The value of cardiac MRI texture analysis in patients with clinically suspected myocarditis

Abstract

Purpose: The aim of this proof-of-concept study was to assess the diagnostic value of texture analysis (TA) based on conventional balanced steady-state-free precession (bSSFP), late gadolinium enhancement (LGE) and T2-weighted cardiac magnetic resonance imaging (CMRI) in patients with clinically suspected myocarditis. Method: A retrospective cohort study was performed based on 30 patients who underwent a comprehensive CMRI due to clinically suspected myocarditis between 2013 and 2018 at the Sahlgrenska University Hospital: 10 patients with clinical signs and positive myocardial biomarkers (Troponin T, indicating myocardial injury) as well as positive CMRI findings according to Lake Louise Criteria (LLC; group 1), 10 patients with clinical signs and positive myocardial biomarkers but negative CMRI findings according to LLC (group 2), and 10 patients with clinical signs but both negative myocardial biomarkers as well as CMRI findings according to LLC (control group). TA was performed on regions-of-interest, encompassing the left ventricle, on short axis bSSFP, LGE and T2-weighted images using a freely available software package. Promising features were selected to assess their diagnostic potential. Result: The differentiation between group 1 and the control group was possible with the help of three texture features based on bSSFP images (Variance: p = 0.004, Gradient Mean: p < 0.001, and Sum Average: p < 0.001), four texture features based on LGE images (Variance: p < 0.001, Skewness: p = 0.004, Gradient Mean: p < 0.001, and Sum Average: p < 0.001) and two texture features based on T2-weighted images (Skewness: p < 0.001 and Sum Average: p = 0.01). Conclusion: Our results show that TA is feasible based on conventional bSSFP, LGE and T2-weighted CMRI enabling automated detection of myocarditisin patients with initial clinical suspicion, emphasizing the value of bSSFP imaging as a promising non-contrast tissue characterization technique.