Added value of fetal MRI as a complementary method to antenatal ultrasound in the assessment of non-CNS fetal congenital anomalies

Abstract

Abstract Background Birth defects and congenital anomalies are different words used to describe developmental abnormalities that occur at birth. Congenital anomalies diagnosis during pregnancy is a difficult topic to which ultrasonography has made significant contributions. The availability of a generally safe, independent technique in the evaluation of prenatal anomalies would be a welcomed clinical and scientific alternative. Ultrasound (US) is the predominant modality for evaluating disorders related to fetus and pregnancy. In most situations, this examination by a professional operator offers sufficient information about fetal morphology, surroundings, and well-being. The abnormalities revealed by ultrasound can be subtle or inconclusive at times. MRI has been demonstrated to be useful in such circumstances in various studies. So the effective use of fetal MRI in the evaluation of non-CNS abnormalities of the body is a reason for adopting fetal MRI as an adjunct to US in obstetric imaging. This study aimed to examine the role of fetal MRI as a complementary method to the antenatal US in assessing non-CNS anomalies and how it changed or modified the diagnosis of anomalies. Results By analyzing the data of 30 pregnant females with fetal non-CNS congenital anomalies, the diagnostic accuracy of prenatal ultrasound alone in the detection of congenital anomalies was 76%, with a sensitivity of about 76%. And diagnostic accuracy of MRI alone was 96.6%, with a sensitivity of approximately 96.6%. Moreover, the diagnostic accuracy of combined prenatal US and prenatal MRI in the detection of congenital anomalies was 100%, with sensitivity about 100% and PPV about 100%. Conclusion Fetal MRI raises confidence in non-CNS malformation assessment. Compared to US, MRI overcomes many of the obstacles faced by the antenatal US. MRI is superior to the US in refining, changing, or adding more diagnostic information about the disease.

Keywords

• Magnetic resonance imaging
• Ultrasound
• Central nervous system