http://med-sci.cn/cgzcx/en/contents_list.asp?issue=202207 zh-cn An RSS feed for Chinese Journal of Magnetic Resonance Imaging http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2022.07.001 Wed,20 Jul 2022 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2022.07.002 ^,s Hospital and the TCGA/TCIA (The Cancer Genome Atlas and The Cancer Imaging Archive) common dataset were retrospectively collected. The above three data sets were integrated, their images were resampling and normalized, and then randomly divided into the training set and the test set in a ratio of 7∶3. A total of 1702 radiomics features of the post-contrast enhanced T1-weighted sequence (CE-T1) and the T2-weighted fluid attenuation inversion recovery sequence (T2-FLAIR) were extracted from preoperative MRI images. Feature selection was performed by single-factor logistic regression (LR), and then performed by least absolute shrinkage and selection operator (LASSO). In order to solve the shortage of minority samples and improve the universality of the model, the synthetic minority oversampling technique (SMOTE) was used to balance the training set, and then multi-factor LR was used for modeling. Finally, the performance and goodness of fit of the model was verified using receiver operating characteristic curve (ROC) and calibration curve, and a nomogram was established for visual risk prediction. Results: There were no statistically significant differences in the clinical characteristics of the two subtypes in the training set and test set (P＜0.05). The area under the curve (AUC) of the radiomics model in the training set and the test set were 0.842 and 0.935, respectively, and the F-Measure were 0.965 and 0.942, respectively. The P value of the Hosmer-Lemeshow test of the calibration curve of the training set was 0.1393. Conclusions: The preoperative MRI radiomics model can predict the subtype of IDH mutation combined with MGMT promoter methylation in LGGs, thus providing auxiliary guidance value for LGGs in molecular subtype diagnosis, temozolomide (TMZ) treatment decision-making and survival prediction.]]> Wed,20 Jul 2022 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2022.07.003 Wed,20 Jul 2022 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2022.07.004 Wed,20 Jul 2022 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2022.07.005 ^,s Hospital from January 2015 to October 2021 were retrospectively analyzed, and then these data were randomly divided into training sets (n=141) and test sets (n=36) at a ratio of 8∶2. The three-dimensional volume region of interest of the tumor was manually delineated on the axial ADC, T1WI and T2WI images, and radiomics features were extracted; the variance threshold method, analysis of variance (ANOVA) and least absolute shrinkage and selection operator (LASSO) based on 5-fold cross validation were used to single out the most valuable radiomic features, and these selected features were combined with two classifiers, logistic regression (LR) and support vector machine (SVM), for training the models, and then the models were verified in the test sets. ROC curve was drawn to evaluate the efficacy of LR and SVM models in differentiating PA from BCA. In addition, the Delong Test was used to compare the models, and the decision curve and calibration curve were used to evaluate the models. Results: A total of 15, 3, 15 and 23 optimal features were obtained from ADC, T1WI, T2WI and combined sequence (ADC+T1WI+T2WI) image respectively. In the training set, the area under the curve (AUC) of the LR and SVM models constructed based on the ADC map, T1WI map, T2WI map, and joint model were 0.955, 0.961, 0.812, 0.813, 0.939, 0.949, 0.994, 0.995, respectively. The AUC values of the LR model constructed based on ADC, T1WI, T2WI and combined sequence image for differential diagnosis of PA and BCA were 0.906, 0.780, 0.868 and 0.972, respectively, and the AUC values of the SVM model were 0.924, 0.783, 0.847 and 0.959, respectively. In the training sets, the combined sequence models were better than the T1WI or T2WI-based radiomics models (P＜0.05), and there was no significant difference between the combined sequence models and the ADC-based radiomics models (P＞0.05), the accuracy, sensitivity and specificity of the combined sequence models were 98.6%-98.7%, 96.4%-98.4%, 98.8%-99.4% respectively, the accuracy, sensitivity and specificity of the ADC radiomics models were 91.4%-91.8%, 75.0%-79.7%, 95.7%-98.1% respectively. In the test sets, there was no significant difference in AUC between the models (P＞0.05). Conclusions: The combined sequence models and ADC-based radiomics models were better than the T1WI and T2WI-based radiomics models in differentiating pleomorphic adenoma and basal cell adenoma. Compared with ADC-based radiomics models, the combined sequence models had higher accuracy, sensitivity and specificity.]]> Wed,20 Jul 2022 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2022.07.006 Wed,20 Jul 2022 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2022.07.007 Wed,20 Jul 2022 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2022.07.008 Wed,20 Jul 2022 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2022.07.009 Wed,20 Jul 2022 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2022.07.010 ^,s Hospital of Nanjing Medical University, including EBOTs (n=72) and MEOTs (n=153) were enrolled. According to the ratio of 8∶2,all cases were randomly divided into the training group (n=153) and validation group (n=39). We used T2WI to manually delineated ROI and extract radiomics features. Mann-Whitney U test, correlation and LASSO regression were used to select features, and then constructed radiomics model by these features, used to calculate Radscore. Combining Radscore with clinic factors, we used multiple logistic regression to construct radiomics nomogram. ROC curve, calibration curve and decision curve analysis and correction were used to evaluate the clinical value of radiomics nomogram. Results: We reserved 10 radiomics features after the feature was filtered. The AUC of the radiomics nomogram which combined HE4 with Radscore in the training group and validation group (training group: 0.947, validation group: 0.914) were higher than those of the single radiomics model (training group:0.925, validation group:0.819). ROC and DCA results showed that the radiomics nomogram had higher reliability. Conclusions: The radiomics nomogram combined radiomics feature based on T2WI and clinical factors is able to distinguish between BEOTs and MEOTs intuitively and accurately and provide guidance for the next clinical decision.]]> Wed,20 Jul 2022 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2022.07.011 Wed,20 Jul 2022 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2022.07.012 Wed,20 Jul 2022 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2022.07.013 Wed,20 Jul 2022 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2022.07.014 ^, local and global efficiency were significantly and the clustering coefficient were significantly lower than that of healthy controls (P＜0.05), and the characteristic path length was significantly higher than that of healthy controls (P＜0.05). There was no significant difference between the two groups in the small-worldness. Conclusions: We revealed the abnormal topological organization of WM network in SSD, suggesting that the brain^,s ability to integrate information and the interconnection between local regions were weakened, which may be related to the abnormality of self-perception and body perception function in patients with SSD. This study may improve our understanding of the neural mechanism of SSD from the WM topological organization level.]]> Wed,20 Jul 2022 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2022.07.015 ^,s disease (PD) patients with freezing of gait (FOG) by resting-state functional magnetic resonance imaging (rs-fMRI) and to explore the pathological mechanism of FOG. Materials and Methods: A total of 17 patients with PD with FOG (FOG+ ), 36 patients with PD without FOG (FOG-), and 44 healthy controls (HC) were recruited. All subjects underwent rs-fMRI scanning. Calculate the DC values of FOG+, FOG-and HC from the resting-state data. The brain regions with statistically significant difference among the three groups were obtained by F test. Two sample t-test was used to compare the differences among FOG+, FOG- and HC. The results were assigned thresholds at P＜0.001 (voxel level) and Familywise error rate (FWE) corrected to P＜0.05 at the cluster level and cluster size＞20. The DC values of brain regions with statistically significant differences among groups were extracted and correlated with the scores of 17-item Hamilton Rating Scale for Depression (HAMD-17) and FOG questionnaire. Results: The results showed that the main effects among the three groups were in the right anterior central gyrus, the right posterior central gyrus, the right insula, the right medial frontal gyrus, the right superior parietal lobule, and the right frontal lobe sub-gyral. Further two-sample analysis showed that compared with the HC group, DC value in the FOG+ group significantly decreased in the right medial frontal gyrus, left precentral gyrus, and right superior temporal gyrus; However, in the left superior frontal gyrus and the right superior frontal gyrus, there was a significant increase. Compared with the HC group, DC value in the FOG group increased significantly in the left superior frontal gyrus, right cerebellar Ⅸ lobule area, and decreased significantly in the right central posterior gyrus, left central posterior gyrus, right superior frontal gyrus, left central anterior gyrus and left external nucleus. In addition, the correlation analysis showed that the FOG questionnaire score of the FOG+ group was positively correlated with the DC values of the left precentral gyrus and the right superior temporal gyrus (r=0.574, P=0.020; r=0.506, P=0.046); HAMD-17 score was positively correlated with right medial frontal gyrus (r=0.547, P=0.028). Conclusions: The abnormal DC values of the frontal lobe, anterior central gyrus, posterior central gyrus, temporal lobe, and cerebellum in PD patients may be closely related to the brain dysfunction of FOG+.]]> Wed,20 Jul 2022 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2022.07.016 ^,s disease (PD) with depression. Materials and Methods: Forty-five PD patients [twenty-two Parkinson^,s disease with depression (PD-Dep) patients, twenty-three Parkinson^,s disease patients without depression (PD-NDep) patients] and twenty-three healthy controls (HCs) were enrolled prospectively from 2020 to 2021 in the Second Hospital of Shanxi Medical University. All participants underwent resting state functional magnetic resonance imaging (rs-fMRI) scan. The progression of disease of patients was measured by 24-item Hamilton Depression Scale (HAMD-24) and Mini-Mental State Examination (MMSE) following each MRI scan. Permutation entropy (PE) was used to explore the complexity of various brain regions in the three groups. At the same time, the correlation between PE value and scale^,s score in PD-Dep group were analyzed. Results: Age, gender, education and MMSE score showed no significant differences among the three groups (P＞0.05). HAMD score in the PD-Dep group was significantly higher than that in the other two groups (P＜0.01). PE value showed significant differences in the right inferior temporal gyrus, left anterior cingulate and right median cingulate gyrus among the three groups. PE values of PD-Dep group were increased in the right median cingulate gyrus than those of PD-NDep group (P=0.007). PE values of PD-Dep group were increased in the right inferior temporal gyrus than those of HCs group (P=0.022). PE values of PD-Dep group were decreased in the left anterior cingulate gyrus than those of HCs group (P=0.007). PE values of PD-NDep group were increased in the right inferior temporal gyrus than those of HCs group (P=0.004). The PE values of PD-NDep group were decreased in the left anterior cingulate and right median cingulate gyrus than those of HCs group (P＜0.01, P=0.019). In addition, the HAMD score was significantly correlated with the PE value of the right median cingulate gyrus (P＜0.01, r=0.790). Conclusions: Permutation entropy can reflect the pathophysiological process of brain complexity changes in patients with PD-Dep. PE value in the right median cingulate gyrus may be an important indicator for evaluating disease progression. Permutation entropy may help provide reference information for early diagnosis, treatment and curative effect evaluation.]]> Wed,20 Jul 2022 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2022.07.017 Wed,20 Jul 2022 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2022.07.018 Wed,20 Jul 2022 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2022.07.019 Wed,20 Jul 2022 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2022.07.020 Wed,20 Jul 2022 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2022.07.021 Wed,20 Jul 2022 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2022.07.022 Wed,20 Jul 2022 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2022.07.026 Wed,20 Jul 2022 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2022.07.027 ^,s disease (PD) is a progressive degenerative disease of the central nervous system, characterized by brain structural change and loss of function caused by neurodystrophy. Metabolic syndrome (MS) refers to a group of interrelated cerebrovascular disease risk factors that lead to insulin resistance. In recent years, more and more studies have shown that metabolic disorders can seriously affect the induction and progression of neurodegenerative diseases. MRI is a non-invasive technique to evaluate the changes of brain structure and function. This article reviews the progress of MRI research on changes in brain structure and function and metabolic disorders in patients with PD.]]> Wed,20 Jul 2022 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2022.07.028 Wed,20 Jul 2022 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2022.07.029 Wed,20 Jul 2022 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2022.07.030 Wed,20 Jul 2022 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2022.07.031 Wed,20 Jul 2022 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2022.07.032 Wed,20 Jul 2022 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2022.07.033 Wed,20 Jul 2022 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2022.07.034 Wed,20 Jul 2022 00:00:00 GMT