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Published on: June 23, 2015
Risk Severity Model for Pediatric Autosomal Dominant Polycystic Kidney Disease Using 3D Ultrasound Volumetry
Luc Breysem1, Frederik De Keyzer1, Pieter Schellekens2,3
1Department of Radiology, University Hospitals Leuven, Leuven, Belgium.
Insights
A new pediatric classification tool using 3D ultrasound was developed for autosomal dominant polycystic kidney disease (ADPKD). This Leuven Imaging Classification helps accurately assess disease severity in children, addressing limitations of adult models.
Area of Science:
- Nephrology
- Medical Imaging
- Genetics
Background:
- Autosomal dominant polycystic kidney disease (ADPKD) affects kidney structure and function.
- Height-adjusted total kidney volume (htTKV) via imaging (Mayo Imaging Class) is a validated prognostic tool in adults.
- No imaging-based prognostic tool currently exists for pediatric ADPKD.
Purpose of the Study:
- To develop a novel imaging-based classification tool for pediatric ADPKD.
- To address the limitations of existing adult prognostic models in children.
- To utilize 3D ultrasound for a more accessible pediatric ADPKD assessment.
Main Methods:
- A prospective cohort of 74 genotyped ADPKD patients underwent 247 longitudinal 3D ultrasound assessments.
- Data was matched to the adult Mayo Imaging Classification (MIC) and subsequently optimized.
- The developed pediatric model was validated using independent patient data.
Main Results:
- The adult MIC underestimated ADPKD severity in children under 15, even with height correction.
- A novel five-level Leuven Imaging Classification pediatric model was created.
- This model uses patient age and 3D ultrasound-derived htTKV for severity stratification.
Conclusions:
- The Leuven Imaging Classification provides a reliable method for discriminating ADPKD severity in children.
- This 3D ultrasound-based tool complements existing adult classifications.
- It offers a much-needed prognostic measure for pediatric ADPKD.
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. Because magnetic resonance imaging and computed tomography in children are difficult, we propose a novel 3D ultrasound-based pediatric Leuven Imaging Classification to complement the MIC.
Methods:
A prospective study cohort of 74 patients with genotyped ADPKD (37 female) was followed longitudinally with ultrasound, including 3D ultrasound, and they underwent in total 247 3D ultrasound assessments, with patients' median age (interquartile range [IQR]) at diagnosis of 3 (IQR, 0-9) years and at first 3D ultrasound evaluation of 10 (IQR, 5-14) years. 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 glucosidase IIα unit only once (1%). Over these 247 evaluations, the median height was 143 (IQR, 122-166) cm and total kidney volume was 236 (IQR, 144-344) ml, leading to an htTKV of 161 (IQR, 117-208) ml/m. Applying the adult Mayo classification in children younger than 15 years strongly underestimated ADPKD severity, 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 Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease used to establish the MIC.
Conclusions:
We proposed a five-level Leuven Imaging Classification ADPKD pediatric model as a novel classification tool on the basis of patients' age and 3D ultrasound-htTKV for reliable discrimination of childhood ADPKD severity.
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