Karyometric Features Research Articles

Quantitative histopathology identifies patients with thin melanomas who are at risk for metastases.

This small exploratory study was designed to test the hypothesis that thin melanoma lesions contain nuclei of two similar phenotypes, in different proportions. In lesions likely to progress to metastatic disease, one of these phenotypes predominates. Histopathological sections from 18 cases of thin melanomas which did not progress to metastasis, and from 10 cases which did progress were imaged and digitized at high resolution, with a total of 2084 and 1148 nuclei, respectively, recorded. Five karyometric features were used to discriminate between nuclei from indolent and from potentially metastatic lesions. For each case, the percentage of nuclei classified by the discriminant function as having come from a potentially metastatic lesion was determined and termed as case classification criterion. Standard histopathological criteria, such as ulceration and high mitotic index, indicated in this material the need for intensive therapy for only one of the 10 participants, as compared with 7/10 identified correctly by the karyometric measure. Using a case classification criterion threshold of 40%, the overall accuracy was 86% in the test set. The proportion of nuclei of an aggressive phenotype may lend itself as an effective prognostic clue for thin melanoma lesions. The algorithm developed in this training set appears to identify those patients at high risk for metastatic disease, and demonstrates a basis for a further study to assess the utility of prognostic clues for thin melanomas.

Abstract ED05-04: Presurgical models to effectively screen preventive agents

Abstract ED05-04: Presurgical models to effectively screen preventive agents

Abstract PR-03: Randomized presurgical trial of finasteride vs. flutamide vs. placebo in prostate cancer

Abstract Background: Prostate cancer (PC) is an ideal target for chemoprevention, with high-grade prostatic intraepithelial neoplasia (HGPIN) as its most likely precursor finasteride, a 5α-reductase inhibitor, reduced prostate cancer incidence by 25% in average-risk men. However, a higher proportion of high-grade PC has been noted whose biological significance is unclear. An alternative targeted approach is the use of androgen receptor antagonists such as flutamide. Presurgical window-of-opportunity trials have been proposed as a model to assess the activity of preventive interventions in a cost-effective manner in PC. In this study we test the effect of minimal low-dose flutamide exposure or finasteride in comparison to placebo on biomarkers associated with PC, HGPIN, and normal prostate tissue. Materials and Methods: This is a prospective randomized phase IIB placebo-controlled double-blind presurgical trial of finasteride 5 mg/day (FIN) vs. flutamide 250 mg/day (FLU) vs. placebo (PLA) in men with PC. Patients with biopsy proven PC, clinical stage ≤T2, candidates to radical retropubic prostatectomy were enrolled. Drugs and placebo were administered for 4 to 6 weeks before surgery. A sample size of 120 patients (40 per arm) was calculated to detect significant differences on change in nuclear area (NA) of epithelial cells between treatment and placebo arms (primary endpoint). To establish a direction of NA change from normal to malignancy a discriminant function derived from differences in morphometric parameters in the pretreatment biopsies between the normal epithelium and the PC tissue was applied to the posttreatment groups. Secondary endpoints include change in proliferation markers (Ki67 labeling index, topoisomerase-IIα), in serum PSA and hormones, safety, and toxicity. Results: 125 patients were randomized at four cooperating institutions (41 FIN, 42 FLU, and 42 PLA). Mean age and PSA at baseline were 64 years and 8.7 ng/mL, respectively, without differences among arms. There were significant differences in NA and Ki67LI of normal and neoplastic cells both before and after treatment (NA interquartile range: 27-40µ2 in normal tissue, 30-50µ2 in HGPIN and 36-55µ2 in cancer tissue) but no differences were detected among arms. Image and discriminant analysis performed in a subgroup of patients (16 FIN, 24 FLU, and 20 PLA) showed in the PLA and FLU arms a higher discriminant function score after treatment, with a significant increase of the mean score by 90% and 50%, respectively, meaning that cases treated with placebo or flutamide undergo a statistically significant further progression of karyometric features. Conversely, FIN-treated PC exhibited only a small further progressive change, with a net increase of the mean score by only 8%. LH significantly increased in the FLU arm; PSA and fPSA decreased while T increased significantly in both treatment arms compared to placebo. Treatment was well tolerated. Conclusion: NA and KI67LI were significantly different among normal, HGPIN and PC tissue and between pre- and posttreatment biopsies. Discriminant analysis detected an inhibition of progressive karyometric pattern in patients treated with finasteride relative to low-dose flutamide and placebo. Our results support the use of nuclear changes as measured by karyometry in presurgical models to assess the activity of preventive agents. This talk is also presented as Poster A68. Citation Information: Cancer Prev Res 2010;3(12 Suppl):PR-03.

Gene Expression Analysis of Biological Systems Driving an Organotypic Model of Endometrial Carcinogenesis and Chemoprevention

An organotypic model of endometrial carcinogenesis and chemoprevention was developed in which normal endometrial organotypic cultures exposed to the carcinogen, DMBA (7,12-dimethylbenz[a]anthracene), developed a cancerous phenotype in the absence, but not presence of subsequent treatment with a flexible heteroarotinoid (Flex-Het), called SHetA2. A discriminant function based on karyometric features of cellular nuclei and an agar clonogenic assay confirmed these histologic changes. Interpretation of microarray data using an internal standard approach identified major pathways associated with carcinogenesis and chemoprevention governed by c-myc, p53, TNFalpha and Jun genes. Cluster analysis of functional associations of hypervariable genes demonstrated that carcinogenesis is accompanied by a stimulating association between a module of genes that includes tumor necrosis factor alpha (TNFalpha), c-myc, and epidermal growth factor-receptor (EGF-R) and a module that includes insulin-like growth factor I-receptor (IGF-IR), p53, and Jun genes. Two secreted proteins involved in these systems, tenascin C and inhibin A, were validated at the protein level. Tenascin C is an EGF-R ligand, and therefore may contribute to the increased EGF-R involvement in carcinogenesis. The known roles of the identified molecular systems in DMBA and endometrial carcinogenesis and chemoprevention supports the validity of this model and the potential clinical utility of SHetA2 in chemoprevention.

Karyometry of the Colonic Mucosa

The study summarizes results of karyometric measurements in epithelial cells of the colorectal mucosa to document evidence of a field effect of preneoplastic development among patients with colorectal adenocarcinoma or adenoma. Karyometric analyses were done on high-resolution images of histologic sections from 48 patients with colorectal adenocarcinomas and 44 patients with adenomas and on images from matching normal-appearing mucosa directly adjacent to such lesions, at a 1-cm and 10-cm distance from the lesions or from the rectal mucosa of adenoma patients, as well as from 24 healthy normal controls with no family history of colonic disease. The nuclei recorded in the histologically normal-appearing mucosa of patients with either colorectal adenoma or adenocarcinoma exhibited differences in karyometric features in comparison with nuclei recorded in rectal mucosa from patients who were free of a colonic lesion. These differences were expressed to the same extent in tissue adjacent to the lesions and in normal-appearing tissue as distant as the rectum. The nuclear chromatin pattern may serve as an integrating biomarker for a preneoplastic development. The field effect might provide an end point in chemopreventive intervention trials.

Chromatin Phenotype Karyometry Can Predict Recurrence in Papillary Urothelial Neoplasms of Low Malignant Potential

Background: A preceding exploratory study (J. Clin. Pathol. 57(2004), 1201–1207) had shown that a karyometric assessment of nuclei from papillary urothelial neoplasms of low malignant potential (PUNLMP) revealed subtle differences in phenotype which correlated with recurrence of disease. Aim of the Study: To validate the results from the exploratory study on a larger sample size. Materials: 93 karyometric features were analyzed on haematoxylin and eosin-stained sections from 85 cases of PUNLMP. 45 cases were from patients who had a solitary PUNLMP lesion and were disease-free during a follow-up period of at least 8 years. The other 40 were from patients with a unifocal PUNLMP, with one or more recurrences in the follow-up. A combination of the previously defined classification functions together with a new P-index derived classification method was used in an attempt to classify cases and identify a biomarker of recurrence in PUNLMP lesions. Results: Validation was pursued by a number of separate approaches. First, the exact procedure from the exploratory study was applied to the large validation set. Second, since the discriminant function 2 of the exploratory study had been based on a small sample size, a new discriminant function was derived. The case classification showed a correct classification of 61% for non-recurrent and 74% for recurrent cases, respectively. Greater success was obtained by applying unsupervised learning technologies to take advantage of phenotypical composition (correct classification of 92%). This approach was validated by dividing the data into training and test sets with 2/3 of the cases assigned to the training sets, and 1/3 to the test sets, on a rotating basis, and validation of the classification rate was thus tested on three separate data sets by a leave-k-out process. The average correct classification was 92.8% (training set) and 84.6% (test set). Conclusions: Our validation study detected subvisual differences in chromatin organization state between non-recurrent and recurrent PUNLMP, thus allowing a very stable method of predicting recurrence of papillary urothelial neoplasms of low malignant potential by karyometry.

Exploratory Study of Ovarian Intraepithelial Neoplasia

This was an exploratory study to test two hypotheses related to potential epithelial precursors to ovarian cancer: (a) histologically normal ovarian surface epithelium exhibited changes in the nuclear chromatin pattern, which indicate an ovarian abnormality, and (b) such changes were detectable in the ovarian surface epithelium of cancer-free subjects who were at high risk for ovarian cancer. Ovaries were carefully collected to avoid damage to the surface epithelium. Five-micron-thick histologic sections were cut and stained with H&E. High-resolution images were recorded from the ovarian surface epithelium and from the underlying stroma of ovaries from normal women (10 cases), women at high risk of developing ovarian cancer (7 cases), and histologically normal areas adjacent to ovarian cancer (3 cases). Karyometric features and measurements of nuclear abnormality were computed for 3,390 epithelial nuclei. Discriminant function analyses and unsupervised learning algorithms were employed to define deviations from normal and to identify the subpopulations of nuclei exhibiting these changes. Epithelium from ovaries harboring a malignant lesion had changes in the nuclear chromatin pattern consistent with a second phenotype, which were not visually detected with histopathologic surveillance. This phenotype was also present in the ovaries obtained from women at increased risk of ovarian cancer, suggesting that it may represent a premalignant abnormality. These changes were statistically significant. The observed changes in karyometric features were sufficiently distinct to warrant further study as both diagnostic and prognostic biomarkers for early detection and prevention of ovarian cancer.

Karyometry detects subvisual differences in chromatin organisation state between non-recurrent and recurrent papillary urothelial neoplasms of low malignant potential

Aim: To analyse nuclear chromatin texture in non-recurrent and recurrent papillary urothelial neoplasms of low malignant potential (PUNLMPs). Materials: Ninety three karyometric features were analysed on haematoxylin and eosin stained...

Application of multilevel models to morphometric data. Part 2. Correlations.

Multilevel organization of morphometric data (cells are “nested” within patients) requires special methods for studying correlations between karyometric features. The most distinct feature of these methods is that separate correlation (covariance) matrices are produced for every level in the hierarchy. In karyometric research, the cell‐level (i.e., within‐tumor) correlations seem to be of major interest. Beside their biological importance, these correlation coefficients (CC) are compulsory when dimensionality reduction is required. Using MLwiN, a dedicated program for multilevel modeling, we show how to use multivariate multilevel models (MMM) to obtain and interpret CC in each of the levels. A comparison with two usual, “single‐level” statistics shows that MMM represent the only way to obtain correct cell‐level correlation coefficients. The summary statistics method (take average values across each patient) produces patient‐level CC only, and the “pooling” method (merge all cells together and ignore patients as units of analysis) yields incorrect CC at all. We conclude that multilevel modeling is an indispensable tool for studying correlations between morphometric variables.

Quantitative Study of Breast Cancer Progression: Different Pathways for Various In Situ Cancers

The chromatin pattern in nuclei from breast ductal proliferative lesions was quantitatively evaluated with the objective of deriving measures of tumor progression. A total of 110 cases were analyzed. There were 38 cases of normal tissue or benign proliferative lesions, 41 cases of ductal carcinoma in situ (DCIS), and 31 cases of microinfiltrating DCIS and of infiltrating cancer. A total of 9424 nuclei were analyzed. High-resolution images were digitally recorded. For each nucleus, 93 karyometric features descriptive of the spatial and statistical distribution of the nuclear chromatin were computed. Data analysis included establishing a profile of relative deviations of each feature from “normal,” called the nuclear signature, and of lesion signatures as well as of trends of lesion progression. Two trends of evolution could be discerned: one from normal to hyperplasia, atypical hyperplasia, and comedo DCIS as representative of high-grade lesions; and the other from normal to hyperplasia to cribriform DCIS, solid DCIS, and infiltrating cancer, representing lower grade lesions. The nuclei in microinfiltrating foci are distinctly different from nuclei in high-grade comedo DCIS. The nuclei in microinfiltrating foci have a statistically significantly lower nuclear abnormality. They may represent outgrowing clones.

Karyometry of secretory cell nuclei in high-grade PIN lesions.

The goal of this study was a karyometric characterization of secretory cell nuclei in high-grade prostatic intraepithelial neoplasia (PIN) lesions. Specifically, the hypothesis is tested that distinctly different subgroups of nuclei exist in these lesions. High-resolution images of 1,713 nuclei from high-grade PIN lesions were recorded. Karyometric features were computed. Discriminant function scores against normal reference nuclei, and nuclear abnormality values were derived. Data sets were processed by a nonsupervised learning algorithm to establish the presence of subgroups of nuclei with statistically different nuclear chromatin distributions. Three sets of nuclei were formed, facing an intact basal cell layer, a near vanishing basal cell layer, and a gap in the basal cell layer. For each set, a nonsupervised learning algorithm formed three statistically different subgroups of approximately equal sizes. Each subgroup is found in every one of the three sampling locations. The total optical density distribution of nuclei in two subgroups suggests an aneuploid distribution, the third subgroup has a near diploid distribution. Secretory cell nuclei in high-grade PIN lesions are a heterogeneous population, forming statistically different subgroups. Studies aimed at characterizing the progression of such lesions should consider the inhomogeneous nature of these nuclei.

Data representation and reduction for chromatin texture in nuclei from premalignant prostatic, esophageal, and colonic lesions

Background To identify nuclei and lesions with great specificity, a large set of karyometric features is arranged in the form of a linear profile, called a nuclear signature. The karyometric feature values are normalized as z-values. Their ordering along the profile axis is arbitrary but consistent. The profile of the nuclear signature is distinctive; it can be characterized by a new set of variables called contour features. A number of data reduction methods are introduced and their performance is compared with that of the karyometric features in the classification of prostatic, colonic, and esophageal lesions. Methods Contour characteristics were reduced to descriptive statistics of the set of z-values in the nuclear signature and to sequence information. The contour features derived were (1) relative frequencies of occurrence of z-values and of their differences and (2) co-occurrence statistics, run lengths of z-values, and statistics of higher-order dependencies. Performance was evaluated by comparing classification scores of diagnostic groups. Results Rates for correct classification by karyometric features alone and contour features alone indicate equivalent performance. Classification by a combined set of features led to an increase in correct classification. Conclusions Image analysis and subsequent data reduction of nuclear signatures of contour features is a novel method, providing quantitative information that may lead to an effective identification of nuclei and lesions. Cytometry 41:133–138, 2000 © 2000 Wiley-Liss, Inc.

Data representation and reduction for chromatin texture in nuclei from premalignant prostatic, esophageal, and colonic lesions

To identify nuclei and lesions with great specificity, a large set of karyometric features is arranged in the form of a linear profile, called a nuclear signature. The karyometric feature values are normalized as z-values. Their ordering along the profile axis is arbitrary but consistent. The profile of the nuclear signature is distinctive; it can be characterized by a new set of variables called contour features. A number of data reduction methods are introduced and their performance is compared with that of the karyometric features in the classification of prostatic, colonic, and esophageal lesions. Contour characteristics were reduced to descriptive statistics of the set of z-values in the nuclear signature and to sequence information. The contour features derived were (1) relative frequencies of occurrence of z-values and of their differences and (2) co-occurrence statistics, run lengths of z-values, and statistics of higher-order dependencies. Performance was evaluated by comparing classification scores of diagnostic groups. Rates for correct classification by karyometric features alone and contour features alone indicate equivalent performance. Classification by a combined set of features led to an increase in correct classification. Image analysis and subsequent data reduction of nuclear signatures of contour features is a novel method, providing quantitative information that may lead to an effective identification of nuclei and lesions.

Tissue Architecture Analysis in Prostate Cancer and Its Precursors: An Innovative Approach to Computerized Histometry

Aims: It is the aim of these studies to derive a numerically defined progression index for prostatic intraepithelial neoplasia (PIN) lesions. Methods: Histometric and karyometric features were automatically extracted from images of histopathologic sections by a machine vision system. Results: Both histometric and karyometric measures lend themselves to the defining of a progression index. Karyometric features were found to be more sensitive. They allow the detection of very early change. Conclusions: It is possible to measure progression of PIN lesions with precision. The methodology would lend itself for measurement of regression due to chemopreventive intervention.

Proliferation index and karyometric features of pancreatic intraductal proliferative lesions.

The increasing frequency and poor prognosis in pancreatic cancer prompt us to search for morphological lesions being a substrate for its development. Studies of autopsy and surgically resected material as well as recent molecular studies have proved that one of the possible pathways of pancreatic neoplasia is the intraepithelial proliferation – dysplasia – cancer sequence. In the present paper we studied the proliferative activity (Ki‐67 index) in pancreatic intraepithelial proliferative lesions and its correlation with geometric features of cell nuclei as signs of increasing dysplasia. The studies were carried out in a group of 35 patients operated on for pancreatic cancer, chronic pancreatitis and other conditions not associated with the pancreas. We used immunohistochemical methods and basic morphometric parameters. The results of our studies indicate that the cell proliferative activity depends both on the type of epithelial proliferation and underlying pancreatic disease. The values of Ki‐67 index are significantly different in low‐grade proliferation (flat and papillary hyperplasia) and high‐grade proliferation (atypical papillary hyperplasia and carcinoma in situ). A set of karyometric features correlates with Ki‐67 index but there is no single feature which would have a diagnostic value.

Prognostic value of karyometric and clinical characteristics in renal cell carcinoma. Quantitative assessment of tumor heterogeneity.

The variation in tumor cell differentiation within one renal cell carcinoma, also termed tumor heterogeneity, renders visual tumor grading of these carcinomas difficult. Karyometric analysis enables description of nuclear characteristics of multiple tumor areas. Hence, karyometric analysis can be used to quantify tumor heterogeneity and thus may aid in a more objective grading of renal cell carcinoma. In 121 patients with renal cell carcinoma (tumors in International Union Against Cancer [UICC] stages I [5 cases], II [23 cases], III [33 cases], and IV [60 cases]), clinical and karyometric features were studied to obtain routinely applicable prognostic factors. Several parts of the tumor were analyzed to obtain a measure of tumor heterogeneity. Univariate and multivariate Cox regression analyses were used to determine the predictive value of karyometric features independent of tumor stage and other clinical characteristics. The Cox univariate regression analysis showed correlation of several clinical and karyometric characteristics with survival. Of the clinical characteristics, TNM stage, tumor size, weight reduction, and performance status were significantly associated with survival. The karyometric features, especially those measurements associated with tumor heterogeneity (e.g. differences in nuclear size or chromatin texture between tumor subpopulations) were of value in predicting prognosis. In the Cox multivariate regression analysis, the Robson and UICC stages proved to be the most powerful predictors of survival (P < 0.0001). Of the clinical features, weight reduction and performance score were the only characteristics offering additional information regarding tumor stage (P < 0.0001). From the karyometric analysis quantification of anisokaryosis in the tumor at time of diagnosis offered additional prognostic information. Moreover, the differences of karyometric features within the tumor presumably associated with tumor heterogeneity correlated with survival. Using the features from the multivariate analysis, prognostic groups could be defined. We conclude that karyometric analysis offers a useful means for quantifying tumor heterogeneity. Multivariate Cox analysis revealed additional value of a grading system based on karyometric analysis to tumor stage. Karyometric analysis can be a useful tool for stratification of patient populations.

Karyometry in recurrent superficial transitional cell tumors of the bladder.

Transitional cell carcinoma of the bladder has a high recurrence rate after local treatment. Progression to a higher stage occurs in 10-30% of the recurrent tumors, and early detection of potentially progressive tumors is important. In the current study morphometric, densitometric, and chromatin textural features of nuclei of superficial bladder tumors (pTa-T1) were studied to determine the value of karyometric features in the prediction of tumor progression. Seventy-two histological samples from 36 patients, consisting of both the primary and the first recurrent superficial tumor, were analyzed. Patients were divided into two groups: those with tumor progression, defined as an increase in tumor stage or occurrence of metastatic disease, and those without. Discriminant analysis on four karyometric features resulted in correct prediction of prognosis of 78% and 97% in the primary and recurrent tumors, respectively (P < 0.001). Tumor grade and stage did not offer additional information concerning prognosis. Karyometric analysis of recurrent superficial transitional cell tumors can be useful in selecting patients who need a more aggressive therapy. However, tumor characteristics of recurrent tumors varied and continuous evaluation of the karyometric features is necessary for early detection of an increase in the malignant potential of the tumor.

Well differentiated follicular neoplasms of the thyroid: reproducibility and validity of a 'decision tree' classification based on nucleolar and karyometric features.

This study was conducted on fine-needle aspirates of well differentiated follicular neoplasms of the thyroid. A 'decision tree' classification based on the percentage of nucleolated nuclei, percentage of nuclei with two or more nucleoli and mean major nuclear diameter was adopted. We observed that the reproducibility and the validity of the follicular adenoma vs follicular carcinoma discrimination are greater than in the subjective evaluation. Moreover, similar classification results were obtained when measurements were performed either with a fully automated image analysis system or with semiautomatic or manual instrumentation. As for reproducibility of the inter-instrument comparisons, the k statistic values ranged from 0.85 to 1.00 (mean value 0.90, that is, an 'almost perfect' degree of agreement); in the subjective evaluations, the inter-observer comparisons showed values ranging from 0.20 to 0.56 (mean value 0.37, that is, 'fair'). In the decision tree classification, feature value thresholds were selected in order to have specificity of 100% and the predictive value of a positive result (carcinoma) of 100%; accuracy was 87% (range 86-89%), sensitivity 74% (71-79%), the predictive value of a negative result (adenoma) 79% (78-82%). In the subjective evaluation the values were as follows: accuracy 67% (64-71%), sensitivity 57% (50-64%), specificity 77% (71-79%), predictive value of a negative result (adenoma) 64% (61-69%), predictive value of a positive result (carcinoma) 71% (67-75%). The conclusion is that, by using a routine microscope equipped with a micrometer, the preoperative diagnosis of follicular carcinoma from smears can be formulated with a high degree of certainty.