Prenatal Diagnosis of Fetal Skeletal Dysplasia Using 3-Dimensional Computed Tomography: A Prospective Study [post]

Miyoko Waratani, Fumitake Ito, Yukiko Tanaka, Aki Mabuchi, Taisuke Mori, Jo Kitawaki
2020 unpublished
Background: Fetal skeletal dysplasia (FSD) comprises a complex group of systemic bone and cartilage disorders. Many FSD phenotypes have indistinct definitions, making definitive prenatal diagnosis difficult. The condition is typically diagnosed using sonography; however, three-dimensional computed tomography (3D-CT) also aids in making a prenatal diagnosis. This study aimed to examine the efficacy of 3D-CT in the prenatal diagnosis of FSD by comparing the diagnostic accuracy of fetal sonography
more » ... of fetal sonography and 3D-CT.Methods: On suspicion of FSD based on ultrasound examination, we performed 3D-CT prenatally to obtain detailed skeletal information on FSD. To minimize exposure of the fetuses to radiation without compromising image quality, we used predetermined 3D-CT settings for volume acquisition.Results: Nineteen fetuses were suspected of having skeletal dysplasia based on ultrasonography findings. Of these, 17 were diagnosed with FSD using 3D-CT. All 17 fetuses diagnosed with FSD prenatally were confirmed postnatally to have the condition. The postnatal diagnosis (campomelic dysplasia) differed from the prenatal diagnosis (osteogenesis imperfecta) in only one infant. Sixteen cases (94.1 %) were diagnosed both prenatally and postnatally with FSD. Five infants had lethal skeletal dysplasia; one died in utero, and four died as neonates. We determined the appropriate delivery method for each infant based on the prenatal diagnosis.Conclusions: 3D-CT is a valuable tool for augmenting ultrasound examinations in the diagnosis of FSD. While improving the diagnostic tool of sonography is essential in cases of suspected FSD, 3D-CT imaging is indispensable for diagnosis and classification, enabling better planning for resuscitation of the infant after birth.Trial registration: University Hospital Medical Information Network (UMIN) Center trial registration number is UMIN000034744. Registered 1 October, 2018 – Retrospectively registered, https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=Roooo39610.
doi:10.21203/rs.3.rs-37187/v3 fatcat:dpekk22za5chrbkpdjrxu6rjoi