Objectives: This study aimed to explore the predictive value of MRI-based radiomic model for progression-free survival (PFS) in nonmetastatic nasopharyngeal carcinoma (NPC). Methods: A total of 327 nonmetastatic NPC patients [training cohort (n = 230) and validation cohort (n = 97)] were enrolled. The clinical and MRI data were collected. The least absolute shrinkage selection operator (LASSO) and recursive feature elimination (RFE) were used to select radiomic features. Five models [Model 1: clinical data, Model 2: overall stage, Model 3: radiomics, Model 4: radiomics + overall stage, Model 5: radiomics + overall stage + Epstein-Barr virus (EBV) DNA] were constructed. The prognostic performances of these models were evaluated by Harrell's concordance index (C-index). The Kaplan-Meier method was applied for the survival analysis. Results : Model 5 incorporating radiomics, overall stage, and EBV DNA yielded the highest C-indices for predicting PFS in comparison with Model 1, Model 2, Model 3, and Model 4 (training cohorts: 0.805 vs. 0.766 vs. 0.749 vs. 0.641 vs. 0.563, validation cohorts: 0.874 vs. 0.839 vs. 836 vs. 0.689 vs. 0.456). The survival curve showed that the high-risk group yielded a lower PFS than the low-risk group. Conclusions:The model incorporating radiomics, overall stage, and EBV DNA showed better performance for predicting PFS in nonmetastatic NPC patients.

Type 2 diabetes mellitus (T2DM) has been associated with cognitive impairment. However, its neurological mechanism remains elusive. Combining regional homogeneity (ReHo) and functional connectivity (FC) analyses, the present study aimed to investigate brain functional alterations in middle-aged T2DM patients, which could provide complementary information for the neural substrates underlying T2DM-associated brain dysfunction. Twenty-five T2DM patients and 25 healthy controls were involved in neuropsychological testing and structural and resting-state functional magnetic resonance imaging (rs-fMRI) data acquisition. ReHo analysis was conducted to determine the peak coordinates of brain regions with abnormal local brain activity synchronization. Then, the identified brain regions were considered as seeds, and FC between these brain regions and global voxels was computed. Finally, the potential correlations between the imaging indices and neuropsychological data were also explored. Compared with healthy controls, T2DM patients exhibited higher ReHo values in the anterior cingulate gyrus (ACG) and lower ReHo in the right fusiform gyrus (FFG), right precentral gyrus (PreCG) and right medial orbit of the superior frontal gyrus (SFG). Considering these areas as seed regions, T2DM patients displayed aberrant FC, mainly in the frontal and parietal lobes. The pattern of FC alterations in T2DM patients was characterized by decreased connectivity and positive to negative or negative to positive converted connectivity. Digital Span Test (DST) forward scores revealed significant correlations with the ReHo values of the right PreCG (ρ = 0.527, p = 0.014) and FC between the right FFG and middle temporal gyrus (MTG; ρ = −0.437, p = 0.048). Our findings suggest that T2DM patients suffer from cognitive dysfunction related to spatially local and remote brain activity synchronization impairment. The patterns of ReHo and FC alterations shed light on the mechanisms underlying T2DM-associated brain dysfunction and might serve as imaging biomarkers for diagnosis and evaluation.

2 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2018;48:459-468.

Type 2 diabetes mellitus (T2DM) affects a vast population and is closely associated with cognitive impairment. However, the mechanisms of cognitive impairment in T2DM patients have not been unraveled. Research on the basic units (nodes or hubs and edges) of the brain functional network on the basis of neuroimaging may advance our understanding of the network change pattern in T2DM patients. This study investigated the change patterns of brain functional hubs using degree centrality (DC) analysis and the connectivity among these hubs using functional connectivity and Granger causality analysis. Compared to healthy controls, the DC values were higher in the left anterior cingulate gyrus (ACG) and lower in the bilateral lateral occipital cortices (LOC) and right precentral gyrus (PreCG) in T2DM patients. The functional connectivity between the left ACG and the right PreCG was stronger in T2DM patients, whereas the functional connectivity among the right PreCG and bilateral LOC was weaker. A negative causal effect from the left ACG to left LOC and a positive effect from the left ACG to right LOC were observed in T2DM patients, while in healthy controls, the opposite occurred. Additionally, the reserve of normal brain function in T2DM patients was negatively associated with the elevated glycemic parameters. This study demonstrates that there are brain functional hubs and connectivity alterations that may reflect the aberrant information communication in the brain of T2DM patients. The findings may advance our understanding of the mechanisms of T2DM-related cognitive impairment.

BackgroundDiffusion-weighted imaging (DWI) is increasingly used to identify pathological complete responses (pCRs) to neoadjuvant chemotherapy (NAC) in breast cancer. The aim of the present study was to assess the utility of DWI using a pooled analysis.Materials and MethodsLiterature databases were searched prior to July 2017. Fifteen studies with a total of 1181 patients were included. The data were extracted to perform pooled analysis, heterogeneity testing, threshold effect testing, sensitivity analysis, publication bias analysis and subgroup analyses.ResultThe methodological quality was moderate. Remarkable heterogeneity was detected, primarily due to a threshold effect. The pooled weighted values were a sensitivity of 0.88 (95% confidence interval (CI): 0.81, 0.92), a specificity of 0.79 (95% CI: 0.70, 0.86), a positive likelihood ratio of 4.1 (95% CI: 2.9, 5.9), a negative likelihood ratio of 0.16 (95% CI: 0.10, 0.24), and a diagnostic odds ratio of 26 (95% CI: 15, 46). The area under the receiver operator characteristic curve was 0.91 (95% CI: 0.88, 0.93). In the subgroup analysis, the pooled specificity of change in the apparent diffusion coefficient (ADC) subgroup was higher than that in the pre-treatment ADC subgroup (0.80 [95% CI: 0.71, 087] vs. 0.63 [95% CI: 0.52, 0.73], P = 0.027).ConclusionsDWI may be an accurate and nonradioactive imaging technique for identifying pCRs to NAC in breast cancer. Nonetheless, there are a variety of issues when assessing DWI techniques for estimating breast cancer responses to NAC, and large scale and well-designed clinical trials are needed to assess the technique's diagnostic value.

The present study revealed that ST patients had altered regional neural activity and inter-regional connectivity in partial auditory and non-auditory brain regions, mainly involving the default mode network and audio-visual network, which could further improve our understanding of the neuroimaging mechanism in ST.

Both PET/CT and breast MRI are used to assess pathological complete response to neoadjuvant chemotherapy (NAC) in patients with breast cancer. The aim is to compare the utility of PET/CT and breast MRI by using head-to-head comparative studies. Literature databases were searched prior to July 2016. Eleven studies with a total of 527 patients were included. For PET/CT, the pooled SEN was 0.87 (95% confidence interval (CI): 0.71–0.95) and SPE was 0.85 (95% CI: 0.70–0.93). For MRI, the pooled SEN was 0.79 (95% CI: 0.68–0.87) and SPE was 0.82 (95% CI: 0.72–0.89). In the conventional contrast enhanced (CE)-MRI subgroup, PET/CT outperformed conventional CE-MRI with a higher pooled sensitivity (0.88 (95% CI: 0.71, 0.95) vs. 0.74 (95% CI: 0.60, 0.85), P = 0.018). In the early evaluation subgroup, PET/CT was superior to MRI with a notable higher pooled specificity (0.94 (95% CI: 0.78, 0.98) vs. 0.83 (95% CI: 0.81, 0.87), P = 0.015). The diagnostic performance of MRI is similar to that of PET/CT for the assessment of breast cancer response to NAC. However, PET/CT is more sensitive than conventional CE-MRI and more specific if the second imaging scan is performed before 3 cycles of NAC.

Background: The precise physiopathological association between the courses of neurodegeneration and cognitive decline in type 2 diabetes mellitus (T2DM) remains unclear. This study sought to comprehensively investigate the distribution characteristics of gray matter atrophy in middle-aged T2DM patients with newly diagnosed mild cognitive impairment (MCI). Methods: Four groups, including 28 patients with early-onset MCI, 28 patients with T2DM, 28 T2DM patients with early-onset MCI (T2DM-MCI), and 28 age-, sex-, and education-matched healthy controls underwent three-dimensional high-resolution structural magnetic resonance imaging. Cortical and subcortical gray matter volumes were calculated, and a structural covariance method was used to evaluate the morphological relationships within the default mode network (DMN). Results: Overlapped and unique cortical/subcortical gray matter atrophy was found in patients with MCI, T2DM and T2DM-MCI in our study, and patients with T2DM-MCI showed lower volumes in several areas than patients with MCI or T2DM. Volume loss in subcortical areas (including the thalamus, putamen, and hippocampus), but not in cortical areas, was related to cognitive impairment in patients with MCI and T2DM-MCI. No associations between biochemical measurements and volumetric reductions were found. Furthermore, patients with MCI and those with T2DM-MCI showed disrupted structural connectivity within the DMN. Conclusion: These findings provide further evidence that T2DM may exacerbate atrophy of specific gray matter regions, which may be primarily associated with MCI. Impairments in gray matter volume related to T2DM or MCI are independent of cardiovascular risk factors, and subcortical atrophy may play a more pivotal role in cognitive impairment than cortical alterations in patients with MCI and T2DM-MCI. The enhanced structural connectivity within the DMN in patients with T2DM-MCI may suggest a compensatory mechanism for the chronic neurodegeneration.