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Objective:To construct a combined radiomics model based on preoperative enhanced computed tomography (CT) examination for predicting microvascular invasion (MVI) in hepatocellular carcinoma (HCC), and provide biological explanations for the radiomics model.Methods:The retrospective cohort study was conducted. The messenger RNA (mRNA) of 424 HCC patients, the clinicopathological data of 39 HCC patients entered into the Cancer Genome Atlas database from its establishment until January 2023, and the clinicopathological data of 53 HCC patients who were admitted to the Gansu Provincial People′s Hospital from January 2020 to January 2023 were collected. The 92 HCC patients were randomly divided into a training dataset of 64 cases and a test dataset of 28 cases with a ratio of 7∶3 based on a random number table method. The CT images of patients in the arterial phase and portal venous phase as well as the corresponding clinical data were analyzed. The 3Dslicer software (version 5.0.3) was used to register the CT images in the arterial phase and portal venous phase and delineate the three-dimensional regions of interest. The original images were preprocessed and the corresponding features were extracted by the open-source software FAE (version 0.5.5). After selecting features using the Least Absolute Shrinkage and Selection Operator, the radiomics model was constructed and the radiomics score (R-score) was calculated. The nomogram was constructed by integrating clinical parameters, imaging features and R-score based on Logistic regression. The gene modules related to radiomics model were obtained and subjected to enrichment analysis by conducting weighted gene co-expression network analysis and correlation analysis. Observation indicators: (1) comparison of clinical characteristics of patients with different MVI properties; (2) establishment of MVI risk model; (3) evaluation of MVI risk model; (4) clustering of gene modules; (5) functional enrichment of feature-correlated gene modules. Measurement data with normal distribution were represented as Mean± SD, and comparison between groups was conducted using the independent sample t test. Measurement data with skewed distribution were represented as M(range), and comparison between groups was conducted using the Mann-Whitney U test. Comparison of count data was conducted using the chi-square test. The intra-/inter-class correlation coefficient (ICC) was used to assess the inter-observer consistency of radiomics feature extracted by different observers. ICC >0.75 indicated a good consistency in feature extraction. The Logistic regression model was used for univariate and multivariate analyses. The receiver operating characteristic curve was drawn, and the area under curve (AUC), the decision curve and the calibration curve were used to evaluate the diagnostic efficacy and clinical practicality of the model. Results:(1) Comparison of clinical characteristics of patients with different MVI properties. Of 92 HCC patients, there were 47 cases with MVI-positive and 45 cases with MVI-negative, and there were significant differences in hepatitis, tumor diameter, peritumoral enhancement, intratumoral arteries, pseudocapsule and smoothness of tumor margin between them ( χ2=5.308, 9.977, 47.370, 32.368, 21.105, 31.711, P<0.05). (2) Establishment of MVI risk model. A total of 1 781 features were extrac-ted from arterial and portal venous phases of the intratumoral and peritumoral regions. After feature dimension reduction, 8 radiomics features were selected from arterial and portal venous phases to construct the combined model. Results of multivariate analysis showed that peritumoral enhancement, intratumoral arteries, pseudocapsule, smoothness of tumor margins, and R-score were independent risk factors for MVI in patients with HCC [ hazard ratio=0.049, 0.017, 0.017, 0.021, 2.539, 95% confidence interval ( CI) as 0.005-0.446, 0.001-0.435, 0.001-0.518, 0.001-0.473, 1.220-5.283, P<0.05]. A nomogram model was constructed incorporating peritumoral enhancement, intratumoral arteries, pseudocapsule, smoothness of tumor margins, and R-score. (3) Evaluation of the MVI risk model. The AUC of radiomics model was 0.923 (95% CI as 0.887-0.944) and 0.918 (95% CI as 0.894-0.945) in the training dataset and test dataset, respectively. The AUC of nomogram model, incorpora-ting both the R-score and radiomics features, was 0.973 (95% CI as 0.954-0.988) and 0.962 (95% CI as 0.942-0.987) in the training dataset and test dataset, respectively. Results of decision curve showed that the nomogram had better clinical utility compared to the R-score. Results of calibration curve showed good consistency between the actual observed outcomes and the nomogram or the R-score. (4) Clustering of gene module. Results of weighted gene co-expression network analysis showed that 8 gene modules were obtained. (5) Functional enrichment of feature-related gene modules. Results of correlation analysis showed 4 gene modules were significantly associated with radiomics features. The radiomics features predicting of MVI may be related to pathways such as the cell cycle, neutrophil extracellular trap formation, and PPAR signaling pathway. Conclusions:The combined radiomics model based on preoperative enhanced CT imaging can predict the MVI status of HCC. By obtaining mRNA gene expression profiles associated with radiomics features, a biological interpretation of the radiomics model is provided.
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Objective:To investigate the abnormal patterns of spontaneous neural activity of patients with type 2 diabetes comorbid depression (T2DD) by using resting-state functional magnetic resonance imaging (rs-fMRI) fractional amplitude of low-frequency (fALFF) analysis, and determine the neuroimaging features of brain damage in T2DD patients.Methods:A perspective study was performed. Fifty-nine type 2 diabetes mellitus (T2DM) patients and 52 T2DD patients, admitted to and accepted treatment in Department of Endocrinology of our hospital from November 2017 to November 2020, were chosen; another 57 healthy controls matched with gender, age and education level, admitted to our hospital at the same time period were enrolled. Their clinical data, neuropsychological test and rs-fMRI data were collected; whole brain fALFF values were calculated, and fALFF values of different brain regions were compared in subjects of the 3 groups. Pearson correlation analysis was used to verify the correlations of fALFF values with clinical variables and neuropsychological scale scores.Results:The fALFF values in bilateral precuneus showed significant difference among the three groups ( P<0.05). The fALFF values in bilateral precuneus of the T2DD and T2DM groups were significantly lower than those in heathy control group ( P<0.05), and those in the T2DD group were lower than those in the T2DM group without significant difference ( P>0.05). Pearson correlation analysis showed that there were no correlations of fALFF values with clinical data and psychometric scale scores in T2DD group and T2DM group ( P>0.05). Conclusion:The abnormal patterns of spontaneous brain activity in the bilateral precuneus may be the neuroimaging markers of brain damage in T2DD patients.
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Objective@#To investigate the alterations of the cerebral resting-state spontaneous neural activity in colorectal cancer patients with depressive symptoms.@*Methods@#Thirty-three colorectal cancer patients (patient group) with depression and 43 healthy subjects (control group) underwent the resting state functional magnetic resonance imaging (rs-fMRI). The amplitude of low-frequency fluctuations (ALFF) and fractional ALFF (fALFF) were calculated. Two independent samples t test were used to compare the ALFF and fALFF values between two groups by DPABI software, and then correlation analysis was performed between ALFF and fALFF with statistical significance and Patient Health Questionnaire (PHQ-9) scores and Generalized Anxiety Disorder (GAD-7) scores.@*Results@#Compared with the control group, the patient group showed significantly lower ALFF and fALFF values in the bilateral precuneus, calcarine gyrus, lingual gyrus, left cuneus, superior, middle, inferior occipital gyrus and right fusiform gyrus (t=-5.730, P<0.05; t=-4.872, P<0.05). There were no significant correlations between the ALFF and fALFF values in these regions and PHQ-9 or GAD-7 scores (P>0.05).@*Conclusion@#Spontaneous decrease of neural activity in occipital and parietal lobes exists in colorectal cancer patients with depression at resting-sate, which may be a potential neurobiological marker.
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Objective To investigate the changes of microstructure and blood perfusion of thalamus and basal ganglia in patients with untreated depressive disorder using diffusion kurtosis imaging (DKI) and three-dimensional arterial spin labeling (3D ASL) perfusion imaging.Methods Totally 21 untreated patients with depressive disorder (disease group) and 32 healthy volunteers (control group) underwent DKI,3D ASL and routine MR scanning were enrolled.DKI parameters (mean kurtosis [MK],axial kurtosis [Ka],radial kurtosis [Kr],fractional anisotropy [FA],mean diffusivity [MD],axial diffusivity [Da] and radial diffusivity [Dr]) and 3D ASL parameters (cerebral blood flow [CBF]) of bilateral heads of caudate nucleus,thalamus and putamens were measured and compared between the 2 groups.Results Compared with control group,Ka of left caudate head in disease group was significantly higher,while Kr was significantly lower (both P＜ 0.05).Ka of right putamens in disease group was significantly higher than that in control group (P＜0.05).Compared with control group,CBF of left caudate head and bilateral putamens decreased significantly in disease group (all P＜0.05).Conclusion Untreated depressed patients show abnormal DKI parameters and blood perfusion in basal ganglia,which indicating that microstructure integrity is impaired and blood perfusion decreases.The abnormalities in basal ganglia microstructure and blood perfusion may serve as one of the neuroimaging features of depressive disorders.
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OBJECTIVE: Bipolar disorder (BD) is often misdiagnosed as unipolar depression (UD), leading to mistreatment and poor clinical outcomes. However, little is known about the similarities and differences in subcorticalgray matter regions between BD and UD. METHODS: Thirty-five BD patients, 30 UD patients and 40 healthy controls underwent diffusional kurtosis imaging (DKI) and three dimensional arterial spin labeling (3D ASL). The parameters including mean kurtosis (MK), axial kurtosis (Ka), radial kurtosis (Kr), fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (Da), radial diffusivity (Dr) and cerebral blood flow (CBF) were measured by using regions-of-interest analysis in the caudate, putamen and thalamus of the subcortical gray matter regions. RESULTS: UD exhibited differences from controls for DKI measures and CBF in the left putamen and caudate. BD showed differences from controls for DKI measures in the left caudate. Additionally, BD showed lower Ka in right putamen, higher MD in right caudate compared with UD. Receiver operating characteristic analysis revealed the Kr of left caudate had the highest predictive power for distinguishing UD from controls. CONCLUSION: The two disorders may have overlaps in microstructural abnormality in basal ganglia. The change of caudate may serve as a potential biomarker for UD.