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基于大样本CT数据的中国儿童肾脏结构参数正常参考值及估算公式

The normal reference values and estimation formulae of renal structural parameters in Chinese children based on large-sample CT data.

作者信息

Qin Yong, Liu En, Ni Xiaoying, Huang Zhongxin, Tian Lu, He Xiaoya, Cai Jinhua, Li Qiu

机构信息

Department of Radiology, Ministry of Education Key Laboratory of Child Development and Disorders, National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation Base of Child Development and Critical Disorders, Chongqing Key Laboratory of Pediatrics, Children's Hospital of Chongqing Medical University, Chongqing, China.

Department of Gastroenterology, Second Affiliated Hospital of Army Medical University, Chongqing, China.

出版信息

Front Pediatr. 2023 Jul 17;11:1174310. doi: 10.3389/fped.2023.1174310. eCollection 2023.

DOI:10.3389/fped.2023.1174310
PMID:37528878
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10388191/
Abstract

PURPOSE

Our aim was to investigate the normal reference value and to establish an estimation formulae for renal structural parameters (RSPs) based on large-sample CT data of Chinese children, which can provide a data reference for the clinical assessment of kidney development and diseases in Chinese children.

MATERIALS AND METHODS

A total of 438 children aged 0-17 years with normal renal CT images and basic indices were continuously collected. The bilateral RSP, including renal length (RL), renal width (RW), renal thickness (RT), renal volume (RV), renal cortical thickness (RCT), renal artery diameter (RAD) and renal CT value, were measured. Kendall's rank correlation was used to analyze the correlation between RSP and sex. Pearson's correlation was used to analyze the correlation between RSP and age, height and weight. Differences in the RSP of bilateral kidneys were analyzed via a paired samples t-test. Multiple linear regression was used to analyze the multivariate relationships between RSP and basic indices and establish the estimation formula of RSP.

RESULTS

The RSP of normal kidneys showed a dynamic increasing trend with age, except for the CT values. The reference value ranges (95% confidence interval) of normal RSP for each age group were determined. Pearson correlation analysis demonstrated strong correlations between RSP (RL, RW, RT, RV, RCT and, RAD) and basic indices (age, height and, weight), with height exhibiting the greatest correlation coefficient, followed by age or weight. Kendall's analysis showed that none of the RSPs were correlated with sex. The RL, RW, RV and RAD of the left kidney were larger than those of the right kidney, and the RT and RCT of the right kidney exhibited opposite results. Multiple linear regression analysis demonstrated a significant linear relationship between the RSP (RL, RW, RT, RV and, RCT) and the variables of the basic indices. The estimation formulae for calculating the RSP were established.

CONCLUSION

This is the first Chinese study to report of the trends, normal reference values and estimation formulae of normal RSP based on large-sample CT data. These results can provide data references for assessing adequate kidney growth or disease damage in Chinese children.

摘要

目的

本研究旨在基于中国儿童的大样本CT数据,探讨肾脏结构参数(RSPs)的正常参考值并建立估算公式,为中国儿童肾脏发育及疾病的临床评估提供数据参考。

材料与方法

连续收集438例0至17岁肾脏CT图像及基本指标正常的儿童。测量双侧RSP,包括肾长(RL)、肾宽(RW)、肾厚(RT)、肾体积(RV)、肾皮质厚度(RCT)、肾动脉直径(RAD)及肾脏CT值。采用肯德尔等级相关分析RSP与性别的相关性。采用皮尔逊相关分析RSP与年龄、身高和体重的相关性。通过配对样本t检验分析双侧肾脏RSP的差异。采用多元线性回归分析RSP与基本指标的多变量关系并建立RSP估算公式。

结果

除CT值外,正常肾脏的RSP随年龄呈动态增加趋势。确定了各年龄组正常RSP的参考值范围(95%置信区间)。皮尔逊相关分析表明,RSP(RL、RW、RT、RV、RCT和RAD)与基本指标(年龄、身高和体重)之间存在强相关性,其中身高的相关系数最大,其次是年龄或体重。肯德尔分析表明,所有RSP均与性别无关。左肾的RL、RW、RV和RAD大于右肾,而右肾的RT和RCT则相反。多元线性回归分析表明,RSP(RL、RW、RT、RV和RCT)与基本指标变量之间存在显著线性关系。建立了计算RSP的估算公式。

结论

本研究是首次基于大样本CT数据报道中国正常RSP的趋势、正常参考值及估算公式的研究。这些结果可为评估中国儿童肾脏的正常生长或疾病损伤提供数据参考。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9c2a/10388191/9ab6b4df19a2/fped-11-1174310-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9c2a/10388191/4f0d74c4f75d/fped-11-1174310-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9c2a/10388191/da1903c41e85/fped-11-1174310-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9c2a/10388191/c79484c408a6/fped-11-1174310-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9c2a/10388191/b61c236a60f7/fped-11-1174310-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9c2a/10388191/47ff7129390e/fped-11-1174310-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9c2a/10388191/d1b8bff79413/fped-11-1174310-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9c2a/10388191/9ab6b4df19a2/fped-11-1174310-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9c2a/10388191/4f0d74c4f75d/fped-11-1174310-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9c2a/10388191/da1903c41e85/fped-11-1174310-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9c2a/10388191/c79484c408a6/fped-11-1174310-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9c2a/10388191/b61c236a60f7/fped-11-1174310-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9c2a/10388191/47ff7129390e/fped-11-1174310-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9c2a/10388191/d1b8bff79413/fped-11-1174310-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9c2a/10388191/9ab6b4df19a2/fped-11-1174310-g007.jpg

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