Jonathan Taylor, Richard Thomas, Peter Metherall, Marieke van Gastel, Emilie Cornec-Le Gall, Anna Caroli, Monica Furlano, Nathalie Demoulin, Olivier Devuyst, Jean Winterbottom, Roser Torra, Norberto Perico, Yannick Le Meur, Sebastian Schoenherr, Lukas Forer, Ron T Gansevoort, Roslyn J Simms, Albert C M Ong
INTRODUCTION: Accurate tools to inform individual prognosis in patients with autosomal dominant polycystic kidney disease (ADPKD) are lacking. Here, we report an artificial intelligence (AI)-generated method for routinely measuring total kidney volume (TKV). METHODS: An ensemble U-net algorithm was created using the nnUNet approach. The training and internal cross-validation cohort consisted of all 1.5T magnetic resonance imaging (MRI) data acquired using 5 different MRI scanners (454 kidneys, 227 scans) in the CYSTic consortium, which was first manually segmented by a single human operator...
February 2024: KI Reports