Multidisciplinary consensus on the classification of prenatal and postnatal urinary tract dilation (UTD...

Area of Science:

• Pediatric Urology
• Fetal Medicine
• Diagnostic Imaging

Background:

• Urinary tract (UT) dilation affects 1-2% of fetuses, with variable clinical management due to limited evidence correlating prenatal findings with postnatal uropathies.
• Lack of consensus in defining and classifying UT dilation hinders accurate diagnosis and management of prenatal and postnatal urological conditions.
• A unified classification system is needed for standardized diagnosis and management of UT dilation.

Purpose of the Study:

• To propose a unified description for urinary tract (UT) dilation applicable both prenatally and postnatally.
• To establish a standardized scheme for perinatal evaluation based on sonographic criteria, creating a classification system for UT dilation.

Main Methods:

• A consensus meeting involving multiple professional societies was convened to develop the classification system.
• Recommendations were based on a detailed literature review and expert opinion.
• The proposed UTD Classification System utilizes six sonographic categories: renal pelvic diameter, calyceal dilation, parenchymal thickness and appearance, and bladder/ureteral abnormalities.

Main Results:

• The UTD Classification System stratifies UT dilation severity based on gestational age and detection timing (prenatal/postnatal).
• Six key sonographic findings form the basis of the classification: anterior-posterior renal pelvic diameter (APRPD), calyceal dilation, renal parenchymal thickness, renal parenchymal appearance, bladder abnormalities, and ureteral abnormalities.
• A follow-up scheme based on the UTD classification was also proposed.

Conclusions:

• The proposed UTD Classification System requires further evaluation to assess its utility in predicting clinical outcomes.
• Currently, the grading system correlates with the risk of postnatal uropathies.
• Future research aims to refine the classification system to predict other clinical outcomes, such as the need for surgical intervention or impact on renal function.