Zhang Jiong, Yu Yuanmeng, Liu Xiaoshuang, Tang Xiong, Xu Feng, Zhang Mingchao, Xie Guotong, Zhang Longjiang, Li Xiang, Liu Zhi-Hong
National Clinical Research Center of Kidney Diseases, Jinling Hospital, Second Military Medical University, Nanjing, China.
Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China.
Kidney Dis (Basel). 2021 Mar;7(2):131-142. doi: 10.1159/000513332. Epub 2021 Feb 12.
Renal fibrosis is a key driver of progression in chronic kidney disease (CKD). Recent advances in diagnostic imaging techniques have shown promising results for the noninvasive assessment of renal fibrosis. However, the specificity and accuracy of these techniques are controversial because they indirectly assess renal fibrosis. This limits fibrosis assessment by imaging in CKD for clinical practice. To validate magnetic resonance imaging (MRI) assessment for fibrosis, we derived representative models by mapping histology-proven renal fibrosis and imaging in CKD.
Ninety-seven adult Chinese CKD participants with histology were studied. The kidney cortex interstitial extracellular matrix volume was calculated by the Aperio ScanScope system using Masson's trichrome slices. The kidney cortex microcirculation was quantitatively assessed by peritubular capillary density using CD34 staining. The imaging techniques included intravoxel incoherent motion diffusion-weighted imaging and magnetic resonance elastography (MRE) imaging. Relevant analyses were performed to evaluate the correlations between MRI parameters and histology variables. Multiple linear regression models were used to describe the relationships between a response variable and other variables. The best-fit lines, which minimize the sum of squared residuals of the multiple linear regression models, were generated.
MRE values were negatively associated with the interstitial extracellular matrix volume ( = -0.397, < 0.001). The best mapping model of extracellular matrix volume with the MRE value and estimated glomerular filtration rate (eGFR) we obtained was as follows: Interstitial extracellular matrix volume = 218.504 - 14.651 × In(MRE) - 18.499 × In(eGFR). DWI-fraction values were positively associated with peritubular capillary density ( = 0.472, < 0.001). The best mapping model of peritubular capillary density with DWI-fraction value and eGFR was as follows: Peritubular capillaries density = 17.914 + 9.403 × (DWI - fraction) + 0.112 × (eGFR).
The study provides histological evidence to support that MRI can effectively evaluate fibrosis in the kidney. These findings picture the graphs of the mapping model from imaging and eGFR into fibrosis, which has significant value for clinical implementation.
肾纤维化是慢性肾脏病（CKD）进展的关键驱动因素。诊断成像技术的最新进展在肾纤维化的无创评估方面显示出了有前景的结果。然而，这些技术的特异性和准确性存在争议，因为它们是间接评估肾纤维化。这限制了在CKD临床实践中通过成像进行纤维化评估。为了验证磁共振成像（MRI）对纤维化的评估，我们通过绘制经组织学证实的肾纤维化和CKD成像得出了代表性模型。
对97名有组织学检查结果的成年中国CKD参与者进行了研究。使用Aperio ScanScope系统通过Masson三色染色切片计算肾皮质间质细胞外基质体积。使用CD34染色通过肾小管周围毛细血管密度定量评估肾皮质微循环。成像技术包括体素内不相干运动扩散加权成像和磁共振弹性成像（MRE）。进行了相关分析以评估MRI参数与组织学变量之间的相关性。使用多元线性回归模型描述响应变量与其他变量之间的关系。生成了使多元线性回归模型的残差平方和最小化的最佳拟合线。
MRE值与间质细胞外基质体积呈负相关（r = -0.397，P < 0.001）。我们获得的细胞外基质体积与MRE值和估计肾小球滤过率（eGFR）的最佳映射模型如下：间质细胞外基质体积 = 218.504 - 14.651 × ln（MRE） - 18.499 × ln（eGFR）。DWI分数值与肾小管周围毛细血管密度呈正相关（r = 0.472，P < 0.001）。肾小管周围毛细血管密度与DWI分数值和eGFR的最佳映射模型如下：肾小管周围毛细血管密度 = 17.914 + 9.403 ×（DWI分数） + 0.112 ×（eGFR）。
该研究提供了组织学证据支持MRI可有效评估肾脏纤维化。这些发现描绘了从成像和eGFR到纤维化的映射模型图，对临床应用具有重要价值。
