Layer-specific Strain Analysis with Cardiac MRI Feature Tracking in Acute Myocarditis

Alexander Isaak; Dmitrij Kravchenko; Narine Mesropyan; Christoph Endler; Leon M Bischoff; Thomas Vollbrecht; Daniel Thomas; Darius Dabir; Sebastian Zimmer; Ulrike Attenberger; Daniel Kuetting; Julian A Luetkens

doi:10.1148/ryct.210318

Layer-specific Strain Analysis with Cardiac MRI Feature Tracking in Acute Myocarditis

Radiol Cardiothorac Imaging. 2022 Jun 9;4(3):e210318. doi: 10.1148/ryct.210318. eCollection 2022 Jun.

Affiliation

¹ Department of Diagnostic and Interventional Radiology (A.I., D. Kravchenko, N.M., C.E., L.M.B., T.V., D.D., U.A., D. Kuetting, J.A.L.) and Department of Internal Medicine II-Cardiology (S.Z.), University Hospital Bonn, Venusberg-Campus 1, 53127 Bonn, Germany; Quantitative Imaging Laboratory Bonn (QILaB), Bonn, Germany (A.I., D. Kravchenko, N.M., C.E., L.M.B., T.V., D. Kuetting, J.A.L.); and Department of Diagnostic and Interventional Radiology, St Vinzenz-Hospital, Cologne, Germany (D.T.).

Abstract

Purpose: To evaluate the diagnostic performance of layer-specific cardiac MRI feature-tracking (FT) strain analysis in patients with acute myocarditis.

Materials and methods: Seventy patients (mean age, 43 years ± 19 [SD]; 46 men) with clinically defined acute myocarditis and 42 healthy controls who underwent cardiac MRI from March 2014 to November 2018 were retrospectively analyzed. FT-based left ventricular peak systolic global longitudinal strain (GLS) and global circumferential strain (GCS) were assessed at subendocardial, midmyocardial, and subepicardial layers. The 2018 Lake Louise criteria (LLC) were assessed. Patients with myocarditis were dichotomized into two groups: those with preserved and those with reduced ejection fraction. For statistical analysis, unpaired t test, one-way analysis of variance, Pearson correlation, and receiver operating characteristic analysis were used.

Results: GLS and GCS values of all layers (eg, midmyocardial GCS: -21.3% ± 5.5 vs -28.0% ± 4.3; P < .001) were impaired in patients with myocarditis compared with controls. Only subepicardial GLS (-20.0% ± 3.3 vs -17.5% ± 3.3; P < .001) and midmyocardial GCS values (-28.0% ± 4.3 vs -23.1% ± 4.3; P < .001) could differentiate between controls and patients with preserved ejection fraction. Midmyocardial GCS correlated with inflammatory myocardial parameters (eg, late gadolinium enhancement percentage, r = 0.48, P < .001). Midmyocardial GCS (area under the receiver operating characteristic curve [AUC], 0.82) and subepicardial GLS (AUC, 0.77) had the highest diagnostic performance for acute myocarditis diagnosis (P < .05 against all other strain parameters). The diagnostic performance of the 2018 LLC was significantly improved by inclusion of these two strain parameters (AUC, 0.92 vs 0.97; P = .04).

Conclusion: Diagnostic performance of cardiac MRI FT strain was different between myocardial layers in acute myocarditis, with midmyocardial GCS and subepicardial GLS providing the highest diagnostic performance.Keywords: MRI, Cardiac, Heart, Left Ventricle, Inflammation, Tissue Characterization, MR-Functional Imaging, Feature-Tracking Strain, Acute Myocarditis Supplemental material is available for this article. © RSNA, 2022.

Keywords: Acute Myocarditis; Cardiac; Feature-Tracking Strain; Heart; Inflammation; Left Ventricle; MRI; MR–Functional Imaging; Tissue Characterization.