Imaging and Quantification of Endothelial Cell Loss in Eye Bank Prepared DMEK Grafts Using Trainable Segmentation Software

Abstract Purpose: To improve accuracy and efficiency in quantifying the endothelial cell loss (ECL) in eye bank preparation of corneal endothelial grafts. Methods: Eight cadaveric corneas were subjected to Descemet Membrane Endothelial Keratoplasty (DMEK) preparation. The endothelial surfaces were stained with a viability stain, calcein AM dye (CAM) and then captured by a digital camera. The ECL rates were quantified in these images by three separate readers using trainable segmentation, a plug-in feature from the imaging software, Fiji. Images were also analyzed by Adobe Photoshop for comparison. Mean times required to process the images were measured between the two modalities. Results: The mean ECL (with standard deviation) as analyzed by Fiji was 22.5% (6.5%) and Adobe was 18.7% (7.0%; p = 0.04). The mean time required to process the images through the two different imaging methods was 19.9 min (7.5) for Fiji and 23.4 min (12.9) for Adobe (p = 0.17). Conclusions: Establishing an accurate, efficient and reproducible means of quantifying ECL in graft preparation and surgical techniques can provide insight to the safety, long-term potential of the graft tissues as well as provide a quality control measure for eye banks and surgeons. Trainable segmentation in Fiji software using CAM is a novel approach to measuring ECL that captured a statistically significantly higher percentage of ECL comparable to Adobe and was more accurate in standardized testing. Interestingly, ECL as determined using both methods in eye bank-prepared DMEK grafts exceeded 18% on average.