Literature DB >> 15598325

Renal arterial resistance index and computerized quantification of fibrosis as a combined predictive tool in chronic allograft nephropathy.

Lars Pape1, Michael Mengel, Gisela Offner, Michael Melter, Jochen H H Ehrich, Juergen Strehlau.   

Abstract

The renal arterial resistance index (RI) and the PicroSirius-Red stained cortical fractional interstitial fibrosis volume (VintFib) proved to be two independent methods that are reliable predictive factors of poor renal allograft outcome. No data have been published, which define the correlation between ultrasound assessment and quantitative morphologic changes. Renal biopsies were performed in 56 children according to increases in s-creatinine >10%. VintFib was calculated by computerized image analysis. RI was determined in two segmental arteries, 1 yr after transplantation and at the time-point of biopsy. RIs 1 yr after transplantation correlated significantly with RIs at time of biopsy (r = 0.58, p < 0.001). VintFib was higher in children with a RI = 80 than in children with a RI < 80 (mean VintFib = 9.5 +/- 3.2% vs. 5.2 +/- 5.1%, p = 0.004). In children with VintFib > 10%, the mean RI was 77 +/- 5 compared with 69 +/- 6 in patients with VintFib < 10% (p = 0.0002). The highest positive predictive value to detect the risk of decline of GFR at 2 yr after biopsy was 98% when an RI = 80% was associated with a VintFib > 10%. For VintFib > 10% or RI = 80 alone, it was 87% or 67%, respectively. The combined measurement of RI and VintFib is a reliable predictive tool for the risk of developing long-term graft dysfunction after kidney transplantation.

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Year:  2004        PMID: 15598325     DOI: 10.1111/j.1399-3046.2004.00229.x

Source DB:  PubMed          Journal:  Pediatr Transplant        ISSN: 1397-3142


  4 in total

Review 1.  Renal interstitial fibrosis: mechanisms and evaluation.

Authors:  Alton B Farris; Robert B Colvin
Journal:  Curr Opin Nephrol Hypertens       Date:  2012-05       Impact factor: 2.894

Review 2.  Artificial intelligence and algorithmic computational pathology: an introduction with renal allograft examples.

Authors:  Alton B Farris; Juan Vizcarra; Mohamed Amgad; Lee A D Cooper; David Gutman; Julien Hogan
Journal:  Histopathology       Date:  2021-03-08       Impact factor: 5.087

Review 3.  What is the best way to measure renal fibrosis?: A pathologist's perspective.

Authors:  Alton B Farris; Charles E Alpers
Journal:  Kidney Int Suppl (2011)       Date:  2014-11

Review 4.  The Landscape of Digital Pathology in Transplantation: From the Beginning to the Virtual E-Slide.

Authors:  Ilaria Girolami; Anil Parwani; Valeria Barresi; Stefano Marletta; Serena Ammendola; Lavinia Stefanizzi; Luca Novelli; Arrigo Capitanio; Matteo Brunelli; Liron Pantanowitz; Albino Eccher
Journal:  J Pathol Inform       Date:  2019-07-01
  4 in total

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