An Automatic Method for Generating an Unbiased Intensity Normalizing Factor in Positron Emission Tomography Image Analysis After Stroke / 神经科学通报·英文版

Positron emission tomography (PET) imaging of functional metabolism has been widely used to investigate functional recovery and to evaluate therapeutic efficacy after stroke. The voxel intensity of a PET image is the most important indicator of cellular activity, but is affected by other factors such as the basal metabolic ratio of each subject. In order to locate dysfunctional regions accurately, intensity normalization by a scale factor is a prerequisite in the data analysis, for which the global mean value is most widely used. However, this is unsuitable for stroke studies. Alternatively, a specified scale factor calculated from a reference region is also used, comprising neither hyper- nor hypo-metabolic voxels. But there is no such recognized reference region for stroke studies. Therefore, we proposed a totally data-driven automatic method for unbiased scale factor generation. This factor was generated iteratively until the residual deviation of two adjacent scale factors was reduced by < 5%. Moreover, both simulated and real stroke data were used for evaluation, and these suggested that our proposed unbiased scale factor has better sensitivity and accuracy for stroke studies.

Abnormal Metabolic Connectivity in Rats at the Acute Stage of Ischemic Stroke / 神经科学通报·英文版

Stroke at the acute stage is a major cause of disability in adults, and is associated with dysfunction of brain networks. However, the mechanisms underlying changes in brain connectivity in stroke are far from fully elucidated. In the present study, we investigated brain metabolism and metabolic connectivity in a rat ischemic stroke model of middle cerebral artery occlusion (MCAO) at the acute stage using F-fluorodeoxyglucose positron emission tomography. Voxel-wise analysis showed decreased metabolism mainly in the ipsilesional hemisphere, and increased metabolism mainly in the contralesional cerebellum. We used further metabolic connectivity analysis to explore the brain metabolic network in MCAO. Compared to sham controls, rats with MCAO showed most significantly reduced nodal and local efficiency in the ipsilesional striatum. In addition, the MCAO group showed decreased metabolic central connection of the ipsilesional striatum with the ipsilesional cerebellum, ipsilesional hippocampus, and bilateral hypothalamus. Taken together, the present study demonstrated abnormal metabolic connectivity in rats at the acute stage of ischemic stroke, which might provide insight into clinical research.

Aberrant Effective Connectivity of Subregions of Posterior Cingulate Cortex in Depressive Disorder / 中国医学影像学杂志

Purpose To explore the role of posterior cingulate cortex (PCC) dysfunction in the pathogenesis of depression and its relationship with the clinical features of depression by analyzing the effective connection among the inner areas of PCC of patients in depression.Materials and Methods The spectral dynamic causal model (spDCM) was used to analyze the resting state functional magnetic resonance imaging (fMRI) data from the PCC inner areas Brodmann area (BA) 23,BA29,BA30,BA31 in the major depressive disorder group (MDD,n=23) and healthy control group (HC,n=36).Results Compared with HC group,the strength of BA30 self-connection of MDD group existed significant difference (t=2.53,P＜0.05).In MDD group,the connection of BA23 toward BA31 had abnormal activation,and the abnormal inhibition occurred in BA23 toward BA30;compared with HC group and after a＜0.05 Hz correction,there were significant differences in the bi-directional connections for BA23 and BA31,BA39 and BA31,BA30 and BA31,and in the unidirectional connections for BA23 to BA31,BA30 to BA23,BA30 to BA29 in MDD group.Conelusion The effective connection and connective nodes and edges in the inner areas of PCC in the depression disorder patients were abnormal.

Volume changes of whole brain gray matter in pediatric patients with Tourette syndrome: evidence from voxel-based morphometry / 中华放射学杂志

ObjectivesTo identify the related abnormalities of gray matter in pediatric patients with Tourette syndrome (TS) by using the optimized voxel-based morphometry (VBM).Methods Three dimensional T1WI was acquired in 31 TS children (28 boys,3 girts,mean age 8 years,range 4-15 years) and 50 age- and sex-matched controls on a 1.5 Tesla Philips scanner. Images were pre-processed and analyzed using a version of VBM 2 in SPM 2.The whole brain gray matter volume was compared between the study and control group by using t-test.Multivariate linear regression analysis was used for analyzing the correlation between the change of grey matter volume within each brain region (mm3 ) and YGTSS score and course of disease of TS patients.Statistical analyses were performed by using SPSS 13.0.ResultsUsing VBM,significant increases in gray matter volumes in left superior parietal lobule, right cerebellar hemisphere and left parahippocampal gyrus were detected in TS patients,and the volume changes were 4059,2126 and 84 mm3 ( t =3.93,3.71,3.58,P ＜ 0.05 ) respectively.Compared to the control group,decreased grey matter volumes were found in medulla and left pons,and the volume changes were 213 and 117 mm3( t =3.53,3.48,P ＜ 0.05 )respectively.Tic severity was not correlated with any volume changes of gray matter in brain (P ＞ 0.05,a small volume correction,KE ≥ 10 voxel).Tic course was negatively correlated with the gray matter volume of left parahippocampal gyrus ( Beta =- 0.391,P =0.039 ).ConclusionsUsing VBM technique,the gray matter abnormalities can be revealed in TS patients without obvious lesions on conventional MR imaging.The increasing volume of temporal and parietal lobes and cerebellar may be an adaptive anatomical change in response to experiential demand. The gray matter volume of the parahippocampal gyrus may be used as one potential objective index for evaluating the prognosis of TS.

Advances of quantitative analysis methods on diffusion tensor imaging / 中国医学影像技术

Quantitative analysis on diffusion tensor imaging is prerequisite. The arithmetic of statistical analysis was reviewed in this article via analyzing the arithmetic of quantitative parameters and fiber track on diffusion tensor imaging.