Does automated 3D imaging of end-systolic shape and contraction improve the prediction of 12-month MACE compared to standard LVEF and ESV in AMI survivors?
Automated 3D left ventricular shape and contraction analysis from CMR significantly improves 12-month MACE prediction in post-AMI patients compared to standard LVEF and ESV.
BACKGROUND: Left ventricular ejection fraction (LVEF) and end-systolic volume (ESV) remain the main imaging biomarkers for post-acute myocardial infarction (AMI) risk stratification. However, they are limited to global systolic function and fail to capture functional and anatomical regional abnormalities, hindering their performance in risk stratification. OBJECTIVES: This study aimed to identify novel 3-dimensional (3D) imaging end-systolic (ES) shape and contraction descriptors toward risk-related features and superior prognosis in AMI. METHODS: A multicenter cohort of AMI survivors (n = 1,021; median age 63 years; 74.5% male) who underwent cardiac magnetic resonance (CMR) at a median of 3 days after infarction were considered for this 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. A fully automated pipeline was developed to segment CMR images, build 3D statistical models of shape and contraction in AMI, and find the 3D patterns related to MACE occurrence. RESULTS: The novel ES shape markers proved to be superior to ESV (median cross-validated area under the receiver-operating characteristic curve 0.681 IQR: 0.679-0.684 vs 0.600 IQR: 0.598-0.602; P < 0.001); and 3D contraction to LVEF (0.716 IQR: 0.714-0.718 vs 0.681 IQR: 0.679-0.684; P < 0.001) in MACE occurrence prediction. They also contributed to a significant improvement in a multivariable setting including CMR markers, cardiovascular risk factors, and basic patient characteristics (0.747 IQR: 0.745-0.749; P < 0.001). Based on these novel 3D descriptors, 3 impairments caused by AMI were identified: global, anterior, and basal, the latter being the most complementary signature to already known predictors. CONCLUSIONS: The quantification of 3D differences in ES shape and contraction, enabled by a fully automated pipeline, improves post-AMI risk prediction and identifies shape and contraction patterns related to MACE occurrence.
Acero et al. (Wed,) studied this question.