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Objective To investigate the application value of quantitative relaxation parameters based on synthetic MRI technology in the differential diagnosis of parotid gland tumors.Methods Conventional MRI and synthetic MRI data of 59 patients with patho-logically confirmed parotid gland tumors were analyzed retrospectively.T1,T2,and proton density(PD)values of the tumor were extracted from T1,T2 and PD mapping.The differences in quantitative relaxation parameters of pleomorphic adenomas,Warthin tumors,and malignant tumors were further compared.Diagnostic performance of each quantitative relaxation parameter was assessed and com-pared via receiver operating characteristic(ROC)curve and DeLong test.Results T2 value was significantly higher in pleomorphic adenomas than that in malignant tumors(P<0.05).The T1,T2,and PD values of pleomorphic adenomas and malignant tumors were significantly higher than those of Warthin tumors(P<0.05).The area under the curve(AUC)of the T2 value in differentia-ting pleomorphic adenomas from malignant tumors was 0.794.The AUC for T1 value(0.939)in differentiating Warthin tumors from malignant tumors was significantly higher than that of T2(0.873,P=0.341)and PD(0.927,P=0.891)values,without sta-tistically significant difference.The AUC for T2 value(0.968)in differentiating pleomorphic adenomas from Warthin tumors was significantly higher than that of T1(0.931,P=0.360)and PD(0.876,P=0.120)values,without statistically significant difference.Conclusion Quantitative relaxation parameters based on synthetic MRI technology may contribute to differentiating pleomorphic adenomas,Warthin tumors,and malignant tumors of the parotid gland.
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Objective To observe the changes in functional connectivity(FC)of raphe nucleus in patients with first-episode depression complicated with suicidal ideation(SI).Methods Ninety-eight first-episode depression patients were prospectively enrolled and assigned into SI group(n=56)or non SI group(n=42)based on complicated with SI or not,while 47 healthy volunteers were recruited as control group.Resting-state functional MRI was performed.FC between dorsal raphe nucleus(DRN),median raphe nucleus(MRN)and the whole brain were analyzed and compared among 3 groups and between each 2 groups,and the correlations of FC of different brain regions with clinical data of SI group were explored.Results Compared with control group,FC between DRN and left cerebellum and left putamen in SI group and non SI group decreased(all P<0.05),between MRN and right inferior temporal gyrus increased but between MRN and left inferior frontal gyrus,right superior occipital gyrus,left inferior parietal lobule,left putamen decreased(all P<0.05).FC between DRN and left putamen in SI group was higher than that in non SI group(P<0.05).FC between MRN and right central posterior gyrus of SI group increased compared with that in the rest 2 groups(both P<0.05).FC between MRN and left putamen in SI group was positively correlated with body mass score of Hamilton depression scale-24(HAMD-24)(rs=0.297,P=0.026).Conclusion Abnormal changes of FC between raphe nucleus and cortex,also between raphe nucleus and subcortical area occurred,and FC between MRN and left putamen positively correlated with body mass score of HAMD-24 in patients with first-episode depression complicated with SI.
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Objective:To explore the interaction effects on brain activity between the smoking addiction and weight status by resting-state functional magnetic resonance imaging.Methods:Retrospective analysis of clinical data and resting-state functional magnetic resonance imaging data were analyzed from 99 recruited subjects from January 2019 to December 2021. All participants were divided into four groups: overweight smokers ( n=24), normal-weight smokers ( n=28), overweight non-smokers ( n=19), and normal weight non-smokers ( n=28). Calculate regional homogeneity (ReHo) to reflect the internal brain activity of the subjects. Two-way ANOVA was used to detect the interaction effects between smoking addiction and overweight on ReHo by SPM12 software, correcting for age, years of education and head motion. Results:The interaction effect between smoking addiction and overweight on ReHo was significant in right superior frontal gyrus(x, y, z=15, 9, 60)(GRF corrected, Pvoxel<0.005, Pcluster<0.05). The ReHo value in the right superior frontal gyrus of overweight smokers was significantly higher than that of normal weight smokers ( t=3.768, P<0.001, Bonferroni corrected). The ReHo values in the right superior frontal gyrus of overweight non-smokers were significantly lower than those of normal weight non-smokers ( t=-3.242, P=0.002, Bonferroni corrected). The ReHo values in the right superior frontal gyurs of normal-weight smokers were significantly lower than those of normal weight non-smokers( t=-3.540, P=0.001, Bonferroni corrected). The ReHo values in the right superior frontal gyrus of overweight smokers were significantly higher than those of overweight non-smokers ( t=3.392, P=0.002, Bonferroni corrected). Correlation analyses showed that the strengthen ReHo value in right superior frontal gyrus was positively associated with pack-year in smoking addicts( r=0.387, P=0.007, Bonferroni corrected). Conclusion:Smoking addiction and overweight have an antagonistic effect on brain activity in the right superior frontal gyrus, which may provide potential therapeutic targets for individuals with comorbidity of smoking addiction and overweight.
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Objective:To investigate the alterations of resting-state functional connectivity (RSFC) in ventral tegmental area (VTA) and substantia nigra (SN) among male smokers, and its correlation with clinical characteristics of smoking.Methods:The resting-state functional magnetic resonance data of 131 subjects recruited from January 2014 to December 2018 were analyzed retrospectively, including 76 smokers (smoking group) and 55 non-smokers (control group). VTA/SN was selected as regions of interest (ROI), and then calculated RSFC between VTA/SN and the whole brain.Based on SPM12 software, independent sample t-test was conducted to compare the differences in RSFC between smoking group and control group.Based on SPSS 22.0 software, Pearson correlation analysis was used to investigate the relationships between the RSFC of brain regions with significant differences and Fagerstr?m test for nicotine dependence (FTND) score, pack-year of smokers. Results:Compared with control group, the results showed decreased RSFC between VTA and the brain regions related default mode network (DMN)(including posterior cingulate cortex, right anterior cuneiform lobe, bilateral superior temporal gyrus, right middle temporal gyrus and right inferior parietal lobule), and regions of limbic system(including right marginal lobe and right angular gyrus), right calcarine (MNI: x, y, z=24, -55, -14) and left insula(MNI: x, y, z=-35, -11, 9) in smoking group(GRF corrected, voxel level P<0.005, cluster level P<0.05). Taking SN as the seed, there was no significant difference between smoking group and control group ( P>0.05). RSFC of VTA-left superior temporal gyrus was positively correlated with pack-year( r=0.243, P=0.034) and FTND ( r=0.282, P=0.014). VTA-left insula RSFC was positively correlated with FTND ( r=0.316, P=0.006). Conclusion:The RSFC in the mesolimbic system and the VTA-DMN circuit exist abnormal changes in smokers.To some extent, it may explain the reward deficits and dysfunction of emotion regulation in smokers, which may provide clues for further understanding the mechanism of tobacco addiction.
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Objective:To investigate the value of the 8-channel eye surface phased array coil in improving image quality and demonstrating ocular masses on 3.0 T MR scanner.Methods:From July 2018 to January 2020, the data of orbital MRI in 692 patients with ocular masses on 6 medical centers were prospectively collected. The patients were simple randomly assigned into 8-channel eye surface phased array coil group (413 patients) or 8-channel head phased array coil group (279 patients), with the same MRI sequences. The signal to noise ratio (SNR) and contrast to noise ratio (CNR) were calculated in orbital anatomy structures and masses (eyelid mass, intraocular mass, lacrimal mass and orbital mass). The image quality scores including motion artifact, mass margin, the relationship between the mass and adjacent structures, and overall image quality were recorded. The differences of image quality between the two groups were compared by two independent sample t-test or Wilcoxon rank test. Results:The SNR and CNR were higher in eye surface coil group than those in head coil group ( P<0.05). The scores of ocular movement artifacts were higher in head coil group than those in surface coil group ( P<0.05). The scores of intraocular mass margin, the relationship between the mass and adjacent structures, and overall image quality were higher in surface coil group than those in head coil group ( P<0.001). There were no significant differences in mass margin, the relationship between the mass and adjacent structures, and overall image quality scores of eyelid, lacrimal gland, and orbital mass between the two groups ( P>0.05). Conclusion:3.0 T MR scanner combined with the 8-channel eye surface phased array coil can improve the SNR and CNR of orbital MR images, the demonstration of the intraocular mass margin and the relationship between the mass and adjacent structures.
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Objective:To investigate the changes in dynamic functional connectivity density (dFCD) and its relationship with Fagerstr?m test for nicotine dependence (FTND) scores in individuals with smoking addiction based on functional MR.Methods:The clinical and imaging data of 176 volunteers recruited through wechat and other online platforms from September 2019 to December 2020 in the First Affiliated Hospital of Zhengzhou University were retrospectively analyzed. The 176 volunteers were male, aged 20 to 55 years old, and were divided into light smoking addiction group (59 cases), heavy smoking addiction group (61 cases) and control group (56 cases). All subjects underwent resting state functional MR scanning and dFCD was calculated. The dFCD values of three groups were analyzed by ANOVA analysis (GRF corrected, voxel level P<0.005, cluster level P<0.01). Bonferroni correction was used for pairwise comparison. Pearson partial correlation analysis was used to analyze the correlation between dFCD values of brain regions with statistically significant differences and FTND scores. Results:Differences in dFCD among light smoking addiction group, heavy smoking addiction group and control group were mainly distributed in the right orbitofrontal cortex, left caudate nucleus, right putamen, bilateral calcarine sulcus cortex, right cuneus, left parahippocampal gyrus, left precuneus, left middle temporal gyrus and bilateral thalamus (GRF corrected, voxel level P<0.005, cluster level P<0.01). Compared with the control group, both the light and heavy smoking addiction groups showed decreased dFCD in the bilateral calcarine sulcus cortex, right cuneus and left precuneus, as well as increased dFCD in the right orbitofrontal cortex, right putamen, left caudate nucleus and left thalamus (Bonferroni corrected, P<0.05). Compared with the control group, the heavy smoking addiction group showed increased dFCD in the right thalamus, and the light smoking addiction group showed decreased dFCD in the left middle temporal gyrus (Bonferroni corrected, P<0.001). Compared with the light smoking addiction group, the heavy smoking addiction group showed increased dFCD in the left middle temporal gyrus and right thalamus, and decreased dFCD in the left parahippocampal gyrus (Bonferroni corrected, P<0.05). The mean value of dFCD in the right thalamus was positively correlated with FTND scores in smoking addiction patients ( r=0.227, P=0.014), and the mean value of dFCD in the right thalamus of the heavy smoking addiction subgroup was positively correlated with FTND scores ( r=0.323, P=0.013). There was no correlation between FTND scores and dFCD in the right thalamus of the light smoking addiction group ( P>0.05). Conclusion:There are changes of neural activity in brain regions related to smoking behaviors among people with different severity of smoking addiction, and smoking behaviors of people with heavy smoking addiction tend to be habitual compared with those with light smoking addiction.
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Objective To observe the value of zero echo time(ZTE)3.0T MRI for detecting lung cancer nodules.Methods Totally 126 lung cancer patients(176 lung nodules)were prospectively enrolled and underwent 3.0T MR axial lung scanning,including T1-volumetric interpolated breath-hold examination(VIBE),T2-BLADE,T2-half-Fourier acquisition single-shot turbo spin-echo(HASTE)and ZTE sequences.The consistency between ZTE MRI and previous CT for displaying characteristics of pulmonary nodules was analyzed,and the sensitivity of different MR sequences for detecting pulmonary nodules were observed.Results Among 176 pulmonary nodules showed on CT,ZTE MRI detected 140 and missed 36 ones.The consistency between ZTE MRI and CT for displaying the maximum diameter and actual maximum diameter of pulmonary nodules were both good(ICC=0.954,0.943,both P<0.001),and the difference between ZTE MRI and CT was small.The consistency between ZTE MRI and CT for displaying tracheal vascular bundles,pleural indentation and internal bronchial inflation signs were all good(Kappa=0.894,0.912,0.917),while for displaying the type and shape of nodules were both moderate(Kappa=0.661,0.501).The sensitivity of ZTE MRI for detecting pulmonary nodules was higher than that of other individual MR sequences(all P<0.05),of combination of ZTE and T2 BLADE was higher than that of other sequence combinations(all P<0.05).Conclusion ZTE 3.0T MRI could be used to detect lung cancer nodules,which was superior to conventional MRI.Combination of ZTE 3.0T MRI with T2-BLADE could improve the sensitivity for detecting pulmonary nodules.
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Objective:To investigate the diagnostic value of X-ray mammography, ultrasound and MRI in breast cancer with silicone implants.Methods:The clinical and imaging data of 20 patients with breast cancer in women with silicone implants in the First Affiliated Hospital of Zhengzhou University from March 2014 to October 2021 were analyzed retrospectively. The mammography, ultrasound and MRI findings were analyzed, and the differences in detection rate, diagnostic accuracy and omission diagnostic rate of breast cancer in women with implants were compared among the three imaging methods.Results:Compared with mammography, both ultrasound and MRI were able to display the prosthesis and breast lesions completely. There were significant differences in detection rate, diagnostic accuracy and omission diagnostic rate among mammography, ultrasound and MRI. And the detection rate and diagnostic accuracy of MRI in breast cancer in women with implants were higher than those of mammography, and the omission diagnostic rate was lower.Conclusions:Ultrasound and MRI are superior to mammography in evaluating breast cancer after silicone prosthesis implantation, and MRI has more advantages in guiding clinical diagnosis and treatment.
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Objective:To investigate the changes in gray matter volume (GMV) and abnormalities in structural covariant network (SCN) patterns in patients with chronic pontine infarction (PI).Methods:Patients with unilateral chronic PI (case group) with the first onset admitted to the First Affiliated Hospital of Zhengzhou University and Tianjin Medical University General Hospital from October 2014 to June 2021 were prospectively included. At the same time, healthy subjects matched with age, gender and education years (normal control group) were included. High-resolution three-dimensional T 1 structural MRI images and behavioral scores of the subjects were collected. The voxel-based morphometry and two-sample t test were used to explore the differences in GMV between the groups. Using GMV differential brain regions as seed points, SCN was constructed to explore the abnormality of structural covariant patterns in patients with PI. Spearman rank correlation analysis was used to analyze the correlation between GMV in differential brain regions and behavioral scores. Results:A total of 60 patients with PI were enrolled, including 33 left PI and 27 right PI, while 34 healthy controls were also enrolled. Compared with the normal control group, the GMV in bilateral posterior cerebellar lobe decreased significantly in the left PI group, and the GMV in left anterior and posterior cerebellar lobes and the right posterior cerebellar lobe decreased significantly in the right PI group (Gaussian random field correction with voxel level P<0.001 and cluster level P<0.05, cluster voxel >20), and there was a significant correlation between GMV values in the left anterior and posterior cerebellar lobes and the right posterior cerebellar lobe and the motor function score ( P<0.05). In addition, compared with the normal control group, the right PI group had broader covariate brain regions and a significant increase in the number of structural connections between covariate brain regions (family-wise error correction with voxel level P<0.05, cluster voxel >20). Conclusions:The GMV in bilateral posterior cerebellar lobe decreases significantly in patients with chronic PI, and were secondary to broader covariate brain regions and structural connections. This may be the neural mechanism of impaired behavioral function in patients with PI.
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Purpose: To investigate the association between clinic-radiological features and glioma-associated epilepsy (GAE), we developed and validated a radiomics nomogram for predicting GAE in WHO grade II~IV gliomas. Methods: This retrospective study consecutively enrolled 380 adult patients with glioma (266 in the training cohort and 114 in the testing cohort). Regions of interest, including the entire tumor and peritumoral edema, were drawn manually. The semantic radiological characteristics were assessed by a radiologist with 15 years of experience in neuro-oncology. A clinic-radiological model, radiomic signature, and a combined model were built for predicting GAE. The combined model was visualized as a radiomics nomogram. The AUC was used to evaluate model classification performance, and the McNemar test and Delong test were used to compare the performance among the models. Statistical analysis was performed using SPSS software, and p < 0.05 was regarded as statistically significant. Results: The combined model reached the highest AUC with the testing cohort (training cohort, 0.911 [95% CI, 0.878-0.942]; testing cohort, 0.866 [95% CI, 0.790-0.929]). The McNemar test revealed that the differences among the accuracies of the clinic-radiological model, radiomic signature, and combined model in predicting GAE in the testing cohorts (p > 0.05) were not significantly different. The DeLong tests showed that the difference between the performance of the radiomic signature and the combined model was significant (p < 0.05). Conclusion: The radiomics nomogram predicted seizures in patients with glioma non-invasively, simply, and practically. Compared with the radiomics models, comprehensive clinic-radiological imaging signs observed by the naked eye have non-discriminatory performance in predicting GAE.
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OBJECTIVE: To investigate the diagnostic value of radial turbo-spin-echo (TSE) T2 mapping and readout segmentation of long variable echo-train diffusion-weighted imaging (RESOLVE DWI) for the differentiation of parotid gland tumors. MATERIALS AND METHODS: One hundred and fifty-four patients with histopathologically confirmed parotid gland tumors were retrospectively recruited from June 2018 to May 2021 at the First Affiliated Hospital of Zhengzhou University. There were 111 benign tumors and 43 malignant tumors. Benign tumors were further divided into pleomorphic adenomas (n = 69) and Warthin's tumors (n = 26). All patients were scanned using T2 mapping and RESOLVE DWI. T2 and ADC values and a combination of the two methods were compared and analyzed for the ability to differentiate parotid gland tumor types. RESULTS: The T2 and ADC values of benign tumors were significantly higher than those of the malignant tumors (127.97 ± 56.29 ms vs 97.53 ± 45.24 ms, 1.27 ± 0.40 × 10-3 mm2/s vs 1.00 ± 0.39 × 10-3 mm2/s, all P < 0.05). The area under the curve (AUC) of the T2 and ADC values for differentiating (1) benign and malignant parotid tumors, (2) pleomorphic adenomas and Warthin's tumors, (3) pleomorphic adenomas and malignant tumors, and (4) Warthin's tumors and malignant tumors were 0.709 and 0.715, 0.918 and 0.994, 0.748 and 0.774, and 0.665 and 0.659, respectively, with no significant differences observed between the T2 and ADC values (all P > 0.05). There were no significant differences in these values among the three tumor groups (malignant tumor, pleomorphic adenoma, and Warthin's tumor groups, all P > 0.05). CONCLUSIONS: T2 mapping and RESOLVE DWI can be used to differentiate various parotid gland tumors. T2 values are comparable to ADC values.
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Adenolinfoma , Adenoma Pleomórfico , Neoplasias de la Parótida , Adenolinfoma/diagnóstico por imagen , Adenolinfoma/patología , Adenoma Pleomórfico/diagnóstico por imagen , Adenoma Pleomórfico/patología , Diagnóstico Diferencial , Imagen de Difusión por Resonancia Magnética/métodos , Humanos , Glándula Parótida/diagnóstico por imagen , Glándula Parótida/patología , Neoplasias de la Parótida/diagnóstico por imagen , Estudios RetrospectivosRESUMEN
Objective:To investigate the microstructural abnormalities of the white matter in first-episode medication-free patients with schizophrenia (FESZ) based on inter-voxel diffusivity metric local diffusion homogeneity (LDH) and traditional intra-voxel diffusivity metric.Methods:A total of 56 FESZ patients admitted to our hospital from January 2020 to December 2021 were selected as research subjects, and 64 healthy volunteers recruited during the same period were selected as healthy controls. All subjects accepted magnetic resonance diffusion tensor imaging, and the LDH, anisotropy fraction (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) were obtained by FSL and PANDA software. Tract-based spatial statistics (TBSS) method was employed to analyze and compare the differences in the diffusivity metrics of white matter fibers between the two groups. For white matter fiber tracts with significant inter-group differences, receiver operating characteristic(ROC) curve was used to evaluate the diagnostic value of each diffusivity metric in FESZ, and Spearman partial correlation was used to analyze the relation between each diffusivity metric and positive and negative symptom scale (PANSS) scores.Results:As compared with that in the heathy control group, LDH in partial voxel clusters in bilateral anterior thalamic radiation of the FESZ group was statistically increased ( P<0.05, FWE correction). As compared with that in the heathy control group, the mean LDH in the tracts of interest (TOI) of the right inferior longitudinal fasciculus and the right uncinate fasciculus in the FESZ group was significantly increased ( P<0.05, FDR correction). In the above 4 fasciculi, ROC analysis showed that LDH had diagnostic efficacy ( P<0.05), and the diagnostic efficacy of LDH was the highest when the fasciculi structures were combined (AUC=0.733, P<0.001). LDH in white matter fiber tracts with significant inter-group differences had no statistical correlation with PANSS scores ( P>0.05). No voxel clusters or TOIs enjoyed statistical differences between groups were noted in the FA, MD, AD and RD parameter maps ( P>0.05). Conclusion:The inter-voxel diffusivity metric LDH can detect the compensatory changes of white matter microstructure in FESZ patients that could not be detected by traditional intra-voxel diffusivity metric.
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Objective:To investigate the value of periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) in improving ability of demonstrating ocular masses on 3.0 T MR scanner.Methods:This study was a multi-center prospective study involving 6 centers. From July 2018 to January 2020, totally 413 patients with ocular masses from 6 centers were prospectively enrolled, and all of them underwent T 1WI and T 2WI, PROPELLER T 1 FLAIR and T 2WI, and contrast-enhanced scans. The signal intensity of eyelid, vitreous body, lacrimal gland, intraorbital segment of optic nerve, and orbital masses of eyelid, intraocular, lacrimal gland and retrobulbar were measured by two radiologists, and the signal to noise ratio (SNR) and contrast noise ratio (CNR) were calculated. The 5-point scoring method was used to evaluate the motion artefacts, tumor edges and the relationship between the tumor and adjacent structures, and the overall score of image quality was calculated. Paired t-test or Wilcoxon signed rank test was used to compare the image quality between PROPELLER and non-PROPELLER images. Results:The SNR and CNR of PROPELLER T 2WI were higher than those of non-PROPELLER T 2WI (all P<0.001). The SNR and CNR of PROPELLER T 1 FLAIR were lower than those of non-PROPELLER T 1WI (all P<0.05). The scores of artefacts and overall image quality in PROPELLER images were higher than those in non-PROPELLER images (all P<0.001). The tumor edge and the relationship between the tumor and adjacent structures scores of eyelid, intraocular, and lacrimal gland masses in PROPELLER images were higher than those in non-PROPELLER images (all P<0.001),while compared to non-PROPELLER images, retro-global masses in PROPELLER images showed no significant differences (all P>0.05). Conclusion:PROPELLER can reduce ocular motion artefacts, effectively improve image quality and ability of demonstrating anterior (eyelid, intraocular, and lacrimal gland) masses.
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Objective:To explore the value of machine learning models based on MRI predict the brain age of smokers and healthy controls, and further to explore the relationship between smoking and brain aging.Methods:This was a retrospective study. Dataset 1 consisted of 95 male smokers [20-50 (34±7) years old] and 49 healthy controls [20-50 (33±7) years old] recruited from August 2014 to October 2017 in First Affiliated Hospital of Zhengzhou University. Dataset 2 contained 114 healthy male volunteers [20-50 (34±11) years old] from the Southwestern University Adult Imaging Database from 2010 to 2015. All subjects underwent high-resolution 3D T 1WI scan. Gaussian process regression (GPR) model and support vector machine model were constructed to predict brain age based on structural MR images of healthy controls in dataset 1 and dataset 2. After the performance of the model was verified by the cross-validation method, the mean absolute error (MAE) between the predicted brain age and the actual age and the correlation ( r-value) between the actual age and the predicted brain age were calculated, and the best model was finally selected. The best models were applied to smokers and healthy controls to predict brain age. Finally, a general linear model was used to compare the differences in brain-predicted age difference (PAD) between smokers and healthy controls with age, taking years of education and total intracranial volume as covariates. Result:The performance of GPR model (MAE=5.334, r=0.747) in predicting brain age was better than support vector machine model (MAE=6.040, r=0.679). The GPR model predicted that PAD value of smokers in dataset 1 (2.19±6.64) was higher than that of healthy controls in dataset 1 (-0.80±8.94), and the difference was statistically significant ( F=8.52, P=0.004). Conclusion:GPR model based MRI has better performance in predicting brain age in smokers and healthy controls, and smokers show increased PAD values, further indicating that smoking accelerates brain aging.
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Objective:To investigate the diagnostic value of three-dimensional amide proton transfer-weighted imaging (APTWI) and its combination with diffusion weighted imaging (DWI) for differentiating breast benign from malignant lesions.Methods:This was a prospective study. From July to December 2020, 226 patients with breast lesions confirmed by surgery or puncture pathology in the First Affiliated Hospital of Zhengzhou University were collected. All patients underwent MR T 1-weighted imaging, T 2-weighted imaging, DWI, APTWI, and dynamic contrast-enhanced MRI, and the apparent diffusion coefficient (ADC) value and the magnetization transfer ratio asymmetry at an offset of 3.5 ppm [MTRasym(3.5 ppm)] were obtained from DWI and APTWI respectively. Mann-Whitney U test was used for the comparison of DWI and APTWI parameters between breast benign and malignant lesions. Receiver operating characteristic (ROC) curve was used to evaluate the differences of diagnostic efficacy between DWI, APTWI, and their combination. Results:There were 226 patients with 226 breast lesions, including 124 malignant and 102 benign lesions. The ADC values of patients with malignant breast lesions [1.03 (0.93, 1.13)×10 -3 mm 2/s] and MTRasym (3.5 ppm) [1.95% (1.10%, 2.88%)] were lower than those of benign breast lesions [1.38 (1.11, 1.55)×10 -3 mm 2/s, 3.30% (2.20%, 4.20%), respectively], and the differences were statistically significant ( Z=-8.19, -6.51, P<0.05). The area under the ROC curves (AUC) of DWI, APTWI, and its combination in the differential diagnosis of benign and malignant breast lesions were 0.817, 0.752, and 0.868, respectively. The AUC of the combination of DWI and APTWI was higher than that of DWI and APTWI ( Z=4.00, 2.93, P<0.05), and there was no significant difference in the AUC between DWI and APTWI diagnoses ( Z=1.58, P>0.05). Taking 1.25×10 -3 mm 2/s as the optimal cut-off value for ADC values, the sensitivity, specificity, and accuracy in differentiating benign from malignant breast lesions were 94.4% (117/124), 62.7% (64/102), and 80.1% (181/226), respectively; Taking 2.70% as the optimal cut-off value for MTRasym (3.5 ppm), the sensitivity, specificity, and accuracy in differentiating benign from malignant breast lesions were 73.4% (91/124), 64.7% (66/102), and 69.5% (157/226), respectively, and the sensitivity, specificity, and accuracy of DWI combined with APTWI in differentiating benign from malignant breast lesions were 82.3% (102/124), 79.4% (81/102), and 81.0% (183/226), respectively. Conclusion:APTWI can be used for the differential diagnosis of benign and malignant breast lesions, and the combination of APTWI and DWI can obtain the better diagnostic performance than the single method.
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Objective:To explore the value of the static and dynamic pelvic floor MRI and diffusion tensor imaging (DTI) in evaluating the morphology and function of urethra in patients with stress urinary incontinence (SUI).Methods:From July 2020 to February 2021, a total of 28 patients with SUI and 45 age-matched healthy controls were prospectively collected at the First Affiliated Hospital of Zhengzhou University. The static and dynamic pelvic floor MRI and DTI were performed for all subjects. The thickness of internal and external sphincter of middle urethra were measured on static MRI images. The functional urethral length (FUL) was measured both on static and maximal strain phase of dynamic MRI images, then the difference of FUL was calculated. The presence of bladder neck funneling and urethra opening were observed on static and dynamic MRI. The muscle fiber bundle image of urethral sphincter complex was obtained by post-processing of DTI original images. The anisotropy fraction (FA), apparent diffusion coefficient (ADC) and three eigenvalues (λ1, λ2, λ3) of annular sphincter and central longitudinal muscle in middle urethra were measured. The independent sample t test and chi-square test were used to analyse the difference of measured parameters in MRI, parameters of DTI and imaging signs between the two groups. Results:Compared with healthy controls, the SUI patients showed that the thickness of external sphincter in middle urethral and FUL in static status and maximal strain phase were significantly decreased ( t=-3.95, -5.72, -8.41, all P<0.001), the difference of FUL between static status and maximal strain phase was significantly increased ( t=4.41, P<0.001). The positive rate of bladder neck funneling in static status and maximal strain phase, urethral opening in maximal strain phase of SUI group increased significantly (χ2=23.09 , 22.25, 26.59, all P<0.001). In SUI group, the FA value of middle urethral annular sphincter decreased significantly ( t=-3.48, P=0.001), while the ADC, λ2 and λ3 values increased significantly ( t=3.19, 2.15 , 2.06, and P=0.002, 0.038 , 0.046, respectively). There was no significant difference in DTI parameters of middle urethral longitudinal muscle between the two groups (all P>0.05). Conclusions:Static and dynamic MRI and DTI techniques can objectively evaluate the changes of urethral morphology and function of SUI patients. The thinning of the external sphincter in the middle urethra, shortening of the FUL and the destruction of the microstructure of the annular sphincter fiber bundle were the main alterations of SUI patients.
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Objective:To evaluate the precision of quantitative CT (QCT) in measuring fat content of goose liver and to explore the influence of tube voltage on liver fat measurement.Methods:From January to March 2017, 22 Landes geese were selected to establish fatty liver models with overfeeding. The QCT was performed under 2 different tube voltages, 80 and 120 kV. In addition to the voltage, the other scanning parameters were the same. Three ROI were placed in the centre part of the left lobe, upper and lower half of the right lobe on the 3D reconstructed images. The volume percentage of goose liver fat (Fat% QCT) was calculated according to the formula provided by Mindways. Immediately after the QCT examinations, each goose was dissected, and the whole liver was removed. Then samples were taken in the corresponding areas of the ROI by QCT. The fat (triglyceride) content of the samples was measured by the biochemical extraction method. The Spearman correlation tests were used to determine the correlation between the QCT measurements of 80 kV and 120 kV groups and the results of biochemical extraction method. The Wilcoxon signed-rank test was performed to compare Fat% QCT between 80 kV and 120 kV groups. Bland-Altman plots were used to assess agreement between the two groups′ measurements. Results:The Fat% QCT of both 80 kV and 120 kV group positively correlated highly with biochemical extraction ( r s=0.936, P<0.001, r s=0.927, P<0.001) respectively. No statistically significant difference of Fat% QCT was detected between 80 kV and 120 kV group ( Z=-0.141, P=0.888). Bland-Altman analysis showed a small difference of Fat% QCT between the 80 kV and 120 kV group, in which mean values were 0.20%. Conclusions:Using biochemical extracted triglyceride as the reference, under the conditions of low-dose 80 kV and standard 120 kV tube voltages, QCT measurement of fat content is accurate and reliable in goose liver.
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Objective:To explore the differences of static and dynamic spontaneous brain activity between male smoking addicts and healthy controls, and analyze the mechanism of smoking addiction.Methods:Based on static amplitude of low-frequency fluctuation (sALFF) and dynamic amplitude of low frequency fluctuation (dALFF), the differences of static and dynamic spontaneous brain activity were compared between male smoking addicts ( n=63) and healthy controls ( n=30) by independent sample t-test. Pearson correlation analysis was used to investigate the relationships between the altered dALFF values and score of Fagerstr?m test for nicotine dependence(FTND) and pack-years of smoking addicted males. Results:Compared with healthy controls, the values of sALFF in the left superior/middle/inferior orbitofrontal gyrus ( t=5.17, clusters≥108) were increased and the variation of dALFF in the right superior temporal/middle gyrus, left orbitofrontal region, left orbital superior/middle/inferior frontal gyrus, right orbitofrontal gyrus/middle/inferior frontal gyrus and right putamen ( t=4.90, 4.37, 4.91, 4.62, 4.59, clusters≥96) were also increased in the smoking addicted group. It was noteworthy that the dALFF values of the right superior temporal/middle gyrus( r=0.252, P=0.047), left orbital region superior frontal gyrus( r=0.281, P=0.026) and right putamen( r=0.313, P=0.012) were positively correlated with pack-years of male smoking addicts. Conclusion:Male smoking addicts may have abnormal static and dynamics spontaneous neural activity in prefrontal cortex (including orbital frontal lobe), putamen and superior temporal/middle gyrus, which are correlated with pack-years.
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Objective:To investigate the abnormalities of gray matter volume (GMV) and the synergistic changes in different cerebral regions in the first-episode and early-onset depression (EOD) patients.Methods:A total of 60 patients with untreated EOD (EOD group) and 64 healthy controls (control group) matched for age, gender, and education underwent high-resolution T 1WI MR scans. Voxel-based morphometry was used to calculate the cerebral GMV. The difference in GMV between the two groups was compared with the t-test. Different brain regions were selected as seeds for structural covariation network (SCN) analysis. Spearman correlation model was used to analyze the correlation between the GMV in different cerebral regions and illness duration as well as the scores of Hamilton rating scale for depression (HAMD) 17 items in EOD group. Results:Compared to control group, the EOD group had significantly increased GMV in the right orbitofrontal cortex, right dorsolateral prefrontal cortex, right inferior parietal lobule, right superior parietal lobule and bilateral precuneus ( P<0.05, corrected by FDR). Based on the right orbitofrontal cortex and dorsolateral prefrontal cortex as seed regions, structural covariance analysis revealed that abnormal cooperative brain regions in EOD group, mainly distributed in the bilateral frontal lobe, parietal lobe, occipital lobe, temporal lobe, paralimbic system and cerebellum ( P<0.05, corrected by FDR). In EOD group, significant negative correlations were observed between the GMV in the right orbitofrontal cortex ( r=-0.314, P=0.015), the left precuneus ( r=-0.283, P=0.029), and illness duration. Significant positive correlations were observed between the GMV in the right dorsolateral prefrontal cortex and the scores of anxiety/somatization factor of HAMD17 ( r=0.331, P=0.010), the left precuneus and weight factor of HAMD17 ( r=0.255, P=0.049), respectively. Conclusions:Abnormal GMV changes are observed in some regions of the prefrontal and parietal lobule in patients with untreated EOD, accompanied by extensive covariant brain regions and additional structural connectivity. In addition, the abnormal GMV changes in some regions are associated with clinical features. Part of the prefrontal and parietal lobule may be the biomarkers to objectively evaluate abnormal brain structure in depression patients in the early stage.
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Objective:To dynamically trace the migration and therapeutic effects of human bone marrow mesenchymal stem cells (MSCs) in mice with liver injury after cell transplantation through in vivo bioluminescent imaging (BLI).Methods:The MSCs were transfected with the lentivirus CMV-Luciferase2-mKate2 and mKate2 positive cells were purified and screened by fluorescence-activated cell sorting (FACS) after 96 h. The purified MSCs-R (MSCs-CMV-Luciferase2-mKate2) were used by in vitro and in vivo BLI. The mice (male BALB/c nude mice) were divided into 4 groups with 9 mice per group by random number table method, including (1) Liver injury experimental group: The liver injury model was established by intraperitoneal injection of CCl 4, and MSCS-R transplantation through spleen injection was performed 24 h later; (2) Control experimental group: The same volume of phosphate buffer (PBS) was injected intraperitoneally, and MSCS-R transplantation through spleen injection was performed 24 h later; (3) Liver injury group: Liver injury model was established and PBS was injected into the spleen;(4) Blank group: The mice were intraperitoneally injected of PBS.BLI was performed daily after cell transplantation until light signals disappeared in the liver region, and the pathological examination of liver tissue was obtained 14 d after MSCs-R transplantation. Linear regression analyses were performed to determine the correlation between the optical signal intensity and the number of cells, and statistical differences of the optical signal intensity between liver injury experimental group and control experimental group were evaluated using the Student′s t test. Results:The MSCs were readily transfected with lentivirus CMV-Luciferase2-mKate2 for 96 h. The transfected MSCs were purified by FACS and more than 95% of MSCs were mKate2 positive. The optical signal intensity of MSCs-R detected by BLI in vitro significantly correlated with cell numbers in vitro (R 2=0.980). In both of liver injury experimental group and control experimental group, cell migration to the liver was observed on the first day after intrasplenic transplantation of MSCs-R, and the optical signal intensity in the area of liver of liver injury experimental group was higher than that of control experimental group ( t=15.476, P<0.001). The optical signal intensity in the hepatic area was observed in 11 d after transplantation in liver injury experimental group, compared to control experimental group in 5 d. Optical signal was not detected in mice in the other two groups. Histopathology showed that the degree of liver injury after MSCs-R transplantation was significantly lower in liver injury experimental group than control experimental group. Conclusions:The dynamical migration of MSCs transplanted to the spleen and settled in the damaged liver could be tracked by BLI, and liver injury can prompt MSCs directionally migrate to the damaged tissues and play their role in repairing liver injury.