http://med-sci.cn/cgzcx/en/contents_list.asp?issue=202606 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.1674-8034.2026.06.001 ObjectiveTo investigate the long-term effects of donepezil on the progression of Alzheimer^,s disease (AD), this study examined the dynamic changes in cognitive function, brain morphology, and structural covariance network properties in AD patients treated with donepezil over a 24-month follow-up period. Materials and MethodsThis study comprises two parts: a cross-sectional study and a longitudinal study of drug therapy. The cross-sectional study included 30 normal controls (NC) and 42 AD patients, evaluating differences in cognition, brain morphology, and global properties and node metrics of structural covariance networks between the two groups. The longitudinal study of drug therapy retrospectively enrolled 26 AD patients receiving donepezil treatment and 26 AD patients who did not receive any AD medication as non-treatment group. Clinical and MRI data were collected from both groups over the 24-month follow-up period. Linear mixed-effects models were employed to analyze changes in cognitive scale scores, volumes of characteristic brain regions, and structural covariance network metrics. ResultsAD patients exhibited significant atrophy in the right hippocampus, left amygdala, left cuneus, and right thalamus (P < 0.05, FWE corrected), accompanied by extensive damage to structural covariance networks. The results of the linear mixed-effects model showed significant time × group interaction effects for the MMSE scores, right hippocampus volume, and left amygdala volume (P < 0.05). The rate of decline in MMSE scores was significantly slower in the donepezil treatment group than in the non-treatment group, and the atrophy rates of the right hippocampus and left amygdala were significantly decelerated. No significant interaction effects were observed for global metrics of the structural covariance network. ConclusionsThe therapeutic effect of donepezil on AD is a multi-level process. Following intervention, global network properties show a transient improvement trend, which may subsequently activates network metrics in brain regions critical for cognition, and thereby delays cognitive decline and atrophy in disease-affected brain regions. However, its long-term influence on the topology of the whole-brain structural covariance network is limited. This study provides multi-level longitudinal evidence for understanding the neuroimaging mechanisms underlying the modulation of AD progression by donepezil. ]]> Sat,20 Jun 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.06.002 ObjectiveThis study aimed to characterize the alterations of resting-state brain functional networks in patients with type 1 diabetes mellitus (T1DM) and to explore their associations with cognitive performance and clinical blood indicators. Materials and MethodsThis was a prospective cross-sectional study. A total of 43 T1DM patients and 52 demographically matched healthy controls (HCs) were enrolled between March 2023 and March 2025. Resting-state functional MRI data were acquired, and graph-theory-based methods were used to construct whole-brain functional networks. Using age, sex, years of education, and mean frame displacement as covariates, two-sample t-tests were performed to compare group differences in network topological properties. Furthermore, partial Pearson/Spearman correlation analyses were conducted to assess the correlations between network metrics and cognitive scores as well as clinical blood indicators. ResultsCompared with HCs, T1DM patients showed declines in overall cognitive performance and specific cognitive subdomains (P < 0.05). Regarding global topological properties, the patients^, brain functional networks retained a small-world property; however, global integration efficiency was significantly decreased and characteristic path length was significantly prolonged. Meanwhile, local information processing capacity was significantly enhanced (P < 0.05). At the nodal level, the right superior temporal pole exhibited significantly increased nodal clustering coefficient and nodal local efficiency (Bonferroni-corrected P < 0.05). Partial correlation analyses revealed that characteristic path length was negatively correlated with naming scores (r = -0.395, P = 0.012)and high-density lipoprotein cholesterol (HDL-C) level (r = -0.337, P = 0.033); normalized characteristic path length was negatively correlated with naming scores (r = -0.329, P = 0.038) and HDL-C level (r = -0.378, P = 0.016); global efficiency was positively correlated with HDL-C level (r = 0.376, P = 0.017); and the nodal clustering coefficient of the right superior temporal pole was negatively correlated with HDL-C level (r = -0.317, P = 0.046). After FDR correction, none of the above correlation results remained statistically significant, suggesting potential associations that should be interpreted with caution. ConclusionsT1DM patients exhibit significant reorganization of brain functional networks, characterized by decreased global efficiency and increased local efficiency, which are associated with specific cognitive impairments and lipid metabolism levels. These findings provide new insights into the neural mechanisms underlying cognitive dysfunction in T1DM and its comprehensive clinical management. ]]> Sat,20 Jun 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.06.003 ObjectiveTo develop and validate a deep learning-radiomics (DL Radiomics) model for predicting the occurrence of bilirubin encephalopathy (BE) in neonates with severe hyperbilirubinemia, compare its performance with conventional clinical models, and explore the potential relationships among biochemical markers, radiomics features, and BE using mediation analysis. Materials and MethodsThis retrospective study included 173 neonates with severe hyperbilirubinemia admitted to the East and West Campuses of the Anhui Provincial Women and Children^,s Medical Center between January 2022 and September 2025. Clinical data and MRI scans were collected, and divided the dataset into two groups using a 7∶3 ratio. Deep learning features and handcrafted radiomics features were extracted from T1-weighted images using DenseNet-121 and PyRadiomics, respectively. After feature selection based on mutual information, a DL Radiomics model (Rad-score) was constructed. Clinical variables were selected using LASSO and logistic regression to build a nomogram model. Model performance was evaluated in the training and testing sets, with internal validation performed using leave-one-out, 10-fold cross-validation, and bootstrapping. Mediation analysis was conducted to assess the relationships among biochemical markers, Rad-score, and BE. ResultsAmong the 173 neonates, 65 (37.57%) developed BE. The final Rad-score was derived from two deep learning features and three radiomics features. In the clinical model, weight, gestational age, mode of delivery, premature rupture of membranes, isoimmune hemolysis, total bilirubin, hemoglobin, and platelet count were identified as independent predictors (OR range: 0.993 to 27.935). The DL Radiomics model achieved area under the curves (AUCs) ranging from 0.762 to 0.796 across datasets, while the clinical model yielded AUCs of 0.767 to 0.843. The nomogram model demonstrated improved performance, with AUCs of 0.873 to 0.916, and the nomogram excluding biochemical variables achieved AUCs of 0.857 to 0.892. Mediation analysis indicated that the association between hemoglobin with total bilirubin and BE was partially mediated by the Radscore, with a mediation proportion of 20.70% and 43.10% (P = 0.006, P = 0.092). ConclusionsThe DL Radiomics model, when combined with clinical variables excluding biochemical markers, demonstrates favorable discriminative performance in predicting BE. In addition, the Radscore is found to be associated with peripheral hemoglobin and total bilirubin levels. ]]> Sat,20 Jun 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.06.004 ObjectiveTo investigate glymphatic system dysfunction and its clinical significance in patients with cerebral small vessel disease (CSVD) presenting with chronic dizziness. Materials and MethodsA retrospective study was conducted, enrolling 136 inpatients with chronic dizziness as the chief complaint from January 2024 to November 2025. Combined with clinical symptoms, signs, and comprehensive auxiliary examinations (including cranial multimodal magnetic resonance imaging, vestibulo-ocular reflex, vestibulospinal reflex, and audiological tests), patients with chronic dizziness with definitive diagnosis were excluded as much as possible. Finally, 32 patients with chronic dizziness with CSVD, complete data, most likely unexplained cause were included in the CSVD with chronic dizziness group, and 32 age, gender, and vascular risk factor as well as emotional and sleep status-matched patients with CSVD without chronic dizziness were assigned to the control group. Total CSVD burden score and Dizziness Handicap Inventory (DHI) score were collected for CSVD with chronic dizziness groups. Meanwhile, glymphatic system function was quantified using diffusion tensor imaging along the perivascular space (ALPS). Correlations between ALPS indices, total CSVD imaging burden, and DHI scores were analyzed. ResultsThere were no significant differences in baseline data between CSVD with chronic dizziness group and CSVD without chronic dizziness group (P > 0.05). The ALPS indices of both left and right (left: CSVD group 1.26 ± 0.21, CSVD without chronic dizziness group 1.48 ± 0.20; right: CSVD with chronic dizziness group 1.26 ± 0.15, CSVD without chronic dizziness group 1.50 ± 0.26) hemispheres in the CSVD with chronic dizziness group were significantly lower than those in the CSVD without chronic dizziness group (P < 0.05). The right ALPS index was negatively correlated with DHI score (r = -0.846, P = 0.002), and bilateral ALPS indices were also significantly negatively correlated with total CSVD imaging burden score (left r = -0.626, P = 0.003; right r = -0.876, P = 0.001). ConclusionsPatients with CSVD presenting with chronic dizziness exhibit bilateral glymphatic system dysfunction, and the right ALPS index is decreased, and symptoms of chronic dizziness are more severe. ]]> Sat,20 Jun 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.06.005 ObjectiveTo investigate the value of white matter hyperintensity (WMH) quantitatively assessed by MRI imaging in predicting the clinical prognosis of patients with acute ischemic stroke (AIS) caused by middle cerebral artery (MCA) occlusion. Materials and MethodsThis retrospective study included 168 AIS patients with middle cerebral artery occlusion treated between July 2021 and July 2024. All patients underwent CT perfusion (CTP) imaging within 24 h of admission, and ischemic volumes at different thresholds were obtained (V_{Tmax>4 s}, V_{Tmax>6 s}, V_{Tmax>8 s}, V_{Tmax>10 s}, V_CBF<30%, V_CBF<38%, and V_CBF<50%). The hypoperfusion intensity ratio (HIR) was calculated as the ratio of V_{Tmax>10 s} to V_{Tmax>6 s}. MRI was performed within 7 days, and regional WMH volumes (periventricular cap, periventricular, deep, and juxtacortical) were measured on T2 fluid-attenuated inversion recovery (FLAIR) images. Short-term neurological improvement was defined as a National Institutes of Health Stroke Scale (NIHSS) score ≤ 1 or a decrease of ≥ 8 points at 7 days. Ninety-day outcome was assessed using the modified Rankin Scale (mRS), with mRS scores of 0-2 classified as good outcome and 3-6 as poor outcome. Spearman correlation analysis was used to evaluate associations between WMH volume and cerebral perfusion status. Binary logistic regression analysis was performed to identify independent predictors of short-term and 90-day outcomes. Combined Model 1 was constructed using baseline NIHSS score, V_{Tmax>6 s}, and V_CBF<30%. On this basis, periventricular WMH volume was added to establish Combined Model 2. Model performance was evaluated using receiver operating characteristic (ROC) curves, DeLong test, calibration curves, and decision curve analysis. ResultsOf the 168 patients, 93 achieved short-term neurological improvement, and 83 had a good 90 - day outcome. Total WMH volume was significantly lower in the short-term improvement group than in the non-improvement group (P < 0.05). Multivariate logistic regression analysis with short-term neurological improvement as the outcome variable demonstrated that V_{Tmax>6 s} (OR = 0.992, 95% CI: 0.986 to 0.998, P = 0.009), V_CBF<30% (OR = 0.981, 95% CI: 0.964 to 0.999, P = 0.036), and total volume of white matter hyperintensities (WMH) (OR = 0.957, 95% CI: 0.928 to 0.987, P = 0.005) were independently associated with short-term neurological improvement in patients. Increased periventricular cap WMH volume was an independent risk factor for poor 90- day outcome (OR = 1.327, 95% CI: 1.089 to 1.618, P = 0.005). Baseline NIHSS score, V_{Tmax>6 s}, V_CBF<30%, and periventricular cap WMH volume were independently associated with poor 90-day outcome. A regression model combining baseline NIHSS score, V_{Tmax>6 s}, V_CBF<30%, and periventricular cap WMH volume achieved the best performance for predicting 90 - day outcome, with an area under the curve (AUC) of 0.895 (95% CI: 0.846 to 0.945; P < 0.001), sensitivity of approximately 81.2%, and specificity of approximately 90.3%. This model outperformed the prediction model based solely on baseline NIHSS score, V_{Tmax>6 s}, and V_CBF<30%. The Delong test indicated an absolute difference of 0.029 between the two models (Z = 2.06, P = 0.03). The Hosmer-Lemeshow test and calibration curve both indicate that Combined Model 1 and Combined Model 2 exhibit favorable calibration performance. Decision curve analysis showed that the net benefit of combined prediction model 2 was consistently higher than that of combined prediction model 1. ConclusionsA larger total volume of WMH measured by MRI in the early stages of hospitalization is associated with a lower rate of short-term neurological improvement in AIS patients. Increased periventricular cap WMH volume is an independent risk factor for poor 90-day outcome in patients with AIS. A regression model integrating baseline NIHSS score, cerebral perfusion status, and periventricular cap WMH volume demonstrates good prognostic performance for predicting 90-day functional outcomes in patients with AIS. ]]> Sat,20 Jun 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.06.006 ObjectiveTo investigate the feasibility of applying the diffusion tensor imaging-analysis along the perivascular space (DTI-ALPS) technique in the brains of full-term neonates with hypoxic-ischemic encephalopathy (HIE). Materials and MethodsA prospective study was conducted. Forty-three HIE full-term neonates aged 1 to 28 days were recruited as the study group, and 37 age- and sex-matched full-term neonates without brain abnormalities served as the control group. All neonates underwent conventional MRI sequences and diffusion tensor imaging (DTI) scans. The DTI-ALPS index, reflecting glymphatic system activity, was obtained through post-processing software. The DTI-ALPS values in relevant brain regions were compared and analyzed between the two groups to identify characteristics of the glymphatic system in HIE neonates. ResultsThe DTI-ALPS index was significantly lower in HIE neonates compared to controls (t = 9.12, P < 0.05). Among HIE neonates, the DTI-ALPS index was lower in the 1 to 5 days subgroup than in the 6 to 10 days subgroup (t = 8.98, P < 0.05), while it was higher in the 11 to 20 days subgroup than in the 6 to 10 days subgroup (t = 8.28, P < 0.05). No significant difference was found between the 11 to 20 days and 21 to 28 days subgroups (t = 0.40, P = 0.70). Mild HIE patients exhibited a higher DTI-ALPS index than moderate/severe HIE patients (F = 36.5, P < 0.05), with no significant difference between moderate and severe HIE patients (t = 1.69, P = 0.114). HIE patients with brain injury had a lower DTI-ALPS index than those without (t = 4.08, P < 0.05). The DTI-ALPS index demonstrated good discriminatory ability for identifying HIE neonates (AUC = 0.922, P < 0.001). ConclusionsThe DTI-ALPS imaging technique reveals abnormalities in the glymphatic system of full-term neonates with hypoxic-ischemic encephalopathy. ]]> Sat,20 Jun 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.06.007 ObjectiveTo investigate the value of high-resolution MRI combined with diffusion tensor imaging (DTI) in the quantitative assessment of ulnar nerve microstructure in cubital tunnel syndrome (CTS) and to analyze the correlation between DTI parameters and clinical severity and electrophysiological parameters. Materials and MethodsForty-two patients with CTS (14 McGowan grade Ⅰ, 18 grade Ⅱ, and 10 grade Ⅲ) and 40 healthy controls were prospectively enrolled. Conventional 3.0 T MRI and DTI were used to measure the ulnar nerve cross-sectional area (CSA), signal intensity ratio, fractional anisotropy (FA), apparent diffusion coefficient (ADC), and radial diffusion coefficient (RD) at the entrance, midsection, and exit of the cubital tunnel. The correlation between imaging parameters and McGowan grade and electrophysiological parameters was analyzed, and the diagnostic performance was evaluated. ResultsThe case group had higher CSA [(19.85 ± 5.32) vs. (8.24 ± 1.86) mm²] and RD [(1.45 ± 0.26) vs. (0.82 ± 0.10) × 10^-3 mm²/s] in the mid-cubital tunnel than the control group, while the FA [(0.42 ± 0.09) vs. (0.61 ± 0.04)] was lower (all P < 0.001). FA was positively correlated with motor nerve conduction velocity (r = 0.682), while RD was negatively correlated (r = -0.712). With increasing McGowan grade, FA progressively decreased [grade Ⅰ (0.49 ± 0.06), grade Ⅱ (0.41 ± 0.05), grade Ⅲ (0.32 ± 0.04)], while RD gradually increased. The RD value had the highest diagnostic efficacy [area under the curve (AUC) = 0.918, sensitivity 88.10%, specificity 87.50%], and the AUC of the FA+RD combined model reached 0.943. ConclusionsDTI technology can quantitatively assess the microstructural changes of the ulnar nerve in cubital tunnel syndrome. DTI parameters are closely correlated with clinical severity and electrophysiological indices. The combined application of FA and RD values has excellent diagnostic efficacy and provides an objective imaging basis for the early diagnosis and assessment of cubital tunnel syndrome. ]]> Sat,20 Jun 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.06.008 ObjectiveThis study aimed to develop and validate a multimodal combined model integrating clinical and radiomic features to predict the early response of patients with locally advanced nasopharyngeal carcinoma (LA-NPC) to intensity-modulated radiotherapy (IMRT) combined with targeted therapy. Materials and MethodsA total of 121 patients with LA-NPC who received IMRT with concurrent targeted therapy were retrospectively enrolled. Patients were divided into an early responder group (n = 95) if their three-dimensional tumor volume reduction rate (TVRR) was ≥ 47%, and a non-responder group (n = 26) if TVRR < 47%. Pre-treatment baseline radiomics features were extracted from T2-weighted imaging (T2WI) and contrast-enhanced T1-weighted imaging (T1WI + C) sequences. Strictly within a 5-fold cross-validation framework, feature selection and radiomics model construction were performed using variance thresholding, minimum redundancy maximum relevance (mRMR), and the least absolute shrinkage and selection operator (LASSO) regression. Logistic regression was applied to select clinical indicators to develop a clinical model. Based on these features, the T2WI model, T1WI+C model, dual-sequence radiomics model, clinical model, and multimodal combined model were respectively constructed, and a nomogram was developed for the multimodal combined model. Model performance and clinical net benefit were evaluated using the area under the receiver operating characteristic (ROC) curve (AUC), calibration curves, and decision curve analysis, and the DeLong test was used to compare the AUCs among different models. ResultsMultivariate analysis ultimately retained 10 radiomics features and 4 clinical features (white blood cell count, platelet count, neutrophil-to-lymphocyte ratio, and platelet-to-lymphocyte ratio). The results of 5-fold cross-validation showed that the multimodal combined model exhibited the optimal predictive performance (mean AUC = 0.867), which was significantly superior to the clinical model alone (mean AUC = 0.612), the dual-sequence radiomics model (mean AUC = 0.760), the T2WI model (mean AUC = 0.773), and the T1WI+C model (mean AUC = 0.696) (all P < 0.05). The calibration curve demonstrated high consistency between the predicted probabilities of the nomogram and the actual observed probabilities. Decision curve analysis confirmed that the combined model yielded the best clinical net benefit across a wide range of threshold probabilities (0.1 ~ 0.8). ConclusionsThe multimodal combined model, integrating multimodal radiomics and clinical indicators, can non-invasively and effectively predict the early response to IMRT combined with targeted therapy in patients with LA-NPC. It holds promise to provide reliable decision support for the early identification of treatment-resistant populations and the formulation of individualized intervention strategies. ]]> Sat,20 Jun 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.06.009 ObjectiveTo investigate the value of cardiac magnetic resonance (CMR) in differentiating patients with late-onset cardiac phenotype Fabry disease (FD) carrying the c.640-801G > A mutation from patients with hypertrophic cardiomyopathy (HCM). Materials and MethodsA total of 28 patients with FD who visited Fuzhou University Affiliated Provincial Hospital between November 2019 and October 2024 were retrospectively enrolled as the FD group. A demographically matched cohort of 28 patients with HCM was enrolled as the HCM group, along with 28 healthy controls (HC). Clinical baseline data were collected from all patients and healthy subjects. Standard CMR examinations were performed using a 3.0 T MRI scanner. Depending on the normality of distribution, continuous variables were compared using parametric tests (independent samples t-test) or non-parametric tests (Mann-Whitney U test). Proportions were analyzed using Fisher^,s exact test. Multiple comparisons for continuous variables were corrected using the Bonferroni method. The efficacy of native T1 mapping in differentiating FD from HCM was assessed by the area under the curve (AUC). ResultsLeft ventricular hypertrophy (LVH) was present in 24 of the 28 FD patients (86%) and all 28 HCM patients (100%), with no significant difference between the groups (P = 0.111). However, the left ventricular lateral wall thickness was significantly greater in FD patients compared to both HCM patients and HCs (P < 0.001). Furthermore, the septal-to-lateral wall ratio was significantly lower in FD than in HCM (P < 0.001), indicating a more symmetrical pattern of LVH in FD. Regarding late gadolinium enhancement (LGE), there was no significant difference in the overall presence of any LGE between the FD and HCM groups (P > 0.999). However, LGE in the basal inferolateral wall (P < 0.001) and at the apex (P = 0.029) was significantly more common in FD compared to HCM. Native T1 values were significantly lower in FD than in HCM for global T1 (P < 0.001), septal T1 (P < 0.001), and T1 within LGE areas (P < 0.001). Compared to HC, FD patients had significantly lower septal native T1 values (P = 0.001), while global native T1 values showed no significant difference (P = 0.121). Native T1 cutoff values of 1240 ms in the interventricular septum, 1273 ms in the global left ventricle, and 1302 ms in LGE areas could effectively differentiate FD from HCM. Septal native T1 demonstrated the strongest discriminative power, with a sensitivity of 89.3%, specificity of 96.43%, positive likelihood ratio of 25.0, and negative likelihood ratio of 0.11. ConclusionsCMR can effectively differentiate patients with the late-onset cardiac phenotype of FD carrying the c.640-801G > A mutation from those with HCM. Compared with HCM, patients with this FD phenotype exhibit a decreased native T1 value on CMR images, an LGE pattern predominantly involving the basal inferolateral segment of the left ventricle, and relatively symmetric LVH. The finding of normal global native T1 values in the presence of extensive LGE suggests pseudo-normalization of native T1. ]]> Sat,20 Jun 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.06.010 ObjectiveTo explore the predictive value of parameters of magnetic resonance imaging (MRI) for the prognosis of patients with hepatocellular carcinoma. Materials and MethodsThe clinical data of 123 patients with hepatocellular carcinoma admitted to the First People^,s Hospital of Changde City from January 2021 to January 2024 were retrospectively selected as the hepatocellular carcinoma group. After one year of follow-up after hepatocellular carcinoma resection, MRI examination found metastases in the liver or other organs, which were judged as tumor metastasis or recurrence. Among them, 37 cases of metastasis or recurrence were selected as the early recurrence group, 86 cases were selected as the no early recurrence group, and clinical data of 123 patients with benign liver lesions were collected as the benign liver lesion group. The clinical data, MRI parameter values and MRI parameter values of different pathological features were compared among the groups. The early recurrence group was included in the positive group, and the non-early recurrence group was included in the negative group. The receiver operating characteristic (ROC) curve was used to analyze the predictive value of MRI parameter values for the prognosis of patients with hepatocellular carcinoma. ResultsThe high expression of antigen identified by monoclonal antibody (Ki-67) and the positive expression of cytokeratin 19 (CK19) in hepatocellular carcinoma group were higher than those in benign liver disease group (P < 0.05). T1, perfusion fraction (f) and pseudo diffusion coefficient (D^*) in hepatocellular carcinoma group were higher than those in benign liver disease group, while T2, true diffusion coefficient (D) and apparent diffusion coefficient (ADC) were lower than those in benign liver disease group (P < 0.05). The T1, f and D^* of patients with clinical stage Ⅲ to Ⅳ, tumor diameter ≥ 5 cm, liver function Child-Pugh grade B/C, tissue Ki-67 high expression and tissue CK19 positive expression were higher than those of patients with clinical stage Ⅰ to Ⅱ, tumor diameter < 5 cm, liver function Child-Pugh grade A, tissue Ki-67 low expression and tissue CK19 negative expression, and T2, D and ADC were lower (P < 0.05). T1, f and D^* in the early recurrence group were higher than those in the non-early recurrence group, while D and ADC were lower (P < 0.05). The area under curve (AUC) of combined detection of T1, f, D, D^* and ADC in predicting the prognosis of patients with hepatocellular carcinoma was higher than that of each single detection (P < 0.05). ConclusionsThe parameter values of MRI in patients with hepatocellular carcinoma were related to their pathological features, and the parameter values of MRI had higher clinical value in predicting the prognosis of patients with hepatocellular carcinoma. ]]> Sat,20 Jun 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.06.011 ObjectiveTo construct and assess an imaging-clinical nomogram model integrating MRI and clinical features to identify candidates for early laparoscopic cholecystectomy (LC) consistent with real-world clinical decision-making in patients with non-severe acute biliary pancreatitis (NSABP), thereby informing surgical timing decisions. Materials and methodsThis retrospective study analyzed the MRI and clinical characteristics of 217 NSABP patients who underwent LC during hospitalization at the Affiliated Hospital of North Sichuan Medical College (Institution 1) and Nanchong Central Hospital (Institution 2). Data from Institution 1 were randomly divided into a training cohort (n = 114) and an internal validation cohort (n = 50) in a 7∶3 ratio, while data from Institution 2 were used as the external validation cohort (n = 53). Patients were classified into early and delayed groups based on surgical timing. Univariable and multivariable logistic regression analyses were performed to identify predictors for the choice of surgical timing. A combined model incorporating both imaging and clinical features was constructed, alongside imaging-only and clinical-only models. The accuracy and clinical application value of the nomogram were assessed using the receiver operating characteristic curve, area under the curve (AUC), calibration curve, and decision curve analysis. ResultsMultivariate logistic regression analysis indicated that a maximum gallstone diameter ≤ 5 mm, elevated total cholesterol (TC) level, increased Acute Physiology and Chronic Health Evaluation Ⅱ (APACHE Ⅱ) score, and increased extrapancreatic inflammation on MRI (EPIM) were independent negative predictors for undergoing LC in patients with NSABP in the early phase. In the training cohort, the AUC values of the combined model, imaging model, and clinical model were 0.931 [95% confidence interval (CI): 0.889 to 0.973], 0.707 (95% CI: 0.614 to 0.800), 0.729 (95% CI: 0.641 to 0.817). The Hosmer-Lemeshow test indicated good consistency for the combined model (P = 0.657). Furthermore, the combined model performed well in both the internal and external validation cohorts, with AUC values of 0.891 (95% CI: 0.798 to 0.984), 0.887(95% CI: 0.799 to 0.975), respectively. ConclusionsThe nomogram model based on MRI characteristics and clinical manifestations can assist in identifying patients with NSABP who may undergo LC in the early phase, and it holds significant value for clinicians in assisting clinicians in selecting appropriate surgical timing. ]]> Sat,20 Jun 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.06.012 ObjectiveThe value of MRI-based radiomics and deep learning (DL) in predicting early progression (EP) after treatment for patients with operable rectal cancer: A pre-treatment observation. Materials and MethodsRetrospectively included 255 rectal cancer patients from center 1 and 69 rectal cancer patients from center 2. Patients from center 1 were divided into a training set (n = 204) and an internal test set (n = 51) at a ratio of 8∶2. Patients from center 2 served as the external validation cohort (n = 69). Follow-up was conducted to record EP, defined as tumor recurrence or metastasis within two years post-treatment. Among all patients, 81 experienced EP, while 243 did not. From MRI images, features were extracted and selected to construct radiomics and DL-radiomics (DLR) models. The predictive performance of the models was evaluated and compared by plotting receiver operating characteristic (ROC) curves and calculating the area under the curve (AUC). Additionally, decision curve analysis (DCA) was employed to assess the clinical utility and discriminative ability of the models. ResultsIn this study, 6 radiomics features and 15 DLR features were selected. A k-nearest neighbor (KNN) classifier was used to construct the radiomics model, while a support vector machine (SVM) classifier was used to construct the DLR model. The DLR model (AUC = 0.866, 95% CI: 0.815 to 0.917) significantly outperformed the radiomics model (AUC = 0.724, 95% CI: 0.656 to 0.793). DCA showed that the DLR model provided higher clinical net benefit than the radiomics model. In the external validation set, the DeLong test revealed an extremely statistically significant difference in predictive performance between the two models (P < 0.001). ConclusionsThe DLR model based on pre-treatment MRI images shows better efficacy in predicting EP after treatment in patients with operable rectal cancer, and has good clinical application value, which can be used as an effective auxiliary tool for clinical prediction of patient prognosis and the formulation of individualized treatment strategies. ]]> Sat,20 Jun 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.06.013 ObjectiveTo evaluate the value of combining dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and mDixon-Quant sequences in intratumoral and peritumoral regions for assessing lymphovascular invasion (LVI) status in rectal cancer. Materials and MethodsA retrospective analysis was conducted on the clinical and imaging data of 78 patients with pathologically confirmed rectal cancer. Based on postoperative pathological results, patients were categorized into lymphovascular invasion (LVI) positive (n = 33) and negative groups (n = 45). The dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters including the volume transfer constant (K^trans), rate constant (K_ep), and extravascular extracellular volume fraction (V_e), as well as the mDixon-Quant parameters R2^* and fat fraction (FF) were measured within both the tumor and peritumoral regions. The differences in each parameter between the two groups were compared. Multivariate logistic regression analysis was performed to screen independent correlated factors for LVI in rectal cancer and construct a predictive model. Bootstrap resampling was adopted for internal validation; the area under the curve (AUC) of receiver operating characteristic (ROC) was used to evaluate the discrimination ability of the model; the Hosmer-Lemeshow test and calibration curves were applied to assess the calibration degree; decision curve analysis (DCA) was utilized to verify the clinical validity of the model. ResultsIntratumoral K^trans, R2^*, FF and peritumoral K^trans, R2^*were significantly higher in the LVI (+) group than in the LVI (-) group, while peritumoral FF was significantly lower (all P < 0.05). Multivariate logistic regression analysis demonstrated that intratumoral K^trans, R2^* FF and peritumoral R2^*, FF were independent influencing factors for LVI in rectal cancer. The AUC of the model constructed by combined parameters was 0.854 (95% CI: 0.764 to 0.944), and the AUC reached 0.875 (95% CI: 0.780 to 0.953) after internal validation via the Bootstrap method, indicating excellent discrimination performance of the model. The calibration curve revealed a high consistency between the predicted probability and the actual risk. The Hosmer-Lemeshow test demonstrated a good model fitting effect (χ² = 4.137, P = 0.845). The results of DCA verified that the model possessed favorable clinical practical value. ConclusionIntratumoral and peritumoral DCE-MRI and mDixon-Quant can effectively evaluate the LVI status of rectal cancer. The combination of multiple parameters can improve predictive performance, better reflect tissue perfusion, hypoxia and lipid metabolism, and provide a reliable non-invasive imaging approach for the preoperative assessment of LVI in rectal cancer. ]]> Sat,20 Jun 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.06.014 ObjectiveTo investigate the value of machine learning model based on 3.0 T high-resolution T2-weighted imaging (HR-T2WI) radiomics features combined with traditional imaging and clinical parameters in predicting lymphovascular space invasion (LVSI) in endometrial cancer (EC). Materials and MethodsThe clinical, pathological and imaging data of 173 EC patients confirmed by surgery and pathology in Yidu Central Hospital of Weifang City from January 2019 to December 2024 were retrospectively analyzed. According to whether LVSI existed in postoperative pathological results, they were divided into LVSI-positive and LVSI-negative groups; they were randomly divided into training set and validation set according to 6∶4 ratio by simple random sampling method for model construction and validation. Clinical baseline parameters and conventional imaging features were collected from all patients, and potential risk factors were screened by single factor logistic regression analysis; At the same time, radiomics features were extracted based on 3.0 T HR-T2WI sequence images, and the minimum absolute shrinkage and selection operator (LASSO) algorithm combined with 10-fold cross validation was used to reduce the dimension of features, and the core radiomics features with discrimination value were screened out. The selected core radiomics features were fused with clinical indicators and traditional quantitative imaging indicators to construct five joint predictive models, including linear support vector classifier (Linear SVC), logistic regression (LR), random forest (RF), decision tree (DT), support vector machine (SVM). Area under the receiver operating characteristic curve (AUC), sensitivity and specificity were used to evaluate the predictive power of each model. Decision curve analysis (DCA) assesses the net clinical benefit of each model within a specified threshold range; calibration curves were used to evaluate the consistency and calibration between the predictive probability of each model and the actual observation results. ResultsAmong the five models, the LR model demonstrated the best predictive performance, and multivariate logistic regression analysis suggested that radiomics score (Rad-score) and apparent diffusion coefficient (ADC) values were independent risk factors for predicting LVSI (P < 0.05). LR model had value of 0.89 (95% CI: 0.83 to 0.96), sensitivity of 0.84, and specificity of 0.88 in the training set and AUC value of 0.92 (95% CI: 0.85 to 1.00), sensitivity of 0.92, and specificity of 0.92 in the validation set, and had a high clinical net benefit. ConclusionsThe combined predictive model based on 3.0 T HR-T2WI imaging features has good predictive value for LVSI status of EC patients. The LR model exhibited optimal performance, with Rad‑score and ADC serving as the primary contributing factors, offering reliable evidence for preoperative risk stratification. ]]> Sat,20 Jun 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.06.015 ObjectiveTo explore the associated factors of adolescent knee sport injury (KSI) with different severity levels based on MRI diagnosis. Materials and MethodsClinical and imaging data of 432 adolescents aged 12 to 18 years were retrospectively collected from June 2022 to June 2024. All subjects were divided into three groups according to the severity of knee injury: normal group (n = 174, no structural injury on MRI), low-grade injury group (n = 146, grade Ⅰ to Ⅱ cartilage injury, grade Ⅰ to Ⅱ meniscal injury, or partial ligament tear), and high-grade injury group (n = 112, grade Ⅲ to Ⅳ cartilage injury, grade Ⅲ to Ⅳ meniscal injury, complete ligament rupture or fracture). Clinical and imaging indicators including age, gender, body mass index (BMI), exercise habits (wearing protective gear and appropriate sports shoes and clothing, pre-exercise warm-up, scientific training program, post-exercise stretching), injury history, discoid meniscus, and femoral trochlear dysplasia were enrolled. Kruskal-Wallis H test and Chi-square test were adopted for univariate analysis to screen statistically significant variables, and multinomial logistic regression analysis was further used to analyze the relevant factors for different severities of knee joint injury. ResultsThe proportions of hospitalization and surgery in the high-grade injury group were higher than those in the low-grade injury group and normal group (P < 0.05). The proportion of abnormal knee joint symptoms in the high-grade injury group was higher than that in the other two groups (P < 0.05). Multinomial logistic regression analysis showed that wearing protective gear, appropriate sports shoes and sportswear during exercise, and warming up before exercise were protective factors for adolescent knee sports injuries (P < 0.05); discoid meniscus and history of injury were risk factors (P < 0.05); and trochlear dysplasia was more likely to be associated with low-grade injuries (P < 0.05). ConclusionsBy classifying different severity levels of injury, this study analyzed the associated factors of adolescent KSI: wearing protective gear, appropriate sports shoes, and adequate warm-up are protective factors; discoid meniscus and injury history are risk factors; trochlear dysplasia is associated with low-grade injuries. ]]> Sat,20 Jun 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.06.016 ObjectiveTo investigate the clinical value of accelerated scanning (AS) combined with deep learning reconstruction (DLR) in lumbar spine magnetic resonance imaging (MRI). Materials and MethodsA retrospective analysis was conducted on 116 patients who underwent lumbar spine MRI. Among them, 54 patients received standard imaging with standard reconstruction (group A), and 62 patients underwent AS (group B). The AS images were further processed using two reconstruction methods: standard reconstruction (group B1, n = 62) and DLR (group B2, n = 62). Image quality was assessed using signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and a 5-point Likert scale. Inter-observer agreement was evaluated using the intra-class correlation coefficient (ICC) and Kappa statistics. ResultsNo significant differences were observed in age, sex, or referral reasons between group A and group B (all P > 0.05). For scan Time: Compared with group A, group B achieved a 46% reduction in total acquisition time (185 seconds reduction). For objective image quality: On T1-weighted imaging: SNR of all tissues and CNR of vertebral body were higher in group B2 than in group A and group B1 (all P < 0.05), while no significant difference was found in CNR of the spinal cord among the three groups (P > 0.05). On T2-weighted imaging, no significant differences were observed in SNR or CNR of any tissues among the three groups (all P > 0.05). For subjective image quality: On T1-weighted imaging, group B2 demonstrated higher scores for artifacts, noise, overall image quality, and diagnostic confidence than group A and group B1 (all P < 0.001); the score for anatomical structure display was higher in group B2 than in group A (P < 0.05), and the noise score was higher in group B1 than in group A (P < 0.05). On T2-weighted imaging, group B2 showed higher scores for anatomical structure display, artifacts, noise, overall image quality, and diagnostic confidence than group A and group B1 (all P < 0.001). For consistency analysis: The ICC values for SNR and CNR measurements were 0.980 (95% CI: 0.963 to 0.990) and 0.972 (95% CI: 0.943 to 0.990), respectively. The ICC values for subjective scores on both T1WI and T2WI were all > 0.900. The Kappa values for the grading diagnosis of spinal stenosis and disc abnormalities ranged from 0.876 to 0.944 (all P < 0.001), indicating good inter-observer agreement. ConclusionsAS combined with DLR significantly shortens lumbar spine MRI acquisition time while improving image quality and demonstrating good diagnostic consistency with standard imaging for various spinal abnormalities, offering substantial clinical value for enhancing workflow efficiency and patient comfort. ]]> Sat,20 Jun 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.06.017 ObjectiveTo compare the image quality and scanning efficiency with the currently widely used rat clinical magnetic resonance imaging protocol, and systematically evaluate the feasibility of using metamaterials for 5.0 T MRI of the rat brain. Materials and MethodsThe imaging accuracy of the metamaterial was first validated by performing T1 mapping and T2 mapping on a uniform inorganic solution phantom, comparing the measured T1 and T2 values. Ten-week-old healthy male Sprague-Dawley rats (n = 5) were included. Each rat was scanned under two imaging conditions: one using a rat coil, and the other using a 48-channel head coil combined with the metamaterial. The signal-to-noise ratio (SNR) of MR images was evaluated and compared between the two conditions while maintaining identical scan times and spatial resolution. To further investigate the potential of the metamaterial for improving imaging efficiency, metamaterial^,s scanning parameters were adjusted to achieve the equivalent image SNR with the rat coil parameters, and the differences in scan time were then compared. ResultsThe T1 mapping and T2 mapping results of the phantom indicated that the metamaterial didn^,t compromise imaging accuracy. Under conditions of same scan time and spatial resolution, the metamaterial group showed significantly higher SNR compared to the rat coil group in T1-weighted imaging (T1WI) (t = 21.57, P < 0.001), T2-weighted imaging (T2WI) (t = 24.175, P < 0.001), T1WI-FLAIR (P = 0.043), and T2WI-FLAIR sequences (t = 8.728, P = 0.001). When adjusted to achieve equivalent image SNR, the scan times for the T2WI, T1WI-FLAIR, and T2WI-FLAIR sequences using the metamaterial were also significantly shorter than those with the rat coil. ConclusionsCompared to existing clinical MRI protocols for animals, the metamaterial significantly enhances the SNR and improves scanning efficiency, thereby advancing the imaging capabilities of animal models within clinical MR systems. ]]> Sat,20 Jun 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.06.018 Sat,20 Jun 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.06.019 ^,s disease (AD) is characterized not only by localized structural atrophy of the brain parenchyma, but more fundamentally, as a neurodegenerative disorder driven by the progressive deterioration of large-scale whole-brain functional network topological dynamics. As a non-invasive neuroimaging technique, resting-state functional magnetic resonance imaging (rs-fMRI) has evolved from the early localization of regional brain activity to the systematic quantification of whole-brain functional network connectivity (FNC). Recent studies indicate that the functional networks of AD patients exhibit highly stage-specific alterations, and the dedifferentiation of network topological properties alongside the degradation of core subcortical hubs precede significant clinical cognitive decline. This review systematically summarizes cutting-edge developments in rs-fMRI within the AD continuum, identifies existing research gaps, and highlights future perspectives to support precision diagnosis and individualized intervention for AD. ]]> Sat,20 Jun 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.06.020 ^,s disease (AD) is a neurodegenerative disorder characterized by progressive cognitive dysfunction and memory impairment, predominantly affecting middle-aged and elderly individuals. Its etiology and pathogenesis remain incompletely understood. In recent years, with the continuous advancement of magnetic resonance imaging techniques, diffusion magnetic resonance imaging (dMRI) has played an increasingly important role in the early diagnosis, differential diagnosis, and treatment monitoring of AD. Techniques applied in AD research include intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI), aquaporin magnetic resonance molecular imaging (AQP-MRMI), diffusion tensor imaging (DTI), neurite orientation dispersion and density imaging (NODDI), and diffusion tensor imaging analysis along the perivascular space (DTI-ALPS). This review summarizes the application progress of the aforementioned dMRI techniques in AD, aiming to provide insights for early diagnosis and pathological mechanism research of AD. ]]> Sat,20 Jun 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.06.021 ^,s metabolic waste clearance axis, and to explore the potential pathways through which pain may influence different components of this system. In addition, it summarizes recent advances in the application of various MRI techniques for evaluating the GS and related structures, and reviews imaging evidence across different pain conditions. Finally, the limitations and future directions of the current research are summarized and discussed, with the aim of providing new insights into pain mechanism research and imaging evaluation. ]]> Sat,20 Jun 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.06.022 Sat,20 Jun 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.06.023 Sat,20 Jun 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.06.024 Sat,20 Jun 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.06.025 Sat,20 Jun 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.06.026 Sat,20 Jun 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.06.027 Sat,20 Jun 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.06.028 ^,s health. Parametrial invasion (PMI) is a critical adverse prognostic factor in cervical cancer, and its presence directly impacts the patient^,s clinical staging and treatment decisions. Therefore, accurate evaluation of PMI is of great significance for formulating individualized treatment strategies and improving patient prognosis. In current clinical practice, the conventional pre-treatment evaluation methods for PMI primarily include clinical examination and imaging examination. In terms of clinical examination, conventional palpation is simple but has limited accuracy, whereas examination under anesthesia (EUA) and augmented EUA (aEUA) can significantly improve diagnostic precision. In radiological evaluation, ultrasound, computed tomography (CT), and magnetic resonance imaging (MRI) each possess distinct advantages and limitations, with MRI serving as the primary diagnostic modality. Furthermore, emerging technologies such as multimodal imaging and medical imaging artificial intelligence technologies offer novel approaches to enhance the diagnostic accuracy of PMI in cervical cancer. This article systematically reviews the current research status, advancements, and limitations regarding the clinical and imaging evaluation of PMI in cervical cancer, aiming to provide a more comprehensive reference for precise clinical staging and treatment decision-making, while also offering guidance for future research directions. ]]> Sat,20 Jun 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.06.029 Sat,20 Jun 2026 00:00:00 GMT