).q RSNA, 2015 Purpose:To quantitatively compare the potential of various diffusion parameters obtained from monoexponential, biexponential, and stretched exponential diffusion-weighted imaging models and diffusion kurtosis imaging in the grading of gliomas. Materials andMethods:This study was approved by the local ethics committee, and written informed consent was obtained from all subjects. Both diffusion-weighted imaging and diffusion kurtosis imaging were performed in 69 patients with pathologically proven gliomas by using a 3-T magnetic resonance (MR) imaging unit. An isotropic apparent diffusion coefficient (ADC), true ADC, pseudo-ADC, and perfusion fraction were calculated from diffusionweighted images by using a biexponential model. A water molecular diffusion heterogeneity index and distributed diffusion coefficient were calculated from diffusion-weighted images by using a stretched exponential model. Mean diffusivity, fractional anisotropy, and mean kurtosis were calculated from diffusion kurtosis images. All values were compared between high-grade and low-grade gliomas by using a Mann-Whitney U test. Receiver operating characteristic and Spearman rank correlation analysis were used for statistical evaluations. Results:ADC, true ADC, perfusion fraction, water molecular diffusion heterogeneity index, distributed diffusion coefficient, and mean diffusivity values were significantly lower in high-grade gliomas than in low-grade gliomas (U = 109, 56, 129, 6, 206, and 229, respectively; P , .05). Pseudo-ADC and mean kurtosis values were significantly higher in high-grade gliomas than in low-grade gliomas (U = 98 and 8, respectively; P , .05). Both water molecular diffusion heterogeneity index (area under the receiver operating characteristic curve [AUC] = 0.993) and mean kurtosis (AUC = 0.991) had significantly greater AUC values than ADC (AUC = 0.866), mean diffusivity (AUC = 0.722), and fractional anisotropy (AUC = 0.500) in the differentiation of low-grade and high-grade gliomas (P , .05). Conclusion:Water molecular diffusion heterogeneity index and mean kurtosis values may provide additional information and improve the grading of gliomas compared with conventional diffusion parameters.q RSNA, 2015

BackgroundPrimary insomnia can severely impair daytime function by disrupting attention and working memory and imposes a danger to self and others by increasing the risk of accidents. We speculated that the neurobiological changes impeding working memory in primary insomnia patients would be revealed by resting-state functional MRI (R-fMRI), which estimates the strength of cortical pathways by measuring local and regional correlations in blood oxygen level dependent (BOLD) signs independent of specific task demands.MethodsWe compared the R-fMRI activity patterns of 15 healthy controls to 15 primary insomnia patients (all 30 participants were right-handed) using a 3.0 T MRI scanner. The SPM8 and REST1.7 software packages were used for preprocessing and analysis. Activity was expressed relative to the superior parietal lobe (SPL, the seed region) to reveal differences in functional connectivity to other cortical regions implicated in spatial working memory.ResultIn healthy controls, bilateral SPL activity was associated with activity in the posterior cingulate gyrus, precuneus, ventromedial prefrontal cortex, and superior frontal gyrus, indicating functional connectivity between these regions. Strong functional connectivity between the SPL and bilateral pre-motor cortex, bilateral supplementary motor cortex, and left dorsolateral prefrontal cortex was observed in both the control group and the primary insomnia group. However, the strength of several other functional connectivity pathways to the SPL exhibited significant group differences. Compared to healthy controls, connectivity in the primary insomnia group was stronger between the bilateral SPL and the right ventral anterior cingulate cortex, left ventral posterior cingulate cortex, right splenium of the corpus callosum, right pars triangularis (right inferior frontal gyrus/Broca’s area), and right insular lobe, while connectivity was weaker between the SPL and right superior frontal gyrus (dorsolateral prefrontal cortex).ConclusionPrimary insomnia appears to alter the functional connectivity between the parietal and frontal lobes, cortical structures critical for spatial and verbal working memory.

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OBJECTIVE: To compare 2D and 3D radiomics features prognostic performance differences in CT images of non-small cell lung cancer (NSCLC). METHOD: We enrolled 588 NSCLC patients from three independent cohorts. Two sets of 463 patients from two different institutes were used as the training cohort. The remaining cohort with 125 patients was set as the validation cohort. A total of 1014 radiomics features (507 2D features and 507 3D features correspondingly) were assessed. Based on the dichotomized survival data, 2D and 3D radiomics indicators were calculated for each patient by trained classifiers. We used the area under the receiver operating characteristic curve (AUC) to assess the prediction performance of trained classifiers (the support vector machine and logistic regression). Kaplan–Meier and Cox hazard survival analyses were also employed. Harrell's concordance index (C-Index) and Akaike's information criteria (AIC) were applied to assess the trained models. RESULTS: Radiomics indicators were built and compared by AUCs. In the training cohort, 2D_AUC = 0.653, 3D_AUC = 0.671. In the validation cohort, 2D_AUC = 0.755, 3D_AUC = 0.663. Both 2D and 3D trained indicators achieved significant results (P < .05) in the Kaplan-Meier analysis and Cox regression. In the validation cohort, 2D Cox model had a C-Index = 0.683 and AIC = 789.047; 3D Cox model obtained a C-Index = 0.632 and AIC = 799.409. CONCLUSION: Both 2D and 3D CT radiomics features have a certain prognostic ability in NSCLC, but 2D features showed better performance in our tests. Considering the cost of the radiomics features calculation, 2D features are more recommended for use in the current study.

DTI measurement could detect abnormality of the optic nerve in patients with glaucoma and may serve as a biomarker of disease severity.

This study investigated the topological characteristics of brain functional networks in chronic insomnia disorder (CID) patients. The resting-state functional magnetic resonance imaging and graph theory analysis method were applied to investigate the brain functional connectome patterns among 45 CID patients and 32 healthy controls. The brain functional connectome was constructed by thresholding partial correlation matrices of 90 brain regions from an automated anatomical labeling atlas. The topologic properties of brain functional connectomes at both global and nodal levels were tested. The CID patients had decreased number of module (p = .014) and hierarchy (p = .038), and increased assortativity (p = .035). Furthermore, some brain regions located in the default mode network, dorsal attention network, and sensory-motor network in these patients showed altered nodal centralities. Within these areas, the node betweenness of right central paracentral lobule had positive correlation with the Pittsburgh Sleep Quality Index score (R = 0.319, p = .039). The results imply that functional disruptions of CID patients may be related to disruptions in global and regional topological organization of the brain functional connectome, and provide new and important insights to understand the pathophysiological mechanisms of CID.

DTI is a valuable method to distinguish postoperative recurrent glioma and radiation injury.

BackgroundA pilot study has shown that real-time fMRI (rtfMRI) neurofeedback could be an alternative approach for chronic pain treatment. Considering the relative small sample of patients recruited and not strictly controlled condition, it is desirable to perform a replication as well as a double-blinded randomized study with a different control condition in chronic pain patients. Here we conducted a rtfMRI neurofeedback study in a subgroup of pain patients – patients with postherpetic neuralgia (PHN) and used a different sham neurofeedback control. We explored the feasibility of self-regulation of the rostral anterior cingulate cortex (rACC) activation in patients with PHN through rtfMRI neurofeedback and regulation of pain perception.MethodsSixteen patients (46–71 years) with PHN were randomly allocated to a experimental group (n = 8) or a control group (n = 8). 2 patients in the control group were excluded for large head motion. The experimental group was given true feedback information from their rACC whereas the control group was given sham feedback information from their posterior cingulate cortex (PCC). All subjects were instructed to perform an imagery task to increase and decrease activation within the target region using rtfMRI neurofeedback.ResultsOnline analysis showed 6/8 patients in the experimental group were able to increase and decrease the blood oxygen level dependent (BOLD) fMRI signal magnitude during intermittent feedback training. However, this modulation effect was not observed in the control group. Offline analysis showed that the percentage of BOLD signal change of the target region between the last and first training in the experimental group was significantly different from the control group’s and was also significantly different than 0. The changes of pain perception reflected by numerical rating scale (NRS) in the experimental group were significantly different from the control group. However, there existed no significant correlations between BOLD signal change and NRS change.ConclusionPatients with PHN could learn to voluntarily control over activation in rACC through rtfMRI neurofeedback and alter their pain perception level. The present study may provide new evidence that rtfMRI neurofeedback training may be a supplemental approach for chronic clinical pain management.