The microstructural change of the brain and its clinical severity association in pediatric Tourette syndrome patients.

BACKGROUND: Gilles de la Tourette syndrome (GTS) is a prevalent pediatric neurological disorder. Most studies point to abnormalities in the cortico-striato-thalamocortical (CSTC) circuits. Neuroimaging studies have shown GTS's extensive impact on the entire brain. However, due to participant variability and potential drug and comorbidity impact, the results are inconsistent. To mitigate the potential impact of participant heterogeneity, we excluded individuals with comorbidities or those currently undergoing medication treatments. Based on the hypothesis of abnormality within the CSTC circuit, we investigated microstructural changes in white matter using diffusion spectrum imaging (DSI). This study offers the first examination of microstructural changes in treatment-naïve pediatric patients with pure GTS using diffusion spectrum imaging. METHODS: This single-center prospective study involved 30 patients and 30 age- and gender-matched healthy volunteers who underwent sagittal T1-weighted MRI and DSI. We analyzed generalized fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity. RESULTS: No significant differences were observed in mean diffusivity and axial diffusivity values between the two groups. However, the patient group exhibited significantly higher generalized fractional anisotropy values in the right frontostriatal tract of the dorsolateral prefrontal cortex, the right frontostriatal tract of the precentral gyrus, and bilateral thalamic radiation of the dorsolateral prefrontal cortex. Additionally, the generalized fractional anisotropy value of the right frontostriatal tract of the precentral gyrus is inversely correlated with the total tic severity scores at the most severe condition. CONCLUSION: Treatment-naïve pediatric GTS patients demonstrated increased connectivity within the CSTC circuit as per diffusion spectrum imaging, indicating possible CSTC circuit dysregulation. This finding could also suggest a compensatory change. It thus underscores the necessity of further investigation into the fundamental pathological changes in GTS. Nevertheless, the observed altered connectivity in GTS patients might serve as a potential target for therapeutic intervention.

Brain Age Difference at Baseline Predicts Clinical Dementia Rating Change in Approximately Two Years.

BACKGROUND: The Clinical Dementia Rating (CDR) has been widely used to assess dementia severity, but it is limited in predicting dementia progression, thus unable to advise preventive measures to those who are at high risk. OBJECTIVE: Predicted age difference (PAD) was proposed to predict CDR change. METHODS: All diffusion magnetic resonance imaging and CDR scores were obtained from the OASIS-3 databank. A brain age model was trained by a machine learning algorithm using the imaging data of 258 cognitively healthy adults. Two diffusion indices, i.e., mean diffusivity and fractional anisotropy, over the whole brain white matter were extracted to serve as the features for model training. The validated brain age model was applied to a longitudinal cohort of 217 participants who had CDR = 0 (CDR0), 0.5 (CDR0.5), and 1 (CDR1) at baseline. Participants were grouped according to different baseline CDR and their subsequent CDR in approximately 2 years of follow-up. PAD was compared between different groups with multiple comparison correction. RESULTS: PADs were significantly different among participants with different baseline CDRs. PAD in participants with relatively stable CDR0.5 was significantly smaller than PAD in participants who had CDR0.5 at baseline but converted to CDR1 in the follow-up. Similarly, participants with relatively stable CDR0 had significantly smaller PAD than those who were CDR0 at baseline but converted to CDR0.5 in the follow-up. CONCLUSION: Our results imply that PAD might be a potential imaging biomarker for predicting CDR outcomes in patients with CDR0 or CDR0.5.

Microstructural differences in white matter tracts across middle to late adulthood: a diffusion MRI study on 7167 UK Biobank participants.

White matter fiber tracts demonstrate heterogeneous vulnerabilities to aging effects. Here, we estimated age-related differences in tract properties using UK Biobank diffusion magnetic resonance imaging data of 7167 47- to 76-year-old neurologically healthy people (3368 men and 3799 women). Tract properties in terms of generalized fractional anisotropy, axial diffusivity, radial diffusivity, and mean diffusivity were sampled on 76 fiber tracts; for each tract, age-related differences were estimated by fitting these indices against age in a linear model. This cross-sectional study demonstrated 4 age-difference patterns. The dominant pattern was lower generalized fractional anisotropy and higher axial diffusivity, radial diffusivity, and mean diffusivity with age, constituting 45 of 76 tracts, mostly involving the association, projection, and commissure fibers connecting the prefrontal lobe. The other 3 patterns constituted only 14 tracts, with atypical age differences in diffusion indices, and mainly involved parietal, occipital, and temporal cortices. By analyzing the large volume of diffusion magnetic resonance imaging data available from the UK Biobank, the study has provided a detailed description of heterogeneous age-related differences in tract properties over the whole brain which generally supports the myelodegeneration hypothesis.

Evaluation of structural connectivity changes in betel-quid chewers using generalized q-sampling MRI.

RATIONALE: Betel quid (BQ) is a common addictive substance in many Asian countries. However, few studies have focused on the influences of BQ on the brain. It remains unclear how BQ can affect structural brain abnormalities in BQ chewers. OBJECTIVES: We aimed to use generalized q-sampling imaging (GQI) to evaluate the impact of the neurological structure of white matter caused by BQ. METHODS: The study population comprised 16 BQ chewers, 15 tobacco and alcohol controls, and 17 healthy controls. We used GQI with voxel-based statistical analysis (VBA) to evaluate structural brain and connectivity abnormalities in the BQ chewers compared to the tobacco and alcohol controls and the healthy controls. Graph theoretical analysis (GTA) and network-based statistical (NBS) analysis were also performed to identify the structural network differences among the three groups. RESULTS: Using GQI, we found increases in diffusion anisotropy in the right anterior cingulate cortex (ACC), the midbrain, the bilateral angular gyrus, the right superior temporal gyrus (rSTG), the bilateral superior occipital gyrus, the left middle occipital gyrus, the bilateral superior and inferior parietal lobule, and the bilateral postcentral and precentral gyrus in the BQ chewers when compared to the tobacco and alcohol controls and the healthy controls. In GTA and NBS analyses, we found more connections in connectivity among the BQ chewers, particularly in the bilateral anterior cingulum. CONCLUSIONS: Our results provided further evidence indicating that BQ chewing may lead to brain structure and connectivity changes in BQ chewers.