Correlation of histologic corneal endothelial cell counts with specular microscopic cell density. 1992

K K Williams, and R L Noe, and H E Grossniklaus, and C Drews-Botsch, and H F Edelhauser
Department of Ophthalmology, Emory University School of Medicine, Atlanta, Ga. 30322.

The central endothelia of 48 eye bank corneas from donors ranging in age from 5 weeks to 88 years were photographed using in vitro specular microscopy. Computer-assisted morphometric analysis of the size and shape of endothelial cells was performed, and cell density was calculated. Histologic examination of the corneas after specular microscopy determined endothelial cell counts using x40 objective magnification. The mean endothelial cell counts from five different high-power fields were calculated. Results showed that there is a direct correlation between cell number and specular microscopy cell density (r = .91 and Spearman rank correlation, 0.69; both significant at P less than .01). A nomogram was developed to estimate corneal endothelial cell density from high-power field cell counts of pathologic specimens.

UI MeSH Term Description Entries
D007223 Infant A child between 1 and 23 months of age. Infants
D008875 Middle Aged An adult aged 45 - 64 years. Middle Age
D012044 Regression Analysis Procedures for finding the mathematical function which best describes the relationship between a dependent variable and one or more independent variables. In linear regression (see LINEAR MODELS) the relationship is constrained to be a straight line and LEAST-SQUARES ANALYSIS is used to determine the best fit. In logistic regression (see LOGISTIC MODELS) the dependent variable is qualitative rather than continuously variable and LIKELIHOOD FUNCTIONS are used to find the best relationship. In multiple regression, the dependent variable is considered to depend on more than a single independent variable. Regression Diagnostics,Statistical Regression,Analysis, Regression,Analyses, Regression,Diagnostics, Regression,Regression Analyses,Regression, Statistical,Regressions, Statistical,Statistical Regressions
D002102 Cadaver A dead body, usually a human body. Corpse,Cadavers,Corpses
D002452 Cell Count The number of CELLS of a specific kind, usually measured per unit volume or area of sample. Cell Density,Cell Number,Cell Counts,Cell Densities,Cell Numbers,Count, Cell,Counts, Cell,Densities, Cell,Density, Cell,Number, Cell,Numbers, Cell
D002648 Child A person 6 to 12 years of age. An individual 2 to 5 years old is CHILD, PRESCHOOL. Children
D002675 Child, Preschool A child between the ages of 2 and 5. Children, Preschool,Preschool Child,Preschool Children
D004728 Endothelium, Corneal Single layer of large flattened cells covering the surface of the cornea. Anterior Chamber Epithelium,Corneal Endothelium,Endothelium, Anterior Chamber,Epithelium, Anterior Chamber,Anterior Chamber Endothelium
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000293 Adolescent A person 13 to 18 years of age. Adolescence,Youth,Adolescents,Adolescents, Female,Adolescents, Male,Teenagers,Teens,Adolescent, Female,Adolescent, Male,Female Adolescent,Female Adolescents,Male Adolescent,Male Adolescents,Teen,Teenager,Youths

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