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Background: Hospitalized COVID-19 patients with troponin elevation have a higher prevalence of cardiac abnormalities than control individuals. However, the progression and impact of myocardial injury on COVID-19 survivors remain unclear., Objectives: This study sought to evaluate myocardial injury in COVID-19 survivors with troponin elevation with baseline and follow-up imaging and to assess medium-term outcomes., Methods: This was a prospective, longitudinal cohort study in 25 United Kingdom centers (June 2020 to March 2021). Hospitalized COVID-19 patients with myocardial injury underwent cardiac magnetic resonance (CMR) scans within 28 days and 6 months postdischarge. Outcomes were tracked for 12 months, with quality of life surveys (EuroQol-5 Dimension and 36-Item Short Form surveys) taken at discharge and 6 months., Results: Of 342 participants (median age: 61.3 years; 71.1% male) with baseline CMR, 338 had a 12-month follow-up, 235 had a 6-month CMR, and 215 has baseline and follow-up quality of life surveys. Of 338 participants, within 12 months, 1.2% died; 1.8% had new myocardial infarction, acute coronary syndrome, or coronary revascularization; 0.8% had new myopericarditis; and 3.3% had other cardiovascular events requiring hospitalization. At 6 months, there was a minor improvement in left ventricular ejection fraction (1.8% ± 1.0%; P < 0.001), stable right ventricular ejection fraction (0.4% ± 0.8%; P = 0.50), no change in myocardial scar pattern or volume (P = 0.26), and no imaging evidence of continued myocardial inflammation. All pericardial effusions (26 of 26) resolved, and most pneumonitis resolved (95 of 101). EuroQol-5 Dimension scores indicated an overall improvement in quality of life (P < 0.001)., Conclusions: Myocardial injury in severe hospitalized COVID-19 survivors is nonprogressive. Medium-term outcomes show a low incidence of major adverse cardiovascular events and improved quality of life. (COVID-19 Effects on the Heart; ISRCTN58667920)., Competing Interests: Funding Support and Author Disclosures This work was supported by NIHR (National Institute for Health and Care Research) and UK Research and Innovation (COV0254). West Yorkshire and Humber Clinical Research Network (CV070) funded the patient information leaflet translation. Dr Berry has received British Heart Foundation support (RE/18/6134217). Dr Artico received funding from the European Association of Cardiovascular Imaging (EACVI Research Grant App000073878). Dr McCann is funded by a NIHR Research Professorship (RP-2017-08-ST2-007). Dr Manisty is funded by a NIHR Clinician Scientist Award (CS-2015-15-003). Drs Ferreira, Piechnik, and Neubauer acknowledge the NIHR Oxford BRC for support of this study. Dr Bucciarelli-Ducci is in part supported by the NIHR Biomedical Research Centre at University Hospitals Bristol NHS (National Health Service) Foundation Trust and the University of Bristol. Additional support was provided by the NIHR Leicester Biomedical Research Centre and the NIHR Leeds Clinical Research Facility. Dr Dweck is supported by the British Heart Foundation (FS/SCRF/21/32010). The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health and Social Care. Dr Moon has served on Advisory Boards for Sanofi and Genzyme. Dr Miller has served on Advisory Boards for Novartis, Boehringer Ingelheim and Lilly Alliance, and AstraZeneca; serves as an advisor for HAYA Therapeutics and PureTech Health; and has received research support from Amicus Therapeutics, Guerbet Laboratories Limited, Roche, and Univar Solutions B.V. Dr Bucciarelli-Ducci is the chief executive officer (part-time) of the Society for Magnetic Resonance. Dr Berry is employed by the University of Glasgow, which holds research and/or consultancy agreements with AstraZeneca, Abbott Vascular, Boehringer Ingelheim, GlaxoSmithKline, HeartFlow, Opsens, and Novartis. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Aims: Cardiovascular magnetic resonance parametric mapping enables non-invasive quantitative myocardial tissue characterization. Human myocardium has normal ranges of T1 and T2 values, deviation from which may indicate disease or change in physiology. Normal myocardial T1 and T2 values are affected by biological sex. Consequently, normal ranges created with insufficient numbers of each sex may result in sampling biases, misclassification of healthy values vs. disease, and even misdiagnoses. In this study, we investigated the impact of using male normal ranges for classifying female cases as normal or abnormal (and vice versa)., Methods and Results: One hundred and forty-two healthy volunteers (male and female) were scanned on two Siemens 3T MR systems, providing averaged global myocardial T1 and T2 values on a per-subject basis. The Monte Carlo method was used to generate simulated normal ranges from these values to estimate the statistical accuracy of classifying healthy female or male cases correctly as 'normal' when using sex-specific vs. mixed-sex normal ranges. The normal male and female T1- and T2-mapping values were significantly different by sex, after adjusting for age and heart rate., Conclusion: Using 15 healthy volunteers who are not sex specific to establish a normal range resulted in a typical misclassification of up to 36% of healthy females and 37% of healthy males as having abnormal T1 values and up to 16% of healthy females and 12% of healthy males as having abnormal T2 values. This paper highlights the potential adverse impact on diagnostic accuracy that can occur when local normal ranges contain insufficient numbers of both sexes. Sex-specific reference ranges should thus be routinely adopted in clinical practice., Competing Interests: Conflict of interest: S.K.P. has patent authorship rights for US patent US20120078084A1: ‘System and methods for shortened Look-Locker inversion recovery (Sh-MOLLI) cardiac gated mapping of T1’, granted on 15 March 2016. S.K.P., I.A.P., and V.M.F. have authorship rights for patent pending PCT/GB2020/051189: ‘A method for identity validation and quality assurance of quantitative magnetic resonance imaging protocols’, filed on 15 May 2020. IPs are owned and managed by Oxford University Innovations., (© The Author(s) 2023. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Background: Hypertensive pregnancy disorders are associated with adverse cardiac remodeling, which can fail to reverse in the postpartum period in some women. The Physician-Optimized Postpartum Hypertension Treatment trial demonstrated that improved blood pressure control while the cardiovascular system recovers postpartum associates with persistently reduced blood pressure. We now report the effect on cardiac remodeling., Methods: In this prospective, randomized, open-label, blinded end point trial, in a single UK hospital, 220 women were randomly assigned 1:1 to self-monitoring with research physician-optimized antihypertensive titration or usual postnatal care from a primary care physician and midwife. Participants were 18 years of age or older, with preeclampsia or gestational hypertension, requiring antihypertensives on hospital discharge postnatally. Prespecified secondary cardiac imaging outcomes were recorded by echocardiography around delivery, and again at blood pressure primary outcome assessment, around 9 months postpartum, when cardiovascular magnetic resonance was also performed., Results: A total of 187 women (101 intervention; 86 usual care) underwent echocardiography at baseline and follow-up, at a mean 258±14.6 days postpartum, of which 174 (93 intervention; 81 usual care) also had cardiovascular magnetic resonance at follow-up. Relative wall thickness by echocardiography was 0.06 (95% CI, 0.07-0.05; P <0.001) lower in the intervention group between baseline and follow-up, and cardiovascular magnetic resonance at follow-up demonstrated a lower left ventricular mass (-6.37 g/m 2 ; 95% CI, -7.99 to -4.74; P <0.001), end-diastolic volume (-3.87 mL/m 2 ; 95% CI, -6.77 to -0.98; P =0.009), and end-systolic volume (-3.25 mL/m 2 ; 95% CI, 4.87 to -1.63; P <0.001) and higher left and right ventricular ejection fraction by 2.6% (95% CI, 1.3-3.9; P <0.001) and 2.8% (95% CI, 1.4-4.1; P <0.001), respectively. Echocardiography-assessed left ventricular diastolic function demonstrated a mean difference in average E/E' of 0.52 (95% CI, -0.97 to -0.07; P =0.024) and a reduction in left atrial volumes of -4.33 mL/m 2 (95% CI, -5.52 to -3.21; P <0.001) between baseline and follow-up when adjusted for baseline differences in measures., Conclusions: Short-term postnatal optimization of blood pressure control after hypertensive pregnancy, through self-monitoring and physician-guided antihypertensive titration, associates with long-term changes in cardiovascular structure and function, in a pattern associated with more favorable cardiovascular outcomes., Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT04273854., Competing Interests: Disclosures L.M. and P.L. are supported by the National Institute for Health and Care Research Oxford Biomedical Research Centre. L.M. is a part-time employee of EMIS Group plc. P.L. is a founder and shareholder of a health care imaging company and a named inventor on patents related to cardiovascular imaging. R.M. has received blood pressure monitors for research from Omron and has worked with Omron and Sensyne on telemonitoring interventions for which licensing and consultancy fees have been paid to the University of Oxford. C.R. has received consultancy fees from Sensyne Health for work on telemonitoring products. J.K. is an executive committee member of the British Society of Cardiac Imaging and Cardiac Computed Tomography. The other authors report no conflicts.

Aims: Obstructive hypertrophic cardiomyopathy (oHCM) is characterized by dynamic obstruction of the left ventricular (LV) outflow tract (LVOT). Although this may be mediated by interplay between the hypertrophied septal wall, systolic anterior motion of the mitral valve, and papillary muscle abnormalities, the mechanistic role of LV shape is still not fully understood. This study sought to identify the LV end-diastolic morphology underpinning oHCM., Methods and Results: Cardiovascular magnetic resonance images from 2398 HCM individuals were obtained as part of the NHLBI HCM Registry. Three-dimensional LV models were constructed and used, together with a principal component analysis, to build a statistical shape model capturing shape variations. A set of linear discriminant axes were built to define and quantify (Z-scores) the characteristic LV morphology associated with LVOT obstruction (LVOTO) under different physiological conditions and the relationship between LV phenotype and genotype. The LV remodelling pattern in oHCM consisted not only of basal septal hypertrophy but a combination with LV lengthening, apical dilatation, and LVOT inward remodelling. Salient differences were observed between obstructive cases at rest and stress. Genotype negative cases showed a tendency towards more obstructive phenotypes both at rest and stress., Conclusions: LV anatomy underpinning oHCM consists of basal septal hypertrophy, apical dilatation, LV lengthening, and LVOT inward remodelling. Differences between oHCM cases at rest and stress, as well as the relationship between LV phenotype and genotype, suggest different mechanisms for LVOTO. Proposed Z-scores render an opportunity of redefining management strategies based on the relationship between LV anatomy and LVOTO., Competing Interests: Conflict of interest: P.L. sits at the scientific advisory board of Ultromics. The remaining authors have nothing to disclose., (© The Author(s) 2022. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Background: Acute myocardial injury in hospitalized patients with coronavirus disease 2019 (COVID-19) has a poor prognosis. Its associations and pathogenesis are unclear. Our aim was to assess the presence, nature, and extent of myocardial damage in hospitalized patients with troponin elevation., Methods: Across 25 hospitals in the United Kingdom, 342 patients with COVID-19 and an elevated troponin level (COVID+/troponin+) were enrolled between June 2020 and March 2021 and had a magnetic resonance imaging scan within 28 days of discharge. Two prospective control groups were recruited, comprising 64 patients with COVID-19 and normal troponin levels (COVID+/troponin-) and 113 patients without COVID-19 or elevated troponin level matched by age and cardiovascular comorbidities (COVID-/comorbidity+). Regression modeling was performed to identify predictors of major adverse cardiovascular events at 12 months., Results: Of the 519 included patients, 356 (69%) were men, with a median (interquartile range) age of 61.0 years (53.8, 68.8). The frequency of any heart abnormality, defined as left or right ventricular impairment, scar, or pericardial disease, was 2-fold greater in cases (61% [207/342]) compared with controls (36% [COVID+/troponin-] versus 31% [COVID-/comorbidity+]; P <0.001 for both). More cases than controls had ventricular impairment (17.2% versus 3.1% and 7.1%) or scar (42% versus 7% and 23%; P <0.001 for both). The myocardial injury pattern was different, with cases more likely than controls to have infarction (13% versus 2% and 7%; P <0.01) or microinfarction (9% versus 0% and 1%; P <0.001), but there was no difference in nonischemic scar (13% versus 5% and 14%; P =0.10). Using the Lake Louise magnetic resonance imaging criteria, the prevalence of probable recent myocarditis was 6.7% (23/342) in cases compared with 1.7% (2/113) in controls without COVID-19 ( P =0.045). During follow-up, 4 patients died and 34 experienced a subsequent major adverse cardiovascular event (10.2%), which was similar to controls (6.1%; P =0.70). Myocardial scar, but not previous COVID-19 infection or troponin, was an independent predictor of major adverse cardiovascular events (odds ratio, 2.25 [95% CI, 1.12-4.57]; P =0.02)., Conclusions: Compared with contemporary controls, patients with COVID-19 and elevated cardiac troponin level have more ventricular impairment and myocardial scar in early convalescence. However, the proportion with myocarditis was low and scar pathogenesis was diverse, including a newly described pattern of microinfarction., Registration: URL: https://www.isrctn.com; Unique identifier: 58667920.

Background: Myocardial scars are assessed noninvasively using cardiovascular magnetic resonance late gadolinium enhancement (LGE) as an imaging gold standard. A contrast-free approach would provide many advantages, including a faster and cheaper scan without contrast-associated problems., Methods: Virtual native enhancement (VNE) is a novel technology that can produce virtual LGE-like images without the need for contrast. VNE combines cine imaging and native T1 maps to produce LGE-like images using artificial intelligence. VNE was developed for patients with previous myocardial infarction from 4271 data sets (912 patients); each data set comprises slice position-matched cine, T1 maps, and LGE images. After quality control, 3002 data sets (775 patients) were used for development and 291 data sets (68 patients) for testing. The VNE generator was trained using generative adversarial networks, using 2 adversarial discriminators to improve the image quality. The left ventricle was contoured semiautomatically. Myocardial scar volume was quantified using the full width at half maximum method. Scar transmurality was measured using the centerline chord method and visualized on bull's-eye plots. Lesion quantification by VNE and LGE was compared using linear regression, Pearson correlation ( R ), and intraclass correlation coefficients. Proof-of-principle histopathologic comparison of VNE in a porcine model of myocardial infarction also was performed., Results: VNE provided significantly better image quality than LGE on blinded analysis by 5 independent operators on 291 data sets (all P <0.001). VNE correlated strongly with LGE in quantifying scar size ( R , 0.89; intraclass correlation coefficient, 0.94) and transmurality ( R , 0.84; intraclass correlation coefficient, 0.90) in 66 patients (277 test data sets). Two cardiovascular magnetic resonance experts reviewed all test image slices and reported an overall accuracy of 84% for VNE in detecting scars when compared with LGE, with specificity of 100% and sensitivity of 77%. VNE also showed excellent visuospatial agreement with histopathology in 2 cases of a porcine model of myocardial infarction., Conclusions: VNE demonstrated high agreement with LGE cardiovascular magnetic resonance for myocardial scar assessment in patients with previous myocardial infarction in visuospatial distribution and lesion quantification with superior image quality. VNE is a potentially transformative artificial intelligence-based technology with promise in reducing scan times and costs, increasing clinical throughput, and improving the accessibility of cardiovascular magnetic resonance in the near future.

Background: Quantitative cardiovascular magnetic resonance (CMR) T1 mapping has shown promise for advanced tissue characterisation in routine clinical practise. However, T1 mapping is prone to motion artefacts, which affects its robustness and clinical interpretation. Current methods for motion correction on T1 mapping are model-driven with no guarantee on generalisability, limiting its widespread use. In contrast, emerging data-driven deep learning approaches have shown good performance in general image registration tasks. We propose MOCOnet, a convolutional neural network solution, for generalisable motion artefact correction in T1 maps. Methods: The network architecture employs U-Net for producing distance vector fields and utilises warping layers to apply deformation to the feature maps in a coarse-to-fine manner. Using the UK Biobank imaging dataset scanned at 1.5T, MOCOnet was trained on 1,536 mid-ventricular T1 maps (acquired using the ShMOLLI method) with motion artefacts, generated by a customised deformation procedure, and tested on a different set of 200 samples with a diverse range of motion. MOCOnet was compared to a well-validated baseline multi-modal image registration method. Motion reduction was visually assessed by 3 human experts, with motion scores ranging from 0% (strictly no motion) to 100% (very severe motion). Results: MOCOnet achieved fast image registration (<1 second per T1 map) and successfully suppressed a wide range of motion artefacts. MOCOnet significantly reduced motion scores from 37.1±21.5 to 13.3±10.5 ( p < 0.001), whereas the baseline method reduced it to 15.8±15.6 ( p < 0.001). MOCOnet was significantly better than the baseline method in suppressing motion artefacts and more consistently ( p = 0.007). Conclusion: MOCOnet demonstrated significantly better motion correction performance compared to a traditional image registration approach. Salvaging data affected by motion with robustness and in a time-efficient manner may enable better image quality and reliable images for immediate clinical interpretation., Competing Interests: SP has patent authorship rights for U.S. patent 9285446 B2 systems and methods for Shortened Look-Locker Inversion Recovery ShMOLLI cardiac gated mapping of T1, granted March 15, 2016; licensed to Siemens Medical. KW is an employee of Circle Cardiovascular Imaging since 2019. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Gonzales, Zhang, Papież, Werys, Lukaschuk, Popescu, Burrage, Shanmuganathan, Ferreira and Piechnik.)

Background: Late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging is the gold standard for noninvasive myocardial tissue characterization but requires intravenous contrast agent administration. It is highly desired to develop a contrast agent-free technology to replace LGE for faster and cheaper CMR scans., Methods: A CMR virtual native enhancement (VNE) imaging technology was developed using artificial intelligence. The deep learning model for generating VNE uses multiple streams of convolutional neural networks to exploit and enhance the existing signals in native T1 maps (pixel-wise maps of tissue T1 relaxation times) and cine imaging of cardiac structure and function, presenting them as LGE-equivalent images. The VNE generator was trained using generative adversarial networks. This technology was first developed on CMR datasets from the multicenter Hypertrophic Cardiomyopathy Registry, using hypertrophic cardiomyopathy as an exemplar. The datasets were randomized into 2 independent groups for deep learning training and testing. The test data of VNE and LGE were scored and contoured by experienced human operators to assess image quality, visuospatial agreement, and myocardial lesion burden quantification. Image quality was compared using a nonparametric Wilcoxon test. Intra- and interobserver agreement was analyzed using intraclass correlation coefficients (ICC). Lesion quantification by VNE and LGE were compared using linear regression and ICC., Results: A total of 1348 hypertrophic cardiomyopathy patients provided 4093 triplets of matched T1 maps, cines, and LGE datasets. After randomization and data quality control, 2695 datasets were used for VNE method development and 345 were used for independent testing. VNE had significantly better image quality than LGE, as assessed by 4 operators (n=345 datasets; P <0.001 [Wilcoxon test]). VNE revealed lesions characteristic of hypertrophic cardiomyopathy in high visuospatial agreement with LGE. In 121 patients (n=326 datasets), VNE correlated with LGE in detecting and quantifying both hyperintensity myocardial lesions ( r =0.77-0.79; ICC=0.77-0.87; P <0.001) and intermediate-intensity lesions ( r =0.70-0.76; ICC=0.82-0.85; P <0.001). The native CMR images (cine plus T1 map) required for VNE can be acquired within 15 minutes and producing a VNE image takes less than 1 second., Conclusions: VNE is a new CMR technology that resembles conventional LGE but without the need for contrast administration. VNE achieved high agreement with LGE in the distribution and quantification of lesions, with significantly better image quality.

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 [β = 0.14; 95% confidence interval (CI) = 0.05-0.24; P = 0.004], left ventricular stroke volume (β = 0.08; 95% CI = 0.03-0.14; P = 0.005), and right ventricular stroke volume (β = 0.08; 95% CI = 0.02-0.13; P = 0.006). In women, alcohol consumption was associated with increased left atrium volume (β = 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., (Published on behalf of the European Society of Cardiology. All rights reserved. © The Author(s) 2020. For permissions, please email: journals.permissions@oup.com.)

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) (β = -4.9 ± 2.4 mL/m²; p = 0.040) and right ventricular end-diastolic index (RVEDVI) (β = -6.2 ± 2.6 mL/m²; p = 0.016) in females and for right ventricular ejection fraction (RVEF) (β = 1.7 ± 0.8%; p = 0.031) in males. A significant effect was discovered in snoring females for left ventricular mass index (LVMI) (β = 3.5 ± 0.9 g/m²; p < 0.001) and in males for left ventricular ejection fraction (LVEF) (β = 1.0 ± 0.3%; p = 0.001) and RVEF (β = 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.

Background: Cardiovascular magnetic resonance T1-mapping is increasingly used for tissue characterization, commonly based on Modified Look-Locker Inversion recovery (MOLLI). However, there are numerous MOLLI variants with differing normal ranges. This lack of standardization presents confusion and difficulty in inter-center comparisons, hindering widespread adoption of T1-mapping., Methods: To address this, we performed a structured literature search for native left ventricular myocardial T1-mapping in healthy humans measured using MOLLI variants at 1.5 and 3 Tesla, across scanner vendors. We then used k-means clustering to structure normal MOLLI-T1 values according to magnetic field strength, and investigated correlations between common imaging parameters: repetition time (TR), echo time (TE), flip angle (FA)., Results: We analyzed data from 2207 healthy controls in 76 independent reports. Normal MOLLI-T1 standard deviations varied by 11-fold, and dependencies on TE, TR, and FA differed between 1.5 T and 3 T, thwarting meaningful T1 standardization even within a single field strength, including the use of Z-score. However, divergent MOLLI-T1 norms may be structured using data clustering. For 1.5 T, two clusters emerged: Cluster1 1.5T : T1 = 958 ± 16 ms (n = 1280); Cluster2 1.5T : T1 = 1027 ± 19 ms (n = 386). For 3 T, three clusters emerged: Cluster1 3T : T1 = 1160 ± 21 ms (n = 330); Cluster2 3T : T1 = 1067 ± 18 ms (n = 178); Cluster3 3T : T1 = 1227 ± 19 ms (n = 41). We then propose the concept of an online calculator for assigning local norms to a known MOLLI-T1 cluster, allowing benchmarking against published norms., Conclusion: Clustered structuring allows T1 standardization of widely-divergent MOLLI variants, benchmarking local norms (usually based on smaller samples) against published norms (larger samples). This may increase confidence and quality control in method implementation, facilitating wider clinical adoption of T1-mapping., Competing Interests: Declaration of Competing Interest SKP has patent authorship rights for U.S. patent US20120078084A1. Systems and methods for shortened Look Locker inversion recovery (Sh-MOLLI) cardiac gated mapping of T1. Granted March 15, 2016. IP is managed by Oxford University Innovations; the license exclusively transferred to Siemens Healthcare. All other authors have no industry relationships relevant to the contents of this paper to disclose., (Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.)

Cardiac magnetic resonance quantitative T1-mapping is increasingly used for advanced myocardial tissue characterisation. However, cardiac or respiratory motion can significantly affect the diagnostic utility of T1-maps, and thus motion artefact detection is critical for quality control and clinically-robust T1 measurements. Manual quality control of T1-maps may provide reassurance, but is laborious and prone to error. We present a deep learning approach with attention supervision for automated motion artefact detection in quality control of cardiac T1-mapping. Firstly, we customised a multi-stream Convolutional Neural Network (CNN) image classifier to streamline the process of automatic motion artefact detection. Secondly, we imposed attention supervision to guide the CNN to focus on targeted myocardial segments. Thirdly, when there was disagreement between the human operator and machine, a second human validator reviewed and rescored the cases for adjudication and to identify the source of disagreement. The multi-stream neural networks demonstrated 89.8% agreement, 87.4% ROC-AUC on motion artefact detection with the human operator in the 2568 T1 maps. Trained with additional supervision on attention, agreements and AUC significantly improved to 91.5% and 89.1%, respectively (p < 0.001). Rescoring of disagreed cases by the second human validator revealed that human operator error was the primary cause of disagreement. Deep learning with attention supervision provides a quick and high-quality assurance of clinical images, and outperforms human operators., (Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.)

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., (Copyright © 2020 Chen, Bai, Davies, Bhuva, Manisty, Augusto, Moon, Aung, Lee, Sanghvi, Fung, Paiva, Petersen, Lukaschuk, Piechnik, Neubauer and Rueckert.)

Purpose: To demonstrate the feasibility and performance of a fully automated deep learning framework to estimate myocardial strain from short-axis cardiac MRI-tagged images., Materials and Methods: In this retrospective cross-sectional study, 4508 cases from the U.K. Biobank were split randomly into 3244 training cases, 812 validation cases, and 452 test cases. Ground truth myocardial landmarks were defined and tracked by manual initialization and correction of deformable image registration using previously validated software with five readers. The fully automatic framework consisted of (a) a convolutional neural network (CNN) for localization and (b) a combination of a recurrent neural network (RNN) and a CNN to detect and track the myocardial landmarks through the image sequence for each slice. Radial and circumferential strain were then calculated from the motion of the landmarks and averaged on a slice basis., Results: Within the test set, myocardial end-systolic circumferential Green strain errors were -0.001 ± 0.025, -0.001 ± 0.021, and 0.004 ± 0.035 in the basal, mid-, and apical slices, respectively (mean ± standard deviation of differences between predicted and manual strain). The framework reproduced significant reductions in circumferential strain in participants with diabetes, hypertensive participants, and participants with a previous heart attack. Typical processing time was approximately 260 frames (approximately 13 slices) per second on a GPU with 12 GB RAM compared with 6-8 minutes per slice for the manual analysis., Conclusion: The fully automated combined RNN and CNN framework for analysis of myocardial strain enabled unbiased strain evaluation in a high-throughput workflow, with similar ability to distinguish impairment due to diabetes, hypertension, and previous heart attack.Published under a CC BY 4.0 license. Supplemental material is available for this article., (2020 by the Radiological Society of North America, Inc.)

Background: Myocardial T1-mapping is increasingly used in multicentre studies and trials. Inconsistent image analysis introduces variability, hinders differentiation of diseases, and results in larger sample sizes. We present a systematic approach to standardize T1-map analysis by human operators to improve accuracy and consistency., Methods: We developed a multi-step training program for T1-map post-processing. The training dataset contained 42 left ventricular (LV) short-axis T1-maps (normal and diseases; 1.5 and 3 Tesla). Contours drawn by two experienced human operators served as reference for myocardial T1 and wall thickness (WT). Trainees (n = 26) underwent training and were evaluated by: (a) qualitative review of contours; (b) quantitative comparison with reference T1 and WT., Results: The mean absolute difference between reference operators was 8.4 ± 6.3 ms (T1) and 1.2 ± 0.7 pixels (WT). Trainees' mean discrepancy from reference in T1 improved significantly post-training (from 8.1 ± 2.4 to 6.7 ± 1.4 ms; p < 0.001), with a 43% reduction in standard deviation (SD) (p = 0.035). WT also improved significantly post-training (from 0.9 ± 0.4 to 0.7 ± 0.2 pixels, p = 0.036), with 47% reduction in SD (p = 0.04). These experimentally-derived thresholds served to guide the training process: T1 (±8 ms) and WT (±1 pixel) from reference., Conclusion: A standardized approach to CMR T1-map image post-processing leads to significant improvements in the accuracy and consistency of LV myocardial T1 values and wall thickness. Improving consistency between operators can translate into 33-72% reduction in clinical trial sample-sizes. This work may: (a) serve as a basis for re-certification for core-lab operators; (b) translate to sample-size reductions for clinical studies; (c) produce better-quality training datasets for machine learning., (Copyright © 2019. Published by Elsevier B.V.)

Introduction: Cardiovascular disease (CVD) is more common in women who have had pregnancy complications such as spontaneous pregnancy loss. We used cross-sectional data from the UK Biobank Imaging Enhancement Study to determine whether pregnancy loss is associated with cardiac or vascular remodelling in later life, which might contribute to this increased risk., Methods: Pregnancy history was reported by women participating in UK Biobank between 2006 and 2010 at age 40-69 years using a self-completed touch-screen questionnaire. Associations between self-reported spontaneous pregnancy loss and cardiovascular measures, collected in women who participated in the Imaging Enhancement Study up to the end of 2015, were examined. Cardiac structure and function were assessed by magnetic resonance (CMR) steady-state free precession imaging at 1.5 Tesla. Carotid intima-media thickness (CIMT) measurements were taken for both common carotid arteries using a CardioHealth Station. Statistical associations with CMR and carotid measures were adjusted for age, BMI and other cardiovascular risk factors., Results: Data were available on 2660 women of whom 111 were excluded because of pre-existing cardiovascular disease and 30 had no pregnancy information available. Of the remaining 2519, 446 were nulligravid and 2073 had a history of pregnancies, of whom 622 reported at least one pregnancy loss (92% miscarriages and 8% stillbirths) and 1451 reported no pregnancy loss. No significant differences in any cardiac or carotid parameters were evident in women who reported pregnancy loss compared to other groups (Table 1)., Conclusion: Women who self-report pregnancy loss do not have significant differences in cardiac structure, cardiac function, or carotid structure in later life to explain their increased cardiovascular risk. This suggests any cardiovascular risks associated with pregnancy loss operate through other disease mechanisms. Alternatively, other characteristics of pregnancy loss, which we were not able to take account of, such as timing and number of pregnancy losses may be required to identify those at greatest cardiovascular risk., Competing Interests: The authors have declared that no competing interests exist.

Background: Diabetes mellitus (DM) is associated with increased risk of cardiovascular disease. Detection of early cardiac changes before manifest disease develops is important. We investigated early alterations in cardiac structure and function associated with DM using cardiovascular magnetic resonance imaging., Methods: Participants from the UK Biobank Cardiovascular Magnetic Resonance Substudy, a community cohort study, without known cardiovascular disease and left ventricular ejection fraction ≥50% were included. Multivariable linear regression models were performed. The investigators were blinded to DM status., Results: A total of 3984 individuals, 45% men, (mean [SD]) age 61.3 (7.5) years, hereof 143 individuals (3.6%) with DM. There was no difference in left ventricular (LV) ejection fraction (DM versus no DM; coefficient [95% CI]: -0.86% [-1.8 to 0.5]; P =0.065), LV mass (-0.13 g/m 2 [-1.6 to 1.3], P =0.86), or right ventricular ejection fraction (-0.23% [-1.2 to 0.8], P =0.65). However, both LV and right ventricular volumes were significantly smaller in DM, (LV end-diastolic volume/m 2 : -3.46 mL/m 2 [-5.8 to -1.2], P =0.003, right ventricular end-diastolic volume/m 2 : -4.2 mL/m 2 [-6.8 to -1.7], P =0.001, LV stroke volume/m 2 : -3.0 mL/m 2 [-4.5 to -1.5], P <0.001; right ventricular stroke volume/m 2 : -3.8 mL/m 2 [-6.5 to -1.1], P =0.005), LV mass/volume: 0.026 (0.01 to 0.04) g/mL, P =0.006. Both left atrial and right atrial emptying fraction were lower in DM (right atrial emptying fraction: -6.2% [-10.2 to -2.1], P =0.003; left atrial emptying fraction:-3.5% [-6.9 to -0.1], P =0.043). LV global circumferential strain was impaired in DM (coefficient [95% CI]: 0.38% [0.01 to 0.7], P =0.045)., Conclusions: In a low-risk general population without known cardiovascular disease and with preserved LV ejection fraction, DM is associated with early changes in all 4 cardiac chambers. These findings suggest that diabetic cardiomyopathy is not a regional condition of the LV but affects the heart globally.

Population imaging studies generate data for developing and implementing personalised health strategies to prevent, or more effectively treat disease. Large prospective epidemiological studies acquire imaging for pre-symptomatic populations. These studies enable the early discovery of alterations due to impending disease, and enable early identification of individuals at risk. Such studies pose new challenges requiring automatic image analysis. To date, few large-scale population-level cardiac imaging studies have been conducted. One such study stands out for its sheer size, careful implementation, and availability of top quality expert annotation; the UK Biobank (UKB). The resulting massive imaging datasets (targeting ca. 100,000 subjects) has put published approaches for cardiac image quantification to the test. In this paper, we present and evaluate a cardiac magnetic resonance (CMR) image analysis pipeline that properly scales up and can provide a fully automatic analysis of the UKB CMR study. Without manual user interactions, our pipeline performs end-to-end image analytics from multi-view cine CMR images all the way to anatomical and functional bi-ventricular quantification. All this, while maintaining relevant quality controls of the CMR input images, and resulting image segmentations. To the best of our knowledge, this is the first published attempt to fully automate the extraction of global and regional reference ranges of all key functional cardiovascular indexes, from both left and right cardiac ventricles, for a population of 20,000 subjects imaged at 50 time frames per subject, for a total of one million CMR volumes. In addition, our pipeline provides 3D anatomical bi-ventricular models of the heart. These models enable the extraction of detailed information of the morphodynamics of the two ventricles for subsequent association to genetic, omics, lifestyle habits, exposure information, and other information provided in population imaging studies. We validated our proposed CMR analytics pipeline against manual expert readings on a reference cohort of 4620 subjects with contour delineations and corresponding clinical indexes. Our results show broad significant agreement between the manually obtained reference indexes, and those automatically computed via our framework. 80.67% of subjects were processed with mean contour distance of less than 1 pixel, and 17.50% with mean contour distance between 1 and 2 pixels. Finally, we compare our pipeline with a recently published approach reporting on UKB data, and based on deep learning. Our comparison shows similar performance in terms of segmentation accuracy with respect to human experts., (Crown Copyright © 2019. Published by Elsevier B.V. All rights reserved.)

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.

Introduction: Aortic distensibility can be calculated using semi-automated methods to segment the aortic lumen on cine CMR (Cardiovascular Magnetic Resonance) images. However, these methods require visual quality control and manual localization of the region of interest (ROI) of ascending (AA) and proximal descending (PDA) aorta, which limit the analysis in large-scale population-based studies. Using 5100 scans from UK Biobank, this study sought to develop and validate a fully automated method to 1) detect and locate the ROIs of AA and PDA, and 2) provide a quality control mechanism., Methods: The automated AA and PDA detection-localization algorithm followed these steps: 1) foreground segmentation; 2) detection of candidate ROIs by Circular Hough Transform (CHT); 3) spatial, histogram and shape feature extraction for candidate ROIs; 4) AA and PDA detection using Random Forest (RF); 5) quality control based on RF detection probability. To provide the ground truth, overall image quality (IQ = 0-3 from poor to good) and aortic locations were visually assessed by 13 observers. The automated algorithm was trained on 1200 scans and Dice Similarity Coefficient (DSC) was used to calculate the agreement between ground truth and automatically detected ROIs., Results: The automated algorithm was tested on 3900 scans. Detection accuracy was 99.4% for AA and 99.8% for PDA. Aorta localization showed excellent agreement with the ground truth, with DSC ≥ 0.9 in 94.8% of AA (DSC = 0.97 ± 0.04) and 99.5% of PDA cases (DSC = 0.98 ± 0.03). AA×PDA detection probabilities could discriminate scans with IQ ≥ 1 from those severely corrupted by artefacts (AUC = 90.6%). If scans with detection probability < 0.75 were excluded (350 scans), the algorithm was able to correctly detect and localize AA and PDA in all the remaining 3550 scans (100% accuracy)., Conclusion: The proposed method for automated AA and PDA localization was extremely accurate and the automatically derived detection probabilities provided a robust mechanism to detect low quality scans for further human review. Applying the proposed localization and quality control techniques promises at least a ten-fold reduction in human involvement without sacrificing any accuracy., Competing Interests: Steffen E. Petersen provides consultancy to Circle Cardiovascular Imaging Inc. (Calgary, Alberta, Canada). This does not alter our adherence to PLOS ONE policies on sharing data and materials. The other authors have declared that no competing interests exist.

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., Competing Interests: Disclosures Dr Petersen provides consultancy to Circle Cardiovascular Imaging Inc, Calgary, Canada. The other authors report no conflicts.

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.

Background: Reduced lung function is common and associated with increased cardiovascular morbidity and mortality, even in asymptomatic individuals without diagnosed respiratory disease. Previous studies have identified relationships between lung function and cardiovascular structure in individuals with pulmonary disease, but the relationships in those free from diagnosed cardiorespiratory disease have not been fully explored., Methods: UK Biobank is a prospective cohort study of community participants in the United Kingdom. Individuals self-reported demographics and co-morbidities, and a subset underwent cardiovascular magnetic resonance (CMR) imaging and spirometry. CMR images were analysed to derive ventricular volumes and mass. The relationships between CMR-derived measures and spirometry and age were modelled with multivariable linear regression, taking account of the effects of possible confounders., Results: Data were available for 4,975 individuals, and after exclusion of those with pre-existing cardiorespiratory disease and unacceptable spirometry, 1,406 were included in the analyses. In fully-adjusted multivariable linear models lower FEV1 and FVC were associated with smaller left ventricular end-diastolic (-5.21ml per standard deviation (SD) change in FEV1, -5.69ml per SD change in FVC), end-systolic (-2.34ml, -2.56ml) and stroke volumes (-2.85ml, -3.11ml); right ventricular end-diastolic (-5.62ml, -5.84ml), end-systolic (-2.47ml, -2.46ml) and stroke volumes (-3.13ml, -3.36ml); and with lower left ventricular mass (-2.29g, -2.46g). Changes of comparable magnitude and direction were observed per decade increase in age., Conclusions: This study shows that reduced FEV1 and FVC are associated with smaller ventricular volumes and reduced ventricular mass. The changes seen per standard deviation change in FEV1 and FVC are comparable to one decade of ageing.

Background: Handgrip strength, a measure of muscular fitness, is associated with cardiovascular (CV) events and CV mortality but its association with cardiac structure and function is unknown. The goal of this study was to determine if handgrip strength is associated with changes in cardiac structure and function in UK adults., Methods and Results: Left ventricular (LV) ejection fraction (EF), end-diastolic volume (EDV), end-systolic volume (ESV), stroke volume (SV), mass (M), and mass-to-volume ratio (MVR) were measured in a sample of 4,654 participants of the UK Biobank Study 6.3 ± 1 years after baseline using cardiovascular magnetic resonance (CMR). Handgrip strength was measured at baseline and at the imaging follow-up examination. We determined the association between handgrip strength at baseline as well as its change over time and each of the cardiac outcome parameters. After adjustment, higher level of handgrip strength at baseline was associated with higher LVEDV (difference per SD increase in handgrip strength: 1.3ml, 95% CI 0.1-2.4; p = 0.034), higher LVSV (1.0ml, 0.3-1.8; p = 0.006), lower LVM (-1.0g, -1.8 --0.3; p = 0.007), and lower LVMVR (-0.013g/ml, -0.018 --0.007; p<0.001). The association between handgrip strength and LVEDV and LVSV was strongest among younger individuals, while the association with LVM and LVMVR was strongest among older individuals., Conclusions: Better handgrip strength was associated with cardiac structure and function in a pattern indicative of less cardiac hypertrophy and remodeling. These characteristics are known to be associated with a lower risk of cardiovascular events.

Background: The effect of menopausal hormone therapy (MHT)-previously known as hormone replacement therapy-on cardiovascular health remains unclear and controversial. This cross-sectional study examined the impact of MHT on left ventricular (LV) and left atrial (LA) structure and function, alterations in which are markers of subclinical cardiovascular disease, in a population-based cohort., Methods: Post-menopausal women who had never used MHT and those who had used MHT ≥3 years participating in the UK Biobank who had undergone cardiovascular magnetic resonance (CMR) imaging and free of known cardiovascular disease were included. Multivariable linear regression was performed to examine the relationship between cardiac parameters and MHT use ≥3 years. To explore whether MHT use on each of the cardiac outcomes differed by age, multivariable regression models were constructed with a cross-product of age and MHT fitted as an interaction term., Results: Of 1604 post-menopausal women, 513 (32%) had used MHT ≥3 years. In the MHT cohort, median age at menopause was 50 (IQR: 45-52) and median duration of MHT was 8 years. In the non-MHT cohort, median age at menopause was 51 (IQR: 48-53). MHT use was associated with significantly lower LV end-diastolic volume (122.8 ml vs 119.8 ml, effect size = -2.4%, 95% CI: -4.2% to -0.5%; p = 0.013) and LA maximal volume (60.2 ml vs 57.5 ml, effect size = -4.5%, 95% CI: -7.8% to -1.0%; p = 0.012). There was no significant difference in LV mass. MHT use significantly modified the effect between age and CMR parameters; MHT users had greater decrements in LV end-diastolic volume, LV end-systolic volume and LA maximal volume with advancing age., Conclusions: MHT use was not associated with adverse, subclinical changes in cardiac structure and function. Indeed, significantly smaller LV and LA chamber volumes were observed which have been linked to favourable cardiovascular outcomes. These findings represent a novel approach to examining MHT's effect on the cardiovascular system.

UK Biobank, a large cohort study, plans to acquire 100,000 cardiac MRI studies by 2020. Although fully-automated left ventricular (LV) analysis was performed in the original acquisition, this was not designed for unsupervised incorporation into epidemiological studies. We sought to evaluate automated LV mass and volume (Siemens syngo InlineVF versions D13A and E11C), against manual analysis in a substantial sub-cohort of UK Biobank participants. Eight readers from two centers, trained to give consistent results, manually analyzed 4874 UK Biobank cases for LV end-diastolic volume (EDV), end-systolic volume (ESV), stroke volume (SV), ejection fraction (EF) and LV mass (LVM). Agreement between manual and InlineVF automated analyses were evaluated using Bland-Altman analysis and the intra-class correlation coefficient (ICC). Tenfold cross-validation was used to establish a linear regression calibration between manual and InlineVF results. InlineVF D13A returned results in 4423 cases, whereas InlineVF E11C returned results in 4775 cases and also reported LVM. Rapid visual assessment of the E11C results found 178 cases (3.7%) with grossly misplaced contours or landmarks. In the remaining 4597 cases, LV function showed good agreement: ESV -6.4 ± 9.0 ml, 0.853 (mean ± SD of the differences, ICC) EDV -3.0 ± 11.6 ml, 0.937; SV 3.4 ± 9.8 ml, 0.855; and EF 3.5 ± 5.1%, 0.586. Although LV mass was consistently overestimated (29.9 ± 17.0 g, 0.534) due to larger epicardial contours on all slices, linear regression could be used to correct the bias and improve accuracy. Automated InlineVF results can be used for case-control studies in UK Biobank, provided visual quality control and linear bias correction are performed. Improvements between InlineVF D13A and InlineVF E11C show the field is rapidly advancing, with further improvements expected in the near future.

Background: The pulmonary artery (PA) distends as pressure increases., Hypothesis: The ratio of PA to aortic (Ao) diameter may be an indicator of pulmonary hypertension and consequently carry prognostic information in patients with chronic heart failure (HF)., Methods: Patients with chronic HF and control subjects undergoing cardiac magnetic resonance imaging were evaluated. The main PA diameter and the transverse axial Ao diameter at the level of bifurcation of the main PA were measured. The maximum diameter of both vessels was measured throughout the cardiac cycle and the PA/Ao ratio was calculated., Results: A total of 384 patients (mean age, 69 years; mean left ventricular ejection fraction, 40%; median NT-proBNP, 1010 ng/L [interquartile range, 448-2262 ng/L]) and 38 controls were included. Controls and patients with chronic HF had similar maximum Ao and PA diameters and PA/Ao ratio. During a median follow-up of 1759 days (interquartile range, 998-2269 days), 181 patients with HF were hospitalized for HF or died. Neither PA diameter nor PA/Ao ratio predicted outcome in univariable analysis. In a multivariable model, only age and NT-proBNP were independent predictors of adverse events., Conclusions: The PA/Ao ratio is not a useful method to stratify prognosis in patients with HF., (© 2018 Wiley Periodicals, Inc.)

Aims: The UK Biobank is a large-scale population-based study utilising cardiovascular magnetic resonance (CMR) to generate measurements of atrial and ventricular structure and function. This study aimed to quantify the association between modifiable cardiovascular risk factors and cardiac morphology and function in individuals without known cardiovascular disease., Methods: Age, sex, ethnicity (non-modifiable) and systolic blood pressure, diastolic blood pressure, smoking status, exercise, body mass index (BMI), high cholesterol, diabetes, alcohol intake (modifiable) were considered important cardiovascular risk factors. Multivariable regression models were built to ascertain the association of risk factors on left ventricular (LV), right ventricular (RV), left atrial (LA) and right atrial (RA) CMR parameters., Results: 4,651 participants were included in the analysis. All modifiable risk factors had significant effects on differing atrial and ventricular parameters. BMI was the modifiable risk factor most consistently associated with subclinical changes to CMR parameters, particularly in relation to higher LV mass (+8.3% per SD [4.3 kg/m2], 95% CI: 7.6 to 8.9%), LV (EDV: +4.8% per SD, 95% CI: 4.2 to 5.4%); ESV: +4.4% per SD, 95% CI: 3.5 to 5.3%), RV (EDV: +5.3% per SD, 95% CI: 4.7 to 5.9%; ESV: +5.4% per SD, 95% CI: 4.5 to 6.4%) and LA maximal (+8.6% per SD, 95% CI: 7.4 to 9.7%) volumes. Increases in SBP were associated with higher LV mass (+6.8% per SD, 95% CI: 5.9 to 7.7%), LV (EDV: +4.5% per SD, 95% CI: 3.6 to 5.4%; ESV: +2.0% per SD, 95% CI: 0.8 to 3.3%) volumes. The presence of diabetes or high cholesterol resulted in smaller volumes and lower ejection fractions., Conclusions: Modifiable risk factors are associated with subclinical alterations in structure and function in all four cardiac chambers. BMI and systolic blood pressure are the most important modifiable risk factors affecting CMR parameters known to be linked to adverse outcomes.

Background: Cardiac abnormalities are frequent in patients with atherosclerotic renovascular disease (ARVD). The Angioplasty and Stenting for Renal Artery Lesions (ASTRAL) trial studied the effect of percutaneous renal revascularization combined with medical therapy compared with medical therapy alone in 806 patients with ARVD., Methods: This was a pre-specified sub-study of ASTRAL (clinical trials registration, current controlled trials number: ISRCTN59586944), designed to consider the effect of percutaneous renal artery angioplasty and stenting on change in cardiac structure and function, measured using cardiac magnetic resonance (CMR) imaging. Fifty-one patients were recruited from six selected ASTRAL centres. Forty-four completed the study (medical therapy n = 21; revascularization n = 23). Full analysis of CMR was possible in 40 patients (18 medical therapy and 22 revascularization). CMR measurements of left and right ventricular end systolic (LV and RVESV) and diastolic volume (LV and RVEDV), ejection fraction (LVEF) and mass (LVM) were made shortly after recruitment and before revascularization in the interventional group, and again after 12 months. Reporting was performed by CMR analysts blinded to randomization arm., Results: Groups were well matched for mean age (70 versus 72 years), blood pressure (148/71 versus 143/74 mmHg), degree of renal artery stenosis (75 versus 75%) and comorbid conditions. In both randomized groups, improvements in cardiac structural parameters were seen at 12 months, but there were no significant differences between treatment groups. Median left ventricular changes between baseline and 12 months (medical versus revascularization) were LVEDV -1.9 versus -5.8 mL, P = 0.4; LVESV -2.1 versus 0.3 mL, P = 0.7; LVM -5.4 versus -6.3 g, P = 0.8; and LVEF -1.5 versus -0.8%, P = 0.7. Multivariate regression also found that randomized treatment assignment was not associated with degree of change in any of the CMR measurements., Conclusions: In this sub-study of the ASTRAL trial, renal revascularization did not offer additional benefit to cardiac structure or function in unselected patients with ARVD., (© The Author 2016. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.)

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/m 2 vs 42 ± 7 g/m 2 ). 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.

Introduction: The relationship of QRS morphology with cardiac structure and function in patients with heart failure is uncertain., Methods: Patients with a clinical diagnosis of heart failure and objective evidence of cardiac dysfunction [either a left ventricular ejection fraction (LVEF) <50 % or an amino-terminal pro-brain natriuretic peptide (NT-proBNP) ≥400 pg/ml] who had been investigated by cardiac magnetic resonance imaging (CMRI) were identified. QRS duration ≥120 ms was grouped morphologically as left (LBBB), right bundle branch block (RBBB) or indeterminate., Results: Of 877 patients, 320 (36 %) had QRS ≥ 120 ms. Compared to patients with LBBB, those with RBBB had a lower median [inter-quartile range (IQR)] right ventricular (RV) ejection fraction [RBBB: 46 (37-57); LBBB: 52 (42-61) %; p = 0.014], greater median (IQR) RV mass [RBBB: 53 (42-73); LBBB: 45 (36-56) g; p < 0.001], higher median (IQR) plasma NT-proBNP [RBBB: 2013 (659-3573); LBBB: 1159 (589-2207) pg/ml, p = 0.026], more signs of peripheral congestion and higher prevalence of atrial fibrillation but had similar LVEF. During a median follow-up of 1302 days (IQR: 742-2237), 311 patients died. Compared with patients who had QRS < 120 ms, those with RBBB [HR 1.98, 95 % CI (1.37-2.86); p < 0.001] had a higher mortality. Age and NT-proBNP were the strongest independent predictors of mortality; neither QRS nor CMRI variables improved prediction., Conclusions: In patients with heart failure and QRS ≥ 120 ms, RBBB is associated with more severe RV dysfunction and congestion and a worse prognosis. However, neither QRS morphology nor CMRI data provide independent prognostic information in a multivariable analysis including NT-proBNP.

Background: Left atrial (LA) volume is an important marker of cardiac dysfunction and cardiovascular outcome in heart failure (HF), but LA function is rarely measured., Methods: Left atrial emptying function (LAEF), its clinical associations and prognostic value was studied in outpatients referred with suspected HF who were in sinus rhythm and had cardiac magnetic resonance imaging (CMRI). Heart failure was defined as relevant symptoms and signs with either a left ventricular ejection fraction (LVEF) <50% or amino-terminal pro-B-type natriuretic peptide (NTproBNP) >400 pg/mL (or >125 pg/mL if taking loop diuretics)., Results: Of 982 patients, 664 fulfilled the HF criteria and were in sinus rhythm. The median (interquartile range, IQR) LAEF was 42 (31-51)% and 55 (48-61)% in patients with and without HF (P < 0.001). Patients with HF in the lowest quartile of LAEF (23%; IQR: 17-28%) had lower LV and right ventricular (RV) EF, and greater LV and RV mass and higher plasma NTproBNP than those in the highest quartile of LAEF (56%; IQR: 53-61%). Log[LAEF] and log[NTproBNP] were inversely correlated (r = -0.410, P < 0.001). During a median follow-up of 883 (IQR: 469-1626) days, 394 (59%) patients with HF died or were admitted with HF and 101 (15%) developed atrial fibrillation (AF). In a multivariable Cox model, increasing LAEF, but not LVEF, was independently associated with survival (HR for 10% change: 0.81 (95%CI: 0.73-0.90), P = <0.001). Increasing age and decreasing LAEF predicted incident AF., Conclusions: In patients with HF, LAEF predicts adverse outcome independently of other measures of cardiac dysfunction., (Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2014. For permissions please email: journals.permissions@oup.com.)

Aims: To investigate the prognostic impact of atherosclerotic renovascular disease in patients with chronic heart failure., Methods and Results: Patients with heart failure due to left ventricular systolic dysfunction underwent cardiac magnetic resonance imaging and contrast-enhanced magnetic resonance angiography. Renal artery stenosis (RAS) was defined as a luminal narrowing >50%. Of the 366 patients investigated, 112 (31%) had RAS, of whom 41 had bilateral RAS. Patients with RAS were older (P < 0.001), had higher blood pressure (P < 0.001), and worse renal function (P = 0.001). In addition, these patients had more admissions and more prolonged hospital stays because of vascular events (0.09 ± 0.26 vs. 0.02 ± 0.16 admissions/per patient/year; P < 0.001; and 1.26 ± 5.79 vs. 0.31 ± 2.54 days/per patient/year; P < 0.001, respectively) and worse prognosis (hazard ratio 1.60, 95% confidence interval 1.10-2.34, P = 0.015). However, in multivariable analysis, a history of diabetes mellitus, decreasing haemoglobin, and increasing left ventricular end-systolic volume index, but not age and RAS, were independently related to outcome., Conclusions: RAS is a common finding in patients suffering from heart failure. Although it is associated with an increased vascular morbidity, it is not an independent predictor of mortality.

Aortic atherosclerosis reduces compliance in the systemic circulation and increases peripheral resistance, afterload and left ventricular wall stress. In patients with heart failure, these changes can impair left ventricular systolic function and energy efficiency, which could reduce exercise capacity. Though the interaction and the impact of aortic atherosclerosis on left ventricular function have been investigated, its prognostic implications in patients with heart failure are unclear. We used cardiac magnetic resonance imaging and gadolinium-enhanced abdominal aortography to investigate the prevalence and prognostic impact of atherosclerotic disease of the abdominal aorta and its side branches in 355 patients with heart failure. Sclerotic abdominal aortic disease was defined as a luminal narrowing >50% of the aorta and its side branches or the presence of abdominal aortic aneurysm. Patients with disease of the aorta and its branches were older (P < 0.0001), had overall longer stay in hospital (P = 0.006) and had more admissions (P = 0.001) and worse prognosis (hazard ratio: 1.97, 95% confidence interval: 1.29-3.00, P = 0.002) than those without. In a multivariable model, increasing age and pulse pressure, diabetes mellitus and increasing left ventricular end-diastolic volume were associated with a worse prognosis, but sclerotic abdominal aortic disease was not independently related to outcome (hazard ratio: 1.06; 95% confidence interval: 0.64-1.74; P = 0.823). These data demonstrate that atherosclerosis of the abdominal aorta and its side branches is common and associated with increased morbidity in patients with chronic heart failure. How such disease should be managed remains uncertain, but its recognition and characterisation are the first steps in finding out.

Background: Cardiovascular magnetic resonance (CMR) with late gadolinium enhancement (LGE) can provide unique data on the transmural extent of scar/viability. We assessed the prevalence of dysfunctional myocardium, including partial thickness scar, which could contribute to left ventricular contractile dysfunction in patients with heart failure and ischaemic heart disease who denied angina symptoms., Methods: We invited patients with ischaemic heart disease and a left ventricular ejection fraction < 50% by echocardiography to have LGE CMR. Myocardial contractility and transmural extent of scar were assessed using a 17-segment model., Results: The median age of the 193 patients enrolled was 70 (interquartile range: 63-76) years and 167 (87%) were men. Of 3281 myocardial segments assessed, 1759 (54%) were dysfunctional, of which 581 (33%) showed no scar, 623 (35%) had scar affecting ≤50% of wall thickness and 555 (32%) had scar affecting > 50% of wall thickness. Of 1522 segments with normal contractile function, only 98 (6%) had evidence of scar on CMR. Overall, 182 (94%) patients had ≥1 and 107 (55%) patients had ≥5 segments with contractile dysfunction that had no scar or ≤50% transmural scar suggesting viability., Conclusions: In this cohort of patients with left ventricular systolic dysfunction and ischaemic heart disease, about half of all segments had contractile dysfunction but only one third of these had > 50% of the wall thickness affected by scar, suggesting that most dysfunctional segments could improve in response to an appropriate intervention.

Aims: The aim of this study was to investigate the prognostic impact of right ventricular (RV) size in patients with chronic heart failure., Methods and Results: Normal volunteers (n = 80) and patients (n = 380) with left ventricular (LV) ejection fraction <45% on echocardiography and on optimal treatment for heart failure underwent cardiac magnetic resonance imaging with measurement of LV and RV volumes, mass and ejection fraction. The mean and the standard deviation (SD) of the RV end-systolic volume index in normal subjects were used to define the normal range as: mean RV end-systolic volume index +2 SD. Patients with dilated RV (>2 SD beyond the mean) (25%) had more frequent evidence of fluid overload in clinical examination and greater LV dimensions (P < 0.0001). During follow-up (median 45, interquartile range: 28-66 months), 37% of patients with and 24% without RV dilation died (log-rank test = 8.4; P = 0.004). In a multivariable Cox regression model, including 13 other clinical variables, RV (HR: 1.08/10 mL/m(2), 95% CI: 1.00-1.18, P = 0.044), but not LV, end-systolic volume index predicted a worse outcome., Conclusion: Twenty-five per cent of patients with heart failure due to LV systolic dysfunction have a dilated right ventricle. Greater RV dimensions predict mortality in patients with chronic heart failure. Treatments aimed at preserving or enhancing RV structure and function, possibly by unloading the RV by reducing pulmonary vascular resistance or left atrial pressure, should be investigated.

Aims: Non-invasive assessment of left ventricular (LV) structure and function is important in the evaluation of cardiac patients. This study was designed to test the accuracy and reproducibility of new generation 3-dimensional echocardiography (3DE) in measuring volumetric and functional LV indices as compared with current "gold standard" of non-invasive cardiac imaging, cardiac magnetic resonance (CMR)., Methods and Results: Sixty-four subjects with good acoustic windows, including 40 cardiac patients with LV ejection fraction (EF)<45%, 14 patients with EF>45% and 10 normal volunteers underwent 3DE using a commercially available Philips Sonos 7500 scanner equipped with a matrix phase-array x4 xMATRIX transducer, and CMR on a 1.5 T Signa CV/i scanner (GE Medical Systems). Volumetric assessment was performed with analytical 4D-LV-Analysis software (TomTec) for 3DE and MRI-Mass software (Medis) for CMR. We found no significant differences in LV end-diastolic volume (EDV), end-systolic volume (ESV) and EF with excellent correlations between the indices measured using 3DE and CMR (r=0.97, r=0.98, and r=0.94, respectively). Bland-Altman analysis showed bias of 7 ml for EDV, 3 ml for ESV and -1% for EF with 3DE with corresponding limits of agreement (2SD) of 28 ml, 22 ml and 10%, respectively. Intraobserver and interobserver variabilities were for EDV: 3% and 4% (3DE) vs 2% and 2% (CMR), for ESV: 3% and 6% (3DE) vs 2% and 3% (CMR), and for EF: 4% and 4% (3DE) vs 2% and 4% (CMR), respectively., Conclusion: New generation 3DE provides accurate and reproducible quantification of LV volumetric and functional data in subjects with good acoustic windows as compared with CMR.

Background: The heart transforms structurally and functionally with age but the nature and magnitude of reported changes appear inconsistent. This study was designed to assess left ventricular (LV) morphology, global and longitudinal function in healthy older men and women using cardiac magnetic resonance (CMR)., Methods: Ninety-five healthy subjects (age 62+/-16 years, range 22-91 years) underwent breath-hold cine CMR. LV end-diastolic volume (EDV), end-systolic volume (ESV), myocardial mass, ejection fraction (EF), mass-to-volume ratio, mean midventricular wall motion, thickness and thickening were calculated from short-axis data sets. Average mitral annular displacement was measured to assess longitudinal LV function., Results: Subjects were divided according to age (< 65 and > or = 65 years) and sex. EDV and ESV indices (corrected for body surface area) decreased whilst EF increased with age. There was no difference in LV myocardial mass index between the age groups, but midventricular wall thickness was significantly higher in older people. Mass-to-volume ratio also increased with age. In contrast to EF, mitral annular displacement declined with age. Midventricular LV wall thickness, myocardial mass index and mass-to-volume ratio were higher in men than in women but there were no differences in measures of global and longitudinal LV systolic function., Conclusions: Due to smaller LV volumes but higher wall thickness, myocardial mass remains unchanged with age. We have found an age-related increase in EF and reduction in longitudinal LV function in apparently normal subjects. This must be borne in mind when assessing older patients with possible heart failure and normal LV systolic function. Men have higher myocardial mass than women.