The Lake Louise criteria (LLc) are the current diagnostic gold standard for the diagnosis of myocarditis. However, they have been developed with the purpose of diagnosing mainly infective myocarditis.
We hypothesized that the LLc would underperform in the detection of myocardial inflammation in autoimmune disease compared to infective myocarditis. We aimed to demonstrate this in a cohort of patients with systemic sclerosis (SSc).
34 patients with suspected infectious myocarditis, 32 diffuse cutaneous SSc patients with a clinical suspicion of cardiac involvement, as well as 31 healthy controls were evaluated with cardiovascular magnetic resonance imaging (CMR) using a 1.5T scanner. The T2 signal ratio (myocardium/skeletal muscle), early and late gadolinium enhancement (EGE/LGE) as well as parametric indices including native/post-contrast T1-mapping, T2 mapping and extracellular volume fraction (ECV) values were determined for all participants. The LLc were compared with a diagnostic model including parametric indices using locally defined cut-off values (Figure 1).
Both the LLc and our proposed model had complete agreement in healthy controls (0 diagnoses of myocarditis). In patients with suspected infective myocarditis, the models had an observed agreement of 91.2 % (95% CI: 76.3-98.1%) in 31/34 patients and a Cohen’s kappa value of 0.35 (p<0.001). However, McNemar’s test for marginal homogeneity was not significant (p=0.637). In SSc patients, there was only 65.6% (95% CI: 46.81-81.4%) observed agreement in 21/32 patients, Cohen’s kappa was 0.31 (p<0.01) and McNemar’s test was significant (p<0.001).
Both the LLc criteria and our proposed parametric model have good specificity. Although both models have good agreement with regard to infective myocarditis, the LLc miss approximately a third of the cases of myocardial inflammation in SSc patients compared to the proposed parametric model. In patients with SSc and suspected myocarditis, both the LLc and our proposed parametric model should be used in conjunction in order to ensure optimal detection and prompt initiation of immunosuppressive treatment.