Date post: | 25-Jun-2015 |
Category: |
Health & Medicine |
Upload: | hai-labs |
View: | 1,930 times |
Download: | 2 times |
Effect of True Area Sample Size on Variability in Endothelial Cell Density
(ECD) Results
Jackie Hai and Vivian XueHAI Laboratories, Inc.
Purpose
Evaluate the effect of sample area size on ECD measurement results and variability
Determine a recommended minimum sample size by comparing the results of cell counts performed within larger areas vs smaller areas
Sample Selection Criteria True area required for all samples
Images captured at high resolution
Low instances of pathology or abnormality
Random selection with variety of ECD, polymegathism, pleomorphism within normal range
Untrue Area: excessive concave curvature (circled)
Untrue Area: incorrect focal depth (cells out of focus)
True Area: flat, focused image with clear cell borderlines
True Area: flat, focused image with clear cell borderlines
Low Resolution Thumbnails(160x120 pixels)
Sample Area: 39981.10μm2
Cells Counted: 113Density: 2826
High Resolution Analysis(640x480 pixels)
Sample Area: 44843.25μm2
Cells Counted: 113Density: 2520
High Resolution Analysis(640x480 pixels)
Sample Selection Criteria True area required for all samples
Images captured at high resolution
Low instances of pathology or abnormality
Random selection with variety of ECD, polymegathism, pleomorphism within normal range
Counting Method
Variable frame counting method
Single-field (40,000μm2 – 60,000μm2)
Multiple-field (20,000μm2 – 25,000μm2)
Single-field variable frame count (60,000μm2)
HAI CAS / EB 2.10
Multiple-field variable frame count 1 of 3 (23,000μm2)
HAI CAS / EB 2.10
Multiple-field variable frame count 2 of 3 (22,000μm2)
HAI CAS / EB 2.10
Multiple-field variable frame count 3 of 3 (22,500μm2)
HAI CAS / EB 2.10
Results
ECD ranged from 1700 – 3500 cells/mm2
Result groupings: Class A (large samples): 40,000μm2 - 70,000μm2 Class B (small samples): 20,000μm2 - 25,000μm2
Standard Deviation: Class A (large samples): 6.27-63.11 (mean 26.3) Class B (small samples): 17.22-155.32 (mean 75.0)
Results
Standard Error (S.D. / √N): Class A (large samples): 3.14-31.56 (mean 13.2) Class B (small samples): 9.94-89.67 (mean 43.3)
Precision (S.E. / Mean): Class A (large samples): 0.0052 Class B (small samples): 0.0156
Results
In every instance: Class A Class B(40,000–70,000μm2) < (20,000–25,000μm2) Mean ECD Mean ECD
RPD ranged from 3.7% – 13.2%
Mean RPD of 7.9%
Conclusion
Larger sample sizes (>40,000μm2) yielded lower standard error and more precise cell count results
Cell counts performed in smaller sample sizes produce significantly higher ECD than larger sample sizes
Discussion
Rate of Change 1,000,000__ in Cell Density = Sample Area(cells per mm2) (in μm2)
Discussion
Sample size was based on area
Samples based solely on # of cells yield smaller sample size in high-density cornea
In smaller samples, ECD increases at a higher rate for every extra cell counted
Discussion
Smaller sample sizes compound possibility for increased margin of error Multiple small samples have longer total
perimeter than a single large sample
Human error factors Image quality Cell identification Tracing of cell boundaries
Recommendations1. Capture images at high resolution and
maximum screen size (640 x 480 pixels).
2. Select the largest sample area possible on the screen for cell counting.
3. If there are folds or distortions, select the largest contiguous true area possible.
4. For high resolution images free of distortions, a minimum selection of 50,000μm2 should always be possible.