Expanded Imaging Classification of Autosomal Dominant Polycystic Kidney Disease.

Area of Science:

• Nephrology
• Medical Imaging
• Genetics

Background:

• Autosomal dominant polycystic kidney disease (ADPKD) risk stratification relies on the Mayo Clinic imaging classification, utilizing height-adjusted total kidney volume (htTKV) and age.
• This classification is limited to patients with typical diffuse cystic disease (class 1) and poorly predicts kidney function decline in the 5%-10% of patients with atypical morphology (class 2).

Purpose of the Study:

• To refine the Mayo Clinic imaging classification for ADPKD by developing a more accurate risk prediction model for patients with atypical morphology.
• To assess the impact of excluding exophytic cysts from htTKV measurements on predicting chronic kidney disease (CKD) stage 3 and estimated glomerular filtration rate (eGFR) trajectory.

Main Methods:

• Identified patients with ADPKD from the HALT-A study, including class 2A with prominent exophytic cysts (class 2Ae) and class 1 with prominent exophytic cysts.
• Recalculated htTKVs for these patients, excluding exophytic cysts, and compared prediction accuracy for CKD stage 3 and eGFR trajectory using original and recalculated htTKVs in logistic and mixed linear models.

Main Results:

• Recalculated htTKVs increased specificity for developing CKD stage 3 from 82.6% to 84.2% across all participants.
• The prediction of CKD stage 3 in class 2Ae patients was better calibrated using recalculated htTKVs (45.5% predicted vs. 13.0% observed) compared to original htTKVs (63.6% predicted).
• Recalculated htTKVs significantly reduced the mean paired difference between predicted and observed eGFR for both class 2Ae (from 17.6 to 4.0 ml/min/1.73 m² ) and class 1 (from -1.7 to 0.1 ml/min/1.73 m²).

Conclusions:

• Excluding prominent exophytic cysts from htTKV measurements improves the accuracy of the Mayo classification for ADPKD.
• This adjusted htTKV measure facilitates the inclusion of class 2 patients and reclassification of class 1 patients, enhancing risk stratification for disease progression.