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P W Hamilton

Publications and source records attributed to P W Hamilton.

At least 55 records · Page 3Linked to original sources
PubMed1997

Quantitative study of ductal breast cancer--patient targeted prognosis: an exploration of case base reasoning.

Current analytic methodologies allow the extraction, even from small tumor masses, of extensive information on the biologic characteristics of malignant lesions, such as tumor aggressivity, metastatic potential, drug resistance, and host interactions. Clinical practice now offers a wide range of therapeutic strategies. Information technological advances offer the opportunity to refer to very large data bases of patient anamnestic data, response to treatment and clinical outcome. There is a need to formulate therapy and prognosis for each individual case. Case based reasoning is a knowledge based methodology where the outcome for complex situations can be predicted by referring to a large data base of cases of known outcomes. The preliminary data obtained from this study suggest that case based reasoning may offer a promising approach to individual targeted prognosis.

Breast Neoplasms↗
PubMed1997

Validation of a rapid method to quantify apoptosis in superficial bladder cancer.

OBJECTIVES: To derive and validate a rapid method for calculating apoptotic indices in superficial transitional cell carcinoma (TCC) as a measure of chemosensitivity to mitomycin. MATERIALS AND METHODS: Apoptotic cells, identified by light microscopy in 20 superficial TCC specimens, were expressed as an index of the total tumour cell population within defined fields. For a given field, the total cell population was estimated by: (i) an exhaustive count of the total number of cells in the field and (ii) an abbreviated method in which the number of cells in a subfield was multiplied to provide an estimate of the total field number. Field and specimen estimates were compared using agreement statistics and the intra- and inter-observer reproducibility of apoptotic indices calculated. RESULTS: Cellularity and apoptotic indices obtained using method (ii) were correlated significantly with the true cell counts (P < 0.001). Agreement statistics showed that only 9.4% of counts fell outside two standard deviations (SD) from the mean in field analysis, and only 10% of counts fell outside 2 SD from the mean in specimen analysis. There was a fivefold variation in tumour cell counts among individual fields. CONCLUSIONS: The reported variation in cellularity among fields shows that the calculation of apoptosis must use the total cell population as the reference. The limits of agreement for the estimated and true cell counts are small enough to be confident that the shorter method to estimate cellularity can be used in place of counting all cells.

Antibiotics, Antineoplastic↗
PubMed1997

Diagnostic distance of high grade prostatic intraepithelial neoplasia from normal prostate and adenocarcinoma.

OBJECTIVE: To develop a distance measure based methodology to support the morphological evaluation of high grade prostatic intraepithelial neoplasia (PIN), a direct precursor of prostate cancer. METHODS: Eight morphological and cellular features were analysed in 20 cases of high grade PIN found in radical prostatectomy specimens from patients with adenocarcinoma. The diagnostic distance was evaluated to measure the extent to which the feature outcomes of the individual high grade PIN cases differed from the expected outcome profile of normal prostate, low and high grade PIN, and cribriform and large acinar adenocarcinoma. The belief value for high grade PIN was evaluated with a Bayesian belief network (BBN). RESULTS: Complete separation existed between the cumulative absolute diagnostic distances of these 20 cases from the prototype feature outcomes of high grade PIN and normal prostate the values for which were < or = 3 (range 0 to 3) and > or = 9 (range 9 to 15), respectively. The distances from low grade PIN (range 3 to 9), cribriform adenocarcinoma (range 2 to 8), and large acinar adenocarcinoma (range 5 to 10) were intermediate and showed overlap in their distribution. When taking into consideration whether the severity of feature changes was increasing or decreasing in comparison with the category prototype outcomes, the cumulative directional diagnostic distances from high grade PIN ranged from -3 to +3. Positive distance values were seen relative to low grade PIN (range +3 to +9) and relative to normal prostate (range +9 to +15). Negative values were found relative to cribriform adenocarcinoma (range -8 to +2). The distance values from large acinar adenocarcinoma ranged from -2 to +4 and partly overlapped with those from the high grade PIN category. A bivariate scattergram derived from both diagnostic distance measures showed excellent separation between the groups' distances. BBN analysis confirmed the morphology based diagnosis. The distance evaluation resulted in 18 cases whose belief value for high grade PIN ranged from 0.60 to 0.87. In the remaining two cases the results of the BBN analysis showed a belief value of 0.50 and 0.57 for low grade PIN and of 0.49 and 0.38 for high grade PIN, respectively. CONCLUSIONS: Distance measure based methodology represents a useful diagnostic decision support tool for the accurate evaluation of high grade PIN.

Adenocarcinoma↗
PubMed1997

DNA denaturation sensitivity may invalidate bromodeoxyuridine--DNA flow cytometric analysis of potential doubling times in colorectal tumours.

BACKGROUND: Flow cytometric analysis of 5-bromo-2'-deoxyuridine (BrdU)-substituted DNA has been used to calculate tumour cell proliferation rate. In this methodology, DNA denaturation, commonly by hydrochloric acid, is essential to expose incorporated BrdU for quantification with monoclonal antibodies. This study was designed to establish the validity of this technique by examining the change in flow cytometric DNA profiles introduced by DNA denaturation procedures. METHODS: Four experiments were performed using suspensions of nuclei derived from human colorectal tumours exposed in vivo to 150 mg/m2 BrdU 8-11 h before sampling. RESULTS: After denaturation with hydrochloric acid 2 mol/l a significant decrease was observed in the DNA aneuploid G1 population (P < 0.001) with a concurrent increase in the DNA aneuploid S phase fraction (P < 0.05). These changes were independent of the washing-centrifugation step and were maximal at different hydrochloric acid concentrations for different tumours. CONCLUSION: Hydrochloric acid denaturation introduces a tumour-specific non-linear variation in the analysis of BrdU.

Aged↗
PubMed1996

p53 mutation, allele loss on chromosome 17p, and DNA content in ovarian carcinoma.

The aim of this investigation was to explore the relationships between p53 mutation, DNA aneuploidy, 17p deletions, and clinical stage in ovarian cancer. Nuclear suspensions were obtained by tissue disaggregation, stained with propidium iodide, and analysed on a Coulter EPICS Elite flow cytometer. DNA cell cycle analysis was performed using Multicycle software (Phoenix Flow Systems). DNA extracted from paraffin-embedded archival carcinomas/non-tumour tissue was used as template for PCR amplification of the microsatellite dinucleotide repeat polymorphism D17S513, a locus telomeric to p53 on 17p13.1. Allele loss at D17S513 was detected in 64.5 per cent of carcinomas (20 of 31 informative cases). DNA aneuploidy was detected in 20 of 54 (37 per cent) carcinomas. Eight of ten cases previously shown to harbour p53 mutations showed aneuploid DNA content. Although ten other DNA aneuploid cases had shown no p53 mutations, the results show a statistically significant association between p53 mutation and DNA aneuploidy (P < 0.01). Furthermore, the mean DNA index of the DNA aneuploid cases was significantly higher in p53 mutant cases compared with those showing no p53 mutation (P = 0.02). There was also a significant association between p53 mutations and stage, between ploidy and stage, and between allelic deletions at D17S513 or p53 and stage, but not between these allelic deletions and ploidy. p53 mutations appear to be associated with DNA aneuploidy in ovarian cancer independently of 17p deletions. p53 mutations, DNA aneuploidy, and 17p deletions are associated with late stage.

Alleles↗
PubMed1996

Three-dimensional reconstruction of perineural invasion in carcinoma of the extrahepatic bile ducts.

Three-dimensional (3D) reconstruction can be used to study the structural relationships between various tissue components and can help in the understanding of disease processes. Examples of perineural invasion have been reconstructed in two cases of adenocarcinoma of the extrahepatic bile duct. Ninety-six serial 5 microns sections were taken from both cases stored on file and 3D images were constructed using a Kontron VIDAS image analysis system. Both cases showed continuity of tumour cells within the perineural space. The isolated islands of malignant glands seen by conventional microscopy were shown to be in continuity with larger tumour cell masses via a complex branching network. In addition, direct continuity was demonstrated between malignant glands within the perineural space and those within the surrounding stromal tissue. During growth, the tumour appeared to have followed the plane of least resistance, although the availability of the perineural space may itself have been shaped by pressure effects and/or proteolytic enzyme secretion. Three-dimensional reconstruction of perineural invasion in adenocarcinoma of the extrahepatic bile ducts shows the value of this technique in demonstrating the structural relationships between the tumour and the host nerve bundle.

Adenocarcinoma↗
PubMed1996

Colorectal cell kinetics.

The assessment of cell proliferation in colorectal tissue may provide information with both prognostic and therapeutic implications. A variety of methods are available, including flow cytometric estimations of S phase fraction, immunohistochemical and autoradiographic visualization of exogenous and endogenous proliferation proteins, and morphological and stathmokinetic techniques. There is some correlation between Dukes stage and proliferation state features, and there is increased proliferative activity throughout the adenoma-carcinoma sequence. Data on cell proliferation rates are difficult to obtain. When correctly applied, the metaphase arrest technique remains the 'gold standard' of measuring proliferation, but its usefulness in clinical practice is limited. Recent studies have employed dual measurement flow cytometry and double labelling techniques to produce rate data.

Biomarkers↗
PubMed1996

Atypical adenomatous hyperplasia (adenosis) of the prostate: development of a Bayesian belief network for its distinction from well-differentiated adenocarcinoma.

The diagnosis of atypical adenomatous hyperplasia (AAH) of the prostate and its distinction from well-differentiated prostatic adenocarcinoma with small acinar pattern (PACsmac; Gleason primary grades 1 or 2) are affected by uncertainties that arise from the fact that the knowledge of AAH histopathology is expressed in descriptive linguistic terms, words, and concepts. A Bayesian belief network (BBN) was used to reduce the problem of uncertainty in diagnostic clue assessment, while still considering the dependencies between elements in the reasoning sequence. A shallow network was designed and developed with an open-tree topology, consisting of a root node containing two diagnostic alternatives (eg, AAH v PACsmac) and 12 first-level descendant nodes for the diagnostic features. Eight of these nodes were based on cell features, three on the type of gland lumen contents and one on the gland shape. The results obtained with prototypes of relative likelihood ratios showed that belief for the diagnostic alternatives is high and that the network can differentiate AAH from PACsmac with certainty. The features that best contributed to the highest belief were those concerning the nucleolar size, frequency, and location. In particular, after the analysis of five nucleolar features (prominent nucleoli, inconspicuous nucleoli, nucleoli with diameter greater than 2.5 micron, nucleolar margination, and nuclei with multiple nucleoli), the belief for AAH was 1.0, being already close to 1.0 when three were evaluated (the value range is 0.0 to 1.0; the closer to 1.0, the greater the belief). The contribution of the three features concerning the gland lumen contents (mucinous material, corpora amylacea, and crystalloids) was such that the final belief did not exceed 0.8. Results with the group of remaining features (eg, basal cell recognition, gland shape variation, cytoplasm appearance, and nuclear size variation) were slightly better. These features allowed a substantial accumulation of belief that was already greater than 0.9 when three were polled. However, the maximum belief value was never obtained. In conclusion, a BBN for AAH diagnosis offers a descriptive classifier that is readily implemented, and allows the use of linguistic, fuzzy variables, and the accumulation of evidence presented by diagnostic clues.

Adenocarcinoma↗
PubMed1996

Interobserver variation in the reporting of cervical colposcopic biopsy specimens: comparison of grading systems.

AIMS: To assess interobserver variation in reporting cervical colposcopic biopsy specimens and to determine whether a modified Bethesda grading system results in better interobserver agreement than the traditional cervical intraepithelial neoplasia (CIN) grading system. METHODS: One hundred and twenty five consecutive cervical colposcopic biopsy specimens were assessed independently by six histopathologists. Specimens were classified using the traditional CIN grading system as normal, koilocytosis, CIN I, CIN II, or CIN III. The specimens were also classified using a modified Bethesda grading system as either normal, low grade squamous intraepithelial lesion (LSIL) or high grade squamous intraepithelial lesion (HSIL). Participants were also asked to categorise biopsy specimens by the CIN system with the addition of the recently proposed category "basal abnormalities of uncertain significance (BAUS)". The degree of agreement between participants was assessed by kappa statistics. RESULTS: Using the CIN system, interobserver agreement was generally poor: unweighted and weighted kappa values between individual pairs of observers ranging from 0.05 to 0.34 (average 0.20) and from 0.20 to 0.54 (average 0.36), respectively. With the modified Bethesda system, interobserver agreement was better but still poor: 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. There was little or no agreement between observers in the diagnosis of BAUS. CONCLUSIONS: Interobserver agreement in the reporting of cervical colposcopic biopsy specimens using the CIN grading system is poor. Agreement, while still poor, is better when a modified Bethesda grading system is used. There is little or no consensus in the diagnosis of BAUS.

Biopsy↗
PubMed1996

Automated reasoning system in histopathologic diagnosis and prognosis of prostate cancer and its precursors.

OBJECTIVE: This article presents the rationale and options offered to diagnostic and prognostic decision support systems for prostate pathology by automated reasoning capabilities. METHODS: The symbolic information used in diagnostic decision-making is systematically ordered, compared, numerically assessed in its probability, and combined such that a conclusion can be drawn. The framework for the processing of such symbolic information may be an expert system, an inference network or a case-based reasoning system. Automated reasoning is implemented by the use of a rule base and information flow control modules. RESULTS: Automated reasoning allows decision support systems to follow highly adaptive decision sequences, capable of handling contradictory evidence, exceptions in diagnostic clue expression, and nonmonotonic decision-making. CONCLUSIONS: Automated reasoning capability in diagnostic and prognostic decision support systems allows highly flexible decision development, very close to human decision procedures.

Artificial Intelligence↗
PubMed1996

An interactive decision support system for breast fine needle aspiration cytology.

OBJECTIVE: To develop a computerized system to assist in the diagnosis of malignancy in breast fine needle aspiration cytology. STUDY DESIGN: A Bayesian belief network was designed to control uncertainty and allow a diagnostic decision to be reached based on the sequential collection of cytologic information. Ten cytologic features were defined as clues that contribute to the diagnostic discrimination of benign and malignant aspirates. The impact of each feature on the diagnostic decision was quantified by a conditional probability matrix. RESULTS: For the assessment of a new case, the computer guides the user through the diagnosis, prompting him or her for information on each of the diagnostic features in turn. For each feature, the user is presented with a series of digitally stored color microscopic images that have been selected to represent good examples of the different feature grades-e.g., pleomorphism: none, mild, moderate and severe. Each image is mapped to an overlapping curve, and by positioning a line on the spectrum where the user feels the case lies, a membership function vector is calculated and entered as evidence into the network. This results in an update in the belief in the diagnostic alternatives. After all the clues have been assessed, a final diagnostic probability is reported. In addition, a cumulative belief curve can be drawn that maps the change in the diagnostic probabilities after each piece of evidence has been submitted, providing unique insight into the diagnostic process. CONCLUSION: Systems like this represent an important step forward in the use of descriptive classifiers. They impose consistency in terminology, improve reproducibility in the grading of cellular abnormalities and remove subjectivity in interpreting the significance of pvisual clues to diagnosis. As such, they represent a necessary tool in pathologic decision making.

Biopsy, Needle↗
PubMed1996

Reproducibility of Bayesian belief network assessment of breast fine needle aspirates.

OBJECTIVE: To assess the consistency of diagnosis of fine needle aspiration biopsies of breast lesions by three experienced and five less experienced pathologists using conventional means and applying a Bayesian belief network (BBN) to 10 diagnostic features to support diagnostic decision making. STUDY DESIGN: Forty fine needle aspiration biopsies, previously assessed by one of the experienced pathologists both conventionally and using a BBN, were assessed by two further experienced pathologists and five less experienced pathologists. RESULTS: Using the BBN, the experienced pathologists arrived at diagnoses in agreement with an established consensus at a slightly lower rate than by conventional means. The less experienced pathologists arrived at the correct diagnoses no more frequently with the help of the BBN than conventionally. CONCLUSION: As used in this study, the BBN did not help less experienced pathologists to interpret their observations but did not enable less experienced pathologists to identify how their observations differed and affected their diagnoses. The prototype system used in this study has since been upgraded by providing computer graphic displays of the features to be observed so that a more uniform mental image can be held by the participating pathologists. This will be tested with the same study design.

Biopsy, Needle↗
PubMed1996

Evaluation of prostatic intraepithelial neoplasia after treatment with a 5-alpha-reductase inhibitor (finasteride). A methodologic approach.

OBJECTIVE: To develop a methodology applicable to the morphologic study of the efficacy of finasteride on prostatic intraepithelial neoplasia (PIN), a putative precursor of prostate cancer. STUDY DESIGN: Three PIN foci were reviewed in two simple prostatectomy specimens from patients with clinical diagnoses of benign prostatic hyperplasia and treated with finasteride for six months. The feasibility of PIN diagnosis and grading based on "diagnostic distance" was investigated. It is a measure of the "extent" to which the observed features are different from those of the untreated prototypes representing the following diagnostic categories: normal prostate, low and high grade PIN and prostatic adenocarcinoma with a cribriform or large acinar pattern. Uncertainty in the PIN diagnosis and grading was dealt with by means of a Bayesian belief network (BBN). RESULTS: The distance measure values of the three PIN foci from the prototype of untreated, nonneoplastic prostate were 9, 7 and 8, respectively, in relative, arbitrary units. Their distance from the two prostate cancer patterns (large acinar and cribriform) was as high as 8-10. The distance of these foci from either low or high grade PIN were as low as 5, 3 and 2, and 3, 5 and 4, respectively. BBN produced the highest belief values for PIN, thus confirming the morphology-based and diagnostic distance-supported diagnosis; however, the belief values were low for both grades. CONCLUSION: The results provided by BBN analyses and diagnostic distance measures support the conclusion that this methodology is applicable to assessing the efficacy of finasteride treatment of PIN.

5-alpha Reductase Inhibitors↗
PubMed1995

Prostatic intraepithelial neoplasia (PIN). Performance of Bayesian belief network for diagnosis and grading.

Prostatic intraepithelial neoplasia (PIN) diagnosis and grading are affected by uncertainties which arise from the fact that almost all knowledge of PIN histopathology is expressed in concepts, descriptive linguistic terms, and words. A Bayesian belief network (BBN) was therefore used to reduce the problem of uncertainty in diagnostic clue assessment, while still considering the dependences between elements in the reasoning sequence. A shallow network was used with an open-tree topology, with eight first-level descendant nodes for the diagnostic clues (evidence nodes), each independently linked by a conditional probability matrix to a root node containing the diagnostic alternatives (decision node). One of the evidence nodes was based on the tissue architecture and the others were based on cell features. The system was designed to be interactive, in that the histopathologist entered evidence into the network in the form of likelihood ratios for outcomes at each evidence node. The efficiency of the network was tested on a series of 110 prostate specimens, subdivided as follows: 22 cases of non-neoplastic prostate or benign prostatic tissue (NP), 22 PINs of low grade (PINlow), 22 PINs of high grade (PINhigh), 22 prostatic adenocarcinomas with cribriform pattern (PACcri), and 22 prostatic adenocarcinomas with large acinar pattern (PAClgac). The results obtained in the benign and malignant categories showed that the belief for the diagnostic alternatives is very high, the values being in general more than 0.8 and often close to 1.0. When considering the PIN lesions, the network classified and graded most of the cases with high certainty. However, there were some cases which showed values less than 0.8 (13 cases out of 44), thus indicating that there are situations in which the feature changes are intermediate between contiguous categories or grades. Discrepancy between morphological grading and the BBN results was observed in four out of 44 PIN cases: one PINlow was classified as PINhigh and three PINhigh were classified as PINlow. In conclusion, the network can grade PIN lesions and differentiate them from other prostate lesions with certainty. In particular, it offers a descriptive classifier which is readily implemented and which allows the use of linguistic, fuzzy variables.

Adenocarcinoma↗