Abstract

ObjectiveThe authors, using image analysis, previously demonstrated nuclear size and summed optical density to be independent prognostic indicators of recurrence in patients with endometrial carcinoma. The same tumors were analyzed by studying the optical features in the G0–G1 peak to see if this changed the values found as well as their importance as prognostic features at greater than 5 years of follow-up.MethodsTumors from 74 consecutive patients, surgically treated, with endometrial cancer, were evaluated. Survival, depth of invasion, lymphvascular space invasion, FIGO stage, grade, histology were analyzed. DNA index, progesterone receptor status, as well as nuclear size (NUSZ), shape (NUSH), and summed optical density (NUSD) were evaluated. NUSZ, NUSH, and NUSD were quantified using image analysis.ResultsFifteen patients died from disease during the observation period of the study. Mean follow-up was 82 months with a median of 84 months. Forty-nine patients had stage I cancers, five stage II, 17 stage III, and three stage IV. NUSZ and NUSD were all significantly different between the original (entire cell cycle) and the re-measured (G0G1 only) values (both P < 0.001). Multivariate analysis showed both the original (P = 0.0001) and G0G1-only (P = 0.046) NUSZ and the original (P = 0.0002) and G0G1-only (P = 0.018) NUSD to be independent prognosticators of survival.ConclusionImage analysis is able to quantify cellular and nuclear parameters not otherwise quantifiable. NUSD and NUSZ correlated with traditional prognostic indicators, were demonstrated independent predictors of survival at over 5 years of follow-up. Although the re-measured NUSZ and NUSD from only the G0–G1 peak were significantly different from the original NUSZ and NUSD, they were not as valuable as prognostic factors. Nuclear size and summed optical density measured from the entire cell cycle are independent prognostic indicators of survival at greater than 5 years of follow-up. Measuring nuclear morphometric features in the G0–G1 peak only does not add any new prognostic information.

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