Global longitudinal and circumferential strains measured by three different CMR feature tracking software showed excellent agreement with tissue tagging (ICC 0.92-0.94 and 0.88-0.91, respectively), whereas global radial and regional strains showed substantial intervendor variability.
Cross-Sectional (n=61)
Single-blind (observers blinded to clinical data)
No
How do different CMR 2D feature tracking software compare with each other and with tissue tagging for measuring global and regional myocardial strain?
Effect estimate: ICC 0.92-0.94
BACKGROUND: Cardiovascular magnetic resonance (CMR) 2D feature tracking (FT) left ventricular (LV) myocardial strain has seen widespread use to characterize myocardial deformation. Yet, validation of CMR FT measurements remains scarce, particularly for regional strain. Therefore, we aimed to perform intervendor comparison of 3 different FT software against tagging. METHODS: In 61 subjects (18 healthy subjects, 18 patients with chronic myocardial infarction, 15 with dilated cardiomyopathy, and 10 with LV hypertrophy due to hypertrophic cardiomyopathy or aortic stenosis) were prospectively compared global (G) and regional transmural peak-systolic Lagrangian longitudinal (LS), circumferential (CS) and radial strains (RS) by 3 FT software (cvi42, Segment, and Tomtec) among each other and with tagging at 3T. We also evaluated the ability of regional LS, CS, and RS by different FT software vs tagging to identify late gadolinium enhancement (LGE) in the 18 infarct patients. RESULTS: (ICC 0.50-0.59) and moderate to poor (ICC 0.44-0.47) between all three FT software and tagging. Also, for regional CS agreement between 2 software was higher (ICC = 0.80) than against the 3rd (ICC = 0.58-0.60), and both better agreed with tagging (ICC = 0.70-0.72) than the 3rd (ICC = 0.57). Regional RS had more variation in the agreement between methods ranging from good (ICC = 0.75) to poor (ICC = 0.05). Finally, the accuracy of scar detection by regional strains differed among the 3 FT software. While the accuracy of regional LS was similar, CS by one software was less accurate (AUC 0.68) than tagging (AUC 0.80, p < 0.006) and RS less accurate (AUC 0.578) than the other two (AUC 0.76 and 0.73, p < 0.02) to discriminate segments with LGE. CONCLUSIONS: We confirm good agreement of CMR FT and little intervendor difference for GLS and GCS evaluation, with variable agreement for GRS. For regional strain evaluation, intervendor difference was larger, especially for RS, and the diagnostic performance varied more substantially among different vendors for regional strain analysis.
Militaru et al. (Mon,) conducted a cross-sectional in Healthy subjects and patients with cardiac pathologies (myocardial infarction, dilated cardiomyopathy, left ventricular hypertrophy) (n=61). CMR 2D feature tracking (cvi42, Segment, Tomtec) vs. CMR tissue tagging was evaluated on Agreement of global longitudinal strain (GLS) between 3 feature tracking software and tagging (ICC 0.92-0.94). Global longitudinal and circumferential strains measured by three different CMR feature tracking software showed excellent agreement with tissue tagging (ICC 0.92-0.94 and 0.88-0.91, respectively), whereas global radial and regional strains showed substantial intervendor variability.