Zhongxiu Hu

Jun 14, 2024 | nature.com | Zhongxiu Hu |Arman Sharbatdaran |Xinzi He |Chenglin Zhu |Jon Blumenfeld |Hanna Rennert | +5 more

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 ( $$n = 36$$ ) 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 $$2.1\% \pm 2\%$$ compared to $$1.1\% \pm 1\%$$ ( $$p = 0.002$$ ) for a 2-parameter fit to the same exponential growth curve used for MIC when 4 measurements were available or $$1.4\% \pm 1\%$$ ( $$p = 0.01$$ ) with 3 measurements averaging together with MIC. On univariate analysis, male sex ( $$p = 0.05$$ ) and PKD2 mutation ( $$p = 0.04$$ ) 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.