4.4 Article

Hippocampal and striatal gray matter volume are associated with a smoking cessation treatment outcome: results of an exploratory voxel-based morphometric analysis

期刊

PSYCHOPHARMACOLOGY
卷 210, 期 4, 页码 577-583

出版社

SPRINGER
DOI: 10.1007/s00213-010-1862-3

关键词

Smoking; VBM; Grey matter volume; MRI; Smoking cessation; Hippocampus

资金

  1. Vector Tobacco Co.
  2. NIDA [K23DA017261]

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Compared to nonsmokers, smokers exhibit a number of potentially important differences in regional brain structure including reduced gray matter (GM) volume and/or density in areas including frontal and cingulate cortices, thalamus, and insula. However, associations between brain structure and smoking cessation treatment outcomes have not been reported. In the present analysis we sought to identify associations between regional GM volume-as measured by voxel-based morphometry (VBM)-and a smoking cessation treatment outcome (point prevalence abstinence at 4 weeks). Adult smokers underwent high-resolution anatomical MRI scanning prior to an open label smoking cessation treatment trial. VBM was conducted in SPM5 using the DARTEL algorithm and relapser vs. quitter groups were compared using independent sample t tests (p < 0.001, uncorrected). Analyses controlled for potentially confounding factors including years smoked, cigarettes per day, total intracranial volume (TIV), and sex. Of 18 smokers, 8 achieved a 4-week point prevalence abstinence, confirmed by CO level (a parts per thousand currency sign8 ppm). After controlling for all covariates, compared to relapsers, quitters had significantly higher GM volume in the left putamen and right occipital lobe, while also significantly lower GM volume in bilateral hippocampus and right cuneus. These preliminary results suggest that maintaining smoking abstinence is associated with higher pre-quit brain volume in regions that subserve habit learning and visual processing, and lower brain volume in regions that subserve long-term memory processes and visual information processing. Future, large-scale studies can determine whether brain structure variables can serve as clinically useful predictors of smoking cessation treatment outcome.

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