High-density areas (HDAs) are frequently observed in follow-up CT of large-vessel occlusions after endovascular therapy. Utilizing the established ASPECTS regions, incorporating the subarachnoid space and ventricles, we developed a novel HDA score to evaluate its correlation and predictive value for hemorrhagic transformations and clinical outcomes. This retrospective, multicenter study included consecutive patients who had HDA on follow-up CT after endovascular therapy. Multivariable logistic regression and area under the receiver operating characteristic curve (AUC) analyses assessed the associations and predictive value of HDA location and score with hemorrhagic transformations and unfavorable clinical outcomes. Among the 1130 consecutive patients treated with endovascular therapy, 542 patients (326 males; median age 70 years) had HDA were finally included. Multivariable logistic regression showed that HDA location in the lentiform nucleus (OR, 1.6; 95

Sudden sensorineural hearing loss (SSNHL) is considered a potential risk factor for cognitive and emotional disorders. Numerous studies have highlighted the function of glymphatic system associated with cognition and emotion, but the underlying neural mechanisms linking SSNHL and cognitive-emotional impairments remain unclear. To further investigate, a total of 60 patients with SSNHL and 60 healthy volunteers were recruited for this study. We calculated volumes of the choroid plexus (ChP), enlarged perivascular spaces (EPVS) and four brain ventricles, including the bilateral lateral ventricles, the third ventricle, and the fourth ventricle, using convolutional neural network model and Freesurfer automatic segmentation tool. The volumes of the ChP and EPVS were used to assess the function of glymphatic system. Subsequently, volumetric differences between groups and the relationship between the volumes of the ChP, EPVS and four brain ventricles were analyzed. Moreover, we explored the correlation between MRI characteristics and neuropsychological scale scores in SSNHL patients. Compared with healthy volunteers, SSNHL patients presented larger ChP and EPVS volumes. In addition, the ChP volume showed a significant correlation with the severity of cognitive and emotional deficits in patients with SSNHL. Taken together, our results suggest alterations in MRI markers associated with glymphatic function in SSNHL patients. Differences in the ChP and EPVS volumes among the groups, with the enlarged ChP volume associated with cognitive and emotional disorders in patients, suggest that volumetric alterations in the ChP and EPVS may serve as characteristic measures in SSNHL.

OBJECTIVE:To develop and externally validate a spatial radiomics nomogram integrating infarct location, lesion radiomics, and clinical predictors for individualized prediction of 90-day unfavorable outcomes in patients with acute ischemic stroke (AIS). MATERIALS AND METHODS:This multicenter retrospective study included 3,502 patients in the training cohort and 421 in the external validation cohort. Unfavorable outcome was defined as a 90-day modified Rankin Scale score of 3-6. Radiomics features were extracted using PyRadiomics, and location features were quantified by mapping infarct masks to a 425-parcellation brain atlas. Six machine learning algorithms were compared for radiomics-based and location-based models. SHapley Additive exPlanations (SHAP) analysis was used to interpret the optimal location-based model. A nomogram integrating Radscore, Locscore, and independent clinical predictors was developed. RESULTS:The optimal location-based model outperformed the optimal radiomics-based model, with area under the receiver operating characteristic curve (AUC) values of 0.793 and 0.767, respectively (p < 0.01). SHAP analysis identified the superior corona radiata, superior longitudinal fasciculus, internal capsule, and precentral gyrus as the most influential regions. The final nomogram incorporated Radscore, Locscore, age, sex, admission National Institutes of Health Stroke Scale score, Trial of ORG 10172 in Acute Stroke Treatment classification, blood glucose level, and infarct volume on DWI. It achieved AUCs of 0.894 and 0.874 in the training and external validation cohorts, with good calibration and clinical utility. CONCLUSION:Infarct location provides incremental prognostic information beyond radiomics. The proposed spatial radiomics nomogram may facilitate early individualized risk stratification in AIS.

Malignant cerebral edema (MCE) is a life-threatening complication after endovascular therapy (EVT) for acute ischemic stroke (AIS). In this multicenter study, we observed a specific gyral hyperdensity sign (GHS) and sought to investigate its association with MCE, analyzing the underlying factors correlated with GHS. Consecutive anterior circulation AIS patients exhibiting post-EVT hyperdensities on 24-h follow-up computed tomography were included. GHS was defined as curvilinear hyperdensities distributed along ⩾2 adjacent cerebral gyri. A total of 542 patients were enrolled. GHS was identified in 142 patients with excellent interobserver agreement (κ = 0.804). We found that GHS (OR = 1.83, 95% CI = 1.13-2.95, P = 0.014) was independently associated with MCE. Furthermore, baseline NIHSS score (OR = 1.05, 95% CI = 1.02-1.09, P = 0.003), blood glucose (OR = 1.15, 95% CI = 1.05-1.25, P = 0.002), infarct ASPECTS (OR = 0.91, 95% CI = 0.83-0.99, P = 0.024), creatinine level (OR = 3.47, 95% CI = 1.71-7.02, P < 0.001), and intracranial internal carotid artery occlusion (OR = 1.66, 95% CI = 1.09-2.55, P = 0.020) were independently correlated with GHS. These results revealed that GHS can be reliably identified and can serve as an early warning indicator for MCE.

BackgroundChemotherapy-related cognitive impairment (CRCI) is a common adverse effect among lung cancer patients undergoing chemotherapy. Glymphatic system dysfunction has been implicated in the pathogenesis of cognitive deficits. This study aimed to investigate the impact of chemotherapy on the glymphatic system in patients with non-small cell lung cancer (NSCLC) and its association with cognitive outcomes. Methods A total of 102 NSCLC patients (53 patients without chemotherapy (CT(-)), 49 patients with chemotherapy (CT(+))) and 56 healthy controls (HCs) were enrolled. Their glymphatic system function was evaluated using the diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index and choroid plexus (CP) volume, derived from DTI and three-dimensional T1-weighted magnetic resonance imaging (3D-T1 MRI), and examined for group differences and associations with neuropsychological outcomes. Results The MoCA scores of NSCLC survivors decreased significantly after chemotherapy. There were significant differences in the DTI-ALPS index and CP volume among the three groups (P < 0.05, one-way ANOVA). Post hoc analyses (Bonferroni-corrected) demonstrated that the CT(+) group exhibited significantly reduced DTI-ALPS indices and enlarged CP volumes compared to both the CT(–) group and the HCs group (P <0.05). DTI-ALPS indexes were positively correlated with MoCA scores (r = 0.448, P= 0.001), and CP volumes were negatively correlated with cognitive performance (r= -0.435, P = 0.002). Mediation analysis indicated that DTI-ALPS indexes partially mediated the relationship between CP volumes and MoCA scores (mediated effect = 32.79%). ConclusionThis research provides new insights into the pathological mechanism of CRCI in patients with NSCLC. These results suggest that glymphatic system-derived metrics (DTI-ALPS indices and CP volume) might act as potential biomarkers for assessing CRCI and tracking neurocognitive changes in NSCLC patients receiving chemotherapy.

BACKGROUND:Accurate assessment of 90-day functional outcomes after anterior circulation large vessel occlusion (LVO) stroke remains challenging. Conventional models relying on a single data dimension have limited assessment power, suggesting that a multidimensional integration strategy could enhance evaluations. PURPOSE:To develop and validate an interpretable machine learning model that integrates radiomics, infarct location, brain frailty, and clinical variables for assessing 90-day functional outcomes in LVO stroke. STUDY TYPE:Retrospective. POPULATION:1051 patients with anterior circulation LVO stroke (mean age 63 ± 13 years; 722 males) from five centers (2018-2023). Eight hundred and seventy-five patients from four centers formed the training (n = 612) and internal validation (n = 263) cohorts, while 176 from the fifth center comprised the external validation cohort. FIELD STRENGTH/SEQUENCE:T1-weighted spin-echo imaging (T1WI), T2-weighted spin-echo imaging (T2WI), T2-weighted fluid-attenuated inversion recovery (FLAIR) imaging, and diffusion-weighted echo-planar imaging (DWI). ASSESSMENT:Infarct volume and radiomic features were extracted from DWI. Infarct location was assessed using the Alberta Stroke Program Early CT Score. Brain frailty was evaluated using cortical/subcortical atrophy, white matter hyperintensity (WMH), and old infarcts. Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for feature selection. STATISTICAL TESTS:Chi-square, Fisher's exact, t-test, Mann-Whitney U, area under the receiver operating characteristic curve (AUC), DeLong test, decision curve analysis, calibration curves, sensitivity, specificity, positive predictive value, negative predictive value, F1 score. Significance level p < 0.05. RESULTS:The fused model outperformed all single-dimension models (ΔAUC = 0.12-0.22), achieving AUCs of 0.87 (training), 0.84 (internal validation), and 0.86 (external validation). The fused model achieved a sensitivity and a specificity of 0.80 in the external validation cohort. Features with the highest mean absolute Shapley Additive Explanations (SHAP) values included lentiform nucleus lesion burden (SHAP = 0.083), WMH (SHAP = 0.080), and lesion burden in the M6 region (posterior middle cerebral artery territory; SHAP = 0.061). DATA CONCLUSION:Integration of infarct location, brain frailty, radiomics, and clinical features improved the 90-day outcome assessment in anterior circulation LVO stroke, providing an interpretable tool for personalized prognosis. LEVEL OF EVIDENCE: 3: TECHNICAL EFFICACY STAGE:2.

PURPOSE:Malignant cerebral edema (MCE) is a life-threatening complication following reperfusion therapy for anterior circulation large vessel occlusion stroke. This study evaluate the association between individual Alberta Stroke Program Early CT Score (ASPECTS) territories and MCE development and to quantify the synergistic risk amplification when a key territory co-occurs with ASPECTS, the National Institutes of Health Stroke Scale (NIHSS) score, and onset-to-CT time. METHODS:This multicenter retrospective study of 523 patients used multivariable logistic regression to identify independent MCE predictors. Generalized linear models and stratified analyses evaluated synergistic effects. RESULTS:MCE occurred in 22.2 % of the cohort. Insular infarction (odds ratio [OR] = 2.93; 95 % confidence interval [CI], 1.51-5.70), higher NIHSS (per point OR = 1.11; 95 % CI, 1.07-1.16), and elevated blood glucose (per mmol/L OR = 1.13; 95 % CI, 1.05-1.22) were factors independently associated with MCE. A critical synergistic effect was observed: coexisting insular infarction and ASPECTS < 6 yielded the highest risk, with 46 % of patients developing MCE (risk ratio [RR] = 4.41; 95 % CI, 2.94-7.42). Insular infarction also amplified MCE risk in patients presenting within 4.5 hours of stroke onset (RR = 5.43; 95 % CI, 3.21-12.43; interaction P = 0.006) and in those with NIHSS scores > 14 (RR = 12.89; 95 % CI, 5.85-58.86). Trend tests confirmed a dose-dependent risk escalation (P < 0.01). CONCLUSION:Insular infarction is a potent risk multiplier, synergistically amplifying MCE risk when combined with extensive early ischemia (ASPECTS < 6) or severe deficits (NIHSS score > 14), particularly during the hyperacute phase.

This study investigated time-dependent group-level changes in chemical exchange saturation transfer (CEST) signals in a mouse model and explored utility in identifying stroke onset time. Multiparametric magnetic resonance imaging (diffusion weighted imaging, arterial spin labeling, and CEST) was conducted on 12 normal and 26 ischemic mice. Imaging findings were validated by immunohistochemical analysis. CEST parameters in infarct and penumbra were compared between strokes within 4.5 h and over 4.5 h. Correlations, regression, and receiver operating characteristic curves evaluated performance. Infarct guanidine, magnetization transfer (MT), nuclear Overhauser enhancement (NOE) (-3.5 ppm), and NOE (-1.6 ppm) significantly differed between groups and associated with onset time (P < .01). MT, NOE (-3.5 ppm), NOE (-1.6 ppm) showed significant associations with onset time in univariate logistic regression (P < .05). The NOE (-3.5 ppm) achieved an area under the curve of 0.848 (95% CI: 0.655-1.000), outperforming apparent diffusion coefficient (z = -2.397, P = .017) and cerebral blood flow (z = -2.271, P = .0271). NOE (-3.5 ppm) signals and lipid peroxidation both declined progressively with ischemic duration. These findings indicate that NOE (-3.5 ppm) signal attenuation parallels lipid peroxidation and may indicate progressive membrane lipid loss in ischemia.

The artificial intelligence-assisted ASPECTS (AI-ASPECTS) system has become an increasingly common tool in clinical practice for assessing acute ischemic stroke (AIS). However, current AI-ASPECTS implementations still rely on the conventional expert-evaluation framework, which uses a simplified two-slice atlas and arbitrarily selected lesion-load thresholds. Our study aimed to develop a refined AI-assisted ASPECTS (Ref-AI-ASPECTS) framework featuring a seamless whole middle cerebral artery (MCA) territory atlas and region-specific, optimally determined lesion-load thresholds, and comprehensively evaluate the performance of this framework across various clinical scenarios for AIS. We enrolled a cohort of 7,655 AIS patients from eleven centers. Modified atlas was created by expanding conventional atlas based on full MCA territory. Ref-AI-ASPECTS with modified atlas and specific lesion-load thresholds was established using a genetic algorithm. The clinical utility of Ref-AI-ASPECTS was assessed by comparing it to the conventional framework (Con-AI-ASPECTS) in terms of correlation with NIHSS scores on admission, dichotomized prediction of mRS at 3 months, and consistency with expert scoring across the training DWI data, external DWI data, expanded CT data, and real-world prospective DWI data. The Ref-AI-ASPECTS frameworks with modified atlas and specific lesion-load thresholds (2

In patients with anterior circulation large vessel occlusion stroke, hyperdense areas (HDAs) on post-thrombectomy computed tomography (CT) reflect blood–brain barrier injury and may herald malignant edema or hemorrhagic transformation. Both complications can progress to life-threatening mass effect, often necessitating surgical interventions such as decompressive craniectomy. We aimed to develop and validate a location-specific HDA score for predicting severe mass effect. This multicenter retrospective study analyzed 865 patients exhibiting HDAs on post-thrombectomy CT. The primary outcome was severe mass effect, defined as decompressive craniectomy or midline shift ≥ 5 mm on follow-up imaging. A location-specific HDA score was developed by expanding the ASPECTS template to include subarachnoid and ventricular compartments. Predictive models integrating imaging and clinical variables were constructed via LASSO regression and validated internally (bootstrapping) and externally. Three HDA locations independently predicted the outcome: insula [adjusted odds ratio (aOR) = 2.02, 95

Functional recovery after acute ischemic stroke is highly heterogeneous. This study aimed to explore and characterize distinct clinical-neuroimaging phenotypes associated with outcomes in patients with anterior circulation large vessel occlusion (LVO) by integrating multidimensional clinical and neuroimaging biomarkers using latent class analysis (LCA). In this retrospective, multicenter study, we included patients with anterior circulation LVO receiving contemporary standard acute stroke care. The analysis integrated clinical factors (age, NIHSS, atrial fibrillation, glucose) and neuroimaging markers (infarct volume, location, and brain frailty) selected via LASSO regression. LCA was performed in a derivation cohort (n = 957) to identify latent phenotypes. Associations between phenotypes and 90-day unfavorable outcomes (modified Rankin Scale 3–6) were assessed using multivariable generalized linear models, with results validated in an independent cohort (n = 131). LCA identified four distinct clinical-neuroimaging : (1) Brain Frailty (24.8

Long-term sensorineural hearing loss (SNHL) is a prevalent condition associated with an increased risk of cognitive impairment. This study aimed to investigate the relationship among gradient connectivity, ventricle volumes, and transcriptional signatures in individuals experiencing cognitive deficits related to long-term SNHL. This study enrolled 81 patients with long-term SNHL and 78 healthy controls (HCs). All participants underwent audiological tests, neuropsychological assessment, and MRI scanning. Connectome gradient analysis and ventricular volume measurements were performed. Additionally, regional gene expression and neurotransmitter receptor data were integrated. Correlation analysis was conducted to examine associations between neuroimaging metrics and cognitive performance. Patients with SNHL had significantly higher hearing thresholds and worse cognitive performance than HCs. The principal gradient was compressed in the SNHL group, with significant differences in the default mode network and dorsal attention network. Enlarged volumes of the choroid plexus and lateral ventricles were also observed in the SNHL group. Correlation analysis revealed significant associations among ventricle volumes, gradient connectivity, and cognitive performance. Transcriptomic analysis revealed 496 genes associated with regions showing an increased principal gradient and 321 genes linked to regions with a decreased gradient. Enrichment analyses indicated these genes were implicated in synaptic plasticity, neurotransmitter regulation, energy metabolism, and neurodegenerative pathways. This study provides new insights into the multifaceted nature of SNHL-related cognitive impairments, suggesting that gradient connectivity, ventricle volumes, and transcriptional signatures are interconnected and may serve as potential biomarkers for monitoring cognitive decline in individuals with long-term SNHL. Future research should focus on elucidating the causal pathways and underlying biological mechanisms connecting these multimodal factors.

INTRODUCTION:To explore microstructure changes across brain white matter and gray matter in tinnitus patients and its effect on neuropsychological performance. METHODS:The cross-sectional study used Multi-shell Diffusion Weighted Imaging data and neuropsychological assessment from 48 tinnitus patients and 48 healthy controls. Microstructural features across over white matter and gray matter based on Diffusion Tensor Imaging (DTI) and Neurite Orientation Dispersion and Density Imaging (NODDI) model using Tract-Based Spatial Statistics (TBSS) and Gray Matter-Based Spatial Statistics (GBSS), as well as topological properties were derived from an advanced tractography model in subjects. Brain-neuropsychological performance correlations were analyzed. RESULTS:Tinnitus patients showed decreased axial diffusivity in forceps minor and right corticospinal tract, increased orientation dispersion in forceps minor, decreased connection strength between the right caudate and pericalcarine, right caudate and superior temporal lobe, and left putamen and cuneus. Global network efficiency and local network efficiency were significantly less in tinnitus patients while feeder connection strength was significantly less in tinnitus patients. The orientation dispersion value mediated the relationship between tinnitus status and Trail Making Test-Part B scores. However, no obvious microstructural changes in gray matter were observed. CONCLUSION:Leveraging multi-shell DWI data, the current study indicated that fiber disruption and internal connectivity organizational changes in brain white matter, rather than gray matter, were more susceptible in tinnitus patients. These microstructural changes in white matter could be associated with changes in cognitive function in tinnitus patients.

AIM:Type 2 diabetes mellitus (T2DM) is a metabolic disorder associated with cognitive decline. This study investigated the interplay between altered effective connectivity (EC) in the Papez circuit, regional atrophy, and choroid plexus volume (CPV) in relation to T2DM-related cognitive deficits. METHODS:Eighty T2DM patients and 75 healthy controls underwent multimodal MRI. Resting-state fMRI data were analyzed using spectral dynamic causal modeling (spDCM) to quantify EC between Papez circuit regions. Structural 3D-T1 images were processed to measure regional volumes and the CPV, which might serve as a proxy for glymphatic activity. Participants underwent standardized cognitive assessments to evaluate neurocognitive function. RESULTS:T2DM patients exhibited significant EC reductions in three Papez circuit pathways: from the hippocampus (HPC) to the mammillary body (MB) (p = 0.001), from the anterior thalamic nucleus (AT) to the anterior cingulate cortex (ACC) (p = 0.005), and from the entorhinal cortex (ERC) to the HPC (p < 0.001). Structural atrophy was observed in the left hippocampus (p = 0.001) and left thalamic (p = 0.006), accompanied by CPV enlargement (p = 0.027). Notably, the HPC to MB connectivity was partially mediated by the CPV, with a significant indirect effect of 0.1456 (95 % CI: 0.0335, 0.2665). The Complex Figure Test delay (CFT-delay) score was positively correlated with the reduced EC in Papez circuit pathways; however, there was a negative correlation between the CFT-delay score and the CPV (r = -0.344, p = 0.002). Furthermore, reduced EC in the Papez circuit exhibited a negative correlation with the Homeostatic Model Assessment for Insulin Resistance (HOMA-IR). CONCLUSION:Our study highlights the complex interplay between Papez circuit functional disruptions, structural atrophy within the circuit, as well as the CPV alterations in T2DM-related cognitive decline. These findings offer potential biomarkers for early detection of cognitive impairments and novel therapeutic targets for intervention in T2DM.

Background:The segmentation of cerebral vasculature on magnetic resonance angiography (MRA) images is crucial for both clinical applications and research. However, existing cerebrovascular segmentation techniques fail to account for the complex geometric and topological features of cerebral vasculature, resulting in suboptimal segmentation of distal small arteries. This study aimed to develop a novel deep vascular network (DVNet) with dual contextual path (DCP) and vascular attention enhancement module (VAEM) to accurately segment the cerebrovasculature. Methods:First, we developed DVNet with DCP and VAEM to accurately segment the cerebral vasculature from the publicly available dataset MR Brain Images of Healthy Volunteers (MIDAS)-I. Second, the segmentation performance of the proposed DVNet was evaluated using the MIDAS-II dataset, followed by further validation using our hospital data. Finally, ablation experiments were performed to evaluate the segmentation performance. Results:Experiments show that the proposed segmentation approach outperforms the previously proposed approaches (U-Net, V-Net, endoplasmic reticulum Net, etc.), with 0.900 Dice and 0.860 mean Intersection over Union (IoU) in the MIDAS-I dataset and 0.715 Dice and 0.713 IoU in the MIDAS-II dataset. External validation revealed good segmentation performance (Dice coefficient: 0.733; IoU: 0.730). Conclusions:Our approach demonstrates that accurate and robust cerebrovascular segmentation is achievable on MRA using DVNet with DCP and VAEM, especially in small distal vessels.

Background The basal ganglia area is a frequent site of stroke, which commonly causes intricate functional impairments. This study aims to uncover disparities in static and dynamic functional connectivity (FC) of the brain in patients afflicted with left-sided basal ganglia stroke (L-BGS) and right-sided basal ganglia region stroke (R-BGS), furthermore scrutinising the mechanism behind the lateralisation of the stroke. Methods A total of 23 patients with L-BGS and 20 patients with R-BGS were recruited, alongside 20 healthy control subjects. Resting-state functional magnetic resonance imaging and sliding window techniques were employed to conduct static and dynamic FC analyses on both patient groups and controls, which can enable a more refined evaluation of the variations in neural signals. Results The inter-network connectivity analysis showed significant changes only in the L-BGS patient group (p < 0.05). The R-BGS group showed increased connectivity in the auditory and posterior visual networks, while the L-BGS group showed reduced connectivity. In dynamic connectivity analyses, the L-BGS group exhibited greater positive network connectivity reorganization. Conclusion Within one month of stroke onset, the L-BGS group showed a more pronounced impairment of inter-network connectivity, alongside enhanced FC compensatory changes of a positive nature. Differential changes in the two patient groups may provide useful information for individualized rehabilitation strategies.

Background:Chemotherapy-related cognitive impairments (CRCIs) are frequently reported by patients with non-small cell lung cancer (NSCLC) following chemotherapy treatment. Studies have revealed that cognitive impairment may be linked to abnormal spontaneous neuronal activity and changes in cerebral blood flow (CBF). However, the specific impact of neurovascular coupling (NVC) alterations on patients who have undergone chemotherapy has not been clarified. The aim of this study was to examine the variations in NVC in patients with lung cancer postchemotherapy and to determine potential correlations between these NVC alterations and neurocognitive dysfunction. Methods:A sample of 43 patients with NSCLC was recruited, including 20 patients treated with chemotherapy [CT(+)] and 23 chemotherapy-naïve [CT(-)] individuals who underwent pseudocontinuous arterial spin labeling (pCASL) scans and resting-state functional magnetic resonance imaging (rs-fMRI), along with neurocognitive evaluations. Global and regional NVC indices were assessed according to correlation coefficients and the ratios between CBF and neuronal activity-derived metrics, including the amplitude of low-frequency fluctuations (ALFF) and regional homogeneity (ReHo). Statistical analyses were conducted to calculate the difference between groups and characterize relationships between alterations in global and regional NVC and cognitive performance. Results:In comparison to the CT(-) group, the CT(+) group exhibited significantly lower coupling strength for global CBF-ALFF and CBF-ReHo correlations (P<0.05). Regionally, the CT(+) group demonstrated a decreased CBF:ALFF ratio in the right middle temporal gyrus (MTG) and left middle frontal gyrus (MFG), as well as an increased CBF:ALFF ratio in the left thalamus and left parahippocampal region. Furthermore, the CT(+) group had higher CBF:ReHo ratios in the left precuneus, right central operculum, right inferior parietal lobule, and right superior occipital gyrus but lower CBF:ReHo ratios in the left inferior frontal gyrus and right MFG (false-discovery rate-corrected P value <0.05). Notably, there was a negative correlation observed between Montreal Cognitive Assessment scores and memory scores and the CBF:ALFF ratios in the right MFG and left parahippocampal region. Conclusions:This research offers comprehensive insights into the neurological foundations of CRCI. The application of multimodal neuroimaging analyses combining rs-fMRI and pCASL may uncover the induction of neurovascular decoupling in lung cancer patients undergoing chemotherapy.

Background Glymphatic dysfunction is proposed as a final common pathway to dementia. Cognitive impairment following ischemic stroke can gradually worsen, potentially leading to post-stroke dementia. This study aimed to examine the changes in glymphatic function in post-stroke patients and explore its relationship with cognition. Methods A total of thirty-two post-stroke patients and twenty-seven healthy controls (HCs) matched for age, sex, and educational level were enrolled in this study. All participants underwent neurological MRI scans and comprehensive cognitive assessments six months following the onset of the stroke. Three glymphatic markers derived from MRI were quantified, including diffusion tensor image analysis along the perivascular space (DTI-ALPS) index, choroid plexus volume (CPV), and enlarged perivascular spaces (PVS) volume. The changes in glymphatic markers and their correlations with cognitive scores were analyzed. Results Post-stroke patients exhibited a significantly decreased DTI-ALPS index (p < 0.001) and an increased CPV (p < 0.001) compared to HCs, while no significant difference was observed in PVS volume. Correlation analysis revealed that the DTI-ALPS index was positively correlated with Digit Span Test (r = 0.426, p = 0.015) and Digit Symbol Substitution Test (rs = 0.363, p = 0.041) scores, and PVS volume showed a positive correlation with Trail Making Test-B scores (rs = 0.391, p = 0.027). After adjusting for confounding factors, multiple linear regression analyses indicated that enlarged PVS volume was independently associated with worse performance in Trail Making Test-B (β = 0.428, p = 0.010). Discussion The findings demonstrated that glymphatic dysfunction, as indicated by a reduced DTI-ALPS index and increased CPV volume, was evident in post-stroke patients and significantly linked to impairments in specific cognitive domains, including working memory, processing speed, and executive function. These observations supported the hypothesis that glymphatic impairment may represent a key mechanistic pathway underlying post-stroke cognitive impairment (PSCI). To further elucidate the causal relationships and identify potential therapeutic targets, future studies incorporating larger cohorts, longitudinal designs, and region-specific PVS analyses are warranted. Conclusion Post-stroke patients exhibited a reduced DTI-ALPS index and an increased CPV, potentially reflecting impaired glymphatic function. Furthermore, these metrics were associated with specific cognitive domains.

Postoperative permanent neurological dysfunction remains a challenging complication in type A acute aortic dissection (TAAAD). Researches evaluating cerebral perfusion and altered blood flow in postoperative patients with TAAAD using non-invasive imaging techniques, such as arterial spin labelling are scarce. This study aims to assess cerebral blood flow (CBF) in postoperative patients with TAAAD, using arterial spin labeling (ASL). This study enrolled 22 postoperative patients and 25 healthy control subjects (HC), they all underwent a three-dimensional pseudo-continuous ASL MRI scanning. Voxel-based comparison of normalized CBF was conducted. The relationship between CBF variation and clinical scale assessment was further analysed. Compared with HC subjects, postoperative patients with TAAAD exhibited lower CBF levels in the right middle frontal gyrus, the right orbit of frontal gyrus, the bilateral fusiform gyrus, the right middle temporal gyrus, the bilateral inferior temporal gyrus, the bilateral lateral occipital cortex and the bilateral cerebellum ( t  > 3.0 and p  < 0.05, FDR corrected at cluster level). These variations were also significantly correlated with multiple clinical rating scales about cognition and emotion. Postoperative patients with TAAAD exhibit abnormalities in several brain regions. The affected areas involve important component of neuro-networks, including psychological cognitive activity, attention and emotion regulation and high-level visual function.

To investigate the effects of platinum-based chemotherapeutic drugs on the effective connectivity (EC) of hippocampal-prefrontal (HIP-PFC) circuit in non-small cell lung cancer (NSCLC) patients utilizing spectral dynamic causal model (sDCM), and to explore its correlation with cognitive deficits. A total of 109 patients diagnosed with NSCLC (57 without chemotherapy (CT-) and 52 with chemotherapy (CT+)) and 60 healthy controls (HCs) were enrolled. Longitudinal data pre- and post-chemotherapy were available for 30 patients. All participants underwent functional magnetic resonance imaging (fMRI) and cognitive assessments. Effective connectivity within the HIP-PFC circuit for all participants were analyzed using the sDCM approach. Relationships between abnormal connectivity strength and neuropsychological scores were evaluated. The results revealed ECs differences among three groups in the HIP-PFC circuit concentrated in the bilateral hippocampus and right frontal lobe. Analysis of paired groups identified more abnormalities across cerebral hemispheres, including excitatory connectivity from l-HIP to right lateral prefrontal cortex (LPFC). The reduced EC from the l-HIP to the medial prefrontal cortex (mPFC) was significantly negatively correlated with the MoCA scores (r = -0.315, p = 0.007), and the reduced EC from the r-HIP to the mPFC was significantly negatively correlated with the memory scores (r = -0.349, p = 0.006). These insights further bolstered the crucial role of the HIP-PFC circuit in the pathophysiology of cognitive impairment induced by platinum-based chemotherapeutic agents, highlighting its potential as a novel imaging biomarker and therapeutic target.