Abstract: FR-PO908
Computer-Based Renal Sonographic Image Analysis on Renal Progression in Patients With Chronic Glomerulopathies
Session Information
- CKD: Epidemiology, Risk Factors, Prevention - II
November 04, 2022 | Location: Exhibit Hall, Orange County Convention Center‚ West Building
Abstract Time: 10:00 AM - 12:00 PM
Category: CKD (Non-Dialysis)
- 2201 CKD (Non-Dialysis): Epidemiology‚ Risk Factors‚ and Prevention
Authors
- Chanlerdfa, Nuntanutch, Phramongkutklao College of Medicine, Bangkok, Thailand
- Chaiprasert, Amnart, Phramongkutklao College of Medicine, Bangkok, Thailand
- Nata, Naowanit, Phramongkutklao College of Medicine, Bangkok, Thailand
- Tasanavipas, Pamila, Phramongkutklao College of Medicine, Bangkok, Thailand
- Varothai, Narittaya, Phramongkutklao College of Medicine, Bangkok, Thailand
- Thimachai, Paramat, Phramongkutklao College of Medicine, Bangkok, Thailand
- Inkong, Pitchamon, Phramongkutklao College of Medicine, Bangkok, Thailand
- Kaewput, Wisit, Phramongkutklao College of Medicine, Bangkok, Thailand
- Supasyndh, Ouppatham, Phramongkutklao College of Medicine, Bangkok, Thailand
- Satirapoj, Bancha, Phramongkutklao College of Medicine, Bangkok, Thailand
Background
Renal sonography is useful diagnostic imaging procedure in chronic glomerulopathies. Quantitative renal echogenicity has not been formerly evaluated regarding its capacity to identify patients at risk for progressive renal disease.
Methods
Renal sonography was performed in 79 patients with chronic kidney disease (CKD) including 37 patients with chronic glomerulonephritis (CGN) undergoing renal biopsy and 42 patients with other glomerulopathies. Sonographic images were processing and analysis by computer programs to determine quantitative renal cortical echogenicity. Patients were followed during a three-month period to evaluated renal progression with estimated glomerular filtration rate (GFR).
Results
Among 79 patients, 31 (39.24%) patients had renal progression. In patients with CGN undergoing renal biopsy, total renal cortical echogenicity and long axis echogenicity was significantly higher than patients without renal progression. In the multivariable analysis, high renal echogenicity remained significantly associated with increased risk of worsening renal function in CGN patients (HR 1.13, 95%CI 1.01-1.25). Long axis renal echogenicity (AUC 0.71; 95%CI 0.52 to 0.89), combining with other findings (AUC 0.93; 95%CI 0.84 to 1.00) achieved a better score predicting CKD progression in CGN group. Furthermore, renal to liver echogenicity ratio was significantly correlated with interstitial fibrosis and tubular atrophy. Renal/liver echogenicity ratio (AUC 0.83; 95%CI 0.69 to 0.97), combining with other findings (AUC 0.95; 95%CI 0.88 to 1.00) achieved a perfect score predicting IFTA>50% in CGN group.
Conclusion
Quantitative renal cortical echogenicity by computer based image analysis might be a useful tool to identify CGN patients with renal progression and related to renal fibrosis.