Shape analysis of tumor cell nuclei in ependymomas by means of Fourier analysis.
OBJECTIVE
To study the prognostic significance of nuclear shape analysis in ependymomas.


METHODS
Tumor cell nuclei in surgical specimens of primary resected ependymomas from 30 patients were evaluated by means of Fourier analysis of nuclear contours, conventional morphometric features (nuclear area, shape factor) and the Ki-67 proliferation index. Fourier analysis can be used for decomposing an irregular nuclear contour by calculating "Fourier amplitudes." Tumors with different tumor grades according to the World Health Organization were compared, as were patients with and without recurrence of ependymomas. Planimetric data were further correlated with the Ki-67 index.


RESULTS
t Test and multivariate analysis showed distinct differences between ependymomas with tumor grade 3 and the other tumor grades. Cross-validated, stepwise discriminant analysis with the event of recurrence as grouping variable revealed correct reclassification in 16/18 cases without recurrence and of 10/12 cases with recurrence. When considering just intracranial ependymomas with total surgical removal, Fourier amplitudes provided 100% correct reclassification concerning recurrence. Proliferation index, in contrast, showed considerable overlap between all tumor grades and between cases with and without recurrence.


CONCLUSIONS
Quantification of the shape of tumor cell nuclei in ependymomas by means of Fourier analysis has prognostic significance and seems to be superior to the Ki-67 index.
Nafe
R
R
Edinger Institute of Neuropathology, Clinics of Johann Wolfgang Goethe University, Frankfurt-Main, and Institute of Biometrics, Medical School, Hannover, Germany.
Schlote
W
W
Schneider
B
B
D001932:Brain Neoplasms / Q000473:pathology; D002467:Cell Nucleus / Q000473:pathology*; D016002:Discriminant Analysis; D004806:Ependymoma / Q000473:pathology*; D005583:Fourier Analysis; D006801:Humans; D018302:Neoplasms, Neuroepithelial / Q000473:pathology; D016016:Proportional Hazards Models