Signal Alteration of Substantia Nigra on 3.0T Susceptibility-weighted Imaging in Parkinson's Disease and Vascular Parkinsonism.

Recent researches have found that 7 Tesla SWI can detect the alteration of substantia nigra hyperintensity in Parkinson's disease (PD), multiple system atrophy (MSA), and progressive supranuclear palsy (PSP). The aim of this study was to investigate whether 3 Tesla SWI (3T SWI) can visualize anatomical alterations occurring in a hyperintense structure of the substantia nigra in PD and vascular parkinsonism (VP), and whether the evaluation of abnormal signal can be used as a factor in the differential diagnosis of PD and VP. Using 3 Tesla MRI, we evaluated 38 healthy subjects, 33 patients with PD and 34 patients with VP. Two blinded readers independently assessed the images. We found that the dorsolateral nigral hyperintensity was absent in 31 of 33 patients with PD and 15 of 34 patients with VP. The dorsolateral nigral hyperintensity was present in 19 of 34 patients with VP and 35 of 38 healthy controls. Group comparisons of absence of dorsolateral nigral hyperintensity revealed significant differences between the patients with PD and those with VP (P<0.001). The sensitivity of SWI for PD was 93.9% and the specificity was 92.1%. Visual assessment of dorsolateral nigral hyperintensity on high-field SWI scans may serve as a new simple diagnostic imaging marker for PD. And our study results indicate that 3T SWI can be used as a tool to identify PD and VP.

[Impulsive decision-making behaviors in heroin addicts: a study of functional magnetic resonance imaging].

OBJECTIVE: To explore the brain regions associated with impulsive decision-making behaviors and interpret the nervous mechanism for addiction and relapse in heroin abusers. METHODS: Using the paradigms of psychological experiment, the subjects in both heroin addiction group (HA group) and normal control group (HC group) performed Iowa gambling task (IGT) and simultaneously underwent functional magnetic resonance imaging (fMRI) scan. All the above data were gathered and then analyzed by SPM5 software to explore both the brain regions and their functional changes correlated with impulsive decision-making. RESULTS: Evidence by IGT behavioral consequences demonstrated that the net scores in HC group increased with numbers of decision-making whereas no increment (fluctuating between-1 and 0) was observed in HA group. Based on the results of fMRI analysis, right orbitofrontal cortex (OFC), dorsolateral prefrontal cortex (DLPFC), left ventromedial prefrontal cortex (MPFC) and anterior cingulate cortex (ACC) were activated in both groups. But the right OFC was more active while the right DLPFC and left MPFC were weaker in HA group versus the HC group. Meanwhile, activation of right lenticular nucleus, right thalamus, right insula, hippocampus and left caudate nucleus were observed in HA group. CONCLUSION: Heroin abusers are incapable of impulsive decision-making in behavioral studies. Such a brain region as prefrontal cortex participates in the decision-making performance and control of impulsiveness. Functionally abnormal brain regions correlated with impulsive decision-making may be one cause of genesis, maintenance and relapse of heroin addiction.

[A voxel-based morphometric analysis of brain gray matter in online game addicts].

OBJECTIVE: To explore the possible brain mechanism of online game addiction (OGA) in terms of brain morphology through voxel-based morphometric (VBM) analysis. METHODS: Seventeen subjects with OGA and 17 age- and gender-matched healthy controls (HC group) were recruited from Department of Psychology at our hospital during February-December 2011. The internet addiction scale (IAS) was used to measure the degree of OGA tendency. Magnetic resonance imaging (MRI) scans were performed to acquire 3-dimensional T1-weighted images. And FSL 4.1 software was employed to confirm regional gray matter volume changes. For the regions where OGA subjects showed significantly different gray matter volumes from the controls, the gray matter volumes of these areas were extracted, averaged and regressed against the scores of IAS. RESULTS: The OGA group had lower gray matter volume in left orbitofrontal cortex (OFC), left medial prefrontal cortex (mPFC), bilateral insula (INS), left posterior cingulate cortex (PCC) and left supplementary motor area (SMA). Gray matter volumes of left OFC and bilateral INS showed a negative correlation with the scores of IAS (r = -0.65, r = -0.78, P < 0.05). CONCLUSION: Gray matter volume changes are present in online game addicts and they may be correlated with the occurrence and maintenance of OGA.