A graphic user interface for the evaluation of knee osteoarthritis (GEKO): an open-source tool for histological grading.

Summary Objective In osteoarthritis (OA) models, histology is commonly used to evaluate the severity of joint damage. Unfortunately, semi-quantitative histological grading systems include some level of subjectivity, and quantitative grading systems can be tedious to implement. The objective of this work is to introduce an open source, graphic user interface (GUI) for quantitative grading of knee OA. Methods Inspired by the 2010 OARSI histopathology recommendations for the rat, our laboratory has developed a G UI for the e valuation of k nee O A, nicknamed GEKO. In this work, descriptions of the quantitative measures acquired by GEKO are presented and measured in 42 histological images from a rat knee OA model. Using these images, across-session and within-session reproducibility for individual graders is evaluated, and inter-grader reliability across different levels of OA severity is also assessed. Results GEKO allowed histological images to be quantitatively scored in less than 1 min per image. In addition, intra-class coefficients (ICCs) were largely above 0.8 for across-session reproducibility, within-session reproducibility, and inter-grader reliability. These data indicate GEKO aided in the reproducibility and repeatability of quantitative OA grading across graders and grading sessions. Conclusions Our data demonstrate GEKO is a reliable and efficient method to calculate quantitative histological measures of knee OA in a rat model. GEKO reduced quantitative grading times relative to manual grading systems and allowed grader reproducibility and repeatability to be easily assessed within a grading session and across time. Moreover, GEKO is being provided as a free, open-source tool for the OA research community. [ABSTRACT FROM AUTHOR]