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Objective: This work investigates the use of deep convolutional neural networks (CNN) to automatically perform measurements of fetal body parts, including head circumference, biparietal diameter, abdominal circumference and femur length, and to estimate gestational age and fetal weight using fetal ultrasound videos. Approach: We developed a novel multi-task CNN-based spatio-temporal fetal US feature extraction and standard plane detection algorithm (called FUVAI) and evaluated the method on 50 freehand fetal US video scans. We compared FUVAI fetal biometric measurements with measurements made by five experienced sonographers at two time points separated by at least two weeks. Intra- and inter-observer variabilities were estimated. Main Results: We found that automated fetal biometric measurements obtained by FUVAI were comparable to the measurements performed by experienced sonographers The observed differences in measurement values were within the range of inter- and intra-observer variability. Moreover, analysis has shown that these differences were not statistically significant when comparing any individual medical expert to our model. Significance: We argue that FUVAI has the potential to assist sonographers who perform fetal biometric measurements in clinical settings by providing them with suggestions regarding the best measuring frames, along with automated measurements. Moreover, FUVAI is able perform these tasks in just a few seconds, which is a huge difference compared to the average of six minutes taken by sonographers. This is significant, given the shortage of medical experts capable of interpreting fetal ultrasound images in numerous countries.

Placental vascular anastomoses in twins lead to a shared circulation and may subsequently enable the development of severe complications such as twin-twin transfusion syndrome (TTTS) and twin anemiapolycythemia sequence (TAPS). The presence of vascular anastomoses has frequently and systematically been studied in monochorionic (MC) placentas, but only rarely in dichorionic (DC) placentas. The aim of this study was to compare the prevalence of vascular anastomoses and evaluate the sharing discordance in MC and DC placentas. All consecutive placentas of MC and DC twins delivered at the Leiden University Medical Center (the Netherlands) and Medical University of Warsaw (Poland) from 2012 to 2015 were routinely injected with colored dye and included in the study. We excluded twin pregnancies treated with fetoscopic laser surgery. A total of 258 placentas were analyzed in this study, including 134 MC placentas and 124 DC placentas. Vascular anastomoses were present in 99% (133/134) of MC placentas and 0% of DC placentas (p < .01). Placental share discordance between MC twins was significantly larger compared to DC twins, 19.8 (interquartile range [IQR] 8.1-33.3) and 10.8 (IQR 6.2-19.0), respectively (p < .01). Vascular anastomoses associated complications occurred in 16% (22/134) MC twins. Our findings show that vascular anastomoses are almost ubiquitous in MC placentas, but non-existent in DC placentas. In addition, unequal placental sharing appears to be more common in MC than in DC placentas.

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