Vuiblet Vincent, Fere Michael, Gobinet Cyril, Birembaut Philippe, Piot Olivier, Rieu Philippe
Matrice Extracellulaire et Dynamique Cellulaire Unit, Centre National pour la Recherche Scientifique, Unité Mixte de Recherche 7369, and Nephrology and Renal Transplantation Department and Biopathology Laboratory, Centre Hospitalier et Universitaire de Reims, Reims, France
Matrice Extracellulaire et Dynamique Cellulaire Unit, Centre National pour la Recherche Scientifique, Unité Mixte de Recherche 7369, and.
J Am Soc Nephrol. 2016 Aug;27(8):2382-91. doi: 10.1681/ASN.2015050601. Epub 2015 Dec 18.
Renal interstitial fibrosis and interstitial active inflammation are the main histologic features of renal allograft biopsy specimens. Fibrosis is currently assessed by semiquantitative subjective analysis, and color image analysis has been developed to improve the reliability and repeatability of this evaluation. However, these techniques fail to distinguish fibrosis from constitutive collagen or active inflammation. We developed an automatic, reproducible Fourier-transform infrared (FTIR) imaging-based technique for simultaneous quantification of fibrosis and inflammation in renal allograft biopsy specimens. We generated and validated a classification model using 49 renal biopsy specimens and subsequently tested the robustness of this classification algorithm on 166 renal grafts. Finally, we explored the clinical relevance of fibrosis quantification using FTIR imaging by comparing results with renal function at 3 months after transplantation (M3) and the variation of renal function between M3 and M12. We showed excellent robustness for fibrosis and inflammation classification, with >90% of renal biopsy specimens adequately classified by FTIR imaging. Finally, fibrosis quantification by FTIR imaging correlated with renal function at M3, and the variation in fibrosis between M3 and M12 correlated well with the variation in renal function over the same period. This study shows that FTIR-based analysis of renal graft biopsy specimens is a reproducible and reliable label-free technique for quantifying fibrosis and active inflammation. This technique seems to be more relevant than digital image analysis and promising for both research studies and routine clinical practice.
肾间质纤维化和间质活动性炎症是同种异体肾移植活检标本的主要组织学特征。目前,纤维化是通过半定量主观分析进行评估的,并且已经开发了彩色图像分析来提高这种评估的可靠性和可重复性。然而,这些技术无法区分纤维化与组成性胶原蛋白或活动性炎症。我们开发了一种基于傅里叶变换红外(FTIR)成像的自动、可重复技术,用于同时定量同种异体肾移植活检标本中的纤维化和炎症。我们使用49个肾活检标本生成并验证了一个分类模型,随后在166个肾移植上测试了该分类算法的稳健性。最后,我们通过将结果与移植后3个月(M3)的肾功能以及M3和M12之间的肾功能变化进行比较,探讨了使用FTIR成像进行纤维化定量的临床相关性。我们的研究表明,FTIR成像对纤维化和炎症分类具有出色的稳健性,超过90%的肾活检标本通过FTIR成像得到了充分分类。最后,FTIR成像对纤维化的定量与M3时的肾功能相关,M3和M12之间纤维化的变化与同期肾功能的变化密切相关。这项研究表明,基于FTIR的同种异体肾移植活检标本分析是一种可重复且可靠的无标记技术,用于定量纤维化和活动性炎症。该技术似乎比数字图像分析更具相关性,并且在研究和常规临床实践中都很有前景。