Prenatal diagnosis and prognosis assessment of fetal intra-abdominal cystic lesions: a retrospective study in 264 cases

Abstract

To assess the accuracy of prenatal diagnosis and the prognosis of fetal-abdominal masses, we reviewed all of the cases which had been diagnosed as having abdominal masses from January 2014 to December 2016. In total, 264 cases were identified as having abdominal masses. Among them, 141 cases (53%) had received specific prenatal diagnoses by prenatal ultrasound (US). MRI had assisted in the diagnosis and prognostic evaluation in 69 cases, increasing the diagnostic rate to 65%. The prenatal diagnoses of 111 cases (65%) were concordant with the postnatal diagnoses. Surgical intervention after birth was needed in 96 cases (39%). Most outcomes were good (89%). We suggest that prenatal US can detect and identify most fetal abdominal masses and that MRI helps to further describe the masses. With early intervention after birth, the prognosis was good in most cases.

Impact Statement

• What is already known on this subject? Fetal-abdominal masses are commonly detected in antenatal examinations. A prenatal ultrasound is the main screening tool for detecting fetal intra-abdominal cystic lesions.

• What the results of this study add? We suggest that MRI is more helpful in some systems to reveal locations and structures. Even prenatal diagnosis cannot reach before birth, prognosis is quite good and expectant therapy is sufficient.

• What the implications are of these findings for clinical practice and/or future research? Our data strengthens the current knowledge of fetal abdominal masses to help relieve anxious parents by telling them that this congenital malformation has good outcomes. But multidiscipline consultation is necessary.

Keywords:

• Fetal abdominal mass
• prenatal diagnosis
• fetal ultrasound
• fetal MRI
• postnatal outcome
• fetal therapy

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China under a Grant No. 81571447.