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(searched for: (title:(Diagnosing Fetal Skeletal Dysplasia Using Three-Dimensional Computed Tomography: A Study Protocol for an Interventional Study)
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Miyoko Waratani, Fumitake Ito, Yukiko Tanaka, Mabuchi Aki, Taisuke Mori, Jo Kitawaki
Journal of Biomedical Research & Environmental Sciences, Volume 1, pp 292-296; doi:10.37871/jbres1156

Abstract:
Background: Fetal skeletal dysplasias are a group of skeletal dysplasias occurring during the fetal stage. As the use of fetal ultrasonography has become widespread, the rate of prenatal diagnosis of skeletal dysplasias has increased. However, many fetal skeletal dysplasia phenotypes have indistinct definitions, making definitive prenatal diagnosis difficult. Fetal imaging methods that are the basis of diagnosing fetal skeletal dysplasias include ultrasonography and three-dimensional computed tomography. The use of three-dimensional computed tomography requires specific imaging techniques and cannot easily be performed at all facilities. In the present study, we propose to conduct a survey for the preparation of a protocol with a low risk, and a high diagnostic accuracy. Methods: In total, 50 pregnant women who undergo three-dimensional computed tomography for the diagnosis of fetal skeletal dysplasias will be included. The primary outcome is prenatal diagnostic accuracy for fetuses with skeletal dysplasias. The secondary outcome is the safety from radiation exposure. Results and conclusion: Three-dimensional computed tomography should be considered for the prenatal diagnosis of fetal skeletal dysplasias, as it is important to judge whether the prognosis is favorable or lethal. When considering the risk of radiation exposure, high quality images that are adequate for a diagnosis have been obtained using low-dose three-dimensional computed tomography scans. This approach reduces the level of radiation to which the pregnant woman and fetus are exposed. Trial registration: University hospital Medical Information Network (UMIN) Center: Trial registration number is UMIN000034744. Data of registration is October 01, 2018. (URL: https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000039610).
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