Objective: To evaluate histometric measurement of nuclear texture in breast biopsy sections in order to detect malignancy-associated changes in apparently normal tissue in the vicinity of carcinoma in situ.
Study design: We previously showed that image cytometry measurements of nuclear features--foremost, texture features, describing the organization of Feulgenstained DNA in the cell--can be used to distinguish normal-appearing, diploid epithelial cells from patients with invasive carcinoma of the breast from those with benign biopsies. In that study, referred to as the "single cell analysis," images of at least 200 epithelial cells were acquired for each slide, and substantial user interaction was required to segment cells from each field. Location of isolated cells and interactive segmentation are both time-consuming procedures, particularly in breast tissue, where nuclei can be tightly clustered within a duct. With histometric texture analysis on the same specimens, segmentation of individual cells was ignored, and texture measurements were performed over the entire cluster of relevant cells. With this approach, ploidy information is not available, and touching and overlapping nuclei are included in the measurements. Measurement of histometric texture properties requires substantially less time (at least an order of magnitude) than individual cell measurement and, if ploidy information is not significant, may therefore provide a more practical means of analysis for tissue sections.
Results: Seventeen cases of invasive carcinoma and 17 cases of nonproliferative breast disease were examined. Using stepwise discriminant function analysis, slides were classified into one of the two groups with an accuracy of 88.6% in the case of single cell analysis and with an accuracy of 88.2% using histometric analysis.
Conclusion: The existence of malignancy-associated changes in the breast was confirmed by an independent analysis of the same specimens. Although the two methods are not directly comparable, we found that histometric texture analysis performs at least as well as single-cell analysis for the detection of malignancy-associated changes in breast carcinoma.