Karyometry and histometry of renal-cell carcinoma

In an attempt to more objectively predict the outcome of renal cancers, karyometric and histometric studies were performed using an interactive computer-based system for the quantitative analysis of tissue sections. Analysis showed a significant relationship between patient survival and metastases and the histometric parameters of nuclear elongation, nuclear crowding and mitotic density, as well as tumor grade. Patients who died tended to have a high mitotic density, elongated and crowded nuclei and high-grade tumors. Ploidy showed no significant correlation with prognosis while nuclear elongation and crowding did. Differences in histologic grade were significantly associated with several histometric variables, including nuclear area, shape, crowding, elongation and mitotic density.     

Tissue architectural features for the grading of prostatic carcinoma

In research for the development of a computer-aided workstation for the objective grading of prostatic carcinoma, tissue architectural (histometric) features were analyzed in ten cases each of well-differentiated, moderately differentiated and poorly differentiated carcinoma (as subjectively graded by the consensus of a panel of experts). Sections were cut at 4 microns, stained by the Feulgen reaction and digitized by two different video-based photometric systems. Some images were interactively segmented, considering the histometric clues to be studied; others were automatically segmented by an expert system-guided technique. The latter procedure produced good results, with over 90% of the nuclei judged to be correctly segmented in 64% of the fields studied and over 80% in another 24% of the fields. While the number of nuclei per field provided some separation of well-differentiated from other lesions, the number of nuclei per gland distinguished between well-differentiated and moderately differentiated lesions. Simplicial decomposition of the images also provided a measure of the degree of differentiation, as did the "texture" of the nuclear placement, based on two run-length statistics. Combination of the run-length features distinguished the three categories of lesions with statistical significance. The results of this study provided insights into the problems (such as the effect of field boundaries) faced in the design of an computer-aided grading system. They also showed the value of expert system-guided scene segmentation and of such histometric features as the field cellularity and the number of nuclei per gland for the discrimination between lesions of different grades of differentiation.     

Karyometric marker features in fine needle aspirates of invasive follicular carcinoma of the thyroid.

Karyometric measurements were performed on fine needle aspirates of clearly identifiable tumor areas and adjacent normal-appearing areas in the surgical specimens from ten patients with invasive follicular carcinoma of the thyroid. Similar measurements were performed on aspirates from nine patients free of thyroid disease (controls). A total of 95 karyometric features were evaluated for each nucleus. Analysis of variance of optical density values indicated (1) a similarity between tumor and normal-appearing nuclei from carcinoma cases, (2) a significant difference between those nuclei and control nuclei and (3) that most of the differences were due to the differences of tissue origin. Stepwise linear discriminant analysis selected ten features that produced a statistically highly significant separation of tumor nuclei from control nuclei. A similar analysis selected six features that produced a statistically highly significant discrimination of normal-appearing nuclei from control nuclei; the validity of those karyometric features as markers of malignancy in normal-appearing nuclei from tissues adjacent to invasive follicular carcinomas of the thyroid was demonstrated by analysis in further training and control sets of nuclei. This analysis in thyroid aspirates identified more marker features than did a previous similar analysis using tissue sections.     

Correlation between automated DNA ploidy measurements of Hürthle-cell tumors and their histopathologic and clinical features

The treatment of Hürthle-cell tumors of the thyroid is controversial because of their rarity and the inconsistent histopathologic criteria for their diagnosis. In order to obtain more objective criteria for the management of Hürthle-cell tumors, the nuclear DNA content of cells from 20 cases was measured with the MicroTICAS system and the correlation between the DNA distribution patterns and the clinical and histopathologic findings was evaluated. Three main DNA patterns were found: euploid, polyploid and aneuploid. The euploid or polyploid Hürthle-cell tumors came from patients who did not develop distant metastases or recurrence whereas the aneuploid variants came from patients who died of their disease and/or developed distant metastases and recurrence. Various correlation analyses were performed between DNA ploidy and age, sex, size of tumor, growth pattern, pleomorphism, invasion and metastases. Our data suggests that an aneuploid DNA pattern or one with a large percentage of aneuploid nuclei with DNA content exceeding 5N may predict eventual metastases or recurrence from Hürthle-cell tumor.     

High-resolution color video cytophotometry

Comparison was made between cytophotometric measurements obtained using two data acquisition systems, one a microphotometer and the other a rapid video camera system, to ascertain whether the degradation of data with the faster video acquisition system still results in recorded images of sufficient quality to permit computer discrimination between cells of very similar appearance. Normal-appearing intermediate cells from cases with normal cytology and those from patients with dysplasia or malignant disease, as well as the subvisual markers within these cells that have rendered them capable of cytophotometric discrimination, were used for the study. Comparison of the data recorded by the two systems indicates that the diagnostic information is preserved in the change-over to a full-field, video-rate scanning system, with differences in the data caused primarily by differences in the spectral response of the two systems. This was reflected in the substantial differences observed in the color-related features and the lesser differences seen in the textural features, while the morphometric features (outline and shape) were virtually unaffected. The differences were primarily expressed on a cell-to-cell basis; in sets of about 300 cells, which would be used in patient-to-patient comparisons, the feature values showed remarkable consistency between the two systems.     

Image understanding system for histopathology

An image understanding machine vision system for histological diagnoses is based on three interacting expert systems: a diagnostic expert system utilizing terms familiar to pathologists, an interpretive expert system relating human diagnostic concepts to computable histometric features and a scene segmentation expert system which extracts the diagnostic information from the imagery. The control software for the image understanding system resides on a multiprocessor computer. This article details measures to maintain system efficiency and to accommodate the requirements of interprocess communication and processing task scheduling.     

The rejection of noncellular artifacts in Papanicolaou-stained slide specimens by an automated high-resolution system. Identification of important cytometric features

The important cytodiagnostic features that permit discrimination of typical cell types by high-resolution image analysis and pattern recognition techniques have been previously studied in detail. An automated system for the diagnosis of Papanicolaou-stained specimens must also deal, however, with the "real world" of extraneous noncellular artifacts and debris found on every slide. Features that are ideal for the separation of typical normal and abnormal cells may not be adequate by themselves to reject these objects. A new set of discriminatory features must be found. In order to identify those features, a large set of images acquired using the TICAS high-resolution television rapid-scanning system was analyzed and studied. These images, from a variety of slide types, included normal cells, abnormal cells and noncellular artifacts identified by low-resolution preprocessing logic as suspicious enough to warrant high-resolution study. The results indicate that the more important features for such discrimination are not those traditionally important in distinguishing abnormal from normal cells but include color relations, shape measures, boundary properties and texture features.     

Histometric features for the grading of prostatic carcinoma

Histometric features for the objective grading of prostatic adenocarcinoma in histologic specimens were analyzed in five cases each of well, moderately and poorly differentiated lesions. Tissue sections from the selected cases were stained by the Feulgen method and digitized by a video-based microphotometer. Twenty total fields were recorded for each grade: ten at high resolution (an image sampling of 0.5 micron per pixel) and ten at low resolution (0.8 micron per pixel), with two fields per case recorded at each resolution. The images were segmented by an automated expert system-guided scene segmentation procedure. The performance of that procedure was measured by comparing the automated counts of nuclei in the segmented fields to the visual counts made by a pathologist in the same fields. For well, moderately and poorly differentiated cases, respectively, the nuclear counts made by the expert system at high resolution were 2.7%, 4.2% and 4.7% higher than the visual counts (as estimated from a total of 6,628 nuclei), but 1.2%, 2.5% and 1.1% lower at low resolution (10,329 nuclei). High-resolution features and tissue textural features were computed for each case. The high-resolution features showed good separation between the three groups of cases. The tissue textural features showed consistent separation between well and moderately differentiated cases. The relaxation of the spatial resolution (to 0.8 micron/pixel spacing) did not affect the selection of features, but led to less separation between the data from different grades. In conclusion, the automated system performed satisfactorily in distinguishing sections of prostatic tumors of varying degrees of differentiation.     

Discriminant analysis on cells from developing squamous cancer of the respiratory tract

Cytologic preparations made from the tracheobronchial tree taken by the Schreiber catheter have been scanned by three color microphotometry. The digitized cell images were processed by the analytical cytodiagnostic programs of the TICAS system. Cells were sorted into two control groups and five groups of increasing atypia ranging from normal epithelium to invasive squamous cell carcinoma. Standard statistical tests, including Wilk's Lambda, Rao's V, and the Kruskal-Wallis tests are performed on these subsets of cell image features. This study demonstrates that discriminant analyses permit differentiation between normal cells and those from marked atypia or carcinoma and that the classification achieves a high degree of agreement with visual assignment.