Dataset Information

Multivendor comparison of global and regional 2D cardiovascular magnetic resonance feature tracking strains vs tissue tagging at 3T.

ABSTRACT:

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

GLS and GCS by all 3 software had an excellent agreement among each other (ICC = 0.94-0.98 for GLS and ICC = 0.96-0.98 for GCS respectively) and against tagging (ICC = 0.92-0.94 for GLS and ICC = 0.88-0.91 for GCS respectively), while GRS showed inconsistent agreement between vendors (ICC 0.10-0.81). For regional LS, the agreement was good (ICC = 0.68) between 2 vendors but less vs the 3^rd (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.

SUBMITTER: Militaru S

PROVIDER: S-EPMC8117295 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundLeft ventricular segmental wall motion analysis is important for clinical decision making in cardiac diseases. Strain analysis with myocardial tissue tagging is the non-invasive gold standard for quantitative assessment, however, it is time-consuming. Cardiovascular magnetic resonance myocardial feature-tracking (CMR-FT) can rapidly perform strain analysis, because it can be employed with standard CMR cine-imaging. The aim is to validate segmental peak systolic circumferential strain (peak SCS) and time to peak systolic circumferential strain (T2P-SCS) analysed by CMR-FT against tissue tagging, and determine its intra and inter-observer variability.MethodsPatients in whom both cine CMR and tissue tagging has been performed were selected. CMR-FT analysis was done using endocardial (CMR-FTendo) and mid-wall contours (CMR-FTmid). The Intra Class Correlation Coefficient (ICC) and Pearson correlation were calculated.Results10 healthy volunteers, 10 left bundle branch block (LBBB) and 10 hypertrophic cardiomyopathy patients were selected. With CMR-FT all 480 segments were analyzable and with tissue tagging 464 segments.Significant differences in mean peak SCS values of the total study group were present between CMR-FTendo and tissue tagging (-23.8 ± 9.9% vs -13.4 ± 3.3%, p<0.001). Differences were smaller between CMR-FTmid and tissue tagging (-16.4 ± 6.1% vs -13.4 ± 3.3%, p=0.001). The ICC of the mean peak SCS of the total study group between CMR-FTendo and tissue tagging was low (0.19 (95%-CI-0.10-0.49), p=0.02). Comparable results were seen between CMR-FTmid and tissue tagging. In LBBB patients, mean T2P-SCS values measured with CMR-FTendo and CMR-FTmid were 418 ± 66 ms, 454 ± 60 ms, which were longer than with tissue tagging, 376 ± 55 ms, both p<0.05. ICC of the mean T2P-SCS between CMR-FTendo and tissue tagging was 0.64 (95%-CI-0.36-0.81), p<0.001, this was better in the healthy volunteers and LBBB group, whereas the ICC between CMR-FTmid and tissue tagging was lower.The intra and inter-observer agreement of segmental peak SCS with CMR-FTmid was lower compared with tissue tagging; similar results were seen for segmental T2P-SCS.ConclusionsThe intra and inter-observer agreement of segmental peak SCS and T2P-SCS is substantially lower with CMR-FTmid compared with tissue tagging. Therefore, current segmental CMR-FTmid techniques are not yet applicable for clinical and research purposes.

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