ABSTRACT
Objective:To investigate the value of large-scale brain network research based on independent component analysis (ICA) in discovering the changes of intrinsic functional connections within and between resting-state networks (RSNs) in first-episode untreated adult patients with major depressive disorder (MDD).Methods:From January 2019 to June 2021, twenty-three patients with MDD (MDD group) and 30 healthy volunteers (HC group) matched with gender, age and years of education were selected. All participants underwent resting-state brain function imaging (rs-fMRI), and the MDD group completed the 17-item Hamilton depression scale(HAMD-17). The independent component analysis (ICA) method was used to analyze rs-fMRI data, and meaningful RSNs were obtained. SPM12 and Gift softwares were used to compare the strength of intrinsic functional connection within and between the RSNs of the MDD group and HC group, and the Pearson correlation analysis was conducted by IBM SPSS statistics 25.0 to evaluate the correlation between the functional connection strength and HAMD-17 scores in MDD group.Results:Compared with the HC group, intrinsic functional connection strength of medial prefrontal cortex (mPFC) (MNI: x, y, z=-6, 54, 25)in MDD group was significantly enhanced, while the intrinsic functional connection strength of the left angular gyrus (AG) (MNI: x, y, z=-48, -66, 21), the left precuneus (PCu) (MNI: x, y, z=-6, -63, 33), the left dorsolateral prefrontal cortex (dlPFC) (MNI: x, y, z=-36, 12, 51)and the right anterior insula (AI) (MNI: x, y, z=36, 21, 0)were significantly weakened. Compared with the HC group, functional connection strength between posterior default mode net work(pDMN) and anterior default mode network(aDMN) in MDD group was significantly weakened ( t=-2.206, P=0.032), and function connection strength between pDMN and left frontal parietal network(lFPN) was significantly strengthened ( t=2.318, P=0.025). In MDD group, intrinsic functional connection strength of mPFC and the functional connection strength of pDMN-lFPN were positively correlated with the HAMD-17 score ( r=0.524, P=0.010; r=0.441, P=0.035). Conclusion:Large-scale brain network study based on the ICA can find abnormal functional connections within and between RSNs in first-episode untreated adult patients with MDD, and provide objective imaging markers for the clinical diagnosis and treatment of MDD.
ABSTRACT
Objective:To investigate the value of dynamic contrast-enhanced(DCE)-MRI based textural analysis in differentiating IDH mutated high-grade gliomas from IDH gene wild types.Methods:Twenty-nine patients with high grade gliomas collected from April 2016 to December 2019 in First People's Hospital of Changzhou were assessed retrospectively, including 10 patients with IDH mutation and 19 patients with IDH gene wild type. All patients underwent DCE, conventional plain and enhanced MR scanning. Omni Kinetics software was used to perform DCE-MRI data processing, volume transfer constant (K trans), ratio constant of tracer refluxing from tissue to plasma (Kep), extravascular extracellular space per unit volume of tissue (Ve), blood plasma volume (Vp) and area under the gadolinium concentration-time curve (AUC) were obtained. Five commonly used textural features, including Energy, Entropy, Inertia, Correlation, and Inver Difference Moment (IDM), were generated based on gray-level co-occurrence matrices. The independent samples t test (normal distributionand equal variance) or Mann-Whitney rank sum test (abnormal distribution or unequal variance) was used to compare the differences in textural features of DCE-MRI parameters between IDH mutated group and IDH gene wild type group. Receiver operating characteristic (ROC) curves were used to evaluate the efficiency of textural features of DCE-MRI parameters in differentiating IDH mutated high-grade gliomas from IDH gene wild types for statistically significant textural features. Results:Entropy of K trans and Ve for IDH mutated group were 5.368±1.458 and 6.698±1.081, respectively; while the corresponding values were 7.334±1.385 and 8.213±1.320 for IDH gene wild type group, respectively. The difference between the two groups was statistically significant ( t values were-3.570, -3.113, P values were 0.001, 0.004, respectively). Inverse difference moment of K trans and Ve for IDH mutated group were 0.567±0.147 and 0.417±0.106, respectively; while for IDH gene wild type group, the values were 0.393±0.119 and 0.296±0.101, respectively. The difference between the two groups was statistically significant ( t values were 3.452, 3.014, P values were 0.002, 0.006, respectively). In all textural features, the area under the ROC curve of entropy of K trans was the largest (0.874), and the sensitivity was the highest (100%), and the specificity of IDM of Ve was the highest (94.7%). Conclusion:Textural analysis of DCE-MRI can help to differentiate IDH mutated high-grade gliomas from IDH gene wild types.