title: A new method of grading malignancy of prostate carcinoma using quantitative microscopic nuclear features.
abstract: A morphometrical assessment of nuclear features and a DNA study were performed on prostate tissue specimens from 33 patients with prostate carcinoma using an image analysing computer. Six nuclear geometric variables were measured and their mean, standard deviation (SD) and standard error (SE) were calculated for each case. The data on nuclear DNA content obtained by static cytometry were processed using an algorithm which provided a DNA grade of malignancy (DNA MG). Using the stepwise multiple regression, we found a significant correlation (p less than 0.01) between the DNA MG, chosen as the dependent variable in the statistical model, and the following nuclear features in decreasing order of importance: area SD, convex perimeter SE, and the mean of maximum diameter. From the correlation coefficients of the variables an equation was built up which provided a geometric nuclear grade of malignancy (GNMG) on a morphometrical basis more closely related to the clinical stage of the tumour (r = 0.75) than the visually assessed histological grade (r = 0.68) based on the Gleason score. This new method of grading malignancy allows an objective and quantitative evaluation to be made of the biological behaviour of the tumour, as measured by the patient's clinical stage.
authors.affiliation: Department of Pathology, City Hospital, Alessandria, Italy.
authors.forename: F
authors.initials: F
authors.lastname: Robutti
authors.forename: F P
authors.initials: FP
authors.lastname: Pilato
authors.forename: P G
authors.initials: PG
authors.lastname: Betta
mesh_terms: D002467:Cell Nucleus / Q000473:pathology*; D004273:DNA, Neoplasm / Q000032:analysis; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008297:Male; D011471:Prostatic Neoplasms / Q000473:pathology* / Q000648:ultrastructure; D012044:Regression Analysis
chemical_list: D004273:DNA, Neoplasm