Whole-Brain Volume CT Angiography can Effectively Detect Early Ischemic Cerebrovascular Diseases

Objective: To investigate the role of whole-brain volume computed tomography (CT) perfusion in assessing early ischemic cerebrovascular diseases. Materials and Methods: Seventy-two patients with early ischemic cerebrovascular diseases who had undergone routine CT scan and 320-row volume CT whole-brain perfusion imaging within 8 h after admission were retrospectively enrolled in this one-center case-sectional study. The perfusion parameters of cerebral blood flow (CBF), cerebral blood volume (CBV), mean transit time (MTT), time to peak (TTP), and dynamic CT angiogram (4D-CTA) were obtained and analyzed. Results: Among 72 patients, 29 cases with 37 cerebral ischemic lesions were found in plain CT scan, whereas 51 cases with 76 lesions were found in whole-brain CT perfusion, with 30.6% more patients being detected. The CBF value was significantly lower in the abnormal than normal corresponding perfusion area in the healthy hemisphere (P<0.05), while the MTT and TTP values were significantly higher in the abnormal than the normal corresponding area (P<0.05). 4D-CTA image suggested that 59 cases had different degrees of stenosis or occlusion, including 11 mild, 18 moderate, 21 severe, and 9 occlusive cases. Four-D-CTA imaging could detect significantly (P<0.05) more patients with abnormal perfusion in severe cerebral vascular stenosis or occlusion than those with no, mild or moderate stenosis (93.33% vs. 16.67%) (P<0.05). The stenosis of intracranial and carotid arteries was positively correlated with MTT and TTP values (P<0.05). Conclusion: Whole-brain volume CT angiography can comprehensively display early cerebral ischemic lesions, cerebral blood perfusion status, and cerebral vascular stenosis, providing valuable information for early detection of ischemic cerebral diseases and appropriate treatment planning.

Case Report: A Case of Moyamoya Syndrome Associated With Multiple Endocrine Neoplasia Type 2A

To the best of our knowledge, we report a case of MEN2A complicated by moyamoya syndrome. A 52-year-old woman presented with vertigo. Magnetic resonance angiography (MRA) revealed bilateral supraclinoid stenosis of the internal carotid artery and abnormal moyamoya-like vessels around the basal ganglia. She had a heterozygous variant of RNF213, which is the susceptibility gene for moyamoya disease. She had also previously received diagnoses of medullary thyroid carcinoma (MTC) at age 23 and left-sided pheochromocytoma (PHEO) at age 41. Genetic testing revealed heterozygosity for a mutation at codon 634 in exon 11 (TGC-TTC mutation; p.Cys634Phe) of the Ret gene. Intracranial vascular stenosis may have been caused by a genetic mutation of RNF213 and hypersecretion of catecholamines by MEN2A. Physicians should recognize that MEN2A can be present with moyamoya syndrome.

Circulating ANGPTL3 and ANGPTL4 levels predict coronary artery atherosclerosis severity

Background We investigated the role of ANGPTL3 and ANGPTL4 in atherosclerosis development and determined whether plasma concentrations of ANGPTL3 and ANGPTL4 are related to the degree of coronary stenosis. Methods A total of 305 consecutive patients with angina who underwent diagnostic coronary angiography were enrolled in the study between August 2017 and August 2018. The levels of ANGPTL3 and ANGPTL4 were measured by using competitive ELISA kits. Results According to the degree of coronary artery stenosis, patients were classified into four types: coronary artery stenosis of < 10%, 10-50%, 50-75, and > 75%. The plasma ANGPTL3 level was higher (51.71 ± 52.67 vs. 24.65 ± 10.32 ng/mL, P < 0.001) and that of ANGPTL4 was lower (454.66 ± 269.05 vs. 875.49 ± 961.15 ng/mL, P < 0.001) in the coronary artery stenosis ≥ 10% group than in the < 10% group. ANGPTL3 and ANGPTL4 levels were significantly associated with the severity of coronary vascular stenosis. ROC curve analyses indicated that ANGPTL3 concentrations above 30.5 ng/mL can predict atherosclerosis with a sensitivity of 71.2% and specificity of 75.3%, and that ANGPTL4 levels below 497.5 ng/mL can predict atherosclerosis with a sensitivity of 63.9% and specificity of 74.5%. ANGPTL3 and ANGPTL4 were determined to be independent risk factors for coronary atherosclerosis with odds ratios (ORs) of 0.189 (95% CI 0.097-0.368, P < 0.001) and 3.625 (95% CI 1.873-7.016, P < 0.001), respectively. Conclusions Increased ANGPTL3 or decreased ANGPTL4 shows an association with coronary atherosclerosis and, may become a predictor of coronary atherosclerosis in the future.

Association of Pericoronary Adipose Tissue Quality Determined by Dual-Layer Spectral Detector CT With Severity of Coronary Artery Disease: A Preliminary Study

Background: Pericoronary adipose tissue (PCAT) is considered as a source of inflammatory mediators, leading to the development of coronary atherosclerosis. The study aimed to investigate the correlation between PCAT quality derived from dual-layer spectral detector CT (SDCT) and the severity of coronary artery disease (CAD), and whether PCAT parameters were independently associated with the presence of CAD.Materials and Methods: A total of 403 patients with symptoms of chest pain who underwent SDCT were included. PCAT quality including fat attenuation index (FAI) measured from conventional polychromatic CT images (FAI120kvp) and spectral virtual mono-energetic images at 40 keV (FAI40keV), slope of spectral HU curve (λHU), and effective atomic number (Eff-Z) were measured around the lesions representing the maximal degree of vascular stenosis in each patient. Meanwhile, overall epicardial adipose tissue (EAT) attenuation was acquired in the conventional polychromatic energy imaging.Results: FAI40keV, λHU, Eff-Z, and FAI120kvp increased along with the degree of CAD in general and were superior to the overall EAT attenuation for detecting the presence of CAD. Multivariate logistic regression analysis indicated that FAI40keV was the most powerful independent indicator (odds ratio 1.058, 95% CI 1.044–1.073; p &lt; 0.001) of CAD among these parameters. Using an optimal cut-off (−131.8 HU), FAI40keV showed higher diagnostic accuracy of 80.6% compared with the other parameters.Conclusions: These preliminary findings suggest that FAI40keV on SDCT may be an appealing surrogate maker to allow monitoring of PCAT changes in the development of CAD.

Magnetic Resonance Imaging Image Segmentation Under Artificial Intelligence Neural Network for Evaluation of the Effect of Butyphthalide Combined With Edaravone on Neurological Function in Patients With Acute Cerebral Infarction

This research was developed to investigate the effect of artificial intelligence neural network-based magnetic resonance imaging (MRI) image segmentation on the neurological function of patients with acute cerebral infarction treated with butylphthalide combined with edaravone. Eighty patients with acute cerebral infarction were selected as the research subjects, and the MRI images of patients with acute cerebral infarction were segmented by convolutional neural networks (CNN) upgraded algorithm model. MRI images of patients before and after treatment of butylphthalide combined with edaravone were compared to comprehensively evaluate the efficacy of this treatment. The results showed that compared with the traditional CNN algorithm, the running time of the CNN upgraded algorithm adopted in this study was significantly shorter, and the Loss value was lower than that of the traditional CNN model. Upgraded CNN model can realize accurate segmentation of cerebral infarction lesions in MRI images of patients. In addition, the degree of cerebral infarction and the degree of arterial stenosis were significantly improved after treatment with butylphthalide and edaravone. Compared with that before treatment, the number of patients with severe cerebral infarction or even vascular stenosis decreased significantly (P &lt; 0.05), and gradually changed to mild vascular stenosis, and the neurological dysfunction of patients was also significantly improved. In short, MRI image segmentation based on artificial intelligence neural network can well-evaluate the efficacy and neurological impairment of butylphthalide combined with edaravone in the treatment of acute cerebral infarction, and it was worthy of promotion in clinical evaluation of the treatment effect of acute cerebral infarction.

Effects of chemerin and homocysteine levels and their associations with occurrence and development of ischemic cerebrovascular disease

Background The current study was conducted to explore the effects of chemerin and homocysteine (Hcy) levels and their associations with the occurrence and development of ischemic cerebrovascular disease (ICVD). Methods There involved a total of 187 patients with ICVD and 190 healthy people for physical examination in Cangzhou Central hospital from January 2020 to April 2021. The participants enrolled were divided into four groups based on the digital subtraction angiography: mild stenosis group (64 cases, stenosis rate 30-49 %), moderate stenosis group (72 cases, stenosis rate 50-69 %), severe stenosis group (51 cases, stenosis rate 70-99 %) and control group (190 cases, in healthy condition). The laboratory indexes of ICVD group and control group were observed and the four groups were further compared. Pearson linear correlation was applied to analyze the link between chemerin and Hcy levels and the degree of cerebral vascular stenosis in ICVD patients, and multivariate logistic regression was used to analyze the influencing factors of ICVD. Results No significant difference was found in general information including age, gender, body mass index (BMI), heart rate, systolic blood pressure, diastolic blood pressure, smoking and drinking between the two groups (P > 0.05). Moreover, there was no significant difference in fasting blood glucose (FBG), total cholesterol (TC) and high density lipoprotein cholesterol (HDL-C) levels between the two groups (P > 0.05). However, the levels of triglyceride (TG), low density lipoprotein cholesterol (LDL-C), chemerin and Hcy in ICVD group were significantly higher than those in control group (P < 0.05). When comparing the four groups, there was no significant difference in FBG and TC levels (P > 0.05). The levels of TG, LDL-C, chemerin and Hcy in mild, moderate and severe stenosis groups were higher than those in control group, the above levels in moderate and severe stenosis group were higher than those in mild stenosis group, and severe stenosis group higher than moderate stenosis group (P < 0.05). Chemerin and Hcy levels were positively correlated with the degree of cerebral vascular stenosis in ICVD patients (r = 0.612, 0.519, P < 0.001). ICVD was regarded as the dependent variable, and the abovementioned general data as well as significant laboratory indicators, including TG, LDL-C, chemerin and Hcy, as independent variables. The results of multivariate logistic regression analysis revealed that TG, LDL-C, chemerin and Hcy were independent influencing factors of ICVD. Conclusions Chemerin and Hcy levels exerted a close link to the occurrence and development of ICVD as independent influencing factors.

Differentially Expressed Circular RNAs in Stenosed Arteriovenous Fistula Tissues of Uremia Patients

BackgroundArteriovenous fistula (AVF) is the most common renal replacement therapy for uremic patients. However, stenosis in AVF may lead to AVF failure, hence prevention and effective management of AVF failure is an issue to be addressed. circular RNAs (circRNAs) dysregulation may be pivotal for the development and progression of AVF stenosis. MethodsFour stenosed tissues from AVF outflow veins and four normal venous tissues without vascular stenosis were collected for RNA-sequencing (RNA-seq). The circRNAs expression profiles were identified by high-throughput sequencing, and the functions and pathways of differentially expressed (DE) circRNAs were annotated by Gene Ontology (GO) and Kyoto Encyclopedia of Gene Genomes (KEGG) enrichment analyses. Seven DE circRNAs were screened for quantitative real‐time polymerase chain reaction (qRT-PCR) validation. circRNA-miRNA interaction network was constructed. ResultsA total of 17,620 circRNA transcripts were examined by RNA-seq, and 208 DE circrRNAs were identified between AG and CG, of which 92 were upregulated and 116 were downregulated. The expression trend in the four selected circRNAs was validated by qRT-PCR, which was consistent with the RNA-seq results. Dysregulated circRNAs may be involved in stenosis by mediating focal adhesion kinase (FAK) pathway. ConclusionOur study revealed abnormal circRNA expression in stenosed tissues of the AVF outflow vein, which was functionally classified. The results indicated that DE circRNAs in the stenosed tissues of AVF and their related FAK pathway have potential to be targets for the prevention and treatment of AVF failure.

Danlou Tablets Inhibit Atherosclerosis in Apolipoprotein E-Deficient Mice by Inducing Macrophage Autophagy: The Role of the PI3K-Akt-mTOR Pathway

Atherosclerosis (AS) is a type of chronic vascular disease, and its etiology is not yet fully understood. AS is characterized by lipid deposition, atherosclerotic plaque formation, vascular stenosis or even complete blockage of the blood vessel wall. Clinical studies have shown that Danlou tablets (DLTs) can improve the heart function, quality of life, and prognosis of patients with coronary heart disease and myocardial infarction. However, its mechanism of action remains unknown. Our study revealed that DLTs ameliorated ApoE−/−AS mouse aortic atherosclerotic plaques [hematoxylin-eosin (HE) staining and small animal ultrasound] and reduced CD68+ macrophage infiltration, the expression of the inflammatory factor interferon-gamma (IFN-γ), vascular smooth muscle α-actin, and serum lipid levels. In vitro, in the macrophage foaming model, DLTs partially restored the activity of RAW264.7 cells, reduced the uptake of lipid droplets, and inhibited lipid droplet accumulation and apoptosis within BMDMs. We also found that Torin1, an autophagy agonist, reduced intracellular lipid deposition in BMDMs, as did DLTs. Moreover, DLTs upregulated the expression of the autophagy-related protein LC3II and decreased p62 accumulation in RAW264.7 cells. DLTs also inhibited the phosphorylation of p-PI3K, p-Akt, and p-mTOR, leading to upregulated autophagy in RAW264.7 cells. In summary, our results suggested that DLTs can promote autophagy in macrophages by inhibiting the PI3K/Akt/mTOR signaling pathway, thereby reducing foam cell formation and improving atherosclerosis.

Deep Learning-Based Computed Tomography Images for Quantitative Measurement of the Correlation between Epicardial Adipose Tissue Volume and Coronary Heart Disease

The epicardial adipose tissue volume (EATV) was quantitatively measured by deep learning-based computed tomography (CT) images, and its correlation with coronary heart disease (CHD) was investigated in this study. 150 patients who underwent coronary artery CT examination in hospital were taken as research objects. Besides, patients from the observation group (group A) suffered from vascular stenosis, while patients from the control group (group B) had no vascular stenosis. The deep convolutional neural network model was applied to construct deep learning algorithm, and deep learning-based CT images were adopted to quantitatively measure EATV. The results showed that the sensitivity, specificity, accuracy, and area under the curve (AUC) of the deep learning algorithm were 0.8512, 0.9899, 0.9623, and 0.9813, respectively. By comparison, the correlation results of the traditional George algorithm, Aslani algorithm, and Lahiri algorithm were all lower than those of the deep learning algorithm, and the difference was statistically substantial ( P < 0.05 ). The epicardial adipose tissue volume of the observation group (114.23 ± 55.46) was higher markedly than the volume of the control group (92.65 ± 43.28), with a statistically huge difference ( P < 0.05 ). The r values of EATV with plaque properties and the number of stenosed coronary vessels were 0.232 and 0.268 in turn, both showing significant positive correlation. In conclusion, the sensitivity and other index values of deep learning algorithm were improved greatly compared with traditional algorithm. CT images based on deep learning algorithm achieved good blood vessel segmentation effects. In addition, EATV was closely related to the development of CHD.