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首页> 美国卫生研究院文献>Frontiers in Neuroscience >Intra- and Inter-scanner Reliability of Scaled Subprofile Model of Principal Component Analysis on ALFF in Resting-State fMRI Under Eyes Open and Closed Conditions
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Intra- and Inter-scanner Reliability of Scaled Subprofile Model of Principal Component Analysis on ALFF in Resting-State fMRI Under Eyes Open and Closed Conditions

机译：睁眼和闭眼条件下静止状态功能磁共振成像中ALFF的主分量分析的规模化子轮廓模型的扫描仪内和扫描仪间可靠性

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Scaled Subprofile Model of Principal Component Analysis (SSM-PCA) is a multivariate statistical method and has been widely used in Positron Emission Tomography (PET). Recently, SSM-PCA has been applied to discriminate patients with Parkinson's disease and healthy controls with Amplitude of Low Frequency Fluctuation (ALFF) from Resting-State Functional Magnetic Resonance Imaging (RS-fMRI). As RS-fMRI scans are more readily available than PET scans, it is important to investigate the intra- and inter-scanner reliability of SSM-PCA in RS-fMRI. A RS-fMRI dataset with Eyes Open (EO) and Eyes Closed (EC) conditions was obtained in 21 healthy subjects (21.8 ± 1.8 years old, 11 females) on 3 visits (V1, V2, and V3), with V1 and V2 (mean interval of 14 days apart) on one scanner and V3 (about 8 months from V2) on a different scanner. To simulate between-group analysis in conventional SSM-PCA studies, 21 subjects were randomly divided into two groups, i.e., EC-EO group (EC ALFF map minus EO ALFF map, n = 11) and EO-EC group (n = 10). A series of covariance patterns and their expressions were derived for each visit. Only the expression of the first pattern showed significant differences between the two groups for all the visits (p = 0.012, 0.0044, and 0.00062 for V1, V2, and V3, respectively). This pattern, referred to as EOEC-pattern, mainly involved the sensorimotor cortex, superior temporal gyrus, frontal pole, and visual cortex. EOEC-pattern's expression showed fair intra-scanner reliability (ICC = 0.49) and good inter-scanner reliability (ICC = 0.65 for V1 vs. V2 and ICC = 0.66 for V2 vs. V3). While the EOEC-pattern was similar with the pattern of conventional unpaired T-test map, the two patterns also showed method-specific regions, indicating that SSM-PCA and conventional T-test are complementary for neuroimaging studies.
机译：主成分分析的按比例缩放子轮廓模型（SSM-PCA）是一种多元统计方法，已广泛用于正电子发射断层扫描（PET）中。最近，SSM-PCA已被用于通过静止状态功能磁共振成像（RS-fMRI）来区分帕金森氏病患者和健康对照者的低频波动幅度（ALFF）。由于RS-fMRI扫描比PET扫描更容易获得，因此研究RS-fMRI中SSM-PCA在扫描仪内部和扫描仪之间的可靠性非常重要。在21次健康受试者（21.8±1.8岁，11位女性）中，通过3次就诊（V1，V2和V3），V1和V2获得了具有睁眼（EO）和闭眼（EC）条件的RS-fMRI数据集。 （平均间隔为14天）在一台扫描仪上，而V3（距V2大约8个月）在另一台扫描仪上。为了模拟常规SSM-PCA研究中的组间分析，将21位受试者随机分为两组，即EC-EO组（EC ALFF图减去EO ALFF图，n = 11）和EO-EC组（n = 10） ）。每次访问都导出了一系列协方差模式及其表达。只有第一个模式的表达在所有访问中两组之间存在显着差异（对于V1，V2和V3，分别为p = 0.012、0.0044和0.00062）。这种模式称为EOEC模式，主要涉及感觉运动皮层，颞上回，额极和视觉皮层。 EOEC模式的表达式显示出合理的扫描仪内部可靠性（ICC = 0.49）和良好的扫描仪内部可靠性（V1对V2的ICC = 0.65，V2对V3的ICC = 0.66）。尽管EOEC模式与常规不成对T检验图的模式相似，但这两种模式还显示了方法特定区域，这表明SSM-PCA和常规T检验对神经影像学研究是互补的。

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