Premium
Comparison of two methods to automatically quantify infarct size in rat isolated hearts following global ischemia and reperfusion (1154.6)
Author(s) -
Riess Matthias,
Shidham Sushrut,
Nabbi Raha,
Gaggl Wolfgang,
LerchGaggl Alexandra
Publication year - 2014
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.28.1_supplement.1154.6
Subject(s) - thresholding , medicine , cardioprotection , software , ischemia , veterans affairs , artificial intelligence , computer science , nuclear medicine , biomedical engineering , cardiology , image (mathematics) , programming language
Infarct size (IS) remains the gold standard to estimate cardiac injury in many animal models. 2,3,5‐triphenyltetrazolium chloride (TTC) staining delineates infarcted from non‐infarcted tissue. Here, we compare manual image analysis to commercially available software using Bayesian differentiation and a newly developed automated freeware algorithm using color thresholding. As part of a study on genome‐dependent cardioprotection we analyzed 855 slices from 156 isolated rat hearts subject to 30/120 min ischemia/reperfusion after different protective treatments. Hearts were cut into 2 mm transverse slices and TTC‐stained, slices scanned on green background and infarcted areas measured manually and automatically by Visiomorph TM and Image J (NIH) whose color threshold T was varied from 125 to 133 to determine the best differentiation for IS. Statistics: linear regression; alpha 0.05. Visiomorph TM correlated well with manual measurements as did Image J where T129 provided the best agreement. IS measurement by either software provides equal results to manual measurements. Both methods enable fast, operator‐independent and reliable IS assessment. Potential shortcomings such as lack of discrimination are offset by significant time‐ and cost‐savings and a better longitudinal resolution by analyzing more slices per heart. Supported by Department of Veterans Affairs (CARA‐026‐10F) and NIH. Grant Funding Source : Supported by Department of Veterans Affairs and NIH.