[The alterations of cerebral cortex thickness based on surface morphology and its correlation with smoking-related characteristics in severe nicotine addicts].

Objective: To explore the alterations of cerebral cortical thickness in severe nicotine addicts by using surface-based morphology (SBM) method and further analyzing the association of these changes with smoking-related characteristics. Methods: Data were retrospectively collected from August 2014 to August 2019 from severe nicotine addicts [aged 25 to 52(38±8)years] and 56 non-smokers healthy volunteers [aged 22 to 51(36±8)years]. All subjects underwent 3.0 T magnetic resonance scans, and FreeSurfer software was used to analyze the difference in cortical thickness between the two groups, and Pearson correlation analysis was used to explore the correlation between the nicotine dependence group and smoking-related characteristics. Results: Compared to control group, the severe nicotine dependence group had a significant reduction in the cortical thickness in 9 areas of the brain, the left cerebral cortex, including: middletemporal, precentral, superiorfrontal, insula [(2.78±0.10) mm vs (2.92±0.17) mm, (2.57±0.15) mm vs (2.70±0.14) mm, (2.63±0.18) mm vs (2.76±0.15) mm, (3.01±0.10) mm vs (3.13±0.13) mm, all P<0.01, respectively], and the right cerebral cortex including: temporalpole, rostralmiddlefrontal, superiorfrontal, postcentral, parsopercularis [(3.12±0.14) mm vs (3.26±0.19) mm, (2.71±0.16) mm vs (2.87±0.18) mm, (2.96±0.15) mm vs (3.10±0.20) mm, (2.57±0.15) mm vs (2.71±0.15) mm, (2.54±0.11) mm vs (2.65±0.15) mm, all P<0.05, respectively]. The cortical thickness of left insular was positively correlated with the initial smoking age (r=0.403,P=0.009), while the cortical thickness of the other brain regions had no significant correlation with smoking-related characteristics (all P>0.05). Conclusion: Significant alterations were observed in cortical thickness in severe nicotine addicts, and there is a correlation between the thickness of the left insular cortex and the age of initial smoking.

[Structural changes of brain gray matter in male long-term smokers under magnetic resonance imaging].

Objective: To evaluate gray matter structure changes in long-term male smokers by voxel-based morphological method. Methods: Fifty long-term smokers and 37 non-smoking healthy volunteers were scanned with Siemens Skyro 3.0T magnetic resonance scanner from August 2014 to August 2016. The subjects underwent routine MRI (excluding intracranial lesions) sequences and 3D-T1 structural sequences (3D-mprage). SPM8 pretreatment based on Matlab was used to analyze the structural data. All of the data were analyzed by SPM8 software. The data were compared between groups with independent sample t test. Spearman correlation analysis was used to analyze the relationship between gray matter volume (GMV) and smoking data of two groups. Results: The gray matter volume of bilateral thalamic, right supramarginal gyrus, left supramarginal gyrus and left putamen of smoking group were (0.55±0.07), (0.40±0.05), (0.48±0.07) and (0.14±0.04) voxels, respectively, and the gray matter volume of the corresponding gyri in control group were (0.61±0.09), (0.43±0.06), (0.54±0.07) and (0.16±0.03) voxels, respectively; and the gray matter volume of smoking group were all lower than those in control group (t=-3.81, -3.51, -3.86, -2.33, all P<0.05), family wise error (FWE) correction (P<0.05). The gray matter volume of bilateral thalamus, right supramarginal gyrus and left putamen was negatively correlated with smoking index (r=-0.368, -0.189, -0.274, all P<0.05), and also negatively correlated with smoking years (r=-0.391, -0.221, -0.355, all P<0.05), and bilateral thalamus gray matter volume was negatively correlated with daily cigarette smoking (r=-0.186, P<0.05). Conclusion: The changes of brain structure of smokers mainly occur on reward-related pathways and marginal systems, and related to accumulation of cigarette smoking.

[Resting-state network evaluation of chronic smokers by functional magnetic resonance imaging.]

Objective: To explore the neuromechanism of nicotine smoking, we use independent component analysis (ICA) of resting-state functional magnetic resonance imaging (fMRI) to investigate the differences of functional connectivity of resting-state networks (RSN) in chronic smokers. Methods: Forty-five chronic smokers and thirty-four age and gender matched normal nonsmoking controls experienced resting-state fMRI scanning in 3.0T MRI scanner.Differences of the function connection in each RSN between chronic smokers group and nonsmoking controls group were analyzed by SPM software which was based on Matlab platform. Results: Compared with normal nonsmoking controls, changes of functional connectivity within each RSN in chronic smokers: (1) medial visual network: functional connectivity decreased in right cuneus (t=4.17, P<0.05) and left calcarine (t=3.08, P<0.05); (2) lateral visual network: decreased in left gyrus occipital superior (t=3.42, P<0.05); (3) occipital pole visual network: decreased in right gyrus occipital medius and left gyrus occipital medius (t=3.58, P<0.05); (4) dorsal attention network (DAN): increased in right gyrus occipital superior (t=3.42, P<0.05); (5) left frontoparietal network: decreased in left inferior parietal lobe (t=3.77, P<0.05); (6) right frontoparietal network: increased in right gyrus frontalis medius (t=3.42, P<0.05). Conclusion: There are some RSNs changes of chronic smokers compared with normal nonsmoking controls, with multiple brain regions functional connectivity abnormalities.