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|dc.description.abstract||Objectives-The purpose of this study was to compare success rates for depiction of the 5 typical transverse planes in the fetal upper thorax between cardiac- and body-based scrolling techniques. Methods-Spatiotemporal image correlation volume data sets acquired at the 4-chamber view level were obtained from low-risk singleton pregnancies with healthy fetuses. Each data set was analyzed by the authors using both cardiac- and body-based techniques. With the cardiac-based technique, the exact 4-chamber view was first identified as an initial plane before scrolling, whereas with the body-based technique, a volume data set was first manipulated to get the fetal orientation in the exact dorsal supine position as an initial plane. In both techniques, the volumes were then scrolled through the upper thorax to identify the standard planes, including the 4-chamber, 5-chamber, 3-vessel, 3-vessel and trachea, and aortic arch views. Results-An analysis of 50 volume data sets to evaluate intraobserver and interobserver variability in the success rates for the 4-chamber, 5-chamber, 3-vessel, 3-vessel and trachea, and aortic arch views showed good agreement. In an analysis of 296 separate data sets, cardiac-based scrolling was associated with significantly higher success rates than body-based scrolling in all standard planes (P < .05). Conclusions-Cardiac-based scrolling resulted in higher success rates for obtaining the standard spatiotemporal image correlation planes than body-based scrolling. Therefore, examiners in the early part of the learning curve should be encouraged to first identify a perfect 4-chamber view at the start of an examination. © 2013 by the American Institute of Ultrasound in Medicine.||en_US|
|dc.title||Comparison of fetal cardiac spatiotemporal image correlation segmental analysis between cardiac- and body-based scrolling||en_US|
|article.title.sourcetitle||Journal of Ultrasound in Medicine||en_US|
|article.stream.affiliations||Chiang Mai University||en_US|
|Appears in Collections:||CMUL: Journal Articles|
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