Estimation Of Gestational Age Research Articles

Real world external validation of metabolic gestational age assessment in Kenya.

Using data from Ontario Canada, we previously developed machine learning-based algorithms incorporating newborn screening metabolites to estimate gestational age (GA). The objective of this study was to evaluate the use of these algorithms in a population of infants born in Siaya county, Kenya. Cord and heel prick samples were collected from newborns in Kenya and metabolic analysis was carried out by Newborn Screening Ontario in Ottawa, Canada. Postnatal GA estimation models were developed with data from Ontario with multivariable linear regression using ELASTIC NET regularization. Model performance was evaluated by applying the models to the data collected from Kenya and comparing model-derived estimates of GA to reference estimates from early pregnancy ultrasound. Heel prick samples were collected from 1,039 newborns from Kenya. Of these, 8.9% were born preterm and 8.5% were small for GA. Cord blood samples were also collected from 1,012 newborns. In data from heel prick samples, our best-performing model estimated GA within 9.5 days overall of reference GA [mean absolute error (MAE) 1.35 (95% CI 1.27, 1.43)]. In preterm infants and those small for GA, MAE was 2.62 (2.28, 2.99) and 1.81 (1.57, 2.07) weeks, respectively. In data from cord blood, model accuracy slightly decreased overall (MAE 1.44 (95% CI 1.36, 1.53)). Accuracy was not impacted by maternal HIV status and improved when the dating ultrasound occurred between 9 and 13 weeks of gestation, in both heel prick and cord blood data (overall MAE 1.04 (95% CI 0.87, 1.22) and 1.08 (95% CI 0.90, 1.27), respectively). The accuracy of metabolic model based GA estimates in the Kenya cohort was lower compared to our previously published validation studies, however inconsistency in the timing of reference dating ultrasounds appears to have been a contributing factor to diminished model performance.

Effective Approaches to Fetal Brain Segmentation in MRI and Gestational Age Estimation by Utilizing a Multiview Deep Inception Residual Network and Radiomics.

To completely comprehend neurodevelopment in healthy and congenitally abnormal fetuses, quantitative analysis of the human fetal brain is essential. This analysis requires the use of automatic multi-tissue fetal brain segmentation techniques. This paper proposes an end-to-end automatic yet effective method for a multi-tissue fetal brain segmentation model called IRMMNET. It includes a inception residual encoder block (EB) and a dense spatial attention (DSAM) block, which facilitate the extraction of multi-scale fetal-brain-tissue-relevant information from multi-view MRI images, enhance the feature reuse, and substantially reduce the number of parameters of the segmentation model. Additionally, we propose three methods for predicting gestational age (GA)-GA prediction by using a 3D autoencoder, GA prediction using radiomics features, and GA prediction using the IRMMNET segmentation model's encoder. Our experiments were performed on a dataset of 80 pathological and non-pathological magnetic resonance fetal brain volume reconstructions across a range of gestational ages (20 to 33 weeks) that were manually segmented into seven different tissue categories. The results showed that the proposed fetal brain segmentation model achieved a Dice score of 0.791±0.18, outperforming the state-of-the-art methods. The radiomics-based GA prediction methods achieved the best results (RMSE: 1.42). We also demonstrated the generalization capabilities of the proposed methods for tasks such as head and neck tumor segmentation and the prediction of patients' survival days.

DeepGA for automatically estimating fetal gestational age through ultrasound imaging

Accurate estimation of gestational age (GA) is vital for identifying fetal abnormalities. Conventionally, GA is estimated by measuring the morphology of the cranium, abdomen, and femur manually and inputting them into the classic Hadlock formula to assess fetal growth. However, this procedure incurs considerable overhead and suffers from bias caused by the operators, yielding suboptimal estimations. To address this challenge, we develop an automatic DeepGA model to achieve fully automatic GA prediction in an end-to-end manner. Our model uses a deep segmentation model (DeepSeg) to accurately identify and segment three critical tissues, including the cranium, abdomen, and femur, in which their morphology is automatically extracted. After that, we are able to directly estimate the GA via a deep regression model (DeepReg). We evaluate DeepGA on a large dataset, including 10,413 ultrasound images from 7113 subjects. It achieves superior performance over the traditional measurement approach, with a mean absolute estimation error (MAE) of 5 days. Our DeepGA model is a novel automatic solution on the basis of artificial intelligence learning that can help radiologists improve the performance of GA estimation in various clinical scenarios, thereby enhancing the efficiency of prenatal examinations.

Portable ultrasound technologies for estimating gestational age in pregnant women: a scoping review and analysis of commercially available models

ObjectivesTo identify all available studies assessing the use of portable ultrasound devices for pregnant women, with the specific aim of finding evidence for devices used to determine gestational age and...

Ultra Sonographic Measurement of Placental Thickness during Pregnancy as a Parameter for Estimating Gestational Age of the Fetus

Background: The most effective prenatal care and successful births are always dependent on accurate gestational age estimation (GA). The gestational age play important role in biochemical tests interpretation. Objective: The study was carried out to find the ultra-sonographic measurements done to check the placental thickness. It is an important factor for the gestational age estimation. Study design: This is a cross-sectional study conducted at Al Nafees Medical College and Hospital, Islamabad for the duration of one year from June 2021 to May 2022. Material and Methods: The study was conducted on 325 pregnant women that visited tertiary care unit for a period of one year. All women were fully aware of the study and written consent was taken from them. Results: the thickness of placenta found at different gestational age. From 15 to 39 weeks of gestation the data was collected and no. of cases having placental thickness were recorded. Maximum and minimum placental thickness in mm was measured and average was taken. The age range of the women was 18-36 years. The 26 years was the mean age. The statistical significance was found by SPSS tool Conclusions: In this study there was found a strong link between week of gestational age and thickness of placenta. Placental thickness along with other parameters were studied in each week by ultrasound and the results were analyzed. In case where the exact duration of pregnancy is unknown, placental thickness can give information about age of fetus and other features like intrauterine stunted growth. Keywords: Placental thickness and gestational age.

Student Competency for Midtrimester Obstetrics Scan upon Completion of the Master's Degree in Medical Sonography.

To evaluate the competency of medical sonographer students who have completed training to estimate the gestational age (GA) and perform fetal biometric measurements compared to obstetricians. We conducted a cross-sectional observational study at the end of the medical sonographer students' practice sessions. In total, 80 midtrimester (18-28 weeks) pregnant women were recruited, and an ultrasound was performed according to the International Society of Sonography in Obstetrics and Gynecology (ISUOG) guideline. Estimated GA calculated from fetal biometric measurements was compared between medical sonographer students and qualified obstetricians. Subsequently, images were randomly evaluated by maternal-fetal medicine specialists to assess the measurement performance. There was no significant difference in the estimated GA between the medical sonographer students and obstetricians (mean difference, 0.01 ± 2.92 day, p = 0.89). However, there was a significant difference in the measurement of the head circumference (HC) and abdominal circumference (AC) (p < 0.001). The overall image quality of the fetal head, abdomen, and femur was considered a good to excellent score (77.5%-80%). There was a perfect and nearly perfect agreement regarding the presence of the placenta previa, adequacy of amniotic fluid, and position of the placenta (k = 0.9-1.0). The medical sonographer students demonstrated competency in GA estimation by fetal biometry measurement similar to obstetricians. However, the quality of the acquired images, according to the ISUOG recommendation, needs improvement, and this should be emphasized in the sonography course curriculum. The results suggest that medical sonographers can relieve obstetricians' workload for ultrasound screening in midtrimester pregnancies.

Risk of fetal or neonatal death or neonatal intensive care unit admission associated with gadolinium magnetic resonance imaging exposure during pregnancy

Concerns have been raised about prenatal exposure to magnetic resonance imaging with gadolinium-based contrast agents because of nonclinical findings of gadolinium retention in fetal tissue and 1 population-based study reporting an association with adverse pregnancy outcomes. This study aimed to evaluate the association between prenatal magnetic resonance imaging exposure with and without gadolinium-based contrast agents and fetal and neonatal death and neonatal intensive care unit admission. We constructed a retrospective cohort of >11 million Medicaid-covered pregnancies between 1999 and 2014 to evaluate the association between prenatal magnetic resonance imaging exposure with and without gadolinium-based contrast agents and fetal and neonatal death (primary endpoint) and neonatal intensive care unit admissions (secondary endpoint). Medicaid claims data were linked to medical records, Florida birth and fetal death records, and the National Death Index to validate the outcomes and gestational age estimates. Pregnancies with multiples, concurrent cancer, teratogenic drug exposure, magnetic resonance imaging focused on fetal or pelvic evaluation, undetermined gadolinium-based contrast agent use, or those preceded by or contemporaneous with congenital anomaly diagnoses were excluded. We adjusted for potential confounders with standardized mortality ratio weighting using propensity scores. Among 5991 qualifying pregnancies, we found 11 fetal or neonatal deaths in the gadolinium-based contrast agent magnetic resonance imaging group (1.4%) and 73 in the non-gadolinium-based contrast agent magnetic resonance imaging group (1.4%) with an adjusted relative risk of 0.73 (95% confidence interval, 0.34-1.55); the neonatal intensive care unit admission adjusted relative risk was 1.03 (0.76-1.39). Sensitivity analyses investigating the timing of magnetic resonance imaging or repeat magnetic resonance imaging exposure during pregnancy and simulating the impact of exposure misclassification corroborated these results. This study addressed the safety concerns related to prenatal exposure to gadolinium-based contrast agents used in magnetic resonance imaging and the risk thereof on fetal and neonatal death or the need for neonatal intensive care unit admission. Although the results on fatal or severe acute effects are reassuring, the impact on subacute outcomes was not evaluated.

A mobile-optimized artificial intelligence system for gestational age and fetal malpresentation assessment

BackgroundFetal ultrasound is an important component of antenatal care, but shortage of adequately trained healthcare workers has limited its adoption in low-to-middle-income countries. This study investigated the use of artificial intelligence for fetal ultrasound in under-resourced settings.MethodsBlind sweep ultrasounds, consisting of six freehand ultrasound sweeps, were collected by sonographers in the USA and Zambia, and novice operators in Zambia. We developed artificial intelligence (AI) models that used blind sweeps to predict gestational age (GA) and fetal malpresentation. AI GA estimates and standard fetal biometry estimates were compared to a previously established ground truth, and evaluated for difference in absolute error. Fetal malpresentation (non-cephalic vs cephalic) was compared to sonographer assessment. On-device AI model run-times were benchmarked on Android mobile phones.ResultsHere we show that GA estimation accuracy of the AI model is non-inferior to standard fetal biometry estimates (error difference −1.4 ± 4.5 days, 95% CI −1.8, −0.9, n = 406). Non-inferiority is maintained when blind sweeps are acquired by novice operators performing only two of six sweep motion types. Fetal malpresentation AUC-ROC is 0.977 (95% CI, 0.949, 1.00, n = 613), sonographers and novices have similar AUC-ROC. Software run-times on mobile phones for both diagnostic models are less than 3 s after completion of a sweep.ConclusionsThe gestational age model is non-inferior to the clinical standard and the fetal malpresentation model has high AUC-ROCs across operators and devices. Our AI models are able to run on-device, without internet connectivity, and provide feedback scores to assist in upleveling the capabilities of lightly trained ultrasound operators in low resource settings.

Placental thickness and its correlation to gestational age estimated by fetal biometry: A cross-sectional study

Background: Accurate estimation of gestational age is important not only for appropriate antenatal care but also is crucial for undertaking various diagnostics tests such as chorionic villous sampling and amniocentesis. In certain conditions, where biometry cannot be entirely relied on for estimation of gestational age placental thickness (PT) that can be used for estimation of gestational age. Aims and Objectives: The aims of this study were as follows: (1) To analyze relationship between PT and gestational age as determined by fetal biometry in second and third trimester of pregnancy. (2) To find out cutoff PT value for differentiating between preterm and term gestations. Materials and Methods: This was a cross-sectional, in which 140 patients, in 2nd and 3rd trimester, were included on the basis of a predefined inclusion and exclusion criteria. PT was measured in mm along with their respective standard deviation. The correlation between PT and gestational age as determined by biometry. Results: The mean age of the studied cases was found to be 4.15±3.5 years. At 12 weeks of gestation, the mean PT was 14.36 mm. There was a strong positive correlation between gestational age and PT in 2nd (r=0.9943) and 3rd (r=0.9973) trimesters. After 37 weeks of gestation, there was no significant correlation between PT and gestational age (P=0.469). Conclusion: PT has a significant positive correlation with gestational age in 2nd and 3rd trimester of pregnancy (up to 37 weeks of gestation) and can be reliably used for determination of gestational age independent of fetal biometry.

Sono-fetal tibial length evaluation as a predictor of gestational age: A case of Nigerian population

Background: Accurate pregnancy dating is essential for guiding patients about the option of termination of pregnancy or in analysis of biochemical serum screening test and to ensure adequate management of pregnant women with the intention to reduce maternal morbidity and mortality, especially when considering the best parameter for estimating gestational age, it is important that the structure has little biological variation, and can be measured with high degree of reproducibility. This study was designed to evaluate the use of fetal tibia length as a tool for the estimation of gestational age among the Nigerian population. Materials and Methods: This was a cross-sectional study, which involved 215 pregnant women selected using convenient sampling technique based on the inclusion criteria in a single private diagnostic centre in Port Harcourt. Ultrasound scan was done on each subject and fetal biometric parameters (Biparietal diameter, femur length and tibial length) and gestational age were assessed and documented. Data obtained were analyzed using descriptive and inferential statistics. Results: The majority (n = 12) of the pregnant women had gestational age of 25 weeks. The mean values for BPD, FL and TL of those with 17th week GA were 36.70±1 0.35, 23.65±0.7 and 22.28±1.42 as the least mean values while the highest mean values were identified in patients that had 41 weeks of GA, which were 95.20±0.00, 79.40±0.00 and 58.00±0.00 for BPD, FL and TL respectively. There were no statistically significance mean differences between BPD (t = 225.17, p = 0.001), FL (t = 100.84, p = 0.001) and TL (t = -33.38, p = 0.001) and the estimated gestational age of 17 weeks. Conclusion: The fetal tibial length (FTL) increases with advancing gestational age in apparently healthy fetus. The FTL can be strongly use as a tool for the prediction of fetal gestational age, where other parameters cannot be evaluated.

Validation of gestational age determination from ultrasound or a metabolic gestational age algorithm using exact date of conception in a cohort of newborns conceived using assisted reproduction technologies

Accurate estimates of gestational age in pregnancy are important for the provision of optimal care. Although current guidelines generally recommend estimating gestational age via first-trimester ultrasound measurement of crown-rump length, error associated with this method can range from 3 to 8 days of gestation. In pregnancies resulting from assisted reproductive technology, estimated due date can be calculated on the basis of the age of the embryo and the date of embryo transfer, arguably providing the most accurate estimates possible. We have developed and extensively validated statistical models to estimate gestational age postnatally using metabolomic markers from blood samples in combination with clinical and demographic data. These models have shown high accuracy compared with first-trimester ultrasound, the recommended method for estimating gestational age in spontaneous pregnancies. We hypothesized that gestational age derived from date and stage of embryo at transfer in newborns conceived using assisted reproduction therapy would provide the most accurate reference standard possible to evaluate and compare the accuracy of both first-trimester ultrasound and metabolomic model-based gestational dating. This study aimed to validate both first-trimester ultrasound dating and postnatal metabolomic gestational age estimation models against gestational age derived from date and stage of embryo at transfer in a cohort of newborns conceived via assisted reproductive technology, both overall and in important subgroups of interest (preterm birth, small for gestational age, and multiple birth). This was a retrospective cohort study of infants born in Ontario, Canada between 2015 and 2017 and captured in the provincial birth registry. Spontaneous conceptions were randomly partitioned into a model derivation sample (80%) and a test sample (20%) for model validation. A cohort of assisted conceptions resulting from fresh embryo transfers was derived to evaluate the accuracy of both ultrasound and model-based gestational dating. Postnatal gestational age estimation models were developed with multivariable linear regression using elastic-net regularization. Gestational age estimates from dating ultrasound and from postnatal metabolomic models were compared with date of embryo transfer reference gestational age in the independent test cohorts. Accuracy was quantified by calculating mean absolute error and the square root of mean squared error. Our model derivation cohort included 202,300 spontaneous conceptions, and the testing cohorts included 50,735 spontaneous conceptions and 1924 assisted conceptions. In the assisted conception cohort, first-trimester dating ultrasound was accurate to within approximately ±1.5 days compared with date of embryo transfer reference overall (mean absolute error, 0.21 [95% confidence interval, 0.20-0.23]). When compared with gestational age derived from date of embryo transfer, the metabolomic estimation models were accurate to within approximately ±5 days overall (0.79 [0.76-0.81] weeks). When ultrasound was used as the reference in validating the metabolomic model, the mean absolute error was slightly higher overall (0.81 [0.78-0.84] weeks). In general, the accuracy of gestational age estimates derived from ultrasound or metabolomic models was highest in term infants and lower in preterm and small-for-gestational-age newborns. Our findings support the accuracy of ultrasound as a gestational age dating tool. They also support the potential utility of metabolic gestational age dating algorithms in settings where ultrasound or other accurate methods of estimating gestational age are not available because of lack of infrastructure or specialized training (eg, low-income countries). However, the accuracy of metabolomic model-based dating was generally lower than that of ultrasound.

Measurement of symphysis fundal height for gestational age estimation in low-to-middle-income countries: A systematic review and meta-analysis.

In low- and middle-income countries (LMIC), measurement of symphysis fundal height (SFH) is often the only available method of estimating gestational age (GA) in pregnancy. This systematic review aims to summarize methods of SFH measurement and assess the accuracy of SFH for the purpose of GA estimation. We searched PubMed, EMBASE, Cochrane, Web of Science, POPLINE, and WHO Global Health Libraries from January 1980 through November 2021. For SFH accuracy, we pooled the variance of the mean difference between GA confirmed by ultrasound versus SFH. Of 1,003 studies identified, 37 studies were included. Nineteen different SFH measurement techniques and 13 SFH-to-GA conversion methods were identified. In pooled analysis of five studies (n = 5838 pregnancies), 71% (95% CI: 66-77%) of pregnancies dated by SFH were within ±14 days of ultrasound confirmed dating. Using the 1 cm SFH = 1wk assumption, SFH underestimated GA compared with ultrasound-confirmed GA (mean bias: -14.0 days) with poor accuracy (95% limits of agreement [LOA]: ±42.8 days; n = 3 studies, 2447 pregnancies). Statistical modeling of three serial SFH measurements performed better, but accuracy was still poor (95% LOA ±33 days; n = 4 studies, 4391 pregnancies). In conclusion, there is wide variation in SFH measurement and SFH-to-GA conversion techniques. SFH is inaccurate for estimating GA and should not be used for GA dating. Increasing access to quality ultrasonography early in pregnancy should be prioritized to improve gestational age assessment in LMIC.

Fetal kidney length as a parameter for determination of gestational age after 20th week in healthy women with uncomplicated pregnancy

Aim: To check the accuracy of Fetal Kidney Length (FKL) in the estimation of Gestational Age (GA). Materials and Methods: The present prospective cross sectional study was conducted in Max Super Specialty Hospital, Mohali, Punjab, India. The subjects were selected from the patients visiting the department of Radio diagnosis on in-patient or out-patient basis. The study was carried out for the duration of 12 months after taking approval from the IEC. Healthy women with uncomplicated pregnancy after 20th week of gestation were included in the study. Results: Out of 203 patients included in the study, 3 (1.3%) were in the age group of &lt; 20 years, 76 (37.7%) were in the age group of 20-25 years, 100 (49%) were in the age group of 25-30 years and 24 (12%) were in the age group of &gt; 30 years. In the 203 pregnant patients, age group included in the study ranged from 18 to 36 years with the mean age of 26.46 years Age of second trimester patients (100 patients) ranged from 19 to 35 with the mean of 26.26 years. The age of third trimester (103 patients) patient ranged from 18 to 36 with mean of 26.67 years.

Estimation of fetal gestational age by fetal kidney length measurement from 20-40th weeks of gestation in healthy women with uncomplicated pregnancy

In the precise estimation of gestational age, fetal kidney length measurement by ultrasound proves to be an effective parameter from 20-40th weeks of gestation.To conduct an ultrasound examination for healthy women with uncomplicated pregnancy from 20 weeks to 40 weeks to determine the association between fetal kidney length and gestational age determined by the last menstrual period and other ultrasound parameters (such as biparietal diameter, head circumference, abdominal circumference and length of the femur). Obtain a nomogram and estimate the gestational age of the fetus by the length of the fetal kidney measured by ultrasound. This study aims to validate the measurement of fetal kidney length as an additional morphological parameter with less variability for estimating fetal growth. This measurement can be included into the pregnancy dating model after 20 weeks of gestation as it is easy to perform, especially when the measurement of biparietal diameter and head circumference is difficult.

Fetal biometry is assessment of fetal growth restriction in Telangana region

Background: Intrauterine increase restriction (IUGR) is most common complication in pregnancy and affects morbidity and mortality in any respect degrees of life. With current Doppler research of the fetal important circulation, inclusive of intracardiac flows and the ductus venosus, higher timing of shipping to decrease morbidity can be possible. Serial ultrasound measurements can offer an inexpensive estimate of fetal gestational age and weight primarily based totally on person and composite fetal biometric measurements. Materials and methods: This study consists of pregnant women who are attending OP /IP in department of OBG, SVS medical college, Mehabubnagar, Telanagana. All the retrospective USG quantitative data was noted in case proforma. Sample size was 100 in our study and was divided into cases and controls. Results: In 2nd trimester FGR parameters like FL (30.32), BPD (41.74), AC (136.34), HC (185.36) , GA (20.22) and EFW (310.04) were less when compared to normal fetus. In 3nd trimester we observed FL (61.44), BPD(79.64), AC(287.54) , HC(314.06) , GA (32.06) and EFW (1695.60) which were less when compared to normal fetus. Conclusion: that all the parameters in FGR from 2nd and 3rd trimester were less when compared to normal.

P-356 Clinical implications of first-trimester ultrasound dating in singleton pregnancies obtained through in vitro fertilization

Abstract Study question Is there a correspondence between ultrasound estimation of gestational age (GAUS) and its calculation based on embryo transfer date (GAIVF), in in-vitro fertilization (IVF) pregnancies? Summary answer GAUS and GAIVF are not overlapping, being the first mildly greater than the latter, maybe due to anticipated ovulation and fertilization or accelerated embryo development. What is known already In IVF pregnancies the precise date of conception is known. However, it is possible that some factors (such as a time delay between conception and implantation, an early in-vitro embryo development, and the maternal environment itself with its altered hormonal milieu) may influence the early stages of embryonic development. Data regarding first-trimester fetal development in IVF pregnancies are in fact conflicting and both underestimation and overestimation of the true GA were reported when traditional charts were used for ultrasound pregnancy dating. Study design, size, duration A retrospective study was performed, including all singleton IVF pregnancies who underwent the first-trimester ultrasound scan for the screening of aneuploidies between January 2014 and June 2019. For each pregnancy GA was determined using two alternative methods: one based on the date of embryo transfer (GAIVF), and one based on ultrasound measurement of crown-rump length (CRL) (GAUS). GA were compared to search for any discrepancy. The impact of pregnancy dating on obstetric outcome was evaluated. Participants/materials, setting, methods All women with singleton pregnancies conceived by conventional IVF or intracytoplasmic sperm injection (ICSI), who performed first-trimester ultrasound scan for the screening of aneuploidies at the Department of Obstetrics and Gynecology ‘L. Mangiagalli', Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, were included. Exclusion criteria were as follows: multiple pregnancy (i.e., the evidence of more than one gestational sac at the first ultrasound scan), abnormal karyotype and/or congenital malformations detected either in pre- or postnatal period. Main results and the role of chance Overall, 249 women were selected: 111 pregnancies (45%) by conventional IVF, and 138 (55%) by ICSI. Among the included women, 127 (51%) pregnancies resulted from frozen-thawed embryo transfer. At first trimester ultrasound scan, the discrepancy in days between GAUS and GAIVF was ≥ 4 days in 32 cases (13%, 95%CI: 9-18%). It ranged within 2 and 3 days in 100 cases (40%, 95%CI: 34-47%). In 117 cases (47%, 95%CI: 41-53%) GAUS and GAIVF overlapped or showed a discrepancy of ± 1 day. Comparing GAUS and GAIVF at first trimester ultrasound scan, the median values of GA were 88 [86 - 91] days and 87 [85 - 90] days, respectively (p &amp;lt; 0.001). The median difference was 1 [0 - 2] days, with GAUS systematically higher than GAIVF. This discrepancy persisted when subgroups were analyzed comparing different IVF procedures (conventional IVF versus ICSI, cleavage versus blastocyst transfer, frozen versus fresh transfer). The overall duration of pregnancy differed, with median values of 274 [269 - 281] days in GAUS group and 273 [268 - 280] days in GAIVF group, (p &amp;gt; 0.001). No impact of the dating method on obstetric outcomes was observed, being no differences in the rate of preterm birth or abnormal fetal growth. Limitations, reasons for caution This is a retrospective study and thus exposed to the inaccuracies of this study design. Moreover, being a single-centre study, the sample size is relatively small. Finally, ultrasound evaluations were performed by multiple operators: although they are all certified, there is some inter-individual variability that may impact on the results. Wider implications of the findings Despite a known date of conception, it is difficult to assume that the oocyte retrieval date precisely resembles the date of natural ovulation and conception. IVF seems to anticipate fertilization. On these bases, it would be advisable to date IVF pregnancies using GAUS to realign them to natural pregnancies. Trial registration number Not Applicable

Fetal kidney length as a useful adjunct parameter for determination of gestational age

Introduction: Accurate gestational age assessment is important in obstetric care ultrasonography. Fetal kidney length is one of the emerging parameter in estimation of fetal gestational age in 3rd trimester. Objectives: Is to the ascertain the precision of ultrasonographic fetal kidney length measurement as a reliable parameter for determination of gestational age in 3rd trimester. Materials and Methods: Cross-sectional observational study was conducted on 152 antenatal women in the 3rd trimester. Gestational age was estimated by early fetal ultrasound measure and last menstrual period. Results: Mean kidney length showed a Pearson’s correlation coefficient of 0.907 and a determination coefficient of 0.822 with GA. The test was significant at P &lt; 0.05. Conclusions: This study confirms that the fetal kidney length measurement for estimating the gestational age accurately in the 3rd trimester.

Estimation of gestational age using ultrasonography in Baluchi sheep.

The aim of this study was to evaluate the correlation between some fetal parameters measured by ultrasonography and fetal age for developing a formula which could be used for estimation of fetal age in Baluchi sheep. Placentome diameter (PD), gestation Sac diameter (GSD), biparietal diameter (BPD), straight crown-rump length (CRL), femural length (FL), occipito-snout diameter (OSD), thoracic diameter (TD) and fetal heart rate (FHR) were measured by transrectal and/or transabdominal ultrasonography. All ewes were synchronized using progesterone sponge for 6 days. On the first day, they received PGF2 and on the last day received 400 IU of equine serum gonadotrophin (eCG). All of the parameters revealed significant correlation by increasing fetal age. Except for PD, for other values linear regression curve was illustrated. BPD (between 36 - 96 days) (R2 = 0.961), CRL (R2 = 0.935), FL (R2 = 0.950), OSD (R2 = 0.981), TD (R2 = 0.975) showed high correlation with fetal age (p < 0.001). Moderate correlation was calculated for FHR (p < 0.001, R2 = 0.883). Low correlations were assessed by measurement of GSD (p = 0.018, R2 = 0.318), BPD (between 96-138 days; p = 0.038, R2 = 0.29) and PD represented the significant non-linear correlation with age (p < 0.001), maximum correlation was assessed by measurement of mean placentome wall diameter. In conclusion, OSD was recommended as the best parameter for estimating of gestational age between days 36 - 109 in Baluchi sheep because of the lowest residuals, the highest correlation coefficient and wide period of availability for imaging in gestation.

Ultrasonographic estimation of gestation age and growth pattern of foetuses in second trimester of pregnancy by multiple growth parameters

Background and Aim- Fetal biometry rely on racial segment attributes, sustenance, hereditary qualities, and a lot more on ecological elements of a specific populace. Therefore, this study aimed to assess various fetal parameter and to establish a regression equation to predict the gestational age (GA) of pregnant women among the population of Western Maharashtra. Methodology- A descriptive, prospective study was conducted on 420 pregnant women in their second trimester (i.e. 14 to 27 weeks of gestation). Thirty women from each week of gestation were studied by ultrasonography for estimation of GA of the fetus. Various parameters such as biparietal diameter (BPD), femur length (FL), head circumference (HC), and abdominal circumference (AC) were studied and compared to the normal standards for GA, based on the initial sonogram from first trimester. Result-. Maximum (3.75 mm) and minimum (1.41 mm) increase in BPD was seen in 21-22 and 26 - 27 weeks, respectively. Maximum (4.50 mm) and minimum (0.42 mm) increase in FL was seen in 19 - 20 and 26 - 27 weeks, respectively.

Better Estimation of Spontaneous Preterm Birth Prediction Performance through Improved Gestational Age Dating.

The clinical management of pregnancy and spontaneous preterm birth (sPTB) relies on estimates of gestational age (GA). Our objective was to evaluate the effect of GA dating uncertainty on the observed performance of a validated proteomic biomarker risk predictor, and then to test the generalizability of that effect in a broader range of GA at blood draw. In a secondary analysis of a prospective clinical trial (PAPR; NCT01371019), we compared two GA dating categories: both ultrasound and dating by last menstrual period (LMP) (all subjects) and excluding dating by LMP (excluding LMP). The risk predictor’s performance was observed at the validated risk predictor threshold both in weeks 191/7–206/7 and extended to weeks 180/7–206/7. Strict blinding and independent statistical analyses were employed. The validated biomarker risk predictor showed greater observed sensitivity of 88% at 75% specificity (increases of 17% and 1%) in more reliably dated (excluding-LMP) subjects, relative to all subjects. Excluding dating by LMP significantly improved the sensitivity in weeks 191/7–206/7. In the broader blood draw window, the previously validated risk predictor threshold significantly stratified higher and lower risk of sPTB, and the risk predictor again showed significantly greater observed sensitivity in excluding-LMP subjects. These findings have implications for testing the performance of models aimed at predicting PTB.