Two statistical approaches to nuclei shape and size in a morphometric description of lymph node sections in non-Hodgkin's lymphoma.
An attempt is made to evaluate more clearly the potential contribution of quantitative nuclear profile shape and size measurements to lymph node section histologic description in 70 cases of non-Hodgkin's lymphoma (NHL). The area of nuclear profiles and five nonredundant and size-free shape indices were measured using the THECLA program on a Leitz Texture Analysis System (Leitz-TAS). Two statistical approaches were applied, known respectively as "parametric," (first statistical moments of variable distributions over samples of 200 nuclear profiles) and "nonparametric," which are percentages of nuclear profiles distributed into five "cytological" classes that are defined by shape: round (A), elongated (B), kidney shaped (C), irregular (D) and cleaved (E) nuclear profiles. Both statistical approaches provide proper overall discrimination of the eight histological categories identified with reasonable reliability by pathologists. Above all, the present report discusses the ability of a set of parametric and nonparametric variables to describe NHL cell populations, in an objective and meaningful way, according to nuclei shape. A method of synthesizing multidimensional correlations (CORICO program) is proposed in support of the discussion. Also, the specific descriptive power of each of the variables is described; in particular, it is concluded that there is a close link between the shape and size of the nuclear profiles of the cells.
Lesty
C
C
Département d'Hématologie CNRS UA 625, Centre de l'Association Claude Bernard, Centre Hospitalier Universitaire la Pitié-Salpêtrière, Paris, France.
Raphaël
M
M
Nonnenmacher
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L
Binet
J L
JL
D002467:Cell Nucleus / Q000648:ultrastructure*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D008198:Lymph Nodes / Q000473:pathology / Q000648:ultrastructure*; D008228:Lymphoma, Non-Hodgkin / Q000473:pathology / Q000648:ultrastructure*; D013223:Statistics as Topic