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Updated: Jul 26, 2025

Cardiac Magnetic Resonance for the Evaluation of Suspected Cardiac Thrombus: Conventional and Emerging Techniques
Published on: June 11, 2019
Improved detection of echocardiographically occult left ventricular thrombi following ST-elevation myocardial
Martin Reindl1, Ivan Lechner1, Magdalena Holzknecht1
1University Clinic of Internal Medicine III, Cardiology and Angiology, Medical University of Innsbruck, Anichstrasse 35, A-6020 Innsbruck, Austria.
Aim:
The aim of this study was to investigate predictors of transthoracic echocardiography (TTE)-occult left ventricular (LV) thrombi (LVT) and to propose a clinical model for improved detection of TTE-occult LVT post-ST-elevation myocardial infarction (STEMI). Patients with acute STEMI are at significant risk for developing LVT. However, this complication often (up to 65%) remains undetected by using TTE, referred to as TTE-occult LVT.
Methods And Results:
In total, 870 STEMI patients underwent TTE and cardiac magnetic resonance (CMR), the reference method for LVT detection, 3 days after infarction. Clinical (body mass index, peak cardiac troponin T) and echocardiographic [ejection fraction, apical wall motion scores (AWMSs)] predictors were analysed. Primary endpoint was the presence of TTE-occult LVT identified by CMR imaging. From the overall cohort, 37 patients (4%) showed an LVT by CMR. Of these thrombi, 25 (68%) were not identified by TTE. Transthoracic echocardiography-occult thrombi did not significantly differ in volume (1.4 vs. 2.74 cm3), diameter (19.0 vs. 23.3 mm), and number of fragments or shape compared with TTE-apparent LVT (all P > 0.05). For predicting these TTE-occult LVT, the 16-segment AWMS (AWMS16Seg) showed highest validity {area under the curve: 0.91 [95% confidence interval (CI): 0.89-0.93]; P < 0.001}, with an association independent of ejection fraction and 17-segment AWMS (AWMS17Seg) [odds ratio: 1.68 (95% CI: 1.43-1.97); P < 0.001] and clinical (body mass index, peak troponin) and angiographic (culprit lesion, post-interventional thrombolysis in myocardial infarction flow) associates of TTE-occult LVT (all P < 0.05). Dichotomization at AWMS16Seg ≥ 8 (n = 260, 30%) allowed for a detection of all TTE-occult LVT (sensitivity: 100%), with a corresponding specificity of 77%.
Conclusion:
After acute STEMI, AWMS16Seg served as a simple and very robust predictor of TTE-occult LVT. An AWMS16Seg-based algorithm to identify patients for additional CMR imaging offers great potential to optimize detection of TTE-occult LVT following STEMI.
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