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Curr Eye Res. 2014 Sep;39(9):894-901. doi: 10.3109/02713683.2014.887120. Epub 2014 Mar 3.

Imaging and quantification of endothelial cell loss in eye bank prepared DMEK grafts using trainable segmentation software.

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Casey Eye Institute, Oregon Health and Science University , Portland, OR , USA and.



To improve accuracy and efficiency in quantifying the endothelial cell loss (ECL) in eye bank preparation of corneal endothelial grafts.


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.


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).


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.


Corneal transplant surgery; Descemet Membrane Endothelial Keratoplasty; endothelial cell loss; eye bank; trainable segmentation

[Indexed for MEDLINE]

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