Validation of histopathological chronicity scores in native kidney biopsies using light microscopy and digital morphometry for predicting renal outcome

Quantitative assessment of chronicity changes in native kidney biopsies offer valuable insights in to disease prognosis, despite the strength of qualitative information. Yet, standardization and reproducibility remain challenging. The present study aims to assess and compare the prognostic utility and reproducibility of two chronicity scoring systems based on light microscopy and whole slide imaging with morphometry and also to evaluate the prognostic utility of structural measurements: cortical non-sclerotic glomerular (NSG) density and NSG area/volume. We designed a retrospective longitudinal study involving 101 adult and paediatric patients who underwent native kidney biopsies. Chronicity scoring was performed using two semi-quantitative methods: Method 1 (method proposed in PMID: 28314581) and Method 2 (method proposed in PMID: 32516862), under light microscopy as well as on whole-slide scanned images, and assessed for prognostic utility. Kidney-Failure-Risk-Equation (KFRE) was employed in combination with chronicity-scoring-methods and assessed for predictive capability. Interobserver reproducibility for the two chronicity methods was studied among three renal pathologists. Structural measurements were performed on whole-slide- scanned-images. Both the chronicity scoring methods significantly predicted decline in estimated glomerular filtration rate (eGFR) and persistent need for renal replacement therapy in follow-up. Method 1 combined with KFRE, outperformed Method 2 in predicting renal survival. Method 2 however showed higher interobserver reproducibility. Combined KFRE plus histopathological scoring methods showed better predictive accuracy. The study validates the precision of chronicity scoring using whole slide scanned images. The morphometric structural measurements showed significant correlations with follow-up eGFR, thereby providing supplementary prognostic information.