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Feasibility of three-dimensional reconstruction and automated measurement of fetal long bones using 5D Long Bone™

Authors
 허혜원 
Issue Date
2015
Description
의과대학/석사
Abstract
Objective: To evaluate the feasibility of 5D Long Bone™ (5D LB™), a new technique that automatically archives, reconstructs images, and measures lengths of fetal long bones, to assess whether the direction of volume sweep influences fetal long bone measurements in three-dimensional (3D) ultrasound and 5D LB™, and to compare measurements of fetal long bone lengths obtained with 5D LB™ and those obtained with conventional two-dimensional (2D) and manual 3D techniques.





Methods: This prospective study included 39 singleton pregnancies at 26+0 to 32+0 weeks of gestation. Multiple pregnancies, fetuses with multiple congenital anomalies, and mothers with underlying medical diseases were excluded. Fetal long bones of the lower extremities―the femur, tibia, and fibula were measured by 2D and 3D ultrasound, and 5D LB™, by an expert and non-expert examiner. First, we analyzed the 3D ultrasound and 5D LB™ data according to 2 different sweeping angles. We analyzed intra- and interobserver variability and agreement between ultrasound techniques. Paired t-test, interclass correlation coefficient (ICC), Bland-Altman plot and Passing-Bablok regression were used for statistical analysis.





Results: There was no statistical difference between long bone measurements analyzed according to 2 different volume-sweeping angles by 3D ultrasound and 5D LB™. Intra- and interobserver variability were not significantly different among all 3 ultrasound techniques. Comparing 2D ultrasound and 5D LB™, the ICC for femur, tibia, and fibula was 0.91, 0.92, and 0.89, respectively.





Conclusion: 5D LB™ is reproducible and comparable with conventional 2D and 3D ultrasound techniques for fetal long bone measurement.
Files in This Item:
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Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Obstetrics and Gynecology (산부인과학교실) > 2. Thesis
Yonsei Authors
Hur, Hye Won(허혜원)
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/148789
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