Left Ventricular Trabeculations at Cardiac MRI: Reference Ranges and Association with Cardiovascular Risk Factors in UK Biobank.

Background The extent of left ventricular (LV) trabeculation and its relationship with cardiovascular (CV) risk factors is unclear. Purpose To apply automated segmentation to UK Biobank cardiac MRI scans to (a) assess the association between individual characteristics and CV risk factors and trabeculated LV mass (LVM) and (b) establish normal reference ranges in a selected group of healthy UK Biobank participants. Materials and Methods In this cross-sectional secondary analysis, prospectively collected data from the UK Biobank (2006 to 2010) were retrospectively analyzed. Automated segmentation of trabeculations was performed using a deep learning algorithm. After excluding individuals with known CV diseases, White adults without CV risk factors (reference group) and those with preexisting CV risk factors (hypertension, hyperlipidemia, diabetes mellitus, or smoking) (exposed group) were compared. Multivariable regression models, adjusted for potential confounders (age, sex, and height), were fitted to evaluate the associations between individual characteristics and CV risk factors and trabeculated LVM. Results Of 43 038 participants (mean age, 64 years ± 8 [SD]; 22 360 women), 28 672 individuals (mean age, 66 years ± 7; 14 918 men) were included in the exposed group, and 7384 individuals (mean age, 60 years ± 7; 4729 women) were included in the reference group. Higher body mass index (BMI) (ß = 0.66 [95% CI: 0.63, 0.68]; P < .001), hypertension (ß = 0.42 [95% CI: 0.36, 0.48]; P < .001), and higher physical activity level (ß = 0.15 [95% CI: 0.12, 0.17]; P < .001) were associated with higher trabeculated LVM. In the reference group, the median trabeculated LVM was 6.3 g (IQR, 4.7-8.5 g) for men and 4.6 g (IQR, 3.4-6.0 g) for women. Median trabeculated LVM decreased with age for men from 6.5 g (IQR, 4.8-8.7 g) at age 45-50 years to 5.9 g (IQR, 4.3-7.8 g) at age 71-80 years (P = .03). Conclusion Higher trabeculated LVM was observed with hypertension, higher BMI, and higher physical activity level. Age- and sex-specific reference ranges of trabeculated LVM in a healthy middle-aged White population were established. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Kawel-Boehm in this issue.

Subclinical Changes in Cardiac Functional Parameters as Determined by Cardiovascular Magnetic Resonance (CMR) Imaging in Sleep Apnea and Snoring: Findings from UK Biobank.

Background and Objectives: Obstructive sleep apnea (OSA) is a common disorder with an increased risk for left ventricular and right ventricular dysfunction. Most studies to date have examined populations with manifest cardiovascular disease using echocardiography to analyze ventricular dysfunction with little or no reference to ventricular volumes or myocardial mass. Our aim was to explore these parameters with cardiac MRI. We hypothesized that there would be stepwise increase in left ventricular mass and right ventricular volumes from the unaffected, to the snoring and the OSA group. Materials and Methods: We analyzed cardiac MRI data from 4978 UK Biobank participants free from cardiovascular disease. Participants were allocated into three cohorts: with OSA, with self-reported snoring and without OSA or snoring (n = 118, 1886 and 2477). We analyzed cardiac parameters from balanced cine-SSFP sequences and indexed them to body surface area. Results: Patients with OSA were mostly males (47.3% vs. 79.7%; p < 0.001) with higher body mass index (25.7 ± 4.0 vs. 31.3 ± 5.3 kg/m²; p < 0.001) and higher blood pressure (135 ± 18 vs. 140 ± 17 mmHg; p = 0.012) compared to individuals without OSA or snoring. Regression analysis showed a significant effect for OSA in left ventricular end-diastolic index (LVEDVI) (ß = -4.9 ± 2.4 mL/m²; p = 0.040) and right ventricular end-diastolic index (RVEDVI) (ß = -6.2 ± 2.6 mL/m²; p = 0.016) in females and for right ventricular ejection fraction (RVEF) (ß = 1.7 ± 0.8%; p = 0.031) in males. A significant effect was discovered in snoring females for left ventricular mass index (LVMI) (ß = 3.5 ± 0.9 g/m²; p < 0.001) and in males for left ventricular ejection fraction (LVEF) (ß = 1.0 ± 0.3%; p = 0.001) and RVEF (ß = 1.2 ± 0.3%; p < 0.001). Conclusion: Our study suggests that OSA is highly underdiagnosed and that it is an evolving process with gender specific progression. Females with OSA show significantly lower ventricular volumes while males with snoring show increased ejection fractions which may be an early sign of hypertrophy. Separate prospective studies are needed to further explore the direction of causality.

Association Between Ambient Air Pollution and Cardiac Morpho-Functional Phenotypes: Insights From the UK Biobank Population Imaging Study.

Background: Exposure to ambient air pollution is strongly associated with increased cardiovascular morbidity and mortality. Little is known about the influence of air pollutants on cardiac structure and function. We aim to investigate the relationship between chronic past exposure to traffic-related pollutants and the cardiac chamber volume, ejection fraction, and left ventricular remodeling patterns after accounting for potential confounders. Methods: Exposure to ambient air pollutants including particulate matter and nitrogen dioxide was estimated from the Land Use Regression models for the years between 2005 and 2010. Cardiac parameters were measured from cardiovascular magnetic resonance imaging studies of 3920 individuals free from pre-existing cardiovascular disease in the UK Biobank population study. The median (interquartile range) duration between the year of exposure estimate and the imaging visit was 5.2 (0.6) years. We fitted multivariable linear regression models to investigate the relationship between cardiac parameters and traffic-related pollutants after adjusting for various confounders. Results: The studied cohort was 62±7 years old, and 46% were men. In fully adjusted models, particulate matter with an aerodynamic diameter <2.5 µm concentration was significantly associated with larger left ventricular end-diastolic volume and end-systolic volume (effect size = 0.82%, 95% CI, 0.09-1.55%, P=0.027; and effect size = 1.28%, 95% CI, 0.15-2.43%, P=0.027, respectively, per interquartile range increment in particulate matter with an aerodynamic diameter <2.5 µm) and right ventricular end-diastolic volume (effect size = 0.85%, 95% CI, 0.12-1.58%, P=0.023, per interquartile range increment in particulate matter with an aerodynamic diameter <2.5 µm). Likewise, higher nitrogen dioxide concentration was associated with larger biventricular volume. Distance from the major roads was the only metric associated with lower left ventricular mass (effect size = -0.74%, 95% CI, -1.3% to -0.18%, P=0.01, per interquartile range increment). Neither left and right atrial phenotypes nor left ventricular geometric remodeling patterns were influenced by the ambient pollutants. Conclusions: In a large asymptomatic population with no prevalent cardiovascular disease, higher past exposure to particulate matter with an aerodynamic diameter <2.5 µm and nitrogen dioxide was associated with cardiac ventricular dilatation, a marker of adverse remodeling that often precedes heart failure development.

Right ventricular shape and function: cardiovascular magnetic resonance reference morphology and biventricular risk factor morphometrics in UK Biobank.

BACKGROUND: The associations between cardiovascular disease (CVD) risk factors and the biventricular geometry of the right ventricle (RV) and left ventricle (LV) have been difficult to assess, due to subtle and complex shape changes. We sought to quantify reference RV morphology as well as biventricular variations associated with common cardiovascular risk factors. METHODS: A biventricular shape atlas was automatically constructed using contours and landmarks from 4329 UK Biobank cardiovascular magnetic resonance (CMR) studies. A subdivision surface geometric mesh was customized to the contours using a diffeomorphic registration algorithm, with automatic correction of slice shifts due to differences in breath-hold position. A reference sub-cohort was identified consisting of 630 participants with no CVD risk factors. Morphometric scores were computed using linear regression to quantify shape variations associated with four risk factors (high cholesterol, high blood pressure, obesity and smoking) and three disease factors (diabetes, previous myocardial infarction and angina). RESULTS: The atlas construction led to an accurate representation of 3D shapes at end-diastole and end-systole, with acceptable fitting errors between surfaces and contours (average error less than 1.5 mm). Atlas shape features had stronger associations than traditional mass and volume measures for all factors (p < 0.005 for each). High blood pressure was associated with outward displacement of the LV free walls, but inward displacement of the RV free wall and thickening of the septum. Smoking was associated with a rounder RV with inward displacement of the RV free wall and increased relative wall thickness. CONCLUSION: Morphometric relationships between biventricular shape and cardiovascular risk factors in a large cohort show complex interactions between RV and LV morphology. These can be quantified by z-scores, which can be used to study the morphological correlates of disease.

Automated quality control in image segmentation: application to the UK Biobank cardiovascular magnetic resonance imaging study.

BACKGROUND: The trend towards large-scale studies including population imaging poses new challenges in terms of quality control (QC). This is a particular issue when automatic processing tools such as image segmentation methods are employed to derive quantitative measures or biomarkers for further analyses. Manual inspection and visual QC of each segmentation result is not feasible at large scale. However, it is important to be able to automatically detect when a segmentation method fails in order to avoid inclusion of wrong measurements into subsequent analyses which could otherwise lead to incorrect conclusions. METHODS: To overcome this challenge, we explore an approach for predicting segmentation quality based on Reverse Classification Accuracy, which enables us to discriminate between successful and failed segmentations on a per-cases basis. We validate this approach on a new, large-scale manually-annotated set of 4800 cardiovascular magnetic resonance (CMR) scans. We then apply our method to a large cohort of 7250 CMR on which we have performed manual QC. RESULTS: We report results used for predicting segmentation quality metrics including Dice Similarity Coefficient (DSC) and surface-distance measures. As initial validation, we present data for 400 scans demonstrating 99% accuracy for classifying low and high quality segmentations using the predicted DSC scores. As further validation we show high correlation between real and predicted scores and 95% classification accuracy on 4800 scans for which manual segmentations were available. We mimic real-world application of the method on 7250 CMR where we show good agreement between predicted quality metrics and manual visual QC scores. CONCLUSIONS: We show that Reverse classification accuracy has the potential for accurate and fully automatic segmentation QC on a per-case basis in the context of large-scale population imaging as in the UK Biobank Imaging Study.

Automated cardiovascular magnetic resonance image analysis with fully convolutional networks.

BACKGROUND: Cardiovascular resonance (CMR) imaging is a standard imaging modality for assessing cardiovascular diseases (CVDs), the leading cause of death globally. CMR enables accurate quantification of the cardiac chamber volume, ejection fraction and myocardial mass, providing information for diagnosis and monitoring of CVDs. However, for years, clinicians have been relying on manual approaches for CMR image analysis, which is time consuming and prone to subjective errors. It is a major clinical challenge to automatically derive quantitative and clinically relevant information from CMR images. METHODS: Deep neural networks have shown a great potential in image pattern recognition and segmentation for a variety of tasks. Here we demonstrate an automated analysis method for CMR images, which is based on a fully convolutional network (FCN). The network is trained and evaluated on a large-scale dataset from the UK Biobank, consisting of 4,875 subjects with 93,500 pixelwise annotated images. The performance of the method has been evaluated using a number of technical metrics, including the Dice metric, mean contour distance and Hausdorff distance, as well as clinically relevant measures, including left ventricle (LV) end-diastolic volume (LVEDV) and end-systolic volume (LVESV), LV mass (LVM); right ventricle (RV) end-diastolic volume (RVEDV) and end-systolic volume (RVESV). RESULTS: By combining FCN with a large-scale annotated dataset, the proposed automated method achieves a high performance in segmenting the LV and RV on short-axis CMR images and the left atrium (LA) and right atrium (RA) on long-axis CMR images. On a short-axis image test set of 600 subjects, it achieves an average Dice metric of 0.94 for the LV cavity, 0.88 for the LV myocardium and 0.90 for the RV cavity. The mean absolute difference between automated measurement and manual measurement is 6.1 mL for LVEDV, 5.3 mL for LVESV, 6.9 gram for LVM, 8.5 mL for RVEDV and 7.2 mL for RVESV. On long-axis image test sets, the average Dice metric is 0.93 for the LA cavity (2-chamber view), 0.95 for the LA cavity (4-chamber view) and 0.96 for the RA cavity (4-chamber view). The performance is comparable to human inter-observer variability. CONCLUSIONS: We show that an automated method achieves a performance on par with human experts in analysing CMR images and deriving clinically relevant measures.

Reference ranges for cardiac structure and function using cardiovascular magnetic resonance (CMR) in Caucasians from the UK Biobank population cohort.

BACKGROUND: Cardiovascular magnetic resonance (CMR) is the gold standard method for the assessment of cardiac structure and function. Reference ranges permit differentiation between normal and pathological states. To date, this study is the largest to provide CMR specific reference ranges for left ventricular, right ventricular, left atrial and right atrial structure and function derived from truly healthy Caucasian adults aged 45-74. METHODS: Five thousand sixty-five UK Biobank participants underwent CMR using steady-state free precession imaging at 1.5 Tesla. Manual analysis was performed for all four cardiac chambers. Participants with non-Caucasian ethnicity, known cardiovascular disease and other conditions known to affect cardiac chamber size and function were excluded. Remaining participants formed the healthy reference cohort; reference ranges were calculated and were stratified by gender and age (45-54, 55-64, 65-74). RESULTS: After applying exclusion criteria, 804 (16.2%) participants were available for analysis. Left ventricular (LV) volumes were larger in males compared to females for absolute and indexed values. With advancing age, LV volumes were mostly smaller in both sexes. LV ejection fraction was significantly greater in females compared to males (mean ± standard deviation [SD] of 61 ± 5% vs 58 ± 5%) and remained static with age for both genders. In older age groups, LV mass was lower in men, but remained virtually unchanged in women. LV mass was significantly higher in males compared to females (mean ± SD of 53 ± 9 g/m2 vs 42 ± 7 g/m2). Right ventricular (RV) volumes were significantly larger in males compared to females for absolute and indexed values and were smaller with advancing age. RV ejection fraction was higher with increasing age in females only. Left atrial (LA) maximal volume and stroke volume were significantly larger in males compared to females for absolute values but not for indexed values. LA ejection fraction was similar for both sexes. Right atrial (RA) maximal volume was significantly larger in males for both absolute and indexed values, while RA ejection fraction was significantly higher in females. CONCLUSIONS: We describe age- and sex-specific reference ranges for the left ventricle, right ventricle and atria in the largest validated normal Caucasian population.

The Association Between Periodontal Disease and Cardiovascular Disease: Insights From Imaging, Observational, and Genetic Data.

Background: Periodontal disease is the sixth most common disease worldwide and may be a contributory risk factor for cardiovascular disease (CVD). Objectives: This study utilizes noninvasive cardiac imaging and longitudinal and genetic data to characterize the association between periodontal disease and both cardiovascular magnetic resonance (CMR) imaging biomarkers of remodeling and incident coronary artery disease (CAD). Methods: From the UK Biobank, 481,915 individuals were included, 91,022 (18.9%) of whom had self-reported periodontal disease. For imaging analysis, 59,019 had paired CMR data. Multivariable linear regression models were constructed to examine the association of periodontal disease on CMR outcomes. The endpoints for the CMR analyses were left ventricle (LV) end-diastolic volume, LV ejection fraction, LV mass, LV mass:volume ratio, LV global longitudinal strain, and native T1 values. The relationship between periodontal disease and CVD was assessed using Cox proportional hazards regression models, with incident CAD as the endpoint. To examine the relationship of genetically determined periodontal disease on CAD, a genome-wide polygenic risk score was constructed. Results: Periodontal disease was associated with a significantly higher LV mass:volume ratio (effect size: 0.00233; 95% CI: 0.0006-0.004) and significantly lower T1 values (effect size: -0.86 ms; 95% CI: -1.63 to -0.09). Periodontal disease was independently associated with an increased hazard of incident CAD (HR: 1.09; 95% CI: 1.07-1.13) at a median follow-up time of 13.8 years. Each SD increase in the periodontal disease polygenic risk score was associated with increased odds of CAD (OR: 1.03; 95% CI: 1.02-1.05). Conclusions: Using an integrated approach across imaging, observational, and genomic data, periodontal disease is associated with biomarkers of subclinical remodeling as well as incident CAD. These findings highlight the potential importance of periodontal disease in the broader context of CVD prevention.

A history of cardiovascular magnetic resonance imaging in clinical practice and population science.

Cardiovascular magnetic resonance (CMR) imaging has become an invaluable clinical and research tool. Starting from the discovery of nuclear magnetic resonance, this article provides a brief overview of the key developments that have led to CMR as it is today, and how it became the modality of choice for large-scale population studies.

Quality control of cardiac magnetic resonance imaging segmentation, feature tracking, aortic flow, and native T1 analysis using automated batch processing in the UK Biobank study.

Aims: Automated algorithms are regularly used to analyse cardiac magnetic resonance (CMR) images. Validating data output reliability from this method is crucial for enabling widespread adoption. We outline a visual quality control (VQC) process for image analysis using automated batch processing. We assess the performance of automated analysis and the reliability of replacing visual checks with statistical outlier (SO) removal approach in UK Biobank CMR scans. Methods and results: We included 1987 CMR scans from the UK Biobank COVID-19 imaging study. We used batch processing software (Circle Cardiovascular Imaging Inc.-CVI42) to automatically extract chamber volumetric data, strain, native T1, and aortic flow data. The automated analysis outputs (∼62 000 videos and 2000 images) were visually checked by six experienced clinicians using a standardized approach and a custom-built R Shiny app. Inter-observer variability was assessed. Data from scans passing VQC were compared with a SO removal QC method in a subset of healthy individuals (n = 1069). Automated segmentation was highly rated, with over 95% of scans passing VQC. Overall inter-observer agreement was very good (Gwet's AC2 0.91; 95% confidence interval 0.84, 0.94). No difference in overall data derived from VQC or SO removal in healthy individuals was observed. Conclusion: Automated image analysis using CVI42 prototypes for UK Biobank CMR scans demonstrated high quality. Larger UK Biobank data sets analysed using these automated algorithms do not require in-depth VQC. SO removal is sufficient as a QC measure, with operator discretion for visual checks based on population or research objectives.

The utility of implantable loop recorders in patient management: an age- and indication-stratified study in the outpatient-implant era.

AIM: Implantable loop recorders (ILRs) are now routinely implanted for long-term cardiac monitoring in the clinical setting. The aim of this study was to examine the real-world performance of these devices focusing on the management changes made in response to ILR-recorded data. METHODS AND RESULTS: This was a single-centre, prospective observational study of consecutive patients undergoing ILR implantation. All patients who underwent implantation of a Medtronic Reveal LINQ device from September 2017 to June 2019 at Barts Heart Centre were included. Five hundred and one patients were included. Three hundred and two (60%) patients underwent ILR implantation for an indication of pre-syncope/syncope, 96 (19%) for palpitations, 72 (14%) for atrial fibrillation (AF) detection with a history of cryptogenic stroke, and 31 (6%) for high risk of serious cardiac arrhythmia. The primary outcome of this study was that an ILR-derived diagnosis altered management in 110 patients (22%). Secondary outcomes concerned subgroup analyses by indication: in patients who presented with syncope/pre-syncope, a change in management resulting from ILR data was positively associated with age [hazard ratio (HR) 1.04, 95% confidence interval 1.02-1.06; P < 0.001] and negatively associated with a normal electrocardiogram at baseline (HR 0.54 [0.31-0.93]; P = 0.03). Few patients (1/57, 2%) aged <40 years in this group underwent device implantation, compared to 19/62 patients (31%) aged 75 years and over (P = 0.0024). Out of 183 (12%) patients, 22 in the 40-74 age range had a device implanted. Among patients who underwent ILR insertion following cryptogenic stroke, 13/72 (18%) had AF detected, leading to a decision to commence anticoagulation. CONCLUSION: These results inform the utility of ILR in the clinical setting. Diagnoses provided by ILR that lead to changes in management are rare in patients under age 40, particularly following syncope, pre-syncope, or palpitations. In older patients, new diagnoses are frequently made and trigger important changes in treatment.

Genome-wide association analysis reveals insights into the genetic architecture of right ventricular structure and function.

Right ventricular (RV) structure and function influence the morbidity and mortality from coronary artery disease (CAD), dilated cardiomyopathy (DCM), pulmonary hypertension and heart failure. Little is known about the genetic basis of RV measurements. Here we perform genome-wide association analyses of four clinically relevant RV phenotypes (RV end-diastolic volume, RV end-systolic volume, RV stroke volume, RV ejection fraction) from cardiovascular magnetic resonance images, using a state-of-the-art deep learning algorithm in 29,506 UK Biobank participants. We identify 25 unique loci associated with at least one RV phenotype at P < 2.27 ×10-8, 17 of which are validated in a combined meta-analysis (n = 41,830). Several candidate genes overlap with Mendelian cardiomyopathy genes and are involved in cardiac muscle contraction and cellular adhesion. The RV polygenic risk scores (PRSs) are associated with DCM and CAD. The findings substantially advance our understanding of the genetic underpinning of RV measurements.

Sex-specific associations between alcohol consumption, cardiac morphology, and function as assessed by magnetic resonance imaging: insights form the UK Biobank Population Study.

AIMS: Data regarding the effects of regular alcohol consumption on cardiac anatomy and function are scarce. Therefore, we sought to determine the relationship between regular alcohol intake and cardiac structure and function as evaluated with cardiac magnetic resonance imaging. METHODS AND RESULTS: Participants of the UK Biobank who underwent cardiac magnetic resonance were enrolled in our analysis. Data regarding regular alcohol consumption were obtained from questionnaires filled in by the study participants. Exclusion criteria were poor image quality, missing, or incongruent data regarding alcohol drinking habits, prior drinking, presence of heart failure or angina, and prior myocardial infarction or stroke. Overall, 4335 participants (61.5 ± 7.5 years, 47.6% male) were analysed. We used multivariate linear regression models adjusted for age, ethnicity, body mass index, smoking, hypertension, diabetes mellitus, physical activity, cholesterol level, and Townsend deprivation index to examine the relationship between regular alcohol intake and cardiac structure and function. In men, alcohol intake was independently associated with marginally increased left ventricular end-diastolic volume [ß = 0.14; 95% confidence interval (CI) = 0.05-0.24; P = 0.004], left ventricular stroke volume (ß = 0.08; 95% CI = 0.03-0.14; P = 0.005), and right ventricular stroke volume (ß = 0.08; 95% CI = 0.02-0.13; P = 0.006). In women, alcohol consumption was associated with increased left atrium volume (ß = 0.14; 95% CI = 0.04-0.23; P = 0.006). CONCLUSION: Alcohol consumption is independently associated with a marginal increase in left and right ventricular volumes in men, but not in women, whereas alcohol intake showed an association with increased left atrium volume in women. Our results suggest that there is only minimal relationship between regular alcohol consumption and cardiac morphology and function in an asymptomatic middle-aged population.

Poor Bone Quality is Associated With Greater Arterial Stiffness: Insights From the UK Biobank.

Osteoporosis and ischemic heart disease (IHD) represent important public health problems. Existing research suggests an association between the two conditions beyond that attributable to shared risk factors, with a potentially causal relationship. In this study, we tested the association of bone speed of sound (SOS) from quantitative heel ultrasound with (i) measures of arterial compliance from cardiovascular magnetic resonance (aortic distensibility [AD]); (ii) finger photoplethysmography (arterial stiffness index [ASI]); and (iii) incident myocardial infarction and IHD mortality in the UK Biobank cohort. We considered the potential mediating effect of a range of blood biomarkers and cardiometabolic morbidities and evaluated differential relationships by sex, menopause status, smoking, diabetes, and obesity. Furthermore, we considered whether associations with arterial compliance explained association of SOS with ischemic cardiovascular outcomes. Higher SOS was associated with lower arterial compliance by both ASI and AD for both men and women. The relationship was most consistent with ASI, likely relating to larger sample size available for this variable (n = 159,542 versus n = 18,229). There was no clear evidence of differential relationship by menopause, smoking, diabetes, or body mass index (BMI). Blood biomarkers appeared important in mediating the association for both men and women, but with different directions of effect and did not fully explain the observed effects. In fully adjusted models, higher SOS was associated with significantly lower IHD mortality in men, but less robustly in women. The association of SOS with ASI did not explain this observation. In conclusion, our findings support a positive association between bone and vascular health with consistent patterns of association in men and women. The underlying mechanisms are complex and appear to vary by sex. © 2020 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

Tissue-tracking in the assessment of late gadolinium enhancement in myocarditis and myocardial infarction.

PURPOSE: To test the diagnostic performance of cardiovascular magnetic resonance (CMR) tissue-tracking (TT) to detect the presence of late gadolinium enhancement (LGE) in patients with a diagnosis of myocardial infarction (MI) or myocarditis (MYO), preserved left ventricular ejection fraction (LVEF) and no visual regional wall motion abnormalities (RWMA). METHODS: We selected consecutive CMR studies of 50 MI, 50 MYO and 96 controls. Receiving operating characteristic (ROC) curve and net reclassification index (NRI) analyses were used to assess the predictive ability and the incremental diagnostic yield of 2D and 3D TT-derived strain parameters for the detection of LGE and to measure the best cut-off values of strain parameters. RESULTS: Overall, cases showed significantly reduced 2D global longitudinal strain (2D-GLS) values compared with controls (-20.1 ± 3.1% vs -21.6 ± 2.7%; p = 0.0008). 2D-GLS was also significantly reduced in MYO patients compared with healthy controls (-19.7 ± 2.9% vs -21.9 ± 2.4%; p = 0.0001). 3D global radial strain (3D-GRS) was significantly reduced in MI patients compared with controls with risk factors (34.3 ± 11.8% vs 40.3 ± 12.5%, p = 0.024) Overall, 2D-GLS yielded good diagnostic accuracy for the detection of LGE in the MYO subgroup (AUROC 0.79; NRI (95% CI) = 0.6 (0.3, 1.02) p = 0.0004), with incremental predictive value beyond risk factors and LV function parameters (p for AUROC difference = 0.048). In the MI subgroup, 2D-GRS (AUROC 0.81; NRI (95% CI) = 0.56 (0.17, 0.95) p = 0.004), 3D-GRS (AUROC 0.82; NRI (95% CI) = 0.57 (0.17, 0.97) p = 0.006) and 3D global circumferential strain (3D-GCS) (AUROC 0.81; NRI (95% CI) = 0.62 (0.22, 1.01) p = 0.002) emerged as potential markers of disease. The best cut-off for 2D-GLS was -21.1%, for 2D- and 3D-GRS were 39.1% and 37.7%, respectively, and for 3D-GCS was -16.4%. CONCLUSIONS: At CMR-tissue tracking analysis, 2D-GLS was a significant predictor of LGE in patients with myocarditis but preserved LVEF and no visual RWMA. Both 2D- and 3D-GRS and 2D-GCS yielded good diagnostic accuracy for LGE detection in patients with previous MI but preserved LVEF and no visual RWMA.

The Effect of Blood Lipids on the Left Ventricle: A Mendelian Randomization Study.

BACKGROUND: Cholesterol and triglycerides are among the most well-known risk factors for cardiovascular disease. OBJECTIVES: This study investigated whether higher low-density lipoprotein (LDL) cholesterol and triglyceride levels and lower high-density lipoprotein cholesterol level are causal risk factors for changes in prognostically important left ventricular (LV) parameters. METHODS: One-sample Mendelian randomization (MR) of 17,311 European individuals from the UK Biobank with paired lipid and cardiovascular magnetic resonance data was performed. Two-sample MR was performed by using summary-level data from the Global Lipid Genetics Consortium (n = 188,577) and UK Biobank Cardiovascular Magnetic Resonance substudy (n = 16,923) for sensitivity analyses. RESULTS: In 1-sample MR analysis, higher LDL cholesterol was causally associated with higher LV end-diastolic volume (ß = 1.85 ml; 95% confidence interval [CI]: 0.59 to 3.14 ml; p = 0.004) and higher LV mass (ß = 0.81 g; 95% CI: 0.11 to 1.51 g; p = 0.023) and triglycerides with higher LV mass (ß = 1.37 g; 95% CI: 0.45 to 2.3 g; p = 0.004). High-density lipoprotein cholesterol had no significant association with any LV parameter. Similar results were obtained by using 2-sample MR. Observational analyses were frequently discordant with those derived from MR. CONCLUSIONS: MR analysis demonstrates that LDL cholesterol and triglycerides are associated with adverse changes in cardiac structure and function, in particular in relation to LV mass. These findings suggest that LDL cholesterol and triglycerides may have a causal effect in influencing cardiac morphology in addition to their established role in atherosclerosis.

Prognostic Significance of Left Ventricular Noncompaction: Systematic Review and Meta-Analysis of Observational Studies.

BACKGROUND: Although left ventricular noncompaction (LVNC) has been associated with an increased risk of adverse cardiovascular events, the accurate incidence of cardiovascular morbidity and mortality is unknown. We, therefore, aimed to assess the incidence rate of LVNC-related cardiovascular events. METHODS: We systematically searched observational studies reporting the adverse outcomes related to LVNC. The primary end point was cardiovascular mortality. RESULTS: We identified 28 eligible studies enrolling 2501 LVNC patients (mean age, 46 years; male/female ratio, 1.7). After a median follow-up of 2.9 years, the pooled event rate for cardiovascular mortality was 1.92 (95% CI, 1.54-2.30) per 100 person-years. LVNC patients had a similar risk of cardiovascular mortality compared with a dilated cardiomyopathy control group (odds ratio, 1.10 [95% CI, 0.18-6.67]). The incidence rates of all-cause mortality, stroke and systemic emboli, heart failure admission, cardiac transplantation, ventricular arrhythmias, and cardiac device implantation were 2.16, 1.54, 3.53, 1.24, 2.17, and 2.66, respectively, per 100 person-years. Meta-regression and subgroup analyses revealed that left ventricular ejection fraction, not the extent of left ventricular trabeculation, had an important influence on the variability of incidence rates. The risks of thromboembolism and ventricular arrhythmias in LVNC patients were similar to dilated cardiomyopathy patients. However, LVNC patients had a higher incidence of heart failure hospitalization than dilated cardiomyopathy patients. CONCLUSIONS: Patients with LVNC carry a similar cardiovascular risk when compared with dilated cardiomyopathy patients. Left ventricular ejection fraction-a conventional indicator of heart failure severity, not the extent of trabeculation-appears to be an important determinant of adverse outcomes in LVNC patients. Registration: https://www.crd.york.ac.uk/PROSPERO/ Unique identifier: CRD42018096313.

Improving the Generalizability of Convolutional Neural Network-Based Segmentation on CMR Images.

Background: Convolutional neural network (CNN) based segmentation methods provide an efficient and automated way for clinicians to assess the structure and function of the heart in cardiac MR images. While CNNs can generally perform the segmentation tasks with high accuracy when training and test images come from the same domain (e.g., same scanner or site), their performance often degrades dramatically on images from different scanners or clinical sites. Methods: We propose a simple yet effective way for improving the network generalization ability by carefully designing data normalization and augmentation strategies to accommodate common scenarios in multi-site, multi-scanner clinical imaging data sets. We demonstrate that a neural network trained on a single-site single-scanner dataset from the UK Biobank can be successfully applied to segmenting cardiac MR images across different sites and different scanners without substantial loss of accuracy. Specifically, the method was trained on a large set of 3,975 subjects from the UK Biobank. It was then directly tested on 600 different subjects from the UK Biobank for intra-domain testing and two other sets for cross-domain testing: the ACDC dataset (100 subjects, 1 site, 2 scanners) and the BSCMR-AS dataset (599 subjects, 6 sites, 9 scanners). Results: The proposed method produces promising segmentation results on the UK Biobank test set which are comparable to previously reported values in the literature, while also performing well on cross-domain test sets, achieving a mean Dice metric of 0.90 for the left ventricle, 0.81 for the myocardium, and 0.82 for the right ventricle on the ACDC dataset; and 0.89 for the left ventricle, 0.83 for the myocardium on the BSCMR-AS dataset. Conclusions: The proposed method offers a potential solution to improve CNN-based model generalizability for the cross-scanner and cross-site cardiac MR image segmentation task.

Cardiovascular magnetic resonance imaging for amyloidosis: The state-of-the-art.

Amyloidosis results from insoluble precursor proteins being deposited in the extracellular compartment. The prognosis of the disease is predominantly determined by cardiac involvement due to amyloid accumulation that contributes to cardiac dysfunction and disturbed conduction of cardiac electrical signals. The clinical and radiological manifestations of amyloidosis are often non-specific, making amyloidosis a diagnostic challenge both for clinicians and radiologists. Cardiovascular magnetic resonance imaging, including conventional sequences, late gadolinium enhancement, T1 mapping and determination of extracellular volume fraction is a multi-dimensional modality for the assessment and diagnosis of cardiac amyloidosis and, in addition, is an excellent tool for risk stratification and disease tracking.

Physical activity and left ventricular trabeculation in the UK Biobank community-based cohort study.

OBJECTIVE: Vigorous physical activity (PA) in highly trained athletes has been associated with heightened left ventricular (LV) trabeculation extent. It has therefore been hypothesised that LV trabeculation extent may participate in exercise-induced physiological cardiac remodelling. Our cross-sectional observational study aimed to ascertain whether there is a 'dose-response' relationship between PA and LV trabeculation extent and whether this could be identified at opposite PA extremes. METHODS: In a cohort of 1030 individuals from the community-based UK Biobank study (male/female ratio: 0.84, mean age: 61 years), PA was measured via total metabolic equivalent of task (MET) min/week and 7-day average acceleration, and trabeculation extent via maximal non-compaction/compaction ratio (NC/C) in long-axis images of cardiovascular magnetic resonance studies. The relationship between PA and NC/C was assessed by multivariate regression (adjusting for potential confounders) as well as between demographic, anthropometric and LV phenotypic parameters and NC/C. RESULTS: There was no significant linear relationship between PA and NC/C (full adjustment, total MET-min/week: ß=-0.0008, 95% CI -0.039 to -0.037, p=0.97; 7-day average acceleration: ß=-0.047, 95% CI -0.110 to -0.115, p=0.13, per IQR increment in PA), or between extreme PA quintiles (full adjustment, total MET-min/week: ß=-0.026, 95% CI -0.146 to -0.094, p=0.67; 7-day average acceleration: ß=-0.129, 95% CI -0.299 to -0.040, p=0.49), across all adjustment levels. A negative relationship was identified between left ventricular ejection fraction and NC/C, significantly modified by PA (ß difference=-0.006, p=0.03). CONCLUSIONS: In a community-based general population cohort, there was no relationship at, or between, extremes, between PA and NC/C, suggesting that at typical general population PA levels, trabeculation extent is not influenced by PA changes.