Computer-based Renal Sonographic Image Analysis of Renal Progression among Patients with Chronic Glomerulopathies
Keywords:
Renal ultrasound, Computer-based image analysis, CKD progressionAbstract
Background: Renal sonography is a useful diagnostic imaging procedure already used in chronic glomerulopathies (CGN). Quantitative renal echogenicity has not been formerly evaluated in regard to its capacity to identify patients at risk for progressive renal disease.
Objective: The study aimed to predict renal progression using computer-based image analysis of renal sonographic findings and to explore association between renal sonographic findings and renal histopathologic indices.
Method: Renal sonography was performed on 37 patients with CGN undergoing renal biopsy. Sonographic images were processed and analyzed using computer programs to determine quantitative renal cortical echogenicity. Patients were followed up over a 3-month period to evaluate renal progression correlated with estimated glomerular filtration rate (GFR).
Results: Among patients with CGN undergoing renal biopsy, total renal cortical echogenicity and long axis echogenicity were significantly higher in those patients with renal progression. Using multivariable analysis, high renal echogenicity showed significant association with increased risk of worsening renal function among patients with CGN (HR 1.13, 95%CI 1.01-1.25). Long axis renal echogenicity (AUC 0.71; 95%CI 0.52-0.89), combined with other findings (AUC 0.93; 95%CI 0.84-1.00) achieved a better score predicting CKD progression in the CGN group. Furthermore, renal to liver echogenicity ratio correlated significantly to interstitial fibrosis and tubular atrophy. Renal/liver echogenicity ratio (AUC 0.83; 95%CI 0.69 to 0.97), combined with other findings (AUC 0.95; 95%CI 0.88 to 1.00), achieved a perfect score predicting IFTA > 50% in the CGN group.
Conclusion: Quantitative renal cortical echogenicity using computer-based image analysis might be a useful tool to identify patients with CGN and renal progression related to renal fibrosis
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Chanlerdfa N, Chaiprasert A, Nata N, Tasanavipas P, Varothai N, Thimachai P, Inkong P, Kaewput W, Supasyndh O, Satirapoj B. Computer-based Renal Sonographic Image Analysis on Renal Progression among Patients with Chronic Glomerulopathies. Presentation at the American Society of Nephrology Renal Week, Orlando, FL, USA, November 2022: https://www.asnonline. org/education/kidneyweek/ 2022/program-session-details.aspx? sessId=435090.
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