From Recognized to Novel Quantitative CMR Biomarkers of LV Recovery: A Paradigm Shift in Acute Myocardial Infarction Imaging

Comprehensive characterization of cardiac contraction for improved post-infarction risk assessment

This study aims at identifying risk-related patterns of left ventricular contraction dynamics via novel volume transient characterization. A multicenter cohort of AMI survivors (n = 1021) who underwent Cardiac Magnetic Resonance (CMR) after infarction was considered for the study. The clinical endpoint was the 12-month rate of major adverse cardiac events (MACE, n = 73), consisting of all-cause death, reinfarction, and new congestive heart failure. Cardiac function was characterized from CMR in 3 potential directions: by (1) volume temporal transients (i.e. contraction dynamics); (2) feature tracking strain analysis (i.e. bulk tissue peak contraction); and (3) 3D shape analysis (i.e. 3D contraction morphology). A fully automated pipeline was developed to extract conventional and novel artificial-intelligence-derived metrics of cardiac contraction, and their relationship with MACE was investigated. Any of the 3 proposed directions demonstrated its additional prognostic value on top of established CMR indexes, myocardial injury markers, basic characteristics, and cardiovascular risk factors (P < 0.001). The combination of these 3 directions of enhancement towards a final CMR risk model improved MACE prediction by 13% compared to clinical baseline (0.774 (0.771-0.777) vs. 0.683 (0.681-0.685) cross-validated AUC, P < 0.001). The study evidences the contribution of the novel contraction characterization, enabled by a fully automated pipeline, to post-infarction assessment.

Combined T1-mapping and tissue tracking analysis predicts severity of ischemic injury following acute STEMI-an Oxford Acute Myocardial Infarction (OxAMI) study

Early risk stratification after ST-segment–elevation myocardial infarction (STEMI) is of major clinical importance. Strain quantifies myocardial deformation and can demonstrate abnormal global and segmental myocardial function in acute ischaemia. Native T1-mapping allows assessment of the severity of acute ischemic injury, however its clinical applicability early post MI is limited by the complex dynamic changes happening in the myocardium post MI. We aimed to explore relationship between T1-mapping and feature tracking imaging, to establish whether combined analysis of these parameters could predict recovery after STEMI. 96 STEMI patients (aged 60 ± 11) prospectively recruited in the Oxford Acute Myocardial Infarction (OxAMI) study underwent 3T-CMR scans acutely (within 53 ± 32 h from primary percutaneous coronary intervention) and at 6 months (6M). The imaging protocol included: cine, ShMOLLI T1-mapping and late gadolinium enhancement (LGE). Segments were divided in the infarct, adjacent and remote zones based on the presence of LGE. Peak circumferential (Ecc) and radial (Err) strain was assessed using cvi42 software. Acute segmental strain correlated with segmental T1-mapping values (T1 vs. Err − 0.75 ± 0.25, p < 0.01; T1 vs. Ecc 0.72 ± 0.32, p < 0.01) and with LGE segmental injury (LGE vs. Err − 0.56 ± 0.29, p < 0.01; LGE vs. Ecc 0.54 ± 0.35, p < 0.01). Moreover, acute segmental T1 and strain predicted segmental LGE transmurality on 6M scans (p < 0.001, r = 0.5). Multiple regression analysis confirmed combined analysis of global Ecc and T1-mapping was significantly better than either method alone in predicting final infarct size at 6M (r = 0.556 vs r = 0.473 for global T1 only and r = 0.476 for global Ecc only, p < 0.001). This novel CMR method combining T1-mapping and feature tracking analysis of acute CMR scans predicts LGE transmurality and infarct size at 6M following STEMI.