Tubular and Glomerular Size by Cortex Depth as Predictor of Progressive CKD after Radical Nephrectomy for Tumor

Clinical Relevance of Computationally Derived Tubular Features: Spatial Relationships and the Development of Tubulointerstitial Scarring in MCD/FSGS

Background

Visual scoring of tubular damage has limitations in capturing the full spectrum of structural changes and prognostic potential. We investigate if computationally quantified tubular features can enhance prognostication and reveal spatial relationships with interstitial fibrosis.

Methods

Deep-learning and image-processing-based segmentations were employed in N=254/266 PAS-WSIs from the NEPTUNE/CureGN datasets (135/153 focal segmental glomerulosclerosis and 119/113 minimal change disease) for: cortex, tubular lumen (TL), epithelium (TE), nuclei (TN), and basement membrane (TBM). N=104 pathomic features were extracted from these segmented tubular substructures and summarized at the patient level using summary statistics. The tubular features were quantified across the biopsy and in manually segmented regions of mature interstitial fibrosis and tubular atrophy (IFTA), pre-IFTA and non-IFTA in the NEPTUNE dataset. Minimum Redundancy Maximum Relevance was used in the NEPTUNE dataset to select features most associated with disease progression and proteinuria remission. Ridge-penalized Cox models evaluated their predictive discrimination compared to clinical/demographic data and visual-assessment. Models were evaluated in the CureGN dataset.

Results

N=9 features were predictive of disease progression and/or proteinuria remission. Models with tubular features had high prognostic accuracy in both NEPTUNE and CureGN datasets and increased prognostic accuracy for both outcomes (5.6%-7.7% and 1.6%-4.6% increase for disease progression and proteinuria remission, respectively) compared to conventional parameters alone in the NEPTUNE dataset. TBM thickness/area and TE simplification progressively increased from non- to pre- and mature IFTA.

Conclusions

Previously under-recognized, quantifiable, and clinically relevant tubular features in the kidney parenchyma can enhance understanding of mechanisms of disease progression and risk stratification.

The histomorphology of the senescent kidney - the clinical relevance of specimen and biopsy findings in the elderly native kidneys

PURPOSE OF REVIEW

Renal pathology is crucial in diagnosing the ageing kidney. Recent technological advances enabled high-resolution molecular investigations into the complex mechanisms of ageing and senescence.

RECENT FINDINGS

The pathological analysis of large kidney tissue collections coupled with computer-assisted morphometry contributed to the establishment of age-related reference values for glomerular or vascular sclerosis, interstitial fibrosis, and tubular atrophy. Furthermore, new high-throughput proteomic and transcriptomic platforms have entered the field of pathology. When coupled with morphology information, these techniques facilitated the study of extracellular matrix modifications and the senescent immune system in the ageing kidney. Finally, iatrogenic complications are now frequent indications for diagnostic kidney biopsies in older patients, potentially accelerating kidney senescence.

SUMMARY

Recent pathology literature supports identifying and prognosticating sclerosing processes in ageing kidneys.

The role of desmoglein-2 in kidney disease

Desmosomes are multi-protein cell-cell adhesion structures supporting cell stability and mechanical stress resilience of tissues, best described in skin and heart. The kidney is exposed to various mechanical stimuli and stress, yet little is known about kidney desmosomes. In healthy kidneys, we found desmosomal proteins located at the apical-junctional complex in tubular epithelial cells. In four different animal models and patient biopsies with various kidney diseases, desmosomal components were significantly upregulated and partly miss-localized outside of the apical-junctional complexes along the whole lateral tubular epithelial cell membrane. The most upregulated component was desmoglein-2 (Dsg2). Mice with constitutive tubular epithelial cell-specific deletion of Dsg2 developed normally, and other desmosomal components were not altered in these mice. When challenged with different types of tubular epithelial cell injury (unilateral ureteral obstruction, ischemia-reperfusion, and 2,8-dihydroxyadenine crystal nephropathy), we found increased tubular epithelial cell apoptosis, proliferation, tubular atrophy, and inflammation compared to wild-type mice in all models and time points. In vitro, silencing DSG2 via siRNA weakened cell-cell adhesion in HK-2 cells and increased cell death. Thus, our data show a prominent upregulation of desmosomal components in tubular cells across species and diseases and suggest a protective role of Dsg2 against various injurious stimuli.

Recognition of intraglomerular histological features with deep learning in protocol transplant biopsies and their association with kidney function and prognosis

Background

The Banff Classification may not adequately address protocol transplant biopsies categorized as normal in patients experiencing unexplained graft function deterioration. This study seeks to employ convolutional neural networks to automate the segmentation of glomerular cells and capillaries and assess their correlation with transplant function.

Methods

A total of 215 patients were categorized into three groups. In the Training cohort, glomerular cells and capillaries from 37 patients were manually annotated to train the networks. The Test cohort (24 patients) compared manual annotations vs automated predictions, while the Application cohort (154 protocol transplant biopsies) examined predicted factors in relation to kidney function and prognosis.

Results

In the Test cohort, the networks recognized histological structures with Precision, Recall, F-score and Intersection Over Union exceeding 0.92, 0.85, 0.89 and 0.74, respectively. Univariate analysis revealed associations between the estimated glomerular filtration rate (eGFR) at biopsy and relative endothelial area (r = 0.19, P = .027), endothelial cell density (r = 0.20, P = .017), mean parietal epithelial cell area (r = -0.38, P < .001), parietal epithelial cell density (r = 0.29, P < .001) and mesangial cell density (r = 0.22, P = .010). Multivariate analysis retained only endothelial cell density as associated with eGFR (Beta = 0.13, P = .040). Endothelial cell density (r = -0.22, P = .010) and mean podocyte area (r = 0.21, P = .016) were linked to proteinuria at biopsy. Over 44 ± 29 months, 25 patients (16%) reached the primary composite endpoint (dialysis initiation, or 30% eGFR sustained decline), with relative endothelial area, mean endothelial cell area and parietal epithelial cell density below medians linked to this endpoint [hazard ratios, respectively, of 2.63 (P = .048), 2.60 (P = .039) and 3.23 (P = .019)].

Conclusion

This study automated the measurement of intraglomerular cells and capillaries. Our results suggest that the precise segmentation of endothelial and epithelial cells may serve as a potential future marker for the risk of graft loss.

Morphometric analysis of chronicity on kidney biopsy: a useful prognostic exercise

Chronic changes on kidney biopsy specimens include increasing amounts of arteriosclerosis, glomerulosclerosis, interstitial fibrosis and tubular atrophy, enlarged nephron size, and reduced nephron number. These chronic changes are difficult to accurately assess by visual inspection but are reasonably quantified using morphometry. This review describes the various patient populations that have undergone morphometric analysis of kidney biopsies. The common approaches to morphometric analysis are described. The chronic kidney disease outcomes associated with various chronic changes by morphometry are also summarized. Morphometry enriches the characterization of chronicity on a kidney biopsy and this can supplement the pathologist's diagnosis. Artificial intelligence image processing tools are needed to automate the annotations needed for practical morphometric analysis of kidney biopsy specimens in routine clinical care.