A comprehensive CMR analysis improves risk stratification in left ventricular noncompaction

Abstract

Abstract Background Left ventricular noncompaction (LVNC) is a heterogeneous and controversial entity. Risk assessment by cardiovascular magnetic resonance (CMR) remains poorly defined. Purpose To develop a CMR prediction model of major adverse cardiovascular events (MACE) in LVNC. Methods We conducted a retrospective longitudinal multicentre cohort study of LVNC patients with core-lab CMR analysis. The endpoint was a composite of MACE: heart failure, ventricular arrhythmias, systemic embolisms and all-cause death. The effect of variables on the endpoint was analysed by Cox regression and variables were dichotomized according to their association with the outcome. Three sequential prediction models were developed: a "traditional model" based on LV ejection fraction (LVEF); a "clinical model" based on daily-practice CMR variables (e.g.: LVEF, right ventricular (RV) EF, and late gadolinium enhancement (LGE)); and a "research model" including advanced parameters (e.g.: global longitudinal strain (GLS) and hemodynamic forces (HDF)). The best prediction models were chosen based on C-statistic and Akaike information criterion (AIC). A risk score was developed based on the third model, and according to proportional hazard ratios. Results A total of 348 patients were included, age was 46 (19) years and 150 (43%) were female. LVEF was 48 (14) % and 32 (10%) had LGE. During a median follow-up of 3.9 (1.8-6.1) years, 54 (16%) patients developed MACE: 27 (8%) heart failure, 32 (9%) ventricular arrhythmias, 2 (1%) systemic embolisms and 6 (2%) deaths. Figure 1 shows the association of the main CMR variables with the endpoint. The "traditional model" (dichotomic LVEF with cut-off point at 40%) had an AUC of 0.71 (95% CI: 0.64-0.78). The best "clinical model" was a combination of LVEF, RVEF (cut-off point 35%), left atrium (LA) volume index (cut-off point 53 mL/m2) and percentage of LGE mass (LGE%, cut-off point 5%), with an AUC of 0.77 (95% CI: 0.70-0.85; p=0.006 compared to the first model). The best "research model" included LVEF, RVEF, LGE%, LA GLS (two cut-off points 17% and 28%), and lateral-septal HDF (cut-off point 3%), with an AUC of 0.85 (95% CI: 0.80-0.90; p=0.007 compared to the second model) (Figure 2a). Subsequently, a risk score was developed: 1 point was assigned to LVEF<40%, RVEF<35%, LGE% >5% and LA-GLS <28%, 2 points to LA-GLS <17% and 4 points to HDF<3%. The score was accurate at identifying both low- (0-4 points), intermediate- (5-7 points) and high-risk (8-9 points) patients (Figure 2b). Conclusions A comprehensive CMR evaluation in LVNC allows for precise risk stratification. Our proposed prediction model could be used to individualise patients’ management, which might improve long-term outcomes.CMR characteristics according to MACEPrediction models of MACE and risk score