Background and objectivesRecent developments indicated that functional magnetic resonance imaging (MRI) could potentially provide noninvasive assessment of kidney interstitial fibrosis in patients with kidney diseases, but direct evidence from histopathology is scarce. We aimed to explore the diagnostic utilities of functional MRI for the evaluation of kidney allograft interstitial fibrosis.Design, setting, participants, & measurementsWe prospectively examined 103 kidney transplant recipients who underwent for-cause biopsies and 20 biopsy-proven normal subjects with functional MRI. Histomorphometric analyses of interstitial fibrosis and peritubular capillary densities were performed on digitally scanned Masson’s trichrome- and CD34-stained slides, respectively. The performances of functional MRI to discriminate interstitial fibrosis were assessed by calculating the area under the curve using receiver-operating characteristic curve.ResultsMain pathologic findings in this single-center cohort were representative of common diagnostic entities in the kidney allografts, with rejection (32%) and glomerulonephritides (31%) accounting for the majority of diagnoses. Apparent diffusion coefficient from diffusion-weighted imaging correlated with interstitial fibrosis (ρ=−0.77; P<0.001). Additionally, decreased arterial spin labelings were accompanied by peritubular capillary density reductions (r=0.77; P<0.001). Blood oxygen level–dependent (BOLD) imaging demonstrated cortical hypoxia with increasing interstitial fibrosis (ρ=0.61; P<0.001). The area under the curve for the discrimination of ≤25% versus >25% interstitial fibrosis and ≤50% versus >50% interstitial fibrosis were 0.87 (95% confidence interval [95% CI], 0.79 to 0.93) and 0.88 (95% CI, 0.80 to 0.93) by apparent diffusion coefficient, 0.92 (95% CI, 0.85 to 0.97) and 0.94 (95% CI, 0.87 to 0.98) by arterial spin labeling, 0.81 (95% CI, 0.72 to 0.88) and 0.86 (95% CI, 0.78 to 0.92) by perfusion fraction, 0.79 (95% CI, 0.69 to 0.87) and 0.85 (95% CI, 0.76 to 0.92) by BOLD imaging, respectively.ConclusionsFunctional MRI measurements were strongly correlated with kidney allograft interstitial fibrosis. The performances of functional MRI for discriminating ≤50% versus >50% interstitial fibrosis were good to excellent.

Background The aim of the study is to compare the diagnostic value of models that based on a set of CT texture and non-texture features for differentiating clear cell renal cell carcinomas(ccRCCs) from non-clear cell renal cell carcinomas(non-ccRCCs). Methods A total of 197 pathologically proven renal tumors were divided into ccRCC(n = 143) and non-ccRCC (n = 54) groups. The 43 non-texture features and 296 texture features that extracted from the 3D volume tumor tissue were assessed for each tumor at both Non-contrast Phase, NCP; Corticomedullary Phase, CMP; Nephrographic Phase, NP and Excretory Phase, EP. Texture-score were calculated by the Least Absolute Shrinkage and Selection Operator (LASSO) to screen the most valuable texture features. Model 1 contains the three most distinctive non-texture features with p < 0.001, Model 2 contains texture scores, and Model 3 contains the above two types of features. Results The three models shown good discrimination of the ccRCC from non-ccRCC in NCP, CMP, NP, and EP. The area under receiver operating characteristic curve (AUC)values of the Model 1, Model 2, and Model 3 in differentiating the two groups were 0.748–0.823, 0.776–0.887 and 0.864–0.900, respectively. The difference in AUC between every two of the three Models was statistically significant (p < 0.001). Conclusions The predictive efficacy of ccRCC was significantly improved by combining non-texture features and texture features to construct a combined diagnostic model, which could provide a reliable basis for clinical treatment options.

<b><i>Background:</i></b> 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. <b><i>Methods:</i></b> 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. <b><i>Results:</i></b> MRE values were negatively associated with the interstitial extracellular matrix volume (<i>Rho</i> = −0.397, <i>p</i> &#x3c; 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 (<i>Rho</i> = 0.472, <i>p</i> &#x3c; 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). <b><i>Conclusions:</i></b> 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.