Improved predictions of total kidney volume growth rate in ADPKD using two-parameter least squares fitting

Abstract Mayo Imaging Classification (MIC) for predicting future kidney growth in autosomal dominant polycystic kidney disease (ADPKD) patients is calculated from a single MRI/CT scan assuming exponential kidney volume growth and height-adjusted total kidney volume at birth to be 150 mL/m. However, when multiple scans are available, how this information should be combined to improve prediction accuracy is unclear. Herein, we studied ADPKD subjects (n = 36 n = 36) with 8+ years imaging follow-up (mean = 11 years) to establish ground truth kidney growth trajectory. MIC annual kidney growth rate predictions were compared to ground truth as well as 1- and 2-parameter least squares fitting. The annualized mean absolute error in MIC for predicting total kidney volume growth rate was 2. 1\% 2\% 2. 1 % ± 2 % compared to 1. 1\% 1\% 1. 1 % ± 1 % (p = 0. 002 p = 0. 002) for a 2-parameter fit to the same exponential growth curve used for MIC when 4 measurements were available or 1. 4\% 1\% 1. 4 % ± 1 % (p = 0. 01 p = 0. 01) with 3 measurements averaging together with MIC. On univariate analysis, male sex (p = 0. 05 p = 0. 05) and PKD2 mutation (p = 0. 04 p = 0. 04) were associated with poorer MIC performance. In ADPKD patients with 3 or more CT/MRI scans, 2-parameter least squares fitting predicted kidney volume growth rate better than MIC, especially in males and with PKD2 mutations where MIC was less accurate.