BACKGROUND: Malignant lymphomas are classified on the basis of morphology, immunohistochemistry, and genetic and molecular biological features. Morphology is considered the most important and basic feature. Lymphomas can be classified as small, medium, or large depending on the cell size, but this criterion tends to be rather subjective. The aim of this study was to investigate the usefulness of an objective approach based on quantitative measurements. METHODS: Twenty specimens of mantle cell lymphoma and 2 specimens of the tonsil were examined. The nuclear area of 6,401 tumor cells of mantle cell lymphoma and 743 normal mantle cells of reactive tonsils were measured by 3 authors by using a user-controlled image-analyzer. The images of the nuclei were outlined using the spline method and the i-solution software, and the data were assessed using ANOVA and Student's t-test. RESULTS: The mean nuclear areas of mantle cell lymphoma cells measured by the 3 authors were 37.9 [7.9] microm2, 37.9 [7.2] microm2, and 38.2 [7.7] microm2 and those of normal mantle cells in reactive tonsil were 28.6 [2.3] microm2, 28.8 [2.0] microm2, and 27.0 [3.0] microm2. There was no statistical difference between the 3 observations of mantle cell lymphoma (P=0.580) and normal tonsils. CONCLUSION: For morphology, nuclear area is considered an important feature in the classification schemes of lymphoma. We showed that nuclear area measurement by using image analyzer can be used as an objective quantitative method. We think that nuclear morphometry may play a significant role in the diagnosis of lymphoma.
Cell Size ; Immunohistochemistry ; Lymphoma ; Lymphoma, Mantle-Cell ; Palatine Tonsil

BACKGROUND: There is a subjective disagreement about nuclear chromatin in the field of pathology. Objective values of red, green, and blue (RGB) light intensities for nuclear chromatin can be obtained through a quantitative analysis using digital images. METHODS: We examined 10 cases of well differentiated neuroendocrine tumors of the rectum, small cell lung carcinomas, and moderately differentiated squamous cell lung carcinomas respectively. For each case, we selected 30 representative cells and captured typical microscopic findings. Using an image analyzer, we determined the longest nuclear line profiles and obtained graph files and Excel data on RGB light intensities. We assessed the meaningful differences in graph files and Excel data among the three different tumors. RESULTS: The nucleus of hematoxylin and eosin-stained tumor cells was expressed as a combination of RGB light sources. The highest intensity was from blue, whereas the lowest intensity was from green. According to the graph files, green showed the most noticeable change in the light intensity, which is consistent with the difference in standard deviations. CONCLUSIONS: The change in the light intensity for green has an important implication for differentiating between tumors. Specific features of the nucleus can be expressed in specific values of RGB light intensities.
Chromatin ; Hematoxylin ; Image Processing, Computer-Assisted ; Light ; Lung ; Neuroendocrine Tumors ; Rectum ; Small Cell Lung Carcinoma

Epithelial-myoepithelial carcinoma (EMC) is a rare low grade malignant tumor of the salivary glands and it shows a characteristic biphasic population of epithelium and myoepithelium. It shows various cytologic and histologic features, so making an exact diagnosis is difficult. We report here on two cases of epithelial-myoepithelial carcinoma arising from the parotid gland and we compare the cytologic findings of the aspirated samples with the histologic findings of the tumors. We think the finding of mixed pattern of large, clear myoepithelia and small epithelia is the most valuable finding in the diagnosis of EMC.
Biopsy, Fine-Needle ; Epithelium ; Parotid Gland ; Salivary Glands

BACKGROUND: There is subjective disagreement regarding nuclear clearing in papillary thyroid carcinoma. In this study, using digital instruments, we were able to quantify many ambiguous pathologic features and use numeric data to express our findings. METHODS: We examined 30 papillary thyroid carcinomas. For each case, we selected representative cancer cells showing clear nuclei and surrounding non-neoplastic follicular epithelial cells and evaluated objective values of green light intensity (GLI) for quantitative analysis of nuclear clearing in papillary thyroid carcinoma. RESULTS: From 16,274 GLI values from 600 cancer cell nuclei and 13,752 GLI values from 596 non-neoplastic follicular epithelial nuclei, we found a high correlation of 94.9% between GLI and clear nuclei. GLI between the cancer group showing clear nuclei and non-neoplastic follicular epithelia was statistically significant. The overall average level of GLI in the cancer group was over two times higher than the non-neoplastic group despite a wide range of GLI. On a polygonal line graph, there was a fluctuating unique difference between both the cancer and non-neoplastic groups in each patient, which was comparable to the microscopic findings. CONCLUSIONS: Nuclear GLI could be a useful factor for discriminating between carcinoma cells showing clear nuclei and non-neoplastic follicular epithelia in papillary thyroid carcinoma.
Carcinoma, Papillary* ; Cell Nucleus ; Epithelial Cells ; Humans ; Image Processing, Computer-Assisted ; Thyroid Gland* ; Thyroid Neoplasms*