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This study describes an image processing method for the assessment of the mitotic count in Feulgen-stained breast cancer sections. The segmentation procedure was optimized to eliminate 95-98% of the nonmitoses, whereas 11% of the mitoses did not survive the segmentation procedure. Contour features and optical density measurements of the remaining objects were computed to allow for classification. Twelve specimens were analyzed, nine used to serve as a training set, and three put aside for later use as independent test set. The fully automatic image processing method correctly classified 81% of the mitoses at the specimen level while inserting 30% false positives. The automatic procedure strongly correlated with the interactive counting procedure (r = 0.98). Although the fully automatic method provided satisfactory results, it is not yet suited for clinical practice. The automated method with an interactive evaluation step gave an accurate reflection of the mitotic count showing an almost perfect correlation with the results of the interactive morphometry (r = 0.998). Therefore this semiautomated method may be useful as prescreening device.

The influence of various DNA measurement errors using a commercially available scanning microdensitometer was evaluated on Feulgen-stained cytologic and histologic samples prepared from paraffin blocks containing invasive ductal breast cancers. The overall average total measurement error was 5.5% for the cytologic specimens and 10.9% for the 4 micron histologic sections. Components of the error included microscopic adjustment variation and focussing errors (3.5% and 1.1%, respectively, for both cytologic and histologic samples) and background intensity estimation errors (3.0% for the cytologic samples and 10.0% for the histologic samples). Measurements of the integrated optical density had a minimal error of 0.5% and an average error of 1.0%. Limitations due to the histologic architecture and/or heterogeneous cell population gave rise to large differences in the selection of nuclei when differently sized scanning masks were used. To improve the reproducibility, masks used should be based on the individual cell size, and background intensity values should be carefully estimated in the vicinity of the selected cells. Overall, the cytologic tumor samples were preferable to the histologic samples for static DNA measurements. It was easier to select cells suitable for measurement in the cytologic samples, and the cytologic measurements were less time consuming and produced a smaller measurement error.

The paper describes an image analysis technique for automated estimation of the epithelial percentage in standard paraffin tissue sections of invasive ductal breast cancers. Two staining procedures are evaluated: Feulgen (pararosanilin) and CAM 5.2-demonstrating the presence of cytokeratin 8 and 18-, both counterstained with naphthol yellow. In the technique, one image is recorded with a filter to visualize where the epithelium lies. This filter is chosen corresponding to the type of staining: it is yellow for Feulgen and blue for anti-cytokeratin CAM 5.2. To visualize where the stroma lies, the same image can be used for anti-cytokeratin CAM 5.2, whereas for Feulgen, a second image has to be recorded from the same microscope field with a blue filter. The image processing steps to determine the total tissue area comprise correction for shading, segmentation of the tissue area, and restoration of the segmented image by removal of small artefacts and closure of small tears in the tissue. The method for determination of the epithelial area consists of the following steps: correction for shading, gaussian blurring, segmentation of nuclei or epithelial cells, and editing of the segmented image by removal of small objects and closure of small spaces between the epithelial nuclei or cells. These image processing steps are compared to those for quantification of the epithelial percentage in gynecologic tumors of epithelial origin. For the Feulgen stain, the method is evaluated on 30 breast cancers of the ductal type (4 grade I, 12 grade II, and 14 grade III).(ABSTRACT TRUNCATED AT 250 WORDS)

In a group of 335 patients with primary breast carcinoma the presence of immunoreactive carcinoembryonic antigen (CEA) and the binding of the lectin peanut agglutinin (PNA) in the primary carcinoma and in axillary lymph node metastases were investigated. The correlation between these results and a variety of established clinical, histopathologic, morphometric and biochemical prognosticators was studied. These features included lymph node status, tumour diameter, tumour type, nuclear grade, histologic grade, oestrogen receptor status, mitotic activity index and a number of nuclear measurements. The results indicate that CEA immunoreactivity of and PNA binding to tumour cells in primary breast carcinomas or lymph node metastases do not correlate with established prognostic factors in breast cancer.

This paper describes an image analysis technique for the counting of nuclei in mitosis in tissue sections. Five experienced pathologists scored mitoses in photographs of preselected areas of tissue sections of the breast. Objects consistently labelled as mitotic cells by all five pathologists were considered "mitoses" in the analysis. In total, there were 45 mitotic nuclei, 68 possible mitotic nuclei and 1,172 nonmitotic nuclei. The image analysis procedure was designed to give priority to a low false negative rate, i.e., misclassification of mitoses. The procedure consists of three steps: 1. Segmentation of the image. 2. Reduction of the number of nonmitotic nuclei by using feature values based on the brightness histogram of the objects. 3. Fully automatic classification of the remaining objects using contour features. The objects remaining after the first two steps were visualized in a composite display for interactive evaluation: 10% of the mitotic nuclei were missed, and 85% of the nonmitotic nuclei were eliminated. The result of the fully automatic procedure described in this paper is rather disappointing and gave a loss of 37% of the mitoses while 5% of the nonmitotic nuclei remained.

A pilot study compared DNA histogram features of ten invasive ductal breast cancers measured by three different techniques: in cytologic and histologic samples using a scanning densitometer and in suspensions of single nuclei using a flow cytometer. The reproducibility of measurements pertaining to quantitative ploidy factors was better for flow cytometry (FCM) than for static cytometry and was worst of all using histologic samples. The use of external reference cells for the precise determination of the diploid value in measurements of paraffin-embedded single nuclei proved to be pointless. Of all static histogram descriptors, the modal value was the most reproducible; however, this feature could not distinguish between diploid and near-diploid tumors. In contrast, using the descriptors of (1) diploid peak width, (2) coefficient of variation of the integrated optical density values and (3) percentage of cells exceeding 2.5c from histograms derived from static measurements, it was possible to distinguish between tumors that were characterized as diploid and near-diploid by FCM (chi-square P = .01). This is the more important because subjective analysis of the static histograms of these tumors failed to identify a cell population deviating from the diploid value in spite of the fact that the FCM DNA index (DI) varied from 1.12 to 1.23. Thus, quantitative histogram descriptors, as evaluated in this study, may add objective information to the measurement of DNA ploidy when using static DNA cytometry, especially in the case of near-diploid tumors. Duplicate FCM assessments of the DI showed the highest correlation of all features investigated (r = .99).

In 234 patients with primary breast cancer, morphometry was performed of three groups of tumour cells: 1. in the primary tumours without lymph node metastases (PRN); 2. in primary tumours with lymph node metastases (PRP) and; 3. in the axillary lymph node metastatic deposits (LMD). The morphometrical analysis included the cellularity index, the mitotic activity index and seven nuclear features. The highest mitotic activity indices (mean: 14.1) were found in the metastatic deposits (LMD), the lowest (mean: 12.5) in the lymph node negative primary tumours (PRN), whereas the lymph node positive primary tumours (PRP) fell in between (mean: 13.2). The cellularity index shows a similar, though reciprocal, trend. The largest standard deviations of the nuclear features were found in primary tumours with lymph node metastases (PRP). In contrast, the metastatic (LMD) nuclei had the smallest standard deviations. The nuclei of the latter are therefore more regular in size and shape. The differences found are not sufficiently large to distinguish PRN and PRP with an acceptable accuracy (the efficiency, sensitivity or specificity did not exceed 67% irrespective of the decision threshold used). Comparison of primary tumours with lymph node metastases and the metastatic deposits, from the same patients, revealed significant correlations of all morphometric features with the exception of the nuclear shape factor and the nuclear axes ratio. Thus, the nuclei of the metastatic cells in general are identical to the nuclei in the primary tumour from which they arise, but in a subset of patients the metastatic tumour cells have much more monomorphous ellipsoid nuclei. Further investigations are needed to see whether this phenomenon indicates a different malignant course.