OBJECTIVES: To investigate the interobserver and intraobserver variability and corresponding learning curve in a semiautomatic approach for a standardized assessment of the fetal heart (fetal intelligent navigation echocardiography [FINE]). METHODS: A total of 30 stored spatiotemporal image correlation volume data sets of second-trimester fetuses were evaluated by 3 physicians with different levels of expertise in fetal echocardiography by using the FINE approach. Data were analyzed regarding the examination time and proper reconstruction of the diagnostic cardiac planes. The completions and numbers of correct depictions of all diagnostic planes were evaluated by a blinded expert (time t0). To determine interobserver and intraobserver variability, the volumes were reassessed after a 4-week training interval (time t1). RESULTS: All operators were able to perform the investigation on all 30 volumes. At t0, the interobserver variability between the beginner and both the advanced (P = .0013) and expert (P < .0001) examiners was high. Focusing on intraobserver variability at t1, the beginner showed a marked improvement (P = .0087), whereas in advanced and expert hands, no further improvement regarding proper achievement of all diagnostic planes could be noticed (P > .999; P = .8383). The beginner also showed improvement in the mean investigation time (t0, 82.8 seconds; t1, 73.4 seconds; P = .0895); nevertheless, the advanced and expert examiners were faster in completing the examination (t1, advanced, 20.9 seconds; expert, 28.3 seconds; each P < .0001). CONCLUSIONS: Based on our results, the FINE technique is a reliable and easily learned method. The use of this semiautomatic work flow-based approach supports evaluation of the fetal heart in a standardized and time-saving manner. A semiautomatic evaluation of the fetal heart might be useful in facilitating the detection of fetal cardiac anomalies.
OBJECTIVES: To investigate the interobserver and intraobserver variability and corresponding learning curve in a semiautomatic approach for a standardized assessment of the fetal heart (fetal intelligent navigation echocardiography [FINE]). METHODS: A total of 30 stored spatiotemporal image correlation volume data sets of second-trimester fetuses were evaluated by 3 physicians with different levels of expertise in fetal echocardiography by using the FINE approach. Data were analyzed regarding the examination time and proper reconstruction of the diagnostic cardiac planes. The completions and numbers of correct depictions of all diagnostic planes were evaluated by a blinded expert (time t0). To determine interobserver and intraobserver variability, the volumes were reassessed after a 4-week training interval (time t1). RESULTS: All operators were able to perform the investigation on all 30 volumes. At t0, the interobserver variability between the beginner and both the advanced (P = .0013) and expert (P < .0001) examiners was high. Focusing on intraobserver variability at t1, the beginner showed a marked improvement (P = .0087), whereas in advanced and expert hands, no further improvement regarding proper achievement of all diagnostic planes could be noticed (P > .999; P = .8383). The beginner also showed improvement in the mean investigation time (t0, 82.8 seconds; t1, 73.4 seconds; P = .0895); nevertheless, the advanced and expert examiners were faster in completing the examination (t1, advanced, 20.9 seconds; expert, 28.3 seconds; each P < .0001). CONCLUSIONS: Based on our results, the FINE technique is a reliable and easily learned method. The use of this semiautomatic work flow-based approach supports evaluation of the fetal heart in a standardized and time-saving manner. A semiautomatic evaluation of the fetal heart might be useful in facilitating the detection of fetal cardiac anomalies.