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. 2019 Mar 21;20(6):605–619. doi: 10.1093/ehjci/jez041

Table 5.

Clinical validation of 2DSTE, 3DSTE, and cMR-FT

Conclusion
Study Patients Method Reference Software Strain r/ICC Bias  ±  2SD (%) 95% CI
2DSTE
 Amundsen et al.53 7 MI, 4 NL cMR tagging MathLab-based custom made programme Long r = 0.87 −9.1 to 8 Accurate
 Cho et al.60 30 CAD cMR tagging GE EchoPAC BT04

  • Long

  • Circ

  • Rad

  • r = 0.51

  • r = 0.64

  • r = 0.60

  • 2 ± 5.5

  • 0.7 ± 5.4

  • 0.4 ± 9.5

  • −13 to 8.7

  • −10.9 to 9.9

  • −19.3 to 18.5

 Modest performance
 Bansal et al.61 30 CAD cMR tagging GE EchoPAC-PC v6.0

  • Long

  • Circ

  • Rad

  • r = 0.5

  • r = 0.63

  • r = 0.59

 Feasible
 Amundsen et al.62 10 MI, 11 NL cMR tagging GE EchoPAC-PC v6.0 In-house STE software Long

  • r = 0.65

  • r = 0.59

  • −8.1 to −13

  • −12 to −11

 Suitable
 Amzulescu et al.45 75 DYS , 30 HCM, 31 NL cMR tagging Philips QLAB 10.3

  • Long

  • Circ

  • ICC = 0.89

  • ICC = 0.80

  • −4.9 ± 3

  • −5.2 ± 5.3

  • −10.5 to 0.8

  • −15.4 to 5.3

 Best for GLS, suitable for GCS, suboptimal for segmental strain
3DSTE
 Kleijn et al.63 45 NL Mid-ventricular cMR tagging Toshiba 3D wall motion tracking software Circ 0.8 10 ± 1.7 6.7–13.2 Circ overestimates strain
 Zhou et al.64 12 NL, 12 DCM, 11 HTA Apical and mid-ventricular cMR tagging SIemens eSie Volume Mechanics Circ

  • 0.89

  • 0.91

  • 1.4

  • −0.2

  • −9.4 to 12.2

  • −8.7 to 8.4

 Feasible
 Amzulescu et al.65 63 DYS, 27 HCM 91 NL cMR tagging Philips Prototype software

  • Long

  • Circ

  • ICC = 0.89

  • ICC = 0.83

  • 0.5 ± 2.3

  • 0.2 ± 3

  • −4.1 to 5.1

  • −5.6 to 6.1

 GLS, GCS accurate, suboptimal for segmental strain
cMR-FT
 Hor et al.66 191 Duchenne muscular dystrophy, 42 NL Mid-ventricular cMR tagging TomTec Diogenes Circ 0.89 −4 to 3.5 No under or overestimation.
 Harrild et al.67 13 NL, 11 HCM Mid-ventricular cMR tagging Customized software programme (Cardiotool) Circ 1 ± 9 −16.6 to 18.6 No under or overestimation.
 Augustine et al.68 145 NL 20 NL had cMR tagging cMR tagging Tomtec 2D Cardiac Performance analysis

  • Long

  • Circ

  • Rad

  • −1

  • −0.7

  • 11

  • −16 to 3

  • −6 to 4

  • −1 to 23

 Long and Rad overestimate
 Wu et al.69 10 NL + 10 left bundle branch, 10 HCM Endocardial and mid-wall layer cMR tagging mid-wall TomTec Diogenes Circ Segmental Mid FT ICC: 0.58 (0.14–0.80) Circ overestimates, segmental FT unreliable.
 Moody et al.70 35 NL + 10 DCM Endocardial layer cMR tagging endo-, mid-, epi-, transmural TomTec Diogenes

  • Long

  • Circ

  • 0.70

  • 0.83

  • 1.3 ± 3.8

  • 0.2 ± 4

 Sufficient agreement.
 Singh et al.71 18 aortic stenosis Endo, endo/epi average cMR tagging TomTec Diogenes

  • Long

  • Circ

 ICC = 0.54 3.6 ± 3.3 −2.9 to 10.2 Long and Circ overestimate

CAD, coronary artery disease; DCM, dilated cardiomyopathy; DYS, dysfunction; HCM, hypertrophic cardiomyopathy; MI, myocardial infarct, NL, normal, healthy volunteers.