Detecting progression of nuclear sclerosis by using human grading versus semiautomated computer grading.

Kleins Lab // Publications // Apr 01 2005

PubMed ID: 15790873

Author(s): Klein BE, Hubbard L, Ferrier NJ, Klein R, Klein DJ, Lee KE, Ewen A, Jensen K, Evans MD. Detecting progression of nuclear sclerosis by using human grading versus semiautomated computer grading. Invest Ophthalmol Vis Sci. 2005 Apr;46(4):1155-62. PMID 15790873

Journal: Investigative Ophthalmology & Visual Science, Volume 46, Issue 4, Apr 2005

PURPOSE To assess indices of nuclear sclerosis derived from digitized images made from color (slide) photographs.

METHODS Film-based slit lamp images taken at baseline and at 5- and 10-year follow-up examinations of the Beaver Dam Eye Study cohort were digitized, and optical traces were taken along an axis through the center of the cornea and lens. Four indices of the severity of sclerosis were calculated based on the optical densities. The associations of the original Beaver Dam grades and these indices to age, vision, and change in severity of sclerosis over two subsequent visits were compared.

RESULTS At baseline photographs, the Spearman correlation between age and severity was 0.65 for the original film-based grading (n = 4518 right eyes) and varied between 0.46 and 0.71 for the measures from digitized images. Correlations of the indices to visual acuity were 0.38 for the film-based grading and ranged from 0.32 to 0.38 for the other indices. The authors assume that nuclear sclerosis does not regress and the percentage of regression is a reflection of error in grading. The percentage of regression and progression of sclerosis over 5- and 10-year intervals was determined for each index. After 5 years, 48.2% progressed and 4.9% regressed, using the Beaver Dam grades; progression occurred in 4.9% to 9.9%, and regression occurred in 4.5% to 7.0% for the other indices. After 10 years, 61.9% progressed and 3.2% regressed using the Beaver Dam grades; progression occurred in 8.0% to 19.7%, and regression occurred in 2.6% to 9.7% for the other indices.

CONCLUSIONS Semiautomated grading of the digitized images can be used to process thousands of images with little oversight by a trained grader. Indices of sclerosis that closely parallel human grading in their relationships to age and visual acuity can be easily computed. However, the indices appear to identify significantly less progression of nuclear sclerosis than does human grading. Further development to define a useful metric for identifying severity and progression of nuclear sclerosis is needed.