A karyometric approach to the characterization of atypical endometrial hyperplasia with and without co-occurring adenocarcinoma

OBJECTIVE: To develop a karyometric image analysis approach to distinguishing atypical endometrial hyperplasia with and without co-occurring adenocarcinoma. STUDY DESIGN: Six cases of atypical hyperplasia without and 6 cases with co-occurring adenocarcinoma, 4 cases of normal endometrium and 3 cases of adenocarcinoma were identified. From each case 100 nuclei were measured in representative diagnostic areas identified by an experienced pathologist. Discriminant analyses were performed. An unsupervised learning algorithm was applied to define and characterize different nuclear phenotypes, and those data were used to identify cases with co-occurring adenocarcinoma. RESULTS: Discriminant analysis showed that nuclei from atypical hyperplasia and atypical hyperplasia with co-occurring adenocarcinoma are statistically different. The unsupervised learning algorithm revealed differences in nuclear subpopulations that can be used to correctly identify an estimated 85% of individual cases. CONCLUSION: Nuclei from atypical hyperplasia without and with co-occurring adenocarcinoma have statistically different karyometric characteristics that may facilitate case classification.     

Progression curves for endometrial lesions

OBJECTIVE: To derive a numeric measure for the progression of endometrial lesions as a baseline study for an eventual assessment of chemopreventive intervention efficacy. STUDY DESIGN: Tissue sections from normal endometrium at the proliferative and secretory phase, simple hyperplasia, atypical hyperplasia from cases free of concomitant adenocarcinoma and adenocarcinoma of the endometrium were recorded at high spatial resolution. Six cases from each diagnostic category were chosen as "typical," and 60 epithelial nuclei were randomly selected for measurement for each case. Discriminant analyses were carried out to derive a direction of progressive change in feature space and to correct the progression curve for the presence of cells not expressing progressive change among the random sample of nuclei. RESULTS: A well-conditioned progression curve was derived based on the mean discriminant function scores for each diagnostic category and the mean nuclear abnormality of the nuclei in each category, as expressed by their deviation in feature values from normal reference nuclei. The lesion signatures showed a clear trend toward extension into the range of higher nuclear abnormalities with increasing progression. There was an indication that abnormal endometrial lesions may comprise cases with distinctly different degrees of nuclear abnormality. CONCLUSION: A numeric assessment of lesion progression for endometrial lesions, based on karyometric measurements, is possible. The data suggest that additional analysis may provide further characterizing information for individual lesions.     

Nuclear chromatin characteristics of breast solid pattern ductal carcinoma in situ.

OBJECTIVE: To characterize nuclei from breast solid pattern ductal carcinoma in situ (DCIS) by their karyometric features and to search for the presence of statistically significantly different subsets of nuclei. STUDY DESIGN: One hundred nuclei from each of 6 normal, 13 solid DCIS, (9 low and intermediate grade and 4 high grade DCIS) histopathologic samples of breast tissue were digitally recorded. Karyometric features were computed and subjected to a nonsupervised learning algorithm (P-index) to identify significantly different subgroups. RESULTS: Nuclei in low grade lesions displayed a diploid/near diploid pattern, while the majority of intermediate grade lesions fell into a range beyond 5N. The high grade lesions showed substantial genomic instability and represented three statistically different subsets or phenotypes. CONCLUSION: There is a progression of nuclear abnormality from low grade to high grade DCIS. The nuclei from high grade DCIS form a heterogeneous set that represents three phenotypes. One of these phenotypes shows a nuclear chromatin pattern that more closely resembles poorly differentiated, infiltrating disease. The observation of such a phenotype may have prognostic implications.     

Chromatin texture in high grade prostatic intraepithelial neoplasia and early invasive carcinoma

OBJECTIVE: To evaluate individual nuclei from high grade prostatic intraepithelial neoplasia (PIN) lesions with early invasive carcinoma foci in the area of microinvasion and in the gland in which the microinvasion originated. STUDY DESIGN: High-resolution, digitized images of nuclei from defined locations were recorded and segmented, and karyometric variables were computed. These included a set of 93 features, which form a nuclear signature characterizing the spatial and statistical distribution of the nuclear chromatin. Nuclei in the glandular epithelium were recorded sequentially, along the basal cell layer, at increasing distances from the point of microinvasion and by random selection in the region of microinvasion. RESULTS: At a distance > 60 nuclear locations from the point of microinvasion, the nuclear signatures corresponded to those seen in high grade PIN. Between 40 and 20 nuclear locations removed from the microinvasion focus the signatures began to change gradually until at a distance of 15-5 locations they strongly resembled the signatures seen in adenocarcinoma. The total optical density decreased to values seen in adenocarcinoma, and the nuclear chromatin had finer granularity. While nuclei in high grade PIN followed a widely dispersed total optical density distribution suggestive of wide-ranging aneuploidy, the nuclei in the region of microinvasion exhibited a less dispersed and bimodal total optical density distribution. CONCLUSION: The chromatin texture signatures showed a clear trend: there was an obvious attenuation as the measured nuclei approached the microinvasion area. The decrease in total optical density at the microinvasion might suggest the emergence of one or two clones that can be responsible for the invasive phenotype.     

Karyometry of infiltrating breast lesions

OBJECTIVE: To characterize nuclei from well-differentiated, moderately differentiated and poorly differentiated lesions of invasive breast cancer by karyometry and to test the hypothesis that these diagnostic categories form homogeneous sets. STUDY DESIGN: Histopathologic sections from 6 cases of well-differentiated, 11 cases of moderately differentiated and 17 cases of poorly differentiated ductal carcinomas were digitally recorded. From each case 100 nuclei were segmented and analyzed by karyometry. A discriminant analysis was performed, and nuclear and lesion signatures were computed. The nonsupervised learning algorithm P-index was applied. A progression curve per diagnostic category based on mean nuclear abnormality and a discriminant function score was derived. RESULTS: The well-differentiated lesions formed a homogeneous set, but both the moderately and poorly differentiated lesions showed 2 significantly different subpopulations with nuclei of substantially different nuclear abnormality and progression. CONCLUSION: The visual histopathologic diagnostic assessment of these lesions was based on an evaluation of both tissue architectural criteria and nuclear criteria. Here, only the pattern of nuclear chromatin was evaluated. Cases belonging to the same diagnostic category as assessed by their differentiation may be further characterized by the extent to which the nuclei deviate from normal. There was substantial case-to-case heterogeneity in these invasive lesions.     

Analysis of nuclear chromatin distribution in cervical glandular abnormalities

OBJECTIVE: To measure the intensity of hematoxylin staining for the analysis of chromatin distribution and to define a clear set of standards. STUDY DESIGN: Cervical smears obtained from 12 patients with glandular lesions, 5 with squamous lesions and 3 without cervical lesions were used for NIH image analysis (public domain NIH image program developed at the U.S. National Institute of Health, available through the Internet by anonymous ftp from zippy.nimh.nih.gov or on floppy disk from the National Technical Information Service, Springfield, Virginia). In addition, the same cervical smears were restained with propidium iodide, and the DNA content in the nuclei was compared with that with hematoxylin staining. RESULTS: Chromatin distribution was categorized into 3 patterns. Pattern A was that for which the highest staining density was localized in the periphery of the nucleus, while in pattern C it was localized in the center of the nucleus. Pattern B was the intermediate type between patterns A and C. In patients with adenocarcinoma, pattern B was predominant; pattern C was also relatively frequent in this group. In atypical glandular cells observed in patients with squamous lesions, patterns A and B were predominant and pattern C rarely seen. Analysis of DNA content in the nucleus revealed that nuclei showing pattern B contained significantly higher quantities of DNA than those showing pattern A. CONCLUSION: Nuclear chromatin distribution seems to correlate well with DNA content, and analysis of the chromatin distribution pattern is helpful for the diagnosis of cervical glandular neoplasia.     

Digital image analysis of silver-stained nucleolar organizer region--associated proteins in endometrial cytologic samples

OBJECTIVE: Digital image analysis was applied to determine the number, area and size of silver-stained nucleolar organizer regions (AgNORs) in cytologic samples from curettage in normal, hyperplastic and malignant endometrium. STUDY DESIGN: Thirty-two archival cytologic smears from curettage (previously stained by the Papanicolaou method) with the histologic diagnosis (4 inactive endometrium, 5 secretion, 5 proliferation, 5 simple hyperplasia, 5 complex hyperplasia, 3 atypical hyperplasia, 5 adenocarcinoma, grade 1) were analyzed with the AgNOR technique. Count, area and size of AgNORs were analyzed in 50 cells per sample using a magnification of 1,000x. Quantitative analysis was performed on an SFORM digital imaging system. Data were analyzed with the SPSS/PC+ program. Mann-Whitney and chi 2 tests were performed. RESULTS: The average value of AgNOR count increased from normal to hyperplastic endometrium and well-differentiated adenocarcinoma. Differences were significant except between atypical hyperplasia and adenocarcinoma. Four, five and more AgNORs in 40% or more of the nuclei were found in complex and atypical hyperplasia and adenocarcinoma. Proliferation, and simple and atypical hyperplasia had similar mean values of AgNOR area. The mean total AgNOR area value increased from normal to hyperplastic had similar mean values of AgNOR area. The mean total AgNOR area value increased from normal to hyperplastic and well-differentiated adenocarcinoma. Differences were statistically significant. AgNOR size in well-differentiated adenocarcinoma was significantly different from that in normal endometrium and different grades of hyperplasia. CONCLUSION: Digital image analysis of AgNOR count, area and size enabled a distinction to be made between normal, hyperplastic and malignant endometrium.     

Karyometry in Barrett's esophagus

OBJECTIVE: To derive a progression curve for lesions in Barrett's esophagus based on karyometric features. STUDY DESIGN: High-resolution imagery of 900 nuclei from normal gastric tissue, Barrett's metaplasia, Barrett's high grade dysplasia and adenocarcinoma of the esophagus was recorded. Karyometric features were computed, and nuclear signatures and lesion signatures for these lesions were derived. A progression curve was defined. RESULTS: Esophageal lesions were distinctly different from the normal gastric fundus tissue, with nuclei from Barrett's metaplasia deviating from normal almost as much as nuclei from high grade dysplasia and adenocarcinoma. There was considerable case-to-case variability and overlap between lesions histologically assigned to different diagnostic categories. CONCLUSION: The karyometric data suggest that Barrett's metaplasia is a more developed lesion than previously assumed.     

Image analysis of mesothelioma. I. differentiation of mesothelioma from adenocarcinoma of the lung

OBJECTIVE: To explore the usefulness of nuclear micromorphometric analysis for the differentiation between epithelial mesothelioma and metastatic adenocarcinoma in the chest wall. STUDY DESIGN: High-resolution images of 2,100 nuclei from 27 cases of epithelial mesothelioma and 15 cases of adenocarcinoma of the lung were recorded. Stepwise discriminant analysis and a nonparametric classifier were applied to derive estimates for a case diagnosis correct classification rate. RESULTS: Nuclei from epithelial mesothelioma and adenocarcinoma of the lung showed statistically significantly different properties, but there was a region of overlap in feature space such that approximately 15-20% of cases could not be correctly classified. The lesion signatures derived from the mesothelioma cases with discriminant function scores that might result in case misclassification and the cases of adenocarcinoma of the lung spanned a similar range of degree of nuclear abnormality. However, the distribution of nuclear abnormality values for the mesothelioma cases has a mode at 0.87 SD from normal, whereas the distribution seen in lung adenocarcinoma cases had a mode at about 3.7 SD. CONCLUSION: Cases of epithelial mesothelioma and adenocarcinoma of the lung have nuclei with a wide range of deviation from normal in the spatial and statistical distribution of their nuclear chromatin. For approximately 80% of cases, correct case classification can be provided by nuclear micromorphometric analysis. Cases of epithelial mesothelioma with highly abnormal nuclei overlap in feature space with nuclei from adenocarcinoma of the lung. However, it is possible that characterization by a lesion signature may allow correct assignment for those cases.     

Karyometric features in nuclei near colonic adenocarcinoma. Statistical analysis.

The normal mucosa adjacent to colonic adenocarcinoma (marginal or transitional mucosa) has been shown to have subtle alterations of architecture, surface glycoproteins and proliferative activity. To evaluate possible changes in nuclear configurations in this marginal mucosa, a large set of cytometric features was evaluated using a computer-assisted video analysis system. Preliminary statistical analysis of the measurements identified six nuclear features useful for discriminating marginal mucosa nuclei from normal (control) mucosa nuclei: total optical density (OD), nuclear area, chromatin texture (from gray value cooccurrence matrix), chromatin coarseness, average OD of nuclear staining and peripheral tendency of the chromatin in the nucleus. An analysis of variance revealed that both patient-to-patient and gland-to-gland variation would limit the usefulness of any one feature as a screening tool. As a group, however, these six features should be investigated further as markers of preneoplastic changes in histologically normal-appearing mucosa.     

Architectural, morphometric and photometric features and their relationship to the main subjective diagnostic clues in the grading of prostatic cancer

Novel software was developed to perform quantitative measurements of architectural and nuclear features in tissue sections. A pilot study was then undertaken to determine the diagnostic relevance of these quantitative features in prostatic tissue and the relationship of these objective features to the subjective clues used by practicing pathologists in the grading of prostatic adenocarcinoma. From a group of 82 cases of adenocarcinoma of the prostate with long-term follow-up, a subset of 15 cases that included 5 each in Mostofi grades I, II and III was carefully selected for analysis. Consecutive sections from each case were stained with hematoxylin and eosin or the Feulgen stain for visual and cytometric evaluations, respectively. The most important differences in the objective architectural features observed between the Mostofi grade I and II cases were the number of nuclei per gland and their distance from the glandular center. Significant differences were also noted in gland size and the variation in gland size. The Mostofi grades were also significantly different in terms of quantitative high-resolution features measuring nuclear size and its variation, total nuclear DNA content and the proportion of very aneuploid nuclei. There was a fairly good agreement between many of the subjective diagnostic clues and their corresponding quantitative architectural and nuclear features. This work (1) significantly extended the capabilities of our PC-based microphotometer system to analyze glandular tissue specimens, (2) provided insight into the objective bases for the expert diagnosis of adenocarcinomas of the prostate and (3) gave preliminary evidence of the ability of quantitative architectural features and high-resolution cytometric features to discriminate between the major diagnostic categories of these lesions.     

Risk biomarker assessment for breast cancer progression: replication precision of nuclear morphometry.

Nuclear morphometry is a method for quantitative measurement of histopathologic changes in the appearance of stained cell nuclei. Numerous studies have indicated that these assessments may provide clinically relevant information related to the degree of progression and malignant potential of breast neoplasia. Nuclear features are derived from computerized analysis of digitized microscope images, and a quantitative Feulgen stain for DNA was used. Features analyzed included: (1) DNA content; (2) nuclear size and shape; and (3) texture features, describing spatial features of chromatin distribution. In this study replicated measurements are described on a series of 54 breast carcinoma specimens of differing pathologic grades. Duplicate measurements were performed using two serial sections, which were processed and analyzed separately. The value of a single feature measurement, the nuclear area profile, was shown to be the strongest indicator of progression. A quantitative nuclear grade was derived and shown to be strongly correlated with not only the pathologic nuclear grade, but also with tubule formation, mitotic grade, and with the overall histopathologic grade. Analysis of replication precision showed that the standard methods of the histopathology laboratory, if practiced in a uniform manner, are sufficient to ensure reproducibility of these assessments. We argue that nuclear morphometry provides a standardized and reproducible framework for quantitative pathologic assessments.     

Detection of underlying characteristics of nuclear chromatin patterns of thyroid tumor cells using texture and factor analyses

BACKGROUND: Aspiration biopsy cytology of thyroid tumors has been used more frequently in recent times to differentiate between malignant and benign lesions. Chromatin patterns of the tumor cell nuclei are one of most important factors for cytologic diagnosis. The interpretation of nuclear chromatin patterns is subjective and more difficult than that of nuclear size or shape. In the present report, we investigated how to detect underlying chromatin characteristics of benign and malignant thyroid tumor cells by means of texture and factor analyses. METHODS: We employed a computer-aided system in which light microscopy was combined with an image processor and monochrome camera. Using this system, 100 randomly selected cells in a Papanicolaou stained, aspiration biopsy cytologic smear in each case of 39 benign and malignant thyroid tumor cases were digitized. We applied two-dimensional and higher texture analyses with the use of co-occurrence and run-length matrices to analyze the chromatin patterns. Factor analysis was used to determine whether a large number of independent variables actually measured one or more underlying common variables. RESULTS: According to parameters with high factor-loading values, the morphologic chromatin characters were classified into three categories according to heterogeneity, contrast, and homogeneity of chromatin patterns. On the basis of analyses with these morphologic categories, nuclei of papillary carcinoma showed higher contrast of chromatin patterns than did those of the benign group. Moreover, there was a variety of contrasting chromatin patterns among cells in each papillary carcinoma case in comparison with the benign group. In contrast, follicular carcinomas showed a significant difference in the standard deviation of factor 3, which indicated more monotonous chromatin patterns among cells in each follicular carcinoma case than in each benign case. CONCLUSION: We believe that this technique, using texture and factor analyses, is useful in the detection of underlying characteristics of nuclear chromatin patterns in aspiration biopsy cytology.     

Potential of radial basis function neural networks in discriminating benign from malignant lesions of the lower urinary tract

OBJECTIVE: To investigate the potential value of morphometry and neural network tools for discriminating benign from malignant nuclei and lesions of the lower urinary tract. STUDY DESIGN: The study group consisted of 33 cases of lithiasis, 41 cases of inflammation, 66 cases of benign hyperplasia of the prostate, 4 cases of carcinoma in situ, 48 cases of grade 1 transitional cell carcinoma of the bladder (TCCB) and 123 cases of grade 2 and 3 TCCB. Images of routinely processed voided urine smears stained by the Giemsa technique were analyzed by a custom image analysis system. Analysis of the images gave a data set of features from 31,158 nuclei. A radial basis function (RBF)-type neural network was employed to discriminate benign from malignant nuclei, based on the extracted morphometric and textural features. Subsequently a second RBF classifier was employed to discriminate benign from malignant cases. The nuclei from 156 randomly selected cases (50% of total cases) was used as a training set, and the nuclei from the remaining 159 cases made up the test set. Similarly, in an attempt to discriminate at the patient level, the same 156 cases were used to train an RBF classifier; the remaining 159 cases were used for the test set. The cases used for training and testing the 2 classifiers (nuclear and patient level) were the same for the 2 kinds of classifiers. RESULTS: Application of the RBF classifier permitted the correct classification of 93.64% of benign nuclei and 85.61% of malignant, giving an overall accuracy of 84.45%. At the patient level the RBF classifier permitted an overall accuracy of 94.97%. These results were on the test sets. CONCLUSION: The role of nuclear morphologic features in the cytologic diagnosis of lower urinary tract alterations was confirmed by the results of this study. The observed overlap in feature space indicates that the nuclear characteristics do not form strictly separate clusters; that fact explains the difficulty morphologists have with reproducible identification of nuclei from the lower urinary tract. Application of RBF offers good classification at the nuclear and patient level and promises to become a powerful tool for everyday practice in the cytologic laboratory.     

Karyometric features of low and high grade glial tumors as compared with their MRI appearance

OBJECTIVE: To compare the results of a magnetic resonance imaging (MRI) grading designed to identify low and high grade gliomas with karyometry used as a tool to grade primary brain tumors. STUDY DESIGN: A consecutive series of 23 primary brain tumors was selected for this study. The neuroradiologist, not knowing the histologic diagnoses, divided the cases into low and high grade categories on the basis of the following 7 features: border sharpness, heterogeneity without contrast, cavitation, contrast enhancement, hypervascularity, mass effect and perifocal T2 hyperintensity. To each feature was given a numerical value, ranging from 1 to 3. All the cases were reviewed and classified by the same pathologist, blinded to the MRI diagnosis. Two hundred nuclei per case were recorded, and 93 karyometric features related to nuclear area, total optical density and chromatin distribution were analyzed for each nucleus. Statistical analysis included discriminant analysis, Kruskal-Wallis test, nonsupervised learning algorithm P-index and Beale statistic. RESULTS: Ten cases were classified as low grade on the basis of their MRI features. The corresponding histopathologic diagnoses were: grade 2 astrocytoma in 2 cases and grade 2 oligodendroglioma in 8 cases. An MRI diagnosis of high grade tumor was made in 13 cases. In 10 cases it was confirmed by the histopathologic diagnosis (3 grade 3 astrocytomas, 1 grade 3 oligodendroglioma and 6 glioblastomas). In the remaining 3 cases the histologic examination revealed a low grade tumor, 1 grade 2 astrocytoma and 2 grade 2 oligodendrogliomas. For the purposes of the karyometric analysis the cases were allocated to the low or high grade category according to their histologic diagnosis (13 cases low grade and 10 cases high grade). Nuclei from low and high grade tumors showed clearly different karyometric characteristics. The oligodendroglioma nuclei had abnormality values close to the low grade standard, while the astrocytoma nuclei were a highly dispersed group with characteristics indicative of a higher degree of nuclear abnormality than the oligodendroglioma nuclei. The results of karyometric analysis showed that grade 2 tumors, corresponding to the low grade group, form a rather distinct category from grade 3 and 4 tumors belonging to the high grade group. CONCLUSION: The results of MRI grading based on a series of features that are routinely assessed by the neuroradiologist to reach a final diagnosis correlate highly with the histopathologic diagnosis. Karyometry can be a useful adjunct to histologic grading.     

Karyometric image analysis for intraepithelial and invasive cervical lesions

OBJECTIVE: To derive an objective, numeric measure for the progression of intraepithelial and invasive squamous cell cervical lesions. STUDY DESIGN: Thin-layer cervical cytology preparations from colposcopically confirmed normal cervix, low grade squamous intraepithelial lesions, high grade squamous intraepithelial lesions and carcinoma were identified from a cross-sectional study. Fifty-nine cases representing 4 diagnostic categories were selected, and 2,375 nuclei from epithelial cells representative of the diagnostic category were randomly selected for imaging and measurement from these cases. Additionally, 1,378 visually normal appearing intermediate cells from low and high grade squamous intraepithelial lesions, as well as from carcinoma cases, were identified for analysis. The nuclei were quantitatively characterized, and discriminant analyses were performed to derive a progression curve from normal cytology to carcinoma. RESULTS: The lesion signatures show a clear increase in nuclear abnormality with increasing progression. A progression curve was derived based on mean discriminant function scores for each diagnostic category and on the mean nuclear abnormality values for the nuclei in each category, as expressed by their deviation in feature values from normal reference nuclei. CONCLUSION: A numeric assessment of lesion progression for cervical precancerous and cancerous lesions based on karyometric measurements is possible and may provide an objective, precise characterization of each lesion as well as a basis for improved performance in automated cytology-based cervical cancer screening.     

Three distinct stages of apoptotic nuclear condensation revealed by time-lapse imaging, biochemical and electron microscopy analysis of cell-free apoptosis

During apoptotic execution, chromatin undergoes a phase change from a heterogeneous, genetically active network to an inert highly condensed form that is fragmented and packaged into apoptotic bodies. We have previously used a cell-free system to examine the roles of caspases or other proteases in apoptotic chromatin condensation and nuclear disassembly. But so far, the role of DNase activity or ATP hydrolysis in this system has not yet been elucidated. Here, in order to better define the stages of nuclear disassembly in apoptosis, we have characterized the apoptotic condensation using a cell-free system and time-lapse imaging. We demonstrated that the population of nuclei undergoing apoptosis in vitro appears to follow a reproducible program of nuclear condensation, suggesting the existence of an ordered biochemical pathway. This enabled us to define three stages of apoptotic chromatin condensation: stage 1 ring condensation; stage 2 necklace condensation; and stage 3 nuclear collapse/disassembly. Electron microscopy revealed that neither chromatin nor detectable subnuclear structures were present inside the stage 1 ring-condensed structures. DNase activity was not essential for stage 1 ring condensation, which could occur in apoptotic extracts depleted of all detectable DNase activity. However, DNase(s) were required for stage 2 necklace condensation. Finally, we demonstrated that hydrolyzable ATP is required for stage 3 nuclear collapse/disassembly. This requirement for ATP hydrolysis further distinguished stage 2 from stage 3. Together, these experiments provide the first steps towards a systematic biochemical characterization of chromatin condensation during apoptosis.     

Chromatin texture analysis of cortical adrenal gland adenomas, including incidentalomas, and adjacent normal-appearing cortical tissue

OBJECTIVE: To describe, by morphometric and chromatin texture analysis, a series of adrenal gland lesions, including Cushing's and Conn's adenomas and incidentalomas. STUDY DESIGN: The material for the study consisted of five consecutive cases of incidentaloma, three cases of Conn's adenoma and three cases of Cushing's adenoma. Also included were five cases of adrenal carcinoma. Sections were stained according to the Feulgen procedure. Measurements were taken from the nodules and from two different zones, identified as outer and inner parts, of the normal-appearing adrenal cortex adjacent to the tumor. Data on approximately 50 nuclei were recorded for each of these three sites (tumor and outer and inner normal-appearing adrenal cortex). The nuclei were subjected to feature extraction and were analyzed by identification procedures--i.e., establishing nuclear and lesion signatures. RESULTS: The total optical density (OD) distributions of the nuclei from the normal-appearing adrenal cortex pointed to their diploid or near-diploid nature. In incidentalomas there was a very small increase in the number of nuclei, with increased total OD. In Conn's adenoma there was a noticeable but modest extension of the total OD distribution into the higher OD range. This trend continued for Cushing's adenoma. The pixel OD histograms for nuclei from normal-appearing tissue and from incidentalomas were hardly distinguishable. Starting with nuclei from Conn's adenoma, a shift toward lower pixel OD values began. The trend continued for nuclei from Cushing's adenoma and was very pronounced for nuclei from carcinoma. The nuclear signatures showed no appreciable difference between nuclei from normal-appearing cortex and from incidentaloma. Nuclei from Conn's adenoma were more similar to those from normal tissue in their signatures than nuclei from Cushing's adenoma. In fact, the nuclear signatures from Cushing's adenoma were almost identical to those of carcinoma. The lesion signatures for normal tissue, incidentaloma and Conn's adenoma confirmed the results seen in the nuclear signatures. There was a very modest increase in the number of nuclei with greater deviation from normal in incidentalomas, and the trend was more obvious in Conn's adenoma. However, in Cushing's adenoma there was a very substantial increase in the number of nuclei, with large deviations of their nuclear chromatin texture from normal. CONCLUSION: Computer-assisted analysis of nuclear characteristics proved useful in identifying and describing differences between groups of tumors arising in the adrenal cortex and highlighted the similarity between incidentalomas and adjacent normal-appearing cortex and between Cushing's adenoma and adrenal carcinoma.