321/321L stainless steel capillary tube Association of white matter hyperintensity with coronary artery calcification in healthy individuals: a cross-sectional study

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White matter hyperintensity (WWH) is a common finding on magnetic resonance imaging (MRI) of the brain and is known to reflect small vessel disease in the brain. The aim of our study was to investigate the association of coronary artery calcium (CCA) with WMH and to elucidate the relationship between WMH and risk factors for atherosclerosis in a large healthy population. This retrospective study included 1337 people who underwent brain MRI and computed tomography with CAC assessment at a tertiary hospital medical center. The GVM of the brain was defined as a Fazekas score of more than 2 points on MRI of the brain. Intracranial arterial stenosis (ICAS) was also assessed and confirmed when angiography showed more than 50% stenosis. Associations of risk factors, CAC and ICAS scores with brain HBG were assessed using multivariate regression analysis. In a multivariate analysis, categories with higher CAC scores showed an increased association with periventricular and profound hypertension in a dose-dependent manner. The presence of ICAS was also significantly associated with brain HBH, and among clinical variables, age and hypertension were independent risk factors. In conclusion, in healthy populations, CAC was significantly associated with brain WMH, which may provide evidence to identify individuals at risk for brain WMH with reference to CAC score.

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321/321L stainless steel 8*0.2 capillary tube

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321/321L stainless steel 8*0.2 capillary tube

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321/321L stainless steel 8*0.2 capillary tube

White matter hyperintensity (WWH) is a common finding in T2-weighted and fluid-attenuated magnetic resonance imaging (MRI) inversion recovery (FLAIR) sequences of the brain1,2. Although the exact pathophysiological mechanism of HHH is unknown, it has been shown to be associated with risk factors for atherosclerosis such as aging, hypertension, diabetes, smoking, and obesity, suggesting a contribution of vascular mechanisms to the development of HHH3,4,5,6. ,7,8,9,10. Pathological studies have also shown that HHH is caused by impaired vascular integrity, thus confirming that HHH is a reflection of small vessel disease in the brain11. In addition, SHG is of clinical importance as it has been shown to affect the incidence and prognosis of various neurological disorders, including cognitive decline, dementia, depression, gait disturbance, and stroke12,13,14,15,16,17,18,19 , 20, 21, 22, 23.
Coronary calcium assessment (CAC) is considered a convenient and reliable measure of an individual’s cumulative susceptibility to atherosclerosis and has been shown to be associated with ischemic stroke and cranial artery stenosis, as well as coronary heart disease24,25. Small cerebral vessel disease readily coexists with atherosclerosis of the large intracranial arteries because small perforating vessels supplying the white matter originate from the large basilar artery. Many studies have identified an association between SHH and risk factors for atherosclerosis or carotid atherosclerosis, however, only a few studies have focused on the relationship between SAS burden and SHH, and these studies have only been conducted in older adults or men 29, 30, 31 . 32.
With the increasing availability of neuroimaging in recent years, the high prevalence and clinical significance of HHH is increasingly recognized as a predictor of cognitive decline and stroke outcome19,20,21,22,23. The motivation for this study was that if the CAC score could be used in clinical practice to predict the risk of SHH, a predictor of various neurological disorders, it could be a convenient and useful tool to determine the possible benefit of other human studies, such as MRI of the brain19,20,21,22,23. We hypothesized that HHH is closely related to CCA burden, an indicator of atherosclerosis, in a large number of healthy individuals in the general population. In addition, we sought to help understand the mechanisms underlying the development of HHH by identifying relevant clinical risk factors. Thus, the main goal of this study was to investigate the association of CAC with WMH in a healthy population. Secondly, the purpose of this study was to elucidate the relationship between SHG and risk factors for atherosclerosis.
This study is a cross-sectional retrospective study based on the general population. We searched electronic databases of participants who underwent medical examinations, including brain MRI and magnetic resonance angiography (MRA), at Gangbuk Samsung Hospital General Medical Centers in Seoul and Suwon between January 2016 and December 2019. The population included subjects who underwent CAC computed tomography (CT) and brain imaging as part of comprehensive physical examinations, which are common health screening methods in Korea. For reference, Korean law requires all employees to undergo regular annual or biennial medical check-ups, so many participants are employees or family members of employees of various companies or local government organizations.
Of the 3983 people, 2646 were excluded for the following reasons: a) disagreement with the use of medical information for any research purposes in a self-administered questionnaire before the examination (n = 376); if repeat tests were performed during the period (n = 43), individuals with repeat tests were excluded, and CT and brain imaging with CAC assessment performed on the same day or at the most recent time interval were selected for the study; (c) known dementia, Parkinson’s disease. history, hydrocephalus, previous brain surgery, brain tumor, moyamoya disease, stroke or hemorrhage (n = 47); (d) individuals with significant brain lesions detected by image analysis, for example, due to prior encephalomalacia due to stroke (larger diameter measurement greater than 15 mm) or old traumatic hemorrhage, arteriovenous malformation, or neoplastic lesion (n = 46); (e) persons with MRI or MRA of insufficient quality for image analysis (n = 2); (f) individuals who did not undergo CT on the CAC scale (n = 1796); (g) individuals who lacked numerical data required for analysis, including body mass index (BMI) and homocysteine ​​levels (n = 336). The flowchart for recruiting study participants is shown in Figure 1.
Include a flowchart of participants. MRI magnetic resonance imaging, MRA magnetic resonance angiography, periventricular white matter hyperintensity PVWMH, deep white matter hyperintensity DWMH.
Thus, 1337 subjects (mean age 51.63 ± 9.20 years, age range 20-89 years, 1157 [86.54%] male patients) were included in this study. All participants were retrospectively assessed for clinical and radiographic findings. This study was conducted in accordance with the principles of the Declaration of Helsinki and was approved by the Institutional Review Board (IRB) of Gangbuk Samsung Hospital (IRB No. 2020-12-036-006). The IRB at Kangbuk Samsung Hospital waived the informed consent requirement due to the use of de-identified data and retrospective study design. All research methods were performed in accordance with the relevant guidelines and regulations.
We collected individual clinical data including gender, age, BMI, systolic and diastolic blood pressure, smoking history, physical activity, and diagnosis and treatment of hypertension, diabetes, hyperlipidemia, and coronary heart disease. From standardized self-administered questionnaires, we collected data on each individual’s medical history and history of smoking, as well as whether they regularly engaged in vigorous physical activity for more than 10 minutes at least 3 times a week.
Because all participants were scheduled to be examined at Ganbuk Samsung Hospital General Medical Center, laboratory tests were performed on the same day as MRI of the brain and MRA after a 12-hour fast, and data included glucose, glycated hemoglobin (HbA1c), levels of total cholesterol, LDL cholesterol, HDL cholesterol, triglycerides and homocysteine.
Arterial hypertension was defined as current intake of antihypertensive drugs, systolic blood pressure ≥ 140 mmHg. or diastolic blood pressure ≥ 90 mmHg33. Diabetes was defined as current antidiabetic drug use, fasting blood glucose ≥ 126 mg/dL, or HbA1c ≥ 6.5%. Dyslipidaemia was defined as current use of lipid-lowering drugs, total cholesterol ≥240 mg/dl, low-density lipoprotein cholesterol ≥160 mg/dl, high-density lipoprotein cholesterol <40 mg/dl, or triglycerides ≥200 mg/dl35.
All participants underwent MRI of the brain and MRA with an eight-channel head coil using a 1.5 T MRI scanner (Optima MR360, GE Healthcare, Milwaukee, Wisconsin or Signa HDxt, GE Healthcare, Milwaukee, Wisconsin). The imaging protocol consisted of axial T1-weighted images (repetition time [TR]/echo time [TE] = 417–450/9 ms or 400–450/10 ms), T2-weighted images (TR/TE = 4343–4694) . /100-110 ms or 4084-4494/95-104 ms), FLAIR images (TR/TE = 11000/127-138 ms or 8800/128-130 ms) and 3D time-of-flight (TOF) images (TR /TE = 28/7 ms or 27/3 ms, slice thickness = 1.2 mm). Slice thickness was 5 mm for all imaging protocols except TOF MRA.
The degree of periventricular and deep WMH was assessed separately according to each subject’s Fazekas scale1, as shown in Supplementary Figure 1 online. PVWMH was scored as follows: 0=none, 1=cap or thin lining, 2=smooth halo, 3=irregular periventricular hyperintensity extending into deep white matter. DWMH is classified as follows: 0 = absent, 1 = punctate, 2 = lesions begin to coalesce, 3 = large areas of confluence. Because brain HBH grade 2 or higher is known to be clinically significant because it is prone to symptoms and progression, we divided patients with Fazekas scores of 2 and 3 into PVBVH and DGBV36,37.
The TOF MRA analysis, based on the warfarin-aspirin symptomatic intracranial disease (WASID) approach, defines intracranial artery stenosis (ICAS) as intracranial artery stenosis greater than 50%38. The vessels included in the analysis were the internal carotid artery from the cavernous segment to the M2 segment of the middle cerebral artery, the A2 segment of the anterior cerebral artery, the P2 segment of the posterior cerebral artery, the basilar artery, and the intracranial artery. segment of the vertebral artery.
All radiological evaluations were performed by a neuroradiologist (JYK), who was not aware of all clinical and laboratory data. The reliability of the visual scale between observers was assessed by a second trained radiographer (JYC) on 700 randomly selected subjects and within a 2-month interval after the first reading. Assess the reliability within the observer. Visual assessments of PVWMH, DWMH, and ICAS showed good inter-expert (Cohen-weighted kappa: 0.7, 0.81, and 0.67, respectively; n = 700) and within-expert (Cohen-weighted kappa: 0.92, 0.88, and 0 .65, respectively; n = 1339) protocol.
CAC score was assessed in individuals who underwent CT to assess CAC within 5 years of brain MRI and MRA39. Of the 1,337 people, 686 had a brain scan on the same day and 651 on another day within 5 years.
The Seoul and Suwon centers used mAc (310 mA × 0.4 s) tube current at 2.5 mm thickness, 400 ms rotation time, 120 kV tube voltage, and 124 ECG-dependent dose modulation. According to Agatston et al.40, CAC was calculated from the 4 major epicardial coronary arteries (left main, left anterior descending, left circumflex, and right coronary arteries). The CT technician was blinded by any information about the subject and the CAC score was automatically determined using the HEARTBEAT-CS software (Philips, Cleveland, OH, USA). CAC scores are divided into three groups: 0, 1-100, and >100.
Baseline characteristics were compared between subjects with and without cerebral WMH using χ2 test for categorical variables and Student’s t-test or Mann-Whitney test for continuous variables, as appropriate. Normally distributed variables are presented as mean ± standard deviation, while non-normally distributed variables are presented as median and interquartile range. Dummy variables were introduced for missing values ​​of categorical variables.
Multivariate logistic regression analysis was performed to calculate odds ratios (ORs) and 95% confidence intervals (CIs) to assess the relationship between brain WMH and CAC scores and risk factors for atherosclerosis. Since HHH prevalence increases with age and varies by sex, all multivariate analyzes performed to assess associations between other variables and HHH18 adjusted for age and sex. Another multivariate logistic regression model was used to assess whether CAC score has an independent association with brain SHG, even after adjusting for atherosclerosis risk factors and ICAS as confounding factors that have been reported to be associated with SHH in previous reports10, 26, 27, 41. Model 1 was adjusted for age and gender, Model 2 was adjusted for age, gender, and risk factors for atherosclerosis (BMI, hypertension, diabetes, dyslipidaemia, current or former smoker, regular exercise, coronary disease history of heart disease and cystine levels). adjusted; Model 3 was adjusted for age, gender, risk factors for atherosclerosis, and presence of ICAS. The presence of brain WMH was assessed according to CAC score categories using CAC score 0 as a benchmark.
Statistical analysis was performed using Stata version 16.1 (StataCorp, College Station, Texas, USA) and R studio version 3.6.3 (RStudio, Boston, Massachusetts, USA). Two-tailed p-values ​​<0.05 were considered statistically significant.
The baseline characteristics of 1337 individuals are shown in Table 1. The mean age of the participants, estimated from the time of MRI of the brain, was 51.63 ± 9.20 years, and 86.54% of the study population were male. The main risk factors for atherosclerosis in this cohort were current or past smoking (57.82%), followed by dyslipidemia (51.76%) and hypertension (28.65%). In terms of radiological variables, 158 patients (11.82%) had PVWMH, 148 (11.07%) had DWMH, and 21 (1.57%) had ICAS. In terms of CAC score, 849 subjects (63.5%) had a CAC score of 0, 332 (24.83%) had a score between 0 and 100, and 156 (11.67%) had a score greater than 100.
In a univariate analysis, age, gender, and most risk factors for atherosclerosis, except for BMI, dyslipidemia, and current or past smoking, were significantly associated with the presence of brain HHH (p < 0.05) (Table 2). Individuals with PVWMH and DWMH were older and had a greater burden of hypertension, diabetes, history of coronary artery disease, CAC, and ICAS than individuals without PVWMH and DWMH. In a univariate analysis, a higher proportion of women and subjects in the WMH group reported that they exercised regularly. The median (interquartile range; IQR) CAC was 62 (IQR 0-269.5) in the PVWMH group and 46.5 (IQR 0-192) in the DWMH group. The distribution of CAC categories by the presence of PVWMH and DWMH is shown in fig. 2. The proportion of categories with higher CAC scores increased with the degree of comorbid WMH.
Percentage of CAC score categories based on having PVMWH (a), DWMH (b), and PVWMH or DWMH (c). Calcification of the coronary arteries of the SAS, white matter hyperintensity SHG, periventricular white matter hyperintensity HVBV, deep white matter hyperintensity SHVH.
Multivariate regression analysis adjusted for age (OR 1.13; 95% CI 1.10-1.16; OR 1.11; 95% CI 1.08-1.14) and hypertension (OR 2.29; 95% CI 1.50–3.50, OR 1.98, 95% CI 1.30–3.02). respectively) is PVWMH after adjusting for age, sex, atherosclerosis risk factors (BMI, hypertension, diabetes, dyslipidemia, current or former smoker, exercise, history of coronary artery disease, and homocysteine ​​levels) and independent significant clinical predictors of DWMH and ICAS (all p < 0.05) (Table 3). There was no significant association between adjusted WMH and sex, BMI, diabetes or dyslipidemia, history of smoking, or regular exercise.
Even after adjusting for confounding factors, categories with higher CAC scores showed an increased association with brain GMI in a dose-dependent manner compared to reference categories with a CAC score of 0. For PVWMH and DWMH, categories with a CAC score greater than 100 (OR 5.45; 95 % CI 3.11–9.54 or 3.66; 95% CI 2.10–6.38) showed greater association than categories with CAC scores of 0 to 100 (OR 2.22; 95% CI). 1.36–3.61, OR 1.59; 95% CI 0.98–2.58). When comparing association with CAC between the PVWMH and DWMH groups, all three multivariate analysis models showed higher associations with PVWMH in both CAC scoring categories. The presence of ICAS also showed a significant association with PVWMH (OR 3.97, 95% CI 1.31-12.06) and DWMH (OR 7.11, 95% CI 2.33-21.77).
Variance inflation coefficients were calculated for all regression models to assess potential multicollinearity, and no problematic multicollinearity was found (Supplementary Table 1 online).
In this study, the risk of cerebral SHH increased with increasing CAC score in a dose-dependent manner, and the results were statistically significant after adjusting for comorbid risk factors for atherosclerosis. Our results are consistent with previous studies showing an association between CAC and brain MRI abnormalities, further supporting the association of CAC with cerebral small vessel atherosclerosis as well as large vessel atherosclerosis29,30,31,32.
Interestingly, in all three multivariate analysis models, the ORs for CAC scores were slightly higher in the PVWMH group than in the DWMH group. This difference may be due to the fact that differences in pathophysiological processes and risk factors are assumed between PVWMH and DWMH11,42,43. PVWMHs are often symmetrically present in both cerebral hemispheres, suggesting a diffuse perfusion disorder, while DWMHs often have an asymmetric distribution, suggesting that they are caused by a focal perfusion disorder. Since the periventricular region is supplied by the terminal arteries of the long medulla and perforating branches [45], it is especially vulnerable when autoregulatory mechanisms for maintaining constant cerebral perfusion are impaired by arteriosclerosis or lipoid hyalinosis [46, 47, 48, 49]. Hypoperfusion and ischemia develop. In particular, several studies have shown that manifestations of systemic atherosclerosis, such as hypertension, diabetes mellitus, and the presence of aortic atherosclerosis, are predominantly associated with PVWMH50,51,52,53, supporting our findings that CAC score, age, and arterial hypertension had higher ORs for PVWMH than for DWMH in all models.
In this study, the presence of ICAS was closely associated with brain HHH, a result that could be explained by the fact that significant stenosis of large intracranial arteries reduces local or regional cerebral perfusion, and this chronic hypoperfusion contributes to fatty hyalinosis, which are the underlying mechanisms. development of WMH 26.54 .
Consistent with many previous studies3, 27, 28, 55 conducted in various ethnic groups, our study also showed that age and hypertension were independently and significantly associated with brain HBG in a multivariate analysis. However, the association between HHH and other risk factors for atherosclerosis has shown mixed results in previous reports27,28,37,56. The reasons for these different results may be due to differences in study populations, criteria for determining risk factors, or methods used to analyze WMH, which require further study.
Several limitations of this study should be noted. First, this is a retrospective study of an Asian population in a monobrand medical center. There may be a risk of selection bias as a large number of study participants were of working age, and more than half of them were male, due to the unique characteristics of South Korea, which requires companies to regularly screen their employees. To reduce bias in cohort studies, long-term, longitudinal, and prospective studies such as the Rotterdam Study57 or the Framingham Study58 should be conducted. Previously, there have been many reports using the Rotterdam Study to focus on the relationship between brain SHG and various risk factors for atherosclerosis Association between cohorts and studies Framingham 4, 59, 60, 61, 62, 63. However, since none of the existing studies have focused on the association between GIBD and CCA in normal populations, our results are of clinical relevance. Second, since MRI analysis is performed visually by radiologists, objectivity may not be enough. However, we tried to overcome this limitation by including a large number of participants and defining subjects with at least moderate or higher WMH as a positive group. In addition, we performed inter-observer and intra-observer reliability tests, and the results showed good agreement. It has also previously been reported that there is a high correlation between visual assessment methods using the Fazekas scale and volumetric analysis used to assess the grade of WMH64,65. Third, individuals with brain lesions were excluded using a self-administered questionnaire that included previous medical history and image analysis of individuals with overt disease and might not filter out individuals with subclinical disease. In addition, the brain MRI program for health screening in our hospital does not include enhanced images, so there is a possibility of missing the diagnosis of pathological brain enhancement, which is not obvious on T1-weighted, T2-weighted and FLAIR images, and the accuracy is not high. Compared to MRA enhancement, the presence of ICAS was rated as relatively low. Fourth, since most of the participants in this study were from a healthy population and most did not have any disease, the proportion of subjects suffering from ICAS was relatively small.
However, this study included more healthy people than previous studies looking at the association between SHG and SAS, and to our knowledge, this is the first study to include healthy adults without specifying gender or age. Limitations of the study 31,32.
The importance of brain WMH and various associated neurological disorders such as dementia and stroke is highlighted due to the dramatic increase in availability of brain imaging and life expectancy, but these diseases remain undefeated. The presence of HHH lesions in the brain is associated with more severe cognitive decline, dementia, depression, and stroke, and there is growing evidence that controlling certain risk factors for atherosclerosis can prevent HHH12, 13, 14, 15, 16, 17, 18, 19 , 20, 21, 22, 23, 66, 67, 68, 69. Thus, our results may provide evidence for screening individuals at risk for brain HHH, an important risk factor and predictor for various neurological diseases, with reference to the score CAC, thereby identifying patients who can benefit from aggressive diagnostic and therapeutic interventions. whether CAC plays an important and independent role in the development of WMH in longitudinal and prospective studies from different regions, age groups and ethnic groups, and other MRI markers of cerebral small vessel disease should also be included for a comprehensive understanding.
In conclusion, CAC score as well as age and hypertension were significantly associated with brain WMH in a large healthy population. The CAC score is an indicator of atherosclerotic burden and has a potential role in predicting the risk of cerebral HHH in clinical practice.
The data set analyzed in this study is not publicly available because it contains sensitive personal information of individuals. These data are available from Kangbuk Samsung Hospital’s Total Healthcare Center upon reasonable request from qualified human investigators. Each request will be reviewed by the Gangbuk Samsung Hospital Institutional Review Board and investigators will be able to access the data in accordance with the terms of the approval.
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