Magnetic resonance imaging for prenatal estimation of birthweight in pregnancy: review of available data, techniques, and future perspectives

Reducing macrosomia-related birth complications in primigravid women: ultrasound- and magnetic resonance imaging-based models

BACKGROUND

Many complications increase with macrosomia, which is defined as birthweight of ≥4000 g. The ability to estimate when the fetus would exceed 4000 g could help to guide decisions surrounding the optimal timing of delivery. To the best of our knowledge, there is no available tool to perform this estimation independent of the currently available growth charts.

OBJECTIVE

This study aimed to develop ultrasound- and magnetic resonance imaging-based models to estimate at which gestational age the birthweight would exceed 4000 g, evaluate their predictive performance, and assess the effect of each model in reducing adverse outcomes in a prospectively collected cohort.

STUDY DESIGN

This study was a subgroup analysis of women who were recruited for the estimation of fetal weight by ultrasound and magnetic resonance imaging at 36 0/7 to 36 6/7 weeks of gestation. Primigravid women who were eligible for normal vaginal delivery were selected. Multiparous patients, patients with preeclampsia spectrum, patients with elective cesarean delivery, and patients with contraindications for normal vaginal delivery were excluded. Of note, 2 linear models were built for the magnetic resonance imaging- and ultrasound-based models to predict a birthweight of ≥4000 g. Moreover, 2 formulas were created to predict the gestational age at which birthweight will reach 4000 g (predicted gestational age); one was based on the magnetic resonance imaging model, and the second one was based on the ultrasound model. This study compared the adverse birth outcomes, such as intrapartum cesarean delivery, operative vaginal delivery, anal sphincter injury, postpartum hemorrhage, shoulder dystocia, brachial plexus injury, Apgar score of <7 at 5 minutes of life, neonatal intensive care unit admission, and intracranial hemorrhage in the group of patients who delivered after the predicted gestational age according to the magnetic resonance imaging-based or the ultrasound-based models with those who delivered before the predicted gestational age by each model, respectively.

RESULTS

Of 2378 patients, 732 (30.8%) were eligible for inclusion in the current study. The median gestational age at birth was 39.86 weeks of gestation (interquartile range, 39.00-40.57), the median birthweight was 3340 g (interquartile range, 3080-3650), and 63 patients (8.6%) had a birthweight of ≥4000 g. Prepregnancy body mass index, geographic origin, gestational age at birth, and fetal body volume were retained for the optimal magnetic resonance imaging-based model, whereas maternal age, gestational diabetes mellitus, diabetes mellitus type 1 or 2, geographic origin, fetal gender, gestational age at birth, and estimated fetal weight were retained for the optimal ultrasound-based model. The performance of the first model was significantly better than the second model (area under the curve: 0.98 vs 0.89, respectively; P<.001). The group of patients who delivered after the predicted gestational age by the first model (n=40) had a higher risk of cesarean delivery, postpartum hemorrhage, and shoulder dystocia (adjusted odds ratio: 3.15, 4.50, and 9.67, respectively) than the group who delivered before this limit. Similarly, the group who delivered after the predicted gestational age by the second model (n=25) had a higher risk of cesarean delivery and postpartum hemorrhage (adjusted odds ratio: 5.27 and 6.74, respectively) than the group who delivered before this limit.

CONCLUSION

The clinical use of magnetic resonance imaging- and ultrasound-based models, which predict a gestational age at which birthweight will exceed 4000 g, may reduce macrosomia-related adverse outcomes in a primigravid population. The magnetic resonance imaging-based model is better for the identification of the highest-risk patients.

Prediction of large-for-gestational age at 36 weeks' gestation: two-dimensional ultrasound vs three-dimensional ultrasound vs magnetic resonance imaging

OBJECTIVE

To compare the performance of two-dimensional ultrasound (2D-US), three-dimensional ultrasound (3D-US) and magnetic resonance imaging (MRI) at 36 weeks' gestation in predicting the delivery of a large-for-gestational-age (LGA) neonate, defined as birth weight ≥ 95th percentile, in patients at high and low risk for macrosomia.

METHODS

This was a secondary analysis of a prospective observational study conducted between January 2017 and February 2019. Women with a singleton pregnancy at 36 weeks' gestation underwent 2D-US, 3D-US and MRI within 15 min for estimation of fetal weight. Weight estimations and birth weight were plotted on a growth curve to obtain percentiles for comparison. Participants were considered high risk if they had at least one of the following risk factors: diabetes mellitus, estimated fetal weight ≥ 90th percentile at the routine third-trimester ultrasound examination, obesity (prepregnancy body mass index ≥ 30 kg/m2) or excessive weight gain during pregnancy. The outcome was the diagnostic performance of each modality in the prediction of birth weight ≥ 95th percentile, expressed as the area under the receiver-operating-characteristics curve (AUC), sensitivity, specificity and positive and negative predictive values.

RESULTS

A total of 965 women were included, of whom 533 (55.23%) were high risk and 432 (44.77%) were low risk. In the low-risk group, the AUCs for birth weight ≥ 95th percentile were 0.982 for MRI, 0.964 for 2D-US and 0.962 for 3D-US; pairwise comparisons were non-significant. In the high-risk group, the AUCs were 0.959 for MRI, 0.909 for 2D-US and 0.894 for 3D-US. A statistically significant difference was noted between MRI and both 2D-US (P = 0.002) and 3D-US (P = 0.002), but not between 2D-US and 3D-US (P = 0.503). In the high-risk group, MRI had the highest sensitivity (65.79%) compared with 2D-US (36.84%, P = 0.002) and 3D-US (21.05%, P < 0.001), whereas 3D-US had the highest specificity (98.99%) compared with 2D-US (96.77%, P = 0.005) and MRI (96.97%, P = 0.004).

CONCLUSIONS

At 36 weeks' gestation, MRI has better performance compared with 2D-US and 3D-US in predicting birth weight ≥ 95th percentile in patients at high risk for macrosomia, whereas the performance of 2D-US and 3D-US is comparable. For low-risk patients, the three modalities perform similarly. © 2023 International Society of Ultrasound in Obstetrics and Gynecology.

Deep learning-based segmentation of whole-body fetal MRI and fetal weight estimation: assessing performance, repeatability, and reproducibility

OBJECTIVES

To develop a deep-learning method for whole-body fetal segmentation based on MRI; to assess the method's repeatability, reproducibility, and accuracy; to create an MRI-based normal fetal weight growth chart; and to assess the sensitivity to detect fetuses with growth restriction (FGR).

METHODS

Retrospective data of 348 fetuses with gestational age (GA) of 19-39 weeks were included: 249 normal appropriate for GA (AGA), 19 FGR, and 80 Other (having various imaging abnormalities). A fetal whole-body segmentation model with a quality estimation module was developed and evaluated in 169 cases. The method was evaluated for its repeatability (repeated scans within the same scanner, n = 22), reproducibility (different scanners, n = 6), and accuracy (compared with birth weight, n = 7). A normal MRI-based growth chart was derived.

RESULTS

The method achieved a Dice = 0.973, absolute volume difference ratio (VDR) = 1.8% and VDR mean difference = 0.75% ([Formula: see text]: - 3.95%, 5.46), and high agreement with the gold standard. The method achieved a repeatability coefficient = 4.01%, ICC = 0.99, high reproducibility with a mean difference = 2.21% ([Formula: see text]: - 1.92%, 6.35%), and high accuracy with a mean difference between estimated fetal weight (EFW) and birth weight of - 0.39% ([Formula: see text]: - 8.23%, 7.45%). A normal growth chart (n = 246) was consistent with four ultrasound charts. EFW based on MRI correctly predicted birth-weight percentiles for all 18 fetuses ≤ 10thpercentile and for 14 out of 17 FGR fetuses below the 3rd percentile. Six fetuses referred to MRI as AGA were found to be < 3rd percentile.

CONCLUSIONS

The proposed method for automatic MRI-based EFW demonstrated high performance and sensitivity to identify FGR fetuses.

CLINICAL RELEVANCE STATEMENT

Results from this study support the use of the automatic fetal weight estimation method based on MRI for the assessment of fetal development and to detect fetuses at risk for growth restriction.

KEY POINTS

• An AI-based segmentation method with a quality assessment module for fetal weight estimation based on MRI was developed, achieving high repeatability, reproducibility, and accuracy. • An MRI-based fetal weight growth chart constructed from a large cohort of normal and appropriate gestational-age fetuses is proposed. • The method showed a high sensitivity for the diagnosis of small fetuses suspected of growth restriction.

Measuring intrauterine growth in healthy pregnancies using quantitative magnetic resonance imaging

OBJECTIVE

The aim of this study was to determine in utero fetal-placental growth patterns using in vivo three-dimensional (3D) quantitative magnetic resonance imaging (qMRI).

STUDY DESIGN

Healthy women with singleton pregnancies underwent fetal MRI to measure fetal body, placenta, and amniotic space volumes. The fetal-placental ratio (FPR) was derived using 3D fetal body and placental volumes (PV). Descriptive statistics were used to describe the association of each measurement with increasing gestational age (GA) at MRI.

RESULTS

Fifty-eight (58) women underwent fetal MRI between 16 and 38 completed weeks gestation (mean = 28.12 ± 6.33). PV and FPR varied linearly with GA at MRI (r_PV,GA = 0.83, r_FPR,GA = 0.89, p value < 0.001). Fetal volume varied non-linearly with GA (p value < 0.01).

CONCLUSIONS

We describe in-utero growth trajectories of fetal-placental volumes in healthy pregnancies using qMRI. Understanding healthy in utero development can establish normative benchmarks where departures from normal may identify early in utero placental failure prior to the onset of fetal harm.

Fetal magnetic resonance imaging at 36 weeks predicts neonatal macrosomia: the PREMACRO study

BACKGROUND

Large-for-gestational-age fetuses are at increased risk of perinatal morbidity and mortality. Magnetic resonance imaging seems to be more accurate than ultrasound in the prediction of macrosomia; however, there is no well-powered study comparing magnetic resonance imaging with ultrasound in routine pregnancies.

OBJECTIVE

This study aimed to prospectively compare estimates of fetal weight based on 2-dimensional ultrasound and magnetic resonance imaging with actual birthweights in routine pregnancies.

STUDY DESIGN

From May 2016 to February 2019, women received counseling at the 36-week clinic. Written informed consent was obtained for this Ethics Committee-approved study. In this prospective, single-center, blinded study, pregnant women with singleton pregnancies between 36 0/7 and 36 6/7 weeks' gestation underwent both standard evaluation of estimated fetal weight with ultrasound according to Hadlock et al and magnetic resonance imaging according to the formula developed by Baker et al, based on the measurement of the fetal body volume. Participants and clinicians were aware of the results of the ultrasound but blinded to the magnetic resonance imaging estimates. Birthweight percentile was considered as the gold standard for the ultrasound and magnetic resonance imaging-derived percentiles. The primary outcome was the area under the receiver operating characteristic curve for the prediction of large-for-gestation-age neonates with birthweights of ≥95th percentile. Secondary outcomes included the comparative prediction of large-for-gestation-age neonates with birthweights of ≥90th, 97th, and 99th percentiles and small-for-gestational-age neonates with birthweights of ≤10th, 5th, and 3rd percentiles for gestational age and maternal and perinatal complications.

RESULTS

Of 2914 women who were initially approached, results from 2378 were available for analysis. Total fetal body volume measurements were possible for all fetuses, and the time required to perform the planimetric measurements by magnetic resonance imaging was 3.0 minutes (range, 1.3-5.6). The area under the receiver operating characteristic curve for the prediction of a birthweight of ≥95th percentile was 0.985 using prenatal magnetic resonance imaging and 0.900 using ultrasound (difference=0.085, P<.001; standard error, 0.020). For a fixed false-positive rate of 5%, magnetic resonance imaging for the estimation of fetal weight detected 80.0% (71.1-87.2) of birthweight of ≥95th percentile, whereas ultrasound for the estimation of fetal weight detected 59.1% (49.0-68.5) of birthweight of ≥95th percentile. The positive predictive value was 42.6% (37.8-47.7) for the estimation of fetal weight using magnetic resonance imaging and 35.4% (30.1-41.1) for the estimation of fetal weight using ultrasound, and the negative predictive value was 99.0% (98.6-99.3) for the estimation of fetal weight using magnetic resonance imaging and 98.0% (97.6-98.4) for the estimation of fetal weight using ultrasound. For a fixed false-positive rate of 10%, magnetic resonance imaging for the estimation of fetal weight detected 92.4% (85.5-96.7) of birthweight of ≥95th percentile, whereas ultrasound for the estimation of fetal weight detected 76.2% (66.9-84.0) of birthweight of ≥95th percentile. The positive predictive value was 29.9% (27.2-32.8) for the estimation of fetal weight using magnetic resonance imaging and 26.2% (23.2-29.4) for the estimation of fetal weight using ultrasound, and the negative predictive value was 99.6 (99.2-99.8) for the estimation of fetal weight using magnetic resonance imaging and 98.8 (98.4-99.2) for the estimation of fetal weight using ultrasound. The area under the receiver operating characteristic curves for the prediction of large-for-gestational-age neonates with birthweights of ≥90th, 97th, and 99th percentiles and small-for-gestational-age neonates with birthweights of ≤10th, 5th, and 3rd percentiles was significantly larger in prenatal magnetic resonance imaging than in ultrasound (P<.05 for all).

CONCLUSION

At 36 weeks' gestation, magnetic resonance imaging for the estimation of fetal weight performed significantly better than ultrasound for the estimation of fetal weight in the prediction of large-for-gestational-age neonates with birthweights of ≥95th percentile for gestational age and all other recognized cutoffs for large-for-gestational-age and small-for-gestational-age neonates (P<.05 for all).

The application of in utero magnetic resonance imaging in the study of the metabolic and cardiovascular consequences of the developmental origins of health and disease

Observing fetal development in utero is vital to further the understanding of later-life diseases. Magnetic resonance imaging (MRI) offers a tool for obtaining a wealth of information about fetal growth, development, and programming not previously available using other methods. This review provides an overview of MRI techniques used to investigate the metabolic and cardiovascular consequences of the developmental origins of health and disease (DOHaD) hypothesis. These methods add to the understanding of the developing fetus by examining fetal growth and organ development, adipose tissue and body composition, fetal oximetry, placental microstructure, diffusion, perfusion, flow, and metabolism. MRI assessment of fetal growth, organ development, metabolism, and the amount of fetal adipose tissue could give early indicators of abnormal fetal development. Noninvasive fetal oximetry can accurately measure placental and fetal oxygenation, which improves current knowledge on placental function. Additionally, measuring deficiencies in the placenta’s transport of nutrients and oxygen is critical for optimizing treatment. Overall, the detailed structural and functional information provided by MRI is valuable in guiding future investigations of DOHaD.

Unique microRNA Signals in Plasma Exosomes from Pregnancies Complicated by Preeclampsia

Although preeclampsia is a common and serious complication of pregnancy, insight into its pathobiology and diagnosis is lacking. Circulating plasma exosomes, which contain RNA and other molecules and have recently become accessible for diagnostics, may be informative in this regard. We tested the hypothesis that preeclampsia may affect the miRNA cargo within circulating maternal blood exosomes. We collected plasma from 60 pregnant women at term, including 20 women with pregnancy complicated by preeclampsia, and 20 women with fetal growth restriction and 20 with healthy pregnancy, serving as controls. We isolated exosomes from the maternal plasma by continuous density gradient ultracentrifugation. Our main outcome variable was exosomal miRNA cargo, analyzed by quantitative polymerase chain reaction-based TaqMan advanced miRNA assay in a card format and the expression of differentially expressed exosomal miRNA in whole plasma from the same participants. We found that 7 miRNA species were differentially expressed in exosomes from women with preeclampsia and those from controls. In contrast, there was no significant difference in exosomal miRNA expression between women with fetal growth restriction and controls. The results were not affected by fetal sex. Only one of the preeclampsia-related, differentially expressed exosomal miRNAs was significantly different in whole plasma miRNA analysis. We concluded that unlike whole plasma miRNA, exosomes extracted from the plasma of women with preeclampsia exhibit a unique miRNA profile, suggesting that plasma exosomal miRNA could provide insight into the pathophysiology of preeclampsia, and may play a role in disease diagnostics.

Ultrasound measurement of fetal abdominal subcutaneous tissue thickness as a predictor of large versus small fetuses for gestational age

Background

Commonly used ultrasound fetal weight estimation formulas show variable degrees of error which is more evident in fetuses with nutritional and metabolic issues; better accuracy of fetal weight estimation can be obtained by incorporation of fetal soft tissue parameters like the fetal subcutaneous tissue in the weight estimation process. The aim of this study was to assess the accuracy of fetal abdominal subcutaneous tissue thickness (FASTT) as an indicator of fetal birth weight.

Results

FASTT showed a high significant statistical correlation with fetal birth weight (r = 0.94, P value = 0.00); it showed higher sensitivity for large for gestational age (LGA) than small for gestational age (SGA) (90.9% and 86.9%, respectively). The best cutoff value for the detection of LGA was ≥ 9.2 mm and ≤ 4.5 for SGA. FASTT showed lower accuracy than abdominal circumference (AC) as an indicator of LGA (92% versus 96%, respectively). Used alone, FASTT is less sensitive than Hadlock formula in both LGA and SGA (90.9% versus 94.5% in LGA and 86.9% versus 88.9% for SGA, respectively). There was no statistical correlation between FASTT and mode of delivery (r = 0.09, P value = 0.23) nor fetal gender (r = 0.15, P value = 0.11)

Conclusion

FASTT is a good indicator of fetal birth weight especially LGA, yet it is less sensitive than AC in the prediction of LGA. It cannot be used as a predictor of mode of delivery and not affected by fetal gender.

The use of magnetic resonance imaging in the prediction of birthweight

Extremes of fetal growth can increase adverse pregnancy outcomes, and this is equally applicable to single and multiple gestations. Traditionally, these cases have been identified using simple two-dimensional ultrasound which is quite limited by its low precision. Magnetic resonance imaging (MRI) has now been used for many years in obstetrics, mainly as an adjunct to ultrasound for congenital abnormalities and increasingly as part of the post-mortem examination. However, MRI can also be used to accurately assess fetal weight as first demonstrated by Baker et al in 1994, using body volumes rather than standard biometric measurements. This publication was followed by several others, all of which confirmed the superiority of MRI; however, despite this initial promise, the technique has never been successfully integrated into clinical practice. In this review, we provide an overview of the literature, detail the various techniques and formulas currently available, discuss the applicability to specific high-risk groups and present our vision for the future of MRI within clinical obstetrics.