http://med-sci.cn/cgzcx/en/contents_list.asp?issue=202402 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.1674-8034.2024.02.001 ObjectiveTo evaluate the value of MR diffusion kurtosis imaging (DKI) and diffusion‑tensor imaging (DTI) in differentiating low-grade gliomas from encephalitis. Materials and MethodsThe imaging data of 58 patients with either low-grade glioma or encephalitis were retrospectively collected. All patients underwent routine MRI and DKI sequence scans before surgery or conservative treatment. The DKI images were processed with NeuDiLab software to obtain the parameter maps of DKI-based mean kurtosis (MK), axial kurtosis (AK) and radial kurtosis (RK), as well as DTI-based mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD) and fractional anisotropy (FA) and diffusion images of b=0 s/mm² (B0). The volumes of interest (VOIs) of the tumor were manually delineated on the B0 image with ITK-SNAP software and were registered to other parametric maps. The mean values of each parameter were extracted with FAE software. Patients were divided into glioma group and encephalitis group according to pathological examination or cerebrospinal fluid examination results. The chi-square test, independent samples t test and Mann-Whitney U test were used to compare the general data, routine MRI findings and diffusion parameters between the two groups. Cohen^,s d values were calculated to evaluate the effect sizes of diffusion parameters. The receiver operating characteristic (ROC) curve was drawn to calculate the area under the curve (AUC), sensitivity, specificity and accuracy. The DeLong test was used to compare the differential diagnostic performance of diffusion parameters. ResultsA total of 51 patients were included in the study, including 29 patients with low-grade gliomas and 22 patients with encephalitis. RK demonstrated the best performance in distinguishing low-grade gliomas from the encephalitis group, with an AUC of 0.878. When the threshold was set at 0.662, the sensitivity was 72.7%, and the specificity was 89.7%. The DeLong test indicated that the diagnostic performance of the DKI model was significantly superior to DTI. ConclusionsDKI is helpful in the differential diagnosis of low-grade gliomas and encephalitis. ]]> Tue,20 Feb 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.02.002 ObjectiveTo investigate the relationship of peridisc attachment to articular disk and condylar morphology in anterior disc displacement with reduction (ADDWR) and anterior disc displacement without reduction (ADDWoR) by analyzing the magnetic resonance imaging (MRI) features of disc-condylar complex and semi-quantitative grading method of peridiscal attachment. Materials and MethodsRetrospective analysis of 74 patients (114 sides) were diagnosed with anterior disc displacement of temporomandibular joint by MRI scan at the Department of Radiology of Fujian Provincial Hospital from May 2021 to September 2022. They were divided into reduction (39 sides) and non-reduction (75 sides) groups. Joint disk morphology were divided into four types (Ⅰ-Ⅳ), condylar morphology into three types and peridisc attachment into six grades. The Kruskal-Wallis test was employed to compare the difference of joint disk morphology, condylar morphology and peridisc attachment between the two groups. The Mann-Whitney U test was used compare the overall and attachment scores of joint disk morphology, condylar morphology and peridisc attachment. Spearman rank correlation analysis was used to compare the overall score of joint disk morphology, condylar morphology and peridisc attachment, as well as the correlation coefficient of attachment and joint disk-condylar complex reducibility. Binary logistic regression was adopted to choose the independent risk factors from peridisc attachment models to predict the joint disk-condylar complex reducibility. ResultsExcept type Ⅲ and type Ⅳ‍, joint disk morphology difference presented statistical significance (P<0.05). Condylar morphology difference presented statistical significance (P<0.05). Except grade 1 to 4, grade 5/grade 6, peridisc attachment grading difference presented statistical significance (P<0.05). Reduction of articular disk was strongly positively correlated to articular disk morphology, condylar morphology and total values of peridisc attachment (r=0.824, 0.626, 0.827, P<0.05). The prediction model of peridisc attachment showed that the lowerbilaminar region attachment was an independent risk factor for articular disc reduction with regression coefficient being 2.979 (OR=19.672, P<0.05). ConclusionsBy analyzing MRI features of disc-condylar complex and the proposed semi-quantitative evaluation, factors affecting articular disc reduction are effectively evaluated, which provides reliable imaging reference for clinical treatment. ]]> Tue,20 Feb 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.02.003 ObjectiveIn this study, 4D flow magnetic resonance imaging (4D Flow MRI) was employed to analyze the hemodynamics of moderate and severe atherosclerotic stenosis in unilateral carotid arteries and investigate the hemodynamic risk factors influencing carotid atherosclerotic stenosis and acute ischemic stroke. Materials and MethodsA total of 20 patients diagnosed with moderate to severe unilateral carotid atherosclerosis using ultrasonography were recruited from January to December at the First Hospital of Jilin University, along with age- and vascular condition-matched normal volunteers (n=26). Clinical data and magnetic resonance data were collected. Hemodynamic parameters such as blood flow, blood flow velocity, wall shear stress (WSS), maximum pressure gradient and energy loss were obtained by CVI 42 software. Compare the measured values between groups for statistical differences using t-tests or Mann Whitney U-tests and subgroup analysis was performed on acute cerebral infarction and non-acute cerebral infarction to explore the effect of hemodynamic changes at the stenosis on the occurrence of stroke. ResultsThe mean blood flow, maximum blood flow, total volume and mean relative pressure difference in the study group were significantly lower than those in the control group (P<0.05), while the maximum energy loss and average energy loss were higher than those in the control group (P<0.05). The mean blood flow was negatively correlated with the degree of stenosis (r=-0.420, P<0.05). There were significant differences in mean blood flow, mean velocity, minimum velocity, maximum blood flow, total volume, and verage axial wall shear stress in the upper, central and lower reaches of all stenosis vessels (P<0.05), and the maximum pressure gradient of downstream acute cerebral infarction group was lower than that of non-acute cerebral infarction group (P<0.05). ConclusionsVisualization and quantitative analysis of 4D Flow MRI shows that energy loss in addition to blood flow was helpful for realistic carotid artery stenosis. Low WSS and downstream maximum pressure gradient of carotid artery stenosis may serve as potential biomarkers for stroke prediction. ]]> Tue,20 Feb 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.02.004 ObjectiveTo obtain the myocardial strain values of the left ventricle at the global and regional level in patients with different subtypes of cardiac amyloidosis (CA) through cardiovascular magnetic resonance feature tracking (CMR-FT). Materials and MethodsThis study included patients with CA who had undergone endocardial biopsy, and 20 cases of immunoglobulin light chain cardiac amyloidosis (AL-CA) and 22 cases of transthyretin cardiac amyloidosi (ATTR-CA) were retrospectively included according to immunohistochemistry, serum immunofixation electrophoresis, and Tcm/HMDP/PYP scintillation imaging. The type and range of late gadolinium enhancement in the two groups were evaluated to reflect the differences in histological characteristics. The radial, circumferential and longitudinal strains (2D and 3D) of the whole left ventricle and myocardium layers (subepicardial and subendocardial) were obtained by CMR-FT technique, and the differences of each parameter between groups were analyzed. Receiver operator characteristic curve analysis was used to analyze the accuracy of strain parameters in distinguishing the two CA types. ResultsCompared with the ATTR-CA group, the left ventricular ejection fraction was slightly lower in the AL-CA group, and the left ventricular end-diastolic volume was relatively smaller, but didn^,t reach statistically significant. After body surface area correction, left ventricular mass in ATTR-CA group was slightly higher than that in AL-CA group [left ventricular mass index: (106.38±29.79) mL/m² vs. (100.04±36.73) mL/m²]. The distribution of late gadolinium enhancement was more diffuse in patients with ATTR-CA type (60%) and more subendocardial in patients with AL-CA type. The absolute values of left ventricular global radial strain (3D) (12.96%±5.21% vs. 16.58%±4.39%),global longitudinal strain (2D) (-6.70%±1.94% vs. -7.87%±1.70%), global circumferential strain-epicardial (GCSepi) (-8.41%±2.78% vs. -10.51%±3.10%) and global longitudinal strain-epicardial (GLSepi) (-6.49%±2.03% vs. -8.15%±1.86%) in ATTR-CA group were lower than that in AL-CA group (all P<0.05). The accuracy of GPSepi and GLSepi were the highest, and the AUC values were both reached 0.705. Logistic regression analysis showed that GLSepi was an independent factor in distinguishing different subtypes (OR=1.60, P=0.021). ConclusionsCMR-FT imaging can provide valuable information about myocardial function and strain in patients with CA. Moreover, it is capable of distinguishing between the two common subtypes, ATTR-CA and AL-CA. The left ventricular myocardial strains in ATTR-CA are lower than those in AL-CA. ]]> Tue,20 Feb 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.02.005 ObjectiveTo extract and analyze the myocardial radiomics features of patients with hypertrophic cardiomyopathy (HCM) and healthy controls, and to explore the clinical application value of radiomics features of HCM based on cardiac magnetic resonance (CMR) radiomics. Materials and MethodsThe CMR imaging and clinical data of 142 patients with HCM and 72 healthy controls from the General Hospital of Ningxia Medical University from January 1, 2018 to December 31, 2022 were retrospectively collected and analyzed. The CMR unenhanced bright-blood cine sequence was used to select the left ventricular long axis two-chamber and four-chamber mitral valve level view. Based on the end-diastolic wall thickness (EDWT), the myocardium of HCM patients was divided into hypertrophic region (no family history of HCM, EDWT≥15 mm; family history of HCM, EDWT≥13 mm) and non-hypertrophic region (no family history of HCM, EDWT <15 mm; family history of HCM, EDWT<13 mm), the region of interest (ROI) was delineated and radiomics features were extracted from the ventricular wall of the same anatomical part of the healthy control group, such as ventricular septum, apex of heart, lateral wall of left ventricle, anterior wall of left ventricle and inferior wall of left ventricle,and the radiomics features were compared between the two groups after grouping. Mann-Whitney U test, recursive feature elimination (RFE), and least absolute shrinkage and selection operator (LASSO) were used to select the radiomics features and establish the radiomics model. Finally, the accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) and area under the curve (AUC) were used to evaluate the performance of each model. The clinical data of HCM patients and healthy controls were statistically analyzed. Results(1) In the HCM group, left ventricular end systolic volume (LVESV), LVESV index (LVESVI), left ventricular end diastolic wall mass (LVED wall mass), left ventricular end diastolic wall+papillary mass (LVED wall+papillary mas), left ventricular end systolic wall mass( LVES wall mass), left ventricular end systolic wall+papillary mass ( LVES wall+papillary mass), left ventricular maximum end-diastolic wall thickness (LVMWT) were higher than those of the healthy control group (P<0.05). (2) The radiomics features of hypertrophic regions and non-hypertrophic regions in HCM patients and the healthy control group had a good discrimination effect on the same anatomical part of left ventricular wall. The radiomics differential model between HCM non-hypertrophic region group (left ventricular anterior wall) and HCM hypertrophic region group (left ventricular anterior wall) was the optimal model in this study, and its AUC value, accuracy, sensitivity, specificity, PPV and NPV were 0.98, 93%, 94%, 92%, 89% and 96% in the training set. In the test set, the values were 0.97, 94%, 92%, 96%, 92%, 96%. ConclusionsThe results show that the radiomics model not only has good efficacy in the identification of hypertrophic and non-hypertrophic regions of the myocardium in HCM and healthy people, but also can well distinguish hypertrophic and non-hypertrophic regions of the myocardium in HCM, indicating that the radiomics method can provide a potential and sensitive new technology for the evaluation of myocardial histological changes through in-depth and comprehensive quantitative analysis of myocardial tissue in HCM patients with different pathological states. It provides a kind of potential and sensitive new technique for evaluation of myocardial histological changes. It is helpful to evaluate the condition of HCM patients more accurately, improve the efficiency of CMR examination and reduce the cost of examination, and provide a new idea for the development and clinical application of artificial intelligence technology to detect myocardial histological status easily and quickly in the future. ]]> Tue,20 Feb 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.02.006 ObjectiveTo investigate the value of apparent diffusion coefficient (ADC) for differential diagnosis of histological type of lung cancer brain metastases and its relationship with Ki-67 proliferation index. Materials and MethodsThe clinical data of 20 patients with small-cell carcinoma brain metastases and 41 patients with non-small-cell lung carcinoma brain metastases confirmed by surgery were analyzed retrospectively. The minimum ADC value (ADC_min), the mean ADC value (ADC_mean), and the ADC values in contralateral normal cerebral white matter were measured on the ADC map, and the relative ADC_min value (rADC_min) and relative ADC_mean value (rADC_mean) were calculated. The differences in ADC values were compared and analyzed, the differential diagnostic value of ADC values was evaluated by plotting receiver operating characteristic (ROC) curves, and the correlation between ADC values and Ki-67 proliferation index was calculated. ResultsThe ADC_min, ADC_mean, rADC_min and rADC_mean values of the small cell lung cancer brain metastasis tumor group were smaller than those of the non-small fine lung cancer brain metastasis tumor group, and the differences between the groups were all statistically significant (P<0.05). Each ADC value could effectively discriminate between small cell lung cancer brain metastases and non-small cell lung cancer brain metastases, among which the rADC_mean value had the best differential diagnostic efficacy, with an area under the curve (AUC) of 0.950 [95% confidence interval (CI): 0.907-0.994]. The optimal cutoff value was of 0.955, and the corresponding sensitivity and specificity were 96.23% and 83.87%, respectively, and the accuracy was 91.67%. The Ki-67 proliferation index in the small cell lung cancer brain metastasis group was greater than that in the non-small cell lung cancer brain metastasis group, and the difference between the groups was statistically significant (P<0.05). A total of 61 patients with lung cancer brain metastasis showed different degrees of negative correlation between the ADC_min, ADC_mean, rADC_min and rADC_mean values and the Ki-67 proliferation index (r=-0.506, r=-0.480, r=-0.569, r=-0.541). ConclusionsADC values can provide differential diagnosis of histological type of lung cancer brain metastases and can predict the expression level of Ki-67 proliferation index. ]]> Tue,20 Feb 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.02.007 ObjectiveTo study the early changes in cortical surface morphology in breast cancer patients in the early stage of chemotherapy and its relationship with cancer-related fatigue (CRF). Materials and MethodsTwenty-five first-diagnosed female breast cancer patients were taken for neuropsychological tests such as Brief Fatigue Inventory (BFI), Hamilton Depression Scale (HAMD), and Hamilton Anxiety Scale (HAMA) and cranial magnetic resonance 3D-T1-weighted data acquisition before (within one week before the start of chemotherapy) and during (within two weeks of the end of the second cycle of chemotherapy) postoperative chemotherapy, respectively. Age-matched healthy women were recruited as a control group during the same period, and clinical information and magnetic resonance data were collected using the same assessed approach during the matched time intervals. Surface-based morphometry (SBM) was used to analyze the surface morphology of the cerebral cortex of all subjects using the computational anatomy toolbox 12 (CAT 12) in the statistical parametric mapping 12 (SPM 12) software, and SPSS 26.0 was used to analyze the correlation between brain areas with altered surface morphology of the cortex and longitudinal changes in CRF during chemotherapy in breast cancer patients. ResultsCompared with the pre-chemotherapy period, the differences in CRF, depression, and anxiety measurement scores of breast cancer patients in the early stage of chemotherapy were statistically significant (P<0.05). The values of cortical thickness, sulcal depth, fractal dimension, and gyrification index parameter of cortical surface morphology of breast cancer patients during chemotherapy changed compared with that of the pre-chemotherapy period. The differences were statistically significant (P<0.05): there was a reduction in cortical thickness in the parietal lobes (bilateral precuneus, right supramarginal, right postcentral) and occipital lobes (bilateral cuneus), a reduction in sulcus depth in the parietal lobes (bilateral inferiorparietal, right supramarginal and superiorparietal), the temporal lobes (right fusiform, superiortemporal and inferiortemporal), the occipital lobes (bilateral lateraloccipital, right cuneus, right pericalcarine), and a reduction in the number of fractal dimensions in the right frontal lobes (superiorfrontal, rostralmiddlefrontal and parsorbitalis), the right parietal lobes (supramarginal and inferiorparietal), and the left occipital lobes (lateraloccipital); The brain regions with increased parameter values were increased gyrification index in the left occipital lobe (lateraloccipital and cuneus), right parietal lobe (supramarginal, superiorparietal, and inferiorparietal), and right temporal lobe (middletemporal, inferiortemporal, and bankssts). Changes in the fractal dimension of the right rostralmiddlefrontal in the early phase of chemotherapy were negatively correlated with longitudinal changes in CRF compared with the pre-chemotherapy phase (r=-0.628, P=0.001). ConclusionsCortical surface morphology in breast cancer patients can undergo early changes during chemotherapy and associated with changes in CRF. ]]> Tue,20 Feb 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.02.008 ObjectiveIn this study, resting state fMRI was used to investigate the changes of brain cognitive function after 2 cycles of anthracycline cyclophosphamide (AC) chemotherapy in breast cancer patients with different expression of δ-catenin. Materials and MethodsA total of 66 patients with breast cancer confirmed by pathology and received standardized chemotherapy for the first time were prospectively collected. According to the level of tissue serum δ-catenin, they were divided into δ-catenin high expression group (n=31), δ-catenin low expression group (n=35) and healthy control (HC) group (n=36). All subjects received neuropsychological score and brain resting state fMRI and 3D-T1 weighted imaging before and after 2 cycles of chemotherapy. The functional indexes of brain resting state, including amplitude of low frequency fluctuation (ALFF), fractional amplitude of low frequency fluctuation (fALFF) and regional homogeneity (ReHo), the neuropsychological scores and the MRI index of brain resting state function were compared and analyzed before and after chemotherapy. ResultsThe expression of human epidermal growth factor receptor 2 (HER-2) in δ-catenin high expression group was significantly higher than that in low expression group (P<0.05). The neurological scores of breast cancer patients before and after chemotherapy showed that there were significant differences in Functional Assessment of Cancer Therapy-Cognitive (FACT-Cog)-SUM, Perceived Cognitive Abilities (PCA), Mini Mental State Examination (MMSE), Montreal Cognitive Assessment (MOCA), Digital Symbol Substitution Test (DSST) and Auditory Verbal Learning Test (AVLT), Line-B scores in δ-catenin high expression group, while only AVLT-long-term memory scores in low expression group had significant differences (P<0.05). Compared with those before chemotherapy, there were significant differences in ALFF and ReHo values in some brain regions (P<0.05). The ALFF values of right anterior cingulate and paracingulate gyrus in δ-catenin low expression group decreased after chemotherapy, while those in δ-catenin high expression group decreased after chemotherapy in right cerebellar hemisphere area 4-5, bilateral insular and left lingual gyrus. Among the ReHo indexes, the ReHo values of the left inferior orbital frontal gyrus decreased in the δ-catenin low expression group after chemotherapy, while those in the left superior marginal gyrus and left triangular inferior frontal gyrus decreased in the δ-catenin high expression group (P<0.05). ConclusionsThe high expression of δ-catenin protein further aggravates the damage of brain cognitive function induced by chemotherapy in patients with breast cancer, which is mainly related to the executive regulation of cognitive function and other related brain regions. ]]> Tue,20 Feb 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.02.009 ObjectiveTo investigate feasibility of a nomogram model developed with apparent diffusion coefficient (ADC) of peritumoral liver tissue to predict local progression of recurrent hepatocellular carcinoma (rHCC) after hepatectomy. Materials and MethodsA retrospective cohort study was conducted by collecting MRI and clinical data of patients with diagnosed rHCC after hepatectomy at the Affiliated Hospital of North Sichuan Medical College from January 2021 to December 2022. Using Firevoxel software, the peritumor mean ADC (pADC_mean), minimum ADC (pADC_min), and maximum ADC (pADC_max) values, as well as the tumor mean ADC (tADC_mean), minimum ADC (tADC_min), and maximum (tADC_max) values were measured. The background liver tissue mean ADC (bADC_mean), minimum ADC (bADC_min), and maximum ADC (bADC_max) values were also obtained. The ratios of pADC_mean to bADC_mean (RPB-ADC_mean), ADC_min (RPB-ADC_min), and ADC_max (RPB-ADC_max) along with the ratios of tADC_mean to bADC_mean (RTB-ADC_mean), ADC_min (RTB-ADC_min), and ADC_max (RTB-ADC_max) were calculated. Cox regression analysis was used to identify independent risk factors, and then a nomogram model was constructed to predict local progression of rHCC after hepatectomy. Receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were employed to evaluate the predictive value of the model for prediction of local progression of rHCC. ResultsA total of 70 patients with rHCC after hepatectomy were enrolled, and the local progression rate of rHCC was 65.7% (46/70) confirmed by follow-up. Multivariate Cox regression analysis revealed that RPB-ADC_mean, pADC_min and vitamin K absence antagonist-Ⅱ were independent risk factors for local progression of rHCC after hepatectomy (all P<0.05). The area under the ROC curve of the nomogram model to predict local progression of rHCC within 3 months and within 6 months after hepatectomy was 0.834 and 0.841, respectively. DCA demonstrated a favorable clinical net benefit of the model. ConclusionsThe pADC_min, RPB-ADC_mean and vitamin K absence antagonist-Ⅱ can be independent risk factors associated with local progression of rHCC after hepatectomy, and the developed nomogram model can intuitively predict local progression of rHCC with good performance and net clinical benefit. ]]> Tue,20 Feb 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.02.010 ObjectiveTo explore the comparison of the detection efficacy of 18-fluoro-labeled prostate specific membrane antigen (¹⁸F-PSMA-1007) positron emission tomography (PET)/computed tomography (CT) and multi-parameter magnetic resonance imaging (mp-MRI) alone and combined with prostate cancer (PCa) and the correlation between maximum standardized uptake value (SUV_max), apparent diffusion coefficient (ADC), SUV_max/ADC, T1, T2, proton density (PD) value and pathological grade of PCa. Materials and MethodsA retrospective analysis was made on 50 patients suspected of PCa who were scheduled to undergo biopsy or surgery in our hospital from April 2020 to September 2022, of which 42 cases were diagnosed with PCa. According to the International Society of Urological Pathology (ISUP), the patients were divided into 5 groups. According to ISUP classification, there were 25 cases in high grade group (≥4 grade) and 17 cases in low grade group (1-3 grade). The differences of SUV_max, ADC and SUV_max/ADC in different grade groups were compared. Spearman correlation analysis was used to analyze the correlation among SUV_max value, ADC value, SUV_max/ADC, T1, T2, PD value and ISUP classification. Taking pathology as the gold standard, the efficacy of ¹⁸F-PSMA-1007 PET/CT and mp-MRI alone or in combination in the detection of benign and malignant prostate was analyzed. The diagnostic efficacy of SUV_max, ADC, SUV_max/ADC and combined parameters was evaluated by drawing receiver operating characteristic (ROC) and calculating the area under the curve (AUC), sensitivity and specificity, and the differences of AUC values were compared by DeLong test. ResultsThere were significant differences in ADC, SUV_max, SUV_max/ADC between high-grade group and low-grade group (all P<0.001). Correlation analysis showed that there was a negative correlation between ADC and SUV_max in 50 cases of prostate diseases (r=-0.516, P<0.05), a negative correlation between ADC and ISUP in 42 cases of diagnosed PCa (r=-0.616, P<0.05), and a positive correlation between SUV_max, SUV_max/ADC and ISUP (r=0.549, r=0.639, all P<0.05). Magnetic resonance image compilation (MAGiC) sequence was completed in 20 cases, in which T1, T2, PD values were not correlated with ISUP (r＝0.045, r=0.202, r=0.028, all P>0.05), T1 and T2 values were positively correlated with ADC (r＝0.616, r=0.756, all P<0.05), while PD values were negatively correlated with ADC (r=-0.506, P<0.05). There was no significant correlation between SUV_max and T1, T2, PD (r＝-0.132, r＝-0.422, r＝0.230, all P>0.05). ROC curve analysis showed that the AUC of SUV_max was 0.940 and the difference was statistically significant (P<0.001). With SUV_max=7.80 as the critical value, the sensitivity and specificity for the diagnosis of PCa were 83.33% and 100.00%, and the AUC of ADC was 0.970 and the difference was statistically significant (P<0.001). When ADC was 1.20×10^-3 mm²/s, the sensitivity and specificity for the diagnosis of PCa were 95.24% and 87.50%, respectively. The AUC of SUV_max/ADC combined diagnosis of PCa was 0.970, and the difference was statistically significant (P<0.001). With SUV_max/ADC=6.43×10³ as the critical value, the sensitivity and specificity of PCa diagnosis were 90.48% and 100.00%, respectively. The AUC of combining the two parameters was 0.976, and the difference was statistically significant (P<0.001). Taking 0.85 as the critical value, the sensitivity of diagnosing PCa was 90.48%, and the specificity was 100.00%. ConclusionsThe combination of ¹⁸F-PSMA-1007 PET/CT and mp-MRI can improve the diagnostic efficiency of PCa. ADC value, SUV_max and SUV_max/ADC can distinguish between low-risk and medium-high-risk PCa. ]]> Tue,20 Feb 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.02.011 ObjectiveTo investigate the differential diagnostic value of apparent diffusion coefficient (ADC) and relative ADC values of diffusion weighted imaging (DWI) for high-risk prostate cancer (hPCa) in the transition zone and their correlation with International Society of Urological Pathology (ISUP) grading group (GG). Materials and MethodsRetrospective analysis was performed on biparametric MRI data from 40 patients with transition zone prostate cancer confirmed by pathology. This analysis involved measuring the mean ADC (ADC_mean) and minimum ADC (ADC_min) of transition zone prostate cancer and stromal hyperplastic nodules. Additionally, it calculated the relative ADC_mean (rADC_mean) and relative ADC_min (rADC_min), defined as the ratio of ADC values between transition zone carcinoma foci and stromal hyperplastic nodules. The receiver operating characteristic (ROC) curve was used to assess the diagnostic efficacy of each ADC parameter for hPCa in the transition zone and to determine the optimal cutoff value based on the Youden^,s index. DeLong^,s test was used to compare the differences in area under the curve (AUC) of the ROC curve. Spearman correlation analysis was performed to analyze the correlation between each of the ADC parameters and ISUP GG. ResultsThe values of ADC_mean, ADC_min, rADC_mean and rADC_min in the hPCa group were lower than those in the lPCa group (all P<0.05). The AUCs for the differential diagnosis of hPCa in the transition zone were 0.775 [95% confidence interval (CI): 0.615-0.892]、0.879 (95% CI: 0.736-0.960)、0.751 (95% CI: 0.589-0.874) and 0.914 (95% CI: 0.782-0.979) for ADC_mean, ADC_min, rADC_mean and rADC_min, respectively. The maximum AUC was observed with rADC_min. rADC_min showed statistically significant differences in AUC compared to both ADC_mean and rADC_mean (all P<0.05), but not with ADC_min (P>0.05). When the optimal cutoff value of rADC_min was taken as 0.664×10^-3 mm²/s with the highest Youden^,s index (0.783), the sensitivity and specificity of diagnosing hPCa in the transition zone were 100.00% and 78.26%, respectively. ADC_mean, ADC_min, rADC_mean and rADC_min values were all negatively correlated with ISUP GG [r=-0.486 (95% CI: -0.755--0.151), -0.613 (95% CI: -0.769--0.365), -0.553 (95% CI: -0.745--0.260) and -0.678 (95% CI: -0.810--0.474, all P≤0.001]. ConclusionsThe efficacy of rADC_min in differential diagnosing hPCa in the transition zone was high. rADC_min was able to noninvasively predict ISUP GG of PCa in the transition zone, which can help to provide personalized treatment decision support for patients. ]]> Tue,20 Feb 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.02.012 ObjectiveTo explore the predictive value of radiomics analysis basedon magnetic resonance single-index and diffusion kurtosis model functional parameter maps for clinically significant prostate cancer (csPCa). Materials and MethodsA retrospective analysis was conducted on 238 prostate patients who visited Ma^,anshan People^,s Hospital from April 2022 to July 2023. They were confirmed by ultrasound-guided puncture or surgical pathology, including 96 csPCa patients and 142 non-csPCa patients. The age of the patients 56-84 (62.34±7.62) years old. The Clinical data within and between the groups were compared. All patients underwent magnetic resonance multi-parameter scanning, after post-processing, the apparent diffusion coefficient (ADC) pseudo-color plots were generated, and the mean kurtosis (MK) and mean diffusivty (MD) pseudo-color plots in the diffusion kurtosis model were obtained. After image preprocessing, the image features of eachfunctional parameter map are extracted. There are a total of 1 056 radiomics features. The maximum correlation minimum redundancy (MRMR) algorithm and least absolute shrinkage and selection operator (LASSO) are used to eliminateredundancy, perform feature dimensionality reduction, and retain high-quality labels for the data of ADC, MD, and MK models. For relevant features, 10-foldcross-validation was applied to obtain a feature subset, and 238 patients were randomly divided into groups in a ratio of 7∶3. Finally, the ADC model screened out 5 omics features, and the MD model screened out 6 omics features. The MK model screened out 6 omics features, established alogistic regression model, calculated the threshold, accuracy, sensitivity, and specificity of the clinical models, radiology, and clinical-radiology models, and drew the receiver operating characteristic (ROC) curve. Calculate the area under the curve (AUC) and 95% confidence interval (CI), use the DeLong test to combine each model in pairs, compare whether the AUC values between the two groups are statistically significant, and further use decision curve analysis (DCA) to evaluate model performance. ResultsThe AUC, specificity and sensitivity of the clinical model in the training set were 0.840 (95% CI: 0.778-0.901), 78.7% and 76.8%, and in the test set were 0.675 (95% CI: 0.539-0.812), 79.0% and 59.2%, respectively. The AUC, specificity and sensitivity of the ADC model in the training set were 0.927 (95% CI: 0.890-0.964), 81.9%, 86.9%, and in the test set were 0.909 (95% CI: 0.835-0.983), 90.6%, 84.1%, respectively; the AUC, specificity and sensitivity of the MD model in the trainingset were 0.934 (95% CI: 0.899-0.969), 85.1%, 84.0%, and in the test set were 0.960 (95% CI: 0.910-1.000), 93.0%, 85.1%, respectively; the AUC, specificity and sensitivity of the MK model in the training set were 0.935 (95% CI: 0.900-0.971), 90.4%, 84.0%, and in the test set were 0.856 (95% CI: 0.770-0.941), 81.3%, 66.6%, respectively. The AUC, specificity and sensitivity of the clinical-radiology model in the training set were 0.946 (95% CI: 0.912-0.980), 88.2% and 89.8%, and in the test set were 0.963 (95% CI: 0.925-1.000), 93.0% and 85.1%, respectively. DeLong test results showed that there was no significant difference between the radiology model and the clinical-radiology combined model (P>0.05). There was a significant difference in AUC value between the clinical model and the other two models (Z=2.836, P=0.004), and there was no significant difference between the other two groups of models (P>0.05). The decision curve shows that the threshold probability of each model is in the range of 0.1-1.0, which has a net benefit for clinical practice. Different models have a positive effect on the diagnosis of csPCa. The clinical-radiology model having the highest diagnostic performance. ConclusionsThe radiomics analysis technology of MRI mono-exponential and diffusion kurtosis model functional parameter map is an effective method for the detection of csPCa. The clinical-radiology combined model has high diagnostic value for csPCa, which can provide relevant technical support for early clinical diagnosis and treatment. ]]> Tue,20 Feb 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.02.013 ObjectiveTo compare the diagnostic performance of the deep learning model based on bi-parametric MRI with a clinical model for clinically significant prostate cancer (csPCa) and explore the value of a combined model incorporating deep learning model and clinical variables to enhance the diagnostic efficacy of csPCa. Materials and MethodsImaging and clinical data from 531 patients (319 csPCa and 212 non-csPCa) who underwent pre-operative MRI and subsequent biopsy and/or surgical pathology examination for clinically suspected PCa at our hospital from February 2017 to May 2022 were retrospectively analyzed. The patients were randomly divided into a training cohort (425 cases) and a testing cohort (106 cases) at a ratio of 8∶2. The volumes of interests were manually segmented on T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and its derivative apparent diffusion coefficient (ADC) maps and a deep learning model was developed utilizing the DenseNet network. Through univariate and multivariate logistic regressions, clinical features were selected to build a clinical model. A deep learning-clinical combined model was created by integrating the output of the deep learning model with clinical variables based on logistic regression. The receiver operating characteristic (ROC) curve was used to assess the model performance, and the DeLong test was employed to compare the diagnostic performance of different models. ResultsLogistic analyses showed that age, prostate specific antigen (PSA) value and prostate imaging reporting and data system (PI-RADS) score were significant factors for predicting csPCa. In the testing set, the AUC of the deep learning model was 0.90 [95% confidence interval (CI): 0.85-0.96], which showed no significant difference with the clinical model [0.85 (95% CI: 0.78-0.92), P=0.245]. The AUC of the deep learning-clinical combined model reached 0.93 (95% CI: 0.88-0.98), which significantly outperformed both the clinical model (P=0.034) and the deep learning model (P=0.048). ConclusionsThe diagnostic performance of the deep learning model for csPCa was comparable to the clinical model. The deep learning-clinical combined mode achieved the highest diagnostic efficacy, which possessed good practical utility and could be utilized as an auxiliary method for clinical diagnosis of csPCa. ]]> Tue,20 Feb 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.02.014 ObjectiveThe efficacy of combining diffusion weighted imaging (DWI) with T2 mapping sequences in differentiating prostate cancer (PCa) and benign prostatic hyperplasia (BPH). Materials and MethodsWe conducted a retrospective analysis of data from 56 patients diagnosed with PCa and 40 patients with BPH, who underwent 3.0 T MRI examinations at our hospital and received pathological confirmation. The scanning sequences included T1WI, T2WI, DWI and T2 mapping sequences. Two observers independently measured the apparent diffusion coefficient (ADC) values and T2 values of the lesions in both groups. The intra-class correlation coefficient (ICC) was used to assess inter-observer agreement. Differences in ADC values and T2 values between the two groups were analyzed using independent samples t-test or Mann-Whitney U test. Logistic regression was employed to create diagnostic models using discrepant parameters and baseline information. ROC curves were constructed to evaluate the diagnostic efficacy of the differentiated parameters and the joint model. The DeLong test was used to compare differences in the area under the ROC curve (AUC). Spearman^,s correlation coefficient was calculated to assess the correlation between ADC values and T2 values. ResultsExcellent agreement was observed between the measurements of the two observers (ICC>0.75). The PCa group exhibited significantly lower ADC and T2 values compared to the BPH group (P<0.01). The AUC values for ADC, T2, ADC-T2 joint model, and ADC-T2-age-total prostate specific antigen (TPSA) joint model in distinguishing PCa from BPH were 0.843, 0.830, 0.896 and 0.927. DeLong^,s test showed statistically significant differences in the ROC curves for ADC and ADC-T2 jointly and for ADC, T2, ADC-T2 model and ADC-T2-age-TPSA joint model (P< 0.05). ADC values were positively correlated with T2 values (r=0.331, P<0.01). ConclusionsDWI and T2 mapping hold substantial value in differentiating between PCa and BPH. The diagnostic efficacy improves when combining these sequences with clinical indicators such as age and TPSA. This combined imaging approach offers promising non-invasive diagnostic guidance for PCa and BPH in clinical settings. ]]> Tue,20 Feb 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.02.015 ObjectiveTo explore the potential value of a 3D convolutional neural network (CNN) model based on automatically segmented meniscus MRI in predicting the occurrence of knee osteoarthritis (KOA). Materials and MethodsThis retrospective study used data from the Osteoarthritis Initiative (OAI), a publicly available database. A total of 130 baseline knee joint MRI images were randomly selected, and the meniscus regions of interest were manually delineated by trained musculoskeletal radiologists to train the meniscus MRI segmentation model. The meniscus segmentation was performed on the incident osteoarthritis cohort of OAI, and a 3D CNN model for KOA prediction was constructed. The incident osteoarthritis cohort included 710 knee joints with baseline Kellgren-Lawrence (KL) grading of ≤1, and no radiographic KOA at baseline. During a 48-month follow-up, cases with radiographic KOA (KL grade≥2) were considered as the case group, while those without radiographic KOA served as the control group, matched in a 1∶1 ratio. KOA prediction models were built using baseline and the time point one year before the occurrence of radiographic KOA (P-1) knee joint MRIs. The Dice coefficient was used to evaluate the performance of the meniscus MRI segmentation model. The predictive value of models based on meniscus MRI, clinical information, and MRI Osteoarthritis Knee Score (MOAKS) was assessed using the area under the curve (AUC) of the receiver operating characteristic curve. ResultsThe meniscus segmentation model achieved a Dice coefficient of 90.32% on the test set. At baseline and P-1 time points, the 3D CNN KOA prediction model (baseline AUC: 0.60; P-1 AUC: 0.71) outperformed models based on clinical information (baseline AUC: 0.55; P-1 AUC: 0.63) and MOAKS (baseline AUC: 0.52-0.56; P-1 AUC: 0.51-0.64) in the test set, with statistically significant differences (P<0.05). ConclusionsThe 3D CNN KOA prediction model based on automatically segmented meniscus MRI demonstrates superior predictive capabilities for the occurrence of radiographic knee osteoarthritis compared to clinical information or semi-quantitative MRI scoring. ]]> Tue,20 Feb 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.02.016 ObjectiveBased on multivariate pattern analysis (MVPA), effectively identify the brain functional connections between flight cadets and healthy individuals. Materials and MethodsFunctional magnetic resonance data were collected from 40 licensed flight major students and 39 ground major students. The functional connectivity matrix was obtained through network functional connectivity analysis as a feature, and the feature dimensionality was reduced using the least absolute shrinkage and selection operator (LASSO) algorithm and independent sample t-test method, respectively. Support vector machines (SVM) with different kernel functions were used for training and prediction, and the performance of the model was evaluated using the left one cross validation method. Finally, the functional connections between corresponding brain regions were located based on the weight information in the trained SVM model. ResultsThe linear kernel SVM model using LASSO feature screening had an accuracy of 81.82%, sensitivity of 82.05%, specificity of 81.58%, and area under the curve (AUC) of 0.88. The kernel function had little effect on the accuracy of the model. In the model, the right paracentral lobule, bilateral posterior central gyrus, bilateral inferior parietal angular gyrus, right fusiform gyrus, left orbital frontal gyrus, left superior parietal gyrus, and right orbital inferior frontal gyrus had higher weights. The weights in the model were concentrated in the somatomotor network (SMN) and default mode network (DMN), accounting for 25.62% and 25.27% of all weights, respectively. ConclusionsSVM combined with LASSO algorithm for feature filtering can effectively recognize the brain of flight students, and has better interpretability and smaller overfitting. The weight information of the model reflects that flight students are mainly different from ordinary people in terms of motor and perceptual abilities. ]]> Tue,20 Feb 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.02.017 ObjectiveThis study aims to investigate the brain activation areas and lateralization patterns of native Chinese speakers processing auditory language signals in dichotic listening conditions. It utilizes the low-pass filtering method and dichotic listening technique to derive neural processing models through functional magnetic resonance imaging (fMRI). Materials and MethodsThirty participants (age 25.36±0.88 years, native Chinese speakers, and strongly right-handed) participated in the study from January to May 2022 in the First Affiliated Hospital of Kunming Medical University. Chinese short sentences were low-pass filtered (<320 Hz), retaining only low-frequency prosodic information. Auditory signals were presented in two dichotic listening conditions: filtered in the left ear and unfiltered in the right ear (FL), and filtered in the right ear and unfiltered in the left ear (FR). Participants alternately listened to two groups of signals, while two sessions of block-design fMRI scanning were conducted. After preprocessing the image data using SPM 12 software, one-sample t-tests within the group and two-sample t-tests between the groups were performed to identify similarities and differences in the distribution and intensity of brain activation areas during signal processing. Regions of interest (ROIs) were identified based on the one-sample t-tests, and the lateralization indices of the ROIs were then calculated to determine lateralization patterns. ResultsBoth signal groups activated the bilateral middle temporal, superior temporal, inferior frontal, the left precentral, and the right middle frontal gyri (P<0.05, FDR-corrected). Additionally, FL signals led to increased blood oxygen levels in the left frontal gyrus (P<0.05, FDR-corrected), and FR signals activated the bilateral inferior parietal lobule (P<0.05, FDR-corrected). Two-sample t-tests revealed significant differences in the right middle temporal gyrus and superior temporal gyrus in the contrast of FR vs. FL (P<0.05, FDR-corrected). No significant difference was observed in the contrast of FL vs. FR. Lateralization indices indicated no clear lateralization patterns at the hemispheric level for both signal groups. However, both groups exhibited right-lateralized activity in the middle frontal gyrus and left asymmetry in the precentral gyrus. Furthermore, the FR signal induced left-lateralized activation in the inferior parietal lobule. ConclusionsProcessing Chinese auditory signals in dichotic listening conditions involves a speech processing model comprising the bilateral middle and superior temporal, inferior frontal gyri, and the right middle frontal gyrus. The dichotic FR signal not only activated language-relevant brain regions but also recruited additional regions for speech perception and cognitive control compared to FL. Conversely, FL appeared to reduce the load of phonological processing in the right middle and superior temporal gyri, aligning with left and right hemispheric specialization for linguistic and prosodic processing. ]]> Tue,20 Feb 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.02.018 ObjectiveTo investigate the application value of MRI contrast agent Gd-DTDAS in multiple sclerosis (MS) rat myelin injury model. Materials and MethodsIn cell experiments, oligodendrocyte precursor cells (OLN-93) were randomly divided into control group 2 (n=3) and lysophosphatidylcholine (LPC) group (n=3), and the cells of LPC group were incubated with 1 mL of 800 μM LPC in a sterile confocal dish for 30 min. Cytotoxicity was evaluated by methyl thiazolyl tetrazolium (MTT), and the absorbance and survival rate of OLN-93 after incubation with Gd-DTDAS for 24 h were calculated. In the uptake experiment, the control group 2 and the LPC group were compared to quantify the uptake value of Gd-DTDAS and the corresponding fluorescence intensity of the two groups. In animal experiments, 6-8 week-old SD rats were randomly divided into control group (n=12) and experimental group (n=18), and the left corpus callosum of rats in the experimental group was injected with 1% LPC solution (1% LPC dissolved in PBS). After molding, behavioral observation was performed (1, 3, 7 d), and T1WI and T2WI sequence scanning were performed 7 d after injecting. Gd-DTDAS staining (n=6) and soaking (n=6) of rat brain tissue were performed according to the MRI abnormal signal site to evaluate the binding of Gd-DTDAS to the myelin site. Among them, the staining experiment was named as control group 3 and experimental group 3, while the soaking experiment group was named as control group 4 and experimental group 4. Gd-DTDAS was injected by tail vein, MRI assessed cerebral myelin sheath changes before and after Gd-DTDAS injection in the experiment group (n=6). ResultsIn the cytotoxicity experiment, when the concentration of Gd-DTDAS increased to 400 μM, the survival rate of OLN-93 cells was about 95%, and there was no significant difference in cell survival between concentrations (t=4.20, P>0.05). In the cell uptake experiment, both groups of cells could uptake Gd-DTDAS, and the uptake of LPC group was significantly lower than that of the control group 2, and the difference was statistically significant (t=31.75, P<0.01). In vitro experiments, compared with the control group 3, the fluorescence intensity of brain tissue sections in the experiment 3 group stained with Gd-DTDAS decreased significantly, and the difference was statistically significant (U=9, P<0.01). After immersion of brain tissue slices in Gd-DTDAS, the MRI resolution significantly increased in both the control group 4 (n=3) and the experiment group 4 (n=6), with statistically significant differences (control group 4, t =8.76, P<0.01; experiment group 4, t =2.89, P<0.01). In vivo experiments, MRI T1maps relaxation in the medullary region was significantly reduced after injection compared with before tail vein injection (t =14.46, P<0.01). ConclusionsThe myelin probe Gd-DTDAS can better bind to myelin-rich regions, and the myelin sheath can be better targeted for MRI, and can specifically show the damage site of myelin sheath in multiple sclerosis. ]]> Tue,20 Feb 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.02.019 ObjectiveExploring the application value of voxel-mirror homotopic connectivity (VMHC) and regional homogeneity (ReHo) in evaluating transcranial direct current stimulation (tDCS) in improving cognitive impairment after stroke. Materials and MethodsA total of 47 patients with post-stroke cognitive impairment (PSCI) were prospectively included and randomly assigned to the tDCS group and sham stimulation group. Among them, 23 patients were in the tDCS group and 24 patients were in the sham stimulation group. Use Mann Whitney U-test to compare the differences in cognitive scale scores between two groups of patients at baseline and 15 days after tDCS or sham stimulation treatment. Use paired t-test to compare the differences in VMHC and ReHo result between two groups of patients at baseline and 15 days after tDCS or sham stimulation treatment. Collect and extract VMHC and ReHo values of different brain regions for correlation analysis with changes in scale scores before and after treatment. ResultsThe Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores of the tDCS group and the sham stimulation group after treatment were better than before treatment, but the tDCS group had better treatment effect. After treatment, the MMSE and MoCA scores improved significantly compared to before treatment, with a statistically significant difference (P<0.05); VMHC results: After treatment, the VMHC values in the bilateral insula and anterior cuneiform lobes of patients in the tDCS group increased (P<0.05, FDR correction), while the VMHC values in the bilateral superior occipital gyrus of patients in the sham stimulation group increased (P<0.05, FDR correction); ReHo results: After treatment, the ReHo values in the anterior cingulate gyrus and inferior parietal angular gyrus of patients in the tDCS group increased (P<0.05, FDR correction), while there was no significant difference in brain regions between the sham stimulation group and before treatment; Correlation analysis: After treatment, the increase in VMHC in the bilateral anterior cuneiform lobes of patients in the tDCS group showed a positive correlation with changes in MMSE and MoCA scales; MMSE (r=0.47, P=0.02); MoCA (r=0.43, P=0.04), while there was no significant correlation between other brain regions and changes in MMSE and MoCA scales. ConclusionsThe cognitive rehabilitation effect of tDCS combined with conventional rehabilitation treatment on PSCI patients is better than that of conventional rehabilitation treatment alone. The application of VMHC and ReHo found that the treatment mechanism of tDCS may be related to improving the functional connectivity and spontaneous activity of some brain regions between the bilateral hemispheres in the default mode network (DMN) and salience network (SN). ]]> Tue,20 Feb 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.02.020 ObjectiveTo investigate the effects of different acceleration factors based on artificial intelligence-assisted compressed sensing (ACS) on the image quality of 3D T2WI fluid-attenuated inversion-recovery (3D T2-FLAIR) sequence. Materials and MethodsTwenty-five healthy volunteers (HC) and fifteen patients with white matter hyperintensity (WMH) were prospectively included in the study. In HC group, the brain 3D T2-FLAIR images were collected by parallel imaging (PI) technique (parallel acquisition acceleration factor was 3) and ACS technique with different acceleration factors (3, 4, 5, 6, 7, 8). The signal intensity (SI) and standard deviation (SD) of all 3D T2-FLAIR images were measured in bilateral centrum semiovale, bilateral caudate nucleus, splenium of corpus callosum, bilateral red nucleus, bilateral substantia nigra, pons and bilateral cerebellum. The signal to noise ratio (SNR) and contrast to noise ratio (CNR) were further calculated. The subjective score of image quality was analyzed according to five grades standard. The intra-class correlation coefficient (ICC) and Kappa test were used to compare the consistency between the measured data and the subjective scores of the two observers. The SNR, CNR and subjective scores of images with different acceleration factors were compared by Friedman test. After comprehensive evaluation, the best ACS acceleration factor is obtained. In the WMH group, 3D T2-FLAIR images of the brain were collected with F3 and the best ACS acceleration factor, and the number of WMH and Fazekas grades were evaluated by two experienced diagnostic physicians. Independent sample t test and Mann-Whitney U test were used for comparative analysis. ResultsIn HC group, The SNR, CNR and subjective scores of different 3D T2-FLAIR sequences were statistically significant (all P<0.05). The results of pairwise comparison showed that the SNR and CNR of 3D T2-FLAIR_ACS3, 3D T2-FLAIR_ACS4 and 3D T2-FLAIR_F3, and the subjective scores of 3D T2-FLAIR_ACS3, 3D T2-FLAIR_ACS4, 3D T2-FLAIR_ACS5 and 3D T2-FLAIR_F3 were not statistically significant (all P>0.05). The SNR, CNR and subjective scores of the remaining images were statistically significant (all P<0.05). In the WMH group, there was no significant difference in the number of WMH and Fazekas grades between 3D T2-FLAIR _F3 and 3D T2-FLAIR _ACS4 ( P>0.05 ). ConclusionsThe acquisition of brain 3D T2-FLAIR with ACS technology can shorten the scanning time under the premise of ensuring image quality and diagnostic efficiency, and ACS4 can be considered as the best acceleration factor. ]]> Tue,20 Feb 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.02.021 ObjectiveUsing magnetic resonance contrast enhancement-steady state free precession (CE-SSFP) cine sequence to detect ST-segment elevation myocardial infarction (STEMI) in elderly patients with microvascular obstruction (MVO). STEMI patients were evaluated for image quality and combined with sequence parameter analysis to further explore its diagnostic performance for MVO. Materials and MethodsThe clinical data of 50 patients with STEMI (STEMI group) from September 2016 to March 2023 were retrospectively analyzed. All patients underwented CE-SSFP cine sequence short axis, four chamber, and two chamber scans. The STEMI patient group was included according to the 2020 European Heart Journal guideline standards and healthy controls matched for gender and age were collected. Qualitative and quantitative image quality evaluation of the myocardium and blood pool were performed on the CE-SSFP sequence by two diagnostic radiologists. The independent sample t test was used to analyze the general information and imaging data between the STEMI group and the healthy control group. The diagnostic performance of CE-SSFP sequence for MVO was analyzed using receiver operating characteristic (ROC) curve. ResultsThe CE-SSFP images of 48 patients (96%) in the STEMI group and 49 volunteers (98%) in the healthy control group could meet the diagnostic conditions; the contrast-to-noise ratio of the blood pool and myocardium in the STEMI group was significantly better than that in the healthy control group (222.9±15.6 vs. 170.1±14.9, t=4.631, P<0.05); the sensitivity of CE-SSFP to manually identify MVO was 91.38%, the specificity was 91.88%, and the Youden index was 0.833; the sensitivity of MVO was evaluated with 2 times the standard deviation. The specificity was 90.23%, the specificity was 89.94%, and the Youden index was 0.802. The areas under the curve for the two methods were 0.931 and 0.909 respectively. ConclusionsThe CE-SSFP sequence can quantitatively evaluate the image quality of patients with STEMI combined with MVO, provide effective indicators for quantitatively identifying MVO, and provide imaging basis for clinical diagnosis. ]]> Tue,20 Feb 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.02.022 ObjectiveTo investigate the effects of different flip angles (FA) and delay times on the image quality of liver and biliary system in hepatobiliary phase (HBP) images of gadobenate dimeglumine (Gd-BOPTA)-enhanced magnetic resonance images (MRI). Materials and MethodsFifty-seven patients with abdominal discomfort, who had undergone a 3.0 T upper abdominal Gd-BOPTA-enhanced MRI scan at our hospital, were retrospectively included. HBP imaging was conducted with FA of 10°, 15°, 20°, 25°, and 30°, at delays of 60 minutes and 120 minutes post-contrast agent injection. These combinations of FA and delay time were categorized into 10 groups. Signal intensity (SI) of the liver and common bile duct, SI and standard deviation (SD) of the erector spinae were measured. Additionally, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and bile to paravertebral muscle ratio (BMR) were calculated. The visibility of the biliary tract in the images was evaluated using the 5-point method. Intra-group correlation coefficient (ICC) and the weighted Kappa test were employed to assess the consistency of the measured data and subjective scores between the two observers. The nonparametric Friedman test was utilized to compare the SNR, CNR, BMR, and subjective scores among images with different combinations of delay time and FA. LSD-t test was used to compare SNR, CNR, BMR and subjective score in each group, and Bonferroni correction was carried out on the results. The optimal combination of FA and delay time was determined based on the statistical results. ResultsThe data and subjective from both observers exhibit strong agreement (ICC values are all>0.75, Kappa values are all>0.75) except the SNR_liver for the 120min/FA15°group (ICC=0.75). Across all parameters values at the group of 120-minute delay time are consistently higher than the group of 60-minute delay time. The SNR of the liver in the 120min/FA30° group ecorded the highest value [63.91 (49.44, 77.15)], which was significantly better than 60min/FA10°and 120min/FA10°groups (P<0.05). The CNR_liver in the 120min/FA30° group ecorded the highest value [44.21 (31.58, 53.64)], demonstrating a significant difference compared to the 60min/FA10°, 60min/FA15°, 60min/FA30° and 120min/FA10° groups (P<0.05). The SNR of the bile duct in the 120min/FA30° group ecorded the highest value [305.27 (193.97, 377.53)], which was significantly better than 60min/FA10°, 60min/FA15°, 60min/FA20°, 60min/FA25°, 120min/FA10°, and 120min/FA15°groups (P<0.05). The CNR_{common bile duct} in the 120min/FA30° group ecorded the highest value [278.66 (180.80, 357.20)] , which was significantly different from the 60min/FA10°, 60min/FA15°, 60min/FA20°, 60min/FA25°, 60min/FA30°, 120min/FA10°, and 120min/FA15°groups (P<0.05). The BMR in the 120min/FA30° group ecorded the highest value[14.75 (11.55, 17.87)], which was significantly different from the 60min/FA10°, 60min/FA15°, 60min/FA20°, 60min/FA25°, 120min/FA10°, and 120min/FA15°groups (P<0.05). According to the subjective scoring results, the visibility of biliary tract at 60min/FA10° was the worst, which was obviously lower than 60min/FA20°, 60min/FA25°, 60min/FA30°, 120min/FA15°, 120min/FA20°, 120min/FA25°, and 120min/FA30°groups (P<0.05). ConclusionsBy evaluating various combinations of different FA and delay times, it is evident that the 120min/FA30° group exhibits the highest image quality for enhanced liver and biliary tract in HBP of Gd-BOPTA-enhanced MRI. Increasing the FA and extending the delay time notably enhance image quality. ]]> Tue,20 Feb 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.02.023 ObjectiveTo investigate the application of compressed sensing (CS) with different acceleration factors (AF) and combined with parallel acqusition technique (PAT) of three-dimensional liver acqusition with volume acceleration flexible (3D LAVA FLEX) breath-holding sequence in rapid magnetic resonance imaging of liver. Materials and MethodsA total of 28 healthy subjects were recruited for liver MRI scan using breath-holding 3D LAVA FLEX sequence combined with PAT AF 2 and CS with different AF at GE Architect 3.0 T MR scancer. The scanning sequences were divided into PAT 2 group and CS 1.2, CS 1.5, CS 2, CS 2.4 group based on PAT 2. Two observers were subjectively rated a 5-point scale on the image quality of water phase, in-phase (IP) and opposed-phase (OP) of liver. In the same slice of porta hepatis, the regions of interest (ROI) were placed on the anterior and posterior segments of the right hepatic lobe, the inner and outer segments of the left hepatic lobe, and the right erector spinae. The signal intensity (SI) value of each ROI and the standard deviationg (SD) value of erector spinae were recorded, and calculated the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Inter-class correlation cofficient (ICC) was used to analyze the consistency of subjective scores and measurement data of the two observers. Kruskal-Wallis H test was used to analyze the differences among subjective scores. One-way analysis of variance (ANOVA) was used to compare the differences of SNR and CNR among different groups. ResultsThere was good agreement between the two observers on the subjective score of image quality and the measured data (ICC>0.75). There was significant difference in subjective evaluation among the five groups of water phase, IP and OP images (P<0.001, P<0.001, P<0.001). There was significant difference in the SNR of the right anterior and posterior lobe and the inner and outer segments of the left lobe among the five groups (P<0.001, P=0.004, P=0.002, P<0.001), but there was no significant difference in the CNR among the five groups (P=0.802, P=0.979, P=0.772, P=0.910).When CS AF=2.4, the subjective scores of water phase, IP and OP images were significantly different from those in the regular PAT 2 group (P=0.009, P<0.001, P<0.001), and the SNR in the anterior and posterior segments of the right hepatic lobe,the inner and outer segments of the left hepatic lobe were significantly different from those in the conventional PAT 2 group (P=0.010, P=0.002, P<0.001, P<0.001). ConclusionsWith the increase of CS AF, the scanning time was gradually shortened. Under the premise of ensuring image quality, CS AF 2 was clinically recommended as the scanning parameter of liver dynamic enhancement and IP, OP imaging for breath-holding 3D LAVA FLEX sequence based on PAT AF 2, and the scanning time was reduced by 44% compared with the regular scanning scheme of PAT AF 2, and the imaging efficiency was greatly improved. ]]> Tue,20 Feb 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.02.026 Tue,20 Feb 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.02.027 Tue,20 Feb 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.02.028 ^,s disease, significantly impacting their quality of life. However, there is still no clear elucidation of the pathogenesis and changes in brain structure and function during the course of the disease. In recent years, multimodal MRI imaging techniques, primarily utilizing diffusion tensor imaging (DTI), three-dimensional T1-weighted imaging (3D T1WI) and functional MRI (fMRI) have been widely employed in the exploration of the pathogenesis of neurological disorders. These techniques have provided new insights into the underlying mechanisms of FOG. Recent research indicates a close association between changes in visual, motor, and cognitive networks and the occurrence of FOG. The author aims to conduct a review by analyzing recent domestic and international literature, summarize multimodal MRI exploration of structural and functional changes in the brains of Parkinson^,s disease patients with freezing of gait. The review discusses the current controversial aspects of FOG research and proposes new perspectives for future comprehensive elucidation of its pathogenesis using multimodal MRI. ]]> Tue,20 Feb 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.02.029 ^,s disease (PD), a prevalent neurodegenerative disorder, is characterized by the degeneration of dopamine neurons containing NM in the substantia nigra, resulting in a decrease in NM. Consequently, the detection of variations in NM-MRI of the substantia nigra can serve as an indirect indicator of the functional state of dopamine neurons. Role of NM-MRI in the diagnosis of PD cannot be ignored, furthermore, this paper reviews the recent advancements in NM-MRI research pertaining to the imaging of PD, with the objective of offering enhanced reference value for future related investigations, it is expected that with the maturity of NM-MRI technology, it will become an imaging tool to assist in clinical PD diagnosis and contribute to the study of the pathological mechanisms of PD. ]]> Tue,20 Feb 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.02.030 Tue,20 Feb 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.02.031 Tue,20 Feb 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.02.032 Tue,20 Feb 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.02.033 1H-MRS) have being used to explore the relationship between neuropathophysiological changes and clinical symptoms of PCS from acute to chronic phase. In this review, in order to gain a deeper understanding of their underlying neuropathological mechanisms from different perspectives, we using various MRI methods in PCS to serve the diagnosis, treatment, and prognosis of diseases by the different stages of patient injury and the severity of symptoms. ]]> Tue,20 Feb 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.02.034 Tue,20 Feb 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.02.035 Tue,20 Feb 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.02.036 Tue,20 Feb 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.02.037 Tue,20 Feb 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.02.038 ^, quality of life and reducing unnecessary economic burden. At the same time, the above technology become a research hotspot gradually in the future. This review focuses on the application of multimodal function MRI in the staging and grading of BC both domestically and internationally in recent years, providing a more reliable imaging basis for clinical diagnosis and treatment. ]]> Tue,20 Feb 2024 00:00:00 GMT