Hanna K Ruotsalainen1,2, Hannah R Bellsham-Revell3, Aaron J Bell3, Jaana I Pihkala1, Tiina H Ojala1, John M Simpson3. 1. Department of Pediatric Cardiology, Children's Hospital, University Hospital of Helsinki and University of Helsinki, Helsinki, Finland. 2. Department of Pediatrics, Kuopio University Hospital, Kuopio, Finland. 3. Department of Congenital Heart Disease, Evelina London Children's Hospital, London, United Kingdom.
Abstract
BACKGROUND: Quantitative echocardiographic assessment of right ventricular function is important in children with hypoplastic left heart syndrome (HLHS). The aim of this study was to examine the repeatability of different echocardiographic techniques, both manual and automated, to measure fractional area change (FAC) in patients with HLHS and to correlate these measurements with magnetic resonance imaging (MRI)-derived ejection fraction (EF). METHODS: Fifty-one children with HLHS underwent transthoracic echocardiography and cardiac MRI under the same general anesthetic as part of routine inter-stage assessment. FAC was measured from the apical four-chamber view using three different techniques: velocity vector imaging (VVI) (Syngo USWP 3.0; Siemens Healthineers), QLAB (Q-lab R 10.0; Philips Healthcare), and manual endocardial contour tracing (Xcelera, Philips Healthcare). Intra- and inter-observer variability was calculated using intra-class correlation coefficient (ICC). FAC was correlated with MRI EF calculated using a single standard method. RESULTS: Fractional area change had a good correlation with MRI-derived EF with an R value for VVI, QLAB, and manual methods of .7, .6, and .4, respectively. Intra- and inter-observer variability for FAC was good for automated echocardiographic methods (ICC>.85) but worse for manual method particularly inter-observer variability of FAC and end-systolic area. Both automated techniques tended to produce higher FAC values compared with manual measurements (P<.001). CONCLUSION: Automation improves the repeatability of FAC in HLHS. There are some differences between automated software in terms of correlation with MRI-derived EF. Measurement bias and wide limits of agreement mean that the same echocardiographic technique should be used during the follow-up of individual patients.
BACKGROUND: Quantitative echocardiographic assessment of right ventricular function is important in children with hypoplastic left heart syndrome (HLHS). The aim of this study was to examine the repeatability of different echocardiographic techniques, both manual and automated, to measure fractional area change (FAC) in patients with HLHS and to correlate these measurements with magnetic resonance imaging (MRI)-derived ejection fraction (EF). METHODS: Fifty-one children with HLHS underwent transthoracic echocardiography and cardiac MRI under the same general anesthetic as part of routine inter-stage assessment. FAC was measured from the apical four-chamber view using three different techniques: velocity vector imaging (VVI) (Syngo USWP 3.0; Siemens Healthineers), QLAB (Q-lab R 10.0; Philips Healthcare), and manual endocardial contour tracing (Xcelera, Philips Healthcare). Intra- and inter-observer variability was calculated using intra-class correlation coefficient (ICC). FAC was correlated with MRI EF calculated using a single standard method. RESULTS: Fractional area change had a good correlation with MRI-derived EF with an R value for VVI, QLAB, and manual methods of .7, .6, and .4, respectively. Intra- and inter-observer variability for FAC was good for automated echocardiographic methods (ICC>.85) but worse for manual method particularly inter-observer variability of FAC and end-systolic area. Both automated techniques tended to produce higher FAC values compared with manual measurements (P<.001). CONCLUSION: Automation improves the repeatability of FAC in HLHS. There are some differences between automated software in terms of correlation with MRI-derived EF. Measurement bias and wide limits of agreement mean that the same echocardiographic technique should be used during the follow-up of individual patients.
Authors: Jamie Penk; Shireen Mukadam; S Javed Zaidi; Vivian Cui; Robert Metzger; David A Roberson; Yi Li Journal: Pediatr Cardiol Date: 2019-10-28 Impact factor: 1.655
Authors: Matthew J Campbell; Michael D Quartermain; Meryl S Cohen; Jennifer Faerber; Oluwatimelehin Okunowo; Yan Wang; Valerie Capone; Jenna DiFrancesco; Laura Mercer-Rosa; David J Goldberg Journal: Echocardiography Date: 2020-08-13 Impact factor: 1.724