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PubMed2005

Molecular classification of human gliomas using matrix-based comparative genomic hybridization.

Gliomas are the most frequent primary brain tumors and comprise a group of morphologically, biologically and clinically heterogeneous neoplasms. The different glioma types are associated with distinct genetic aberrations, which may provide useful information for tumor classification as well as prediction of prognosis and response to therapy. To facilitate the molecular classification of gliomas, we established a genomic microarray that consists of bacterial artificial chromosome (BAC) and P1-derived artificial chromosome (PAC) clones representing tumor suppressor genes, proto-oncogenes and chromosomal regions frequently gained or lost in gliomas. In addition, reference clones distributed evenly throughout the genome in approximately 15 Mbp intervals were spotted on the microarray. These customized microarrays were used for matrix-based comparative genomic hybridization (matrix CGH) analysis of 70 gliomas. Matrix CGH findings were validated by molecular genetic analyses of candidate genes, loss of heterozygosity studies and chromosomal CGH. Our results indicate that matrix CGH allows for the sensitive and specific detection of gene amplifications as well as low-level copy number gains and losses in clinical glioma samples. Furthermore, molecular classification based on matrix CGH data closely paralleled histological classification and was able to distinguish with few exceptions between diffuse astrocytomas and oligodendrogliomas, anaplastic astrocytomas and anaplastic oligodendrogliomas, anaplastic oligodendrogliomas and glioblastomas, as well as primary and secondary glioblastomas. Thus, matrix CGH is a powerful technique that allows for an automated genomic profiling of gliomas and represents a promising new tool for their molecular classification.

Adult↗
PubMed1976

A new classification of generalized carcinoma of the breast based on response to therapy.

Classifications of generalized carcinoma of the breast were based up to now on factors of definitely proven prognostic significance. These classifications are very useful in defining prognosis, but they help only to a limited extent in selecting treatment. We are proposing a new classification of three groups for generalized carcinoma of the breast according to objective response to therapy: to (a) responders, (b) nonresponders, and (c) patients with static disease. It is pointed out that in some cases there is discrepancy between prognosis and response to therapy, as some patients with "poor prognosis" respond dramatically to treatment while others with "good prognosis" do not respond to any type of treatment and treatment is actually harmful. It is also pointed out that our classification has a dynamic meaning, as a patient can switch from one group to another. The proposed classification might be of more help in deciding the therapeutic management.

Adult↗
PubMed1995

Computerized consensus diagnosis: a classification strategy for the robust analysis of MR spectra. I. Application to 1H spectra of thyroid neoplasms.

We introduce and apply a new classification strategy we call computerized consensus diagnosis (CCD). Its purpose is to provide robust, reliable classification of biomedical data. The strategy involves the cross-validated training of several classifiers of diverse conceptual and methodological origin on the same data, and appropriately combining their outcomes. The strategy is tested on proton magnetic resonance spectra of human thyroid biopsies, which are successfully allocated to normal or carcinoma classes. We used Linear Discriminant Analysis, a Neural Net-based method, and Genetic Programming as independent classifiers on two spectral regions, and chose the median of the six classification outcomes as the consensus. This procedure yielded 100% specificity and 100% sensitivity on the training sets, and 100% specificity and 98% sensitivity on samples of known malignancy in the test sets. We discuss the necessary steps any classification approach must take to guarantee reliability, and stress the importance of fuzziness and undecidability in robust classification.

Adenocarcinoma, Follicular↗
PubMed2005

Combination of feature-reduced MR spectroscopic and MR imaging data for improved brain tumor classification.

The purpose of this paper is to evaluate the effect of the combination of magnetic resonance spectroscopic imaging (MRSI) data and magnetic resonance imaging (MRI) data on the classification result of four brain tumor classes. Suppressed and unsuppressed short echo time MRSI and MRI were performed on 24 patients with a brain tumor and four volunteers. Four different feature reduction procedures were applied to the MRSI data: simple quantitation, principal component analysis, independent component analysis and LCModel. Water intensities were calculated from the unsuppressed MRSI data. Features were extracted from the MR images which were acquired with four different contrasts to comply with the spatial resolution of the MRSI. Evaluation was performed by investigating different combinations of the MRSI features, the MRI features and the water intensities. For each data set, the isolation in feature space of the tumor classes, healthy brain tissue and cerebrospinal fluid was calculated and visualized. A test set was used to calculate classification results for each data set. Finally, the effect of the selected feature reduction procedures on the MRSI data was investigated to ascertain whether it was more important than the addition of MRI information. Conclusions are that the combination of features from MRSI data and MRI data improves the classification result considerably when compared with features obtained from MRSI data alone. This effect is larger than the effect of specific feature reduction procedures on the MRSI data. The addition of water intensities to the data set also increases the classification result, although not significantly. We show that the combination of data from different MR investigations can be very important for brain tumor classification, particularly if a large number of tumors are to be classified simultaneously.

Algorithms↗
PubMed2002

Expert system support using a Bayesian belief network for the classification of endometrial hyperplasia.

Accurate morphological classification of endometrial hyperplasia is crucial as treatments vary widely between the different categories of hyperplasia and are dependent, in part, on the histological diagnosis. However, previous studies have shown considerable inter-observer variation in the classification of endometrial hyperplasias. The aim of this study was to develop a decision support system (DSS) for the classification of endometrial hyperplasias. The system used a Bayesian belief network to distinguish proliferative endometrium, simple hyperplasia, complex hyperplasia, atypical hyperplasia and grade 1 endometrioid adenocarcinoma. These diagnostic outcomes were held in the decision node. Four morphological features were selected as diagnostic clues used routinely in the discrimination of endometrial hyperplasias. These represented the evidence nodes and were linked to the decision node by conditional probability matrices. The system was designed with a computer user interface (CytoInform) where reference images for a given clue were displayed to assist the pathologist in entering evidence into the network. Reproducibility of diagnostic classification was tested on 50 cases chosen by a gynaecological pathologist. These comprised ten cases each of proliferative endometrium, simple hyperplasia, complex hyperplasia, atypical hyperplasia and grade 1 endometrioid adenocarcinoma. The DSS was tested by two consultant pathologists, two junior pathologists and two medical students. Intra- and inter-observer agreement was calculated following conventional histological examination of the slides on two occasions by the consultants and junior pathologists without the use of the DSS. All six participants then assessed the slides using the expert system on two occasions, enabling inter- and intra-observer agreement to be calculated. Using unaided conventional diagnosis, weighted kappa values for intra-observer agreement ranged from 0.645 to 0.901. Using the DSS, the results for the four pathologists ranged from 0.650 to 0.845. Both consultant pathologists had slightly worse weighted kappa values using the DSS, while both junior pathologists achieved slightly better values using the system. The grading of morphological features and the cumulative probability curve provided a quantitative record of the decision route for each case. This allowed a more precise comparison of individuals and identified why discordant diagnoses were made. Taking the original diagnoses of the consultant gynaecological pathologist as the 'gold standard', there was excellent or moderate to good inter-observer agreement between the 'gold standard' and the results obtained by the four pathologists using the expert system, with weighted kappa values of 0.586-0.872. The two medical students using the expert system achieved weighted kappa values of 0.771 (excellent) and 0.560 (moderate to good) compared to the 'gold standard'. This study illustrates the potential of expert systems in the classification of endometrial hyperplasias.

Bayes Theorem↗
PubMed2003

Raman spectroscopy, a potential tool for the objective identification and classification of neoplasia in Barrett's oesophagus.

Histopathology remains the gold standard technique for the diagnosis of intraepithelial neoplasia (dysplasia) in Barrett's oesophagus, but it is highly subjective and relies on blind biopsy targeting. The aim of this study was to evaluate Raman spectroscopy, a rapid, non-invasive, molecular, specific analytical technique, for the objective identification and classification of Barrett's neoplasia in vitro. A secondary objective was to demonstrate the need for a rigorous gold standard in the development of new diagnostic techniques. Forty-four patients with a mean age of 69 years (range 34-89 years) undergoing surveillance for Barrett's oesophagus were included in the study. Three consultant pathologists independently assessed snap-frozen oesophageal biopsy specimens. Raman spectra were measured on 87 histopathologically homogeneous samples. Spectral classification models were developed using multivariate analysis for the prediction of pathology. Histopathology and Raman classification results were compared. Raman spectral prediction with a consensus pathology classification model gave sensitivities between 73% and 100% and specificities of 90-100%. A high level of agreement (kappa = 0.89) was demonstrated between the three-subset biopsy targeting model and consensus pathology opinion. This compares favourably with the agreement measured between an independent pathologist and the consensus pathology opinion for the same spectra (kappa = 0.76). Raman spectroscopy appears to provide a highly sensitive and specific technique for the identification and classification of neoplasia in Barrett's oesophagus.

Adult↗
PubMed2003

Protocols for disease classification from mass spectrometry data.

We report our results in classifying protein matrix-assisted laser desorption/ionization-time of flight mass spectra obtained from serum samples into diseased and healthy groups. We discuss in detail five of the steps in preprocessing the mass spectral data for biomarker discovery, as well as our criterion for choosing a small set of peaks for classifying the samples. Cross-validation studies with four selected proteins yielded misclassification rates in the 10-15% range for all the classification methods. Three of these proteins or protein fragments are down-regulated and one up-regulated in lung cancer, the disease under consideration in this data set. When cross-validation studies are performed, care must be taken to ensure that the test set does not influence the choice of the peaks used in the classification. Misclassification rates are lower when both the training and test sets are used to select the peaks used in classification versus when only the training set is used. This expectation was validated for various statistical discrimination methods when thirteen peaks were used in cross-validation studies. One particular classification method, a linear support vector machine, exhibited especially robust performance when the number of peaks was varied from four to thirteen, and when the peaks were selected from the training set alone. Experiments with the samples randomly assigned to the two classes confirmed that misclassification rates were significantly higher in such cases than those observed with the true data. This indicates that our findings are indeed significant. We found closely matching masses in a database for protein expression in lung cancer for three of the four proteins we used to classify lung cancer. Data from additional samples, increased experience with the performance of various preprocessing techniques, and affirmation of the biological roles of the proteins that help in classification, will strengthen our conclusions in the future.

Biomarkers↗
PubMed2004

Towards a structural classification of phosphate binding sites in protein-nucleotide complexes: an automated all-against-all structural comparison using geometric matching.

A method is described for the rapid comparison of protein binding sites using geometric matching to detect similar three-dimensional structure. The geometric matching detects common atomic features through identification of the maximum common sub-graph or clique. These features are not necessarily evident from sequence or from global structural similarity giving additional insight into molecular recognition not evident from current sequence or structural classification schemes. Here we use the method to produce an all-against-all comparison of phosphate binding sites in a number of different nucleotide phosphate-binding proteins. The similarity search is combined with clustering of similar sites to allow a preliminary structural classification. Clustering by site similarity produces a classification of binding sites for the 476 representative local environments producing ten main clusters representing half of the representative environments. The similarities make sense in terms of both structural and functional classification schemes. The ten main clusters represent a very limited number of unique structural binding motifs for phosphate. These are the structural P-loop, di-nucleotide binding motif [FAD/NAD(P)-binding and Rossman-like fold] and FAD-binding motif. Similar classification schemes for nucleotide binding proteins have also been arrived at independently by others using different methods.

Algorithms↗
PubMedDate not supplied

Residual tumor (R) classification and prognosis.

The tumor status following treatment is described by the residual tumor (R) classification: R0, no residual tumor; R1, microscopic residual tumor; R2, macroscopic residual tumor. Residual tumor may be found in the area of primary tumor and its regional lymph nodes and/or at distant sites. The R classification reflects the effects of treatment and influences further treatment planning. Furthermore, the R classification is a strong predictor of prognosis. An acceptable long-term prognosis can be expected only in R0 patients. Although there exist clear correlations between stage and R classification the differences in prognosis of R0 versus R1,2 cannot be explained by differences in stage alone. The prognostic significance of R classification is demonstrated by respective data for non-small cell lung carcinoma, squamous cell carcinoma of oesophagus, gastric carcinoma, ductal adenocarcinoma of the pancreas, colorectal carcinoma, lung and liver metastases.

Carcinoma, Ductal, Breast↗
PubMed2003

A practical and user-friendly toxicity classification system with microbiotests for natural waters and wastewaters.

Various types of toxicity classification systems have been elaborated by scientists in different countries, with the aim of attributing a hazard score to polluted environments or toxic wastewaters or of ranking them in accordance with increasing levels of toxicity. All these systems are based on batteries of standard acute toxicity tests (several of them including chronic assays as well) and are therefore dependent on the culturing and maintenance of live stocks of test organisms. Most systems require performance of the bioassays on dilution series of the original samples, for subsequent calculation of L(E)C50 or threshold toxicity values. Given the complexity and costs of these toxicity measurements, they can only be applied in well-equipped and highly specialized laboratories, and none of the classification methods so far has found general acceptance at the international level. The development of microbiotests that are independent of continuous culturing of live organisms has stimulated international collaboration. Coordinated at Ghent University, Belgium, collaboration by research groups from 10 countries in central and eastern Europe resulted in an alternative toxicity classification system that was easier to apply and substantially more cost effective than any of the earlier methods. This new system was developed and applied in the framework of a cooperation agreement between the Flemish community in Belgium and central and eastern Europe. The toxicity classification system is based on a battery of (culture-independent) microbiotests and is particularly suited for routine monitoring. It indeed only requires testing on undiluted samples of natural waters or wastewaters discharged into the aquatic environment, except for wastewaters that demonstrate more than 50% effect. The scoring system ranks the waters or wastewaters in 5 classes of increasing hazard/toxicity, with calculation of a weight factor for the concerned hazard/toxicity class. The new classification system was applied during 2000 by the participating laboratories on samples of river water, groundwaters, drinking waters, mine waters, sediment pore waters, industrial effluents, soil leachates, and waste dump leachates and was found to be easy to apply and reliable.

Animals↗
PubMed1994

A new classification of developmental language disorders (DLD).

Eighty children with DLD were examined with 18 language tests, mainly derived from a neuropsychological investigation called NEPSY (NEuroPSYchological Investigation for Children). The children were 6-0 to 7-9 years old and attended kindergarten. The test profiles of the first 40 children, Group 1, were utilized for the elaboration of a classification of DLD. The test profiles were grouped into five subgroups with the aid of a Q-type factor analysis. Then the classification was modified to suit clinical application by collapsing two pairs of subgroups. The resulting categories were called: the Global Subtype, the Specific Dyspraxia Subtype, and the Specific Comprehension Subtype. The classification was validated, first, by a follow-up study. It was predicted that spelling problems would occur in the Global and the Specific Comprehension Subtypes, but not in the Specific Dyspraxia Subtype. At follow-up, 3 years later, the hit rate was found to be 80.5%. In a second validation procedure, the classification was tried out on the 40 children examined later, Group 2. The coverage of the classification was 85%. Five outliers (12.5%) seemed to form a fourth category, called the Specific Dysnomia Subtype. An expressive subtype was not observed.

Articulation Disorders↗
PubMed2002

Two notions of conspicuity and the classification of phyllotaxis.

Invoking cylindrical Bravais lattices, Adler (1974, 1977) proposed a mathematically precise definition for the botanical classification of phyllotaxis. It is based on opposed pairs of parastichy families, that are conspicuous and visible. Jean (1988) generalized this concept to non-opposed pairs of parastichy families. In the present paper it is shown that this generalization implies a notion of conspicuity different from Adler's. This is made obvious by redefining the key terms of the two approaches. Both classifications are well defined. For Adler's, this is shown by presenting a general proof for his conjecture that conspicuous (in the sense of Adler) opposed pairs of parastichy families are visible. There are indications that in applications to models of phyllotaxis (van Iterson model, inhibitor models) their solutions are better characterized by Jean's classification. The differences between Adler's and Jean's classification show up only in very rare cases, so that the practice of pattern determination is only insignificantly touched by the present results. It turns out that the widely used contact parastichy method to determine phyllotactic patterns gives results according to Jean's classification rather than Adler's.

Models, Biological↗
PubMed1977

Testicular cancer, histologic classification and staging, topography of lymph node metastases.

From the clinical point of view, histologic classification is intended to give suggestions for therapy (therapeutic classification) and to provide the basis for an assessment of end results (prognostic classification). In adults, the essential therapeutic question is: seminoma (only seminoma) or non-seminoma? The frequency of seminoma among the germinal testicular tumours influenced by the subtlety of the histologic examination. The histologic report should include the MOSTOFI (25) classification and the prognostic group classification of DIXON and MOORE (7). Staging of testicular cancer and criteria for the comparison of treatment results are discussed. The topography of lymphatic metastases of testicular cancer was investigated. The great majority of testicular cancers metastasize regularly, i.e., primarily into the testicular lymph center and/or along the testicular vein, and only secondarily in other lymph nodes. This provides a foundation for the increasing tendency to modified bilateral retroperitioneal node dissection.

Adult↗
PubMed1987

Culture-bound syndromes and international disease classifications.

An important endeavor in the world psychiatric community is the development of an international classification of psychiatric disorders that will be more culture-free than either the current DSM-III or ICD-9. This classification should be clinically useful and relevant to psychiatric experience in all countries of the world. A major problem in this endeavor is the existence of the so-called culture-bound syndromes syndromes (CBS's) which reflect cultural influences on disease patterns and render them difficult to place in disease classifications which have their origins in Western cultures. Literally dozens of disorders have been labelled CBS's around the world, and considerable looseness has developed in the use of the CBS rubric. Recently it has been proposed that all illnesses (both physical and psychiatric) are in fact culture bound. In reaction to this drift towards meaninglessness, a new definition for CBS's is proposed - a collection of signs and symptoms (excluding notions of cause) which is restricted to a limited number of cultures primarily by reason of certain of their psychosocial features. In this definition, notions of etiology and illness labels are excluded because these are highly variable and change over time. On the other hand, collections of signs and symptoms (i.e., syndromes), insofar as they are reasonably complete descriptions of nature, remain constant over time and are verifiable by all investigators. Using two CBS's from the Pacific basin area - taijin-kyofu-sho and latah - as examples, the following conclusions are drawn: CBS status should not be assigned on the basis of differential distribution of illnesses because of accidents of geography or on the basis of local labels or notions of cause; epidemiological features of diseases such as global prevalence or age/sex differentials of those affected should not be used as basis of CBS status; the meaning of illness, both for individuals and for cultures, is an important area of study in its own right but such meanings should not be confused with syndrome descriptions or used as criteria for an international disease classification; a truly international classification of diseases is close to realization through relatively minor alterations in the Axis I designations and descriptions of DSM-III. Few entirely new categories would be required.

Adult↗
PubMed1981

Histopathological correlation of the Kiel with the original Rappaport classification of malignant non-hodgkin lymphomas.

Using the Kiel and the Rappaport classifications, a comparative histopathological analysis of 486 cases with non-Hodgkin lymphomas from a prospective study of the Kiel Lymphoma Study Group, still in progress, was performed. The greater part of Rappaport's classical lymphoma entities was found to be inhomogeneous and to include tumors of considerable prognostic heterogeneity, as shown by differences in actuarial survival. Some of the Kiel lymphoma entities have been identified in several lymphoma types of the Rappaport classification, indicating that "translation" of one scheme into the other is difficult or impossible. In addition, centrocytic lymphoma of the Kiel classification may not be homogeneous. On the whole, the Kiel classification appears to be superior to the original Rappaport classification in categorizing the various prognostically diverse types of non-Hodgkin lymphomas.

Germany, West↗
PubMed1979

Comparison between clinical and radiological classification of infants with the respiratory distress syndrome (RDS).

Clinical and radiological classifications of the severity of the respiratory distress syndrome (RDS) were made in 55 infants. According to the clinical classification 17 infants belonged to the first class (mild RDS), 22 to the second (moderate RDS), and 16 to the third class (severe RDS). In the classification based on radiological findings the numbers of infants in classes 1, 2 and 3 were 18, 19 and 18 respectively. On the basis of both the clinical and radiological findings, 11 infants belonged to the mild RDS class, 11 to the moderate, and 12 to the severe RDS class. Thus, 34 infants had the same clinical and radiological classification. In 21 infants there were discrepancies between the clinical and the radiological classifications, but only one infant with the most severe radiological findings belonged to the mild RDS class and only one infant with mild radiological findings belonged to the worst RDS class.

Humans↗
PubMed1995

Morphological classification and identification of neurons in the inferior colliculus: a multivariate analysis.

In this paper a modern statistical method is applied to an old cell classification and identification problem in the central nucleus of the inferior colliculus. In a recent computer-based reconstruction study of Golgi-impregnated neurons in the rat, two types of cell with flattened dendritic arbors, flat (F) and less flat (LF), were defined. Both types contributed to the anisotropic and laminar pattern of the nucleus. The classification was based on five morphological features of complete dendritic arbors, two assessed visually and three numerically. With respect to the latter criteria, the two types were classified by preselected cut-off values. The distinction of the two types was supported, among other things, by a prevailing spatial segregation into laminar and interlaminar compartments. The cell sample was too small, however, to validate the classification and segregation definitively. In the present study, the classification is tested by the partial least squares regression method which is independent of the preselected cut-off values, and is able to handle small sample sizes and interdependent variables. In the plots, the F and LF cells are clearly separated into two distinct clusters, strongly supporting the distinction of the two types. The different density of the two clusters shows that the F cells are more homogeneous that the LF cells. The relative importance of the classification criteria is also evaluated. The three-dimensional (3D) inspection and the 3D convex hull-based form factor were found to be the most powerful criteria for identifying the two cell types, while the 2D evaluation of camera lucida drawings, a standard method in neuroanatomy, proved to have the least predictive value.

Animals↗
PubMed1975

Proceedings: Prognosis of non-Hodgkin's lymphomas with special emphasis on the staging classification.

The prognosis of the non-Hodgkin's lymphomas is determined by 1. the pattern of origin and spread which can be demonstrated in a staging classification, 2, the histopathological type, and 3. the effectiveness and scope of the treatment methods, particularly radio- and chemo-therapy. In the following paper the Ann Arbor Classification, which was originally conceived of for both disease groups (Hodgkin's and non-Hodgkin's lymphomas), is discussed particularly with respect to the applicability and prognostic evaluation for the non-Hodgkin's lymphomas. The Ann Arbor Classification may in essence reflect the oncological characteristics of the non-Hodgkin's accurately; there are, however, a number of findings with qualitative and quantitative differences which defy integration into the Ann Arbor Classification. The qualitative differences consist of the differing lymphatic and extralymphatic origins and their consequence for spread and prognosis. The quantitative differences refer to the varying patterns of distribution of the different stages of spreading, whereby the dissemination stages in the non-Hodgkin's lymphomas are more dependent on the histological form than is the case with the Hodgkin's lymphomas, and thus must play a greater role in the prognostic evaluation and indication for treatment. Suggestions have been made for a modification of the Ann Arbor Staging Classification for the non-Hodgkin's lymphomas.

Humans↗