| Autor: |
Gregory J. Wehner, Linyuan Jing, Christopher M. Haggerty, Jonathan D. Suever, Jing Chen, Sean M. Hamlet, Jared A. Feindt, W. Dimitri Mojsejenko, Mark A. Fogel, Brandon K. Fornwalt |
| Jazyk: |
angličtina |
| Rok vydání: |
2018 |
| Předmět: |
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| Zdroj: |
Journal of Cardiovascular Magnetic Resonance, Vol 20, Iss 1, Pp 1-11 (2018) |
| Druh dokumentu: |
article |
| ISSN: |
1532-429X |
| DOI: |
10.1186/s12968-018-0485-4 |
| Popis: |
Abstract Background Cardiovascular magnetic resonance (CMR) feature tracking is increasingly used to quantify cardiac mechanics from cine CMR imaging, although validation against reference standard techniques has been limited. Furthermore, studies have suggested that commonly-derived metrics, such as peak global strain (reported in 63% of feature tracking studies), can be quantified using contours from just two frames – end-diastole (ED) and end-systole (ES) – without requiring tracking software. We hypothesized that mechanics derived from feature tracking would not agree with those derived from a reference standard (displacement-encoding with stimulated echoes (DENSE) imaging), and that peak strain from feature tracking would agree with that derived using simple processing of only ED and ES contours. Methods We retrospectively identified 88 participants with 186 pairs of DENSE and balanced steady state free precession (bSSFP) image slices acquired at the same locations across two institutions. Left ventricular (LV) strains, torsion, and dyssynchrony were quantified from both feature tracking (TomTec Imaging Systems, Circle Cardiovascular Imaging) and DENSE. Contour-based strains from bSSFP images were derived from ED and ES contours. Agreement was assessed with Bland-Altman analyses and coefficients of variation (CoV). All biases are reported in absolute percentage. Results Comparison results were similar for both vendor packages (TomTec and Circle), and thus only TomTec Imaging System data are reported in the abstract for simplicity. Compared to DENSE, mid-ventricular circumferential strain (Ecc) from feature tracking had acceptable agreement (bias: − 0.4%, p = 0.36, CoV: 11%). However, feature tracking significantly overestimated the magnitude of Ecc at the base (bias: − 4.0% absolute, p |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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