Search Results (31)

Background/Objectives: To construct and compare multivariable prediction models for the early prediction of large-for-gestational-age (LGA) neonates, using ultrasound biometry and maternal characteristics. Methods: This retrospective cohort study analyzed data from singleton pregnancies that underwent routine ultrasound examinations at 30⁺⁰–34⁺⁰ weeks of gestation. Ultrasound parameters included fetal abdominal circumference (AC), head circumference (HC), femur length (FL), HC-to-AC ratio, mean uterine artery pulsatility index (mUtA-PI), and presence of polyhydramnios. LGA neonates were defined as those having a birthweight > 90th percentile. Logistic regression was used to evaluate associations between ultrasound markers and LGA after adjusting for the following maternal and pregnancy-related covariates: maternal age, body mass index, parity, gestational diabetes mellitus (GDM), pre-existing diabetes, previous cesarean section (PCS), assisted reproductive technology (ART) use, smoking, hypothyroidism, and chronic hypertension. Associations were expressed as adjusted odds ratios (aORs) with 95% confidence intervals (CIs). Three prognostic models were developed utilizing the following predictors: (i) biometric ultrasound measurements including AC, HC-to-AC ratio, FL, UtA-PI, and polyhydramnios (Model 1), (ii) a combination of biometric ultrasound measurements and clinical–maternal data (Model 2), and (iii) only the estimated fetal weight (EFW) (Model 3). Results: In total, 3808 singleton pregnancies were included in the analyses. The multivariable analysis revealed that AC (aOR 1.07, 95% CI [1.06, 1.08]), HC to AC (aOR 1.01, 95% CI [1.006, 1.01]), FL (aOR 1.01, 95% CI [1.009, 1.01]), and the presence of polyhydramnios (aOR 4.97, 95% CI [0.7, 58.8]) were associated with an increased risk of LGA, while a higher mUtA-PI was associated with a reduced risk (aOR 0.98, 95% CI [0.98, 0.99]). Maternal parameters, such as GDM, pre-existing diabetes, elevated pre-pregnancy BMI, absence of uterine artery notching, mUtA-PI, and multiparity, were significantly higher in the LGA group. Both models 1 and 2 showed similar performance (AUCs: 84.7% and 85.3%, respectively) and outperformed model 3 (AUC: 77.5%). Bootstrap and temporal validation indicated minimal overfitting and stable model performance, while decision curve analysis supported potential clinical utility. Conclusions: Models using biometric and Doppler ultrasound at 30–34 weeks demonstrated good discriminative ability for predicting LGA neonates, with an AUC up to 84.7%. Adding maternal characteristics did not significantly improve performance, while the biometric model performed better than EFW alone. Sensitivity at conventional thresholds was low but increased substantially when lower probability cut-offs were applied, illustrating the model’s threshold-dependent flexibility for early risk stratification in different clinical screening needs. Although decision curve analysis was performed to explore potential clinical utility, external validation and prospective assessment in clinical settings are still needed to confirm generalizability and to determine optimal decision thresholds for clinical application. Full article

Objective: To evaluate the predictive value of umbilical artery half peak systolic velocity deceleration time (UA hPSV-DT) for composite adverse perinatal outcomes (CAPO) in pregnancies complicated by gestational diabetes mellitus (GDM). Methods: In this prospective observational study, 120 singleton pregnancies in the third trimester were enrolled: 30 insulin-regulated GDM (IRGDM), 30 diet-regulated GDM (DRGDM), and 60 healthy controls. UA hPSV-DT and standard Doppler indices were measured using a standardized protocol by a single perinatologist. An abnormal UA hPSV-DT was defined as <5th percentile for gestational age. Maternal metabolic parameters, fetal biometry, and neonatal outcomes were recorded. The primary outcome was CAPO, defined as the presence of one or more adverse perinatal events. Results: Median UA hPSV-DT values were significantly lower in IRGDM (171 ms) and DRGDM (184 ms) compared with controls (227 ms) (p = 0.006). Abnormal UA hPSV-DT occurred in 43.3% of GDM cases and was associated with higher estimated fetal weight and abdominal circumference percentiles, increased amniotic fluid, elevated OGTT values, higher HbA1c, and more frequent insulin therapy (p < 0.01 for all). In GDM pregnancies, CAPO occurred in 73.1% of the abnormal UA hPSV-DT group versus 11.8% of the normal group (p < 0.001). ROC analysis identified a cut-off of < 181 ms for predicting CAPO (AUC 0.741, 70.3% sensitivity, 66.7% specificity). Conclusions: UA hPSV-DT is a novel, reproducible Doppler parameter that independently predicts adverse perinatal outcomes in GDM pregnancies, even when conventional UA Doppler indices are normal. Incorporating UA hPSV-DT into routine surveillance may improve risk stratification and guide management to optimize perinatal outcomes. Full article

Objective: To investigate the association between prenatal ultrasonographic markers of macrossomia and C-peptide, a neonatal hyperinsulinemia marker, in pregnancies complicated by gestational diabetes mellitus (GDM), with a focus on fetal adipose tissue thickness, liver length, and interventricular septal thickness. Methods: This prospective cohort study included 223 pregnant women followed from 28 to 36 weeks of gestation in two referral centers in Brazil. The GDM group and matched controls underwent serial ultrasound assessments of fetal biometry, including thigh, abdominal, and subscapular skinfolds, fetal liver length, and interventricular septum thickness. Neonatal hyperinsulinemia was assessed using umbilical cord C-peptide levels. Statistical analyses included t-tests, chi-square tests, correlation analyses, and multivariate logistic regression. Results: Fetuses of mothers with GDM exhibited significantly greater abdominal [t(221) = −3.999, p < 0.01] and subscapular [t(221) = −2.502, p = 0.02] skinfolds, liver length [t(221) = −3.785, p < 0.01], and interventricular septum [t(221) = −4.781, p < 0.01] thickness. However, umbilical cord C-peptide levels did not differ significantly between groups [t(189) = −1.724, p = 0.09]. Only weak correlations were found between fetal ultrasound markers and C-peptide levels. Among all parameters, subcutaneous tissue thickness showed the highest (ρ = 0.30), though still limited, predictive value. Conclusions: Fetuses of mothers with GDM demonstrated increased measures of liver length, subscapular adiposity, and interventricular septal thickness compared to controls. However, these prenatal biometric markers showed weak correlations with neonatal C-peptide levels. Full article

Objective: The aim of this study was to analyze the concordance between estimated fetal weight (EFW) and birth weight among ultrasound examinations with fetal biometry considered adequate and inadequate according to the International Society of Ultrasound in Obstetrics and Gynecology (ISUOG) guidelines, and its association with adverse perinatal outcomes. Methods: This was a retrospective and cross-sectional study carried out in two centers, involving parturients who delivered between 37 and 41 weeks. The following parameters were evaluated: biparietal (BPD), head circumference (HC), abdominal circumference (AC), and femur length (FL) measurement; EFW; the interval between the ultrasound and delivery; and the discrepancy between EFW and birth weight. A minimum of 140 participants were required to assess the association between EFW and birth weight. Results: A total of 305 ultrasound examinations were selected and divided into two groups: adequate (Group I n = 115) and inadequate (Group II n = 190) fetal biometry. The measurements of the cephalic pole (BPD + HC), AC, and FL were inadequate in 69.5% (132/190), 91.6% (175/190), and 72.1% (137/190) of participants, respectively. Group I had a lower gestational age at ultrasound examination (38.4 vs. 39.9 weeks, p < 0.001), a larger BPD measurement (93.9 vs. 91.6 mm, p = 0.001), a longer interval between ultrasound examination and delivery (3.8 vs. 2.0 days, p < 0.001), and a smaller discrepancy between EFW and birth weight (7.2 vs. 9.5%, p = 0.002) than Group II. In Group I, EFW was a strong significant predictor (AUC:0.94, 95%CI 0.85–0.99, p = 0.032) for identifying birth weight >4000 g. An EFW cut-off value of 4019.0 g was found to be a correct identifier for 85.7% of newborns with a birth weight >4000 g, with a false-positive rate of 13.7%. Group I had a lower risk of postpartum hemorrhage (7.0% vs. 15.8%, OR:0.39, 95%CI 0.17–0.90, p = 0.024) and composite adverse perinatal outcomes (13.0 vs. 23.3%, OR:0.49, 95%CI 0.26–0.94, p = 0.030) than Group II. In Group I patients, undergoing an ultrasound 7 days before delivery was an independent predictor of composite adverse perinatal outcomes [x²(1) = 4.9, OR:0.49, 95%CI: 0.26–0.94, R² Nagelkerke:0.026, p = 0.030]. Conclusions: We observed a high rate of inadequate fetal biometry. There was poor concordance between EFW and birth weight. EFW was a strong significant predictor for identifying macrosomia. Ultrasound examination performed 7 days before delivery was an independent predictor of adverse perinatal outcomes. Full article

Background/Objectives: Little is known about the advantages of Diffusion Tensor Imaging (DTI) when evaluating the fetal corpus callosum (CC), a sensitive indicator for normal brain development. This study evaluates the contribution of DTI compared to T2-weighted imaging to assess fetal CC biometry. Methods: Data from the fetal MRI exams of singleton pregnancies between July 2017 and 2019 were retrospectively analyzed. Mid-sagittal sections were used to measure the CC biometry, and inter- and intra-observer agreements were assessed using the interclass correlation coefficient (ICC), targeting an ICC above 0.85. Results: The results from 100 patients (mean gestational age, 32.24 weeks) indicated excellent inter-observer reliability for DTI (ICC = 0.904, 95% CI = 0.815–0.952) and moderate agreement for T2-weighted imaging (ICC = 0.719, 95% CI = 0.556–0.842). Intra-observer assessments showed excellent reliability for both DTI and T2-weighted imaging (ICC = 0.967, 95% CI = 0.933–0.984 and ICC = 0.942, 95% CI = 0.884–0.971, respectively). However, a comparison between DTI and T2-weighted images for CC biometry showed poor agreement (ICC = 0.290, 95% CI = 0.071–0.476). Conclusions: In conclusion, the study highlights a lack of agreement between DTI and T2-weighted imaging in fetal CC biometry, suggesting the need for further research to understand this discrepancy and the role of DTI in fetal health. Full article

Background/Objectives: Systematic quality review of ultrasound exams is recommended to ensure accurate diagnosis. Our primary objectives were to develop a quantitative method for quality review of estimated fetal weight (EFW) and to assess the accuracy of EFW for an entire practice and for individual personnel. A secondary objective was to evaluate the accuracy of fetal sex determination. Methods: This is a retrospective cohort study. Eligible ultrasound exams included singleton pregnancies with live birth and known birth weight (BW). A published method was used to predict BW from EFW for exams with ultrasound-to-delivery intervals of up to 12 weeks. Mean error and median absolute error (AE) were compared between different personnel. Image audits were performed for exams with AE > 30% and exams with reported fetal sex different than newborn sex. Results: We analyzed 1938 exams from 890 patients. In the last exam before birth, the median AE was 5.9%, and the predicted BW was within ±20% of the actual BW in 97.2% of patients. AE was >30% in 28 exams (1.4%); image audit found correct caliper placement in all 28. Only two patients (0.2%) had AE > 30% on the last exam before birth. One sonographer systematically over-measured head and abdominal circumferences, leading to EFWs that were overestimated. Reported fetal sex differed from newborn sex in seven exams (0.4%) and five patients (0.6%). Images in four of these patients were annotated with the correct fetal sex, but a clerical error was made in the report. In one patient, an unclear image was labeled “probably female”, but the newborn was male. Conclusions: The accuracy of EFW in this practice was similar to literature reports. The quantitative analysis identified a sonographer with outlier measurements. Time-consuming image audits could be focused on a small number of exams with large errors. We suggest some enhancements to ultrasound reporting software that may help to reduce clerical errors. We provide tools to help other practices perform similar quality reviews. Full article

Background/Objectives: To evaluate the quality of an ultrasound practice, both large-scale and focused audits are recommended by professional organizations, but such audits can be time-consuming, inefficient, and expensive. Our objective was to develop a time-efficient, quantitative, objective, large-scale method to evaluate fetal biometry measurements for an entire practice, combined with a process for focused image review for personnel whose measurements are outliers. Methods: Ultrasound exam data for a full year are exported from commercial ultrasound reporting software to a statistical package. Fetal biometry measurements are converted to z-scores to standardize across gestational ages. For a large-scale audit, sonographer mean z-scores are compared using analysis of variance (ANOVA) with Scheffe multiple comparisons test. A focused image review is performed on a random sample of exams for sonographers whose mean z-scores differ significantly from the practice mean. A similar large-scale audit is performed, comparing physician mean z-scores. Results: Using fetal abdominal circumference measurements as an example, significant differences between sonographer mean z-scores are readily identified by the ANOVA and Scheffe test. A method is described for the blinded image audit of sonographers with outlier mean z-scores. Examples are also given for the identification and interpretation of several types of systematic errors that are unlikely to be detectable by image review, including z-scores with large or small standard deviations and physicians with outlier mean z-scores. Conclusions: The large-scale quantitative analysis provides an overview of the biometry measurements of all the sonographers and physicians in a practice, so that image audits can be focused on those whose measurements are outliers. The analysis takes little time to perform after initial development and avoids the time, complexity, and expense of auditing providers whose measurements fall within the expected range. We encourage commercial software developers to include tools in their ultrasound reporting software to facilitate such quantitative reviews. Full article

Background/Objectives: The utility of shear wave elastography (SWE) as an adjunct to ultrasound biometry and Doppler velocimetry for the examination of placental dysfunction and suboptimal fetal growth is unclear. To date, limited data exist correlating the mechanical properties of placentae with fetal growth. This study aimed to investigate the relationship between placental shear wave velocity (SWV) and ultrasound estimated fetal weight (EFW), and to ascertain if placental SWV is a suitable proxy measure of placental function in the surveillance of small-for-gestational-age (SGA) pregnancies. Methods: This prospective, observational cohort study compared the difference in placental SWV between SGA and appropriate-for-gestational-age (AGA) pregnancies. There were 221 women with singleton pregnancies in the study cohort—136 (61.5%) AGA and 85 (38.5%) SGA. Fetal biometry, Doppler velocimetry, the deepest vertical pocket of amniotic fluid, and mean SWV were measured at 2–4-weekly intervals from recruitment to birth. Results: There was no difference in mean placental SWV in SGA pregnancies compared to AGA pregnancies, nor was there any relationship to EFW. Conclusions: Although other studies have shown some correlation between increased placental stiffness and SGA pregnancies, our investigation did not support this. The mechanical properties of placental tissue in SGA pregnancies do not result in placental SWVs that are apparently different from those of AGA controls. As this study did not differentiate between constitutionally or pathologically small fetuses, further studies in growth-restricted cohorts would be of benefit. Full article

Objectives: Congenital diaphragmatic hernia (CDH) is defined as organ protrusion from the abdominal to the thoracic cavity. The Hadlock formula is the most commonly used tool for calculating estimated fetal weight (EFW). The anatomical nature of CDH usually leads to underestimation of the abdominal circumference, resulting in underestimation of fetal weight. Accurate weight estimation is essential before birth for counselling, preparation before surgery and ECMO. The research is made to compare the accuracy of Hadlock’s formula and Faschingbauer’s formula for fetal weight estimation in CDH fetuses population. Methods: In our study, we investigated differences between EFW and actual birthweight in 42 fetuses with CDH as compared to 80 healthy matched controls. EFW was calculated using the Hadlock formula and a recently introduced formula described by Faschingbauer et al., which was tailored for fetuses with CDH. Additionally, both of the formulas were adjusted for the interval between the ultrasound and delivery for both of the groups. Results: The majority of hernias were left-sided (92.8% vs. 7.2%). EFW adjusted for the interval between the ultrasound and delivery had the highest correlation with the actual birthweight in both, study group and controls. We compared the results for both tools and found the Hadlock formula to predict birthweight in CDH children with a 7.8 ± 5.5% error as compared to 7.9 ± 6.5% error for the Faschingbauer’s formula. Conclusions: The Hadlock formula adjusted for the interval between the ultrasound and delivery is a more precise method of calculating EFW in fetuses with CDH. Routine biometry scan using Hadlock’s formula remains reliable for predicting birthweight. Full article

As the use of magnetic resonance imaging of the fetal brain has evolved, the need to understand its efficiency in the biometry of the fetal brain has broadened. This study aimed to assess the level of agreement and correlation between the two cardinal imaging methods of fetal neuroimaging, ultrasonography (US) and magnetic resonance imaging (MRI), by measuring the corpus callosum (CC) and transverse cerebellar diameter (TCD) in terms of length and percentile. Measurements of CC and TCD length and percentile were documented over a 7-year span in a tertiary referral medical center. All US and MRI examinations were performed in the customary planes and subcategorized by valid reference charts. Exclusion and inclusion criteria were set before the collection and processing of the data. A total of 156 fetuses out of 483 were included in the study. A positive, strong correlation and agreement were found (r = 0.78; ICC = 0.76) between US and MRI in TCD measurements. For CC length measurement, a moderate correlation and moderate agreement (r = 0.51; ICC = 0.49) between US and MRI was observed. TCD and CC percentiles had lower levels of correlation and agreement compared with the length variables. Our study indicates good agreement between MRI and US in the assessment of TCD measurement as a part of antenatal neuroimaging. Furthermore, while the two techniques are not always compatible, they are complementary methods. Full article

The echocardiographic monitoring of a fetus with multiple nuchal cords around the fetal neck is important as it may result in cardiac remodeling and preferential streaming, thus affecting the condition of the fetus. The main aim of our study was to assess whether the collision of the umbilical cord around the fetal neck can lead to discrepancies in the size of the pulmonary artery and the aorta in the three-vessel view and to an increase in the size of the heart, which may result from the compression of the carotid arteries caused by the umbilical cord wrapping around the fetal neck. A total number of 854 patients were included in this study and divided into three groups. Group A (control group) included 716 fetuses (84%) without the umbilical cord around the fetal neck. Group B (study group B) included 102 fetuses (12%) with one coil of the umbilical cord around the fetal neck. Group C (study group C) included 32 fetuses (4%) with two coils of the umbilical cord around the fetal neck. The range of the gestational age of the patients considered for this study was 27–40.2 weeks based on the ultrasound biometry and was not statistically different between the analyzed groups A, B and C (p > 0.05). The Pa/Ao index was calculated by dividing the value of the width of the pulmonary artery (in mm) to the width of the aorta (in mm) measured in the ultrasound three-vessel view. We found that fetuses that the fetuses with one and two coils of the umbilical cord around the neck showed significantly higher values of the width of the pulmonary trunk with the unchanged value of the aorta width. Therefore, we also observed significantly higher values of the ratio of the pulmonary trunk to the aorta for the fetuses wrapped with the umbilical cord around the neck compared with the control group without the umbilical cord around the neck (. Moreover, in the fetuses with one and two coils of the umbilical cord around the fetal neck, an increased amount of amniotic fluid was observed, whereas larger dimensions of CTAR in the fetuses with two coils of the umbilical cord around the neck were present (p < 0.05). The wrapping of the fetus with the umbilical cord around the fetal neck may induce the redistribution of blood flow, leading to fetal heart enlargement and disproportion and may be the cause of polyhydramnios. Full article

In this work, a novel multimodal learning approach for early prediction of birth weight is presented. Fetal weight is one of the most relevant indicators in the assessment of fetal health status. The aim is to predict early birth weight using multimodal maternal–fetal variables from the first trimester of gestation (Anthropometric data, as well as metrics obtained from Fetal Biometry, Doppler and Maternal Ultrasound). The proposed methodology starts with the optimal selection of a subset of multimodal features using an ensemble-based approach of feature selectors. Subsequently, the selected variables feed the nonparametric Multiple Kernel Learning regression algorithm. At this stage, a set of kernels is selected and weighted to maximize performance in birth weight prediction. The proposed methodology is validated and compared with other computational learning algorithms reported in the state of the art. The obtained results (absolute error of 234 g) suggest that the proposed methodology can be useful as a tool for the early evaluation and monitoring of fetal health status through indicators such as birth weight. Full article

The gestation period in ferrets lasts 42 days (range 38–42). Numerous cases of maternal and paternal cannibalism have been reported, so it is important for breeders to know the exact date of parturition in order to separate the mother from the other ferrets in the herd. Fetal ultrasonographic biometry and specific formulae for assessing fetal growth have not yet been developed in ferrets as they have been in dogs and cats. The aim of this study was to develop a formula, similar to those available for other domestic species, that could be used in ferrets to date the birth of a litter to within one day. Among the different ultrasonographic parameters, the biparietal diameter (BP) gave a very accurate prediction and showed a significant relationship with days before parturition. The formula developed could allow better planning of care before, during and after parturition, thus helping to reduce neonatal mortality. Full article

The distinct placental angioarchitecture in monochorionic (MC) pregnancies increases the risk of complications such as twin–twin transfusion syndrome (TTTS), twin anemia polycythemia sequence (TAPS), and selective fetal growth restriction (sFGR). The aim of this systematic review was to evaluate the incidence, type, and severity of cerebral injury and structural brain development on fetal and/or neonatal cerebral magnetic resonance imaging (MRI) in MC twins with or without complications. Twenty-three studies were included, covering a wide range of complications observed during MC pregnancies, with studies involving sIUFD (n = 12), TTTS (n = 7), mixed complications (n = 2), TAPS (n = 1), and uncomplicated MC pregnancy (n = 1). TAPS and sFGR were largely underrepresented in the current literature. The included studies reported that MC pregnancies with single intrauterine fetal demise (sIUFD) are most at risk for cerebral injury during the fetal period. The overall median incidence of cerebral injury after sIUFD was 28.3% (0–55%). Severe antenatal cerebral injury after sIUFD was detected antenatally in 6.5% (0–36%) of the cases. Three of the included studies described the incidence, type, and severity of cerebral injury on neonatal MRI in MC twins. Structural brain development based on cerebral biometry was only assessed in two studies, revealing significantly smaller biometric measurements of the cerebrum in cases of single sIUFD or smaller twins compared to singleton pregnancies. To enhance our understanding of the potential risks and pathophysiological mechanisms associated with cerebral injury and structural brain development in MC twins, there is a need for future studies and standardized protocols using serial fetal and neonatal MRI imaging in addition to routine ultrasound imaging. Full article

Artificial intelligence (AI) has gained prominence in medical imaging, particularly in obstetrics and gynecology (OB/GYN), where ultrasound (US) is the preferred method. It is considered cost effective and easily accessible but is time consuming and hindered by the need for specialized training. To overcome these limitations, AI models have been proposed for automated plane acquisition, anatomical measurements, and pathology detection. This study aims to overview recent literature on AI applications in OB/GYN US imaging, highlighting their benefits and limitations. For the methodology, a systematic literature search was performed in the PubMed and Cochrane Library databases. Matching abstracts were screened based on the PICOS (Participants, Intervention or Exposure, Comparison, Outcome, Study type) scheme. Articles with full text copies were distributed to the sections of OB/GYN and their research topics. As a result, this review includes 189 articles published from 1994 to 2023. Among these, 148 focus on obstetrics and 41 on gynecology. AI-assisted US applications span fetal biometry, echocardiography, or neurosonography, as well as the identification of adnexal and breast masses, and assessment of the endometrium and pelvic floor. To conclude, the applications for AI-assisted US in OB/GYN are abundant, especially in the subspecialty of obstetrics. However, while most studies focus on common application fields such as fetal biometry, this review outlines emerging and still experimental fields to promote further research. Full article