Thrombus formation in the left ventricle after large myocardial infarction – assessment with cardiac magnetic resonance imaging

• Published in: Swiss medical weekly Vol. 145; no. 2526; p. w14122
• Main Authors: Sürder, Daniel, Gisler, Valentin, Corti, Roberto, Moccetti, Tiziano, Klersy, Catherine, Zuber, Michel, Windecker, Stephan, Moschovitis, Aris, Kozerke, Sebastian, Lüscher, Thomas Felix, Erne, Paul, Manka, Robert
• Format: Journal Article
• Language: English
• Published: Switzerland SMW supporting association (Trägerverein Swiss Medical Weekly SMW) 22-06-2015
• Subjects: Aged; Anticoagulants; Anticoagulants - therapeutic use; Body Mass Index; coronary thrombosis; Echocardiography; Female; Heart Ventricles - diagnostic imaging; Humans; Magnetic Resonance Imaging; Male; myocardial infarction; Myocardial Infarction - complications; Platelet Count; Radiography; Thrombosis - diagnostic imaging; Thrombosis - drug therapy; Thrombosis - etiology
• ISSN: 1424-7860; 1424-3997
• DOI: 10.4414/smw.2015.14122

Left ventricular thrombus (LVT) formation may worsen the post-infarct outcome as a result of thromboembolic events. It also complicates the use of modern antiplatelet regimens, which are not compatible with long-term oral anticoagulation. The knowledge of the incidence of LVT may therefore be of importance to guide antiplatelet and antithrombotic therapy after acute myocardial infarction (AMI).
In 177 patients with large, mainly anterior AMI, standard cardiac magnetic resonance imaging (CMR) including cine and late gadolinium enhancement (LGE) imaging was performed shortly after AMI as per protocol. CMR images were analysed at an independent core laboratory blinded to the clinical data. Transthoracic echocardiography (TTE) was not mandatory for the trial, but was performed in 64% of the cases following standard of care. In a logistic model, 3 out of 61 parameters were used in a multivariable model to predict LVT.
LVT was detected by use of CMR in 6.2% (95% confidence interval [CI] 3.1%-10.8%). LGE sequences were best to detect LVT, which may be missed in cine sequences. We identified body mass index (odds ratio 1.18; p = 0.01), baseline platelet count (odds ratio 1.01, p = 0.01) and infarct size as assessed by use of CMR (odds ratio 1.03, p = 0.02) as best predictors for LVT. The agreement between TTE and CMR for the detection of LVT is substantial (kappa = 0.70).
In the current analysis, the incidence of LVT shortly after AMI is relatively low, even in a patient population at high risk. An optimal modality for LVT detection is LGE-CMR but TTE has an acceptable accuracy when LGE-CMR is not available.