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

Fetuses at the extremes of growth abnormalities carry a risk of perinatal morbidity and death. Their identification traditionally is done by 2-dimensional ultrasound imaging, the performance of which is not always optimal. Magnetic resonance imaging superbly depicts fetal anatomy and anomalies and has contributed largely to the evaluation of high-risk pregnancies. In 1994, magnetic resonance imaging was introduced for the estimation of fetal weight, which is done by measuring the fetal body volume and converting it through a formula to fetal weight. Approximately 10 studies have shown that magnetic resonance imaging is more accurate than 2-dimensional ultrasound imaging in the estimation of fetal weight. Yet, despite its promise, the magnetic resonance imaging technique currently is not implemented clinically. Over the last 5 years, this technique has evolved quite rapidly. Here, we review the literature data, provide details of the various measurement techniques and formulas, consider the application of the magnetic resonance imaging technique in specific populations such as patients with diabetes mellitus and twin pregnancies, and conclude with what we believe could be the future perspectives and clinical application of this challenging technique. The estimation of fetal weight by ultrasound imaging is based mainly on an algorithm that takes into account the measurement of biparietal diameter, head circumference, abdominal circumference, and femur length. The estimation of fetal weight by magnetic resonance imaging is based on one of the 2 formulas: (1) magnetic resonance imaging-the estimation of fetal weight (in kilograms)=1.031×fetal body volume (in liters)+0.12 or (2) magnetic resonance imaging-the estimation of fetal weight (in grams)=1.2083×fetal body volume (in milliliters)ˆ0.9815. Comparison of these 2 formulas for the detection of large-for-gestational age neonates showed similar performance for preterm (P=.479) and for term fetuses (P=1.000). Literature data show that the estimation of fetal weight with magnetic resonance imaging carries a mean or median relative error of 2.6 up to 3.7% when measurements were performed at <1 week from delivery; whereas for the same fetuses, the relative error at 2-dimensional ultrasound imaging varied between 6.3% and 11.4%. Further, in a series of 270 fetuses who were evaluated within 48 hours from birth and for a fixed false-positive rate of 10%, magnetic resonance imaging detected 98% of large-for-gestational age neonates (≥95th percentile for gestation) compared with 67% with ultrasound imaging estimates. For the same series, magnetic resonance imaging applied to the detection of small-for-gestational age neonates ≤10th percentile for gestation, for a fixed 10% false-positive rate, reached a detection rate of 100%, compared with only 78% for ultrasound imaging. Planimetric measurement has been 1 of the main limitations of magnetic resonance imaging for the estimation of fetal weight. Software programs that allow semiautomatic segmentation of the fetus are available from imaging manufacturers or are self-developed. We have shown that all of them perform equally well for the prediction of large-for-gestational age neonates, with the advantage of the semiautomatic methods being less time-consuming. Although many challenges remain for this technique to be generalized, a 2-step strategy after the selection of a group who are at high risk of the extremes of growth abnormalities is the most likely scenario. Results of ongoing studies are awaited (ClinicalTrials.gov Identifier # NCT02713568).