Effect of Specular Focal Distance on Endothelial Cell Density Accuracy
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Effect of Specular Focal Distance on Endothelial Cell Density Accuracy
- 1. Effect of Specular Focal Distance on Endothelial Cell Counting Accuracy Jackie Hai and Vivian Xue HAI Laboratories, Inc.
- 2. Special Thanks for providing research cornea
- 3. Purpose Quantify the relationship between focal distance and image distortion in specular microscopy Determine predictive model of cell counting error based on amount of deviance from true endothelial cell shape and size
- 4. High Resolution Analysis Sample Area: 39981.10μm2 (640x480 pixels) Cells Counted: 113 Density: 2826
- 5. High Resolution Analysis Sample Area: 44843.25μm2 (640x480 pixels) Cells Counted: 113 Density: 2520
- 6. Method High resolution specular image of standard calibration lens Baseline pachymetry of 0.000mm established for focused image
- 7. Calibration Lens Baseline focal distance = 0.000mm
- 8. Method Images captured 30μm, 40μm, 50μm, 30 40 50 60μm, 70μm, 80μm, 90μm and 100μm 60 70 80 90 100 from baseline focal distance 10 sample area measurements per image (single blind trial) Determine mean area of each image Simple linear regression model
- 9. Focal Deviance = 0.030mm
- 10. Focal Deviance = 0.060mm
- 11. Focal Deviance = 0.100mm
- 12. Results
- 13. Results Focal Deviance (F) Mean Area (A) F=30μm A=9,666μm2 F=40μm A=9,444μm2 F=50μm A=9,180μm2 F=60μm A=9,055μm2 F=70μm A=8,869μm2 F=80μm A=8,767μm2 F=90μm A=8,694μm2 F=100μm A=8,467μm2
- 14. Results Projected cell counting error
- 15. Endothelial Cell Density 2500 cells/mm2 Focal Measured Difference Deviance Density from Original F=0μm 2500 +0 F=30μm 2615 +115 F=60μm 2750 +250 F=100μm 2953 +453
- 16. Endothelial Cell Density 3000 cells/mm2 Focal Measured Difference Deviance Density from Original F=0μm 3000 +0 F=30μm 3137 +137 F=60μm 3300 +300 F=100μm 3544 +544
- 17. Conclusion Focal Deviance Cell Density Error Negligible 0-29μm (<100 cells/mm2) Non-negligible 30-59μm (>100 cells/mm2) Problematic 60-100μm (>200 cells/mm2)
- 18. Focal Deviance = 0.100mm
- 19. Focal Deviance = 0.060mm
- 20. Focal Deviance = 0.030mm
- 21. Focal Deviance = 0.000mm
- 22. True Endothelial Area Cell Density 42,061μm2 2377 cells/mm2 Focal Measured Endothelial Deviance Area Cell Density F=0μm 42,061μm2 2377 cells/mm2 F=30μm 39,893μm2 2507 cells/mm2 F=60μm 37,792μm2 2646 cells/mm2 F=100μm 36,711μm2 2724 cells/mm2
- 23. Qualitative Properties In Focus Out of Focus Cell borders are bold Cell borders are fuzzy and clearly visible and poorly visible High contrast between Low contrast between cell borders and interiors cell borders and interiors Cell surfaces are even Cell surfaces are uneven and consistently lit and/or have hot spots Cell morphology includes Cell morphology appears regular polygons flattened or stretched
- 24. Focal Deviance = 0.000mm 640x480
- 25. Focal Deviance = 0.030mm 640x480
- 26. Focal Deviance = 0.060mm 640x480
- 27. Focal Deviance = 0.100mm 640x480
- 28. Discussion Minimizing focal deviance is essential to capturing true area and attaining accurate cell density Higher resolution images allow better judgment of focal deviance Lower resolution images obscure focal deviance due to compression
- 29. Focal Deviance = 0.100mm 640x480 160x120
- 30. Focal Deviance = 0.060mm 640x480 160x120
- 31. Focal Deviance = 0.030mm 640x480 160x120
- 32. Focal Deviance = 0.000mm 640x480 160x120
- 33. Recommendations Allow donor tissue to warm up to room temperature Use both coarse and fine Z-knobs to attain optimum focus If it is difficult to focus, change the angle of the chamber or vial
- 34. Recommendations Capture specular images at the highest possible resolution (e.g. 640x480 pixels) Select flat areas of endothelial cells to perform density analysis http://www.hailabs.com/specular-microscopy
Editor's Notes
- Today I’m going to talk about the effect of specular focal distance on endothelial cell counting accuracy. This is a continuation of our specular microscopy series started last year, where as the manufacturer we’ve been asked to give recommended best practices based on scientific methodology.
- We’d like to thank the North Carolina Eye Bank for being very helpful with providing research cornea for this study.
- The purpose of our analysis was two-fold: first, to quantify the relationship between the focal distance of the microscope and any resulting image distortion, and secondly, to formulate a predictive model of cell counting error based on the amount of deviance from true size and shape of the cells.
- It’s common knowledge that accurate cell counts depend on high quality images. We’ve also observed, anecdotally, that samples captured out of focus throw off the cell density when compared to
- the same samples captured in focus. We wanted to take this observation a step further and actually describe the mathematic relationship between focus and cell density.
- Here’s what we did. First, we took a high resolution specular image of a standard calibration lens and established a baseline pachymetry measurement of zero micrometers to represent an image that is totally in focus.
- This is the baseline “zero” calibration image.
- Then, on the same calibration lens, we captured a series of increasingly out of focus images, at 30, 40, 50, 60, 70, 80, 90 and 100 micrometers distance from the baseline. We used a single blind trial to take 10 sample area measurements for each image, for a total of 80 samples. Based on this data, we determined the mean area of a section of the calibration grid at each level of focal distance and plotted a simple linear regression line to model the behavior.
- Here’s an example of the sampling method, performed on a focal deviance of 30 micrometers.
- Here we are at 60 micrometers.
- And 100 micrometers. Note the mean area of 8467 square micrometers for these four blocks is much smaller than the mean area of 10,000 square micrometers for the same four blocks in the baseline “zero” image. This is because as you go out of focus, the image becomes distorted and appears smaller. This shrinking effect carries over to endothelial cells, and I’ll show you examples later in the presentation.
- Here are the results in graphical form, illustrating the relationship between focal deviance and measured area. The mean areas are in blue, and the “best fit” regression line is in red.
- If you look at the numbers, you’ll notice an inverse relationship between focal deviance and area. The more out of focus you go, the lower the area becomes.
- Using the linear regression model, we can extrapolate from focal deviance to area to cell density. This table shows the cell density error at each 10-micrometer increment of focal deviance. The green level represents a smaller error, a difference in density less than 100 cells per square millimeter. The yellow level represents a difference in density greater than 100 cells per square millimeter. And the orange level represents the largest error, a difference in density greater than 200 cells per square millimeter.
- Let’s say you have a cornea with an ECD of 2500. That’s 2500 at zero focal deviance, totally in focus. The same cornea at 30 micrometers focal deviance now has a density reading of over 2600. At 60 micrometers, 2750. And at 100 micrometers out of focus, the density reads over 2950.
- The effect is even more pronounced at higher densities. For a cornea with an ECD of 3000, the difference in density from 0 to 100 micrometers of focus is over 500 cells per square millimeter.
- We can draw the conclusion that the cell density error is negligible for a focal deviance of 0 to 29 micrometers, non-negligible from 30 to 59 micrometers, and problematic from 60 to 100 micrometers and above. That’s enough math, let’s look at a real-life example.
- Here’s a specular image of a donor cornea captured 100 micrometers out of focus.
- Here’s the same cornea, with the same group of cells selected, at 60 micrometers out of focus.