Computer-based malignancy grading of astrocytomas employing a support vector machine classifier, the WHO grading system and the regular hematoxylin-eosin diagnostic staining procedure

OBJECTIVE: To investigate and develop an automated technique for astrocytoma malignancy grading compatible with the clinical routine. STUDY DESIGN: One hundred forty biopsies of astrocytomas were collected from 2 hospitals. The degree of tumor malignancy was defined as low or high according to the World Health Organization grading system. From each biopsy, images were digitized and segmented to isolate nuclei from background tissue. Morphologic and textural nuclear features were quantified to encode tumor malignancy. Each case was represented by a 40-dimensional feature vector. An exhaustive search procedure in feature space was utilized to determine the best feature combination that resulted in the smallest classification error. Low and high grade tumors were discriminated using support vector machines (SVMs). To evaluate the system performance, all available data were split randomly into training and test sets. RESULTS: The best vector combination consisted of 3 textural and 2 morphologic features. Low and high grade cases were discriminated with an accuracy of 90.7% and 88.9%, respectively, using an SVM classifier with polynomial kernel of degree 2. CONCLUSION: The proposed methodology was based on standards that are common in daily clinical practice and might be used in parallel with conventional grading as a second-opinion tool to reduce subjectivity in the classification of astrocytomas.     

Cytological grading of breast cancer in Giemsa-stained fine needle aspiration smears

A potential cytological nuclear grading based on a semi-quantitative evaluation of three basic nuclear features, size of cell nuclei, anisonucleosis and the proportion of nucleoli-containing-nuclei, was tested on 74 Giemsa-stained fine needle aspiration of breast smears for its reliability in establishing the malignant potential of breast cancer. The prognostic impact of DNA-ploidy and S-phase fraction was also assessed. A good correlation between the three basic nuclear features, DNA-ploidy, S-phase fraction, cytological nuclear grade and histological grade, was shown. Using the cytological nuclear grade proposed, correct classification of cases between low histological grade (HG I) and high histological grade (HG II + HG III) was achieved in 79.73%. A statistically significant difference in 5-year survival rate was also observed between low malignancy grade and high malignancy grade breast cancer patients, regardless of the grading method used. DNA-ploidy and S-phase fraction were not statistically significant in establishing the malignant potential of breast cancer.     

Genetic analysis to complement histopathological diagnosis of brain tumors

Gliomas, the most frequent tumors originating in the human nervous system, are divided into various subtypes. Currently, microscopic examination alone is insufficient for classification and grading so that genetic profiles are increasingly being emphasized in recognition of the emerging role of molecular diagnostic approaches to glioma classification. Glioblastomas (WHO grade IV) may develop de novo (primary glioblastomas) or through progression from lower-grade astrocytomas (secondary glioblastomas), while both glioblastomas show similar histological features. In contrast, they do constitute distinct disease entities that evolve through different genetic pathways, and are likely to differ in prognosis and response to therapy. Oligodendrogliomas (WHO grade II) account for 2.7% of brain tumors and 5-18% of all gliomas. Since this tumor is recognized as a particular subtype of glioma that shows remarkable responses to chemotherapy, a correct diagnosis is of prime importance. The difficulty is that histological differentiation of oligodendrogliomas from diffuse astrocytomas is highly subjective in cases without typical morphological features and there is a lack of reliable immunohistochemical markers. While histological distinction of low-grade gliomas from reactive astrocytes is also often difficult, reactive astrocytes usually lack genetic alterations. More biological and molecular approaches to glioma classification thus appear warranted to provide improved means to achieve correct diagnoses.     

Computer-aided classification of malignancy in astrocytomas. I. The value of nuclear parameters obtained by automated black and white image analysis.

Ninety-three selected cases of astrocytomas including glioblastomas (astrocytomas grades 1-4) were evaluated by means of Feulgen-stained microscopic slides for nuclear parameters obtained by automated black and white image analysis (ABWIA). The goal was to determine to what extent nuclear features evaluated by ABWIA were applicable as classifiers for the computer-aided numerical classification of malignancy in astrocytomas. Before the automated evaluation, all tumours had been subjectively graded according to the Mayo Clinic grading rules as delineated by Ringertz. Twenty-three nuclear parameters were evaluated and tested for their classification impact. With a model of five parameters (number of nuclei per area, mean of the convex form factor, extinction sum, extinction variation, and full-width-half-maximum of the extinction distribution) the highest reclassification rate of 75% correctly reclassified cases was obtained. Although this is a good result for a classification using only nuclear parameters, it is too poor for practical application. Thus, nuclear parameters evaluated by ABWIA alone are insufficient for numerical classification models assessing the malignant expression of astrocytomas.     

Pathologic significance of proliferative activity and oncoprotein expression in astrocytic tumors

OBJECTIVE: To clarify the clinicopathologic significance of immunohistochemistry for proliferative activity and oncoprotein expression in astrocytic tumors. STUDY DESIGN: Ninety-seven cases of brain astrocytic tumors with histologic grading and follow-up data were investigated with immunohistochemistry and image analyzer to detect the expression of proliferating cell nuclear antigen (PCNA), silver-binding nucleolar organizer regions (AgNORs) and several oncoproteins. RESULTS: PCNA was significantly related to AgNORs, grading and prognosis of astrocytomas. The frequency of mutant p53 protein expression was higher in grade 2-4 astrocytomas than in grade 1. Epidermal growth factor (EGF) (37.1%), EGF receptor (83.5%) and p21ras (42.3%) expression levels were related to neither the grade nor prognosis of the tumors. The positive ratios of p53 antibodies were higher in grades 2-4 than in grade 1, and the intensities correlated with PCNA but not with prognosis. CONCLUSION: Aberrations of c-erbB-2, p21ras, EGF and EGF receptor might be early events in the initiation and progression of astrocytomas, whereas p53 overexpression is involved in all the stages. Immunohistochemical detection had no prognostic value. PCNA could be important to the evaluation of astrocytoma malignancy.     

The language of systematics,and the philosophy of ‘total evidence’

This contribution analyses the primacy of classification over generalization, and the philosophy of total evidence that emerges from the relation of homology to character statements. Primary conjectures of homology are basic character statements, i.e. statements that predicate properties of organisms, properties that are instantiated by those organisms and/or their parts. Secondary conjectures of homology are embedded in a second‐level (metalinguistic) discourse that turns on the coherence or incoherence of those basic character statements relative to a hierarchy. The coherence or incoherence of character statements is a logical relation between statements, not a causal (historical) relation between organisms. The choice of the hypothesis of relationships that is supported by the largest set of coherent basic character statements is based on the empirical presupposition that the properties referred to by the set of coherent character statements are grounded in causally efficacious relations of inheritance and ontogeny, and co‐instantiated because they are inherited through common ancestry (Hennig's auxiliary principle). Unless that empirical presupposition is causally grounded, phylogeny reconstruction is of an inherently probabilistic nature, whether under parsimony or other models of analysis. The causal grounding of a coherent set of character statements typically seeks a link between character statements and causally efficacious generative mechanisms for morphological characters (as is defeasibly indicated by topology and connectivity), or secondary structure information for molecular characters.     

Quantitative analysis of vessels with smooth muscle layer in astrocytic tumors: correlation with histological grade and prognostic significance

Angiogenesis plays an important role in the progression of astrocytic tumors and its evaluation is a major prognostic factor. Although the form of proliferating vessels ranges from fine capillaries to well-developed vascular structures with a smooth muscle layer, the characteristics of vascular smooth muscle cells (SMCs) are not understood in detail. We therefore examined the density, size and shape of tumor vessels, as well as CD34-immunoreactive (CD34-Vs) or α-smooth muscle actin-immunoreactive (SMA-Vs) vessels in 46 primary astrocytomas (grade II diffuse astrocytomas, n=11, grade III anaplastic astrocytomas, n=15, grade IV glioblastomas, n=20) and in normal brain tissues from 10 autopsies. We also examined the expression of high molecular weight caldesmon (h-CD, a marker of the contractile phenotype of smooth muscle) and of platelet-derived growth factor receptor β (PDGFR-β). The SMA-Vs were significantly more dense and larger in grade IV than grade III, whereas those of CD34-Vs did not differ between grade III and IV. Changes in the shape of CD34-Vs and SMA-Vs correlated with histological grading. The expression of h-CD was reduced, whereas that of PFGFR-β was increased in high grade-astrocytomas. Kaplan-Meier analysis indicated that the density of SMA-Vs, the size of both CD34 and SMA-Vs and PDGFR-β expression were significant prognostic factors. These findings suggest that SMA-Vs are significantly associated with the progression of astrocytomas and that these vessels provide useful information for the histological diagnosis and survival of patients with these types of brain tumors.     

A modern reproducible method for the histologic grading of astrocytomas with statistical classification tools

OBJECTIVE: To investigate whether statistical classification tools can infer the correct World Health Organization (WHO) grade from standardized histologic features in astrocytomas and how these tools compare with GRADO-IGL, an earlier computer-assisted method. STUDY DESIGN: A total of 794 human brain astrocytomas were studied between January 1976 and June 2005. The presence of 50 histologic features was rated in 4 categories from 0 (not present) to 3 (abundant) by visual inspection of the sections under a microscope. All tumors were also classified with the corresponding WHO grade between I and IV. We tested the prediction performance of several statistical classification tools (learning vector quantization [LVQ], supervised relevance neural gas [SRNG], support vector machines [SVM], and generalized regression neural network [GRNN]) for this data set. RESULTS: The WHO grade was predicted correctly from histologic features in close to 80% of the cases by 2 modern classifiers (SRNG and SVM), and GRADO-IGL was predicted correctly in > 84% of the cases by a GRNN. CONCLUSION: A standardized report, based the 50 histologic features, can be used in conjunction with modern classification tools as an objective and reproducible method for histologic grading of astrocytomas.     

Grade classification of neuroepithelial tumors using high-resolution magic-angle spinning proton nuclear magnetic resonance spectroscopy and pattern recognition

Clinical data have shown that survival rates vary considerably among brain tumor patients, according to the type and grade of the tumor. Metabolite profiles of intact tumor tissues measured with high-resolution magic-angle spinning proton nuclear magnetic resonance spectroscopy (HRMAS (1)H NMRS) can provide important information on tumor biology and metabolism. These metabolic fingerprints can then be used for tumor classification and grading, with great potential value for tumor diagnosis. We studied the metabolic characteristics of 30 neuroepithelial tumor biopsies, including two astrocytomas (grade I), 12 astrocytomas (grade II), eight anaplastic astrocytomas (grade III), three glioblastomas (grade IV) and five medulloblastomas (grade IV) from 30 patients using HRMAS (1)H NMRS. The results were correlated with pathological features using multivariate data analysis, including principal component analysis (PCA). There were significant differences in the levels of N-acetyl-aspartate (NAA), creatine, myo-inositol, glycine and lactate between tumors of different grades (P<0.05). There were also significant differences in the ratios of NAA/creatine, lactate/creatine, myo-inositol/creatine, glycine/creatine, scyllo-inositol/creatine and alanine/creatine (P<0.05). A soft independent modeling of class analogy model produced a predictive accuracy of 87% for high-grade (grade III-IV) brain tumors with a sensitivity of 87% and a specificity of 93%. HRMAS (1)H NMR spectroscopy in conjunction with pattern recognition thus provides a potentially useful tool for the rapid and accurate classification of human brain tumor grades.     

Karyometric features of low and high grade glial tumors as compared with their MRI appearance

OBJECTIVE: To compare the results of a magnetic resonance imaging (MRI) grading designed to identify low and high grade gliomas with karyometry used as a tool to grade primary brain tumors. STUDY DESIGN: A consecutive series of 23 primary brain tumors was selected for this study. The neuroradiologist, not knowing the histologic diagnoses, divided the cases into low and high grade categories on the basis of the following 7 features: border sharpness, heterogeneity without contrast, cavitation, contrast enhancement, hypervascularity, mass effect and perifocal T2 hyperintensity. To each feature was given a numerical value, ranging from 1 to 3. All the cases were reviewed and classified by the same pathologist, blinded to the MRI diagnosis. Two hundred nuclei per case were recorded, and 93 karyometric features related to nuclear area, total optical density and chromatin distribution were analyzed for each nucleus. Statistical analysis included discriminant analysis, Kruskal-Wallis test, nonsupervised learning algorithm P-index and Beale statistic. RESULTS: Ten cases were classified as low grade on the basis of their MRI features. The corresponding histopathologic diagnoses were: grade 2 astrocytoma in 2 cases and grade 2 oligodendroglioma in 8 cases. An MRI diagnosis of high grade tumor was made in 13 cases. In 10 cases it was confirmed by the histopathologic diagnosis (3 grade 3 astrocytomas, 1 grade 3 oligodendroglioma and 6 glioblastomas). In the remaining 3 cases the histologic examination revealed a low grade tumor, 1 grade 2 astrocytoma and 2 grade 2 oligodendrogliomas. For the purposes of the karyometric analysis the cases were allocated to the low or high grade category according to their histologic diagnosis (13 cases low grade and 10 cases high grade). Nuclei from low and high grade tumors showed clearly different karyometric characteristics. The oligodendroglioma nuclei had abnormality values close to the low grade standard, while the astrocytoma nuclei were a highly dispersed group with characteristics indicative of a higher degree of nuclear abnormality than the oligodendroglioma nuclei. The results of karyometric analysis showed that grade 2 tumors, corresponding to the low grade group, form a rather distinct category from grade 3 and 4 tumors belonging to the high grade group. CONCLUSION: The results of MRI grading based on a series of features that are routinely assessed by the neuroradiologist to reach a final diagnosis correlate highly with the histopathologic diagnosis. Karyometry can be a useful adjunct to histologic grading.     

Cytological grading of breast carcinoma—a feasible proposition?

Fine needle aspiration cytology (FNAC) of the breast is widely used in the diagnosis of breast carcinoma. In some centres this is sometimes the only diagnostic procedure performed prior to definitive treatment. A grading system based on cytology would be helpful in the selection of patients for appropriate therapy. The aim of this study, therefore, was to devise such a system for grading breast carcinoma based on cytological features alone. The features assessed were the degree of cell clustering, nuclear pleomorphism, nuclear diameter, the presence of multiple, easily visible nucleoli and necrosis. Cytological features were compared to the histological grade of the tumours following excision. Discriminant analysis showed that the features with the closest correlation with histological grade were nuclear diameter, nuclear pleomorphism and the presence of nucleoli. A scoring system based on these three parameters enabled the classification of tumours into high and low cytological grades which showed a close correlation with histological grade.     

Real-time quantification of the proliferative state in astrocytomas

OBJECTIVE: To evaluate proliferative activity in a set of gliomas and to compare the quantitative data obtained by a real-time processor with the labelling index (LI) and mitotic index (MI). STUDY DESIGN: Ki-67 immunostaining was performed on paraffin-embedded specimens from 42 cases of glioblastomas, 17 cases of anaplastic astrocytomas and 14 cases of low grade astrocytomas. Nuclear positivity was calculated as LI and by a real-time image processor for quantitative evaluation. MI was also calculated at 10 high-power fields. The data obtained from glioblastomas were compared with those from anaplastic and low grade astrocytomas. To all the data was applied the Pearson test to verify the correlation between counting and quantitative values and between proliferative markers and survival. RESULTS: A positive trend from low grade astrocytomas to glioblastomas was found for Ki-67 (LI and quantitative values) and MI, with highly significant differences between the three grades of gliomas considered. A good correlation between LI and quantitative values of Ki-67 was found. Very little relationship resulted between survival and Ki-67 LI. No relationship was found between survival and quantitative values of Ki-67. CONCLUSION: Ki-67 allowed effective separation of astrocytic tumors with different grades of malignancy. Quantitative evaluation of color information by means of a real-time processor proved to be a useful, objective and fast way to obtain readings, useful for grading purposes but not for prognostic evaluation.     

Lectins as differentiation markers of human gliomas.

The lectins Concanavalin A (Con A), Ricinus communis agglutinin (RCA-I), Peanut agglutinin (PNA) and Wheat germ agglutinin (WGA) as well as the immunomarkers for glial fibrillary acidic protein (GFAP) and myelin basic protein (MBP) were used in a series of 21 glial tumors (4 pylocytic astrocytomas, 5 grade II astrocytomas, 3 anaplastic astrocytomas, 4 glioblastomas and 5 oligodendrogliomas). ConA binds to all tumoral astrocytes in low grade astrocytomas, as well as to well differentiated tumoral astrocytes in anaplastic astrocytomas and glioblastomas. RCA-I has a similar behaviour. PNA, and to a lesser degree WGA, binds selectively to the oligodendroglial plasma membrane in well differentiated oligodendrogliomas. The results suggest that these lectins are markers of differentiation in gliomas rather than of malignancy.     

Topometric analysis of diffuse astrocytomas

OBJECTIVE: To investigate differences between astrocytomas of WHO grade 2 and anaplastic astrocytomas of WHO grade 3 in terms of topometric variables characterizing individual tumor cell nuclei. STUDY DESIGN: Paraffin sections from surgical specimens from 25 astrocytomas (grade 2, n = 11; grade 3, n = 14) were analyzed by means of an image analysis system. At least 300 tumor cell nuclei were measured in the region with the highest Ki-67 proliferation index. Three different kinds of topometric variables were determined for each tumor cell nucleus: (1) several distances; (2) the variable Angle 2/1, the angle between the straight lines representing the distance to the nearest and second-nearest nucleus; and (3) the number of neighbors according to our mathematical definition. RESULTS: Most topometric variables showed distinct differences between the 2 tumor grades (multivariate analysis of variance), with 88% cases correctly reclassified by means of cross-validated discriminant analysis. The variables with the highest discriminatory power were the SD of Angle 2/1 and the ratio between the distance to the second-nearest and nearest tumor cell nucleus, with lower values for these variables in anaplastic astrocytomas. Even variables concerning neighborhood relationships showed significant differences. CONCLUSION: The results of this pilot study show that this first set of topometric variables is sufficient to detect differences between topologic characteristics of tumor cell nuclei in astrocytomas grade 2 and grade 3. Topometry seems to be an important tool for grading astrocytomas.     

Pleomorphism of the nuclear envelope in breast cancer: a new approach to an old problem

In routine practice, nuclear pleomorphism of tumours is assessed by haematoxylin staining of the membrane-bound heterochromatin. However, decoration of the nuclear envelope (NE) through the immunofluorescence staining of NE proteins such as lamin B and emerin can provide a more objective appreciation of the nuclear shape. In breast cancer, nuclear pleomorphism is one of the least reproducible parameters to score histological grade, thus we sought to use NE proteins to improve the reproducibility of nuclear grading. First, immuno-fluorescence staining of NE as well as confocal microscopy and three-dimensional reconstruction of nuclei in cultured cells showed a smooth and uniform NE of normal breast epithelium in contrast to an irregular foldings of the membrane and the presence of deep invaginations leading to the formation of an intranuclear scaffold of NE-bound tubules in breast cancer cells. Following the above methods and criteria, we recorded the degree of NE pleomorphism (NEP) in a series of 273 invasive breast cancers tested by immunofluorescence. A uniform nuclear shape with few irregularities (low NEP) was observed in 135 cases or, alternatively, marked folds of the NE and an intranuclear tubular scaffold (high NEP cases) were observed in 138 cases. The latter features were significantly correlated (P-value <0.002) with lymph node metastases in 54 histological grade 1 and in 173 cancers with low mitotic count. Decoration of the NE might thus be regarded as a novel diagnostic parameter to define the grade of malignancy, which parallels and enhances that provided by routine histological procedures.     

Characteristic cytological features of histological grade one (G1) breast carcinomas in fine needle aspirates

Objective:  To analyse the spectrum of nuclear features as well as dissociation pattern found in fine needle aspirates (FNAC) from histological grade 1 breast carcinomas and evaluate the critical cytological features of these lesions.
Material and methods:  The material consisted of FNAC smears from 494 histologically confirmed grade 1 breast carcinomas. All smears were revaluated for cell dissociation pattern, nuclear size, cell uniformity, nucleoli, nuclear margin and chromatin pattern. All features were compared with the histological subtype and cytological grading.
Results:  73.9% of the cases were cytological grade 1, 24.3% were grade 2 and 1.8% were grade 3. The majority of the cases had a cell dissociation pattern showing both a population of single carcinoma cells and cell clusters (65.9%). Practically all tumours had a granular chromatin pattern (94.7%) and a slightly irregular nuclear margin with folds and grooves (94%) irrespective of histological subtype and cytological grading. Nucleoli were mostly indistinct or small (74%), whereas 24.3% were noticeable and 1.7% abnormal. Practically all cases revealed some degree of pleomorphism with 74.3% showing mild and 22.4% a distinct pleomorphism. A small subgroup of IDC was classified as monomorphic (3.3%). Almost all tumours had nuclear sizes in the range of 2–4 × RBC (96.9%).
Conclusion:  Not all histological grade 1 carcinomas are cytological grade 1. About 25% were grade 2, and a small subpopulation reached grade 3. The typical/average findings in FNAC from grade 1 breast carcinomas were a population of both groups and single cells showing mild pleomorphism, granular chromatin, slightly irregular nuclear margin, indistinct nucleolus and nuclear size 2–4 × RBC.     

Differential expression of E-cadherin gene in human neuroepithelial tumors

Cadherins are cell-to-cell adhesion molecules that play an important role in the establishment of adherent-type junctions by mediating calcium-dependent cellular interactions. The CDH1 gene encodes the transmembrane glycoprotein E-cadherin which is important in maintaining homophilic cell-cell adhesion in epithelial tissues. E-cadherin interacts with catenin proteins to maintain tissue architecture. Structural defects or loss of expression of E-cadherin have been reported as a common feature in several human cancer types. This study aimed to evaluate the expression of E-cadherin and their correlation with clinical features in microdissected brain tumor samples from 81 patients, divided into 62 astrocytic tumors grades I to IV and 19 medulloblastomas, and from 5 white matter non-neoplasic brain tissue samples. E-cadherin (CDH1) gene expression was analyzed by quantitative real-time polymerase chain reaction. Mann-Whitney, Kruskal-Wallis, Kaplan-Meir, and log-rank tests were performed for statistical analyses. We observed a decrease in expression among pathological grades of neuroepithelial tumors. Non-neoplasic brain tissue showed a higher expression level of CDH1 gene than did neuroepithelial tumors. Expression of E-cadherin gene was higher in astrocytic than embryonal tumors (P = 0.0168). Low-grade malignancy astrocytomas (grades I-II) showed higher CDH1 expression than did high-grade malignancy astrocytomas (grades III-IV) and medulloblastomas (P < 0.0001). Non-neoplasic brain tissue showed a higher expression level of CDH1 gene than grade I malignancy astrocytomas, considered as benign tumors (P = 0.0473). These results suggest that a decrease in E-cadherin gene expression level in high-grade neuroepithelial tumors may be a hallmark of malignancy in dedifferentiated tumors and that it may be possibly correlated with their progression and dissemination.     

Automated diagnosis of brain tumours astrocytomas using probabilistic neural network clustering and support vector machines

A computer-aided diagnosis system was developed for assisting brain astrocytomas malignancy grading. Microscopy images from 140 astrocytic biopsies were digitized and cell nuclei were automatically segmented using a Probabilistic Neural Network pixel-based clustering algorithm. A decision tree classification scheme was constructed to discriminate low, intermediate and high-grade tumours by analyzing nuclear features extracted from segmented nuclei with a Support Vector Machine classifier. Nuclei were segmented with an average accuracy of 86.5%. Low, intermediate, and high-grade tumours were identified with 95%, 88.3%, and 91% accuracies respectively. The proposed algorithm could be used as a second opinion tool for the histopathologists.     

Is Structural Equation Modeling Advantageous for the Genetic Improvement of Multiple Traits?

Structural equation models (SEMs) are multivariate specifications capable of conveying causal relationships among traits. Although these models offer insights into how phenotypic traits relate to each other, it is unclear whether and how they can improve multiple-trait selection. Here, we explored concepts involved in SEMs, seeking for benefits that could be brought to breeding programs, relative to the standard multitrait model (MTM) commonly used. Genetic effects pertaining to SEMs and MTMs have distinct meanings. In SEMs, they represent genetic effects acting directly on each trait, without mediation by other traits in the model; in MTMs they express overall genetic effects on each trait, equivalent to lumping together direct and indirect genetic effects discriminated by SEMs. However, in breeding programs the goal is selecting candidates that produce offspring with best phenotypes, regardless of how traits are causally associated, so overall additive genetic effects are the matter. Thus, no information is lost in standard settings by using MTM-based predictions, even if traits are indeed causally associated. Nonetheless, causal information allows predicting effects of external interventions. One may be interested in predictions for scenarios where interventions are performed, e.g., artificially defining the value of a trait, blocking causal associations, or modifying their magnitudes. We demonstrate that with information provided by SEMs, predictions for these scenarios are possible from data recorded under no interventions. Contrariwise, MTMs do not provide information for such predictions. As livestock and crop production involves interventions such as management practices, SEMs may be advantageous in many settings.     

Computer-aided classification of malignancy in astrocytomas. II. The value of categorically evaluated histologic and non-histologic features for a numerical classifier.

The present study was carried out in order to obtain a numerical classifier for the assessment of the malignancy in astrocytomas including glioblastomas ('astrocytomas grade 4'). The attempt resulted in 'TESTAST 268', a classifier based on a reference sample of 268 tumours, 67 in each of four malignancy classes. TESTAST 268 aids the identification of astrocytomas with one of four malignancy classes by means of eight classification variables, five histologic and three non-histologic. Identification is achieved with the aid of linear discriminant functions, both according to Bayes' decision rule (BAYTEST) and by canonical discriminant analysis (CANTEST) using the squared Mahalanobis distance. The discriminant functions with the calibration of the reference sample of the 268 tumours may be implemented on personal and even small pocket computers for practical application.