Affiliations: Department of Pulmonary Diseases, Institute for Cardiovascular Research, VU University Medical Center, Amsterdam, The Netherlands | Department of Pathology, Institute for Cardiovascular Research, VU University Medical Center, Amsterdam, The Netherlands | Department of Physiology, Institute for Cardiovascular Research, VU University Medical Center, Amsterdam, The Netherlands
Note: [] Corresponding author: Dr. J.A.M. Beliën, PhD, Department of Pathology, VU University Medical Center Amsterdam, Room 0 E 50, P.O. Box 7057, 1007 MB Amsterdam, The Netherlands. Tel.: +31 20 444 4025; Fax: +31 20 444 2964; E-mail: JAM.Belien@ vumc.nl.
Abstract: Background: Fibrosis is associated with various cardiac pathologies and dysfunction. Current quantification methods are time-consuming and laborious. We describe a semi-automated quantification technique for myocardial fibrosis and validated this using traditional methods. Methods: Pulmonary Hypertension (PH) was induced in adult Wistar rats by subcutaneous monocrotaline (MCT) injection (40 mg/kg). Cryosections of myocardial tissue (5 μm) of PH rats (n=9) and controls (n=9) were stained using Picrosirius red and scanned with a digital microscopic Mirax slide scanner. From these sections 21 images were taken randomly of each heart. Using ImageJ software a macro for automated image analysis of the amount of fibrosis was developed. For comparison, fibrosis was quantified using traditional polarisation microscopy. Both methods were correlated and validated against stereology as the gold standard. Furthermore, the method was tested in paraffin-embedded human tissues. Results: Automated analysis showed a significant increase of fibrosis in PH hearts vs. control. Automated analysis correlated with traditional polarisation and stereology analysis (r2=0.92 and r2=0.95, respectively). In human heart, lungs, kidney and liver, a similar correlation with stereology (r2=0.91) was observed. Time required for automated analysis was 22 and 33% of the time needed for stereology and polarisation analysis, respectively. Conclusion: Automated quantification of fibrosis is feasible, objective and time-efficient.
