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Background: Uteroplacental insufficiency in fetuses with growth restriction (FGR) leads to chronic hypoxia and stress, predominantly affecting the adrenal glands. However, the mechanisms of impact remain unclear. Objectives: This study is aimed at comparing the Doppler indices of the adrenal artery and the adrenal gland sizes between FGR and those with normal growth. Materials and Methods: A multicenter, cross-sectional study was conducted from February to December 2023. We compared 34 FGR to 34 with normal growth in terms of inferior adrenal artery (IAA) Doppler indices and adrenal gland volumes. Results: The IAA peak systolic velocity (PSV) in the FGR group was 14.9 ± 2.9 cm/s compared to 13.5 ± 2.0 cm/s in the normal group, with a mean difference of 1.4 cm/s (95% confidence interval [CI]: 0.27-2.65; p value = 0.017). There were no significant differences between groups in terms of IAA pulsatility index (PI), resistance index (RI), or systolic/diastolic (S/D), with p values of 0.438, 0.441, and 0.658, respectively. The volumes of the corrected whole adrenal gland and the corrected neocortex were significantly larger in the FGR group, with p values of 0.031 and 0.020, respectively. Conclusion: Both increased IAA PSV and enlarged volumes of the corrected whole adrenal gland and neocortex were found in fetuses with FGR, suggesting significant adrenal gland adaptation in response to chronic intrauterine stress.

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This study presents the modified Cordes method, a novel ultrasonographic technique that provides a precise and practical evaluation of fetal situs during pregnancy, particularly in the first and early second trimesters. This method entails precisely aligning the probe and hand to obtain a clear image of the fetal thorax in the axial plane. The fundamental procedures involve ascertaining the initial location of the fetal head, rotating the probe, aligning the thorax at the center, and positioning the left hand to clearly identify the fetal situs. Tests conducted in many pregnancies have verified that the modified Cordes approach offers prompt and precise identification of fetal situs and is more accessible to acquire, particularly for new practitioners. The modified Cordes approach is a straightforward and reliable technique for establishing the position of the fetus. Its application during the first and early second trimesters improves diagnostic accuracy by minimizing the chances of misinterpretation. This method offers benefits by making the process of determining fetal situs more objective and straightforward for practitioners with varying degrees of experience.

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The goal of our research is to elucidate and better assess placental function in rats with preeclampsia through an innovative application of ultrasound-based radiomics. Using a rat model induced with L-NAME, we carefully investigated placental dysfunction via microstructural analysis and immunoprotein level assessment. Employing the Boruta feature selection method on ultrasound images facilitated the identification of crucial features, consequently enabling the development of a robust model for classifying placental dysfunction. Our study included 12 pregnant rats, and thorough placental evaluations were conducted on 160 fetal rats. Distinct alterations in placental microstructure and angiogenic factor expression were evident in rats with preeclampsia. Leveraging high-throughput mining of quantitative image features, we extracted 558 radiomic features, which were subsequently used to construct an impressive evaluation model with an area under the receiver operating curve (AUC) of 0.95. This model also exhibited a remarkable sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of 88.7%, 91.5%, 90.2%, 90.4%, and 90.0%, respectively. Our findings highlight the ability of ultrasound-based radiomics to detect abnormal placental features, demonstrating its potential for evaluating both normative and impaired placental function with high precision and reliability.

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INTRODUCTION: Undetected high-risk conditions in pregnancy are a leading cause of perinatal mortality in low-income and middle-income countries. A key contributor to adverse perinatal outcomes in these settings is limited access to high-quality screening and timely referral to care. Recently, a low-cost one-dimensional Doppler ultrasound (1-D DUS) device was developed that front-line workers in rural Guatemala used to collect quality maternal and fetal data. Further, we demonstrated with retrospective preliminary data that 1-D DUS signal could be processed using artificial intelligence and deep-learning algorithms to accurately estimate fetal gestational age, intrauterine growth and maternal blood pressure. This protocol describes a prospective observational pregnancy cohort study designed to prospectively evaluate these preliminary findings. METHODS AND ANALYSIS: This is a prospective observational cohort study conducted in rural Guatemala. In this study, we will follow pregnant women (N =700) recruited prior to 18 6/7 weeks gestation until their delivery and early postpartum period. During pregnancy, trained nurses will collect data on prenatal risk factors and obstetrical care. Every 4 weeks, the research team will collect maternal weight, blood pressure and 1-D DUS recordings of fetal heart tones. Additionally, we will conduct three serial obstetric ultrasounds to evaluate for fetal growth restriction (FGR), and one postpartum visit to record maternal blood pressure and neonatal weight and length. We will compare the test characteristics (receiver operator curves) of 1-D DUS algorithms developed by deep-learning methods to two-dimensional fetal ultrasound survey and published clinical pre-eclampsia risk prediction algorithms for predicting FGR and pre-eclampsia, respectively. ETHICS AND DISSEMINATION: Results of this study will be disseminated at scientific conferences and through peer-reviewed articles. Deidentified data sets will be made available through public repositories. The study has been approved by the institutional ethics committees of Maya Health Alliance and Emory University.

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OBJECTIVE: Fetal venous system malformations frequently coincide with cardiac or extracardiac anomalies. This study explores our experience with an integrated fetal echocardiography approach and analyzes the characteristics and outcomes of fetal venous system disorders. MATERIALS AND METHODS: We conducted a retrospective study with 7048 pregnant women (7255 fetuses) who underwent complete two-dimensional (2D) fetal echocardiographic examinations. We primarily employed an integrated 2D approach. Three-/four-dimensional (3D/4D) spatiotemporal image correlation was supplemental. Fetal venous disorders were classified into 3 groups: cardinal (Group 1), umbilical and vitelline (Group 2), and pulmonary (Group 3) systems, based on embryological-anatomical considerations. Maternofetal data were recorded alongside imaging diagnoses. RESULTS: Congenital venous malformations were identified in 98 fetuses, yielding a prevalence of 1.35% (98/7255). Six participants had coexisting venous disorders from different groups. Group 1 included 48 fetuses with persistent left superior vena cava (LSVC) and 3 others (unidentified brachiocephalic vein, left inferior vena cava (IVC), and interrupted IVC with azygous continuation to SVC). Group 2 had 39 fetuses with persistent right umbilical vein and 7 with umbilical-portal-ductus venosus disorders. Group 3 had 7 fetuses with pulmonary venous return disorders. Group 2 showed the most favorable outcomes (alive and without neonatal death), while Group 3 exhibited the poorest. Associated cardiac defects were observed in 43.1% of Group 1, 8.7% of Group 2, and 57.1% of Group 3 (P < 0.001), displaying a broad spectrum of non-specific anomalies. Meanwhile, Group 2 had a greater occurrence of a single venous disorder (93.5%) compared to Group 1 (88.2%) and Group 3 (57.1%) (P = 0.020). CONCLUSION: Our approach offers an integrated strategy for assessing the fetal venous system during fetal echocardiography, providing multiple views to characterize venous anomalies. The presence of a fetal venous disorder may indicate the coexistence of more severe abnormalities, and the prognosis depends on associated anomalies or the venous disorders per se.

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Importance: Accurate assessment of gestational age (GA) is essential to good pregnancy care but often requires ultrasonography, which may not be available in low-resource settings. This study developed a deep learning artificial intelligence (AI) model to estimate GA from blind ultrasonography sweeps and incorporated it into the software of a low-cost, battery-powered device. Objective: To evaluate GA estimation accuracy of an AI-enabled ultrasonography tool when used by novice users with no prior training in sonography. Design, Setting, and Participants: This prospective diagnostic accuracy study enrolled 400 individuals with viable, single, nonanomalous, first-trimester pregnancies in Lusaka, Zambia, and Chapel Hill, North Carolina. Credentialed sonographers established the "ground truth" GA via transvaginal crown-rump length measurement. At random follow-up visits throughout gestation, including a primary evaluation window from 14 0/7 weeks' to 27 6/7 weeks' gestation, novice users obtained blind sweeps of the maternal abdomen using the AI-enabled device (index test) and credentialed sonographers performed fetal biometry with a high-specification machine (study standard). Main Outcomes and Measures: The primary outcome was the mean absolute error (MAE) of the index test and study standard, which was calculated by comparing each method's estimate to the previously established GA and considered equivalent if the difference fell within a prespecified margin of ±2 days. Results: In the primary evaluation window, the AI-enabled device met criteria for equivalence to the study standard, with an MAE (SE) of 3.2 (0.1) days vs 3.0 (0.1) days (difference, 0.2 days [95% CI, -0.1 to 0.5]). Additionally, the percentage of assessments within 7 days of the ground truth GA was comparable (90.7% for the index test vs 92.5% for the study standard). Performance was consistent in prespecified subgroups, including the Zambia and North Carolina cohorts and those with high body mass index. Conclusions and Relevance: Between 14 and 27 weeks' gestation, novice users with no prior training in ultrasonography estimated GA as accurately with the low-cost, point-of-care AI tool as credentialed sonographers performing standard biometry on high-specification machines. These findings have immediate implications for obstetrical care in low-resource settings, advancing the World Health Organization goal of ultrasonography estimation of GA for all pregnant people. Trial Registration: ClinicalTrials.gov Identifier: NCT05433519.

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OBJECTIVE: To investigate the value of magnetic resonance examination technique for prenatal genetic diagnosis and clinical intrauterine treatment of fetal congenital cystic adenoma (CCAM) of the lung. METHODS: A retrospective analysis was conducted on 108 pregnant women admitted to a certain hospital from January 2016 to January 2022 for pre natal examination and consultation on eugenics. The selected pregnant women were aged 20-40 and had a gestational age of 17-36 weeks. Ultrasound and MRI examinations were performed on 108 pregnant women who met the inclusion criteria. Follow-up and investigation were conducted on the fetus after being diagnosed with CCAM. To analyze the results of prenatal genetic diagnosis, chromosome microarray analysis (CMA) was used to analyze samples with pathogenic Copy Number Variants (CNV) and identify pathogenic genes. Finally, the imaging diagnosis results obtained through statistical software were analyzed, and the correlation between pathogenic genes and CCAM, as well as the clinical application value of MRI in fetal intrauterine treatment was explored. RESULTS: Among all cases, 68 fetuses were diagnosed with CCAM through ultrasound examination; 71 fetuses were diagnosed with CCAM through MRI examination. A total of 74 samples were confirmed as CCAM by autopsy and neonatal CT. The sensitivity, specificity, and accuracy of MRI in diagnosing fetal congenital CCAM were higher than those of ultrasound examination. The expression of CCAM was positively correlated with DUSP22, PRSS1, and SHOX, with all R values greater than 0.8. The clinical decision curve showed that when the probability of fetal CCAM was less than 0.03, the prenatal genetic diagnostic model of MRI was not applicable; But when the probability of fetal CCAM was higher than 0.05, the auxiliary intrauterine treatment effect that MRI diagnostic methods achieved was significantly better than conventional diagnosis. CONCLUSION: MRI is significantly better than ultrasound in the diagnosis of CCAM, which can effectively improve the sensitivity of diagnosis and provide accurate information for the eugenics of pregnant women, and has high clinical application value.

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The Society of Radiologists in Ultrasound convened a multisociety panel to develop a first-trimester US lexicon based on scientific evidence, societal guidelines, and expert consensus that would be appropriate for imagers, clinicians, and patients. Through a modified Delphi process with consensus of at least 80%, agreement was reached for preferred terms, synonyms, and terms to avoid. An intrauterine pregnancy (IUP) is defined as a pregnancy implanted in a normal location within the uterus. In contrast, an ectopic pregnancy (EP) is any pregnancy implanted in an abnormal location, whether extrauterine or intrauterine, thus categorizing cesarean scar implantations as EPs. The term pregnancy of unknown location is used in the setting of a pregnant patient without evidence of a definite or probable IUP or EP at transvaginal US. Since cardiac development is a gradual process and cardiac chambers are not fully formed in the first trimester, the term cardiac activity is recommended in lieu of 'heart motion' or 'heartbeat.' The terms 'living' and 'viable' should also be avoided in the first trimester. 'Pregnancy failure' is replaced by early pregnancy loss (EPL). When paired with various modifiers, EPL is used to describe a pregnancy in the first trimester that may or will not progress, is in the process of expulsion, or has either incompletely or completely passed. © RSNA and Elsevier, 2024 Supplemental material is available for this article. This article is a simultaneous joint publication in Radiology and American Journal of Obstetrics & Gynecology. All rights reserved. The articles are identical except for minor stylistic and spelling differences in keeping with each journal's style. Either version may be used in citing this article. See also the editorial by Scoutt and Norton in this issue.

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BACKGROUND: Orofacial clefts are one of the most common congenital malformations of the fetal face and ultrasound is mainly responsible for its diagnosis. It is difficult to view the fetal palate, so there is currently no unified standard for fetal palate screening, and the diagnosis of cleft palate is not included in the relevant prenatal ultrasound screening guidelines. Many prenatal diagnoses for cleft palate are missed due to the lack of effective screening methods. Therefore, it is imperative to increase the display rate of the fetal palate, which would improve the detection rate and diagnostic accuracy for cleft palate. We aim to introduce a fetal palate screening software based on the "sequential sector scan though the oral fissure", an effective method for fetal palate screening which was verified by our follow up results and three-dimensional ultrasound and to evaluate its feasibility and clinical practicability. METHODS: A software was designed and programmed based on "sequential sector scan through the oral fissure" and three-dimensional ultrasound. The three-dimensional ultrasound volume data of the fetal face were imported into the software. Then, the median sagittal plane was taken as the reference interface, the anterior upper margin of the mandibular alveolar bone was selected as the fulcrum, the interval angles, and the number of layers of the sector scan were set, after which the automatic scan was performed. Thus, the sector scan sequential planes of the mandibular alveolar bone, pharynx, soft palate, hard palate, and maxillary alveolar bone were obtained in sequence to display and evaluate the palate. In addition, the feasibility and accuracy of the software in fetal palate displaying and screening was evaluated by actual clinical cases. RESULTS: Full views of the normal fetal palates and the defective parts of the cleft palates were displayed, and relatively clear sequential tomographic images and continuous dynamic videos were formed after the three-dimensional volume data of 10 normal fetal palates and 10 cleft palates were imported into the software. CONCLUSIONS: The software can display fetal palates more directly which might allow for a new method of fetal palate screening and cleft palate diagnosis.

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BACKGROUND: This study aimed to update systematic reviews and meta-analyses on the diagnostic accuracy of postnatal clinical scoring (PCS) methods and foot length (FL) measurement for assessing gestational age (GA) and birth weight in low-income and middle-income countries (LMICs). In addition, the quality of reference standards, including antenatal ultrasound (A-US), last menstrual period (LMP), PCS and newborn weighing scales, was also evaluated. METHODS: Studies from LMICs published between January 2000 and February 2024 were searched, using databases such as PubMed, Web of Science, Cochrane Library, CINAHL and Scopus. Studies that compared PCS and/or FL with LMP and/or A-US to estimate GA or used calibrated newborn weighing scales for birthweight estimation were included. The risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies-II tool and evaluated the quality of the reference standards. When sufficient data were available, pooled estimates were calculated using random-effects models. RESULTS: A total of 50 studies were included. A-US was a reasonable tool for GA assessment if conducted by physicians using fetal biometry and the Hadlock method for GA estimation. LMP was reasonable when women had regular cycles, knew their LMP, were not using contraceptives and LMP data were collected by healthcare providers. When A-US was used as the reference standard, PCS methods estimated GA with a precision of ±2.8 to ±3.2 weeks. FL measurement <7.5 cm showed a pooled sensitivity of 76.2% and specificity of 36.6% for identifying preterm birth. FL measurement ≤7.6 cm had a pooled sensitivity of 78.6% and specificity of 65.7% for identifying low birth weight (LBW). High heterogeneity across studies was observed. CONCLUSION: This systematic review and meta-analysis highlights significant variability and methodological inconsistencies in using PCS methods and FL measurement for estimating GA and LBW in LMICs. The observed high heterogeneity across studies suggests a cautious interpretation of the results. PROSPERO REGISTRATION NUMBER: CRD42020209455.

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New technologies for detecting pregnancy shortly after mating/insemination and identifying gestational age are essential for speeding up the reproductive cycle and ensuring high reproductive efficiency in livestock farming. Ultrasonography can successfully identify pregnancy and determine gestational age in many domestic animals. On the other hand, many herds of camel and buffalo and flocks of sheep are aware of the day of service, making it difficult to appropriately manage pregnant animals. This study provides a review of the literature on various techniques for ultrasonographically diagnosing pregnancy in camels, buffaloes, and sheep, focusing on the most appropriate times to use each technique, the earliest opportunity to diagnose pregnancy, and the possibility of using various parts of the fetus to create mathematical equations to determine gestational age. Some limitations of ultrasonography in pregnancy diagnosis were identified and significant pregnancy events in dromedaries were discussed, including left-horn and twin pregnancies. The data presented here will prove essential for researchers, farmers, and countries that rely heavily on these animals for providing meat, milk, cosmetics, and other animal products to enhance reproduction and production efficiency.

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INTRODUCTION: Abnormal placental cord insertions (APCIs) are significant risk factors for pregnancy complications, encompassing marginal cord insertion (MCI), velamentous cord insertion (VCI), and vasa previa (VP). While ultrasound is the primary imaging modality, its accuracy can be limited by factors such as maternal obesity and fetal positioning. Complementary to ultrasound, magnetic resonance imaging (MRI) offers a more precise visualization of the fetus, placenta, and umbilical cord relationships. This study aims to investigate the diagnostic value of prenatal magnetic resonance imaging (MRI) for APCIs compared with prenatal ultrasound. METHODS: We retrospectively collected data from 613 patients who underwent prenatal placental ultrasound and MRI. Of those who were confirmed as APCIs through surgery or pathology, the prenatal MRI features were compared with prenatal ultrasound. The diagnostic efficacy of prenatal MRI and ultrasound for APCIs was assessed based on the clinicopathological findings. RESULTS: Fifty-six patients were confirmed as APCIs by surgery or pathology, comprising 31 marginal cord insertions (MCIs), 18 velamentous cord insertions (VCIs), 5 vasa previa (VP) cases, and 2 VCI cases combined with VP. Ultrasound examination showed 55.36 % sensitivity (31/56) and 98.38 % specificity (486/494) in diagnosing APCIs, whereas MRI demonstrated 87.50 % sensitivity (49/56) and 98.88 % specificity (531/537). CONCLUSION: For APCIs complicated by placental location or morphological abnormalities, MRI demonstrates superior diagnostic efficacy compared to ultrasound in late pregnancy.

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OBJECTIVES: To develop a deep learning (DL)-model using convolutional neural networks (CNN) to automatically identify the fetal head position at transperineal ultrasound in the second stage of labor. MATERIAL AND METHODS: Prospective, multicenter study including singleton, term, cephalic pregnancies in the second stage of labor. We assessed the fetal head position using transabdominal ultrasound and subsequently, obtained an image of the fetal head on the axial plane using transperineal ultrasound and labeled it according to the transabdominal ultrasound findings. The ultrasound images were randomly allocated into the three datasets containing a similar proportion of images of each subtype of fetal head position (occiput anterior, posterior, right and left transverse): the training dataset included 70 %, the validation dataset 15 %, and the testing dataset 15 % of the acquired images. The pre-trained ResNet18 model was employed as a foundational framework for feature extraction and classification. CNN1 was trained to differentiate between occiput anterior (OA) and non-OA positions, CNN2 classified fetal head malpositions into occiput posterior (OP) or occiput transverse (OT) position, and CNN3 classified the remaining images as right or left OT. The DL-model was constructed using three convolutional neural networks (CNN) working simultaneously for the classification of fetal head positions. The performance of the algorithm was evaluated in terms of accuracy, sensitivity, specificity, F1-score and Cohen's kappa. RESULTS: Between February 2018 and May 2023, 2154 transperineal images were included from eligible participants across 16 collaborating centers. The overall performance of the model for the classification of the fetal head position in the axial plane at transperineal ultrasound was excellent, with an of 94.5 % (95 % CI 92.0--97.0), a sensitivity of 95.6 % (95 % CI 96.8-100.0), a specificity of 91.2 % (95 % CI 87.3-95.1), a F1-score of 0.92 and a Cohen's kappa of 0.90. The best performance was achieved by the CNN1 - OA position vs fetal head malpositions - with an accuracy of 98.3 % (95 % CI 96.9-99.7), followed by CNN2 - OP vs OT positions - with an accuracy of 93.9 % (95 % CI 89.6-98.2), and finally, CNN3 - right vs left OT position - with an accuracy of 91.3 % (95 % CI 83.5-99.1). CONCLUSIONS: We have developed a DL-model capable of assessing fetal head position using transperineal ultrasound during the second stage of labor with an excellent overall accuracy. Future studies should validate our DL model using larger datasets and real-time patients before introducing it into routine clinical practice.

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BACKGROUND: Congenital defects of the central nervous system are the second cause of disability in childhood, representing up to 20 % of structural malformations diagnosed prenatally. The accurate prenatal diagnosis of fetal neurological anomalies and the assessment of cortical development are critical for early intervention and improved long-term outcomes. Neurosonography plays a vital role in this process, providing detailed insights into the structural and functional development of the fetal brain. This systematic review aims to synthesize current knowledge on neurosonographic indicators for prenatal diagnosis, with a special focus on cortical development and its impact in cases of fetal growth defects. MATERIAL AND METHODS: We conducted a comprehensive search for primary literature in PubMed database were searched for English and Spanish-language, peer-reviewed literature published in the last 15 years. Additional articles were identified by scrutinizing others search platforms (Cochrane Library, UpToDate). Inclusion criteria were single pregnancy and no known feto-maternal pathologies at the beginning of the study. RESULTS: Of the 361 published abstracts identified, 35 met criteria for inclusion. The review highlighted the importance of detailed neurosonographic assessments, including the evaluation of cerebral fissures such as the Sylvian fissure, parieto-occipital fissure, and calcarine fissure. Targeted ultrasound techniques were found to provide comprehensive insights comparable to fetal magnetic resonance imaging. We underscored the significant impact of intrauterine growth restriction on cortical development, with early intervention being crucial. Genetic and congenital infection screenings were emphasized as essential components of prenatal assessment. CONCLUSION: The assessment of fetal brain maturation patterns according to gestational age allows us to rule out a delay in cortical development. The heterogeneity of methods and evaluable parameters in fetal neurodevelopment makes it necessary to standardize the evaluation of the main structures of interest both for screening and for the diagnosis of cortical development anomalies, even with the aim of trying to improve upgrade prognostic advice.

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This study aimed to investigate the predictive value of real-time shear wave elastography (SWE) for spontaneous preterm birth (SPB). This study prospectively selected 175 women with singleton pregnancies at 16 to 36 weeks of gestation. Cervical length (CL) and uterocervical angle (UCA) were measured using transvaginal ultrasonography. Real-time shear wave elastography was used to measure Young's modulus values, including the average Young's modulus (Emean) and the maximum Young's modulus (Emax) at 4 points: point A on the inner lip of the cervical os, point B on the outer lip of the cervical os, point C on the inner lip of the external os, and point D on the outer lip of the external os. Receiver operating characteristic (ROC) curve analysis was performed to compare the accuracy of Young's modulus values at the 4 points, CL, and UCA in predicting SPB. Significant variables were used to construct a binary logistic regression model to predict the multifactorial predictive value of SPB, which was evaluated using an ROC curve. A total 176 valid cases, including 160 full-term pregnancies and 16 SPB, were included in this study. Receiver operating characteristic curve analysis revealed that Emean at point A, as well as Emean and Emax at point D, had a relatively high accuracy in diagnosing SPB, with area under the curve values of 0.704, 0.708, and 0.706, respectively followed by CL (0.670), SWE at point C (Emean 0.615, Emax 0.565), SWE at point B (Emean 0.577, Emax 0.584), and UCA (0.476). Binary logistic regression analysis showed that comorbidities during pregnancy (including diabetes mellitus, hypertension, cholestasis and thyroid dysfunction), CL, and Emean at point A were independent predictors of preterm birth. In addition, the AUC value of the logistic regression model's ROC curve was 0.892 (95% CI: 0.804-0.981), with a sensitivity of 0.867, specificity of 0.792, and Youden's index of 0.659, indicating that the regression model has good predictive ability for SPB. Real-time shear wave elastography showed a higher predictive value for SPB than CL and UCA. The SWE combined with CL and comorbidities during pregnancy model has a good predictive ability for SPB.

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Importance: The identification of the cavum septum pellucidum (CSP) is an integral part of the routine second trimester fetal anatomy scan. The absence or nonvisualization of the CSP has significant clinical implications and requires further evaluation and counseling for the pregnant patient. Objective: The aim of this review is to review the importance of accurate sonographic identification of the CSP and the underlying pathologies that can be associated with nonvisualization of this structure. Evidence Acquisition: A literature review was performed with PubMed using key words including CSP, fetal anatomy ultrasound, and fetal anomalies. Results: The absence of the CSP is associated with several central nervous system pathologies, all with a wide range of phenotypic outcomes, ranging from normal to very severe or lethal. Relevance: Most obstetrician-gynecologists will have a patient in whom a CSP is not identified on fetal ultrasound. Thus, it is imperative to have a general understanding of this relatively common entity.

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Transrectal and transabdominal ultrasonography is an established method to monitor pregnancy, fetal growth and wellbeing in different species. Growth charts with multiple bio-morphometric parameters to estimate days of gestation and days before parturition exist in small companion animals, sheep and goats, riding type horses and large ponies but not in small horse breeds like Shetland ponies. The aim of this study was to apply fetal biometric assessment and detailed description of physiologic fetal development to mid and late term pregnancies in Shetland mares and to generate reference data for clinical practice and for future research. Fetal parameters were collected starting on day 101 of pregnancy in five Shetland mares. The fetal biometric parameters determined consisted of aortic diameter, eye diameter, combined rib and intercostal distance (CRID), stomach length and width and different heart morphology parameters in sagittal and frontal plane. Additionally, fetal activity and organ development in terms of differentiation and changes in echogenicity were recorded. Considering reliably assessable parameters, fetal CRID was the best predictor for gestational age with ± 13.6 days and fetal aortic diameter the most accurate for prediction of days until parturition with ± 16.2 days.

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