Computer-assisted quantification of fibrosis in chronic allograft nephropaty by picosirius red-staining: a new tool for predicting long-term graft function.
BACKGROUND
Chronic allograft nephropathy (CAN) has become the predominant limiting factor for long-term transplant survival. A cardinal histomorphologic correlate for CAN is interstitial fibrosis. Currently, no method has been established in routine use that reliably quantifies the extent of interstitial fibrosis in renal grafts. We have used staining with picrosirius red followed by computerized image analysis to study the correlation between graft fibrosis and future development of glomerular filtration rate (GFR) in a group of children with advanced CAN.


METHODS
Renal biopsies were performed in 56 children (mean age, 13.7+/-3.6 years) after a mean period of 4.6+/-3.1 years after transplantation because of significant increases in serum creatinine. All biopsy specimens were stained with picrosirius red. The magnitude of fibrotic tissue was calculated by computerized image analysis. Linear regression analysis was performed correlating the intensity of graft fibrosis and the changes in the GFR at the time points of renal biopsy and 2 years later.


RESULTS
There was a significant positive correlation (r=0.62, P<0.001) between the picrosirius red-stained cortical fractional interstitial fibrosis volume (V(intFib)) and the decrease of GFR within 2 years postrenal biopsy. When V(intFib) was below 5%, 82% of the patients had an increase in GFR within 2 years. Ninety-three percent of the patients with greater than 10% of fibrosis experienced a worsening renal function after 2 years. When comparing patients with stable GFR with patients having a decrease in GFR, a highly significant difference in V(intFib) was found (P=0.008).


CONCLUSIONS
The quantitative measurement of fibrosis by picrosirius red staining appears to be a useful prognostic indicator for estimating long-term graft function in CAN and may provide an easy, fast, and inexpensive tool helpful for treatment decisions in patients developing CAN.
D000293:Adolescent; D001391:Azo Compounds; D002648:Child; D002908:Chronic Disease; D004396:Coloring Agents; D003404:Creatinine / Q000097:blood; D005260:Female; D005355:Fibrosis; D006084:Graft Rejection / Q000453:epidemiology / Q000473:pathology; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D016030:Kidney Transplantation / Q000473:pathology* / Q000502:physiology; D008297:Male; D011237:Predictive Value of Tests; D011379:Prognosis; D012044:Regression Analysis; D014184:Transplantation, Homologous / Q000473:pathology; D016896:Treatment Outcome
D001391:Azo Compounds; D004396:Coloring Agents; D003404:Creatinine