Department of Physics and Astronomy, University of Georgia Franklin College of Arts and Sciences, Athens, Georgia, USA.
University of Georgia Bio-Imaging Research Center, Athens, Georgia, USA.
Brain Connect. 2023 Nov;13(9):563-573. doi: 10.1089/brain.2023.0001. Epub 2023 Sep 29.
Hypertension affects over a billion people worldwide, and the application of neuroimaging may elucidate changes brought about by the disease. We have applied a graph theory approach to examine the organizational differences in resting-state functional magnetic resonance imaging (rs-fMRI) data between hypertensive and normotensive participants. To detect these groupwise differences, we performed statistical testing using a modified difference degree test (DDT). Structural and rs-fMRI data were collected from a cohort of 52 total (29 hypertensive and 23 normotensive) participants. Functional connectivity maps were obtained by partial correlation analysis of participant rs-fMRI data. We modified the DDT null generation algorithm and validated the change through different simulation schemes and then applied this modified DDT to our experimental data. Through a comparative analysis, the modified DDT showed higher true positivity rates (TPR) when compared with the base DDT while also maintaining false positivity rates below the nominal value of 5% in nearly all analytically thresholded trials. Applying the modified DDT to our rs-fMRI data showed differential organization in the hypertension group in the regions throughout the brain including the default mode network. These experimental findings agree with previous studies. While our findings agree with previous studies, the experimental results presented require more investigation to prove their link to hypertension. Meanwhile, our modification to the DDT results in higher accuracy and an increased ability to discern groupwise differences in rs-fMRI data. We expect this to be useful in studying groupwise organizational differences in future studies.
高血压影响着全球超过 10 亿人,神经影像学的应用可能阐明该疾病带来的变化。我们应用图论方法来研究高血压和正常血压参与者的静息态功能磁共振成像(rs-fMRI)数据之间的组织差异。为了检测这些组间差异,我们使用改进的差异度检验(DDT)进行了统计检验。结构和 rs-fMRI 数据是从 52 名参与者(29 名高血压和 23 名正常血压)的队列中收集的。通过对参与者 rs-fMRI 数据的部分相关分析获得功能连接图。我们修改了 DDT 零假设生成算法,并通过不同的模拟方案验证了这种变化,然后将这种改进的 DDT 应用于我们的实验数据。通过对比分析,改进的 DDT 在与基本 DDT 相比时显示出更高的真阳性率(TPR),同时在几乎所有分析阈值试验中,假阳性率仍保持在名义值 5%以下。将改进的 DDT 应用于我们的 rs-fMRI 数据显示,高血压组在包括默认模式网络在内的整个大脑区域的组织存在差异。这些实验结果与先前的研究一致。虽然我们的发现与先前的研究一致,但所呈现的实验结果需要进一步研究来证明它们与高血压之间的联系。同时,我们对 DDT 的改进提高了准确性,并提高了在 rs-fMRI 数据中辨别组间差异的能力。我们期望这在未来的研究中对研究组间组织差异有用。