Comparison of T1 mapping techniques for ECV quantification. histological validation and reproducibility of ShMOLLI versus multibreath-hold T1 quantification equilibrium contrast CMR

BACKGROUND: Myocardial extracellular volume (ECV) is elevated in fibrosis or infiltration and can be quantified by measuring the haematocrit with pre and post contrast T1 at sufficient contrast equilibrium. Equilibrium CMR (EQ-CMR), using a bolus-infusion protocol, has been shown to provide robust measurements of ECV using a multibreath-hold T1 pulse sequence. Newer, faster sequences for T1 mapping promise whole heart coverage and improved clinical utility, but have not been validated. METHODS: Multibreathhold T1 quantification with heart rate correction and single breath-hold T1 mapping using Shortened Modified Look-Locker Inversion recovery (ShMOLLI) were used in equilibrium contrast CMR to generate ECV values and compared in 3 ways.Firstly, both techniques were compared in a spectrum of disease with variable ECV expansion (n=100, 50 healthy volunteers, 12 patients with hypertrophic cardiomyopathy, 18 with severe aortic stenosis, 20 with amyloid). Secondly, both techniques were correlated to human histological collagen volume fraction (CVF%, n=18, severe aortic stenosis biopsies). Thirdly, an assessment of test:retest reproducibility of the 2 CMR techniques was performed 1 week apart in individuals with widely different ECVs (n=10 healthy volunteers, n=7 amyloid patients). RESULTS: More patients were able to perform ShMOLLI than the multibreath-hold technique (6% unable to breath-hold). ECV calculated by multibreath-hold T1 and ShMOLLI showed strong correlation (r(2)=0.892), little bias (bias -2.2%, 95%CI -8.9% to 4.6%) and good agreement (ICC 0.922, range 0.802 to 0.961, p<0.0001). ECV correlated with histological CVF% by multibreath-hold ECV (r(2)= 0.589) but better by ShMOLLI ECV (r(2)= 0.685). Inter-study reproducibility demonstrated that ShMOLLI ECV trended towards greater reproducibility than the multibreath-hold ECV, although this did not reach statistical significance (95%CI -4.9% to 5.4% versus 95%CI -6.4% to 7.3% respectively, p=0.21). CONCLUSIONS: ECV quantification by single breath-hold ShMOLLI T1 mapping can measure ECV by EQ-CMR across the spectrum of interstitial expansion. It is procedurally better tolerated, slightly more reproducible and better correlates with histology compared to the older multibreath-hold FLASH techniques

Fully Automated Myocardial Strain Estimation from Cardiovascular MRI–tagged Images Using a Deep Learning Framework in the UK Biobank

Purpose: To demonstrate the feasibility and performance of a fully automated deep learning framework to estimate myocardial strain from short-axis cardiac magnetic resonance tagged images. Methods and Materials: In this retrospective cross-sectional study, 4508 cases from the UK Biobank were split randomly into 3244 training and 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 1) a convolutional neural network (CNN) for localization, and 2) 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 basal, mid, and apical slices respectively (mean +/- std. dev. of differences between predicted and manual strain). The framework reproduced significant reductions in circumferential strain in diabetics, hypertensives, and participants with previous heart attack. Typical processing time was ~260 frames (~13 slices) per second on an NVIDIA Tesla K40 with 12GB RAM, compared with 6-8 minutes per slice for the manual analysis. Conclusions: The fully automated RNNCNN 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.Comment: accepted in Radiology Cardiothoracic Imagin

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

Validation of Cardiovascular Magnetic Resonance-Derived Equation for Predicted Left Ventricular Mass Using the UK Biobank Imaging Cohort: Tool for Donor-Recipient Size Matching.

BACKGROUND: Current guidance from International Society for Heart and Lung Transplantation recommends using body weight for donor-recipient size matching for heart transplantation. However, recent studies have shown that predicted heart mass, using body weight, height, age, and sex, may represent a better method of size matching. We aim to validate a cardiovascular magnetic resonance (CMR)-derived equation for predicted left ventricular mass (LVM) in a cohort of normal individuals in the United Kingdom. METHODS: This observational study was conducted in 5065 middle-aged (44-77 years old) UK Biobank participants who underwent CMR imaging in 2014 to 2015. Individuals with cancer diagnosis in the previous 12 months or history of cardiovascular disease were excluded. Predicted LVM was calculated based on participants' sex, height, and weight recorded at the time of imaging. Correlation analyses were performed between the predicted LVM and the LVM obtained from manual contouring of CMR cine images. The analysis included 3398 participants (age 61.5±7.5 years, 47.8% males). RESULTS: Predicted LVM was considerably higher than CMR-derived LVM (mean±SD of 138.8±28.9 g versus 86.3±20.9 g). However, there was a strong correlation between the 2 measurements (Spearman correlation coefficient 0.802, P<0.0001). CONCLUSIONS: Predicted LVM calculated using a CMR-derived equation that incorporates height, weight, and sex has a strong correlation with CMR LVM in large cohort of normal individuals in the United Kingdom. Our findings suggest that predicted heart mass equations may be a valid tool for donor-recipient size matching for heart transplantation in the United Kingdom

Prospective association between handgrip strength and cardiac structure and function in UK adults.

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

Light to moderate coffee consumption is associated with lower risk of death: a UK Biobank study

Aims: To study the association of daily coffee consumption with all-cause and cardiovascular (CV) mortality and major CV outcomes. In a subgroup of participants who underwent cardiovascular magnetic resonance (CMR) imaging, we evaluated the association between regular coffee intake and cardiac structure and function.Methods: UK Biobank participants without clinically manifested heart disease at the time of recruitment were included. Regular coffee intake was categorized into 3 groups: zero, light-to-moderate (0.5-3 cups/day) and high (&gt;3 cups/day). In the multivariate analysis, we adjusted for the main CV risk factors.Results: We included 468,629 individuals (56.2 ± 8.1 years, 44.2% male), 22.1% did not consume coffee on a regular basis, 58.4% had 0.5-3 cups per day and 19.5% had &gt;3 cups per day. Compared to non-coffee drinkers, light-to-moderate (0.5-3 cups per day) coffee drinking was associated with lower risk of all-cause mortality (multivariate HR = 0.88, 95%CI : 0.83-0.92; p &lt; 0.001) and CV mortality (multivariate HR = 0.83, 95%CI : 0.74-0.94; p = 0.006), and incident stroke (multivariate HR = 0.79, 95%CI : 0.63-0.99 p = 0.037) after a median follow-up of 11 years. CMR data were available in 30,650 participants. Both light-to-moderate and high coffee consuming categories were associated with dose-dependent increased left and right ventricular end-diastolic, end-systolic and stroke volumes, as well as greater left ventricular mass. Conclusion: Coffee consumption of up to 3 cups per day was associated with favorable CV outcomes. Regular coffee consumption was also associated with a likely healthy pattern of CMR metrics in keeping with the reverse of age-related cardiac alterations

Adverse cardiovascular magnetic resonance phenotypes are associated with greater likelihood of incident coronavirus disease 2019: findings from the UK Biobank.

BACKGROUND: Coronavirus disease 2019 (COVID-19) disproportionately affects older people. Observational studies suggest indolent cardiovascular involvement after recovery from acute COVID-19. However, these findings may reflect pre-existing cardiac phenotypes. AIMS: We tested the association of baseline cardiovascular magnetic resonance (CMR) phenotypes with incident COVID-19. METHODS: We studied UK Biobank participants with CMR imaging and COVID-19 testing. We considered left and right ventricular (LV, RV) volumes, ejection fractions, and stroke volumes, LV mass, LV strain, native T1, aortic distensibility, and arterial stiffness index. COVID-19 test results were obtained from Public Health England. Co-morbidities were ascertained from self-report and hospital episode statistics (HES). Critical care admission and death were from HES and death register records. We investigated the association of each cardiovascular measure with COVID-19 test result in multivariable logistic regression models adjusting for age, sex, ethnicity, deprivation, body mass index, smoking, diabetes, hypertension, high cholesterol, and prior myocardial infarction. RESULTS: We studied 310 participants (n = 70 positive). Median age was 63.8 [57.5, 72.1] years; 51.0% (n = 158) were male. 78.7% (n = 244) were tested in hospital, 3.5% (n = 11) required critical care admission, and 6.1% (n = 19) died. In fully adjusted models, smaller LV/RV end-diastolic volumes, smaller LV stroke volume, and poorer global longitudinal strain were associated with significantly higher odds of COVID-19 positivity. DISCUSSION: We demonstrate association of pre-existing adverse CMR phenotypes with greater odds of COVID-19 positivity independent of classical cardiovascular risk factors. CONCLUSIONS: Observational reports of cardiovascular involvement after COVID-19 may, at least partly, reflect pre-existing cardiac status rather than COVID-19 induced alterations