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首页> 外文会议>Conference on Biomedical Applications in Molecular, Structural, and Functional Imaging >A multivariate pattern analysis study of the HIV-related white matter anatomical structural connections alterations
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A multivariate pattern analysis study of the HIV-related white matter anatomical structural connections alterations

机译：HIV相关白品解剖结构连接改变的多变量模式分析研究

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It's widely known that HIV infection would cause white matter integrity impairments. Nevertheless, it is still unclear that how the white matter anatomical structural connections are affected by HIV infection. In the current study, we employed a multivariate pattern analysis to explore the HIV-related white matter connections alterations. Forty antiretroviral-therapy-naieve HIV patients and thirty healthy controls were enrolled. Firstly, an Automatic Anatomical Label (AAL) atlas based white matter structural network, a 90 × 90 FA-weighted matrix, was constructed for each subject. Then, the white matter connections deprived from the structural network were entered into a lasso-logistic regression model to perform HIV-control group classification. Using leave one out cross validation, a classification accuracy (ACC) of 90% (P=0.002) and areas under the receiver operating characteristic curve (AUC) of 0.96 was obtained by the classification model. This result indicated that the white matter anatomical structural connections contributed greatly to HIV-control group classification, providing solid evidence that the white matter connections were affected by HIV infection. Specially, 11 white matter connections were selected in the classification model, mainly crossing the regions of frontal lobe, Cingulum, Hippocampus, and Thalamus, which were reported to be damaged in previous HIV studies. This might suggest that the white matter connections adjacent to the HIV-related impaired regions were prone to be damaged.
机译：众所周知，艾滋病毒感染会导致白质诚信障碍。然而，尚不清楚白品解剖结构连接如何受艾滋病毒感染的影响。在目前的研究中，我们采用了多变量模式分析来探讨艾滋病毒相关的白质连接改变。第四十四次抗逆转录病毒治疗 - 令人医期和三十个健康对照。首先，为每个受试者构建基于自动解剖标签（AAL）的白质结构网络，90×90加权矩阵。然后，进入结构网络中剥夺的白质连接被进入卢斯逻辑回归模型，以执行HIV控制组分类。使用留下交叉验证，通过分类模型获得了90％（P = 0.002）的分类精度（ACC）和0.96的接收器操作特性曲线（AUC）的区域。该结果表明，白质解剖结构连接对HIV对照组分类有很大贡献，提供了艾滋病毒感染影响白质连接的固体证据。特别是，在分类模型中选择了11个白质连接，主要在综合突出的地区横跨前叶，海马和丘脑的区域，这些地区在先前的艾滋病毒研究中据报道受损。这可能表明与艾滋病毒相关的受损区域相邻的白质连接易于损坏。

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