Machine learning slice-wise whole-lung CT emphysema score correlates with airway obstruction.

OBJECTIVES: Quantitative CT imaging is an important emphysema biomarker, especially in smoking cohorts, but does not always correlate to radiologists' visual CT assessments. The objectives were to develop and validate a neural network-based slice-wise whole-lung emphysema score (SWES) for chest CT, to validate SWES on unseen CT data, and to compare SWES with a conventional quantitative CT method. MATERIALS AND METHODS: Separate cohorts were used for algorithm development and validation. For validation, thin-slice CT stacks from 474 participants in the prospective cross-sectional Swedish CArdioPulmonary bioImage Study (SCAPIS) were included, 395 randomly selected and 79 from an emphysema cohort. Spirometry (FEV1/FVC) and radiologists' visual emphysema scores (sum-visual) obtained at inclusion in SCAPIS were used as reference tests. SWES was compared with a commercially available quantitative emphysema scoring method (LAV950) using Pearson's correlation coefficients and receiver operating characteristics (ROC) analysis. RESULTS: SWES correlated more strongly with the visual scores than LAV950 (r = 0.78 vs. r = 0.41, p < 0.001). The area under the ROC curve for the prediction of airway obstruction was larger for SWES than for LAV950 (0.76 vs. 0.61, p = 0.007). SWES correlated more strongly with FEV1/FVC than either LAV950 or sum-visual in the full cohort (r = - 0.69 vs. r = - 0.49/r = - 0.64, p < 0.001/p = 0.007), in the emphysema cohort (r = - 0.77 vs. r = - 0.69/r = - 0.65, p = 0.03/p = 0.002), and in the random sample (r = - 0.39 vs. r = - 0.26/r = - 0.25, p = 0.001/p = 0.007). CONCLUSION: The slice-wise whole-lung emphysema score (SWES) correlates better than LAV950 with radiologists' visual emphysema scores and correlates better with airway obstruction than do LAV950 and radiologists' visual scores. CLINICAL RELEVANCE STATEMENT: The slice-wise whole-lung emphysema score provides quantitative emphysema information for CT imaging that avoids the disadvantages of threshold-based scores and is correlated more strongly with reference tests than LAV950 and reader visual scores. KEY POINTS: • A slice-wise whole-lung emphysema score (SWES) was developed to quantify emphysema in chest CT images. • SWES identified visual emphysema and spirometric airflow limitation significantly better than threshold-based score (LAV950). • SWES improved emphysema quantification in CT images, which is especially useful in large-scale research.

Consequences of Using Post- or Prebronchodilator Reference Values in Interpreting Spirometry.

Rationale: Postbronchodilator spirometry is used for the diagnosis of chronic obstructive pulmonary disease. However, prebronchodilator reference values are used for spirometry interpretation. Objectives: To compare the resulting prevalence rates of abnormal spirometry and study the consequences of using pre- or postbronchodilator reference values generated within SCAPIS (Swedish CArdioPulmonary bioImage Study) when interpreting postbronchodilator spirometry in a general population. Methods: SCAPIS reference values for postbronchodilator and prebronchodilator spirometry were based on 10,156 and 1,498 never-smoking, healthy participants, respectively. We studied the associations of abnormal spirometry, defined by using pre- or postbronchodilator reference values, with respiratory burden in the SCAPIS general population (28,851 individuals). Measurements and Main Results: Bronchodilation resulted in higher predicted medians and lower limits of normal (LLNs) for FEV1/FVC ratios. The prevalence of postbronchodilator FEV1/FVC ratio lower than the prebronchodilator LLN was 4.8%, and that of postbronchodilator FEV1/FVC lower than the postbronchodilator LLN was 9.9%, for the general population. An additional 5.1% were identified as having an abnormal postbronchodilator FEV1/FVC ratio, and this group had more respiratory symptoms, emphysema (13.5% vs. 4.1%; P < 0.001), and self-reported physician-diagnosed chronic obstructive pulmonary disease (2.8% vs. 0.5%, P < 0.001) than subjects with a postbronchodilator FEV1/FVC ratio greater than the LLN for both pre- and postbronchodilation. Conclusions: Pre- and postbronchodilator spirometry reference values differ with regard to FEV1/FVC ratio. Use of postbronchodilator reference values doubled the population prevalence of airflow obstruction; this was related to a higher respiratory burden. Using postbronchodilator reference values when interpreting postbronchodilator spirometry might enable the identification of individuals with mild disease and be clinically relevant.

Prevalence of Subclinical Coronary Artery Atherosclerosis in the General Population.

BACKGROUND: Early detection of coronary atherosclerosis using coronary computed tomography angiography (CCTA), in addition to coronary artery calcification (CAC) scoring, may help inform prevention strategies. We used CCTA to determine the prevalence, severity, and characteristics of coronary atherosclerosis and its association with CAC scores in a general population. METHODS: We recruited 30 154 randomly invited individuals age 50 to 64 years to SCAPIS (the Swedish Cardiopulmonary Bioimage Study). The study includes individuals without known coronary heart disease (ie, no previous myocardial infarctions or cardiac procedures) and with high-quality results from CCTA and CAC imaging performed using dedicated dual-source CT scanners. Noncontrast images were scored for CAC. CCTA images were visually read and scored for coronary atherosclerosis per segment (defined as no atherosclerosis, 1% to 49% stenosis, or ≥50% stenosis). External validity of prevalence estimates was evaluated using inverse probability for participation weighting and Swedish register data. RESULTS: In total, 25 182 individuals without known coronary heart disease were included (50.6% women). Any CCTA-detected atherosclerosis was found in 42.1%; any significant stenosis (≥50%) in 5.2%; left main, proximal left anterior descending artery, or 3-vessel disease in 1.9%; and any noncalcified plaques in 8.3% of this population. Onset of atherosclerosis was delayed on average by 10 years in women. Atherosclerosis was more prevalent in older individuals and predominantly found in the proximal left anterior descending artery. Prevalence of CCTA-detected atherosclerosis increased with increasing CAC scores. Among those with a CAC score >400, all had atherosclerosis and 45.7% had significant stenosis. In those with 0 CAC, 5.5% had atherosclerosis and 0.4% had significant stenosis. In participants with 0 CAC and intermediate 10-year risk of atherosclerotic cardiovascular disease according to the pooled cohort equation, 9.2% had CCTA-verified atherosclerosis. Prevalence estimates had excellent external validity and changed marginally when adjusted to the age-matched Swedish background population. CONCLUSIONS: Using CCTA in a large, random sample of the general population without established disease, we showed that silent coronary atherosclerosis is common in this population. High CAC scores convey a significant probability of substantial stenosis, and 0 CAC does not exclude atherosclerosis, particularly in those at higher baseline risk.

Pubertal Body Mass Index Change Is Associated With Adult Coronary Atherosclerosis and Acute Coronary Events in Men.

OBJECTIVE: The aim with the present study was to evaluate the association between pubertal body mass index (BMI) change and adult coronary artery calcification (CAC) score and risk of acute coronary events. APPROACH AND RESULTS: We included 37 672 men from the BMI Epidemiology Study and calculated their pubertal BMI change (BMI at 20 years−BMI at 8 years). Coronary artery computed tomography analysis of CAC score, midlife BMI, and major risk factors for coronary heart disease were available for a sub-cohort through linkage with the SCAPIS (Swedish Cardio Pulmonary Bioimage Study) cohort (n=922). Information on first acute coronary events was retrieved from Swedish national registers (n=37 672, events n=1873). Pubertal BMI change (odds ratio per SD increase, 1.32 [1.14­1.52]), but not childhood BMI, was associated with middle age CAC score ≥1. This association for pubertal BMI change was maintained after adjustment for midlife BMI at CAC analysis and in a model including major cardiovascular risk factors. Individuals who became overweight during puberty (hazard ratio, 2.11 [1.79­2.49]), but not those overweight at 8 years who normalized their weight during puberty, had substantially increased risk of acute coronary events compared with men who were never overweight. Among subjects with an acute coronary event, individuals with pubertal onset overweight were at increased risk of death due to the event. CONCLUSIONS: Pubertal BMI change is an independent predictor of CAC score and risk of acute coronary events in adult men. Excessive BMI increase during puberty may initiate the coronary atherosclerotic process, thereby increasing the risk and severity of adult acute coronary events.

Accelerometer derived physical activity patterns in 27.890 middle-aged adults: The SCAPIS cohort study.

The present study aims to describe accelerometer-assessed physical activity (PA) patterns and fulfillment of PA recommendations in a large sample of middle-aged men and women, and to study differences between subgroups of socio-demographic, socio-economic, and lifestyle-related variables. A total of 27 890 (92.5% of total participants, 52% women, aged 50-64 years) middle-aged men and women with at least four days of valid hip-worn accelerometer data (Actigraph GT3X+, wGT3X+ and wGT3X-BT) from the Swedish CArdioPulmonary bioImage Study, SCAPIS, were included. In total, 54.5% of daily wear time was spent sedentary, 39.1% in low, 5.4% in moderate, and only 0.1% in vigorous PA. Male sex, higher education, low financial strain, born in Sweden, and sedentary/light working situation were related to higher sedentary time, but also higher levels of vigorous PA. High BMI and having multiple chronic diseases associated strongly with higher sedentary time and less time in all three PA intensities. All-year physically active commuters had an overall more active PA pattern. The proportion fulfilling current PA recommendations varied substantially (1.4% to 92.2%) depending on data handling procedures and definition used. Twenty-eight percent was defined as having an "at-risk" behavior, which included both high sedentary time and low vigorous PA. In this large population-based sample, a majority of time was spent sedentary and only a fraction in vigorous PA, with clinically important variations between subgroups. This study provides important reference material and emphasizes the importance of a comprehensive assessment of all aspects of the individual PA pattern in future research and clinical practice.

Multi-Reader-Multi-Split Annotation of Emphysema in Computed Tomography.

Emphysema is visible on computed tomography (CT) as low-density lesions representing the destruction of the pulmonary alveoli. To train a machine learning model on the emphysema extent in CT images, labeled image data is needed. The provision of these labels requires trained readers, who are a limited resource. The purpose of the study was to test the reading time, inter-observer reliability and validity of the multi-reader-multi-split method for acquiring CT image labels from radiologists. The approximately 500 slices of each stack of lung CT images were split into 1-cm chunks, with 17 thin axial slices per chunk. The chunks were randomly distributed to 26 readers, radiologists and radiology residents. Each chunk was given a quick score concerning emphysema type and severity in the left and right lung separately. A cohort of 102 subjects, with varying degrees of visible emphysema in the lung CT images, was selected from the SCAPIS pilot, performed in 2012 in Gothenburg, Sweden. In total, the readers created 9050 labels for 2881 chunks. Image labels were compared with regional annotations already provided at the SCAPIS pilot inclusion. The median reading time per chunk was 15 s. The inter-observer Krippendorff's alpha was 0.40 and 0.53 for emphysema type and score, respectively, and higher in the apical part than in the basal part of the lungs. The multi-split emphysema scores were generally consistent with regional annotations. In conclusion, the multi-reader-multi-split method provided reasonably valid image labels, with an estimation of the inter-observer reliability.

A deep multi-stream model for robust prediction of left ventricular ejection fraction in 2D echocardiography.

We propose a deep multi-stream model for left ventricular ejection fraction (LVEF) prediction in 2D echocardiographic (2DE) examinations. We use four standard 2DE views as model input, which are automatically selected from the full 2DE examination. The LVEF prediction model processes eight streams of data (images + optical flow) and consists of convolutional neural networks terminated with transformer layers. The model is made robust to missing, misclassified and duplicate views via pre-training, sampling strategies and parameter sharing. The model is trained and evaluated on an existing clinical dataset (12,648 unique examinations) with varying properties in terms of quality, examining physician, and ultrasound system. We report [Formula: see text] and mean absolute error = 4.0% points for the test set. When evaluated on two public benchmarks, the model performs on par or better than all previous attempts on fully automatic LVEF prediction. Code and trained models are available on a public project repository .

NoiseNet, a fully automatic noise assessment tool that can identify non-diagnostic CCTA examinations.

Image noise and vascular attenuation are important factors affecting image quality and diagnostic accuracy of coronary computed tomography angiography (CCTA). The aim of this study was to develop an algorithm that automatically performs noise and attenuation measurements in CCTA and to evaluate the ability of the algorithm to identify non-diagnostic examinations. The algorithm, "NoiseNet", was trained and tested on 244 CCTA studies from the Swedish CArdioPulmonary BioImage Study. The model is a 3D U-Net that automatically segments the aortic root and measures attenuation (Hounsfield Units, HU), noise (standard deviation of HU, HUsd) and signal-to-noise ratio (SNR, HU/HUsd) in the aortic lumen, close to the left coronary ostium. NoiseNet was then applied to 529 CCTA studies previously categorized into three subgroups: fully diagnostic, diagnostic with excluded parts and non-diagnostic. There was excellent correlation between NoiseNet and manual measurements of noise (r = 0.948; p < 0.001) and SNR (r = 0.948; <0.001). There was a significant difference in noise levels between the image quality subgroups: fully diagnostic 33.1 (29.8-37.9); diagnostic with excluded parts 36.1 (31.5-40.3) and non-diagnostic 42.1 (35.2-47.7; p < 0.001). Corresponding values for SNR were 16.1 (14.0-18.0); 14.0 (12.4-16.2) and 11.1 (9.6-14.0; p < 0.001). ROC analysis for prediction of a non-diagnostic study showed an AUC for noise of 0.73 (CI 0.64-0.83) and for SNR of 0.80 (CI 0.71-0.89). In conclusion, NoiseNet can perform noise and SNR measurements with high accuracy. Noise and SNR impact image quality and automatic measurements may be used to identify CCTA studies with low image quality.

Self-Report Tool for Identification of Individuals With Coronary Atherosclerosis: The Swedish CardioPulmonary BioImage Study.

BACKGROUND: Coronary atherosclerosis detected by imaging is a marker of elevated cardiovascular risk. However, imaging involves large resources and exposure to radiation. The aim was, therefore, to test whether nonimaging data, specifically data that can be self-reported, could be used to identify individuals with moderate to severe coronary atherosclerosis. METHODS AND RESULTS: We used data from the population-based SCAPIS (Swedish CardioPulmonary BioImage Study) in individuals with coronary computed tomography angiography (n=25 182) and coronary artery calcification score (n=28 701), aged 50 to 64 years without previous ischemic heart disease. We developed a risk prediction tool using variables that could be assessed from home (self-report tool). For comparison, we also developed a tool using variables from laboratory tests, physical examinations, and self-report (clinical tool) and evaluated both models using receiver operating characteristic curve analysis, external validation, and benchmarked against factors in the pooled cohort equation. The self-report tool (n=14 variables) and the clinical tool (n=23 variables) showed high-to-excellent discriminative ability to identify a segment involvement score ≥4 (area under the curve 0.79 and 0.80, respectively) and significantly better than the pooled cohort equation (area under the curve 0.76, P<0.001). The tools showed a larger net benefit in clinical decision-making at relevant threshold probabilities. The self-report tool identified 65% of all individuals with a segment involvement score ≥4 in the top 30% of the highest-risk individuals. Tools developed for coronary artery calcification score ≥100 performed similarly. CONCLUSIONS: We have developed a self-report tool that effectively identifies individuals with moderate to severe coronary atherosclerosis. The self-report tool may serve as prescreening tool toward a cost-effective computed tomography-based screening program for high-risk individuals.

Pre-diabetes is associated with attenuation rather than volume of epicardial adipose tissue on computed tomography.

The volume of epicardial adipose tissue (EATV) is increased in type-2 diabetes (T2D), while its attenuation (EATA) appears to be decreased. Similar patterns have been suggested in pre-diabetes, but data is scarce. In both pre-diabetes and T2D, any independent role of EATV and EATA in disease development remains to be proven, a task complicated by their substantial co-variation with other anthropometrics, e.g. BMI, waist circumference, and abdominal visceral adipose tissue (VAT). EATV and EATA was quantified in computed tomography (CT) images in a population study (n = 1948) using an automatic technique. Data was available on BMI, waist circumference, abdominal visceral adipose tissue (VAT) area, insulin resistance (IR) and glucose tolerance, the latter ranging from normal (NGT), over pre-diabetes (impaired fasting glucose [IFG, n = 414] impaired glucose tolerance [IGT, n = 321] and their combination [CGI, n = 128]), to T2D. EATV was increased in pre-diabetes, T2D and IR in univariable analyses and when adjusting for BMI, however not when adjusting for waist or VAT. EATA was reduced in pre-diabetes, T2D and IR in univariable analyses and when adjusting for BMI and waist, however not when adjusting for VAT. Adjustment for other co-variates had little influence on the results. In conclusion, EATV is increased and EATA reduced in pre-diabetes, T2D and IR, however, significant co-variation with other anthropometrics, especially VAT, obscures their function in disease development. The current results do not exclude a pathophysiological role of epicardial fat, but future studies need to adjust for anthropometrics, or focus on the microenvironment within the pericardial sac.

High-quality annotations for deep learning enabled plaque analysis in SCAPIS cardiac computed tomography angiography.

Background: Plaque analysis with coronary computed tomography angiography (CCTA) is a promising tool to identify high risk of future coronary events. The analysis process is time-consuming, and requires highly trained readers. Deep learning models have proved to excel at similar tasks, however, training these models requires large sets of expert-annotated training data. The aims of this study were to generate a large, high-quality annotated CCTA dataset derived from Swedish CArdioPulmonary BioImage Study (SCAPIS), report the reproducibility of the annotation core lab and describe the plaque characteristics and their association with established risk factors. Methods and results: The coronary artery tree was manually segmented using semi-automatic software by four primary and one senior secondary reader. A randomly selected sample of 469 subjects, all with coronary plaques and stratified for cardiovascular risk using the Systematic Coronary Risk Evaluation (SCORE), were analyzed. The reproducibility study (n = 78) showed an agreement for plaque detection of 0.91 (0.84-0.97). The mean percentage difference for plaque volumes was -0.6% the mean absolute percentage difference 19.4% (CV 13.7%, ICC 0.94). There was a positive correlation between SCORE and total plaque volume (rho = 0.30, p < 0.001) and total low attenuation plaque volume (rho = 0.29, p < 0.001). Conclusions: We have generated a CCTA dataset with high-quality plaque annotations showing good reproducibility and an expected correlation between plaque features and cardiovascular risk. The stratified data sampling has enriched high-risk plaques making the data well suited as training, validation and test data for a fully automatic analysis tool based on deep learning.

Semi-supervised learning with natural language processing for right ventricle classification in echocardiography-a scalable approach.

We created a deep learning model, trained on text classified by natural language processing (NLP), to assess right ventricular (RV) size and function from echocardiographic images. We included 12,684 examinations with corresponding written reports for text classification. After manual annotation of 1489 reports, we trained an NLP model to classify the remaining 10,651 reports. A view classifier was developed to select the 4-chamber or RV-focused view from an echocardiographic examination (n = 539). The final models were two image classification models trained on the predicted labels from the combined manual annotation and NLP models and the corresponding echocardiographic view to assess RV function (training set n = 11,008) and size (training set n = 9951. The text classifier identified impaired RV function with 99% sensitivity and 98% specificity and RV enlargement with 98% sensitivity and 98% specificity. The view classification model identified the 4-chamber view with 92% accuracy and the RV-focused view with 73% accuracy. The image classification models identified impaired RV function with 93% sensitivity and 72% specificity and an enlarged RV with 80% sensitivity and 85% specificity; agreement with the written reports was substantial (both κ = 0.65). Our findings show that models for automatic image assessment can be trained to classify RV size and function by using model-annotated data from written echocardiography reports. This pipeline for auto-annotation of the echocardiographic images, using a NLP model with medical reports as input, can be used to train an image-assessment model without manual annotation of images and enables fast and inexpensive expansion of the training dataset when needed.

Increased vascularization of shoulder regions of carotid atherosclerotic plaques from patients with diabetes.

OBJECTIVE: Increased vascularization is considered an important contributing factor for plaque vulnerability. Microvascular proliferative disease in patients with diabetes results in renal damage and visual loss. We assessed the hypothesis that vascularization in carotid atherosclerotic tissue is increased in diabetic patients, especially in the critical shoulder regions of the plaque. METHODS: Carotid endarterectomy specimens, clinical data, and blood samples were collected from patients with symptomatic carotid artery stenosis (median 85 days after clinical event) and pharmacologic treatment for diabetes (n = 26) or no diabetes (n = 85). Plaques were fixed in formalin and transverse tissue sections prepared. Histopathology and immunohistochemistry were performed for detection of endothelial cells (anti-CD34), macrophages (anti-CD68), vascular endothelial growth factor (VEGF), and its receptor (VEGFR-2). Neovascularization was assessed as CD34(+) neovessel density in the entire section area and by the presence or absence of CD34(+) vessels in the shoulder and cap regions of the plaques. RESULTS: The patient groups did not differ significantly in neovascularization in the entire transverse sections (2.0 vs 2.1 vessels/mm(2); P = .61) or in the fibrous cap (52% of the patients in both groups; P = .95). Neovascularization of the plaque shoulder regions was observed in 52% of the diabetic patients and in 26% of the nondiabetic patients (P = .028). VEGF-stained areas were similar in the two patient groups (0.4% and 0.2% of shoulder area; P = .61). Patients with diabetes had more VEGFR-2 (1.0% vs 0.2% of shoulder area; P < .016) and less CD68 staining (0.4% vs 3.6% of shoulder area; P < .008). Time from clinical event to surgery was positively associated with neovascularization of the plaque shoulder regions (≤90 days, 18% of patients; >90 days, 50% of patients; P = .002), independently of diabetes status. CONCLUSIONS: Diabetes was associated with increased vascularization of the shoulder regions in patients with symptomatic carotid atherosclerotic plaques. This was accompanied by increased expression of VEGFR-2. The increased vascularization of the plaque shoulder regions may help explain why patients with diabetes are at increased risk of atherosclerotic complications.

Artificial intelligence based automatic quantification of epicardial adipose tissue suitable for large scale population studies.

To develop a fully automatic model capable of reliably quantifying epicardial adipose tissue (EAT) volumes and attenuation in large scale population studies to investigate their relation to markers of cardiometabolic risk. Non-contrast cardiac CT images from the SCAPIS study were used to train and test a convolutional neural network based model to quantify EAT by: segmenting the pericardium, suppressing noise-induced artifacts in the heart chambers, and, if image sets were incomplete, imputing missing EAT volumes. The model achieved a mean Dice coefficient of 0.90 when tested against expert manual segmentations on 25 image sets. Tested on 1400 image sets, the model successfully segmented 99.4% of the cases. Automatic imputation of missing EAT volumes had an error of less than 3.1% with up to 20% of the slices in image sets missing. The most important predictors of EAT volumes were weight and waist, while EAT attenuation was predicted mainly by EAT volume. A model with excellent performance, capable of fully automatic handling of the most common challenges in large scale EAT quantification has been developed. In studies of the importance of EAT in disease development, the strong co-variation with anthropometric measures needs to be carefully considered.

Cadmium Exposure and Coronary Artery Atherosclerosis: A Cross-Sectional Population-Based Study of Swedish Middle-Aged Adults.

BACKGROUND: The general population is ubiquitously exposed to the toxic metal cadmium through the diet and smoking. Cadmium exposure is associated with increased morbidity and mortality in myocardial infarction and stroke. Atherosclerosis is the main underlying mechanism of myocardial infarction. However, associations between cadmium and coronary artery atherosclerosis have not been examined. OBJECTIVES: Our study sought to examine the hypothesis that blood cadmium (B-Cd) is positively associated with coronary artery calcification, as a measure of coronary artery atherosclerosis in the population-based Swedish SCAPIS study. METHODS: Our analysis included 5,627 individuals (51% women), age 50-64 y, enrolled from 2013 to 2018. The coronary artery calcium score (CACS) was obtained from computed tomography. Blood cadmium was determined by inductively coupled plasma mass spectrometry (ICP-MS). Associations between B-Cd and coronary artery calcium score (CACS Agatston score) were evaluated using prevalence ratios (PRs) in models adjusted for sex, age, smoking, hypertension, diabetes, low-density cholesterol/high-density cholesterol ratio, and family history. RESULTS: The median B-Cd concentration was 0.24µg/L. The prevalence of positive coronary artery calcium (CACS>0) was 41% and the prevalence of CACS≥100 was 13%. Relative to the lowest quartile (Q) of B-Cd (<0.16µg/L), the highest quartile (median 0.63µg/L) was associated with a small but significant increase in CACS>0 (PR 1.1; 95% CI: 1.0, 1.3), and a greater relative increase in CACS≥100 (PR 1.6; 95% CI: 1.3, 2.0). When restricted to 2,446 never-smokers, corresponding PRs were 1.1 (95% CI 0.9, 1.3) for CACS>0 (63 cases in Q4) and 1.7 (95% CI 1.1, 2.7) for CACS≥100 (17 cases in Q4). DISCUSSION: Blood cadmium in the highest quartile was associated with CACS in a general population sample with low to moderate cadmium exposure. This supports the hypothesis that atherosclerosis is an important mechanism underlying the associations between cadmium and incident cardiovascular disease. The findings suggest that public health measures to reduce cadmium exposure are warranted. https://doi.org/10.1289/EHP8523.

Beta-Cell Function, Self-rated Health, and Lifestyle Habits in 64-Year-Old Swedish Women with Metabolically Healthy Obesity Phenotype.

BACKGROUND: A subset of obese individuals do not present metabolic abnormalities that commonly define the metabolic syndrome (MetS). This is referred to as a metabolically healthy obese (MHO) phenotype. The aim of the present study was to evaluate the prevalence of the MHO phenotype and its relationship with beta cell dysfunction by measuring C-peptide and proinsulin, anthropometric-, metabolic- and lipid appearance, as well as lifestyle behaviors and self-rated health in a cohort of 64-year-old Swedish women. METHODS: The National Cholesterol Education Program definition was used to assess MetS. We defined normal weight as body mass index (BMI) 18.5-24.9 kg/m2 and obesity as BMI ≥30 kg/m2 to categorize participants as metabolically healthy normal weight, MHO, and metabolically unhealthy obese. RESULTS: The MHO phenotype represented 36.3% of obese participants and 16.3% of total participants. The MHO group were at greater risk of having proinsulin levels >11 pmol/L, indicating impaired beta cell function. Further, homeostatic model assessment for insulin resistance, fasting plasma levels of insulin, and C-peptide showed significant trends, with the MHO phenotype group having intermediate levels among three groups. Health behaviors such as leisure time physical activity and alcohol intake were also intermediate in individuals with the MHO phenotype. CONCLUSION: In this study, we demonstrate that over a third of the obese women in our sample were MHO. Further, women with the MHO phenotype showed intermediate profiles considering beta cell function and insulin resistance, as well as metabolic variables, and tended to rate their general health as worse than otherwise similar individuals of normal weight.

Weight gain and blood pressure.

OBJECTIVE: Although the causality of the obesity--hypertension association is established, the potential for prevention is not. We hypothesized that weight gain between early adulthood and mid-life is associated with higher mid-life blood pressure. METHODS: We investigated the hypothesis using a large contemporaneous population-based mid-life cohort of men and women aged 50-64 years. Recalled body weight at age 20 years was self-reported, and mid-life body weight and office blood pressures were measured in accordance with a detailed protocol. RESULTS: On average, men had gained 14.9 (95% CI 14.6-15.2) kg of weight, and women 14.6 (95% CI 14.4-14.9) kg, between age 20 years and the mid-life examination, corresponding to 0.40 (95% CI 0.39-0.41) kg/year for men and women. Both weight at age 20 years and weight at the mid-life examination were associated with mid-life blood pressures. On average, a 10 kg weight increase between age 20 years and mid-life was associated with 2.2 (95% CI 0.9-3.5) mmHg higher systolic and 1.7 (95% CI 0.9-2.5) mmHg higher diastolic mid-life blood pressure in men, and 3.2 (2.5-4.0) mmHg higher systolic and 2.4 (1.9-2.9) mmHg higher diastolic mid-life blood pressure in women. Mid-life weight was more closely associated than weight at age 20 years with mid-life blood pressure. For a given mid-life weight, blood pressure was higher in persons with higher weight gain from age 20 years. CONCLUSION: In sum, weight gain between early adulthood and mid-life was associated with higher mid-life blood pressure. The magnitude of the association indicates a potentially great public health impact of strategies to prevent weight gain throughout adulthood.

Does retinopathy predict stroke recurrence in type 2 diabetes patients: A retrospective study?

AIMS: To study if retinopathy increases the risk of stroke recurrence in stroke patients with type 2 diabetes. Also, to study if stroke patients with type 2 diabetes have an increased risk of stroke recurrence compared to non-diabetics and if stroke patients with type 2 diabetes, regardless of retinopathy, have a higher incidence of carotid stenosis. Also, to study if stroke patients with type 2 diabetes retinopathy have increased incidence of carotid stenosis. METHODS: We included 445 patients with type 2 diabetes mellitus and a matched control group of 445 patients without diabetes, who had all suffered their first stroke or TIA. Information on retinopathy, risk factors and stroke recurrence were obtained from registers and medical records. RESULTS: Retinopathy did not increase the risk of stroke recurrence in diabetes patients, HR 0.89 (0.51-1.53), p = 0.67. The risk of stroke recurrence was not increased in diabetics compared to non-diabetes. Diabetes patients had an increased prevalence of carotid stenosis compared to non-diabetics, 1.69 (1.15-2.48), p = 0.008. The prevalence of carotid stenosis in diabetics with retinopathy was not increased compared to diabetics without retinopathy. CONCLUSION: Retinopathy is not a predictor of stroke recurrence or carotid stenosis in type 2 diabetes patients.

Inverse association between size of the lipid-rich necrotic core and vascularization in human carotid plaques.

PURPOSE: To study the relationship between the size of the lipid-rich necrotic core measured by MRI (magnetic resonance imaging) and the level of plaque vascularization measured by contrast-enhanced ultrasound, in human carotid plaques. Further, to compare the size of lipid-rich necrotic core from MRI to plaque echogenicity. METHODS: Thirty-one subjects with carotid plaques underwent standard B-mode ultrasound, contrast-enhanced ultrasound and MRI. The lipid-rich necrotic core was quantified using MRI. Contrast-enhanced ultrasound was used to measure carotid plaque vascularization. Standard B-mode ultrasound was used to measure plaque echogenicity as greyscale median. RESULTS: The amount of lipid-rich necrotic core correlated inversely with the degree of plaque vascularization (r = -0·40, P = 0·03). There were no correlations between the degree of plaque vascularization and the amount of fibrous tissue or calcifications. There were no correlations between greyscale median and the lipid-rich necrotic core, fibrous tissue or calcifications. CONCLUSIONS: We show that more dense plaque vascularization is associated with a lower plaque content of lipid-rich necrotic core. A large lipid-rich necrotic core and high plaque vascularization are both proposed as predictors of vulnerability, and our finding is therefore odds with some earlier observations. Our finding can be explained by the fact that the necrotic core of the plaque contains no viable tissue and therefore less of the plaque can be vascularized if the lipid-rich necrotic core is large. Our study suggests that the true relation between plaque vascularization and other indices of vulnerability is more complex than initially thought.

Comparison between magnetic resonance imaging and B-mode ultrasound in detecting and estimating the extent of human carotid atherosclerosis.

BACKGROUND: In MRI studies of carotid plaques, ultrasound is used to find plaques, which are later imaged using MRI. The performance in plaque detection has not been compared between the modalities. The aim of the current study was to compare the performance of MRI and ultrasound in detecting carotid artery plaques and measuring extent of atherosclerosis. METHODS: Subjects with at least one plaque (height≥2·5 mm) on ultrasound were imaged using MRI. The number of plaques and their height was measured in both modalities; plaque area and volume were analysed on ultrasound and MRI, respectively. RESULTS: Thirty-eight subjects were included. MRI detected plaques in 95% of carotid arteries with a plaque height of ≥2·5 mm on ultrasound and in all carotid arteries with a plaque exceeding 2·5 mm. MRI detected 53% of the plaques with a height below 2·5 mm. The plaque height measured with both techniques correlated significantly, 0·59, P<0·0001. Ultrasound-derived plaque height and plaque area correlated similarly to MRI-derived plaque volume, r = 0·52; P<0·0001 and r = 0·47; P = 0·001, respectively. CONCLUSIONS: We conclude that MRI has a similar sensitivity to ultrasound in finding carotid artery plaques that are 2·5 mm or higher. In smaller plaques, MRI detects fewer plaques. Multiple carotid plaques seen on ultrasound most often are a misinterpretation of the anatomy and correspond to a single plaque. Plaque height on ultrasound is comparable to plaque height on MRI and correlates fairly well with plaque volume on MRI making it an interesting proxy for plaque burden.