A technical challenge in translational models of kidney injury is determination of the extent of cell death. Histologic sections are commonly analyzed by area morphometry or unbiased stereology, but stereology requires specialized equipment. Therefore, a challenge to rigorous quantification would be addressed by an unbi ased st ereol ogy t ool wi t h reduced equi pment dependence. We hypothesized that it would be feasible to build a novel software component which would facilitate unbiased stereologic quantification on scanned slides, and that unbiased stereology would demonstrate greater precision and decreased bias compared with 2D morphometry. Material and methods. We developed a macro for the widely used image analysis program, Image J, and per f or med car di ac ar r est wi t h car di opul monar y resuscitation (CA/CPR, a model of acute cardiorenal syndrome) in mice. Fluorojade-B stained kidney sections were analyzed using three methods to quantify cell death: gold standard stereology using a controlled stage and commer ci al l y-avai l abl e sof t war e, unbi ased st er eol ogy usi ng t he novel I mageJ macr o, and quantitative 2D morphometry also using the novel macro. Results. There was strong agreement between both methods of unbiased stereology (bias-0.004±0.006 with 95% l i mi t s of agr eement-0. 015 t o 0. 007). 2D mor phomet r y demonst r at ed poor agr eement and significant bias compared to either method of unbiased stereology. Conclusion. Unbiased stereology is facilitated by a novel macro for ImageJ and results agree with those obtained using gold-standard methods. Automated 2D morphometry overestimated tubular epithelial cell death and correlated modestly with values obtained from unbiased stereology. These results support widespread use of unbiased stereology for analysis of histologic outcomes of injury models.
- Acute kidney injury
- Cavalieri principle
- Tubular necrosis
ASJC Scopus subject areas
- Pathology and Forensic Medicine