Clin Res Cardiol (2022). https://doi.org/10.1007/s00392-022-02002-5

Optimized Clinical Approach to Identify Left Ventricular Thrombi Following ST-Elevation Myocardial Infarction
M. Reindl1, I. Lechner1, M. Holzknecht1, C. Tiller1, P. Fink1, A. Mayr2, F. Troger2, M. Theurl1, G. Klug1, C. Brenner1, A. Bauer1, B. Metzler1, S. J. Reinstadler1
1Department für Innere Medizin III - Kardiologie und Angiologie, Medizinische Universität Innsbruck, Innsbruck, AT; 2Klinik für Radiologie, Medizinische Universität Innsbruck, Innsbruck, AT;

Background: Compared with transthoracic echocardiography (TTE), cardiac magnetic resonance (CMR) imaging has a considerably higher sensitivity for left ventricular (LV) thrombus detection in patients after ST-elevation myocardial infarction (STEMI). However, CMR imaging is not routinely available to screen all STEMI patients. The aim of this study was to establish a simple and robust TTE algorithm that identifies specific patients for additional CMR to optimize LV thrombus detection post-STEMI.   

Methods: In total, 659 consecutive STEMI patients underwent TTE and CMR 3 (interquartile range:2-4) days after infarction (median time difference between both modalities 0.5 days). LV ejection fraction (LVEF) and two different apical wall motion scores (AWMS), one using the 17-segment-model (AWMS17Seg) and one using the 16-segment-model (AWMS16Seg), were evaluated by TTE. Primary endpoint was defined as presence of LV thrombus by CMR (n=31, 5%).

Results: The AWMS16Seg showed highest predictive value (area under the curve [AUC]:0.91 [95%CI:0.89-0.93];p<0.001), which was significantly higher (both p-values for difference:<0.05) compared to LVEF (AUC:0.84 [95%CI:0.82-0.87];p<0.001) and AWMS17Seg (AUC:0.87 [95%CI:0.85-0.90];p<0.001). The relation between AWMS16Seg and LV thrombus remained significant after adjustment for LVEF and AWMS17Seg (odds ratio 1.65 [95%CI:1.16-2.35];p=0.006) as well as for clinical (hypertension, hyperlipidemia, peak troponin) and angiographic (culprit lesion, post-interventional TIMI flow) predictors of LV thrombus (both p<0.001). Dichotomization at AWMS16Seg ≥8 (n=222, 34%) allowed detection of all LV thrombi (sensitivity:100%), with a corresponding specificity of 70% (negative and positive predictive value 100% and 14%, respectively).

Conclusions: AWMS16Seg by TTE served as simple and very robust predictor of CMR-verified LV thrombi post-STEMI. An AWMS16Seg-based TTE algorithm to identify patients for additional CMR imaging offers great potential to optimize detection of LV thrombi following STEMI.

https://dgk.org/kongress_programme/jt2022/aP526.html