title: Assessment of in vivo microstructure alterations in gray matter using DKI in Internet gaming addiction.
abstract: BACKGROUND
  The aim of the current study was to investigate the utility of diffusional kurtosis imaging (DKI) in the detection of gray matter (GM) alterations in people suffering from Internet Gaming Addiction (IGA).
  
  
  METHODS
  DKI was applied to 18 subjects with IGA and to 21 healthy controls (HC). Whole-brain voxel-based analyses were performed with the following derived parameters: mean kurtosis metrics (MK), radial kurtosis (K⊥), and axial kurtosis (K//). A significance threshold was set at P <0.05, AlphaSim corrected. Pearson's correlation was performed to investigate the correlations between the Chen Internet Addiction Scale (CIAS) and the DKI-derived metrics of regions that differed between groups. Additionally, we used voxel-based morphometry (VBM) to detect GM-volume differences between the two groups.
  
  
  RESULTS
  Compared with the HC group, the IGA group demonstrated diffusional kurtosis parameters that were significantly less in GM of the right anterolateral cerebellum, right inferior and superior temporal gyri, right supplementary motor area, middle occipital gyrus, right precuneus, postcentral gyrus, right inferior frontal gyrus, left lateral lingual gyrus, left paracentral lobule, left anterior cingulate cortex, and median cingulate cortex. The bilateral fusiform gyrus, insula, posterior cingulate cortex (PCC), and thalamus also exhibited less diffusional kurtosis in the IGA group. MK in the left PCC and K⊥ in the right PCC were positively correlated with CIAS scores. VBM showed that IGA subjects had higher GM volume in the right inferior and middle temporal gyri, and right parahippocampal gyrus, and lower GM volume in the left precentral gyrus.
  
  
  CONCLUSIONS
  The lower diffusional kurtosis parameters in IGA suggest multiple differences in brain microstructure, which may contribute to the underlying pathophysiology of IGA. DKI may provide sensitive imaging biomarkers for assessing IGA severity.
authors.forename: Yawen
authors.initials: Y
authors.lastname: Sun
authors.forename: Jinhua
authors.initials: J
authors.lastname: Sun
authors.affiliation: Department of Radiology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, P,R, China. clare1475@hotmail.com.
authors.forename: Yan
authors.initials: Y
authors.lastname: Zhou
authors.forename: Weina
authors.initials: W
authors.lastname: Ding
authors.forename: Xue
authors.initials: X
authors.lastname: Chen
authors.forename: Zhiguo
authors.initials: Z
authors.lastname: Zhuang
authors.forename: Jianrong
authors.initials: J
authors.lastname: Xu
authors.forename: Yasong
authors.initials: Y
authors.lastname: Du
mesh_terms: D000293:Adolescent; D000328:Adult; D016739:Behavior, Addictive / Q000473:pathology* / Q000523:psychology*; D039721:Diagnostic and Statistical Manual of Mental Disorders; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods; D005260:Female; D066128:Gray Matter / Q000473:pathology*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D020407:Internet; D008297:Male; D011569:Psychiatric Status Rating Scales; D018910:Video Games / Q000523:psychology*; D055815:Young Adult