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Farhat I, Maréchal E, Calmo D, Ansart M, Paindavoine M, Bard P, Tarris G, Ducloux D, Felix SA, Martin L, Tinel C, Gibier JB, Funes de la Vega M, Rebibou JM, Bamoulid J, Legendre M. Recognition of intraglomerular histological features with deep learning in protocol transplant biopsies and their association with kidney function and prognosis. Clin Kidney J 2024; 17:sfae019. [PMID: 38370429 PMCID: PMC10873504 DOI: 10.1093/ckj/sfae019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Indexed: 02/20/2024] Open
Abstract
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.
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Affiliation(s)
- Imane Farhat
- Department of Nephrology, CHU Dijon, Dijon, France
| | | | - Doris Calmo
- Department of Nephrology, CHU Besançon, Besançon, France
| | - Manon Ansart
- LEAD-CNRS, UMR 5022, Université de Bourgogne, Dijon, France
| | | | - Patrick Bard
- LEAD-CNRS, UMR 5022, Université de Bourgogne, Dijon, France
| | | | - Didier Ducloux
- Department of Nephrology, CHU Besançon, Besançon, France
- Etablissement Français du sang, Besançon, France
| | | | | | - Claire Tinel
- Department of Nephrology, CHU Dijon, Dijon, France
- Etablissement Français du sang, Besançon, France
| | | | | | - Jean-Michel Rebibou
- Department of Nephrology, CHU Dijon, Dijon, France
- Etablissement Français du sang, Besançon, France
| | - Jamal Bamoulid
- Department of Nephrology, CHU Besançon, Besançon, France
- Etablissement Français du sang, Besançon, France
| | - Mathieu Legendre
- Department of Nephrology, CHU Dijon, Dijon, France
- LEAD-CNRS, UMR 5022, Université de Bourgogne, Dijon, France
- Etablissement Français du sang, Besançon, France
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