BACKGROUND: Left ventricular (LV) ejection fraction (EF) is a routine clinical standard to assess cardiac function. Global longitudinal strain (GLS) and global circumferential strain (GCS) have emerged as important LV functional measures. The objective of this study was to determine the relationships of GLS and GCS by speckle-tracking echocardiography and featuring-tracking cardiac magnetic resonance (CMR) to CMR EF as a standard of reference in the same patients. METHODS: A total of 73 consecutive patients aged 55 ± 15 years clinically referred for both CMR and echocardiography (EF range, 8%-78%) were studied. Routine steady-state free precession CMR images were prospectively analyzed offline using feature-tracking software for LV GLS, GCS, volumes, and EF. GLS was averaged from three standard longitudinal views and GCS from the mid-LV short-axis plane. Echocardiographic speckle-tracking was used from the similar imaging planes for GLS, GCS, LV volumes, and EF. RESULTS: Feature-tracking CMR strain was closely correlated with speckle-tracking strain in the same patients: GLS, r = -0.87; GCS, r = -0.92 (P < .0001). End-diastolic and end-systolic volumes and EF by feature-tracking CMR were significantly correlated with standard manual tracing of multiple CMR short-axis images (r = 0.97, r = 0.98, and r = 0.97, P < .0001 for all). GLS and GCS by echocardiography and CMR feature-tracking were closely correlated with standard CMR EF: r = -0.85 and r = -0.95, respectively (P < .001). Global strain measures (in absolute values) were correlated with EF using the formula EF = 3(GLS) + 8% or EF = 2.5(GCS) + 8%. CONCLUSIONS: GLS and GCS by feature-tracking CMR analysis was a rapid means to obtain myocardial strain similar to speckle-tracking echocardiography. GLS and GCS were closely correlated with CMR EF in this patient series and may play a role in the clinical assessment of LV function.
BACKGROUND: Left ventricular (LV) ejection fraction (EF) is a routine clinical standard to assess cardiac function. Global longitudinal strain (GLS) and global circumferential strain (GCS) have emerged as important LV functional measures. The objective of this study was to determine the relationships of GLS and GCS by speckle-tracking echocardiography and featuring-tracking cardiac magnetic resonance (CMR) to CMR EF as a standard of reference in the same patients. METHODS: A total of 73 consecutive patients aged 55 ± 15 years clinically referred for both CMR and echocardiography (EF range, 8%-78%) were studied. Routine steady-state free precession CMR images were prospectively analyzed offline using feature-tracking software for LV GLS, GCS, volumes, and EF. GLS was averaged from three standard longitudinal views and GCS from the mid-LV short-axis plane. Echocardiographic speckle-tracking was used from the similar imaging planes for GLS, GCS, LV volumes, and EF. RESULTS: Feature-tracking CMR strain was closely correlated with speckle-tracking strain in the same patients: GLS, r = -0.87; GCS, r = -0.92 (P < .0001). End-diastolic and end-systolic volumes and EF by feature-tracking CMR were significantly correlated with standard manual tracing of multiple CMR short-axis images (r = 0.97, r = 0.98, and r = 0.97, P < .0001 for all). GLS and GCS by echocardiography and CMR feature-tracking were closely correlated with standard CMR EF: r = -0.85 and r = -0.95, respectively (P < .001). Global strain measures (in absolute values) were correlated with EF using the formula EF = 3(GLS) + 8% or EF = 2.5(GCS) + 8%. CONCLUSIONS: GLS and GCS by feature-tracking CMR analysis was a rapid means to obtain myocardial strain similar to speckle-tracking echocardiography. GLS and GCS were closely correlated with CMR EF in this patient series and may play a role in the clinical assessment of LV function.
Authors: Kan Zhang; Richard Sheu; Nicole M Zimmerman; Andrej Alfirevic; Shiva Sale; A Marc Gillinov; Andra E Duncan Journal: J Cardiothorac Vasc Anesth Date: 2018-10-24 Impact factor: 2.628
Authors: Sara W Tantawy; Shaimaa Abdelsattar Mohammad; Ahmed M Osman; Wesam El Mozy; Ahmed S Ibrahim Journal: Int J Cardiovasc Imaging Date: 2020-09-09 Impact factor: 2.357
Authors: Kimberly Kallianos; Gabriel C Brooks; Kanae Mukai; Florent Seguro de Carvalho; Jing Liu; David M Naeger; Teresa De Marco; Karen G Ordovas Journal: Acad Radiol Date: 2017-08-31 Impact factor: 3.173
Authors: Sunil J Ghelani; David M Harrild; Kimberlee Gauvreau; Tal Geva; Rahul H Rathod Journal: Int J Cardiovasc Imaging Date: 2016-04-18 Impact factor: 2.357