosis are as follows: ≥F1 0.76 (p<0.001, 95% CI, 0.71–0.81, I2 = 75.33%), 0.92 (p<0.001, 95% CI, 0.80–0.97, I2 = 79.36%); ≥F2 0.84 (p = 0.35, 95% CI, 0.81–0.86, I2 = 9.55%), 0.83 (p<0.001, 95% CI, 0.77–0.88, I2 = 86.56%); ≥F3 0.89 (p = 0.56, 95% CI, 0.86–0.92, I2 = 0%), 0.86 (p<0.001, 95% CI, 0.82–0.90, I2 = 75.73%); F4 0.89 (p = 0.24, 95% CI, 0.84–0.92, I2 = 20.56%), 0.88 (p<0.001, 95% CI, 0.84–0.92, I2 = 82.75%), respectively. Sensitivity analysis showed no significant changes if any one of the studies was excluded. Publication bias was not detected in this meta-analysis.ConclusionsOur study suggests that SWE is a helpful method to appraise liver fibrosis severity. Future studies that validate these findings would be appropriate.

ObjectiveHepatocellular carcinoma (HCC) is the third leading cause of cancer death worldwide. We conducted network meta-regression within a Bayesian framework to compare and rank different treatment strategies for HCC through direct and indirect evidence from international studies.Methods and analysesWe pooled the OR for 1-year, 3-year and 5-year overall survival, based on lesions of size ˂ 3 cm, 3–5 cm and ≤5 cm, using five therapeutic options including resection (RES), radiofrequency ablation (RFA), microwave ablation (MWA), transcatheter arterial chemoembolisation (TACE) plus RFA (TR) and percutaneous ethanol injection (PEI).ResultsWe identified 74 studies, including 26 944 patients. After adjustment for study design, and in the full sample of studies, the treatments were ranked in order of greatest to least benefit as follows for 5 year survival: (1) RES, (2) TR, (3) RFA, (4) MWA and (5) PEI. The ranks were similar for 1- and 3-year survival, with RES and TR being the highest ranking treatments. In both smaller (<3 cm) and larger tumours (3–5 cm), RES and TR were also the two highest ranking treatments. There was little evidence of inconsistency between direct and indirect evidence.ConclusionThe comparison of different treatment strategies for HCC indicated that RES is associated with longer survival. However, many of the between-treatment comparisons were not statistically significant and, for now, selection of strategies for treatment will depend on patient and disease characteristics. Additionally, much of the evidence was provided by non-randomised studies and knowledge gaps still exist. More head-to-head comparisons between both RES and TR, or other approaches, will be necessary to confirm these findings.

Objectives-This work aimed to investigate whether quantitative radiomics imaging features extracted from ultrasound (US) can noninvasively predict breast cancer (BC) metastasis to axillary lymph nodes (ALNs). Methods-Presurgical B-mode US data of 196 patients with BC were retrospectively studied. The cases were divided into the training and validation cohorts (n = 141 versus 55). The elastic net regression technique was used for selecting features and building a signature in the training cohort. A linear combination of the selected features weighted by their respective coefficients produced a radiomics signature for each individual. A radiomics nomogram was established based on the radiomics signature and US-reported ALN status. In a receiver operating characteristic curve analysis, areas under the curves (AUCs) were determined for assessing the accuracy of the prediction model in predicting ALN metastasis in both cohorts. The clinical value was assessed by a decision curve analysis. Results-In all, 843 radiomics features per case were obtained from expertdelineated lesions on US imaging in this study. Through radiomics feature selection, 21 features were selected to constitute the radiomics signature for predicting ALN metastasis. Area under the curve values of 0.778 and 0.725 were obtained in the training and validation cohorts, respectively, indicating moderate predictive ability. The radiomics nomogram comprising the radiomics signature and US-reported ALN status showed the best performance for ALN detection in the training cohort (AUC, 0.816) but moderate performance in the validation cohort (AUC, 0.759). The decision curve showed that both the radiomics signature and nomogram displayed good clinical utility. Conclusions-This pilot radiomics study provided a noninvasive method for predicting presurgical ALN metastasis status in BC.