“A NOVEL ATTEMPT IN ESTIMATION OF FETAL WEIGHT USING NEW SOFT TISSUE MEASUREMENTS”

2021 ◽  
pp. 1-3
Author(s):  
Sathyan Gnanasigamani ◽  
Sudhakar Vadivel ◽  
Bala Subramaniam ◽  
Sakthivel Raja Ganesan ◽  
Pradeebaa Thiyagarajan ◽  
...  
Keyword(s):  
Birth Weight ◽  
Soft Tissue ◽  
Strong Predictor ◽  
Three Dimensional ◽  
Fetal Weight ◽  
Ultrasound Measurement ◽  
Accurate Estimation ◽  
Tissue Thickness ◽  
Third Trimester ◽  
Soft Tissue Thickness

Background: The Accurate estimation of fetal weight is important in modern obstetrics. Currently, Hadlock's formula is used widely for fetal weight estimation, which includes BPD, AC, FL and HC. The correct plane of measurement of various standard parameters is difcult to obtain especially in third trimester. Hence soft tissue thicknesses of the fetus are tested for correlation with birth weight in this study. Materials & Methods: A prospective observational study conducted among 90 pregnant females referred for Ultrasound examination in the third trimester with an interval from the ultrasound scan to delivery of ≤7 days from 2019 to 2020. Results: The measurements of abdominal, fetal mid-thigh and mid-arm soft tissue thicknesses correlated well with birth weight in a high statistically signicant positive linear relationship. A new regression model developed out of the soft tissue thicknesses(FASTT, FMASTT, FTSTT) correlates better than the Hadlock's model and Sujitkumar Hiwale et al model (For Indian population) based on BPD, HC, AC and FL Conclusion: Ultrasound measurement of soft tissue thickness may prove to be a strong predictor of fetal weight essential for sonographic assessment of pregnancy. They are easy and simple hence fetal soft tissue thickness measurements, both two- and three-dimensional, may prove to be a diagnostic parameter that has as small an error rate as possible, is quick to use and reproducible by different examiners

scholarly journals Evaluation of Fetal Mid-Thigh Soft Tissue Thickness and Femur Length for Estimation of Fetal Birth Weight

2020 ◽  
Vol 3 (2) ◽  
pp. 01-10
Author(s):  
Nareman Elhamamy
Keyword(s):  
Birth Weight ◽  
Soft Tissue ◽  
Fetal Weight ◽  
Tissue Thickness ◽  
Femur Length ◽  
Soft Tissue Thickness ◽  
Percent Difference ◽  
Fetal Birth Weight ◽  
Kappa Value ◽  
The Difference

Accurate calculation of fetal weight relies on two equally important factors: the use of a formula with strong intrinsic properties, and the use of sonographic biometric parameters that are not susceptible to errors in measurement. From a statistical perspective, the inclusion of multiple variables in a model improves multicollinearity chances and decreases each measurement's internal error. Precisely predicting estimated fetal weight during childbirth may have a significant impact on successful obstetric management, especially in the case of suspected macrosomia or low birth weight. Macrosomic fetuses can cause maternal and neonatal complications during childbirth, and low-born fetuses are at increased risk for perinatal morbidity and mortality. The main aim of the study was to assess the accuracy of measurement of mid-thigh soft tissue thickness and femur length, in estimation of expected fetal birth weight The study was conducted during the period January 2017 to August 2019, at Tanta University hospitals, Obstetrics & Gynecology department. 65 pregnant ladies at term (between 37-40weeks) were included in the study. Results: Mean difference between fetal weight by Hadlock formulae and actual fetal weight is -10.88g; percent difference is (0.32%). The difference statistically insignificant p>0.05. Mean difference between fetal weight by Scioscia’s formulae and Actual fetal weight is 2.83; the percent difference is (0.08%). The difference statistically insignificant p>0.05. Good agreement between Hadlock formulae and Actual Fetal Weight Kappa value (0.73).Also shows moderate agreement between Scioscia’s formulae and Actual Fetal Weight Kappa value (0.52). area under curve Hadlock formulae (0.79), Scioscia’s formulae (0.78) for detecting fetal weight ≥3500gm among pregnant women at 39-40 weeks of gestation. Conclusion: The mid-thigh soft tissue thickness and femur length can be used in estimation of expected fetal birth weight like as other sonographic parameters. The validity of Scioscia's formulae is not better than Hadlock formulae in detection of fetal weight less than 3500 gm. The validity of both formulae Scioscia's and Hadlock in detection of fetal weight more than 3500 gm. Reduced and cannot be dependable in extremes of weight.

scholarly journals Estimation of fetal weight by measurement of fetal thigh soft-tissue thickness in the late third trimester

2008 ◽  
Vol 31 (3) ◽  
pp. 314-320 ◽  
Author(s):  
M. Scioscia ◽  
F. Scioscia ◽  
A. Vimercati ◽  
F. Caradonna ◽  
C. Nardelli ◽  
...  
Keyword(s):  
Soft Tissue ◽  
Fetal Weight ◽  
Tissue Thickness ◽  
Third Trimester ◽  
Soft Tissue Thickness

Antenatal ultrasound measurement of fetal-thigh soft-tissue thickness as a predictor of fetal birth weight

2021 ◽  
Vol 34 (2) ◽  
pp. 724
Author(s):  
MohammedF. M. Attalla ◽  
AymanE Solyman ◽  
Sayed AbdelMoneim ◽  
WaleedA Mousa ◽  
AlaaM Abdelgied
Keyword(s):  
Birth Weight ◽  
Soft Tissue ◽  
Ultrasound Measurement ◽  
Tissue Thickness ◽  
Antenatal Ultrasound ◽  
Soft Tissue Thickness ◽  
Fetal Birth Weight

scholarly journals Better Predictor of Fetal Weight: Mid-Thigh Soft- Tissue Thickness Versus Hadlock’s Method – A Prospective Observational Study

2020 ◽  
Vol 6 (2) ◽  
pp. 25-30
Author(s):  
K M Kibballi Madhukeshwar Adarsh ◽  
Prakash Aswathi ◽  
H Pavithra ◽  
Hassan Hadi ◽  
Sunny Jomon ◽  
...  
Keyword(s):  
Soft Tissue ◽  
Observational Study ◽  
Prospective Observational Study ◽  
Fetal Weight ◽  
Tissue Thickness ◽  
Soft Tissue Thickness

Fetal weight estimation by automated three-dimensional limb volume model in late third trimester compared to two-dimensional model: a cross-sectional prospective observational study

2021 ◽  
Author(s):  
Xining Wu ◽  
Zihan Niu ◽  
Zhonghui Xu ◽  
Yuxin Jiang ◽  
Yixiu Zhang ◽  
...  
Keyword(s):  
Birth Weight ◽  
3D Model ◽  
Three Dimensional ◽  
Fetal Weight ◽  
Percentage Error ◽  
Limb Volume ◽  
Third Trimester ◽  
Volume Model ◽  
Estimated Error ◽  
2D Model

Abstract Background: Accurate estimation of fetal weight is important for prenatal care and for detection of fetal growth abnormalities. Prediction of fetal weight entails the indirect measurement of fetal biometry by ultrasound that is then introduced into formulae to calculate the estimated fetal weight. The aim of our study was to evaluate the accuracy of the automated three-dimensional(3D) fractional limb volume model to predict fetal weight in the third trimester.Methods: Prospective 2D and 3D ultrasonography were performed among women with singleton pregnancies 7 days before delivery to obtain 2D data, including fetal biparietal diameter, abdominal circumference and femur length, as well as 3D data, including the fractional arm volume (AVol) and fractional thigh volume (TVol). The fetal weight was estimated using the 2D model and the 3D fractional limb volume model respectively. Percentage error = (estimated fetal weight - actual birth weight) ÷ actual birth weight × 100. Systematic errors (accuracy) were evaluated as the mean percentage error (MPE). Random errors (precision) were calculated as±1 SD of percentage error.Results: Ultrasound examination was performed on 56 fetuses at 39.6 ± 1.4 weeks gestation. The average birth weight of the newborns was 3393 ± 530 g. The average fetal weight estimated by the 2D model was 3478 ± 467 g, and the MPE was 3.2 ± 8.9. The average fetal weights estimated by AVol and TVol of the 3D model were 3268 ± 467 g and 3250 ± 485 g, respectively, and the MPEs were -3.3 ± 6.6 and -3.9 ± 6.1, respectively. For the 3D TVol model, the proportion of fetuses with estimated error ≤ 5% was significantly higher than that of the 2D model (55.4% vs. 33.9%, p < 0.05). For fetuses with a birth weight < 3500 g, the accuracy of the AVol and TVol models were better than the 2D model (-0.8 vs. 7.0 and -2.8 vs. 7.0, both p < 0.05). Moreover, for these fetus, the proportions of estimated error ≤ 5% of the AVol and TVol models were 58.1% and 64.5%, respectively, significantly higher than that of the 2D model (19.4%) (both p < 0.05). The consistency of different examiners measuring fetal AVol and TVol were satisfactory,with the intraclass correlation coefficients of 0.921 and 0.963, respectively.Conclusion: In this cohort,the automated 3D fractional limb volume model improves the accuracy of weight estimation in most third-trimester fetuses. In particular, the 3D model estimation accuracy for fetuses with weight < 3500 g is significantly higher than that of the traditional 2D model.

scholarly journals In-Office Guided Implant Placement for Prosthetically Driven Implant Surgery

2017 ◽  
Vol 10 (3) ◽  
pp. 246-254 ◽  
Author(s):  
Daryoush Karami ◽  
Hamid Reza Alborzinia ◽  
Reza Amid ◽  
Mahdi Kadkhodazadeh ◽  
Navid Yousefi ◽  
...  
Keyword(s):  
Soft Tissue ◽  
Direct Observation ◽  
Three Dimensional ◽  
Hard Tissue ◽  
Tissue Thickness ◽  
Computed Tomographic ◽  
Implant Placement ◽  
Soft Tissue Thickness ◽  
Ct Data ◽  
The Cost

Application of surgical stents for implant placement via guided flapless surgery is increasing. However, high cost, need for some professional machines, and not taking into account the soft-tissue parameters have limited their application. We sought to design and introduce a technique named in-office guided implant placement (iGIP) to decrease the cost by using available devices in office and enhance the applicability of surgical stents. A customized surgical stent was fabricated based on prosthetic, soft- and hard-tissue parameters by taking into account the amount of available bone (using the computed tomographic [CT] data), soft-tissue thickness and contour (using a composite-covered radiographic stent), and position of the final crown (by diagnostic cast wax up and marking the final crown position with composite). The efficacy of iGIP, in terms of the accuracy of the three-dimensional position of the implant placed in the study cast and in patient's mouth, was confirmed by direct observation and postoperative CT. The iGIP can enhance implant placement in the prosthetically desired position in various types of edentulism. Using this technique minimizes the risk of unwanted consequences, as the soft-tissue thickness and contour are taken into account when fabricating a surgical stent.

Fetal mid-thigh soft-tissue thickness: a novel method for fetal weight estimation

2014 ◽  
Vol 290 (6) ◽  
pp. 1101-1108 ◽  
Author(s):  
Wessam Abuelghar ◽  
Ahmed Khairy ◽  
Gasser El Bishry ◽  
Mohamed Ellaithy ◽  
Taha Abd-Elhamid
Keyword(s):  
Soft Tissue ◽  
Fetal Weight ◽  
Weight Estimation ◽  
Tissue Thickness ◽  
Fetal Weight Estimation ◽  
Soft Tissue Thickness ◽  
Novel Method

scholarly journals Fetal weight estimation by automated three-dimensional limb volume model in late third trimester compared to two-dimensional model: a cross-sectional prospective observational study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xining Wu ◽  
Zihan Niu ◽  
Zhonghui Xu ◽  
Yuxin Jiang ◽  
Yixiu Zhang ◽  
...  
Keyword(s):  
Birth Weight ◽  
Three Dimensional ◽  
Fetal Weight ◽  
Percentage Error ◽  
Weight Estimation ◽  
Limb Volume ◽  
Third Trimester ◽  
Volume Model ◽  
Estimated Error ◽  
2D Model

Abstract Background Accurate estimation of fetal weight is important for prenatal care and for detection of fetal growth abnormalities. Prediction of fetal weight entails the indirect measurement of fetal biometry by ultrasound that is then introduced into formulae to calculate the estimated fetal weight. The aim of our study was to evaluate the accuracy of fetal weight estimation of Chinese fetuses in the third trimester using an automated three-dimensional (3D) fractional limb volume model, and to compare this model with the traditional two-dimensional (2D) model. Methods Prospective 2D and 3D ultrasonography were performed among women with singleton pregnancies 7 days before delivery to obtain 2D data, including fetal biparietal diameter, abdominal circumference and femur length, as well as 3D data, including the fractional arm volume (AVol) and fractional thigh volume (TVol). The fetal weight was estimated using the 2D model and the 3D fractional limb volume model respectively. Percentage error was defined as (estimated fetal weight - actual birth weight) divided by actual birth weight and multiplied by 100. Systematic errors (accuracy) were evaluated as the mean percentage error (MPE). Random errors (precision) were calculated as ±1 SD of percentage error. The intraclass correlation coefficient (ICC) was used to analyze the inter-observer reliability of the 3D ultrasound measurements of fractional limb volume. Results Ultrasound examination was performed on 56 fetuses at 39.6 ± 1.4 weeks’ gestation. The average birth weight of the newborns was 3393 ± 530 g. The average fetal weight estimated by the 2D model was 3478 ± 467 g, and the MPE was 3.2 ± 8.9. The average fetal weights estimated by AVol and TVol of the 3D model were 3268 ± 467 g and 3250 ± 485 g, respectively, and the MPEs were − 3.3 ± 6.6 and − 3.9 ± 6.1, respectively. For the 3D TVol model, the proportion of fetuses with estimated error ≤ 5% was significantly higher than that of the 2D model (55.4% vs. 33.9%, p < 0.05). For fetuses with a birth weight < 3500 g, the accuracy of the AVol and TVol models were better than the 2D model (− 0.8 vs. 7.0 and − 2.8 vs. 7.0, both p < 0.05). Moreover, for these fetuses, the proportions of estimated error ≤ 5% of the AVol and TVol models were 58.1 and 64.5%, respectively, significantly higher than that of the 2D model (19.4%) (both p < 0.05). The inter-observer reliability of measuring fetal AVol and TVol were high, with the ICCs of 0.921 and 0.963, respectively. Conclusion In this cohort, the automated 3D fractional limb volume model improves the accuracy of weight estimation in most third-trimester fetuses. Prediction accuracy of the 3D model for neonatal BW, particularly < 3500 g was higher than that of the traditional 2D model.

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