Myocardial scaring in ischemic heart diseases: role of late gadolinium-enhanced cardiac MRI

Abstract

Objective To highlight the role of late gadolinium-enhanced cardiac magnetic resonance (LGE-CMRI) examination in the detection of location and transmural extent of myocardial scarring in relatively short CMRI examination duration. Background It is important to identify viable myocardium in patients with known or suspected ischemic heart disease to improve their long-term survival and to allow patients to avoid the risks associated with revascularization therapy. Patients and methods A total of 30 consecutive patients with suspected or having previous attack of ischemic heart disease were examined by different sequences of CMRI. Morphological, functional, and viability evaluation for distinction of viable and nonviable myocardium had been done by two independent observers. Results Regarding the distribution of LGE myocardium, almost perfect interobserver agreement was observed on per patient basis (κ=1.0 and 95% confidence interval=1.0–1.0) (P=1.0) and on per segment basis(κ=0.98 and 95% confidence interval=0.97–1.0) (P=0.84). On evaluation of transmural extent of LGE on per-segment basis, a substantial interobserver agreement was noted regarding the detection of 1–25% myocardial wall enhancement (κ=1.0 and 95% confidence interval=1.0–1.0). Otherwise, an almost perfect interobserver agreement was noted on detection of other degrees of mural extent of LGE (P=0.94). On correlation of segments with abnormal wall motion abnormalities and LGE, it was noticed that segmental wall motion abnormality could predict myocardial scarring with 58.08% sensitivity and 99.7% specificity; however, normal wall motion cannot exclude myocardial scarring. The overall duration needed for complete CMRI examination was ±35–40 min, with mean duration of 37.5±1.92 min. Conclusion CMR examination is a robust technique that can provide functional, morphological, and viability information in a relatively short CMRI examination duration (±35–40 min), which allow risk stratification of patients and predicting their outcomes.