Apoptosis and its clinical significance for bladder cancer therapy.
Explore the source record for details and available documents.
Apoptosis↗
Biomedical subjects
P W Hamilton
Publications and source records attributed to P W Hamilton.
Subtle morphological and molecular changes in normal-looking epithelium in prostates with prostatic intraepithelial neoplasia or cancer.
BACKGROUND: Prostate cancer develops over an extended period of time. Until recently, the events initiating the process and the developments concomitant with the evolution towards invasive disease were largely unknown. METHODS: Analytical and quantitative methods are applied to provide insights into certain individual molecular events and their effects on the complex multiple feedback system of cellular metabolism and regulation in prostate neoplasia. RESULTS: Prostatic intraepithelial neoplasia (PIN) and prostate cancer (PCa) are associated with or possibly preceded by changes in the chromatin of secretory cell nuclei. The changes are detectable with a Bayesian belief network and quantifiable by computer image analysis in prostatic tissue that still appears histologically normal. In addition, normal-looking prostate epithelium shows some molecular changes similar to those present in the associated preneoplastic and neoplastic lesions. Such changes are also occasionally present in normal prostate glands without PIN and cancer. CONCLUSIONS: The subtle morphological and molecular changes of normal-looking epithelium might be seen as the onset of the development of prostatic neoplasia.
Adenocarcinoma↗
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.
Artificial Intelligence↗
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.
Adenocarcinoma↗
Case-based prediction of survival in colorectal cancer patients.
OBJECTIVE: To develop an approach to the prediction of survival in patients with colorectal cancer using nearest neighbor analysis and case-based reasoning. STUDY DESIGN: A total of 216 patients with full clinicopathologic records and five-year follow-up were the subjects of this study. They were divided into a core database of 162 cases and a test group of 54 cases, with follow-up on all patients. When the patient was still alive at the end of the follow-up period, censored survival time was used. For each of the test cases, the four closest neighbors from the database were retrieved and their median survival time recorded and used as the predicted estimate of survival. Case matching was based on a Euclidean multivariate distance measure for the three best predictor variables: patient age, Dukes stage and tubule configuration. Cases with the smallest distance from the test case were considered to be the most similar. The predicted survival times for the test cases were compared with the actual, observed survival in the test cases to determine the success of this approach. RESULTS: The results showed reasonable concordance between observed and predicted survival figures, although there was a large degree of spread. Classification of cases into < or = 60 and > 60 months' survival showed a correct classification rate of 63%. For the prediction of survival time, the distribution of differences between observed and predicted survival times for the uncensored test cases had a median value of--5 months but also showed a wide dispersion of values. Correlation of observed and predicted survival times, while not reaching statistical significance at P < .05, did show a strong positive association. CONCLUSION: Case-based approaches to the prediction of survival times in cancer patients are important. The results of the current study illustrate the difficulties in applying this approach to survival data and highlight the complexity of patient information and the inability to accurately predict patient outcome on a small subset of clinicopathologic features. While extensive work needs to be carried out to improve prediction power, this study illustrates the potential for case-based analyses. The ability to retrieve feature-matched cases from hospital patient databases has clear, independent advantages in patient management, but the ability to provide reliable, targeted prognostic estimates on individual cases should be a common goal in medical research.
Adult↗
Cell proliferation studies in primary synovial chondromatosis.
Primary synovial chondromatosis (PSC) is thought to be a cartilaginous metaplasia, but it may recur locally and malignant change has been reported. Histologically, the cartilage is usually cellular, with binucleate forms. These findings suggest that the disease is not simply a metaplasia but imply a proliferative component. In this study, immunohistochemical detection of Ki-67 protein using an antigen retrieval microwave heating technique and DNA image cytometry (VIDAS image analysis system) has been used to assess the proliferative activity in 20 cases of PSC and the results have been compared with those obtained in other cartilage tissues: ten enchondromas, ten chondrosarcomas, and ten samples of normal articular cartilage. There was no detectable staining for Ki-67 protein in cases of PSC or in benign tissues, but there was a significant association between Ki-67 labelling index and grade in the chondrosarcomas (P < 0.01). The absence of mitotic figures and the lack of Ki-67 protein in PSC are consistent with a metaplasia. All enchondromas gave diploid DNA histograms but non-diploid histograms were obtained i eight cases (40 per cent) of PSC, with significant populations of hyperdiploid and DNA aneuploid cells. The mean DNA content, the percentage of hyperdiploid cells, the percentage of DNA aneuploid cells, and the 2c deviation index were all significantly higher in PSC than in enchondromas (P < 0.01). These findings with image cytometry suggest a proliferative process in the development of at least some cases of PSC. In terms of cell proliferative activity, PSC appears to occupy a position which is intermediate between benign enchondromas and malignant chondrosarcomas, which may explain the aggressive clinical behaviour occasionally seen in this condition.
Bone Neoplasms↗
Bcl-2/Bax ratios in chronic lymphocytic leukaemia and their correlation with in vitro apoptosis and clinical resistance.
Explore the source record for details and available documents.
Apoptosis↗
Inter- and intra-observer variation in the histopathological reporting of cervical squamous intraepithelial lesions using a modified Bethesda grading system.
OBJECTIVE: 1. To assess inter- and intra-observer variation in the histopathological reporting of cervical colposcopic biopsies using a histologic modification of the cytological Bethesda grading system; 2. to determine the histologic profile of those cases which resulted in diagnostic disagreement. METHODS: Consecutive cervical colposcopic biopsies (n = 125) were assessed independently by six experienced histopathologists. Cases were classified as normal, low grade squamous intraepithelial lesion or high grade squamous intraepithelial lesion. Six months later the process was repeated. The degree of inter and intra-observer variation was assessed by kappa statistics. All cases in which there was less than perfect inter and intra-observer agreement were reviewed by the coordinator of the study. RESULTS: In the first round of the study inter-observer agreement was generally poor, with unweighted and weighted kappa values ranging from 0.15 to 0.58 (average 0.30) and from 0.21 to 0.61 (average 0.36) respectively. In the second round inter-observer agreement was better, with unweighted and weighted kappa values ranging from 0.08 to 0.55 (average 0.33) and from 0.22 to 0.59 (average 0.42). Ten of the 15 pairs of observers achieved fair inter-observer agreement using weighted kappa analysis. The degree of intra-observer agreement was better, unweighted and weighted kappa values ranging from 0.26 to 0.61 (average 0.47) and from 0.34 to 0.62 (average 0.51) respectively. Two of the six participants achieved fair intra-observer agreement and two achieved good intra-observer agreement using weighted kappa analysis. There were marked difficulties in the separation of normal squamous epithelium from low grade squamous intraepithelial lesion and in the separation of low grade from high grade squamous intraepithelial lesions. Histopathological review revealed that many of the difficulties in the separation of normal and low grade squamous intraepithelial lesion were in the distinction between superficial vacuolated cells and true koilocytes. Difficulties also resulted in the separation of basal cell hyperplasia, inflammatory associated changes and immature squamous metaplasia from low grade squamous intraepithelial lesion. Conditions which resulted in difficulty in the separation of low grade and high grade squamous intraepithelial lesions included florid koilocytotic change and immature metaplastic squamous epithelium with atypia. In some cases, there was a full spectrum of diagnoses from normal to high grade squamous intraepithelial lesion. These were largely cases of immature metaplastic squamous epithelium with atypia and of thin or atrophic squamous epithelium with atypia. CONCLUSIONS: Most pairs of observers can achieve fair inter-observer agreement in the reporting of cervical colposcopic biopsies using a modified Bethesda system. Intra-observer agreement is also generally fair to good using this system. It may be that a two tier grading system is more appropriate for the histopathological reporting of these biopsies than the traditional three-tier intraepithelial neoplasia (CIN) system.
Biopsy↗
Machine vision in the detection of prostate lesions in histologic sections.
OBJECTIVE: To explore the utility of N-gram encoding for the automated detection and delineation of regions of histologic abnormality in tissue sections of prostate. STUDY DESIGN: Digitized imagery of tissue sections from normal prostate glandular tissue, stroma and regions of well- and poorly differentiated lesions was recorded and successively subdivided into square subregions of 256 x 256 to 16 x 16 pixels. N-grams of N = 2 to N = 6 were computed, with each element assuming a value representing an optical density interval 0.30 units wide, covering the range from optical density = 0.0 to 1.80. Then, from a large database, prototype frequency histograms of the different N-grams were established. For each subregion the Euclidean distances to the different prototype histograms were computed and defined as "distance to prototype" features. Standard discriminant analyses and a nonparametric classifier were used to assign subregions to the different tissue categories. RESULTS: Classification of subregions was achieved for most discrimination tasks at a correct recognition rate ranging from 85% to 100% on both training set and test set data, with a few exceptions. N-grams of N > 4 had considerable discriminatory power. CONCLUSION: N-gram encoding has the potential to provide highly discriminating, texture-based characterization of subregions of digitized imagery of prostate lesions and may be very useful in the development of decision procedures for the automated detection of prostate lesions by a machine vision system.
Algorithms↗
Statistical histometry of the basal cell/secretory cell bilayer in prostatic intraepithelial neoplasia.
OBJECTIVE: To delineate the sampling requirements for a histometric assessment of progression in low grade and high grade prostatic intraepithelial neoplasia (PIN) lesions. STUDY DESIGN: Images of whole glands from normal prostates, low grade PIN lesions and high grade PIN lesions were digitized. The images were processed by a machine vision system and automatically segmented, and a number of histometric characteristics descriptive of the disruption of the basal cell layer were extracted. Next, high-resolution images of secretory cell nuclei still facing or no longer facing intact segments of the basal cell layer were recorded and karyometrically analyzed. RESULTS: For the characterization of an individual lesion a minimum of 20-30 glands should be analyzed to provide an estimate of a progression index. Then, a change in progression, or due to regression, of approximately 16% can be documented. The disruption of the basal cell layer is accompanied by statistically highly significant changes in the chromatin texture and spatial distribution in secretory cell nuclei no longer facing an intact segment of that layer. CONCLUSION: Automated histometry by machine vision can provide valuable quantitative data for diagnostic assessment and for monitoring the efficacy of chemopreventive treatment.
Analysis of Variance↗
Nuclear chromatin texture in prostatic lesions. I. PIN and adenocarcinoma.
OBJECTIVE: To document changes in the chromatin pattern in secretory cell nuclei from prostates with prostatic intraepithelial neoplasia (PIN) or adenocarcinoma. STUDY DESIGN: High-resolution images of nuclei were recorded, and a set of features descriptive of the chromatin texture and spatial distribution was computed. From this data set, features undergoing a monotonic trend of progression were selected and plotted to reveal trends in lesion progression. RESULTS: The nuclear chromatin in secretory cells in prostates with either PIN or malignant adenocarcinoma undergoes distinct and statistically significant changes in its texture and spatial distribution. Two trends of progressive change were observed. First, the values of a number of features descriptive of the clumpiness of the chromatin increase from values found in normal prostates to those recorded for nuclei from low grade to high grade PIN lesions. The second trend is a decrease in the values of the same features from those found in nuclei from high grade PIN still facing an intact basal cell layer to those no longer facing such a layer. This may be the first detectable step in progression towards development of a malignant lesion. There is a further decrease in nuclei in glands immediately adjacent to adenocarcinoma and in malignant lesions themselves. CONCLUSION: The described changes may lend themselves to the monitoring of lesion progression or of response to treatment or to chemopreventive intervention.
Adenocarcinoma↗
Nuclear chromatin texture in prostatic lesions. II. PIN and malignancy associated changes.
OBJECTIVE: The objective of this study was to identify and document prostatic intraepithelial neoplasia (PIN) and malignancy associated changes in secretory cell nuclei from visually normal appearing tissue regions of prostates harboring PIN or adenocarcinoma. STUDY DESIGN: High-resolution digitized images of nuclei were recorded in histologically normal appearing tissue regions at defined distances from the margin of PIN or malignant lesions. Features descriptive of nuclear chromatin texture were computed and used to derive a discriminant function score for each nucleus. RESULTS: Secretory cell nuclei in prostates harboring either PIN or adenocarcinoma were shown to have statistically significantly different chromatin texture from secretory cell nuclei recorded in prostates free from any such lesion. The expression of PIN or malignancy associated changes was documented for distances up to 10 mm from the margin of a lesion. CONCLUSION: The finding of characteristic changes in nuclear chromatin texture of nuclei from histologically normal appearing tissue in prostates with PIN or adenocarcinoma offers the potential for higher sensitivity of detection of such lesions and for earlier detection of changes potentially preceding the development of clinically significant disease.
Cell Nucleus↗
Chromatin texture signatures in nuclei from prostate lesions.
OBJECTIVE: To characterize nuclei from prostatic lesions in a highly specific manner by developing a nuclear chromatin texture signature and to characterize lesions by means of their composition of nuclei with diverse degrees of deviation from normal. STUDY DESIGN: High-resolution digitized imagery of nuclei from normal prostates, from prostatic neoplastic lesions of low and high grade and from histologically normal appearing regions of prostates with low and high grade prostatic intraepithelial neoplasia (PIN) lesions were recorded. A set of 65 features descriptive of the spatial and statistical distribution of nuclear chromatin was computed for each nucleus. These features were arranged and processed to form a distinctive signature. A distance metric from "normal" was defined and computed for each nucleus. RESULTS: Profiles of feature values can, after suitable scaling, be presented as distinctive feature value signatures. For many practical applications, profiles based on a standardized distance from normal nuclei may be more useful. Such profiles allow the derivation of a progression curve, showing increasing distances for diagnostic groups with increasing lesion progression up to high grade PIN lesions. Within each diagnostic group different cases show distinctive distributions of nuclei with differing degrees of deviation from normal, allowing the derivation of a lesion signature. CONCLUSION: Nuclear chromatin texture signatures may be of value for the characterization of both nuclei and lesions. They are based on a more comprehensive use of information offered by the nuclear chromatin pattern than that included in classification methods. While these signatures offer a more specific characterization of a clinical sample, they also are subject to more variability within a diagnostic category. This may not be due to randomness but may reflect some actual differences between lesions.
Adenocarcinoma↗
Case diagnosis as positive identification in prostatic neoplasia.
OBJECTIVE: To apply a distance measure and Bayesian belief network-based methodology to the positive identification of case diagnosis in prostatic neoplasia. STUDY DESIGN: Eight morphologic and cellular features were analyzed in 20 cases of normal prostate, 20 of low grade prostatic intraepithelial neoplasia (PIN), 20 of high grade PIN, 20 of prostatic adenocarcinoma with a cribriform pattern and 20 of prostatic adenocarcinoma with an acinar pattern. The diagnostic distance was evaluated to measure the "extent" to which the feature outcomes of the individual cases differed from the expected profile of outcomes in typical cases of normal prostate, low and high grade PIN, and cribriform and large acinar adenocarcinoma. Belief values were evaluated with a Bayesian belief network (BBN). RESULTS: A bivariate representation of the cumulative absolute diagnostic distances of all the cases from the prototypes of normal prostate and cribriform adenocarcinoma was made. Three separate groups of cases were observed, corresponding to normal prostate, low grade PIN and cribriform adenocarcinoma. An additional group was formed by the cases of high grade PIN and acinar adenocarcinoma--i.e., there was complete overlap between the diagnostic distance values of cases belonging to these two categories. However, these cases showed differences in clue outcomes. To explore the contribution of such observations to case identification, a bivariate representation of the diagnostic distances from high grade PIN and acinar adenocarcinoma was made. The cases then formed five separate groups corresponding to the five diagnostic categories. When the individual cases were considered, their shortest distance was from the prototype of the category into which they were originally diagnosed. The BBN gave these diagnostic categories the highest belief values. CONCLUSION: The combined evaluation of diagnostic distance and belief represents an identification procedure. The numeric value of certainty characterizes individual cases according to the level of progression from PIN toward cancer.
Bayes Theorem↗
Automated histometry in quantitative prostate pathology.
OBJECTIVE: To review progress on the development of machine vision and image understanding in prostate tissue histology and to discuss the problems and opportunities afforded to pathology through the use of these techniques. STUDY DESIGN: A variety of concepts in machine vision are explored, and methodologies are described that have been developed to deal with the complexities of histologic imagery. The theory of human vision and its impact on machine vision are discussed. Software has been specifically developed for the analysis of prostate histology, allowing accurate gland segmentation, basal cell identification and measurement of vascularization within lesions. RESULTS: Image interpretation can be achieved using knowledge-based image analysis and the application of local object-oriented processing. This successfully allows an automated quantitative analysis of histologic morphology in the diagnosis of prostate intraepithelial neoplasia and invasive prostatic cancer. The use of low-power image scanning, based on textural or n-gram mapping, permits the development of fully automated devices for the rapid detection of tissue abnormalities. High-power, knowledge-guided scene segmentation can be carried out for the quantitative analysis of cellular features and the objective grading of the lesion. CONCLUSION: Automated tissue section scanning and image interpretation is now possible and holds much promise in prostate pathology and other diagnostically demanding areas. Issues of standardization still need to be addressed, but the development of such systems will undoubtedly enhance our diagnostic capabilities through the automation of time-consuming procedures and the quantitative evaluation of disease processes.
Humans↗
DNA ploidy by confocal laser scanning microscopy.
Explore the source record for details and available documents.
DNA, Neoplasm↗
Computerized scene segmentation for the discrimination of architectural features in ductal proliferative lesions of the breast.
The distinction between ductal hyperplasia (DH) and ductal carcinoma in situ (DCIS) still remains a problem in the histological diagnosis of non-invasive breast lesions. In this study, a method was developed for the automatic segmentation and quantitative analysis of breast ducts using knowledge-guided machine vision. This permitted duct profiles and intraduct lumina to be identified and their shape, size, and number computed. These were used to derive measures of duct cribriformity and architectural complexity which were examined as an objective tool in the characterization of duct pattern in proliferative lesions. A total of 215 images of ducts were digitally captured from 22 cases of DCIS and 21 cases of DH diagnosed independently by two pathologists. The cribriformity index proved to be a useful measure of duct architecture, showing a nosotonic increase with increasing duct complexity. The number of lumins also increased with increasing overgrowth of ductal epithelium until the duct was filled. Discriminant analysis of the duct characteristics for benign and malignant groups selected the lumen area/duct area ratio and the duct area as significant discriminatory variables and they were combined into a discriminant function. Of the lumens features, the mean area of the lumen and the polar average (mean of the distribution of the number of events with an increasing spiral from the centre of the duct) were combined into a second discriminant function. Plotting cases against these two functions provided good separation of DH and DCIS groups, with correct classification estimated on the training sample as being over 80 per cent. With an increasing incidence of complex proliferative lesions arising from mammography, the ability to diagnose these lesions correctly is more important than ever. The use of expert system-guided machine vision facilitates the quantitative evaluation of breast duct architecture; along with established histological and cytological criteria, it is hoped that this will lead to a more objective means of diagnosis and disease classification.
Aged↗
Automated location of dysplastic fields in colorectal histology using image texture analysis.
Automation in histopathology is an attractive concept and recent advances in the application of computerized expert systems and machine vision have made automated image analysis of histological images possible. Systems capable of complete automation not only require the ability to segment tissue features and grade histological abnormalities, but, must also be capable of locating diagnostically useful areas from within complex histological scenes. This is the first stage of the diagnostic process. The object of this study was to develop criteria for the automatic identification of focal areas of colorectal dysplasia from a background of histologically normal tissue. Fields of view representing normal colorectal mucosa (n = 120) and dysplastic mucosa (n = 120) were digitally captured and subjected to image texture analysis. Two features were selected as being the most important in the discrimination of normal and adenomatous colorectal mucosa. The first was a feature of the co-occurrence matrix and the second was the number of low optical density pixels in the image. A linear classification rule defined using these two features was capable of correctly classifying 86 per cent of a series of training images into their correct groups. In addition, large histological scenes were digitally captured, split into their component images, analysed according to texture, and classified as normal or abnormal using the previously defined classification rule. Maps of the histological scenes were constructed and in most cases, dysplastic colorectal mucosa was correctly identified on the basis of image texture: 83 per cent of test images were correctly classified. This study demonstrates that abnormalities in low-power tissue morphology can be identified using quantitative image analysis. The identification of diagnostically useful fields advances the potential of automated systems in histopathology: these regions could than be scrutinized at high power using knowledge-guided image segmentation for disease grading. Systems of this kind have the potential to provide objectivity, unbiased sampling, and valuable diagnostic decision support.
Adenomatous Polyps↗