ABSTRACT
OBJECTIVE: To search for morphologic nuclear features in the epithelial lining of odontogenic keratocysts to differentiate simple from Gorlin syndrome cysts. STUDY DESIGN: Five cases of syndrome-associated keratocysts and five of simple ones were studied. Thirty nuclei from the epithelial basal layer for each case were analyzed by the shape analytical morphometry (SAM) software system to quantitatively evaluate nuclear dimensions (area, perimeter, diameter), contour irregularities and nuclear shape asymmetries. Results were subjected to Student's t test and cluster analysis. RESULTS: Values of nuclear dimensions were very close in both groups of keratocysts, without any significant statistical differences. The variables related to nuclear profile irregularities, as well as those describing nuclear asymmetry, showed significantly higher values (P < .001) in syndromic cysts. Cluster analysis produced two different clusters by using variables related to nuclear contour irregularities. CONCLUSION: Preliminary results indicate the existence of nuclear morphologic differences between simple and syndromic cysts.
Subject(s)
Basal Cell Nevus Syndrome/genetics , Cell Nucleus/ultrastructure , Adult , Aged , Basal Cell Nevus Syndrome/pathology , Cell Nucleus/genetics , Cluster Analysis , Diagnosis, Differential , Disease Progression , Female , Humans , Male , Middle Aged , Mutation , Odontogenic Cysts/genetics , Odontogenic Cysts/ultrastructureABSTRACT
The revised edition of the WHO classification of brain tumours now includes the "atypical" meningioma (grade II) which should be placed between the common type (grade I) and anaplastic type (grade III) according to histomorphological features and prognosis. However, diagnostic criteria for atypical meningioma are vague and the significance of brain invasion in the determination of malignancy is controversial. Nuclear pleomorphism and mitoses are usually considered the most important parameters to distinguish atypical and malignant meningiomas. According to WHO classification we selected eight cases of meningioma diagnosed as atypical (3 cases) and malignant (5 cases). All the tumours were supratentorially located. Nine cases of benign meningiomas were also studied as a control group. Morphometrical analysis was carried out by S.A.M. (Shape Analytical Morphometry) system. S.A.M. logical architecture assumes that each irregular shape contains elements of two distinct logical domains: gross distortions that interest the contour and its local perturbations. These features were investigated separately by analytical procedures to acquire independent parameters both on the logical and the numerical level. The results, statistically evaluated, show that nuclear pleomorphism is not a satisfactory criterion, if used alone, to distinguish atypical from malignant meningioma (Discriminant Analysis: 19% of minimum error).
Subject(s)
Brain Neoplasms/pathology , Meningioma/pathology , Brain Neoplasms/classification , Humans , Neoplasm StagingABSTRACT
Malignant mesothelioma is difficult to distinguish from other pleural malignancies and also from benign mesothelial lesions. A morphometric study has been performed to distinguish between them using quantitative size and shape parameters. Seven cases of malignant mesothelioma, 5 cases of pleural metastatic adenocarcinoma and 4 cases of benign mesothelial lesions were selected and subjected to S.A.M. (Shape Analytical Morphometry). The results, statistically evaluated, showed that morphometric parameters can be proposed for diagnostic purposes being useful in the discrimination among the three populations. In fact, multivariate discriminant analysis (MDA) of the quantitative parameters obtained by morphometrical study distinguished the three groups of lesions with only 2% of error between BML/MM, 7% of error between BML/MA and 25% between MM/MA.
Subject(s)
Image Interpretation, Computer-Assisted , Mesothelioma/pathology , Pleural Neoplasms/pathology , Adenocarcinoma/diagnosis , Adenocarcinoma/secondary , Biopsy , Cell Nucleus/ultrastructure , Cell Size , Diagnosis, Differential , Epithelium/pathology , Humans , Hyperplasia , Mesothelioma/diagnosis , Multivariate Analysis , Pleural Neoplasms/diagnosis , Pleural Neoplasms/secondary , SoftwareABSTRACT
OBJECTIVE: To determine whether nuclear morphometry can confirm or add useful information to classic clinicopathological prognosticators to identify the subpopulation of breast carcinoma patients with node-negative (N-) disease, at high risk of disease relapse. STUDY DESIGN: On the basis of results obtained by clinicopathologic evaluation of a group of patients with N- breast cancer, on a test group of 56 cases (32 patients disease free and 24 with relapse), we performed a morphometric analytical study of nuclei using the Shape Analytical Morphometry (SAM) software system; 20 nuclei for each case and 17 morphometric parameters for each nucleus were analyzed. RESULTS: The SAM system allowed us to quantify shape differences in nuclei in terms of contour irregularities and asymmetries along with evaluation of nuclear dimensions. Dimensional and analytic parameters were subjected to univariate (Student's t test) and multivariate (Hotelling's test) analysis. Multivariate discriminant analysis showed that an exact forecast of disease relapse could be made in 77% of patients with N- breast cancer by using a set of six both analytic and dimensional parameters. CONCLUSION: These results confirm that nuclear pleomorphism is the result of both contour irregularities and shape asymmetries and that even though they should be considered preliminary results, they stress the importance of quantitative shape evaluation.
Subject(s)
Breast Neoplasms/pathology , Cell Nucleus/ultrastructure , Lymph Nodes/pathology , Female , Humans , Karyometry/methods , Mitotic Index , Prognosis , Survival AnalysisABSTRACT
Meningiomas are the most common neoplasms of the central nervous system and their biological behavior is not always predictable from the histologic appearance of the tumors. The nuclear pleomorphism seems to be one of the most important morphological features in the prediction of recurrence. By using analytical morphometric methods it is possible to quantify nuclear atypias and to obtain parameters describing nuclear contour irregularities and distortions of the figure. Moreover the amount of information obtained from analytical procedure allowed to discriminate, by multivariate discriminant analysis recurrent or no-recurrent meningiomas (5% of error).
Subject(s)
Cell Nucleus/pathology , Meningeal Neoplasms/pathology , Meningioma/pathology , Neoplasm Recurrence, Local/diagnosis , Discriminant Analysis , Humans , Image Processing, Computer-Assisted , Multivariate Analysis , Reproducibility of ResultsABSTRACT
In the histological grading of oral squamous cell carcinoma (OSCC) nuclear features are very important. Nevertheless evaluation is usually performed in a subjective and not highly reproducible way. The aim of this work was to investigate the relationship between nuclear shape and survival in 30 cases of carcinoma of the tongue. All the patients were divided into two groups: short-term survival and long-term survival. Twenty nuclei for each tumour were submitted to a morphometrical study by the shape analytical morphometry (SAM) software system. It was thus possible to evaluate not only nuclear dimensions but also nuclear contour irregularities and nuclear shape asymmetries. Multivariate discriminant analysis (MDA) of the quantitative parameters obtained by the morphometrical study distinguished the patients of the two groups with only a 10% error; moreover successful cluster analysis was performed by using Fourier parameters. Both these sets of results were achieved mainly owing to the parameters for contour irregularities.
Subject(s)
Carcinoma, Squamous Cell/ultrastructure , Cell Nucleus/pathology , Tongue Neoplasms/ultrastructure , Adult , Aged , Aged, 80 and over , Female , Follow-Up Studies , Humans , Male , Middle Aged , Multivariate Analysis , Prognosis , Survival RateSubject(s)
Mesothelioma/pathology , Pleural Neoplasms/pathology , Cell Nucleus/pathology , Cell Size , Humans , Image CytometryABSTRACT
Eighteen cases of astrocytomas diagnosed as grades 1-3 of malignancy were studied with analytical morphometry to determine if different grades can be discriminated by size and shape parameters related to the nuclei. The shape analytical morphometry system was used to calculate dimensional measurements and express shape irregularities through quantitative parameters. With the shape asymmetry evaluator procedure, nuclear symmetry was evaluated. All parameters subjected to univariate and multivariate strategies were the same in easily distinguishing grade 1 from the others. Grades 2 and 3 could not be discriminated completely by either dimensional or with analytical parameters revealing strong similarities of nuclear shape and dimensions.
Subject(s)
Astrocytoma/ultrastructure , Cell Nucleus/ultrastructure , Astrocytoma/classification , Discriminant Analysis , Humans , Multivariate Analysis , Reproducibility of Results , SoftwareABSTRACT
Histological grading of oral squamous cell carcinoma (OSCC) is usually evaluated in a semiquantitative way and this causes a low grade of reproducibility of this prognostic evaluation. The aim in this preliminary phase is to investigate the relation between nuclear shape (studied by an analytical procedure) and histological grading to evaluate the weight of nuclear shape and dimension in grading formulation. Nine cases of OSCC were studied (3 cases of G1, G2 and G3 respectively) with 20 nuclei for each case. All the tumors were localized on the lip. Histologic grading according to the Bryne system was performed. Each nucleus was submitted to a morphometrical study by the SAM (Shape Analytical Morphometry) system which, apart from dimensions allows us to evaluate nuclear contour irregularities and nuclear shape asymmetry. Nuclei of squamous cell carcinoma show a progressive increase in dimensions (area, perimeter and diameter) from G1 to G3. Nuclei of G3 carcinoma are characterized by the most irregular shape. Size differences (mean value) are significant to differentiate G1 nuclei from G2 and G3 nuclei while shape parameters are useful in distinguishing G3 nuclei from G1 and G2. Multivariate discriminant analysis showed that by using only nuclear parameters it is possible to correctly classify about 80% of nuclei. This study, using quantitative methods, confirmed nuclear pleomorphism to be the most important feature in grading evaluation.