RESUMO
BACKGROUND: Nicotine and illicit stimulants are very addictive substances. Although associations between grey matter and dependence on stimulants have been frequently reported, white matter correlates have received less attention. METHODS: Eleven international sites ascribed to the ENIGMA-Addiction consortium contributed data from individuals with dependence on cocaine (n = 147), methamphetamine (n = 132) and nicotine (n = 189), as well as non-dependent controls (n = 333). We compared the fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD) and mean diffusivity (MD) of 20 bilateral tracts. Also, we compared the performance of various machine learning algorithms in deriving brain-based classifications on stimulant dependence. RESULTS: The cocaine and methamphetamine groups had lower regional FA and higher RD in several association, commissural, and projection white matter tracts. The methamphetamine dependent group additionally showed lower regional AD. The nicotine group had lower FA and higher RD limited to the anterior limb of the internal capsule. The best performing machine learning algorithm was the support vector machine (SVM). The SVM successfully classified individuals with dependence on cocaine (AUC = 0.70, p < 0.001) and methamphetamine (AUC = 0.71, p < 0.001) relative to non-dependent controls. Classifications related to nicotine dependence proved modest (AUC = 0.62, p = 0.014). CONCLUSIONS: Stimulant dependence was related to FA disturbances within tracts consistent with a role in addiction. The multivariate pattern of white matter differences proved sufficient to identify individuals with stimulant dependence, particularly for cocaine and methamphetamine.
Assuntos
Cocaína , Metanfetamina , Substância Branca , Imagem de Tensor de Difusão , Humanos , Metanfetamina/efeitos adversos , Nicotina , Substância Branca/diagnóstico por imagemRESUMO
OBJECTIVES: The goal of this study is to examine the effect of contrast agent (CA) dose and diffusion coefficient on the estimation of vessel size index (VSI). MATERIALS AND METHODS: Three groups of four participants were enrolled in this study and two different experiments were performed. Different dose of CA, namely 0.1 mmol/kg and 0.05 mmol/kg were assessed in two groups of normal subjects. Diffusion coefficient effect was assessed in the third group with high-grade glioma. Imaging included gradient echo and spin-echo DSC and DTI on a 3-T MR Scanner. RESULTS: VSI estimation using half of standard dose of CA showed higher values compared to the application of standard, with a ratio of 2 for the WM and 1.5 for the GM. VSI estimates for tumor tissues (22 µm) were considerably higher compared to contra-lateral Normal-Appearing WM (NAWM, 4 µm, P < 0.01) and Normal-Appearing GM (NAGM, 8 µm, P < 0.04). DISCUSSION: Application of standard dose for CA injection and also taking into account the effect of diffusion coefficient can lead to a better correlation of VSI with previous theoretically predicted values and improvement of individual diagnostics in tumor evaluations.