Abstract
Total kidney volume represents the most solid prognostic biomarker for autosomal dominant polycystic kidney disease, because it mirrors cyst growth that precedes kidney function decline. Considerable variability of glomerular filtration rate trajectories, however, remains unexplained by total kidney volume, and its calculation is time-consuming. Using deep learning algorithms, Gregory etal. determined total kidney volume and other, novel, imaging-based biomarkers. They achieved automation and improved prognostic accuracy for long-term kidney function loss, yet the study leaves some open questions and room for further improvement.
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