Resting-state fMRI network efficiency as a mediator in the relationship between the glymphatic system and cognitive function in obstructive sleep apnea hypopnea syndrome: Insights from a DTI-ALPS investigation.

INTRODUCTION: Obstructive sleep apnea hypopnea syndrome (OSAHS) is associated with cognitive impairment and physiological complications, necessitating further understanding of its mechanisms. This study investigates the relationship between glymphatic system function, brain network efficiency, and cognitive impairment in OSAHS patients using diffusion tensor image analysis along the perivascular space (DTI-ALPS) and resting-state fMRI. MATERIALS AND METHODS: This study included 31 OSAHS patients and 34 age- and gender-matched healthy controls (HC). All participants underwent GE 3.0T magnetic resonance imaging (MRI) with diffusion tensor image (DTI) and resting-state fMRI scans. The DTI-ALPS index and brain functional networks were assessed. Differences between groups and correlations with clinical characteristics were analyzed. Additionally, the mediating role of brain network efficiency was explored. Finally, receiver operating characteristics (ROC) analysis assessed diagnostic performance. RESULTS: OSAHS patients had significantly lower ALPS-index (1.268 vs. 1.431, p < 0.0001) and moderate negative correlation with Apnea Hypopnea Index (AHI) (r = -0.389, p = 0.031), as well as moderate positive correlation with Montreal Cognitive Assessment (MoCA) (r = 0.525, p = 0.002). Moreover, global efficiency (Eg) of the brain network was positively correlated with the ALPS-index and MoCA scores in OSAHS patients (r = 0.405, p = 0.024; r = 0.56, p = 0.001, respectively). Furthermore, mediation analysis showed that global efficiency partially mediated the impact of glymphatic system dysfunction on cognitive impairment in OSAHS patients (indirect effect = 4.58, mediation effect = 26.9 %). The AUROC for identifying OSAHS and HC was 0.80 (95 % CI 0.69 to 0.91) using an ALPS-index cut-off of 1.35. CONCLUSIONS: OSAHS patients exhibit decreased ALPS-index, indicating impaired glymphatic system function. Dysfunction of the glymphatic system can affect cognitive function in OSAHS by disrupting brain functional network, suggesting a potential underlying pathological mechanism. Additionally, preliminary findings suggest that the ALPS-index may offer promise as a potential indicator for OSAHS.

Diffusion Tensor and Kurtosis MRI-Based Radiomics Analysis of Kidney Injury in Type 2 Diabetes.

BACKGROUND: Diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) can provide quantitative parameters that show promise for evaluation of diabetic kidney disease (DKD). The combination of radiomics with DTI and DKI may hold potential clinical value in detecting DKD. PURPOSE: To investigate radiomics models of DKI and DTI for predicting DKD in type 2 diabetes mellitus (T2DM) and evaluate their performance in automated renal parenchyma segmentation. STUDY TYPE: Prospective. POPULATION: One hundred and sixty-three T2DM patients (87 DKD; 63 females; 27-80 years), randomly divided into training cohort (N = 114) and validation cohort (N = 49). FIELD STRENGTH/SEQUENCE: 1.5-T, diffusion spectrum imaging (DSI) with 9 different b-values. ASSESSMENT: The images of DSI were processed to generate DKI and DTI parameter maps, including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD). The Swin UNETR model was trained with 5-fold cross-validation using 100 samples for renal parenchyma segmentation. Subsequently, radiomics features were automatically extracted from each parameter map. The performance of the radiomics models on the validation cohort was evaluated by utilizing the receiver operating characteristic (ROC) curve. STATISTICAL TESTS: Mann-Whitney U test, Chi-squared test, Pearson correlation coefficient, least absolute shrinkage and selection operator (LASSO), dice similarity coefficient (DSC), decision curve analysis (DCA), area under the curve (AUC), and DeLong's test. The threshold for statistical significance was set at P < 0.05. RESULTS: The DKI_MD achieved the best segmentation performance (DSC, 0.925 ± 0.011). A combined radiomics model (DTI_FA, DTI_MD, DKI_FA, DKI_MD, and DKI_RD) showed the best performance (AUC, 0.918; 95% confidence interval [CI]: 0.820-0.991). When the threshold probability was greater than 20%, the combined model provided the greatest net benefit. Among the single parameter maps, the DTI_FA exhibited superior diagnostic performance (AUC, 887; 95% CI: 0.779-0.972). DATA CONCLUSION: The radiomics signature constructed based on DKI and DTI may be used as an accurate and non-invasive tool to identify T2DM and DKD. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.

Quantitative Study of the Changes in Cerebral Blood Flow and Iron Deposition During Progression of Alzheimer's Disease.

BACKGROUND: Advanced Alzheimer's disease (AD) has no effective treatment, and identifying early diagnosis markers can provide a time window for treatment. OBJECTIVE: To quantify the changes in cerebral blood flow (CBF) and iron deposition during progression of AD. METHODS: 94 subjects underwent brain imaging on a 3.0-T MRI scanner with techniques of three-dimensional arterial spin labeling (3D-ASL) and quantitative susceptibility mapping (QSM). The subjects included 22 patients with probable AD, 22 patients with mild cognitive impairment (MCI), 25 patients with subjective cognitive decline (SCD), and 25 normal controls (NC). The CBF and QSM values were obtained using a standardized brain region method based on the Brainnetome Atlas. The differences in CBF and QSM values were analyzed between and within groups using variance analysis and correlation analysis. RESULTS: CBF and QSM identified several abnormal brain regions of interest (ROIs) at different stages of AD (p < 0.05). Regionally, the CBF values in several ROIs of the AD and MCI subjects were lower than for NC subjects (p < 0.001). Higher QSM values were observed in the globus pallidus. The CBF and QSM values in multiple ROI were negatively correlated, while the putamen was the common ROI of the three study groups (p < 0.05). The CBF and QSM values in hippocampus were cross-correlated with scale scores during the progression of AD (p < 0.05). CONCLUSION: Iron deposition in the basal ganglia and reduction in blood perfusion in multiple regions existed during the progression of AD. The QSM values in putamen can be used as an imaging biomarker for early diagnosis of AD.

The Relationship of Functional Connectivity of the Sensorimotor and Visual Cortical Networks Between Resting and Task States.

The intrinsic activity of the human brain maintains its general operation at rest, and this ongoing spontaneous activity exhibits a high level of spatiotemporally correlated activity among different cortical areas, showing intrinsically organized brain functional connectivity (FC) networks. Many functional network properties of the human brain have been investigated extensively for both rest and task states, but the relationship between these two states has been rarely investigated yet and remains unclear. Comparing well-defined task-specific networks with corresponding intrinsic FC networks may reveal their relationship and improve our understanding of the brain's operations at both rest and task states. This study investigated the relationship of the sensorimotor and visual cortical FC networks between the resting and task states. The sensorimotor task was to rub right-hand fingers, and the visual task was to open and close eyes, respectively. Our study demonstrated a general relationship of the task-evoked FC network with its corresponding intrinsic FC network, regardless of the tasks. For each task type, the study showed that (1) the intrinsic and task-evoked FC networks shared a common network and the task enhanced the coactivity within that common network compared to the intrinsic activity; (2) some areas within the intrinsic FC network were not activated by the task, and therefore, the task activated only partial but not whole of the intrinsic FC network; and (3) the task activated substantial additional areas outside the intrinsic FC network and therefore recruited more intrinsic FC networks to perform the task.