Evaluating the Changes of White Matter Microstructures in Tobacco Addicts Based on Diffusion Tensor Imaging

Abstract

Departmental sources Background: The tract-based spatial statistics (TBSS) method was used to investigate the changes of white matter microstructure in tobacco addicts, and to analyze its correlation with smoking index, smoking years, and daily smoking amount. Material/Methods: Routine magnetic resonance imaging (excluding intracranial lesions) and diffusion tensor imaging (DTI) sequence scanning were performed in 156 nicotine addicts (nicotine dependence group) and 81 non-nicotine addicts (control group) recruited from the study group. TBSS method was used to preprocess DTI data, and age and education level were taken as covariables to statistically analyze relevant parameters between nicotine dependence group and control group, such as fractional anisotropy (FA) value and smoking index. Spearman correlation analysis was performed on smoking status and FA values in brain regions with significant differences between nicotine dependent group and control group, and the test level a was 0.05. Results: Compared with control group, FA values of white matter in part of the posterior limb of the right inner capsule (r=-0.428, P=0.003), the right superior radiating crown (r=-0.136, P=0.004), the right posterior radiating crown (r=-0.229, P=0.003), the right superior longitudinal bundle (r=-0.474, P=0.002), the right inferior longitudinal bundle (r=-0.354, P=0.003) and the inferior frontal occipital bundle (r=-0.310, P=0.002) were decreased, which were negatively correlated with smoking index (P<0.05). Conclusions: Nicotine can damage the microstructure of white matter in specific brain regions and damage neurons, with cumulative effects.

Tobacco and Nervous System Development and Function—New Findings 2015–2020

“…The study revealed significant, system-specific effects of perinatal exposure to secondhand smoke on sensory brain structures later in life [ 14 ]. Similarly, in a magnetic resonance imaging study, nicotine potential of destruction to white matter and neurons was confirmed [ 68 ]. Moreover, nicotine deprivation in smokers was associated, in an MRI study, with lower brain activity in its areas responsible for attention contrary to areas involved with craving, which showed lower activity when nicotine was present [ 69 ].…”

Multi‐level prediction of substance use: Interaction of white matter integrity, resting‐state connectivity and inhibitory control measured repeatedly in every‐day life

“…Our study is the first to integrate white matter microstructural integrity into the multiple levels of impairment that SUD patients exhibit in Low FA values typically reflect low coherence of the linear microstructure of white matter tracts. 42 As presumed outcomes of the toxic effect of substance use, studies demonstrated that FA values decrease with heavy 43 or long-term drinking, 44 continued smoking 45 and cannabis use 46 generally with lower scores being linked to poorer clinical outcomes. In our study, lower FA values in clusters encompassing the callosal genu and body and the bilateral anterior corona radiata were linked to poorer mean inhibition performance assessed via mobile Stroop testing in the SUD sample.…”

The impact of levamisole and alcohol on white matter microstructure in adult chronic cocaine users

“…Consistently, we included-apart from age, sex, ADHD and ICV-MDMA and nicotine in all models, as it has been shown that MDMA can alter GM and WM integrity, 88 whereas nicotine alters WM microstructure. 89,90 These models are likely to illustrate WM alterations by the particular substances compared with HC. Yet, as HC did not consume cocaine or levamisole, we could not enter all three variables (alcohol, cocaine and levamisole) in one statistical model to assess the strongest impact on WM integrity by a particular substance by this comparison.…”

“…Here, we adjusted for age, sex, ADHD, nicotine, MDMA, ICV, alcohol and cocaine use. Model 3: Testing for the influence of alcohol on WM integrity. Here, we adjusted for age, sex, ADHD, nicotine, MDMA, ICV, levamisole and cocaine use. Consistently, we included—apart from age, sex, ADHD and ICV—MDMA and nicotine in all models, as it has been shown that MDMA can alter GM and WM integrity, 88 whereas nicotine alters WM microstructure 89,90 …”

“…Consistently, we included—apart from age, sex, ADHD and ICV—MDMA and nicotine in all models, as it has been shown that MDMA can alter GM and WM integrity, 88 whereas nicotine alters WM microstructure. 89 , 90 …”