Quantitative Assessment of Kidney Interstitial Fibrosis Using Optical Spectroscopy Mediated through a Fine Needle Probe.

key pointsIntrarenal elastic-scattering spectroscopy at multiple sites accurately quantifies kidney fibrosis in a CKD rat model. Machine learning analysis predicted the histologic fibrosis grades with >98% accuracy. This method provided a rapid, objective tool for kidney evaluation at the point of care without increasing bleeding complications.

backgroundQuantitative assessment of renal fibrosis on biopsy remains a time-consuming step and is subject to interobserver variability, staining inconsistencies, and sampling errors, given the heterogeneous nature of renal fibrosis. An objective, rapid, and point-of-care evaluation method at multiple locations in the kidney is particularly needed for preimplantation donor kidney assessment, where such limitations can lead to the erroneous nonuse of approximately 20% of grafts. We investigated the accuracy of an orthogonal technique-elastic scattering spectroscopy (ESS)-and compared it against the conventional interstitial fibrosis and tubular atrophy (IFTA) scale.

methodsCKD was induced in rats via an adenine-enriched diet. A customized fine-needle ESS probe was used to acquire spectral data at predetermined intrarenal depths, followed by standard histopathologic scoring. Linear regression was initially used to correlate ESS-derived spectral features with expert-reported IFTA scores. Subsequently, both continuous and categorical random forests (RFs) were implemented to predict fibrosis severity.

resultsRF regression applied to the 300-500 nm spectral range yielded R2 values of 0.925, 0.917, and 0.838 at depths of 1.5, 3 mm (renal cortex), and 5 mm (corticomedullary junction and medulla) depths, respectively. Averaging across depths increased the R2 to 0.961. Corresponding categorical RF accuracies were 98.14%, 96.74%, and 93.49%, with an averaged overall accuracy of 98.61% following five-fold cross-validation.

conclusionsIntrarenal ESS provides a robust, depth-resolved, and quantitative estimation of fibrosis that closely parallels histologic IFTA scoring. Multidepth sampling improves predictive accuracy by minimizing local variability. ESS thus represents a promising, objective, rapid, and scalable adjunct for point-of-care kidney tissue evaluation at multiple points within the kidney without increasing risk of bleeding.