Hydrolysis profiles of formalin fixed paraffin-embedded tumors based on IOD (integrated optical density) and nuclear texture feature measurements.

The aim of the study was to determine optimal hydrolysis time for the Feulgen DNA staining of archival formalin fixed paraffin-embedded surgical samples, prepared as single cell suspensions for image cytometric measurements. The nuclear texture features along with the IOD (integrated optical density) of the tumor nuclei were analysed by an automated high resolution image cytometer as a function of duration of hydrolysis treatment (in 5 N HCl at room temperature). Tissue blocks of breast carcinoma, ovarian serous carcinoma, ovarian serous tumor of borderline malignancy and leiomyosarcoma were included in the study. IOD hydrolysis profiles showed plateau between 30 and 60 min in the breast carcinoma and leiomyosarcoma, and between 40 and 60 min in the ovarian serous carcinoma and ovarian serous tumor of borderline malignancy. Most of the nuclear texture features remained stable after 20 min of hydrolysis treatment. Our results indicate that the optimal hydrolysis time for IOD and for nuclear texture feature measurements, was between 40 and 60 min in the cell preparations from tissue blocks of three epithelial and one soft tissue tumor.

Detection of compact low-chromatin areas in cell nuclei images.

When analysing some DNA stained human cell nuclei using a light microscope or an quantitative image cytometer, compact low-chromatin areas (CLCA) can be observed. We are still not certain about the meaning and source of this phenomena. To enable the detection of CLCA by an image cytometer, a special image processing algorithm has to be developed and new nuclear cell features have to be designed. The presented image processing algorithm automatically detects CLCA in nuclei cell images taken from different tissues. The algorithm is composed of many basic image processing operations. The sequence of operations is determined by a priory knowledge about the properties of CLCA as a set of heuristic roles. The calculated CLCA features are CLCA area, perimeter, average intensity, compactnes and edge sharpness. The matching of the automatic CLCA detection and manual detection (performed by a biologist) was tested using 1400 cell nuclei. The results show a 83.4% match for the nuclei without CLCA and a 93.8% match for the cells with CLCA.

3D presentation of the nuclear cell features in quantitative cytometry.

The use of an image cytometer in analysis of smears and needle aspirates provides valuable information to a cytologist. It allows to combine the overall impression, formed by visually inspecting the cells, with measured and numerically expressed nuclear cell features. Both types of information can be used efficiently only if presented to the expert in an appropriate way. Cell images (as they are seen with a microscope) are easily analysed by the experts. However, measured nuclear features can not be presented as a list of numerical values. Instead, an user interface should be developed, providing graphical presentation of the nuclear features. It should show as much information as possible and provide a comprehensive link between nuclear features and cell images. The user interface described in this paper shows nuclear features in three dimensions. It is based on a perspective projection of the three dimensional feature space onto a two dimensional surface. It allows the user to dynamically change the perspective, i.e., to look at the virtual three dimensional structure from different viewpoints. Each nucleus is represented by a single object in the three dimensional space. When an object in the three dimensional feature space is selected, the image (or the visual appearance) of the corresponding cell is shown. When a nucleus image is selected, its position in the feature space is highlighted. This provides an interconnection between nuclear cell features and cell images allowing simultaneous analysis of both types of information.