http://med-sci.cn/cgzcx/en/contents_list.asp?issue=202609 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.1674-8034.2026.09.001 Sun,20 Sep 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.09.002 ObjectiveTo explore the value of chest CT-derived body composition analysis combined with amide proton transfer-weighted (APTw) imaging in assessing the functional prognosis of patients with acute ischemic stroke (AIS). Materials and MethodsThis prospective study enrolled 108 AIS patients (age 62.96 ± 9.55 years). All patients underwent both head APTw imaging and chest CT scans. Functional outcomes were assessed using the 90-day modified Rankin scale (mRS) and patients were dichotomized into a favorable prognosis group (mRS ≤ 2, n = 58) and an unfavorable prognosis group (mRS > 2, n = 50). Body composition analysis based on non-contrast chest CT images included epicardial adipose tissue (EAT), visceral adipose tissue at the 12th thoracic vertebra level (VAT_T12), subcutaneous adipose tissue at the 12th thoracic vertebra level (SAT_T12), and skeletal muscle at the 12th thoracic vertebra level (SM_T12). Quantitative parameters derived from the APTw images [including the maximum values of APT (APTwmax_lesion and APTwmax_contralateral side), minimum values (APTwmin_lesion and APTwmin_contralateral side), average values (APTwmean_lesion and APTwmean_contralateral side), and the APTwmax-min value in the infarct core and contralateral normal white matter] were assessed. Differences in quantitative parameters between groups were evaluated using independent samples t-tests or the Mann-Whitney U test. Univariate and multivariate logistic regression analyses were performed to screen for independent predictors associated with AIS functional prognosis, and a nomogram model was constructed accordingly. The predictive performance of the model was assessed using the receiver operating characteristic (ROC) curve, calculating the area under the curve (AUC), accuracy, sensitivity, and specificity. Differences in AUC values between models were compared using DeLong^,s test. Calibration curves were used to evaluate the deviation between predicted and actual probabilities, and the Hosmer-Lemeshow test was employed to assess model goodness-of-fit (P > 0.05 indicating good fit). The clinical utility of the model was evaluated using decision curve analysis (DCA). The importance of each feature within the nomogram model was interpreted using SHapley additive explanations (SHAP). ResultsBased on 90-day mRS scores, patients were categorized into the favorable prognosis group (n = 58, mRS: 0-2) and the unfavorable prognosis group (n = 50, mRS: 3-6). Apart from admission mRS (t = 3.782, P < 0.001) and National Institutes of Health Stroke Scale (NIHSS) (t = 2.743, P = 0.006), other clinical characteristics showed no significant differences between groups. Body composition analysis revealed that patients in the unfavorable prognosis group had significantly higher epicardial adipose tissue volume (EATV) and visceral adipose tissue area at the 12th thoracic vertebra level (VAT_T12) (t = 4.948, 3.765, P < 0.001), but lower attenuation values for EAT, VAT_T12, and SM_T12 (t = -3.025, P = 0.002; t = -2.434, P = 0.015; t = -2.350, P = 0.021, respectively) compared to the favorable prognosis group. Analysis of APTw-derived quantitative parameters showed significantly lower APTwmin_lesion (t = -3.036, P = 0.002) and higher APTwmax-min_lesion (t = 2.365, P = 0.018) values in the unfavorable prognosis group. After screening for multicollinearity [variance inflation factor (VIF) < 5], multivariate logistic regression identified admission mRS score [OR = 2.726 (95% CI: 1.347 to 5.517), P = 0.005], EATV [OR = 1.019 (95% CI: 1.002 to 1.036), P = 0.026], and APTwmin_lesion [OR = 0.236 (95% CI: 0.084 to 0.662), P = 0.006] as independent predictors of unfavorable prognosis. A nomogram model was subsequently constructed. The AUC values for predicting AIS functional prognosis were 0.704, 0.777, 0.670, and 0.873 for the individual independent predictors and the combined nomogram model, respectively. The calibration curve (Hosmer-Lemeshow test X-squared = 10.533, P = 0.230) and DeLong^,s test (P < 0.05) confirmed that the nomogram model^,s predicted probabilities were highly consistent with the actual outcomes and that its performance was superior to that of individual predictors. The DCA curve demonstrated that the nomogram model provided the optimal net clinical benefit across all threshold probabilities. SHAP analysis revealed that the order of feature contribution to the nomogram model was EATV, followed by APTwmin_lesion, and then admission mRS score. ConclusionsThe combination of chest CT-derived body composition analysis and APTw imaging provides a comprehensive assessment of AIS functional prognosis from dual perspectives: local brain injury characteristics and systemic metabolic reserve status. This approach offers a more reliable multi-dimensional imaging basis for the early and precise identification of patients at high risk for unfavorable outcomes, thereby providing a basis for risk stratification and health management in AIS patients. ]]> Sun,20 Sep 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.09.003 ObjectiveThis study aims to investigate the value of abdominal CT body composition analysis combined with diffusion kurtosis imaging (DKI) for the preoperative prediction of tumor budding (TB) grade in patients with T3 to T4 rectal cancer. Materials and MethodsA retrospective analysis was conducted on data from 89 patients diagnosed with T3 to T4 rectal adenocarcinoma, confirmed by postoperative pathology. All patients underwent pelvic 3.0 T MRI and whole abdominal CT examinations prior to surgery. Based on the pathological results, the TB grade was categorized into two groups: a low-intermediate grade TB group (52 cases) and a high grade TB group (37 cases). Two observers measured the quantitative parameters of DKI in the lesions of both groups, including fractional anisotropy (FA) value, mean diffusivity (MD) value, and mean kurtosis (MK) value. The TotalSegmentator tool was utilized to automatically segment subcutaneous fat, visceral fat, and muscle at the L3 level of the abdominal CT scans. Python software facilitated the automatic calculation of subcutaneous fat area (SFA), visceral fat area (VFA), and muscle area (MA). The ratios of VFA to SFA (VFA/SFA), SFA to standard body weight (SBW) (SFA/SBW), VFA to SBW (VFA/SBW), MA to SBW (MA/SBW), and the difference between VFA and SFA (VFA-SFA) were calculated. The consistency of DKI parameters assessed by two observers was evaluated using the intra-class correlation coefficient (ICC). To examine the differences in DKI parameters and body composition indicators across the groups, either a Mann-Whitney U test or an independent sample t-test was utilized. A multivariate logistic regression analysis was performed to determine independent risk factors, which facilitated the creation of a combined prediction model based on these factors. The diagnostic performance of each individual risk factor, as well as the combined prediction model, was evaluated through the receiver operating characteristic (ROC) curve. To compare the diagnostic efficacy between the individual variables and the combined model, the DeLong test was employed, whereas the McNemar test was used to assess differences in sensitivity and specificity. ResultsThe consistency of the DKI quantitative parameters measured by the two observers was good, with ICC values exceeding 0.75. In the high grade TB group, the MK, VFA, and VFA/SBW values were 0.938 (0.891, 1.019), [150.620 (107.685, 199.840)] cm², and 2.490 (1.730, 3.210), respectively, significantly surpassing those in the low-intermediate grade TB group, which had values of 0.776 (0.685, 0.878), [117.205 (72.067, 169.762)] cm², and 2.115 (1.242, 2.650). The MD value in the high grade TB group was (1.113 ± 0.105) μm²/ms, which was lower than that in the low-intermediate grade TB group (1.347 ± 0.257) μm²/ms. The differences between the two groups for all the aforementioned parameters were statistically significant (P < 0.05). The results of multivariate logistic regression analysis indicated that the MK value [odds ratio: 4.104, 95% confidence interval (CI): 2.223 to 7.578] and the VFA/SBW value [odds ratio: 2.335 (95% CI: 1.300 to 4.195)] were independent risk predictors for TB grade (P < 0.05). The area under the curve (AUC) for predicting TB grade based on the MK and VFA/SBW values, as well as their combined prediction model, were 0.838, 0.627, and 0.886, respectively. The sensitivity of these models was 91.89%, 72.97%, and 81.08%, respectively, while the specificity was 67.31%, 50.00%, and 80.77%, respectively. The diagnostic efficacy of the combined prediction model was superior to that of VFA/SBW alone, and its specificity exceeded that of both MK and VFA/SBW, with statistically significant differences (P < 0.05). ConclusionsFor patients with T3 to T4 rectal cancer, DKI has been shown to effectively predict TB grade. Additionally, body composition analysis serves to preliminarily stratify the risk of TB. The integration of these two modalities significantly enhances the accuracy of predicting TB grade, thereby providing more comprehensive insights into the interplay between host factors and local tumor characteristics for preoperative TB risk assessment. ]]> Sun,20 Sep 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.09.004 ObjectiveTo evaluate the value of preoperative chest CT-derived body composition indices combined with quantitative multiparametric magnetic resonance imaging (mpMRI) features of prostate cancer (PCa) lesions and periprostatic adipose tissue (PPAT), together with clinical laboratory indicators, for predicting perineural invasion (PNI) in PCa. Materials and MethodsSeventy five patients with pathologically confirmed PCa were retrospectively enrolled and divided into a PNI-positive group (n = 35) and a PNI-negative group (n = 40). Muscle and adipose tissue areas and their ratios at the T12 vertebral level were automatically quantified from non-contrast chest CT images using Total Segmentator. Quantitative parameters derived from intravoxel incoherent motion (IVIM) and mDIXON-QUANT sequences were extracted from intraprostatic lesions and PPAT on mpMRI. Regions of interest were independently delineated by two radiologists, and mean values were used after interobserver agreement was confirmed by intra-class correlation coefficient. Independent predictors of PNI were identified using univariate analysis followed by multivariate logistic regression. Single-parameter and combined prediction models were constructed and evaluated using receiver operating characteristic (ROC) analysis and area under the curve (AUC). Model performance was compared using the DeLong test, and a nomogram was developed for visualization of the combined model. Model calibration was assessed using the Hosmer-Lemeshow goodness-of-fit test, and internal validation was performed using bootstrap resampling (1000 repetitions). ResultsThe PNI-positive group exhibited significantly higher muscle area [(86.54 ± 16.42) cm² vs. (76.52 ± 14.84) cm²], PPAT-fat fraction (FF) [(69.37% ± 9.33%) vs. (62.07% ± 7.24%)], and IVIM-perfusion fraction (f) values [0.47 (0.33, 0.63) vs. 0.31 (0.25, 0.60)] and significantly lower red blood cell (RBC) levels [(3.90 ± 0.35) /μL vs. (4.26 ± 0.40) /μL] compared with the PNI-negative group (all P < 0.05). Multivariate analysis identified muscle area [AUC = 0.668, 95% confidence interval (CI): 0.545 to 0.790], PPAT-FF (AUC = 0.724, 95% CI: 0.610 to 0.839), and RBC (AUC = 0.673, 95% CI: 0.550 to 0.796) as independent predictors of PNI. The combined model (muscle area + PPAT-FF + RBC) achieved an AUC of 0.848 (95% CI: 0.763 to 0.933), with a sensitivity of 71.4% and a specificity of 80.0%. Its predictive performance was significantly superior to that of each single indicator (DeLong test: combined model vs. muscle area, P = 0.012; combined model vs. PPAT-FF, P = 0.023; combined model vs. RBC, P = 0.008). ConclusionsIntegration of chest CT-based body composition metrics with mpMRI quantitative features of prostate cancer lesions and periprostatic adipose tissue, together with clinical laboratory indicators, significantly enhances the preoperative prediction of perineural invasion in prostate cancer. ]]> Sun,20 Sep 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.09.005 ObjectiveTo investigate the relationship between body mass index (BMI) and lumbar paraspinal muscle imaging parameters with the recurrence of chronic low back pain (CLBP). Materials and MethodsThe patients with CLBP were prospectively recruited from the First Affiliated Hospital of Kunming Medical University, Baoshan People^,s Hospital, Dali Bai Autonomous Prefecture People^,s Hospital and The first People^,s Hospital of Honghe State. Clinical and imaging data were collected. Patients were divided into non-overweight (18.5 to 23.9 kg/m²) and overweight (≥ 24.0 kg/m²) groups based on BMI, and differences in paraspinal muscle parameters between groups were analyzed. Univariate and multivariate analyses were used to identify risk factors for CLBP recurrence. Receiver operating characteristic (ROC) curves were employed to evaluate the predictive performance of different models and to compare model performance after incorporating paraspinal muscle parameters and BMI. ResultsThis study included a total of 317 patients with CLBP, consisting of 126 males (39.75%). Recurrence was observed in 116 patients (36.59%), and 110 patients (34.70%) were overweight. The multifidus muscle proton density fat fraction (MPDFF) was significantly higher in the recurrence group than in the non-recurrence group (P < 0.05). At the L4-L5 level, the multifidus muscle cross sectional area (MCSA) was significantly smaller in the recurrence group compared to the non-recurrence group (P < 0.05). Logistic regression analysis showed that elevated MPDFF_L4-L5 (P = 0.008, OR = 1.04) and MCSA_L4-L5 (P = 0.037, OR=0.84) were independent predictors of CLBP recurrence. The area under the receiver operating characteristic curve (AUC) for the model combining lumbar paraspinal parameters with clinical characteristics was superior to that of BMI (0.64 vs. 0.60, P < 0.05). ConclusionsLumbar paraspinal muscle PDFF is associated with CLBP recurrence and has a better predictive value than BMI. ]]> Sun,20 Sep 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.09.006 ObjectiveTo investigate the impact of fat deposition in various depots on the atherogenic index of plasma (AIP) among middle-aged and elderly postmenopausal females. Materials and MethodsA prospective observational study was conducted, enrolling 102 postmenopausal middle-aged and elderly females who visited our hospital between December 2022 and June 2024. Clinical and biochemical data were collected. Quantitative CT was used to measure the visceral fat area (VFA), subcutaneous fat area (SFA), and paraspinal muscle (erector spinae and multifidus muscles, psoas major) fat area to calculate the fat fraction (FF) at the level of the third lumbar vertebra. The CT values of skeletal muscles at the same level were also measured. MRI mDixon-quant sequences were employed to assess the proton density fat fraction (PDFF) of the liver, pancreas, and lumbar bone marrow. Clinical data and fat content of different depots were compared between the low and high AIP groups, logistic regression analysis was employed to identify the factors influencing AIP. Receiver operating characteristic (ROC) curves were applied to evaluate the diagnostic efficacy of each parameter in identifying the high AIP phenotype. ResultsThe high-AIP group exhibited significantly higher BMI, VFA, and liver PDFF compared to the low-AIP group (P < 0.05). Both VFA (OR = 1.020, 95% CI: 1.005 to 1.036) and liver PDFF (OR = 1.241, 95% CI: 1.081 to 1.424) were identified as independent risk factors for high AIP. The diagnostic performance of liver PDFF in diagnosing high AIP is superior to that of BMI (P = 0.044). Both liver PDFF and VFA showed good diagnostic efficacy for high AIP, with area under the curve (AUC) of 0.823 and 0.788, respectively. The cutoff values were 4.58% for liver PDFF and 127.6 cm² for VFA, with corresponding sensitivities of 82.1% and 96.4%, and specificities of 77.0% and 50.0%, respectively. Furthermore, a combined model integrating VFA and liver PDFF significantly improved the ability to predict high AIP, with an AUC of 0.847, a sensitivity of 92.9%, and a specificity of 63.5%. ConclusionsVFA and liver PDFF are independent risk factors for elevated AIP in postmenopausal females. Compared with BMI, imaging-based quantitative assessment of fat provides a more accurate prediction of high-risk populations for atherosclerosis. ]]> Sun,20 Sep 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.09.007 ObjectiveTo investigate the coordinated changes in brain structure and function in obese children, providing imaging evidence for understanding the effects of obesity on pediatric neurodevelopment. Materials and MethodsThis study was a prospective case-control study, consecutively enrolling 46 obese children aged 8 to 14 years and 48 children of normal weight. Multimodal MRI scanning was performed using a 3.0 T scanner, including three-dimensional T1-weighted imaging (3D-T1WI), diffusion tensor imaging (DTI), and resting-state functional MRI (rs-fMRI), to compare differences in gray and white matter volumes, white matter integrity, and functional network connectivity between the two groups. ResultsCompared with control group, the obese group showed significantly reduced volumes in prefrontal cortex and hippocampus (P < 0.001), and significantly increased volumes in the striatum and orbitofrontal cortex (P < 0.001). DTI showed significantly decreased fractional anisotropy values in the corpus callosum and internal capsule in the obese group (P < 0.001). Functional analysis revealed altered network connectivity in the obese group, with enhanced connectivity within reward and default mode networks and weakened connectivity within the executive control network (P < 0.001). Structural and functional changes were significantly correlated (r = 0.58 to 0.65, P < 0.001). ConclusionsThis study suggests that obese children may exhibit a coordinated patterns of reduced volume in cognitive control regions accompanied by reward system hyperactivation. Multimodal MRI may help elucidate the associations between obesity and structural and functional brain alterations in children, providing imaging clues for the early identification and precision intervention of obesity-related neurodevelopmental disorders. ]]> Sun,20 Sep 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.09.008 ObjectiveTo investigate the abnormal characteristics of static amplitude of low-frequency fluctuations (sALFF) and dynamic amplitude of low-frequency fluctuations (dALFF) in resting-state functional magnetic resonance imaging (rs-fMRI) among adolescents with autism spectrum disorder (ASD), and to analyze their associations with clinical symptoms and the distribution of neurotransmitter systems. Materials and MethodsThis was a retrospective case-control study. Fifty-seven adolescents with ASD and 71 age- and sex-matched healthy controls (HC) were retrospectively screened from the Autism Brain Imaging Data Exchange (ABIDE) database as study subjects. After standard preprocessing, whole-brain sALFF and dALFF (calculated using a sliding-window approach) were derived. After controlling for age, gender, mean framewise displacement, and full-scale IQ, two-sample t-tests were performed for intergroup comparisons, followed by Gaussian Random Field (GRF) correction. Pearson correlation analyses were conducted to assess relationships between altered brain activity and stereotyped behavior scores from the Autism Diagnostic Observation Schedule (ADOS). Spatial correlation analyses between case-control difference maps and templates of 10 neurotransmitter receptors / transporters were performed using the JuSpace toolbox with correction for multiple comparisons. ResultsCompared with the HC group, the ASD group exhibited significantly decreased sALFF in the left medial orbital superior frontal gyrus (peak t = -4.347, GRF corrected, P < 0.05) and significantly increased dALFF in the left middle frontal gyrus (peak t = 4.429, GRF corrected, P < 0.05) and orbital part of the left middle frontal gyrus (peak t = 5.327, GRF corrected, P < 0.05). The reduced sALFF in the left medial orbital superior frontal gyrus showed a positive correlational trend with ADOS stereotyped behavior scores (r = 0.263, uncorrected P = 0.048), while increased dALFF in the orbital part of the left middle frontal gyrus showed a stronger positive correlation trend (r = 0.294, uncorrected P = 0.026). Spatial correlation analysis revealed that sALFF alterations were negatively correlated with dopamine D1 receptor density (r = -0.73, q < 0.01) and positively correlated with dopamine D2 receptor density (r = 0.92, q < 0.01). In contrast, dALFF alterations were positively correlated with serotonin 5-HT4 receptor (r = 0.43, q < 0.01) and dopamine D1 receptor density (r = 0.42, q < 0.01), and negatively correlated with serotonin 5-HT1a receptor (r = -0.23, q < 0.05), dopamine D2 receptor density (r = -0.65, q < 0.01) and ¹⁸F‑FDOPA uptake distribution (r = -0.50, q < 0.01). ConclusionsAdolescents with ASD exhibit distinct abnormalities in both static and dynamic local brain activity within the prefrontal cortex. Dynamic alterations show stronger associations with stereotyped behaviors. These functional abnormalities are closely related to dopaminergic and serotonergic systems, suggesting that dALFF may serve as a putative neuroimaging biomarker reflecting the neurobiological mechanisms of ASD. ]]> Sun,20 Sep 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.09.009 ObjectiveTo investigate alterations in intranetwork functional connectivity in Parkinson^,s disease (PD) based on independent component analysis (ICA). Materials and MethodsIn this prospective case-control study, resting-state functional magnetic resonance imaging (fMRI) data from 28 patients with PD and 32 healthy controls (HC) were preprocessed. ICA was performed to identify resting-state functional networks. Differences in intranetwork functional connectivity between the two groups were compared, and correlations between the functional connectivity strength of altered brain regions and Unified Parkinson^,s Disease Rating Scale Part Ⅲ (UPDRS Ⅲ) scores were analyzed. ResultsCompared with HC, patients with PD exhibited significantly decreased functional connectivity within the left paracentral lobule of the somatomotor network (SMN) (t = -5.21, P_FWE-corr < 0.001), as well as within the right middle frontal gyrus (t = -4.71, P_FWE-corr = 0.015) and right inferior parietal lobule (t = -4.68, P_FWE-corr = 0.015) of the right frontoparietal network (RFPN). The functional connectivity strength of the left paracentral lobule was negatively correlated with the UPDRS Part Ⅲ score (r = -0.512, P = 0.005, q = 0.015), whereas no significant correlations were observed between the UPDRS Part Ⅲ score and the functional connectivity strengths of the right middle frontal gyrus (r = 0.049, P = 0.805, q = 0.805) or the right inferior parietal lobule (r = 0.115, P = 0.560, q = 0.805). ConclusionsReduced functional connectivity within the SMN was associated with motor symptom severity in patients with PD, whereas the clinical implications of reduced functional connectivity within the RFPN remain to be further elucidated. ]]> Sun,20 Sep 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.09.010 ObjectiveTo explore the fractional amplitude of low-frequency fluctuation (fALFF), regional homogeneity (ReHo), and voxel-mirrored homotopic connectivity (VMHC) during the resting state in patients with post-stroke cognitive impairment (PSCI), and to investigate their correlations with clinical indicators and neurocognitive assessment scales. Materials and MethodsA total of 61 patients with PSCI admitted to the Department of Neurology of the First Affiliated Hospital of Xinjiang Medical University from June 2025 to December 2025 were enrolled. In addition, 50 community-dwelling healthy controls (HC) without a history of cognitive impairment were recruited. All participants underwent resting-state functional magnetic resonance imaging. A two-sample t-test was performed using the DPABI V8.2 software package to compare resting-state functional differences between the two groups and identify brain regions with significant differences. Using the AAL atlas, the fALFF, ReHo, and VMHC values of these regions were extracted, and correlation analyses were performed between these functional indicators and neurocognitive assessment scales. ResultsCompared with the HC group, PSCI group showed decreased fALFF values in left medial superior frontal gyrus, left inferior parietal lobule, and right angular gyrus. Decreased ReHo values were observed in left inferior parietal lobule, left middle frontal gyrus, right superior parietal lobule, and right postcentral gyrus. In addition, decreased VMHC values were found in bilateral postcentral gyri, bilateral middle temporal gyri, and bilateral angular gyri. Correlation analysis revealed that fALFF value of left inferior parietal lobule was negatively correlated with Montreal Cognitive Assessment (MoCA) scores (r = -0.29, P = 0.021). No significant correlations were found among fALFF, ReHo, or VMHC values of other brain regions and MoCA scores (P > 0.05). ConclusionsThis study demonstrated that PSCI patients exhibited alterations in fALFF, ReHo, and VMHC values in specific brain regions compared with healthy individuals. Moreover, fALFF value of left inferior parietal lobule was associated with cognitive performance. These findings provide new insights into potential neural mechanisms underlying functional brain alterations in PSCI patients. ]]> Sun,20 Sep 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.09.011 ObjectiveUsing amide proton transfer (APT) imaging, we analyzed APT signal alterations in patients with obstructive sleep apnea (OSA) and the associations between cerebral APT signals, obesity, cognitive performance, and daytime sleepiness. Materials and MethodsA total of 121 subjects were prospectively enrolled, including 81 patients with OSA and 40 healthy controls. All participants underwent 3.0 T cranial APT-weighted imaging and conventional MRI sequences. Fourteen whole-brain regions of interest (ROIs) were manually delineated to extract APT values. Multi-dimensional cognitive assessments and the Epworth Sleepiness Scale (ESS) were performed concurrently. The Mann-Whitney U test was used to compare intergroup differences in regional APT values. Partial correlation analyses adjusted for confounding factors were performed to explore correlations among variables. Mediation effect tests were conducted using the Bootstrap method with 5000 resamples, and the false discovery rate (FDR) correction was applied for multiple comparisons. ResultsAPT values of the left frontal lobe, the bilateral parietal lobes, left temporal lobe, and bilateral hippocampi were significantly higher in the OSA group than those in the control group (Z = -3.223, -2.700, -4.143, -3.923, -3.218, and -3.813, respectively; all P < 0.05 after FDR correction). After adjustment for age, sex, and education level, APT signals of these abnormal brain regions were correlated with body mass index (BMI), multiple cognitive metrics, and ESS scores. Mediation analyses demonstrated that left temporal lobe APT signals exerted partial mediating effects on the associations between BMI and digit symbol test performance, baseline processing speed, conflict‑processing speed, global cognitive function, and ESS scores [standardized indirect effect β = -0.052, 95% confidence interval (CI): -0.109 to -0.007; β = 0.078, 95% CI: 0.012 to 0.149; β = 0.081, 95% CI: 0.013 to 0.153; β = 0.080, 95% CI: 0.014 to 0.155; β = 0.054, 95% CI: 0.008 to 0.113; mediating effect proportions were 14.2%, 33.4%, 31.4%, 32.2%, and 12.8%, respectively]. ConclusionsPatients with OSA exhibit characteristic regional alterations in APT signals. Associations were observed among BMI, cerebral APT values, and cognitive impairment in all subjects. The left temporal lobe APT signal alterations may represent a potential cerebral intermediate link between BMI and cognitive impairment as well as daytime sleepiness. APT signals may serve as potential non-invasive neuroimaging biomarkers for assessing cognitive damage in patients with OSA. ]]> Sun,20 Sep 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.09.012 ObjectiveTo explore the value of multi-delay arterial spin labeling (m-ASL) in assessing territorial perfusion impairment in patients with posterior circulation ischemic stroke (PCIS). Materials and MethodsThis prospective study included 54 PCIS patients [29 in the posterior cerebral artery (PCA) group, 25 in the vertebrobasilar artery (VBA) group] and 27 healthy control (HC). All subjects underwent both single-delay ASL (s-ASL) and m-ASL scanning sequences. Parameters including CBF₂₀₀₀, corrected cerebral blood flow (cCBF), arterial transit time (ATT), and arterial cerebral blood volume (aCBV) were obtained. Independent samples t-test was used to compare parameters between the unaffected side of PCIS patients and the HC. Paired sample t-test was used to compare CBF from s-ASL and m-ASL between the HC and PCIS patients, as well as to compare various parameters between the infarct lesions and their mirror regions in PCIS patients. ResultsThe CBF measured in the posterior circulation by m-ASL was significantly higher than that by s-ASL (P < 0.05). In both the PCA and VBA territories, cCBF was significantly lower (P < 0.05) and ATT was significantly prolonged (P < 0.05) on the unaffected side of patients compared to the HC. In the PCA and VBA groups, CBF₂₀₀₀, cCBF, and aCBV were significantly lower in the infarct lesions compared to the mirror regions (P < 0.05), while no significant difference was found in ATT. The ΔCBF from m-ASL was significantly higher than that from s-ASL in the PCA group (P < 0.05), whereas no significant difference in ΔCBF was found between the two techniques in the VBA group. ConclusionsThe m-ASL can correct the underestimation of CBF by s-ASL and provide multiple perfusion parameters, offering a more detailed characterization of perfusion impairment patterns in the posterior circulation territories of PCIS patients. ]]> Sun,20 Sep 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.09.013 ObjectiveTo construct cerebral blood flow functional networks using arterial spin labeling (ASL), investigate their topological characteristics and associations with cognitive function in patients with mild cognitive impairment (MCI), and evaluate the potential value of related network metrics for the early diagnosis of MCI. Materials and MethodsA total of 113 patients with MCI and 83 age- and sex-matched healthy controls were prospectively enrolled. Cerebral blood flow (CBF) was quantitatively measured using ASL. The brain was parcellated into 116 regions according to the Automated Anatomical Labeling (AAL) atlas, with these regions defined as network nodes. Kernel density estimation was subsequently used to model the probability distribution of CBF values within each brain region. Jensen-Shannon divergence (JSD) was applied to quantify differences between regional CBF probability distributions, and individual cerebral blood flow networks were constructed through similarity transformation. Global and nodal topological metrics were calculated using graph-theoretical analysis, and the area under the curve (AUC) of each metric across a sparsity range of 0.04 to 0.40 was used for statistical analysis. Between-group comparisons were performed using a nonparametric permutation test based on covariate residualization with 10,000 permutations, controlling for age, sex, and years of education. Multiple comparisons were corrected using the Benjamini-Hochberg false discovery rate (FDR) method. Partial Spearman correlation analyses controlling for age, sex, and years of education were conducted to evaluate the associations between network metrics and scores on the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Digit Span Test (DST). ResultsCompared with the healthy control group, the MCI group exhibited cerebral blood flow network alterations predominantly at the nodal level. (1) Global properties: Global efficiency and the small-world coefficient tended to increase, whereas path length tended to decrease in patients with MCI; however, none of these differences remained statistically significant after FDR correction. (2) Nodal properties: Within core regions of the default mode network, nodal local efficiency and clustering coefficient were decreased in the left posterior cingulate gyrus and left inferior parietal lobule, suggesting impaired local information processing. Increased betweenness centrality in the left inferior frontal gyrus suggests an enhanced bridging role in network information transfer. The parahippocampal gyrus showed asymmetric alterations between the hemispheres, with increased nodal local efficiency on the left and increased nodal degree centrality and nodal efficiency on the right. Nodal efficiency and clustering coefficient were also increased in basal ganglia regions, including the caudate nucleus and lentiform nucleus (FDR-corrected P < 0.05). (3) Correlation analysis: MMSE scores were positively correlated with the clustering coefficient and nodal local efficiency of the left triangular part of the inferior frontal gyrus, whereas DST scores were positively correlated with normalized characteristic path length. MMSE scores were negatively correlated with global efficiency, normalized clustering coefficient, small-world coefficient, and betweenness centrality of the left triangular part of the inferior frontal gyrus (FDR-corrected P < 0.05). ConclusionsCerebral blood flow network abnormalities in patients with MCI were primarily characterized by nodal topological reorganization in key brain regions. Several network metrics showed statistically significant associations with cognitive scores, suggesting that these metrics may reflect individual differences in cognitive function in patients with MCI and may have potential value for adjunctive cognitive assessment. ]]> Sun,20 Sep 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.09.014 ObjectiveTo analyze functional lateralization of the cerebral hemispheres and the mechanism of acupuncture in ischemic stroke (IS) patients based on voxel-level functional magnetic resonance imaging (fMRI). Materials and MethodsThe study included 60 inpatients with ischemic stroke (IS) at Dongzhimen Hospital of Beijing University of Chinese Medicine and 30 healthy controls. IS patients were divided into a left ischemic stroke (LIS) group and a right ischemic stroke (RIS) group based on the location of the lesion. The patient groups received acupuncture intervention with the hand-foot 12 needles acupuncture, while the control group received no intervention. At the whole-brain voxel level, brain regions showing significant differences in degree centrality (DC) were compared between the LIS group, RIS group, and control group. Regions with significant DC differences were then used as seed points for functional connectivity (FC) analysis. ResultsA total of 35 patients with IS, including 20 cases in the LIS group and 15 cases in the RIS group, as well as 29 healthy controls (HC) were enrolled in this study. The degree centrality (DC) values of Cerebelum_6_R in the LIS group (t = -4.79, P < 0.001) and Calcarine_R in the RIS group (t = -4.19, P < 0.001) were significantly lower than those of the HC group. Following acupuncture intervention, the FC between the Calcarine_R and the Occipital_Sup_R in the RIS group was significantly higher than that before intervention (t = 5.37, P < 0.001). Regarding pre-intervention FC, the LIS group exhibited significantly lower FC between the Cerebelum_6_R and the Precentral_L (t = -7.84), Calcarine_L (t = -6.32), Cingulum_Mid_L (t = -5.17), and Precentral_R (t = -5.68) compared with the HC group. Similarly, in the RIS group, the FC between the Cerebelum_6_R and the Precentral_R (t = -5.26), Cuneus_L (t = -5.24), Lingual_L (t = -4.91), and Calcarine_R (t = -4.16) was significantly lower than that of the HC group; furthermore, the FC between the Calcarine_R and the Occipital_Mid_R (t = -6.41), Occipital_Mid_L (t = -5.10), Cerebelum_Crus1_L (t = -4.99), and Temporal_Inf_R (t = -4.84) was also significantly lower than that of the HC group (all P < 0.001). After acupuncture intervention, the FC between the Cerebelum_6_R and the Postcentral_L (t = -6.08), Precentral_R (t = -5.38), Postcentral_R (t = -4.80), Precentral_L (t = -3.85), and Postcentral_L (t = -5.55) in the LIS group remained significantly lower than that of the HC group (all P < 0.001), whereas no statistically significant difference was observed between the RIS group and the HC group. ConclusionsIschemic stroke patients with different lesion sides exhibit statistically significant differences in DC and FC. Furthermore, acupuncture modulation may exert hemisphere-specific functional lateralization effects. ]]> Sun,20 Sep 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.09.015 ObjectiveTo investigate the predictive value of plaque features combined with the integrity of the circle of Willis for recurrent stroke and the correlation between the integrity of the circle of Willis and plaque features. Materials and MethodsA total of 85 patients with symptomatic intracranial atherosclerotic stenosis were enrolled retrospectively. All patients underwent high-resolution magnetic resonance vessel wall imaging within 14 days after symptom onset, and were divided into an initial stroke group and a recurrent stroke group according to clinical and imaging data. The two groups were compared in terms of the integrity of the circle of Willis, characteristics of intracranial responsible plaques, plaque number, and plaque coexistence. Multivariate logistic regression analysis was performed to identify independent imaging markers correlated with recurrent stroke history. Binary logistic regression analysis was adopted to assess the correlation between the integrity of the circle of Willis and the characteristics of intracranial vulnerable plaques. ResultsCompared with the initial stroke group, the recurrent stroke group had a higher degree of responsible vessel stenosis (t = -2.367, P = 0.020), a larger total number of plaques (Z = -4.401, P = 0.001), and higher incidence rates of irregular plaque surface (χ² = 6.953, P = 0.008), incomplete symptomatic posterior circle of Willis (χ² = 11.318, P = 0.001) and plaque coexistence (χ² = 7.063, P = 0.008); multivariate logistic regression analysis showed that the total number of plaques (OR = 2.101, 95% CI: 1.109 to 3.976, P = 0.023) and incomplete symptomatic posterior circle of Willis (OR = 2.984, 95% CI: 1.021 to 9.041, P = 0.045) were independently associated with history of recurrent ischemic stroke. The combined logistic regression model exhibited the optimal predictive performance. Its area under the curve (AUC) was significantly higher than that of the single predictor of incomplete symptomatic posterior segment of the circle of Willis, while no statistically significant difference in predictive efficacy was observed between the combined model and the single predictor of total plaque number. Univariate logistic regression analysis showed that incomplete anterior circle of Willis was independently correlated with irregular plaque surface (OR = 6.522, 95% CI: 2.381 to 17.836, P = 0.001), and incomplete symptomatic posterior circle of Willis was also independently correlated with irregular plaque surface (OR = 3.373, 95% CI: 1.266 to 8.942, P = 0.015). After adjusting for age, gender and clinical risk factors including smoking history, drinking history, hyperlipidemia, hypertension and diabetes, multivariate logistic regression analysis further revealed that incomplete anterior circle of Willis was independently associated with irregular plaque surface (OR = 6.741, 95% CI: 2.390 to 19.023, P = 0.001), and incomplete symptomatic posterior circle of Willis remained independently correlated with irregular plaque surface (OR = 3.420, 95% CI: 1.249 to 9.355, P = 0.017). ConclusionsIncreased plaque number and ipsilateral posterior circulation defects of the circle of Willis were more common in patients with anterior circulation ischemic stroke and a history of recurrent stroke. Both incomplete anterior circle of Willis and incomplete symptomatic posterior circle of Willis are independently correlated with irregular plaque surface. Integrated cranio-cervical high-resolution magnetic resonance vessel wall imaging allows direct visualization and comparison of plaque features and anatomical configurations of the circle of Willis between patients with first-ever and recurrent stroke, and provides imaging evidence for stroke risk stratification. ]]> Sun,20 Sep 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.09.016 ObjectiveTo evaluate the diagnostic performance of a combined model based on perfusion parameters derived from three-dimensional arterial spin labeling (3D-ASL) and time-dependent diffusion MRI (TDD-MRI) for differentiating true progression (TP) from pseudoprogression (PsP) in postoperative glioma patients with suspected progression after radiotherapy. Materials and MethodsThis study was registered at ClinicalTrials.gov under the registration number NCT07687277. Seventy-five postoperative glioma patients with suspected progression during follow-up at Lanzhou University Second Hospital from March 2024 to February 2025 were prospectively enrolled. Final classification was based on the Response Assessment in Neuro-Oncology 2.0 (RANO 2.0) criteria, repeat surgery or biopsy pathology when available, and serial clinical-imaging follow-up findings. Patients were ultimately classified into the TP group (n = 45) and the PsP group (n = 30). All patients underwent conventional MRI, 3D-ASL and TDD-MRI examinations. The contrast-enhancing solid region on contrast-enhanced T1-weighted imaging was delineated as the volume of interest (VOI). Perfusion parameters, including the mean, maximum and minimum relative cerebral blood flow (rCBF_mean, rCBF_max and rCBF_min), and microstructural parameters, including the apparent diffusion coefficient at 20 Hz (ADC_{20 Hz}), the apparent diffusion coefficient at 40 Hz (ADC_{40 Hz}), Cellularity, and Diameter, were extracted. Interobserver agreement was assessed using intra-class correlation coefficient (ICC). Group differences were compared using the independent-samples t test or Mann-Whitney U test. Univariable logistic regression, least absolute shrinkage and selection operator (LASSO) regression, and enter-method multivariable logistic regression were performed to identify imaging parameters associated with TP/PsP differentiation and establish a combined model. Receiver operating characteristic (ROC) curve analysis was used to evaluate diagnostic performance. ResultsAll parameters showed good interobserver agreement, with ICCs greater than 0.75. rCBF_mean, rCBF_max, rCBF_min, and Cellularity were higher in the TP group than in the PsP group, whereas ADC_{20 Hz} and ADC_{40 Hz} were lower in the TP group. The corresponding group-comparison Z values were 2.926, 3.412, 2.190, 4.451, 4.973, and 4.938, respectively, and all differences were significant (all P < 0.05). Diameter showed no significant difference between the two groups (Z = 0.990, P = 0.322). LASSO regression selected rCBF_max, ADC_{20 Hz}, ADC_{40 Hz}, and Cellularity to construct the combined model. Enter-method multivariable logistic regression showed that rCBF_max (OR = 1.061, 95% CI: 1.001 to 1.126, P = 0.048) and ADC_{40 Hz} (OR = 0.668, 95% CI: 0.473 to 0.942, P = 0.021) were independent factors for differentiating TP from PsP. ROC analysis showed that the combined model had the numerically highest area under the curve (AUC) of 0.890 (95% CI: 0.797 to 0.951), with a sensitivity of 73.33% and a specificity of 93.33%. Among single parameters, ADC_{40 Hz} showed the highest AUC of 0.839 (95% CI: 0.735 to 0.913). The DeLong test showed that the AUC of the combined model was significantly higher than those of rCBF_max and Cellularity (all P < 0.05), whereas its AUC was not significantly different from those of ADC_{20 Hz} or ADC_{40 Hz} (all P > 0.05). ConclusionsThe multiparametric model combining 3D-ASL and TDD-MRI showed diagnostic performance for differentiating TP from PsP. In glioma patients with suspected progression after postoperative radiotherapy, this model may provide adjunctive information for differential diagnosis and imaging support for comprehensive clinical assessment. ]]> Sun,20 Sep 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.09.017 ObjectiveTo investigate the diagnostic value of high-resolution T2-weighted imaging (HR-T2WI) fused with field-of-view optimized and constrained undistorted single-shot diffusion-weighted imaging (Focus-DWI) in the preoperative T staging of rectal cancer. Materials and MethodsThis retrospective diagnostic accuracy study included MRI data of 99 patients with rectal cancer who were admitted to the Sixth Affiliated Hospital of Sun Yat-sen University from July 2022 to January 2024. The imaging data included axial HR‑T2WI, Focus‑DWI, and their fused images (T2WI-Fusion). With postoperative pathological findings as the gold standard, four radiologists (two senior and two junior) independently evaluated the preoperative T staging based on HR‑T2WI and T2WI‑Fusion, respectively. Weighted Kappa statistics were used to assess agreement with pathological results. Diagnostic sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were then calculated. Receiver operating characteristic (ROC) curves were plotted to obtain the area under the curve (AUC), and the DeLong test was employed to compare the differences in AUC between the two sequences. ResultsThe postoperative pathological T staging results for the 99 patients were as follows: 49 cases of ≤ T2 stage, 35 cases of T3 stage, and 15 cases of T4 stage. When using HR‑T2WI alone, the AUCs of the four radiologists for diagnosing ≤ T2, T3, and T4 stages were 0.765 to 0.847, 0.628 to 0.710, and 0.717 to 0.840, respectively, with Kappa values ranging from 0.611 to 0.751. Senior radiologists showed better diagnostic agreement (0.676 to 0.751) than junior radiologists (0.611 to 0.616). After applying T2WI‑Fusion, the AUCs for each T stage increased to 0.858 to 0.949, 0.769 to 0.890, and 0.864 to 0.970, respectively, and the Kappa values increased to 0.784 to 0.910. The DeLong test showed that the differences in AUC between the two sequences were statistically significant (all P < 0.05). Diagnostic consistency improved significantly for both senior and junior radiologists, with junior radiologists experiencing a more marked enhancement in both diagnostic performance and consistency. ConclusionsThe fused T2WI-Fusion images combining HR-T2WI and Focus-DWI can significantly improve the accuracy of preoperative T staging for rectal cancer and have high clinical application value. ]]> Sun,20 Sep 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.09.018 ObjectiveTo prospectively investigate the preoperative predictive value of intratumoral and peritumoral magnetic resonance image compilation (MAGiC) combined with multiplexed sensitivity-encoding diffusion-weighted imaging (MUSE-DWI) for neurovascular invasion (NVI) in rectal cancer. Materials and MethodsSeventy patients with rectal cancer were prospectively enrolled. All patients underwent preoperative MAGiC and MUSE-DWI sequences, and intratumoral (solid tumor component) and peritumoral mesorectal quantitative parameters were measured, including longitudinal relaxation time (T1), transverse relaxation time (T2), proton density (PD), and apparent diffusion coefficient (ADC). Using postoperative pathological results as the gold standard, patients with either perineural invasion (PNI) or lymphovascular invasion (LVI) were assigned to the NVI-positive group (n = 31), and those with neither were assigned to the NVI-negative group (n = 39). Univariate analysis was used to compare clinical data, MAGiC-derived quantitative parameters, and ADC values between the two groups. Parameters that differed significantly were entered into binary logistic regression to identify independent predictors of NVI and to develop a combined diagnostic model. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of individual parameters and the combined model. Calibration curves and decision curve analysis (DCA) were used to assess the calibration and clinical utility of the combined model. ResultsUnivariate analysis showed that intratumoral T1 (T1_intra), intratumoral T2 (T2_intra), peritumoral PD (PD_peri), and intratumoral ADC (ADC_intra) were significantly lower in the NVI-positive group than in the NVI-negative group (all P < 0.05), while peritumoral T1 (T1_peri) and peritumoral ADC (ADC_peri) were significantly higher (all P < 0.05). T1_peri, T2_intra, and PD_peri were independent predictors of rectal cancer NVI (PNI and/or LVI). The combination of these three parameters yielded the highest area under the ROC curve (AUC) of 0.906 [95% confidence interval (CI): 0.812 to 0.963] for diagnosing NVI, which was higher than the intratumoral parameter combination (T1_intra + T2_intra + ADC_intra) and the peritumoral parameter combination (T1_peri + PD_peri + ADC_peri), with AUC (95% CI) of 0.868 (0.765 to 0.937) and 0.829 (0.720 to 0.908), respectively. DeLong test showed no statistically significant differences between the combined model and the intratumoral or peritumoral models (Z = 1.497 and 1.221, P = 0.134 and 0.222, respectively). The calibration curve and DCA demonstrated good calibration and clinical utility of the combined model. The AUC of the peritumoral parameter combination was slightly higher than that of the intratumoral combination, but the difference was also not statistically significant (Z = 0.562, P = 0.574). Subgroup analysis showed that the combined model predicted LVI (25 positive cases) and PNI (19 positive cases) with AUC (95% CI) of 0.891 (0.793 to 0.953) and 0.827 (0.717 to 0.907), respectively. ConclusionsMAGiC combined with MUSE-DWI quantitative parameters enables effective preoperative assessment of NVI in rectal cancer. The combination of independent intratumoral and peritumoral predictors provides good diagnostic performance and offers objective quantitative imaging evidence for preoperative risk stratification and individualized treatment decision-making. ]]> Sun,20 Sep 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.09.019 ObjectiveTo evaluate energy metabolism impairment in the gastrocnemius (GM) and soleus (SOL) muscles of the calf in patients with lower-extremity peripheral artery disease (PAD) and healthy volunteers using phosphorus-31 magnetic resonance spectroscopy (³¹P-MRS). Materials and MethodsThis prospective study enrolled 15 PAD patients (patient group) and 16 age-, sex-, and BMI-matched healthy volunteers (control group) who met the inclusion and exclusion criteria. All subjects underwent resting-state ³¹P-MRS multi-voxel scanning of the posterior calf muscles on the left side using a 3.0 T MR scanner with a ³¹P surface coil. Two observers independently selected GM and SOL voxels for post-processing analysis using JMRUI software, obtaining the peak area under the curve for metabolites including phosphocreatine (PCr), adenosine triphosphate (ATP) (with the total area under the three ATP peaks recorded as tATP), phosphodiesters (PDE), and inorganic phosphate (Pi). Metabolite ratios were subsequently calculated, including Pi/tATP, PCr/tATP, Pi/PCr, and PDE/PCr. Statistical analyses were performed using GraphPad Prism 10.1.2 and MedCalc 15.2.2. Inter-observer agreement was assessed using the intra-class correlation coefficient (ICC). Within-group differences in metabolic parameters between GM and SOL were compared using paired t-tests for normally distributed data and the Wilcoxon signed-rank test for non-normally distributed data. Between-group differences in GM and SOL metabolic parameters were assessed using independent t-tests or Mann-Whitney U tests, as appropriate, with Cohen^,s d effect sizes calculated to evaluate the sensitivity of each metabolic indicator in discriminating PAD. Receiver operating characteristic (ROC) curves and the corresponding area under the curve (AUC) were computed to further quantify diagnostic performance, with sensitivity and specificity derived via the Youden index. Differences between AUCs were compared using the DeLong test, and McNemar test was used to compare sensitivity and specificity across metabolic indicators. ResultsInter-observer agreement was good for all metabolic parameters in both groups (all ICC > 0.80). No significant within-group differences in metabolic parameters between GM and SOL were observed in either group (all P > 0.05). Compared with the control group, the patient group demonstrated significantly elevated GM Pi/tATP (0.223 ± 0.050 vs. 0.170 ± 0.066, P = 0.007), Pi/PCr (0.154 ± 0.036 vs. 0.105 ± 0.036, P = 0.002), and PDE/PCr (0.158 ± 0.056 vs. 0.076 ± 0.028, P < 0.001). Similarly, SOL Pi/tATP (0.223 ± 0.051 vs. 0.161 ± 0.045, P = 0.004), Pi/PCr (0.147 ± 0.037 vs. 0.105 ± 0.026, P = 0.005), and PDE/PCr (0.143 ± 0.040 vs. 0.073 ± 0.025, P < 0.001) were all significantly elevated, with SOL PDE/PCr showing the largest Cohen^,s d effect size among all between-group comparisons (d = 2.1). ROC curve analysis showed that PDE/PCr in both GM and SOL (AUC = 0.896 and 0.942, respectively) achieved better diagnostic performance than the other metabolic indices. DeLong test showed that the AUC difference between SOL Pi/PCr and PDE/PCr was statistically significant (P = 0.044), while differences among all other pairs of metabolic indices were not significant (all P > 0.05). McNemar test showed that, for sensitivity, SOL PDE/PCr (93.3%) was significantly higher than SOL Pi/PCr (53.3%, P = 0.031) but did not differ significantly from SOL Pi/tATP (86.7%, P > 0.05). No significant differences in sensitivity were found between GM PDE/PCr (80.0%) and GM Pi/tATP (100.0%) or Pi/PCr (86.7%, all P > 0.05). For specificity, GM PDE/PCr (87.5%) was significantly higher than GM Pi/tATP (50.0%, P = 0.031) but did not differ significantly from GM Pi/PCr (68.8%, P > 0.05); no significant differences in specificity were found among the SOL metabolic indices (all P > 0.05). ConclusionsThis study preliminarily demonstrates that ³¹P-MRS has the potential to assess changes in skeletal muscle energy metabolism in patients with PAD, and the increase in PDE/PCr ratio in SOL can serve as a potentially sensitive indicator for evaluating energy metabolism disorders in PAD. ]]> Sun,20 Sep 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.09.020 ObjectiveTo investigate the role of an inflammation-targeted MRI molecular probe in visualizing neuroinflammation and providing targeted therapy in ischemic stroke. Materials and MethodsThe inflammation-targeted probe (MA@Z-UMino) was prepared by co-incubating macrophages with Zeolitic Imidazolate Framework-8 (ZIF-8) loaded with minocycline and ultrasmall superparamagnetic iron oxide (USPIO), followed by characterization. A left middle cerebral artery occlusion/reperfusion (MCAO/R) mouse model was established. A total of 100 male C57BL/6 mice aged 8 to 9 weeks were assigned to the normal control group (n=10), Sham group (n=10), and MCAO/R group (n=80). Sixty MCAO/R mice were randomly divided into the MCAO/R, ZIF-8-loaded USPIO (Z-U), minocycline (Mino), macrophage (MA), ZIF-8-loaded USPIO and minocycline (Z-UMino), and MA@Z-UMino groups (n=10 per group). These groups, together with the normal control group and Sham group, were used for therapeutic efficacy evaluation, including 2, 3, 5-triphenyltetrazolium chloride (TTC) staining, inflammatory cytokine analysis, and behavioral and histopathological assessments in selected representative groups. The remaining 20 MCAO/R mice were randomly divided into the Z-UMino and MA@Z-UMino groups (n=10 per group) for in vivo magnetic resonance imaging (MRI). MRI was performed before and at 0.5, 1, and 2 h after injection. The signal-to-noise ratio (SNR) of the brain tissue on the lesion side and its percentage decrease were calculated. Brain specimens were further analyzed pathologically. ResultsMA@Z-UMino exhibited a predominantly anti-inflammatory phenotype. The transverse relaxation rate of MA@Z-UMino was 17.08 mM^-1s^-1, indicating its effectiveness for T2-weighted imaging. In vivo MRI showed that the SNR reduction rate of lesion-side brain tissue decreased more obviously in the MA@Z-UMino group than that in the Z-UMino group at 2 h post-treatment (2 h, 31.24 ± 9.30 vs. 15.88 ± 6.79, P < 0.001). Prussian blue staining and immunofluorescence confirmed probe accumulation in the infarct region. Compared with the MCAO/R group, the MA@Z-UMino group showed a significantly smaller infarct area (36.42 ± 5.49 vs. 15.72 ± 4.78, P < 0.001), reduced inflammation, and improved motor function. ConclusionsMA@Z-UMino enables targeted recognition of the inflammatory microenvironment in ischemic stroke, MRI-based visualization, and neuroprotective therapy in mice with MCAO/R. ]]> Sun,20 Sep 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.09.021 ObjectiveTo compare pulmonary solid nodule diameter measurements and image quality obtained using ultrashort echo time (UTE) sequences on 0.55 T and 1.5 T MRI systems during different respiratory phases and to assess the feasibility of 0.55 T UTE sequences for measuring pulmonary solid nodule diameter and evaluating image quality. Materials and MethodsTwenty-six patients with pulmonary solid nodules detected on chest CT who underwent inspiratory and expiratory phase 3D-UTE scans on both 0.55 T and 1.5 T MRI systems were prospectively enrolled, and a total of 84 pulmonary solid nodules were detected on CT. Seventeen pulmonary solid nodules that could not be completely visualized on all four 3D-UTE image sets were excluded, and six patients were excluded because they had no eligible pulmonary solid nodules; 67 pulmonary solid nodules in 20 patients were ultimately included in the quantitative analysis. Two radiologists independently measured the maximum diameter of each pulmonary solid nodule on CT and each MRI image set and performed subjective (5-point Likert scale) and objective assessments; the latter included the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of the nodules. Interobserver agreement for subjective scores was evaluated using a weighted kappa test; intraclass correlation coefficients (ICCs) and Bland-Altman analyses were used to assess both interobserver agreement and the agreement between CT and each MRI acquisition. Multiple related samples were compared using the Friedman two-way analysis of variance by ranks, with Dunn^,s correction for pairwise comparisons. ResultsOf the 84 pulmonary solid nodules detected on CT, 67 (79.8%) were fully visualized on all four 3D-UTE image sets; the visualization rate was 91.2% (62/68) for pulmonary solid nodules ≥6 mm and only 31.3% (5/16) for those <6 mm in diameter. Interobserver agreement was excellent for all parameters (diameter ICCs, 0.980 to 0.985). The CT reference diameter was 10.5 (6.9, 17.0) mm, and the pulmonary solid nodule diameters measured on 0.55 T inspiratory, 0.55 T expiratory, 1.5 T inspiratory, and 1.5 T expiratory UTE images were 10.6 (6.4, 16.5) mm, 10.8 (6.5, 17.0) mm, 10.2 (6.5, 16.6) mm, and 9.7 (6.5, 16.9) mm, respectively, with no statistically significant overall difference among the five groups (χ²=6.105, P=0.191); the ICCs between CT and each MRI acquisition ranged from 0.986 to 0.991, with mean biases ranging from -0.50 to 0.32 mm and no systematic bias. The overall distribution of subjective scores differed significantly among the four MRI image groups (χ² = 15.16, P = 0.002), whereas no significant pairwise difference was observed after Dunn^,s correction (all P > 0.05). The overall distributions of SNR and CNR both differed significantly among the four groups (χ²=80.50 and 92.82, respectively; both P < 0.001); during both the inspiratory and expiratory phases, SNR and CNR were significantly higher at 1.5 T than at 0.55 T (all P < 0.001), whereas neither metric differed significantly between the inspiratory and expiratory phases at the same field strength. ConclusionsFor pulmonary solid nodules that can be clearly visualized on 3D-UTE images, the mean diameter measurements obtained with 0.55 T and 1.5 T UTE sequences during different respiratory phases were comparable to the CT reference values. However, the limits of agreement at the individual nodule level were relatively wide, and the measurement differences for some pulmonary solid nodules may exceed clinically acceptable ranges. For pulmonary solid nodules ≥6 mm that are detectable on UTE sequences, 0.55 T 3D-UTE may serve as a radiation-free adjunct to CT for nodule diameter assessment; however, it cannot yet replace CT for initial screening for pulmonary solid nodules or follow-up evaluation of all pulmonary solid nodules. ]]> Sun,20 Sep 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.09.023 ^,s disease, and secondary cognitive impairment; however, its underlying mechanisms have not yet been fully elucidated. Resting-state functional magnetic resonance imaging (rs-fMRI), which requires no externally imposed task stimulation, can objectively reflect spontaneous neural activity and therefore serves as a non-invasive imaging tool for investigating central mechanisms. Various rs-fMRI analytical methods, including amplitude of low-frequency fluctuation, regional homogeneity, and functional connectivity (FC), can reveal how acupuncture at GV24 may modulate local functional activity in specific brain regions and alters connectivity within and between brain networks. This review summarizes recent rs-fMRI studies on acupuncture at GV24 for the treatment of cognitive impairment (CI) and identifies associated functional changes in specific brain regions and networks, including the hippocampus, prefrontal cortex, cingulate gyrus, default mode network, frontoparietal network, and limbic system. Current evidence suggests that acupuncture may exert integrative regulatory and remodeling effects on brain functional states by enhancing FC between the default mode network, frontoparietal network, and limbic system. The authors also note several limitations in existing studies, including small sample sizes, substantial heterogeneity in intervention protocols, and insufficient mechanistic interpretation. Future research should therefore expand sample size, promote multicenter collaboration, standardize acupuncture-fMRI research protocols, and conduct longitudinal follow-up studies. This review aims to provide new perspectives on the central mechanisms underlying acupuncture treatment for CI and to clarify potential directions for optimizing clinical diagnosis and treatment. ]]> Sun,20 Sep 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.09.024 ^, quality of life. Acupuncture, as a non-pharmacological therapy, has demonstrated definite efficacy in improving ischemic PSCI, and its mechanisms involve inhibiting neuronal apoptosis, enhancing synaptic plasticity, anti-neuroinflammation, and regulating cerebral energy metabolism. MRI studies on acupuncture treatment for ischemic PSCI primarily utilize multiple imaging modalities such as diffusion tensor imaging, quantitative susceptibility mapping, resting-state functional MRI, and magnetic resonance spectroscopy. These modalities respectively reveal that acupuncture can repair white matter microstructural damage, reduce excessive cerebral iron deposition, modulate cognitive-related brain network functional connectivity, and optimize cerebral metabolite levels. This review aims to systematically summarize relevant literature, integrate data from the aforementioned multiple MRI sequences, elucidate the central effects of acupuncture in treating ischemic PSCI, point out limitations of existing studies, and propose directions for future research, thereby providing imaging evidence for individualized clinical diagnosis and treatment evaluation. ]]> Sun,20 Sep 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.09.025 ^,s current state, this paper first employs literature statistics and visual analytic approaches to delineate the global research landscape. On this basis, this review summarizes the research status of various ML models (conventional algorithms, deep learning and ensemble learning) based on non-contrast CT, CTA, CTP and multiple MRI sequences for AIS prognosis prediction. This paper also identifies the current limitations of existing research in areas such as data heterogeneity, external validation, image standardization, model interpretability, and clinical translation; it further suggests that future efforts should focus on strengthening multicenter prospective validation studies, standardizing image data processing workflows, and enhancing model interpretability and clinical relevance to facilitate the application of these approaches in the personalized prognostic assessment of AIS. ]]> Sun,20 Sep 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.09.026 Sun,20 Sep 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.09.027 Sun,20 Sep 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.09.028 Sun,20 Sep 2026 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2026.09.029 ^, overall nutritional status, inflammatory response, and immune function, and has gradually become an important tool in the management of cancer patients. Through interdisciplinary collaboration, the combination of nutrition, sports medicine, and oncology provides patients with more precise and personalized treatment plans. With the development of AI technology, deep learning algorithms can automatically identify, segment, and quantify muscle and adipose tissue, improving the efficiency and accuracy of BCA and enhancing its feasibility for clinical application. However, the field still faces challenges such as inconsistent measurement standards, insufficient prospective validation, poor generalization ability of AI models, and difficulties in clinical integration. Therefore, this article reviews the progress of BCA imaging technology and its applications in metabolic syndrome, tumors, acute inflammation, geriatrics, chronic disease risk assessment, treatment response and tolerability, and prognostic prediction. It systematically analyzes the limitations of current research and proposes future directions such as establishing a standardized system, conducting multi-center prospective studies, promoting the clinical application of interpretable AI, and integrating multi-omics data, aiming to provide a reference for the clinical translation and standardized application of BCA. ]]> Sun,20 Sep 2026 00:00:00 GMT