Risk Severity Model for Pediatric Autosomal Dominant Polycystic Kidney Disease Using 3D Ultrasound Volumetry.

BACKGROUND: Height-adjusted total kidney volume (htTKV) measured by imaging defined as Mayo Imaging Class (MIC) is a validated prognostic measure for autosomal dominant polycystic kidney disease (ADPKD) in adults to predict and stratify disease progression. However, no stratification tool is currently available in pediatric ADPKD. Since magnetic resonance imaging and computed tomography in children are difficult, we propose a novel 3D ultrasound based pediatric Leuven Imaging Classification (LIC) to complement the MIC.

METHODS: A prospective study cohort of seventy-four genotyped ADPKD patients (37 female) is followed longitudinally with ultrasound including 3D ultrasound and they underwent in total 247 3D ultrasound assessments, with patients' median age (interquartile range) at diagnosis of 3 (0-9) years and at first 3D ultrasound evaluation of 10 (5-14) years with htTKV of 161 (117-208) mL/m. First, data matching was done to the published MIC classification, followed by subsequent optimization of parameters and model type.

RESULTS: PKD1 was confirmed in 70 patients (95%), PKD2 in three (4%), and GANAB only once (1%). Over these 247 evaluations, the median height was 143 (122-166) cm and total kidney volume was 236 (144-344) mL, leading to an htTKV of 161 (117-208) mL/m. Applying the adult Mayo classification below the age of 15 years strongly underestimated ADPKD severity in children, even with correction for height. We therefore optimized the model with our pediatric data and eventually validated it with data of young patients from Mayo Clinic and the CRISP Consortium used to establish the MIC.

CONCLUSIONS: We proposed a 5-level "LIC ADPKD Pediatric Model" as a novel classification tool based on patients' age and 3D ultrasound-htTKV for reliable discrimination of childhood ADPKD severity.