OBJECTIVE: To evaluate the performance of karyometry and histometry in the
prediction of survival, recurrence and response of early-stage invasive cer
STUDY DESIGN: Nuclear morphometry, chromatin texture and tissue architectur
e (characterized by syntactic structure analysis) were measured using a sem
iautomated image analysis system on 46 cases of Feulgen-stained tissue sect
ions. The performance of the features was compared to that of clinical feat
ures, reported to be the best prognosticators until now, such as age, lymph
o-vascular permeation, histologic type, stage and grade. A K nearest neighb
or classifier was used for classification.
RESULTS: In the prediction of three-year survival, recurrence and response,
syntactic structure analysis proved to be the best performer. Classificati
on rates were, respectively, 100%, 94.4% and 94.5%. In all classifications,
karyometric and histometric features outperformed clinical features. In ge
neral, the best performing features described differences in second-order p
opulation statistics (standard deviations).
CONCLUSION: The results show that a quantitative analysis based on nuclear
morphology, chromatin texture and histology can be considered an excellent
aid in the prognosis of invasive cervical carcinoma. The measurements are n
ot hampered by the Meed to undertake complete resections and are suited to
daily practice when implemented in a semiautomated image analysis system.