http://med-sci.cn/cgzcx/en/contents_list.asp?issue=202501 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.1674-8034.2025.01.001 Mon,20 Jan 2025 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2025.01.002 Mon,20 Jan 2025 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2025.01.003 Mon,20 Jan 2025 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2025.01.004 ObjectiveThe mutation status of the B-Raf proto-oncogene, serine/threonine kinase (BRAF) gene, a homolog of the murine sarcoma virus oncogene B, is related to the survival of patients with colorectal tumors. This study aims to explore the feasibility of using a radiomics model to predict BRAF gene mutations in colorectal cancer patients. Materials and MethodsA retrospective analysis was conducted on the case data of patients diagnosed with rectal cancer at our institution from June 2020 to June 2023, utilizing exon sequencing to identify BRAF gene mutations. Survival analysis was performed to evaluate the relationship between BRAF mutations and prognosis in rectal cancer. From 260 patients with multi-parametric magnetic resonance imaging, 7,388 modules were extracted, including preoperative T1-weighted images (T1WI), T2-weighted images (T2WI), and contrast-enhanced T1-weighted images (CE-T1WI). Finally, a feature-based radiomics model was established using convolutional neural networks (ConvNet). The model^,s performance was evaluated using receiver operating characteristic (ROC) curves, accuracy, sensitivity, and specificity as metrics. ResultsThe study included 89 patients with BRAF mutations and 171 patients with wild-type BRAF. There were no significant differences in clinical characteristics such as tumor malignancy staging, age, and sex between the two groups (P > 0.05); however, a significant difference was observed in the 5-year survival rates. The survival duration of the BRAF mutation group was significantly lower than that of the wild-type group (P < 0.001). The area under the ROC curve for the predictive model was 0.929, The Kappa statistic for the consistency analysis with pathological results was 0.87, indicating good predictive value. ConclusionsThe radiomics model constructed using convolutional neural networks can effectively distinguish BRAF mutation status in rectal cancer patients, providing new insights for non-invasive screening of BRAF status in the future. ]]> Mon,20 Jan 2025 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2025.01.005 ObjectiveThe main objective of this study is to use the grayscale inversion technology in the post-processing workstation to reverse the density in conventional CT scanned images, to obtain images similar to MRI-T2WI, and to evaluate the application value of multidetector-row computed tomography (MDCT) in mesorectal fascia (MRF) display. Materials and MethodsThe images of 87 patients with rectal adenocarcinoma who only had preoperative CT examination because of contraindications in MRI scanning were retrospectively analyzed. The differences of peritoneal reflection and MRF display and display range between conventional CT images and "conventional CT+inversion images" were subjectively evaluated and compared. According to the postoperative pathological results, the diagnostic accuracy of conventional CT images and "conventional CT+inversion images" for MRF invasion was compared. The images of 123 patients with rectal adenocarcinoma who underwent radical surgery in the same period and had complete preoperative MRI data were collected retrospectively. The peritoneal reflection, MRF display and display range in MRI-T2WI were subjectively evaluated. The accuracy of MRI in the diagnosis of MRF invasion was evaluated according to the postoperative pathological results. The differences of peritoneal reflection, MRF display, display range and diagnostic accuracy of MRF invasion between "conventional CT+inversion images" and MRI-T2WI were compared. ResultsThe display rate of peritoneal reflection was 24.1% in conventional CT images and 52.9% in "conventional CT+inversion images", and the display rate of peritoneal reflection was significantly higher in "conventional CT+inversion images" than in conventional CT images (P < 0.001). In the display range of MRF, the display range of "conventional CT+inversion images" was significantly larger than that of conventional CT images, and there were significant differences in anterior, posterior, left and right positions (P < 0.001). Taking the circumferential resection margin (CRM) status evaluated by pathology as the gold standard. The sensitivity, specificity and accuracy of conventional CT images for the diagnosis of MRF invasion were 73.3%, 93.1% and 81.6%, respectively; the sensitivity, specificity and accuracy of "conventional CT+inversion images" for the diagnosis of MRF invasion were 100.0%, 95.8% and 96.6%, respectively. The accuracy of "conventional CT+inversion images" was significantly higher than that of conventional CT images (P = 0.035). The sagittal MRI-T2WI showed 80.5% of peritoneal reflection, and MRI-T2WI was superior to inversion CT in showing peritoneal reflection (P < 0.001). In terms of MRF display range, there is a difference in the posterior MRF display range between "conventional CT+inversion images" and axial MRI-T2WI, with MRI-T2WI being able to display a larger range. The sensitivity, specificity, and accuracy of MRI images in diagnosing MRF invasion were 100.0%, 93.1%, and 93.5%, respectively, using the CRM status of pathological evaluation as the gold standard. There was no statistical difference in the accuracy of MRI images and "conventional CT+inversion images" in diagnosing MRF invasion (P = 0.528). ConclusionsConventional CT images after inversion can better display and evaluate MRF status, and for patients with contraindications of MRI scanning, "conventional CT+inversion images" can be used as a better alternative to imaging evaluation, and provide an important reference for the formulation of individual diagnosis. ]]> Mon,20 Jan 2025 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2025.01.006 ObjectiveThrough the study of intravoxel incoherent motion (IVIM), this research investigates the predictive value of tumor and mesorectum parameters for synchronous rectal liver metastasis (SRLM) in rectal cancer. Materials and MethodsA retrospective analysis was conducted on data from 112 patients with pathologically confirmed rectal cancer, including 42 patients with SRLM. The patients were divided into the SRLM group (n = 42) and the non-SRLM group (n = 70). On the maximum cross-sectional image of the tumor, three regions of interest (ROI) were delineated: one in the tumor, one in the near-tumor area (ROI < 5 mm from the tumor), and one in the distant-tumor area (ROI > 10 mm from the tumor). IVIM parameters apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudo-diffusion coefficient (D^*), and perfusion fraction (f) were measured The Mann-Whitney U test and the Wilcoxon test were used to compare the statistical significance of parameter differences between and within the groups, respectively. The predictive performance of parameters showing statistically significant differences between groups was evaluated using receiver operating characteristic (ROC) curves. ResultsCompared with the non- SRLM group, the SRLM group showed significantly increased parameters ADC, D, and f in the distant tumor area (P < 0.001), and increased D and f in the near tumor area (P < 0.05). However, the differences in tumor parameters were not statistically significant (P > 0.05). After intragroup comparison, the ADC values in the distal tumor regions of both groups were significantly lower than those in the corresponding proximal tumor regions and tumor parameters (P < 0.05), and the D values were significantly lower than those in the corresponding proximal tumor regions and tumor parameters (P < 0.001). Yet, ADC and D in the near tumor area showed no statistically significant differences compared to the corresponding tumor parameters (P > 0.05). Although the parameter f in the distant tumor area was lower than in the near tumor area, this difference was not statistically significant in the SRLM group (P > 0.05). The parameters ADC, D, and f in the distant tumor area predicted the area under the curve (AUC) for predicting SRLM using the ADC, D, and f parameters of the mesorectum distal to the tumor were 0.769 (95% CI: 0.675 to 0.862), 0.745 (95% CI: 0.644 to 0.845), and 0.733 (95% CI: 0.635 to 0.831), respectively. ConclusionsThe IVIM parameters ADC, f, and D in the distant tumor area of the mesorectum can serve as imaging biomarkers to predict the likelihood of SRLM in rectal cancer. Their assessment is of significant clinical importance for the timely diagnosis of SRLM and for identifying patients with occult and high-risk Liver metastases. ]]> Mon,20 Jan 2025 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2025.01.007 ObjectiveTo explore the value of amide proton transfer weighted (APTw) imaging with apparent diffusion coefficient (ADC) in the preoperative assessment of tumor budding (TB) grade in rectal cancer. Materials and MethodsWe retrospectively analyzed the clinical and imaging data of 121 patients with rectal cancer. Based on pathological tumor budding counts, the patients were categorized into intermediate-low-grade and high-grade groups. The APT and ADC values were compared between the two groups, and the correlation between APT and ADC values and TB grades was investigated. Intra-class correlation coefficients (ICC) were used to assess the consistency of data measured by the observer before and after evaluation. Binary logistic regression comprehensive input method was employed to analyze the association between variables and the grade of rectal cancer tumor budding. Receiver operating characteristic (ROC) curves were utilized to assess the statistical significance of parameters and their combined efficacy. The area under the curve (AUC) along with its 95% confidence interval, as well as corresponding thresholds, sensitivities, and specificities, were calculated. DeLong tests were conducted to compare the differences in AUC. Spearman correlation analysis was performed to investigate the relationship between each parameter and tumor budding. ResultsOne hundred and twenty-one patients were enrolled, The distribution of TB grade was intermediate-low grade (n = 69) and high-grade (n = 52). The APT and ADC values measured by the two observers showed good consistency, with ICC values were 0.925, 0.877. The APT value for intermediate-low grade TB of rectal cancer was significantly lower (2.068% ± 0.588%) compared to high-grade TB (3.167% ± 0.592%) (P < 0.001). Additionally, the ADC value for intermediate-low grade rectal cancer TB [(1.064 ± 0.131) × 10^-3 mm²/s] was higher than that of the high-grade TB group [(0.903 ± 0.138) × 10^-3 mm²/s]. In multivariate analysis, APT value [OR: 15.079 (95% CI: 4.822 to 47.154)] and ADC value [OR: 0.004 (95% CI: 0.001 to 0.228)] were identified as independent risk factors for predicting TB grades. The areas under the curve (AUC) for APT, ADC, and their combined assessment of rectal cancer tumor budding grade were 0.916, 0.821, and 0.918, respectively. The DeLong test results showed statistically significant differences in AUCs between ADC and APT values, as well as their combined assessment of TB grade (P = 0.024, 0.004). The decision curve shows that the combination of the two has higher clinical value than using APT and ADC values alone. APT values exhibited a moderate positive correlation with TB grade (r = 0.713, P < 0.001), while ADC values demonstrated a moderate negative correlation with TB grade (r = -0.550, P < 0.001). ConclusionsAPT and ADC can effectively assess the TB grade of rectal cancer and have some clinical applications, and the combination of APT and ADC can significantly improve the diagnostic efficacy. ]]> Mon,20 Jan 2025 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2025.01.008 ObjectiveTo investigate the application value of MRI apparent diffusion coefficient (ADC) combined with clinicopathological characteristics in predicting microsatellite instability (MSI) of colorectal cancer. Materials and MethodsThe clinicopathologic data of 144 patients with colorectal cancer confirmed by pathology were analyzed retrospectively. All patients underwent abdominal or pelvic MRI examination before surgery. According to immunohistochemistry (IHC) results, patients were divided into MSI group and microsatellite stability (MSS) group. The MSI group included cases with high frequency MSI (MSI-H) and low frequency MSI (MSI-L). SPSS software was used to compare the clinical baseline data of patients, and binary logistic regression was used to analyze MSI risk factors for colorectal cancer. Multivariate regression independent predictors were included to construct a nomogram model. Receiver operating characteristic (ROC) was used to evaluate the diagnostic efficacy of ADC model and ADC-clinicopathological combined model, and the area under the curve (AUC) was calculated. DeLong test was used to compare the model differences. Calibration curves were used to evaluate the predictive accuracy of the model, and decision and impact curves were used to evaluate the clinical utility of the predictive model. ResultsOne hundred and forty-four patients with colorectal cancer were included, including 16 patients in MSI group and 128 patients in MSS group. ADC value (1.107 ± 0.335) × 10^-3 mm²/s in MSI group was higher than that in MSS group (0.868 ± 0.262) × 10^-3 mm²/s, P = 0.011. Among the collected clinicpathological features, the history of chronic gastroenteritis (P < 0.001), D2-40 (P = 0.009), clinical stage (P < 0.001), showed statistically significant differences between the MSI group and the MSS group. The above four independent predictors were combined to form a nomogram. Among the ADC model and the ADC-clinicopathologic feature combined model, the ADC-clinicopathologic feature combined model predicted the MSI performance of colorectal cancer better. The AUC was 0.901 [95% (confidence interval, CI): 0.783 to 1.000], and the sensitivity and specificity were 87.5% and 93.0%, respectively. ConclusionsThis study shows that the ADC model and the ADC-clinicopathological features combined model have good predictive performance for MSI status of colorectal cancer, and the ADC-clinicopathological features combined model has the best performance. This study can provide a safe and non-invasive method for predicting MSI of colorectal cancer before clinical operation. ]]> Mon,20 Jan 2025 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2025.01.009 ObjectiveTo explore the application value of preoperative prediction of lymphovascular invasion (LVI) in rectal cancer patients using axial high-resolution T2WI and deep transfer learning radiomics. Materials and MethodsA retrospective analysis was conducted on clinical and imaging data of 384 patients diagnosed with rectal cancer by postoperative pathology at Yijishan Hospital of Wannan Medical College from January 2018 to December 2023. Patients were divided into an LVI-positive group (81 cases) and an LVI-negative group (303 cases) based on pathological LVI status, and randomly assigned to a training group (n = 269) and a validation group (n = 115) in a 7∶3 ratio. The ResNet-34 model was used as the base model for deep transfer learning feature extraction. Deep transfer learning features and traditional radiomics features were extracted from the tumor body, and feature dimension reduction was performed using Spearman rank correlation and least absolute shrinkage and selection operator (LASSO) regression to eliminate redundant features and retain those with the highest predictive value. Six machine learning algorithms [adaptive boosting (AdaBoost), naïve Bayes (NB), elastic net (Enet), gradient boosting machine (GBM), neural networks (NN), and support vector machine (SVM)] were used to construct prediction models based on traditional radiomics features, deep transfer learning features, and combined features. Evaluate the diagnostic performance of each model using receiver operating characteristic (ROC) curves, which demonstrated the models^, effectiveness. ResultsAfter dimension reduction through Spearman rank correlation and LASSO regression, 23 optimal features were selected, including 6 traditional radiomics features and 17 deep transfer learning features. All constructed models based on combined features model demonstrated a higher area under the curve (AUC) than those based on individual features alone. The AUCs for the training group were 0.956, 0.802, 0.879, 0.966, 0.973, and 0.944, respectively, and for the validation group, 0.924, 0.868, 0.901, 0.892, 0.817, and 0.905, respectively. ConclusionsThe model based on combined features demonstrates high efficacy in predicting LVI status in rectal cancer, aiding in preoperative individualized prediction and potentially improving patient prognosis. ]]> Mon,20 Jan 2025 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2025.01.010 ObjectiveTo investigate the ability of MRI imaging to predict disease-free survival (DFS) at 3 years after neoadjuant chemoradiotherapy (nCRT) for locally advanced rectal cancer (LARC). Materials and MethodsClinical informations and imaging data of 100 patients with LARC were retrospectively analyzed, including 50 patients with disease progression and 50 patients without disease progression. The training set and test set were randomly allocated according to 4∶1. The imaging features of T2WI axis fast spin echo (FSE) and T2WI sagittal were extracted from preoperative MRI, and then dimensionality was reduced using minimum redundancy maximum correlation filter. Logistic regression was used to construct a nomogram containing the clinical parameter carbohydrate antigen 19-9 (CA19-9). Receiver operating characteristi (ROC), decision curve analysis (DCA) and calibration curves were drawn to evaluate the nomogram prediction effect. ResultsIn clinical information, CA19-9 level was statistically significant in training set and test set (P < 0.05). Among the key imaging features, the features of T2WI sagittal and T2WI FSE sequences contributed the most to the prediction of DFS. Our model demonstrated high predictive accuracy on both the training and validation sets, with the area under the ROC curve (AUC) reached 0.933 [95% confidence interval (CI): 79.7% to 100.0%] and 0.980 (CI: 79.7% to 100.0%) on the training set and validation set, respectively. ConclusionsThe radiomics model established in this study can effectively predict DFS after nCRT in LARC patients, which can provide an important reference for clinical decision-making. ]]> Mon,20 Jan 2025 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2025.01.011 ObjectiveTo investigate the temporal variability of functional brain network alterations in patients with traumatic axonal injury (TAI) utilizing the voxel-based dynamic functional connectivity density (dFCD) method. Materials and MethodsWe recruited 182 patients with traumatic brain injury attending the Department of Neurosurgery of the First Affiliated Hospital of Nanchang University and collected resting-state functional magnetic resonance data, from which we screened 26 patients with simple TAI that met the clinical diagnosis, and recruited matched 27 healthy controls in the community. The data processing toolkit DPABI based on MATLAB 2016b platform was used to preprocess the data, and then the temporal variability of dFCD was investigated based on the Dynamic BC toolbox combined with the sliding time window method, and finally the correlation between the dFCD values and the clinical scales was analyzed. ResultsCompared with controls, we found increased dFCD variability in the right hippocampus/parahippocampal gyrus and right insula/rolandic operculum (voxel level P < 0.01, cluster level P < 0.05, GRF corrected), and decreased dFCD variability in the right medial superior frontal gyrus, bilateral supplementary motor areas/left paracentral lobule/left precentral gyrus in patients with TAI (voxel level P < 0.01, cluster level P < 0.05, GRF corrected), mainly involved in the default mode network, salience network, and the sensorimotor network, and correlation analyses did not reveal significant correlations between dFCD values and clinical scales. ConclusionsThe results of dFCD variability in patients with TAI reflect more subtle changes in dynamic brain activity, deepening the understanding of abnormalities in whole-brain functional connectivity in patients with TAI. ]]> Mon,20 Jan 2025 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2025.01.012 ObjectiveTo explore the abnormal spontaneous neural activity in young adults with pre-diabetes mellitus (PDM) and type 2 diabetes mellitus (T2DM) and its relationship with clinical indicators and cognitive function. Materials and MethodsThis study prospectively enrolled 34 patients with T2DM, 35 patients with PDM, and 34 normal controls (NC), all under the age of 40. All participants underwent comprehensive laboratory examinations and 3.0 T rs-fMRI scanning. Following image preprocessing, low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and degree centrality (DC) indices were computed. Two-sample t-tests were employed to compare differences between groups, with gender, age, and years of education controlled as covariates. Additionally, correlations between rs-fMRI indices, clinical indicators, and cognitive scores were evaluated. ResultsCompared to healthy controls, the PDM group showed increased spontaneous neural activity in several brain regions, such as the left inferior frontal gyrus (t = 4.710, GRF corrected, voxel-level P < 0.005, cluster-level P < 0.05), along with decreased activity in regions such as the right inferior parietal lobule (t = -4.097, GRF corrected, voxel-level P < 0.005, cluster-level P < 0.05). Similarly, the T2DM group exhibited enhanced spontaneous neural activity in multiple brain areas, including the left inferior frontal gyrus (t = 6.348, GRF corrected, voxel-level P < 0.005, cluster-level P < 0.05), as well as reduced activity in regions like the right inferior parietal lobule (t = -5.141, GRF corrected, voxel-level P < 0.005, cluster-level P < 0.05). Additionally, significant correlations were observed between certain resting-state fMRI metrics and clinical indicators or cognitive scores. For example, in the PDM group, the ALFF value of the right middle frontal gyrus showed a significant negative correlation with the MoCA score (r = -0.410, P = 0.014). ConclusionsOur study demonstrates that brain functional indices in young individuals with PDM and T2DM are associated with clinical indicators and cognitive function. Our findings enhance the understanding of the pathophysiology of diabetic brain injury and provide potential biological evidence for its early diagnosis. ]]> Mon,20 Jan 2025 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2025.01.013 ObjectiveTremor-dominant Parkinson^,s disease (TDPD) is considered a benign subtype of Parkinson^,s disease. Early identification of microstructural alterations in TDPD is critical for advancing our understanding of its disease trajectory and for optimizing early therapeutic interventions. This study aims to explore microstructural alterations in the white matter tracts of the brain in early-stage TDPD using free water imaging (FWI). Furthermore, the study investigates the relationship between these alterations and clinical symptoms, thereby uncovering the pathophysiological mechanisms of early-stage TDPD. Materials and MethodsFWI data from 39 early-stage TDPD patients (H-Y stage 1 or 2) and 38 healthy controls (HC) were analyzed in this study to identify white matter tract abnormalities. Free water (FW), fractional anisotropy (FA), and mean diffusivity (MD) values were extracted from white matter regions showing significant differences between groups. These values were subsequently correlated with clinical measures, including the MDS-UPDRS Ⅲ score and tremor sub-scores, using multiple linear regression analysis. Furthermore, logistic regression as employed to assess the relationship between FW values and H-Y stage, providing insights into the pathophysiological mechanisms underlying early-stage TDPD. ResultsIn early TDPD patients, white matter fiber tracts exhibited significantly increased FW values (P < 0.05), notably in the genu of corpus callosum (t = 1.909, P = 0.049) and the bilateral anterior limb of the internal capsule (left t = 2.194, P = 0.049; right t = 2.064, P = 0.048). No significant differences were found in MD values of these tracts between groups. However, the FA values, prior to TFCE correction (P < 0.05), were significantly reduced in the genu of corpus callosum (t = -1.832, P = 0.029) and the bilateral superior corona radiata (left t = -2.012, P = 0.034; right t = -1.881, P = 0.021). These findings suggest that the white matter tracts may be indicative of neurodegenerative processes. The FW value in the left anterior limb of internal capsule was significantly positively correlated with the MDS-UPDRS tremor score (β = 32.798, P < 0.001) and the MDS-UPDRS Ⅲ score (β = 98.496, P = 0.012). Additionally, binary logistic regression analysis revealed that the FW value of the right superior longitudinal fasciculus served as a significant predictor of H-Y staging (β = 0.97, P = 0.04). ConclusionsFWI can sensitively detect microstructural alterations in the white matter tracts of early-stage TDPD patients. The study indicates extensive neuroinflammatory changes in the white matter microstructure of TDPD patients, providing new insights for the diagnosis and evaluation of clinical symptoms of the disease. ]]> Mon,20 Jan 2025 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2025.01.014 ObjectiveTo investigate the disparities in brain functional connectivity (FC) among patients with first-episode depression comorbid with insomnia (FEDCI) and those with recurrent depression comorbid with insomnia (RDCI), and to assess its association with clinical manifestations. Materials and MethodsA cohort of 53 patients with depression comorbid with insomnia was studied. The participants were categorized into two groups: 32 patients with FEDCI and 21 patients with RDCI. Additionally, 21 healthy controls (HC) served as a control group. The 17-item Hamilton Depression Scale (HAMD-17) was used to assess the degree of depression, Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI) to assess the degree of depression and sleep status. The PSQI and ISI were used to assess sleep status. Resting-state blood oxygen level-dependent functional magnetic resonance imaging (fMRI) data were acquired from all participants. Using SPSS software, we employed univariate analysis of variance to compare FC differences based on the bilateral rostral anterior cingulate cortex (rACC) as seed regions across the three groups, and analyzed its correlation with clinical scales. fMRI data underwent GRF correction with voxel-level P < 0.001 and cluster-level P < 0.05. ResultsThe differences in demographics and clinical symptom scores between the two groups were not statistically significant (P > 0.05). The difference in FC based on bilateral rACC between the FEDCI and RDCI groups and the HC group was not statistically significant (P > 0.05). However, with the left rACC as a seed region, the RDCI group exhibited lower FC values in the left angular gyrus and right middle frontal gyrus compared to the HC group. In comparison to the FEDCI group, the RDCI group had higher FC values in the left angular gyrus and left inferior frontal gyrus (P < 0.05). Utilizing the right rACC as a seed region, the FEDCI group displayed a higher FC value in the left thalamus, while showing lower FC values in the left posterior central gyrus and right insula compared to the HC group (P < 0.05). Furthermore, the FEDCI group exhibited lower FC values in the left posterior central gyrus and right insula compared to the RDCI group (P < 0.05). Correlation analysis revealed a positive association between the FC values of the left anterior cingulate gyrus and left angular gyrus in the FEDCI group with the HAMD-17 (P = 0.012, r = 0.439). Additionally, the number of depression episodes in the RDCI group positively correlated with the FC value between the left rACC and left inferior frontal gyrus (P = 0.002, r = 0.654). ConclusionsThere exist significant differences in prefrontal, the emotional and somatosensory motor network brain functional networks between patients with FEDCI and RDCI, which correlate with clinical symptoms and the number of depressive episodes. ]]> Mon,20 Jan 2025 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2025.01.015 ObjectiveTo develop a deep learning model based on MRI diffusion-weighted imaging (DWI) and evaluate its ability to predict 90-day outcomes in acute ischemic stroke (AIS) patients undergoing intravenous thrombolysis. Materials and MethodsA retrospective analysis was conducted on clinical and imaging data from 677 AIS patients treated with intravenous thrombolysis at two hospitals. MRI-DWI images were collected through picture archiving and communication systems (PACS). A deep neural network was used to extract imaging features. Dataset 1 (Hospital 1) was randomly split into a training set (70%) and a testing set (30%) to develop four models: a clinical features-based machine learning model (Model A), an MRI-DWI radiomics features-based machine learning model (Model B), a deep learning model using MRI-DWI features (Model C), and a combined model integrating clinical and deep learning features (Model D) to predict 90-day outcomes [Patients with a modified Rankin Scale (mRS) score less than 2 at 90 days are considered to have a good prognosis]. Dataset 2 (Hospital 2) was used for external validation. Predictive performance was assessed using the receiver operating characteristic (ROC) curve and area under the curve (AUC). ResultsThe AUCs of Models A, B, and C were 0.705 [95% confidence interval (CI): 0.613 to 0.792], 0.846 (95% CI: 0.777 to 0.906), and 0.877 (95% CI: 0.811 to 0.934), respectively. Model D demonstrated superior predictive performance with an AUC of 0.930 (95% CI: 0.890 to 0.963). External validation showed consistent performance, with AUCs of 0.887 (95% CI: 0.798 to 0.960) for Model C and 0.947 (95% CI: 0.891 to 0.984) for Model D. ConclusionsMRI-DWI radiomics features play a crucial role in predicting 90-day outcomes in AIS patients treated with intravenous thrombolysis. Deep learning models outperform traditional machine learning models, and the integration of clinical and deep learning features provides a robust tool for personalized prognosis and treatment planning in AIS. ]]> Mon,20 Jan 2025 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2025.01.016 ObjectiveTo summarize the MRI features of brain abnormalities associated with the use of vigabatrin (VGB) in the treatment of infantile spasms. Materials and MethodsTo retrospectively analyze the baseline imaging characteristics and follow-up imaging characteristics of children with infantile spasticity who admitted in the First Medical Center of the Chinese People^,s Liberation Army (PLA) and were treated with VGB and presented with cephalometric imaging changes from July 2019 to May 2023. ResultsA total of 32 children with infantile spasticity were collected, with a mean age of (10.34 ± 0.86) months. Cerebral MRI showed that 21 cases involved bilateral thalamus, brainstem (dorsal), basal ganglia (pallidum), and dentate nucleus of the cerebellum in a symmetrical distribution. Nine cases involved bilateral hippocampus, one case involved unilateral hippocampus, and one case involved bilateral shell nuclei and head of caudate nucleus. The positive detection rates of lesions were 100.0% in diffusion weighted imaging (DWI) sequence, 50.0% in apparent diffusion coefficient (ADC) sequence, 46.9% in T2 sequence, 25.0% in fluid attenuated inversion recovery (FLAIR) sequence and 25.0% in T1 sequence. After regression analysis, the results showed that the presentation of typical versus atypical VGB-associated brain abnormalities on MRI (VABAM) was independent of a variety of clinical factors, such as gender, age, etiology, peak VGB dose, VGB dosage during MRI examinations, and new onset of symptoms. The corresponding P values for these factors were 0.888, 0.924, 0.955, 0.360, 0.058, and 0.636. At the follow-up of 10 children, 1 case of the original abnormal signal completely disappeared, 5 cases were reduced, 1 case had little change, and 3 cases of the abnormal signals were more obvious than before. At the time of detection of MRI abnormalities, two cases had new extrapyramidal predominant symptoms, and the children^,s clinical symptoms disappeared after discontinuation of the drug. ConclusionsSymmetrical DWI abnormal signals in the thalamus, brainstem (dorsal), pallidum, and cerebellopontine dentate nucleus on cranial MRI can be seen during aminocaproic acid treatment for infantile spasticity, and some of them can involve the hippocampus, mostly reversible. DWI has a high detection rate for lesions. ]]> Mon,20 Jan 2025 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2025.01.017 ObjectiveTo apply the cardiac magnetic resonance (CMR) four-dimensional flow (4D Flow) technique to measure blood flow in the left ventricle of patients with hypertensive heart disease (HHD) and to investigate the feasibility of using left ventricular hemodynamic parameters for the early diagnosis of left ventricular diastolic dysfunction. Materials and MethodsFifty-four HHD patients were prospectively enrolled. According to the left ventricular ejection fraction (LVEF), they were divided into 34 patients in the HHD LVEF reduced group (LVEF < 50%) and 20 patients in the HHD LVEF preserved group (LVEF ≥ 50%). At the same time, 40 healthy volunteers were enrolled as the control group. All three groups were scanned with a 3.0 T magnetic resonance steady-state free-flow sequence and CMR 4D Flow sequence. CVI42 software was used for image post-processing analysis, including left ventricular function parameters, early diastolic mitral flow velocity (E peak), and late diastolic mitral flow velocity (A peak). One-way analysis of variance (ANOVA) or Kruskal-Wallis test was performed to compare the clinical data and imaging parameters among the three groups. Pearson correlation analysis was conducted to examine the relationship between the mitral peak velocity ratio (E/A) and the left ventricular end-diastolic volume index (LVEDVI), left ventricular end-systolic volume index (LVESVI), amd LVEF. ResultsThe mitral E peak and E/A were lower in the HHD LVEF preserved group and HHD LVEF reduced group than in the control group [HHD LVEF preserved group vs. HHD LVEF reduced group vs. healthy control group: E peak, 60.10 (46.25, 83.45) cm/s vs. 61.50 (51.80, 92.50) cm/s vs. 91.42 (88.06, 98.74) cm/s; E/A, (1.15 ± 0.36) vs. (1.00 ± 0.35) vs. (1.78 ± 0.22)] (P < 0.05). The A peak was higher than that of the control group [HHD LVEF preserved group vs. HHD LVEF reduced group vs. healthy control group: 59.45 (54.10, 76.65) cm/s vs. 68.85 (53.10, 94.20) cm/s vs. 53.37 (49.06, 56.40) cm/s] (P < 0.05). Analysis showed a negative correlation between E/A and both LVEDVI (r = -0.306, P = 0.024) and LVESVI (r = -0.357, P = 0.008), whereas a positive correlation was observed between E/A and LVEF (r = 0.353, P = 0.009). ConclusionsLeft ventricular diastolic function can be quantitatively assessed in patients with HHD using the CMR 4D Flow technique. Early changes in diastolic function can be detected even when left ventricular systolic function remains unaltered, which demonstrates significant potential for application in the early diagnosis of HHD. ]]> Mon,20 Jan 2025 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2025.01.018 ObjectiveTo develop an extreme gradient boosting (XGBoost) model based on clinical and imaging features to differentiate between benign and malignant non-mass breast lesions. Materials and MethodsData were collected from January 2018 to July 2024 from two institutions, focusing on 480 non-mass breast lesions with pathological results obtained from two types of mammography equipment. Patients were categorized into a modeling group [n = 310, digital mammography (DM) examination], an internal validation group (n = 108, DM examination), and an external validation group [n = 62, digital breast tomosynthesis (DBT) examination]. Preoperative breast X-ray (DM or DBT), MRI, and clinical characteristics were recorded. The XGBoost algorithm and multivariate logistic regression (LR) analysis were employed to develop the XGBoost and LR models, respectively. Diagnostic performance was assessed using receiver operating characteristic (ROC) curves. ResultsIn the modeling group, patients were randomly split in a 7∶3 ratio into a training set (n = 217) and a test set (n = 93). The proportion of malignant non-mass lesions in the training set, test set, internal validation group of the training set, and external validation group of the training set, were 159 (73%), 58 (62%), 73 (68%) and 43 (69%), respectively. The XGBoost model outperformed the LR model in diagnostic accuracy, demonstrating superior performance across the independent training, test, and internal, external validation sets of the training set, with area under the curve (AUC) ranging from 0.884 to 0.913. Additionally, the XGBoost model exhibited good calibration and clinical net benefit in all four cohorts. ConclusionsThe XGBoost model accurately differentiates between benign and malignant non-mass breast lesions, indicating its potential for widespread clinical application. ]]> Mon,20 Jan 2025 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2025.01.019 ObjectiveTo investigate the value of CT and MRI features of pancreatic neuroendocrine neoplasm (panNEN) in predicting its pathological grade. Materials and MethodsThe clinical and imaging data of 106 patients with panNEN in the Third Hospital of Peking University were analyzed retrospectively. According to the World Health Organization (WHO) classification and classification standard of 2019, the patients were divided into low-grade group [neuroendocrine neoplasm (NEN) of G1 grade] and middle-high-grade group [NEN of G2, G3 grade and neuroendocrine carcinoma (NEC)]. Sex, age, tumor shape, tumor location, tumor volume, cystic and solid nature, CT and MRI signal characteristics, vascular invasion and hepatic metastasis were analyzed. t test, Mann-whitney U test, chi-square test and Wilcoxon rank-sum test were used to analyze the data, and binary logistic regression was used to construct the prediction model. ResultsThere were significant differences in tumor volume, hepatic metastasis and vascular invasion between low-grade group and middle-high-grade group, but no significant differences in sex, age, cystic nature and location. On CT and MRI, only diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) images showed significant differences in signal characteristics. Multivariate logistic regression analysis showed that tumor volume, hepatic metastasis and vascular invasion were independent predictors of panNEN pathological grade, the combined model predicted the AUC of the high-grade group in panNEN to be 0.861 (95% CI: 0.798 to 0.923), with a sensitivity of 78.1% and a specificity of 83.3%. ConclusionsThe combined model based on tumor volume, hepatic metastasis and vascular invasion can effectively predict panNEN pathological grade before operation and is helpful for clinical treatment decision. ]]> Mon,20 Jan 2025 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2025.01.020 ObjectiveTo evaluate the feasibility of enhanced T2 star-weighted angiography (ESWAN) in differentiating diagnosis between benign and malignant renal tumors with T2WI hypo-intensity. Materials and MethodsThe preoperative MRI data of 145 patients with benign and malignant renal lesions (145 lesions in total, including 112 malignant lesions and 33 benign lesions) confirmed by ESWAN sequence scanning of MR and pathology were collected prospectively. Drawing the region of interest with low signal intensity on T2WI at the level of the largest tumor area. Parameters were compared by Kruskal-Wallis test and Chi-square test. The statistically significant parameters were combined and the model was established by multivariate logistic regression. The receiver operating characteristic (ROC) curve of parameters being statistically different between groups were drawn for identifying benign and malignant renal tumors with T2WI low signal, and the diagnostic efficacies were evaluated. ResultsThere was significant difference between the R2^* value and magnitude in diagnosing benign and malignant renal tumors with T2WI hypo-intensity. The area under the ROC curve (AUC) of R2^* values was 0.891 [95% confidence interval (CI): 0.829 to 0.937, P < 0.001], with the sensitivity, specificity of 97.3%, 72.7%, respectively. The AUC of magnitude values was 0.869 (95% CI: 0.803 to 0.920, P < 0.001) and the sensitivity, specificity of 86.6%, 81.8%. The AUC of phase values was 0.563 (95% CI: 0.478 to 0.645, P = 0.249), with the sensitivity, specificity of 67.9%, 54.6%. The AUC of combined R2^* value and magnitude was 0.886 (95% CI: 0.823 to 0.933, P < 0.001), with the sensitivity, specificity of 97.3%, 72.7%. The AUC of combined R2^* value and long axis of lesion was 0.894 (95% CI: 0.832 to 0.939, P < 0.001), with the sensitivity, specificity of 92.0%, 81.8%. The AUC of combined magnitude and long axis of lesion was 0.858 (95% CI: 0.790 to 0.910, P < 0.001), with the sensitivity, specificity of 75.9%, 90.9%. ConclusionsThe R2^* value and combined R2^* value and long axis of lesion provide an effective way to discriminate benign from malignant renal tumors with T2WI hypo-intensity and the combined R2^* value and long axis of lesion has better diagnostic performance. ]]> Mon,20 Jan 2025 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2025.01.021 ObjectiveTo explore the diagnostic value of magnetic resonance image complication (MAGiC) sequence combined with ultra-high b-value diffusion weighted imaging (uh-DWI) in parametrial infiltration of cervical cancer. Materials and MethodsProspectively analyzed 40 patients with surgically and pathologically proven cervical cancer from Ningde Normal University Affiliated Ningde Municipal Hospital from August 2022 to April 2024. Patients were divided into two groups based on pathological results: parametrial infiltration negative group and positive group. Both groups underwent MAGiC and ultra-high b-value DWI (uh-DWI), and tumor longitudinal relaxation values (T1), transverse relaxation values (T2), proton density (PD) values, and ultra-high b-value apparent diffusion coefficients (ADC_uh) were measured. To make comparisons, the Mann-Whitney U test was utilized to assess the parameter values between the negative and positive groups. We applied the receiver operating characteristic (ROC) curve to evaluate the diagnostic efficacy of cervical cancer parametrial infiltration for each parameter and the combination of parameters with differences. ResultsAmong the 40 cervical cancer patients, there were 35 instances of squamous cell carcinoma and 5 instances of adenocarcinoma; 28cases in the negative group and 12 cases in the positive group. The T1 and T2 values in the positive group were lower than those in the negative group, with a statistically significant difference (P < 0.01). There was no significant difference in PD values between the two groups (P = 0.141). The positive group^,s ADC_uh value was lower than that of the negative group (P < 0.001). The area under the curve (AUC) for T1, T2, and ADC_uh to distinguish cervical cancer parametrial invasion were 0.899 (95% CI: 0.762 to 0.972), 0.962 (95% CI: 0.849 to 0.997), 0.934 (95% CI: 0.809 to 0.988), respectively, with sensitivities and specificities of 86.36%, 77.80%, 100.00%, 77.78%, and 77.27%, 94.44%, respectively. The AUC for the combined differentiation of parametrial infiltration could be increased to 0.985, with a sensitivity of 100.00% and a specificity of 95.40%. ConclusionsThe combination of MAGiC and ultra-high b-value DWI is helpful in judging parametrial infiltration of cervical cancer. The comprehensive use of the advantages of multi-parametric MRI and the combination of parameters with differences can obtain good diagnostic efficacy for parametrial invasion. ]]> Mon,20 Jan 2025 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2025.01.022 ObjectiveTo investigate the value of 2D phase contrast magnetic resonance imaging (PC MRI) in quantitative analysis of mean blood flow velocity (MV) in patients with iliac vein compression syndrome (IVCS). Materials and MethodsThirty patients (trial group) with IVCS diagnosed by digital subtraction angiography (DSA) in interventional vascular surgery from December 2023 to July 2024 and ten healthy volunteers (control group) were collected. Clinical data of patients were collected and Philips superconducting MRI 1.5 T was performed. On the basis of balance fast field echo (B-FFE) sequences, 2D PC MRI were set vertically on the coronal, sagittal and axial images of the inferior vena cava and both of external iliac vein. The MV values in the region of interest (ROI) in the vertical cross section of the vessels were obtained by using quantitative flow (Q_FLOW) post-processing software. All 2D PC MRI checks forward twice, and the sequence stability is verified by analyzing the consistency of the two scan results (Bland-Altman diagram). Comparing the MV value between both of external iliac veins in two groups to assesses the effect of common iliac vein compression on blood flow. The MV difference of bilateral external iliac veins in the trial group (healthy external iliac MV － affected external iliac MV) was compared with that in the control group (right external iliac MV － left external iliac MV), and the efficacy of velocity difference in diagnosing IVCS was analyzed. The iliac-vena cava pressure gradient measured by central venous catheter (CVC) in interventional procedures was analyzed in correlation with MV in the distal part of the stenosed iliac vein. ResultsThe results of the two scans were highly positively correlated (P < 0.001, all). The MV of the narrow iliac vein was lower than that of the healthy side in the trial group (P < 0.001), and the MV values of bilateral external iliac veins in the control group were not statistically significant (P = 0.518). The MV difference of bilateral external iliac veins was effective in the diagnosis of IVCS, the AUC was 0.939 (95% CI: 0.887 to 0.991), the sensitivity was 81.7% and the specificity was 100.0%. The pressure gradient measured by CVC was negatively correlated with MV at the distal end of the stenotic vein (r = -0.951, P < 0.001). Conclusions2D PC MRI is reliable and stable in measuring the blood flow velocity of narrow iliac vein. The difference of bilateral external iliac vein MV has high specificity in the diagnosis of IVCS. The relationship of MV and venous pressure is consistent with Bernoulli^,s principle. 2D PC MRI can be used as a tool for non-invasive diagnosis of IVCS and indirect assessment tool to provide an important reference for the surgical indication of endovascular interventional therapy in patients with IVCS. ]]> Mon,20 Jan 2025 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2025.01.023 ObjectiveTo explore the reproducibility of intravoxel incoherent motion diffusion weighted imaging (IVIM-DWI) based virtual magnetic resonance elastography (vMRE) in measuring the stiffness of infrapatellar fat pad (IPFP). Materials and MethodsA total of 50 subjects underwent two IVIM-DWI examinations utilizing 10 b-values, with intervals of 30 to 60 minutes, employing an 18-channel knee coil. The shift apparent diffusion coefficient (sADC) was calculated from two different b-values (200 to 800 s/mm² and 200 to 1500 s/mm²), which were subsequently converted into virtual shear moduli based on IVIM-DWI MRI (μ_{diff_800} and μ_{diff_1500}). Two readers independently outlined the entire IPFP region of interest (ROI) on the vMRE stiffness map to obtain the mean and standard deviation (SD) of μ_diff. The intra-class correlation coefficient (ICC), coefficient of variation (CoV), and the limits of agreement (LoA) of Bland-Altmanwere utilized to evaluate short-term test-retest repeatability, as well as intra-observer and inter-observer consistency. ResultsThe average and SD values of μ_{diff_1500} demonstrated excellent intra- and inter-observer consistency, with an ICC of ≥ 0.90 (P < 0.001). Notably, the intra-observer CoV for the SD values was greater than 10%. The intra and inter-observer ICC values for the average of μ_{diff_800} were 0.926 and 0.910, respectively (P < 0.001), while the ICC values for the SD of μ_{diff_800} were 0.841 and 0.855, respectively (P < 0.001), with all CoV exceeding 10%. In comparison to μ_{diff_800} (ICC = 0.886; CoV = 13.7%), the average of μ_{diff_1500} exhibited excellent repeatability upon retesting (ICC = 0.932; CoV = 7.5%). The average deviation (SD) between two scans of μ_{diff_1500} was -0.01 (0.37), whereas for μ_{diff_800}, it was 0.05 (0.79). The 95% LoA for μ_{diff_1500} ranged from -0.88 to 0.87, while for μ_{diff_800}, it ranged from -0.63 to 0.73. ConclusionsThe findings suggest that the vMRE, utilizing IVIM-DWI, holds substantial promise for assessing the tissue elasticity of the IPFP. Furthermore, the virtual elasticity values derived from b-value combinations of 200 to 1500 s/mm² demonstrate superior intra-observer and inter-observer consistency, as well as enhanced short-term test-retest repeatability. ]]> Mon,20 Jan 2025 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2025.01.024 ObjectiveTo Compare the image quality and clinical value of two dimensional T2 weighted imaging turbo spin echo (2D T2-TSE) and three dimensional T2 weighted imaging sampling perfection with application optimized contrast using different flip angle evolution (3D T2-SPACE) sequences using MRI phase scout technology in prone position scanning of occult tethered cord syndrome occult tethered cord syndrome (OTCS). Materials and MethodsA retrospective analysis was performed on 30 children under 6 years of age with suspected OTCS who received MRI examination in our hospital from January 2023 to October 2023. 2D T2-TSE and 3D T2-SPACE sequences in prone position using phase scout technology were both used to examine the children. Subjective scoring was based on overall image quality, spinal conus display, cauda equina and terminal filament display, subarachnoid cerebrospinal fluid signal display and background noise display, record the scanning time, and calculate the intraspinal image signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). The image quality scores, scanning time, intraspinal SNR and CNR of the two sequences were compared. Paired t test and Mann-Whitney U test were used to compare and analyze the evaluation results of the two test methods. Using Kappa test, evaluate the consistency of subjective scoring by two radiologists and consistency of objective quantitative analysis by two technicians. P < 0.05 was considered statistically significant. ResultsIn the subjective scores of image quality, the scores of the two radiologists were more consistent (Kappa = 0.794, P < 0.001), the overall image quality, cauda equina and terminal filament display, subarachnoid cerebrospinal fluid signal display and background noise display scores of 3D T2-SPACE sequence were higher than those of 2D T2-TSE sequence (Z = -2.305, -4.242, -3.453, -2.201, P < 0.05). On the display of the spinal conus, 2D T2-TSE consistent with 3D T2-SPACE (Z = -0.948, P > 0.05). In objective quantitative analysis, the scores of intraspinal SNR and CNR measurement results by two technicians were most consistent (Kappa = 0.851, 0.734, P < 0.001). Comparing the 2D T2-TSE with the 3D T2-SPACE sequence, intraspinal SNR and CNR of 3D T2-SPACE sequence were better than those of 2D T2-TSE sequence by analysis results of two measurements (The first measurement of SNR and CNR: t = -3.058, -3.703; The second measurement of SNR and CNR: t = -2.981, -2.965, P < 0.05 for all). The scanning time of 3D T2-SPACE sequence was longer than that of 2D T2-TSE sequence [(183.67±34.89) s vs. (120.53±27.93) s, t = -10.087, P < 0.001]. ConclusionsIn the prone position MRI examination of suspected OTCS patients, the 3D T2-SPACE sequence using phase scout technology can provide better intraspinal image quality compared with the 2D T2-TSE sequence, smaller FOV and voxels, and more reliable information for clinical practice and treatment compared to the 2D T2-TSE sequence. ]]> Mon,20 Jan 2025 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2025.01.027 Mon,20 Jan 2025 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2025.01.028 Mon,20 Jan 2025 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2025.01.029 ^,s disease (AD) spectrum. The findings suggest that dFC analysis of regions such as the hippocampus, precuneus, and inferior frontal gyrus holds great potential for deepening our understanding of AD pathogenesis, offering a more reliable imaging-based theoretical framework for explaining the longitudinal progression of AD. Using dFC as a central theme, this review explores current advancements and future directions in the study of the AD spectrum, providing new insights for future neuroimaging research on AD. ]]> Mon,20 Jan 2025 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2025.01.030 Mon,20 Jan 2025 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2025.01.031 Mon,20 Jan 2025 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2025.01.032 ^, quality of life. This paper summarizes recent research findings on the use of AI for early screening, diagnosis and prediction of glaucoma, and discusses the advantages and challenges of its application in this field. The purpose of this review is to provide a comprehensive reference for researchers and clinicians to advance the further development of AI technology in the prevention and treatment of glaucoma, and ultimately to achieve the goal of optimizing patient management and improving eye health worldwide. ]]> Mon,20 Jan 2025 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2025.01.033 Mon,20 Jan 2025 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2025.01.034 Mon,20 Jan 2025 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2025.01.035 Mon,20 Jan 2025 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2025.01.036 Mon,20 Jan 2025 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2025.01.037 Mon,20 Jan 2025 00:00:00 GMT