The methylation status of oxygen 6-methylguanine-DNA methyltransferase (MGMT) promoter has been associated with treatment response in glioblastoma(GBM). Using pre-operative MRI techniques to predict MGMT promoter methylation status remains inconclusive. In this study, we investigated the value of features from structural and advanced imagings in predicting the methylation of MGMT promoter in primary glioblastoma patients. Ninety-two pathologically confirmed primary glioblastoma patients underwent preoperative structural MR imagings and the efficacy of structural image features were qualitatively analyzed using Fisher’s exact test. In addition, 77 of the 92 patients underwent additional advanced MRI scans including diffusion-weighted (DWI) and 3-diminsional pseudo-continuous arterial spin labeling (3D pCASL) imaging. Apparent diffusion coefficient (ADC) and relative cerebral blood flow (rCBF) values within the manually drawn region-of-interest (ROI) were calculated and compared using independent sample t test for their efficacies in predicting MGMT promoter methylation. Receiver operating characteristic curve (ROC) analysis was used to investigate the predicting efficacy with the area under the curve (AUC) and cross validations. Multiple-variable logistic regression model was employed to evaluate the predicting performance of multiple variables. MGMT promoter methylation was associated with tumor location and necrosis (P < 0.05). Significantly increased ADC value (P < 0.001) and decreased rCBF (P < 0.001) were associated with MGMT promoter methylation in primary glioblastoma. The ADC achieved the better predicting efficacy than rCBF (ADC: AUC, 0.860; sensitivity, 81.1%; specificity, 82.5%; vs rCBF: AUC, 0.835; sensitivity, 75.0%; specificity, 78.4%; P = 0.032). The combination of tumor location, necrosis, ADC and rCBF resulted in the highest AUC of 0.914. ADC and rCBF are promising imaging biomarkers in clinical routine to predict the MGMT promoter methylation in primary glioblastoma patients.
Objectives: To quantitatively summarize the specific changes in brain structure and function in migraine patients.Methods: A literature screening of migraine was conducted from inception to Sept 1, 2022, in PubMed, Web of Science, Cochrane Library, and Medline databases using the keyword combination of “migraine and MRI.” Activation likelihood estimation (ALE) was performed to assess the differentiation of functional connectivity (FC), regional homogeneity (ReHo), and gray matter volume (GMV) of migraine patients.Results: Eleven voxel-based morphometry (VBM) studies and 25 resting-state fMRI (rs-fMRI) studies (16 FC and 9 ReHo studies) were included in this study. ALE analysis revealed the ReHo increase in the brainstem and left thalamus, with no decreased area. Neither increased nor decreased regions were detected in FC and GMV of migraine patients.Conclusions: The left thalamus and brainstem were the significantly activated regions of migraine. It is a meaningful insights into the pathophysiology of migraine. The consistent alterated brain areas of morphometrical and functional in migraine patients were far from reached based on current studies.
A cortical plasticity after long-duration single side deafness (SSD) is advocated with neuroimaging evidence while little is known about the short-duration SSDs. In this case-cohort study, we recruited unilateral sudden sensorineural hearing loss (SSNHL) patients and age-, gender-matched health controls (HC), followed by comprehensive neuroimaging analyses. The primary outcome measures were temporal alterations of varied dynamic functional network connectivity (dFNC) states, neurovascular coupling (NVC) and brain region volume at different stages of SSNHL. The secondary outcome measures were pure-tone audiograms of SSNHL patients before and after treatment. A total of 38 SSNHL patients (21 [55%] male; mean [standard deviation] age, 45.05 [15.83] years) and 44 HC (28 [64%] male; mean [standard deviation] age, 43.55 [12.80] years) were enrolled. SSNHL patients were categorized into subgroups based on the time from disease onset to the initial magnetic resonance imaging scan: early- (n = 16; 1-6 days), intermediate- (n = 9; 7-13 days), and late- stage (n = 13; 14-30 days) groups. We first identified slow state transitions between varied dFNC states at the early-stage SSNHL, then revealed the decreased NVC restricted to the auditory cortex at the intermediate- and late-stage SSNHL. Finally, a significantly decreased volume of the left medial superior frontal gyrus (SFGmed) was observed only in the late-stage SSNHL cohort. Furthermore, the volume of the left SFGmed is robustly correlated with both disease duration and patient prognosis. Our study offered neuroimaging evidence for the evolvement from functional to structural brain alterations of SSNHL patients with disease duration less than 1 month, which may explain, from a neuroimaging perspective, why early-stage SSNHL patients have better therapeutic responses and hearing recovery.
Owing to the limitations of cross‐sectional studies, it is unclear whether social media induce brain changes, or if individuals with certain biological traits are more likely to use social media. Functional connectivity (FC) can reflect cerebral functional plasticity, and if social media can influence cerebral FC, then the FC of light social media users should be more similar to that of heavy users after they “heavily” used social media for a long period. We combined longitudinal study design and intersubject correlation (ISC) analysis to investigate this similarity. Thirty‐five heavy and 21 light social media users underwent cognitive tests and functional MRIs. The 21 light social media users underwent another functional MRI scan after completing an additional four‐week social media task. We conducted the ISC at the group, individual, and brain‐region levels to investigate the similarity of FC and locate the brain regions most affected by social media. The FC of light social media users was more similar to that of heavy social media users after they completed the four‐week social media task. Then, social media had an impact on half of the brain, involving almost all brain networks. Finally, cerebral FC that mostly affected by social media was associated with selective attention. We concluded that the impact of social media use on cerebral functional connectivity changes is revealed by ISC method and longitudinal design, which may provide guidance for clinical practice. The methods used in the current research could also be applied to similar domains.