The usefulness of diffusion-weighted magnetic resonance (MR) imaging (DWI) for differentiating central lung cancer from postobstructive lobar collapse (POC) was investigated. Thirty-three cases suspected of lung cancer and POC on chest bolus computed tomography (CT) underwent thoracic MR imaging examinations. MR examinations were performed using a 1.5-T clinical scanner. Scanning sequences were T1-weighted imaging, T2-weighted imaging (T2WI) and DWI with b=0, 500 s/mm(2), four excitations and segmented breath-holding. The densities and signals of cancer and postobstructive collapsed lung were compared on bolus-enhanced CT, T2W and DW images. Statistical analyses were performed with chi-square test, paired t-test, non-parameter test and kappa statistics. Differentiation between cancer and POC was possible on bolus CT, T2W and DW images in 14, 21 and 26 patients, respectively. Eight cases that were impossible to differentiate on T2W images were distinguishable on DWI, demonstrating that DWI is complementary to T2WI. Using a combination of T2W and DW images, 88% (29/33) of cases were differentiated on MR imaging. Thus, a combination of T2W and DW imaging is superior to bolus-CT or T2WI alone. The contrast-to-noise ratio of DWI was significantly higher than that of T2WI. Agreement between two independent observers on the differential ability of lung cancer and POC was higher for DWI (kappa=0.474) than for T2WI (kappa=0.339). The degree of consolidation around the cancer was negatively correlated with the degree of artifact and degree of deformation. It is feasible to use DWI to differentiate lung cancer from POC. DWI played a role in confirming and providing complementary information to that obtained from T2WI. Our data indicate that using a combination of the two scanned sequences was the best means of distinguishing between lung cancer and POC.

No abstract

Objective This study was designed to evaluate the clinical efficacy of combined traditional Chinese medicine (TCM) and conventional chemotherapy versus conventional chemotherapy in patients with stage II-IIIA non-small-cell lung cancer (NSCLC) after radical surgery. Methods A retrospective cohort study was conducted in patients with stage II-IIIA NSCLC from Subei People's Hospital and Yangzhou Traditional Chinese Medicine Hospital in Yangzhou City of Jiangsu Province from 2012 to 2016. Patients were divided into two groups: the TCM user group (patients receiving treatment with integrated TCM and conventional chemotherapy) and the non-TCM user group (patients receiving conventional chemotherapy only). The two groups were compared for their median disease-free survival (DFS) and median overall survival (OS). Results A total of 67 patients with stage II-IIIA NSCLC were enrolled between January 2012 and December 2016. The median DFS for the non-TCM user group was 601 days (95% confidence interval [CI], 375.7-826.3). The median DFS for TCM user group could not be calculated. However, log-rank analysis showed that the median survival time in the TCM user group was significantly longer than that of the non-TCM user group (P < 0.05). In addition, several significant risk factors were detected for predicting disease prognosis in patients with NSCLC, such as age, ECOG, lymphatic metastasis, and body mass index (BMI). For patients harboring these independent risk factors, the DFS of TCM user group was much longer than that of non-TCM user group (P < 0.05). Conclusion Adjuvant therapy with TCM may reduce the rate of tumor recurrence and metastasis and prolong DFS of patients with stage II-IIIA NSCLC.

No abstract

As one of the most important mesoscopic properties of networks, the community structure plays an important role in cascading failures on isolated networks. However, the study for understanding the influences of the community structure on the cascading failures on interdependent scale-free networks remains missing. In this paper, we investigate cascading failures on interdependent modular scale-free networks under inner attacks and hub attacks from the global and local perspective. We mainly analyse the inter-community connections and coupling preferences, i.e. random coupling in communities (RCIC), assortative coupling in communities (ACIC) and assortative coupling with communities (ACWC). We find that increasing inter-community connections can enhance the robustness of interdependent modular scale-free networks for both inner attacks and hub attacks. Furthermore, we also find that the ACIC is more beneficial to resisting cascading failures compared with RCIC or ACWC. For ACIC, the cascading failures propagate mainly in a local community where the initial failure occurs. It is meaningful to control the cascading failures on interdependent modular scale-free networks by constructing ACIC.