Accurate Estimation Of Gestational Age Research Articles

Correlation of Estimated Gestational Age with the Anterior-Posterior Thigh Diameter and Other Parameters of Fetal Biometry

Background: Accurate gestational age estimation is vital for tracking pregnancy, identifying growth issues, and guiding clinical decisions. Including anterior-posterior thigh diameter (APTD) in fetal biometry enhances fetal health assessment. Correlating EGA with APTD and other biometry parameters is crucial for evaluating fetal growth and development. This study aimed to evaluate the correlation of estimated gestational age with the anterior-posterior thigh diameter and other parameters of fetal biometry. Methods: This cross-sectional study was conducted at the Department of Radiology and Imaging, Mymensingh Medical College & Hospital, Mymensingh, Bangladesh, from January 2010 to January 2012. A total of 250 healthy women between the 24th and 38th weeks of normal pregnancy were enrolled using a purposive sampling technique. Data analysis was performed using SPSS version 23.0. Results: More than one-third (34.0%) of participants were aged 21-25 years. The mean gestational age was 30.93 ± 4.32 weeks, and over half (56.4%) were primigravida. Significant positive correlations were found between fetal anterior-posterior thigh diameter and gestational age (r=1.0; p<0.001), bi-parietal diameter (r=0.856; p<0.001), head circumference (r=0.962; p<0.001), abdominal circumference (r=0.972; p<0.001), and femur length (r=0.948; p<0.001). Conclusion: The fetal anterior-posterior thigh diameter shows significant positive correlations with several parameters, including gestational age, biparietal diameter, head circumference, abdominal circumference, and femur length in this study.

Accuracy of prenatal and postnatal biomarkers for estimating gestational age: a systematic review and meta-analysis

Knowledge of gestational age (GA) is key in clinical management of individual obstetric patients, and critical to be able to calculate rates of preterm birth and small for GA at a population level. Currently, the gold standard for pregnancy dating is measurement of the fetal crown rump length at 11-14 weeks of gestation. However, this is not possible for women first presenting in later pregnancy, or in settings where routine ultrasound is not available. A reliable, cheap and easy to measure GA-dependent biomarker would provide an important breakthrough in estimating the age of pregnancy. Therefore, the aim of this study was to determine the accuracy of prenatal and postnatal biomarkers for estimating gestational age (GA). Systematic review prospectively registered with PROSPERO (CRD42020167727) and reported in accordance with the PRISMA-DTA. Medline, Embase, CINAHL, LILACS, and other databases were searched from inception until September 2023 for cohort or cross-sectional studies that reported on the accuracy of prenatal and postnatal biomarkers for estimating GA. In addition, we searched Google Scholar and screened proceedings of relevant conferences and reference lists of identified studies and relevant reviews. There were no language or date restrictions. Pooled coefficients of correlation and root mean square error (RMSE, average deviation in weeks between the GA estimated by the biomarker and that estimated by the gold standard method) were calculated. The risk of bias in each included study was also assessed. Thirty-nine studies fulfilled the inclusion criteria: 20 studies (2,050 women) assessed prenatal biomarkers (placental hormones, metabolomic profiles, proteomics, cell-free RNA transcripts, and exon-level gene expression), and 19 (1,738,652 newborns) assessed postnatal biomarkers (metabolomic profiles, DNA methylation profiles, and fetal haematological components). Among the prenatal biomarkers assessed, human chorionic gonadotrophin measured in maternal serum between 4 and 9 weeks of gestation showed the highest correlation with the reference standard GA, with a pooled coefficient of correlation of 0.88. Among the postnatal biomarkers assessed, metabolomic profiling from newborn blood spots provided the most accurate estimate of GA, with a pooled RMSE of 1.03 weeks across all GAs. It performed best for term infants with a slightly reduced accuracy for preterm or small for GA infants. The pooled RMSEs for metabolomic profiling and DNA methylation profile from cord blood samples were 1.57 and 1.60 weeks, respectively. We identified no antenatal biomarkers that accurately predict GA over a wide window of pregnancy. Postnatally, metabolomic profiling from newborn blood spot provides an accurate estimate of GA, however, as this is known only after birth it is not useful to guide antenatal care. Further prenatal studies are needed to identify biomarkers that can be used in isolation, as part of a biomarker panel, or in combination with other clinical methods to narrow prediction intervals of GA estimation. The research was funded by the Bill and Melinda Gates Foundation (INV-000368). ATP is supported by the Oxford Partnership Comprehensive Biomedical Research Centre with funding from the NIHR Biomedical Research Centre funding scheme. The views expressed are those of the authors and not necessarily those of the UK National Health Service, the NIHR, the Department of Health, or the Department of Biotechnology. The funders of this study had no role in study design, data collection, analysis or interpretation of the data, in writing the paper or the decision to submit for publication.

Problems with gestational age estimation by last menstrual period and ultrasound among late antenatal care attendant women in a low-resource setting in Africa, Sudan.

Accurate estimation of gestational age is essential to interpret and manage several maternal and perinatal indicators. Last menstrual period (LMP) and ultrasound are the two most common methods used for estimating gestational age. There are few published studies comparing the use of LMP and ultrasound in Sub-Saharan Africa to estimate gestational age and no studies on this topic in Sudan. A cross-sectional study was conducted in Gadarif Maternity Hospital in Sudanduring November through December 2022. Sociodemographic information was collected, and the date of the first day of each participant's LMP was recorded. Ultrasound examinations were performed (measuring crown-rump length in early pregnancy and biparietal diameter and femur length in late pregnancy) using a 3.5-MHz electronic convex sector probe. Bland-Altman analysis was performed. Four-hundred seventy-six pregnant women were enrolled. The median (interquartile range [IQR]) age and gravidity was 24.0 (20.0‒29.0) years and 2 (1‒4), respectively. There was a strong positive correlation between gestational age determined by LMP and ultrasound (r = 0.921, P < 0.001). The mean gestational age estimate according to LMP was higher than that determined by ultrasound, with a difference, on average, of 0.01 week (95% confidence interval [CI]: - 0.05, 0.07). Bland-Altman analysis showed the limits of agreement varied from - 1.36 to 1.38 weeks. A linear regression analysis showed proportional bias. The coefficient of difference of the mean was equal to 0.26 (95% CI: 0.01, 0.03, P < 0.001). Based on our results, there was a bias in LMP-based gestational age estimates when compared with the reproducible method (ultrasound).

Estimating gestational age using the anthropometric measurements of newborns in North Shewa Zone public hospitals, Oromia, Ethiopia.

The accurate estimation of gestational age is crucial in identifying prematurity and other health problems in newborns and in providing appropriate perinatal care. Although there are numerous methods for measuring gestational age, they are not always applicable. During these situations, it becomes challenging to ascertain whether a baby has been born prematurely or not. Therefore, this study aims to estimate gestational age by utilizing newborn anthropometric parameters. The objective of this study is to estimate the gestational age of newborns in public hospitals located in the North Shewa Zone of the Oromia Region in Ethiopia, by using anthropometric parameters. A cross-sectional study was conducted at a facility from February 2022 to April 2022, using an interview-based questionnaire and anthropometric measurements. The anthropometric parameters that were measured include foot length (FL), mid-upper arm circumference (MUAC), and chest and head circumference (CHC). The study's sample size had a total of 420 participants. The data were cleaned, edited, manually checked for completeness, and entered into Epi-data version 3.1. Subsequently, the data were transferred into SPSS for analysis. The data were analyzed using descriptive analysis, simple linear regression, and multiple linear regressions. Finally, the data were presented using statements and tables. There is a significant and positive correlation between anthropometric parameters, including head circumference (r: 0.483), MUAC (r: 0.481), foot length (r: 0.457), and chest circumference (r: 0.482) with gestational age. All anthropometric parameters demonstrated positive and significant estimates of gestational age. The combination of the four measurements yielded the strongest estimate of gestational age. Gestational age can be calculated by the formula: Gestational age (Weeks) = 9.78 + 0.209*CHC + 0.607*MUAC + 0.727*FL + 0.322*HC. Gestational age can be measured using head circumference, mid-upper arm circumference, foot length, and chest circumference. Utilizing the four anthropometric parameters in combination exhibits greater efficacy in estimating gestational age than using them individually. Therefore, it is recommended to use these alternative approaches when standard methods are not applicable.

Comparative Study between Crown-Rump Length and Fetal Volume in First Trimester for Accurate Estimation of Gestational Age

Comparative Study between Crown-Rump Length and Fetal Volume in First Trimester for Accurate Estimation of Gestational Age

A new formula for estimating gestational age by crown-rump length

The accurate estimation of gestational age by ultrasound is crucial in prenatal care for the monitoring of fetal growth and development. As changes in maternal childbearing age, body habitus, and ultrasound technology occur, previously published formulas may not be accurate for today's population. This study aimed to develop new formulas for calculating the gestational age based on a first-trimester ultrasound scan and to compare the new formulas with preexisting formulas. This study was a single-center, retrospective observational study that included pregnancies conceived using in vitro fertilization. The pregnancies had known dates of embryo transfer and multiple standard ultrasound examinations in the first trimester of pregnancy. Pregnancies ending with a miscarriage or termination in the first trimester of pregnancy were excluded. A polynomial regression analysis was performed to determine the optimal model that represented the relationship between gestational age and crown-rump length. The models were evaluated using systematic error, random error, absolute difference of the calculated gestational age and actual gestational age, and proportion of estimation within 0 and 2 days of the known gestational age. The optimal model was chosen and compared with preexisting formulas. Overall, 1436 ultrasound results were included in the analysis. The analysis produced 3 models: linear, cubic, and quadratic models with correlation coefficients of 0.968, 0.989, and 0.991, respectively. The cubic formula was superior to the linear and quadratic formulas concerning systematic error, random error, absolute difference, and proportion of estimation within 0 and 2 days. The new formula had a lower systematic error, random error, and mean absolute difference (0.06%, 2.43%, and 0.97 days, respectively) and the highest proportion of estimation within 0 and 2 days (37.4% and 93.5%, respectively) than previously published formulas. The formula proposed in this study followed a cubic model and seemed to be able to more accurately estimate gestational age in the first trimester of pregnancy based on crown-rump length compared with previously published formulas.

Machine learning for accurate estimation of fetal gestational age based on ultrasound images

Accurate estimation of gestational age is an essential component of good obstetric care and informs clinical decision-making throughout pregnancy. As the date of the last menstrual period is often unknown or uncertain, ultrasound measurement of fetal size is currently the best method for estimating gestational age. The calculation assumes an average fetal size at each gestational age. The method is accurate in the first trimester, but less so in the second and third trimesters as growth deviates from the average and variation in fetal size increases. Consequently, fetal ultrasound late in pregnancy has a wide margin of error of at least ±2 weeks’ gestation. Here, we utilise state-of-the-art machine learning methods to estimate gestational age using only image analysis of standard ultrasound planes, without any measurement information. The machine learning model is based on ultrasound images from two independent datasets: one for training and internal validation, and another for external validation. During validation, the model was blinded to the ground truth of gestational age (based on a reliable last menstrual period date and confirmatory first-trimester fetal crown rump length). We show that this approach compensates for increases in size variation and is even accurate in cases of intrauterine growth restriction. Our best machine-learning based model estimates gestational age with a mean absolute error of 3.0 (95% CI, 2.9–3.2) and 4.3 (95% CI, 4.1–4.5) days in the second and third trimesters, respectively, which outperforms current ultrasound-based clinical biometry at these gestational ages. Our method for dating the pregnancy in the second and third trimesters is, therefore, more accurate than published methods.

Estimation of gestational age in third trimester using mean fetal kidney length in comparison with fetal biometry

Background: Accurate estimation of gestational age (GA) is crucial for providing quality health care and need for intervention in inadvertent conditions such as fetal growth restriction. Various parameters are used for measuring GA, but none of them are valid in 3rd trimester. Recently some studies focused on Fetal kidney length (FKL) measurement for correct estimation of GA. This study focused on the validation of accuracy of FKL.Objective: Estimation of gestational age in third trimester using mean foetal kidney length. Comparing the mean FKL with Biparietal diameter (BPD), Head circumference (HC), Abdominal circumference (AC), and Femur length (FL).Methodology: Ultrasonography was done among 150 healthy antenatal with known Last menstrual period (LMP) in 3rd trimester to measure FKL, BPD, HC, AC, and FL.Results: In the present study, 51.3% were of primi paras. With increased GA, FKL also increased. Regarding correlation, FKL had very strong correlation with GA than other indices. Conclusion: FKL was the better parameter in estimating GA in 3rd trimester.

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.

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.

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.

Ultrasonographic Evaluation of Fetal Sacral Length: Correlation with Gestational Age

Introduction: Obstetricians need an accurate estimate of gestational age to decide when to terminate the pregnancy and how to deliver the baby. When unreliable menstrual history cannot be used to determine gestational age, ultrasonography comes in handy. Ultrasonography has been used to determine gestational age using a variety of parameters. However, all of these parameters are only reliable in the first and second trimesters of pregnancy. They become less reliable as the pregnancy progresses, due to a variety of factors, with a maximum variability of about 3 to 3.5 weeks in the third trimester. Methods: A total of 200 pregnant women participated in this prospective observational study at the Department of Radiology and Imaging, Bangladesh Institute of Research and Rehabilitation in Diabetes, Endocrine, and Metabolic Disorders. The research was carried out between January 2001 and December 2002. Result: The participants' average age was 24.54 years. Only 3% of the participants were in the oldest age range of 36-40 years, with 38 percent of the participants being between the ages of 21 and 25. The average height of the participants was 150-154 cm in 52 percent of the cases. The mean SD height and weight were 152.40±3.44 cm and 54.80±4.45 kg, respectively. There is a strong positive relationship between fetal sacral length and gestational age, according to BPD and FL. The relationship between gestational age and fetal sacral length was demonstrated to be statistically significant. There was no statistically significant relationship between fetal sacral length and maternal height. Conclusion: Fetal sacral length is well related to gestational age. If sacral length is measured accurately with a high-resolution ultrasound scanner, it can be used reliably as an additional parameter throughout pregnancy in conjunction with other established parameters.

Readiness to Provide Antenatal Corticosteroids for Threatened Preterm Birth in Public Health Facilities in Northern India.

In 2014, the Government of India (GOI) released operational guidelines on the use of antenatal corticosteroids (ACS) in preterm labor. However, without ensuring the quality of childbirth and newborn care at facilities, the use of ACS in low- and middle-income countries is potentially harmful. This study assessed the readiness to provide ACS at primary and secondary care public health facilities in northern India. A cross-sectional study was conducted in 37 public health facilities in 2 districts of Haryana, India. Facility processes and program implementation for ACS delivery were assessed using pretested study tools developed from the World Health Organization (WHO) quality of care standards and WHO guidelines for threatened preterm birth. Key gaps in public health facilities' process of care to provide ACS for threatened preterm birth were identified, particularly concerning evidence-based practices, competent workforce, and actionable health information system. Emphasis on accurate gestational age estimation, quality of childbirth care, and quality of preterm care were inadequate. Shortage of trained staff was widespread, and a disconnect was found between knowledge and attitudes regarding ACS use. ACS administration was provided only at district or subdistrict hospitals, and these facilities did not uniformly record ACS-specific indicators. All levels lacked a comprehensive protocol and job aids for identifying and managing threatened preterm birth. ACS operational guidelines were not widely disseminated or uniformly implemented. Facilities require strengthened supervision and standardization of threatened preterm birth care. Facilities need greater readiness to meet required conditions for ACS use. Increasing uptake of a single intervention without supporting it with adequate quality of maternal and newborn care will jeopardize improvement in preterm birth outcomes. We recommend updating and expanding the existing GOI ACS operational guidelines to include specific actions for the safe and effective use of ACS in line with recent scientific evidence.

Using AMANHI-ACT cohorts for external validation of Iowa new-born metabolic profiles based models for postnatal gestational age estimation.

BackgroundGlobally, 15 million infants are born preterm and another 23.2 million infants are born small for gestational age (SGA). Determining burden of preterm and SGA births, is essential for effective planning, modification of health policies and targeting interventions for reducing these outcomes for which accurate estimation of gestational age (GA) is crucial. Early pregnancy ultrasound measurements, last menstrual period and post-natal neonatal examinations have proven to be not feasible or inaccurate. Proposed algorithms for GA estimation in western populations, based on routine new-born screening, though promising, lack validation in developing country settings. We evaluated the hypothesis that models developed in USA, also predicted GA in cohorts of South Asia (575) and Sub-Saharan Africa (736) with same precision.MethodsDried heel prick blood spots collected 24-72 hours after birth from 1311 new-borns, were analysed for standard metabolic screen. Regression algorithm based, GA estimates were computed from metabolic data and compared to first trimester ultrasound validated, GA estimates (gold standard).ResultsOverall Algorithm (metabolites + birthweight) estimated GA to within an average deviation of 1.5 weeks. The estimated GA was within the gold standard estimate by 1 and 2 weeks for 70.5% and 90.1% new-borns respectively. Inclusion of birthweight in the metabolites model improved discriminatory ability of this method, and showed promise in identifying preterm births. Receiver operating characteristic (ROC) curve analysis estimated an area under curve of 0.86 (conservative bootstrap 95% confidence interval (CI) = 0.83 to 0.89); P < 0.001) and Youden Index of 0.58 (95% CI = 0.51 to 0.64) with a corresponding sensitivity of 80.7% and specificity of 77.6%.ConclusionMetabolic gestational age dating offers a novel means for accurate population-level gestational age estimates in LMIC settings and help preterm birth surveillance initiatives. Further research should focus on use of machine learning and newer analytic methods broader than conventional metabolic screen analytes, enabling incorporation of region-specific analytes and cord blood metabolic profiles models predicting gestational age accurately.

Placental thickness and Transcerebellar diameter for accurate estimation of gestational age in the second trimester (A cross sectional study)

Objective: To assess the accuracy of combined measurementof placental thickness and transcerebellar diameter in estimation of fetal gestational age in second trimester.Patients and Methods: A cross sectional study was conducted at ultrasound unit, department of obstetrics and gynecology,Ain shams University Maternity Hospital in the period betweenJanuary 2020 and March 2020.The population studied included161 pregnant ladies at 14 to 26 weeks.Trans-abdominal ultrasound (Samsung H60, Convex Pro = CV1 = 8MHz - probe 4.9MHz) was used to asses placental thickness and transcerebellardiameter.Results: Our results showed that there is positive correlationbetween Placental thickness and gestational age r= 0.44 whichis highly significant (P value < 0.001). Also highly statisticallysignificant positive correlation between TCD and G.A (P value < 0.001) r= 0.92. Statistical analysis of our results showedthat trans-cerebellar diameter was more accurate than placentalthickness for accurate estimation of gestational age with almostperfect agreement (0.91) between gestational age by last menstrual period and gestational age by trans-cerebellar diameter.Conclusion: Client’s aged 32.8 ±3.4. More than half had primary infertility with mean duration of 4.6 ± 2.4. Female factorinfertility was the commonest cause of infertility. The pregnancy rate per embryo transfer was 36.4%, miscarriage rate was9.1%, while the live rate was 27.3%. The mean VAS scores at1hour, 6 hours, 24 hours and at embryo transfer were 7.1 ± 2.8,4.6 ±1.4, 2.8 ±1.2 and 1.0 ± 0.9 respectively. The mean Likertscore was 2.4 ± 0.9.Conclusion: Both placental thickness and TCD are useful fetalbiometric parameters that can be used for assessment of gestational age. Although placental thickness is positively correlatedto G.A, it is not as accurate as TCD. Unfortunately, combineduse of placental thickness and TCD is not superior to TCDalone in accurate estimation of gestational age.

Comparison of first trimester dating methods for gestational age estimation and their implication on preterm birth classification in a North Indian cohort

BackgroundDifferent formulae have been developed globally to estimate gestational age (GA) by ultrasonography in the first trimester of pregnancy. In this study, we develop an Indian population-specific dating formula and compare its performance with published formulae. Finally, we evaluate the implications of the choice of dating method on preterm birth (PTB) rate. This study’s data was from GARBH-Ini, an ongoing pregnancy cohort of North Indian women to study PTB.MethodsComparisons between ultrasonography-Hadlock and last menstrual period (LMP) based dating methods were made by studying the distribution of their differences by Bland-Altman analysis. Using data-driven approaches, we removed data outliers more efficiently than by applying clinical parameters. We applied advanced machine learning algorithms to identify relevant features for GA estimation and developed an Indian population-specific formula (Garbhini-GA1) for the first trimester. PTB rates of Garbhini-GA1 and other formulae were compared by estimating sensitivity and accuracy.ResultsPerformance of Garbhini-GA1 formula, a non-linear function of crown-rump length (CRL), was equivalent to published formulae for estimation of first trimester GA (LoA, − 0.46,0.96 weeks). We found that CRL was the most crucial parameter in estimating GA and no other clinical or socioeconomic covariates contributed to GA estimation. The estimated PTB rate across all the formulae including LMP ranged 11.27–16.50% with Garbhini-GA1 estimating the least rate with highest sensitivity and accuracy. While the LMP-based method overestimated GA by 3 days compared to USG-Hadlock formula; at an individual level, these methods had less than 50% agreement in the classification of PTB.ConclusionsAn accurate estimation of GA is crucial for the management of PTB. Garbhini-GA1, the first such formula developed in an Indian setting, estimates PTB rates with higher accuracy, especially when compared to commonly used Hadlock formula. Our results reinforce the need to develop population-specific gestational age formulae.

Evaluation of ultrasonographic fetal kidney length for gestational age detection in late second and third trimesters

Accurate estimation of gestational age is necessary to obtain materials for different tests as well as to interpret the results of these tests.Unfortunately sometimes calculation of EDD based on LMP becomes very difficult when (a) The menstrual cycle is irregular; (b) Patient fails to remember LMP or reports inaccurately (c) Pregnancy occurs during lactational amenorrhoea &amp; (d) if patient have bleeding in early pregnancy. After 24 weeks the symphysio-fundal height in cm. approximates to the number of weeks up to 36 weeks of gestation. But a number of factors influence the measurement including multiple gestation, IUGR, diabetic pregnancy, maternal size, variation in fetal lie &amp; engagement as well as inter &amp; intra observer measurement variation.Ultrasonic measurement of fetal biometry (CRL, BPD, FL) are considered to be reliable when they are performed in first &amp; early 2nd trimester (&lt;24 weeks). In this study, we aimed to evaluate the accuracy of ultrasonographic fetal kidney length measurement as a new parameter for estimation of gestational age in late second and third trimester in correlation to other commenly used parameters as, BPD, FL, AC. This study was conducted on 122 pregnant women attending antenatal care clinics of Obstetrics and Gynecology department Soliman Fakeeh Hospital, KSA. All were in the late second and third trimester (between 24-40 weeks) of gestation. Cases included in the study were divided into four gestational age groups with four weeks interval. The length of the fetal kidney was measured. The mean gestational age was calculated on the bases of biparietal diameter (BPD).femur length (FL) and abdominal circumference (AC). The fetal kidney measurements were obtained by the same sonographer to avoid interobserver variation using (GE machine E8) and were compared with gestational age using statistical analysis No statistically significant differences were found between the right and the left renal measurements in cases in which the two kidneys were imaged In this study, during the second and third trimester the mean kidney length showed gradual rate of increase. the mean kidney length was found to be 30.52.1 mm at mean gestational age of 26weeks and became at the mean gestational age of34 weeks, 40.4103 mm(:(±1.98) and at mean gestational age of 38 week it measured44.41mm((±2.1). In addition, we found a positive correlation between kidney length and gestational age. We suggested regression Formula to calculate it. Conclusion: Throughout this study, we can conclude that Fetal kidney length could be used with accuracy in the late second and third trimester especially in women who are uncertain of date of LMP and are booked late for ANC.however its accuracy is decreased when we use it in late third trimester.Other ultrasonographic parameters used for estimation of the gestational age as BPD ,AC are less satisfactory ,when compared with femur length and kidney length.

INNOVATE GESTATIONAL AGE ESTIMATION MODEL FOR IRAQI FETUSES BASED ON ULTRASOUND IMAGES MEASUREMENTS

Imaging by Ultrasound (US) is an accurate and useful modality for the assessment of gestational age (GA), estimation fetal weight, and monitoring the fetal growth during pregnancy, is a routine part of prenatal care, and that can greatly impact obstetric management. Estimation of GA is important in obstetric care, making appropriate management decisions requires accurate appraisal of GA. Accurate GA estimation may assist obstetricians in appropriately counseling women who are at risk of a preterm delivery about likely neonatal outcomes, and it is essential in the evaluation of the fetal growth and detection of intrauterine growth restriction. There are many formulas are used to estimate fetal GA in the world, but it's not specify for Iraqi population and leading to some error in GA estimation results, so the objective of this study is to innovate GA estimation model for Iraqi people. This study was performed in the department of Obstetrics and Gynecology in Al- Yarmouk Teaching Hospital and AL- Alawiya Teaching Hospital in Baghdad, Iraq, during 2019 on 200 pregnant women of singleton and normal pregnancies, fetal GA (20-40) weeks (W). The obtained dataset (fetal biometry), were utilized to create GA estimation model in Iraq using IBM SPSS Version 23 software package (IBM^® Software). The statistical analysis of proposed GA model showed, the correlation (R) of model is 0.987 it is very high value and this is a good result to obtain the best regression model. as well as the Std error of Estimation was 0.61095 this is very small value and indicate the best result. The significant of model P=0.000 That means the model, as a whole, is a significant fit to the data (because P &lt; 0.05).

The Role of Fetal Kidney Length and Fetal Transverse Diameter of Heart in Prediction of Gestational Age

Objective: Currently there is no single ultrasonological parameter for accurate estimation of gestational age in third trimester. The present study is undertaken to validate the fetal kidney length and fetal transverse diameter of heart measurement as a measurement of fetal growth with less variability. Materials &amp; Methods: It is a cohort study conducted in Department of Obstetrics and Gynaecology, NEIGRIHMS from 2015 to 2016. 224 women with singleton pregnancies and sure of LMP were enrolled. Each woman underwent minimum three ultrasonographic measurements- at first trimester for gestational age by CRL, at second trimester with fetal conventional biometry, at third trimester with Fetal kidney length, transverse diameter of heart and fetal conventional biometric parameters and analysed with SPSS Version22. Results: The gestational age with CRL was within three days of the menstrual age. In second trimester, conventional parameter (BPD,HC,AC,FL) were better parameters. Conventional parameter did not correspond to gestational age calculated from LMP. (BPD, R2= 0.4819, HC R2- 0.507, AC R2- 0.5175, FL R2-0.5243, Combined Conventional parameter R2- 0.5888). Fetal kidney length (R2-0.8356) and transverse diameter of heart (R2-0.8795) better correlated with gestational age. Conclusion: Kidney length and transverse diameter of heart are better predictors of gestational age in third trimester.

ISUOG Practice Guidelines: ultrasound assessment of fetal biometry and growth.

INTRODUCTION These Guidelines aim to describe appropriate assessment of fetal biometry and diagnosis of fetal growth disorders. These disorders consist mainly of fetal growth restriction (FGR), also referred to as intrauterine growth restriction (IUGR) and often associated with small‐for‐gestational age (SGA), and large‐for‐gestational age (LGA), which may lead to fetal macrosomia; both have been associated with a variety of adverse maternal and perinatal outcomes. Screening for, and adequate management of, fetal growth abnormalities are essential components of antenatal care, and fetal ultrasound plays a key role in assessment of these conditions. The fetal biometric parameters measured most commonly are biparietal diameter (BPD), head circumference (HC), abdominal circumference (AC) and femur diaphysis length (FL). These biometric measurements can be used to estimate fetal weight (EFW) using various different formulae1. It is important to differentiate between the concept of fetal size at a given timepoint and fetal growth, the latter being a dynamic process, the assessment of which requires at least two ultrasound scans separated in time. Maternal history and symptoms, amniotic fluid assessment and Doppler velocimetry can provide additional information that may be used to identify fetuses at risk of adverse pregnancy outcome. Accurate estimation of gestational age is a prerequisite for determining whether fetal size is appropriate‐for‐gestational age (AGA). Except for pregnancies arising from assisted reproductive technology, the date of conception cannot be determined precisely. Clinically, most pregnancies are dated by the last menstrual period, though this may sometimes be uncertain or unreliable. Therefore, dating pregnancies by early ultrasound examination at 8–14 weeks, based on measurement of the fetal crown–rump length (CRL), appears to be the most reliable method to establish gestational age. Once the CRL exceeds 84 mm, HC should be used for pregnancy dating2–4. HC, with or without FL, can be used for estimation of gestational age from the mid‐trimester if a first‐trimester scan is not available and the menstrual history is unreliable. When the expected delivery date has been established by an accurate early scan, subsequent scans should not be used to recalculate the gestational age1. Serial scans can be used to determine if interval growth has been normal. In these Guidelines, we assume that the gestational age is known and has been determined as described above, the pregnancy is singleton and the fetal anatomy is normal. Details of the grades of recommendation used in these Guidelines are given in Appendix 1. Reporting of levels of evidence is not applicable to these Guidelines.