Total Kidney Volume (TKV) Progression Prediction in ADPKD Using Radiomics

Total Kidney Volume (TKV) Progression Prediction in ADPKD Using Radiomics

This poster explores whether baseline cyst radiomics from routine MRI can help predict future total kidney volume (TKV) in autosomal dominant polycystic kidney disease (ADPKD). Using machine learning to analyze cyst-level imaging features, the researchers found that baseline radiomics provided a noninvasive signal for predicting follow-up TKV, with prediction most reliable in patients with earlier-stage disease. The findings highlight the potential for radiomics to capture prognostic information beyond cyst size alone and support more individualized risk stratification.

• Explore the potential of MRI radiomics to predict TKV progression and capture prognostic heterogeneity beyond cyst size alone.
• See how machine learning was applied to cyst-level imaging features to predict follow-up TKV in patients with ADPKD.
• Learn where the approach showed the greatest predictive accuracy and why further validation in larger, multicenter cohorts is needed.