BACKGROUND: Judgments about irreversible renal disease are frequently based on the sonographic appearance of the kidneys. However, the sensitivity and specificity of sonography in identifying chronic, irreversible disease have never been determined, and the specific pathologic changes that increase renal cortical echogenicity have not been defined. METHODS: We retrospectively compared sonographic parameters (length, quantitative echogenicity, cortical thickness, and parenchymal thickness) to biopsy findings of glomerular sclerosis, tubular atrophy, interstitial fibrosis, and interstitial inflammation in 207 patients. RESULTS: Echogenicity showed the strongest correlation with all 4 histologic parameters (r= 0.28-0.35). Renal size was significantly correlated with glomerular sclerosis (r=-0.26) and tubular atrophy (r= 0.20). Parenchymal thickness, but not cortical thickness, correlated with tubular atrophy (r=-0.23). By multivariate analysis, tubular atrophy and interstitial inflammation, but not interstitial fibrosis, were significant determinants of cortical echogenicity. Severe chronic disease (>50% sclerosed glomeruli or a score of 3 out of 5 or greater for tubular atrophy or interstitial fibrosis) was present in 69% and 47% of patients with combined renal length <20 cm and >20 cm, respectively (P= <0.05). For cortical echogenicity >1.0 (>liver echogenicity) and </=1.0, the proportions of severe disease were 66% and 30%, respectively (P < 0.001). Severe disease was present in 86% of patients with combined renal length <20 cm and cortical echogenicity >1.0. CONCLUSION: Cortical echogenicity is the sonographic parameter that correlates best with renal histopathology. Although size or echogenicity alone are poor predictors of chronic irreversible disease, the likelihood of treatable disease in small kidneys with increased cortical echogenicity is very low.
BACKGROUND: Judgments about irreversible renal disease are frequently based on the sonographic appearance of the kidneys. However, the sensitivity and specificity of sonography in identifying chronic, irreversible disease have never been determined, and the specific pathologic changes that increase renal cortical echogenicity have not been defined. METHODS: We retrospectively compared sonographic parameters (length, quantitative echogenicity, cortical thickness, and parenchymal thickness) to biopsy findings of glomerular sclerosis, tubular atrophy, interstitial fibrosis, and interstitial inflammation in 207 patients. RESULTS: Echogenicity showed the strongest correlation with all 4 histologic parameters (r= 0.28-0.35). Renal size was significantly correlated with glomerular sclerosis (r=-0.26) and tubular atrophy (r= 0.20). Parenchymal thickness, but not cortical thickness, correlated with tubular atrophy (r=-0.23). By multivariate analysis, tubular atrophy and interstitial inflammation, but not interstitial fibrosis, were significant determinants of cortical echogenicity. Severe chronic disease (>50% sclerosed glomeruli or a score of 3 out of 5 or greater for tubular atrophy or interstitial fibrosis) was present in 69% and 47% of patients with combined renal length <20 cm and >20 cm, respectively (P= <0.05). For cortical echogenicity >1.0 (>liver echogenicity) and </=1.0, the proportions of severe disease were 66% and 30%, respectively (P < 0.001). Severe disease was present in 86% of patients with combined renal length <20 cm and cortical echogenicity >1.0. CONCLUSION: Cortical echogenicity is the sonographic parameter that correlates best with renal histopathology. Although size or echogenicity alone are poor predictors of chronic irreversible disease, the likelihood of treatable disease in small kidneys with increased cortical echogenicity is very low.
Authors: Sarah Faubel; Nayana U Patel; Mark E Lockhart; Melissa A Cadnapaphornchai Journal: Clin J Am Soc Nephrol Date: 2013-11-14 Impact factor: 8.237
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Authors: Eno Hysi; Xiaolin He; Muhannad N Fadhel; Tianzhou Zhang; Adriana Krizova; Michael Ordon; Monica Farcas; Kenneth T Pace; Victoria Mintsopoulos; Warren L Lee; Michael C Kolios; Darren A Yuen Journal: JCI Insight Date: 2020-05-21
Authors: Rishi Patel; Sandra Kang; Ali Kord Valeshabad; Binal N Shah; Jin Han; Michel Gowhari; Robert E Molokie; Karen Xie; James P Lash; Victor R Gordeuk; Santosh L Saraf Journal: Am J Hematol Date: 2019-08-18 Impact factor: 10.047