Identifying Methamphetamine Dependence Using Regional Homogeneity in BOLD Signals
Identifying Methamphetamine Dependence Using Regional Homogeneity in BOLD Signals
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DOI：
10.1155/2020/3267949
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发表时间：
2020-05
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影响因子：
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通讯作者：
Hufei Yu;Shucai Huang;Xiaojie Zhang;Qiuping Huang;Jun Liu;Hong-xian Chen;Yan Tang
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作者：
Hufei Yu;Shucai Huang;Xiaojie Zhang;Qiuping Huang;Jun Liu;Hong-xian Chen;Yan Tang
甲基苯丙胺是一种高度成瘾性的毒品，滥用后会引起一系列精神和身体上的异常后果。本文旨在研究区域同质性异常（ReHo）是否可以使用机器学习方法区分甲基苯丙胺依赖（MAD）个体与对照受试者的有效特征。我们利用静息态fMRI测量了41名MAD患者和42名年龄和性别匹配的对照组的区域同质性，发现与对照组相比，MAD患者的右侧内侧上级额回的ReHo值较低，但右侧颞下梭状回的ReHo值较高。此外，AdaBoost分类器，一个非常有效的机器学习集成学习，被用来从具有异常ReHo值的对照受试者中分类MAD个体。通过使用留一法交叉验证方法，我们得到了超过84.3%的准确率，这意味着我们几乎可以通过机器学习方法在ReHo值上区分MAD个体和对照受试者。总之，我们的研究结果表明，AdaBoost分类器-神经影像学方法可能是一种很有前途的方法来发现一个人是否已经对甲基苯丙胺成瘾，同时，本文还表明，静息态fMRI应该被认为是一种生物标志物，一种无创的和有效的辅助工具来评估MAD。
Methamphetamine is a highly addictive drug of abuse, which will cause a series of abnormal consequences mentally and physically. This paper is aimed at studying whether the abnormalities of regional homogeneity (ReHo) could be effective features to distinguish individuals with methamphetamine dependence (MAD) from control subjects using machine-learning methods. We made use of resting-state fMRI to measure the regional homogeneity of 41 individuals with MAD and 42 age- and sex-matched control subjects and found that compared with control subjects, individuals with MAD have lower ReHo values in the right medial superior frontal gyrus but higher ReHo values in the right temporal inferior fusiform. In addition, AdaBoost classifier, a pretty effective ensemble learning of machine learning, was employed to classify individuals with MAD from control subjects with abnormal ReHo values. By utilizing the leave-one-out cross-validation method, we got the accuracy more than 84.3%, which means we can almost distinguish individuals with MAD from the control subjects in ReHo values via machine-learning approaches. In a word, our research results suggested that the AdaBoost classifier-neuroimaging approach may be a promising way to find whether a person has been addicted to methamphetamine, and also, this paper shows that resting-state fMRI should be considered as a biomarker, a noninvasive and effective assistant tool for evaluating MAD.