Association between white matter lesions and the cerebral glucose metabolism in patients with cognitive impairment

Risk Factors of Restroke in Patients with Lacunar Cerebral Infarction Using Magnetic Resonance Imaging Image Features under Deep Learning Algorithm

This study was aimed to explore the magnetic resonance imaging (MRI) image features based on the fuzzy local information C-means clustering (FLICM) image segmentation method to analyze the risk factors of restroke in patients with lacunar infarction. In this study, based on the FLICM algorithm, the Canny edge detection algorithm and the Fourier shape descriptor were introduced to optimize the algorithm. The difference of Jaccard coefficient, Dice coefficient, peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), running time, and segmentation accuracy of the optimized FLICM algorithm and other algorithms when the brain tissue MRI images were segmented was studied. 36 patients with lacunar infarction were selected as the research objects, and they were divided into a control group (no restroke, 20 cases) and a stroke group (restroke, 16 cases) according to whether the patients had restroke. The differences in MRI imaging characteristics of the two groups of patients were compared, and the risk factors for restroke in lacunar infarction were analyzed by logistic multivariate regression. The results showed that the Jaccard coefficient, Dice coefficient, PSNR value, and SSIM value of the optimized FLICM algorithm for segmenting brain tissue were all higher than those of other algorithms. The shortest running time was 26 s, and the highest accuracy rate was 97.86%. The proportion of patients with a history of hypertension, the proportion of patients with paraventricular white matter lesion (WML) score greater than 2 in the stroke group, the proportion of patients with a deep WML score of 2, and the average age of patients in the stroke group were much higher than those in the control group (P < 0.05). Logistic multivariate regression showed that age and history of hypertension were risk factors for restroke after lacunar infarction (P < 0.05). It showed that the optimized FLICM algorithm can effectively segment brain MRI images, and the risk factors for restroke in patients with lacunar infarction were age and hypertension history. This study could provide a reference for the diagnosis and prognosis of lacunar infarction.

Complete Evaluation of Dementia: PET and MRI Correlation and Diagnosis for the Neuroradiologist

This article will familiarize neuroradiologists with the pathophysiology, clinical findings, and standard MR imaging and PET imaging features of multiple forms of dementia as well as new emerging techniques. Cases were compiled from multiple institutions with the goal of improved diagnostic accuracy and improved patient care as well as information about biomarkers on the horizon. Dementia topics addressed include the following: Alzheimer disease, frontotemporal dementia, cerebral amyloid angiopathy, Lewy body dementia, Parkinson disease and Parkinson disease variants, amyotrophic lateral sclerosis, multisystem atrophy, Huntington disease vascular dementia, and Creutzfeldt-Jakob disease.

Impaired GABAergic and glutamatergic neurometabolic activity in aged mice brain as measured by 1 H-[13 C]-NMR spectroscopy

Healthy aging is associated with a decline in cognitive function, and is a major risk factor for many neurodegenerative diseases. Although, there are several evidence that brain mitochondrial function is altered with aging its significance at the cellular level is elusive. In this study, we have investigated mitochondrial TCA cycle and neurotransmitter cycle fluxes associated with glutamatergic, GABAergic neurons and astroglia in the cerebral cortex and hippocampus of young (6 months) and aged (24 months) C57BL6 mice by using ¹ H-[¹³ C]-NMR spectroscopy together with timed infusion of ¹³ C-labeled glucose and acetate. The ratio V_Cyc /V_TCA was determined from a steady-state [2-¹³ C]acetate experiment. Metabolic fluxes were obtained by fitting a three-compartment metabolic model to ¹³ C turnover of amino acids from glucose. Levels of glutamate, aspartate and taurine were reduced in the cerebral cortex, while glutamine and choline were elevated in the hippocampus of aged mice. Interestingly, the rate of acetate oxidation increased in the cerebral cortex, while the flux of mitochondrial TCA cycle of glutamatergic neurons decreased in the cerebral cortex (P < .0001) and hippocampus (P = .025) of aged mice. The glutamate-glutamine neurotransmitter cycle flux was reduced in the cerebral cortex (P < .0001). The GABAergic TCA cycle flux was reduced in the cerebral cortex (P = .0008), while GABA-glutamine neurotransmitter cycling flux was also reduced in the cerebral cortex (P = .011) and hippocampus (P = .042) of aged brain. In conclusion, the reduction in excitatory and inhibitory neurotransmitter activity of glutamatergic and GABAergic neurons in the cerebral cortex and hippocampus correlates qualitatively with declined cognitive function in aged mice.

Cerebral Small Vessel Disease and Alzheimer's Disease: A Review

Alzheimer's disease (AD) is the most common cause of dementia. Despite this, clear pathophysiology for AD has not been confirmed, and effective treatments are still not available. As AD results in a complex disease process for cognitive decline, various theories have been suggested as the cause of AD. Recently, cerebral small vessel disease (SVD) has been suggested to contribute to the pathogenesis of AD, as well as contributing to vascular dementia. Cerebral SVD refers to a varied group of diseases that affect cerebral small arteries and microvessels. These can be seen as white matter hyperintensities, cerebral microbleeds, and lacunes on magnetic resonance imaging. Data from epidemiological and clinical-pathological studies have found evidence of the relationship between cerebral SVD and AD. This review aims to discuss the complex relationship between cerebral SVD and AD. Recent reports that evaluate the association between these diseases will be reviewed.

Vascular, inflammatory and metabolic risk factors in relation to dementia in Parkinson's disease patients with type 2 diabetes mellitus

There are limited data on vascular, inflammatory, metabolic risk factors of dementia in Parkinson’s disease (PD) with type 2 diabetes mellitus (DM) (PD-DM). In a study of 928 subjects comprising of 215 PD with DM (including 31 PD-DM with dementia, PD-DMD), 341 PD without DM (including 31 PD with dementia, PDD) and 372 DM without PD (including 35 DM with dementia, DMD) patients, we investigated if vascular, inflammatory, metabolic, and magnetic resonance imaging (MRI) markers were associated with dementia in PD-DM. Lower fasting blood glucose (FBG<5mmol/L, OR=4.380; 95%CI: 1.748-10.975; p=0.002), higher homocysteine (HCY>15μmol/L, OR=3.131; 95%CI: 1.243-7.888; p=0.015) and hyperlipidemia (OR=3.075; 95%CI: 1.142-8.277; p=0.026), increased age (OR=1.043; 95%CI: 1.003-1.084; p=0.034) were the most significant risk factors in PDD patients. Lower low-density lipoprotein cholesterol (LDL-C<2mmol/L, OR=4.499; 95%CI: 1.568-12.909; p=0.005) and higher fibrinogen (>4g/L, OR=4.066; 95%CI: 1.467-11.274; p=0.007) were the most significant risk factors in PD-DMD patients. The area under the curve (AUC) for fibrinogen and LDL-C was 0.717 (P=0.001), with a sensitivity of 80.0% for the prediction of PD-DMD.

In summary, we identified several factors including LDL-C and fibrinogen as significant risk factors for PD-DMD and these may have prognostic and treatment implications.

Relationship Between Type 2 Diabetes and White Matter Hyperintensity: A Systematic Review

White matter (WM) disease is recognized as an important cause of cognitive decline and dementia. White matter lesions (WMLs) appear as white matter hyperintensities (WMH) on T2-weighted magnetic resonance imaging (MRI) scans of the brain. Previous studies have shown that type 2 diabetes (T2DM) is associated with WMH. In this review, we reviewed the literature on the relationship between T2DM and WMH in PubMed and Cochrane over the past five years and explored the possible links among the presence of T2DM, the course or complications of diabetes, and WMH. We found that: (1) Both from a macro- and micro-scopic point of view, most studies support the relationship of a larger WMH and a decrease in the integrity of WMH in T2DM; (2) From the relationship between brain structural changes and cognition in T2DM, the poor performance in memory, attention, and executive function tests associated with abnormal brain structure is consistent; (3) Diabetic microangiopathy or peripheral neuropathy may be associated with WMH, suggesting that the brain may be a target organ for T2DM microangiopathy; (4) Laboratory markers such as insulin resistance and fasting insulin levels were significantly associated with WMH. High HbA1c and high glucose variability were associated with WMH but not glycemic control.