Development of a generalized model for kidney depth estimation in the Chinese population: A multi-center study

Qian Li, Zhongyun Pan, Qiang Li, Masoud Baikpour, Eugene Cheah, Kai Chen, Wenliang Li, Yiqing Song, Jingjing Zhang, Lijuan Yu, Changjing Zuo, Jianjun Liu, Aimin Yang, Zhiling Ding, Juan Li, Yongjun Luo, Tiannv Li, Yanlin Feng, Shupeng Yu, Laiping XieGanhua Luo, Qian Wang, Longxiao Wei, Yue Chen, Hua Sun, Chenghe Lin, Wengui Xu, Wenrui Zhao, Xiang Peng, Cheng Wang, Xingmin Han, Ya Ba, Yanjun Zhang, Wei Li, Wei Zhang, Hui Yang

Research output: Contribution to journalArticle


Purpose: To establish an accurate and reliable equation for kidney depth estimation in adult patients from different Chinese geographical regions. Method: This multicenter study enrolled Eastern Asian Chinese patients with abdominal PET/CT scans at 26 imaging centers from six macro-regions across China in 3 years. Age, gender, height, weight, primary disease and its extent on PET scans of the participants were collected as potential predictive factors. Kidney depth on CT, defined as the average of the vertical distances from the posterior skin to the farthest anterior and closest posterior surfaces of each kidney, was measured as the standard reference. The new kidney depth model was constructed using a multiple regression model, and its performance was compared to those of three established models by computing the absolute value of estimation errors in comparison with CT-measured kidney depth. Results: A total of 2502 patients were enrolled and classified into training (n=1653) and testing (n = 849) subsets. In the training subset, two kidney depth models were constructed: Left (cm): 0.013×age+0.117×gender-0.044×height+0.087×weight+7.951, Right (cm): 0.005×age+0.013×gender-0.035×height+0.082×weight+7.266 (weight: kg, height: cm, gender = 0 if female, 1 if male). In the testing subset, one-way analysis of variance showed that the estimation errors of the new models did not significantly differ among the 6 regions. Bland-Altman analysis determined that new equations had lower estimated biases (left: 0.039 cm, right: 0.018 cm) compared with other existing models. Conclusion: The new equations were highly accurate for kidney depth estimation in adults from all over China, with lower estimation errors compared to other established models.

Original languageEnglish (US)
Article number108840
JournalEuropean Journal of Radiology
StatePublished - Mar 2020


  • Age
  • Computed tomography
  • Height
  • Kidney depth
  • Weight

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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  • Cite this

    Li, Q., Pan, Z., Li, Q., Baikpour, M., Cheah, E., Chen, K., Li, W., Song, Y., Zhang, J., Yu, L., Zuo, C., Liu, J., Yang, A., Ding, Z., Li, J., Luo, Y., Li, T., Feng, Y., Yu, S., ... Yang, H. (2020). Development of a generalized model for kidney depth estimation in the Chinese population: A multi-center study. European Journal of Radiology, 124, [108840].