Cardiac volumes, function and mass were measured in line with standardized post-processing recommendations44. Papillary muscles were included as a part of the LV blood volume (suiteHEART, NeoSoft). LV end-diastolic volumes (EDVs) and end-systolic volumes (ESVs) were determined using the rule of discs. Ejection fraction was computed as (EDV − ESV) / EDV. All volumetric indices were normalized to body surface area. Reference values were based on the UK Biobank Study30. Myocardial T1 and T2 relaxation times were measured in the septal myocardium of the midventricular SAX slice45, as per internal standardized operating procedures and with quality control by the core laboratory staff, blinded to the underlying clinical information and group allocation using pseudonymized datasets. The quality of the motion correction and co-registration of the inline maps was verified on the scanner, and, if unsatisfactory, the acquisition was repeated. Manual motion correction by propagating the septal region of interest through the individual images, followed by the manual image co-registration, was performed if not resolved by the means above. Areas of LGE were excluded from the measurements to avoid confounding diffuse fibrosis with replacement scar. Interpretation of LGE images followed standardized post-processing recommendations. Myocardial LGE was visually defined by two observers based on the presence and predominant pattern as ischemic or non-ischemic44. Pericardial involvement was considered present when enhancement involved both pericardial layers, irrespective of the size of pericardial effusion46. Cine images were employed for derivation of GLS analyses using Medis Suite MR version 2.1 (Medis Medical Imaging Systems)47.

Statistical analysis

Data were entered using electronic case report forms in REDCap (Research Electronic Data Capture, Vanderbilt University). All analysis was performed using R version 3.6.1 (https://www.r-project.org/). Normality of distributions was tested using the Shapiro–Wilk test. Categorical data are presented as counts (percentages) and continuous variables as mean (± s.d.) or medians (IQRs), as appropriate for the type of data. Comparisons between groups were conducted using one-way ANOVA for normally distributed parameters and Kruskal–Wallis rank-sum test for non-normally distributed data. Fischer exact and χ2 tests were used for proportions. ANCOVAs adjusted for baseline values were used to assess the differences between the baseline and follow-up of the whole cohort as well as to compare follow-up observations between different groups and timepoints, using the baseline variable as a covariate. Least square means with 95% confidence intervals (CIs) were reported with adjustment for baseline. In case of P < 0.05 on the global level, pairwise comparisons were conducted and adjusted using Bonferroni correction. Exploratory univariate and multivariate analyses were used to predict the presence of symptoms at follow-up using binary logistic regression and presented with odds ratios (ORs), 95% CIs and P values. q-values are provided to correct for the false discovery rate in multiple testing. The univariate analysis focuses on the potential association of clinical, blood and imaging variables with regard to cardiac symptom status as the outcome variable. We included a priori variables of interest but omitted rarer occurrences, such as risk factors. All tests were two-tailed. P values less than 0.001 were considered statistically significant.

Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.