Chenglin Zhu

2 months ago | mdpi.com | Shiqi Zhang |Limei Xu |Chenglin Zhu |Jing Li

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Sep 6, 2024 | mdpi.com | Siliang Xiang |Xiao Luo |Chenglin Zhu |Jiarong Li

All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.

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.