A morphometrically-based classification rule for the diagnosis of primary mesothelial lesions.
A computer-aided morphometrical study was performed on histological specimens of reactive hyperplastic (n = 10) and malignant (n = 17) mesothelium. For each cell, seven nuclear features were measured and 13 parameters computed. Using stepwise variable selection, discriminant analysis chose the nuclear contour index, the standard deviation of the nuclear area, and the mean of the nuclear perimeter as discriminating features between hyperplastic and malignant mesothelium. The coefficients of these variables were included in a discriminant function which gave perfect discrimination between the two groups of lesions. When the function was assessed on a test set of hyperplastic (n = 10) and malignant (n = 17) mesothelial lesions treated as 'unknown', complete separation between these two diagnostic categories was achieved. This classification rule may help to increase the level of confidence with which a histological diagnosis of mesothelioma can be established.
Robutti
F
F
Department of Pathology, City Hospital, Alessandria, Italy.
Betta
P G
PG
Donna
A
A
Pavesi
M
M
D002467:Cell Nucleus / Q000648:ultrastructure; D003937:Diagnosis, Differential; D004848:Epithelium / Q000473:pathology / Q000648:ultrastructure; D006801:Humans; D006965:Hyperplasia / Q000175:diagnosis / Q000473:pathology; D007091:Image Processing, Computer-Assisted; D007620:Karyometry; D008297:Male; D008654:Mesothelioma / Q000175:diagnosis / Q000473:pathology* / Q000648:ultrastructure