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Einleitung: Der intrazelluläre Übergang ist eine Region der zytoplasmatischen Membran und steht im engen Zusammenhang mit den Aktinfilamenten des Zytoskeletts, wo E-Cadherin als ein ca-abhängiges Molekül interagiert. Beta-Catenin steht in Verbindung mit dem zytoplasmatischen Teil des E-Cadherin und interagiert in dem komplexen Aktinnetz des Zytoskeletts. Beide Proteine spielen eine wichtige Rolle in der Vermittlung von Zellkontakten und Gewebestabilität, während ihr Abbau mit dem Aufkommen von Neoplasien in Verbindung steht. In der vorliegenden Studie wurde die Expression von E-Cadherin und beta-Catenin in Parotistumoren untersucht, um einen möglichen Zusammenhang bei der Karzinogenese dieser Tumore nachzuweisen. Methoden: Zur Untersuchung gelangten archivierte Parotiskarzinom-Proben, die immunhistochemisch mit der Methode „Evision/horseradish peroxidase“ analysiert wurden. Insgesamt wurden 69 tumoröse Gewebeproben untersucht, davon 46 Adeno-Mischkarzinome, 18 Warthin-Tumore, 3 mukoepidermoidale Karzinome, sowie ein adenoid-zystisches- und ein Plattenepithel-Karzinom. Proben aus gesundem Parotisgewebe wurden zur Kontrolle herangezogen. Ergebnisse: Membranoese und zytoplasmatische Expression von E-Cadherin wurde in 54/69 und von beta-Catenin in 68/69 beobachtet. Die Verteilung beider Proteine war in allen untersuchten Gewebeproben ähnlich, wobei E-Cadherin in weniger Proben ausgedrückt wurde. Kräftigere Expression beider Proteine wurde in Warthin- und allen bösartigen Tumoren beobachtet. Abschwächung bzw. vollständiger Verlust der Expression von E-Cadherin wurde nur in den Mischtumoren nachgewiesen. Schlussfolgerung: Die Ergebnisse weisen auf einen direkten Zusammenhang zwischen der Expression von E-Cadherin und beta-Catenin und dem histologischem Typ der Parotistumore hin., GMS Current Posters in Otorhinolaryngology - Head and Neck Surgery; 7:Doc30; ISSN 1865-1038

OBJECTIVE: To develop an advanced diagnostic method for urinary bladder tumour grading. A novel soft computing modelling methodology based on the augmentation of fuzzy cognitive maps (FCMs) with the unsupervised active Hebbian learning (AHL) algorithm is applied. MATERIAL AND METHODS: One hundred and twenty-eight cases of urinary bladder cancer were retrieved from the archives of the Department of Histopathology, University Hospital of Patras, Greece. All tumours had been characterized according to the classical World Health Organization (WHO) grading system. To design the FCM model for tumour grading, three experts histopathologists defined the main histopathological features (concepts) and their impact on grade characterization. The resulted FCM model consisted of nine concepts. Eight concepts represented the main histopathological features for tumour grading. The ninth concept represented the tumour grade. To increase the classification ability of the FCM model, the AHL algorithm was applied to adjust the weights of the FCM. RESULTS: The proposed FCM grading model achieved a classification accuracy of 72.5%, 74.42% and 95.55% for tumours of grades I, II and III, respectively. CONCLUSIONS: An advanced computerized method to support tumour grade diagnosis decision was proposed and developed. The novelty of the method is based on employing the soft computing method of FCMs to represent specialized knowledge on histopathology and on augmenting FCMs ability using an unsupervised learning algorithm, the AHL. The proposed method performs with reasonably high accuracy compared to other existing methods and at the same time meets the physicians' requirements for transparency and explicability. Artif Intell Med

OBJECTIVE: The paper aims at improving the prediction of superficial bladder recurrence. To this end, feedforward neural networks (FNNs) and a feature selection method based on unsupervised clustering, were employed. MATERIAL AND METHODS: A retrospective prognostic study of 127 patients diagnosed with superficial urinary bladder cancer was performed. Images from biopsies were digitized and cell nuclei features were extracted. To design FNN classifiers, different training methods and architectures were investigated. The unsupervised k-windows (UKW) and the fuzzy c-means clustering algorithms were applied on the feature set to identify the most informative feature subsets. RESULTS: UKW managed to reduce the dimensionality of the feature space significantly, and yielded prediction rates 87.95% and 91.41%, for non-recurrent and recurrent cases, respectively. The prediction rates achieved with the reduced feature set were marginally lower compared to the ones attained with the complete feature set. The training algorithm that exhibited the best performance in all cases was the adaptive on-line backpropagation algorithm. CONCLUSIONS: FNNs can contribute to the accurate prognosis of bladder cancer recurrence. The proposed feature selection method can remove redundant information without a significant loss in predictive accuracy, and thereby render the prognostic model less complex, more robust, and hence suitable for clinical use. Artif Intell Med

Neoplasms of the sellar region are entities with a large differential diagnosis. Although paraganglionic cells have not been demonstrated in the pituitary or adjacent structures, the existence of sellar region paragangliomas is well-documented. To elucidate, in this area the nature of these unusual tumors is relatively difficult. Clinical history, physical examination, radiographic investigation as well as intraoperative gross observation are the same as those of sellar meningioma or pituitary adenoma. Immunohistochemistry, using neuroendocrine markers and electron microscopy are the two definitive diagnostic methods to differentiate among these entities. The clinical management, the possible pathogenesis of the tumor, the importance of immunohistochemistry in making the diagnosis and the clinical outcome of these patients are discussed. Clin Neuropathol

Primary malignant melanoma of the vagina is a very rare, but very aggressive tumor. We describe a case of primary vaginal melanoma and review the literature. The patient, a 73-year-old, gravida 2, para 2 postmenopausal Greek woman, presented with abnormal vaginal bleeding for 30 days. On vaginal examination there was a 5.5 x 5 x 2 cm raised, ulcerated and irregular lesion on the posterior vaginal wall. Pathology examination of the entire specimen demonstrated a nodular vaginal melanoma. The histologic diagnosis was confirmed by positive immunostaining. The patient began postoperative immunotherapy with interferon-a2b. She died 25 months later because of cerebral metastases. In conclusion, the prognosis of vaginal melanoma is very poor, despite the treatment modality, because most cases are diagnosed at a late stage.

OBJECTIVE: To develop a method for the automated segmentation of images of routinely hematoxylin-eosin (H-E)-stained microscopic sections to guarantee correct results in computer-assisted microscopy. STUDY DESIGN: Clinical material was composed 50 H-E-stained biopsies of astrocytomas and 50 H-E-stained biopsies of urinary bladder cancer. The basic idea was to use a support vector machine clustering (SVMC) algorithm to provide gross segmentation of regions holding nuclei and subsequently to refine nuclear boundary detection with active contours. The initialization coordinates of the active contour model were defined using a SVMC pixel-based classification algorithm that discriminated nuclear regions from the surrounding tissue. Starting from the boundaries of these regions, the snake fired and propagated until converging to nuclear boundaries. RESULTS: The method was validated for 2 different types of H-E-stained images. Results were evaluated by 2 histopathologists. On average, 94% of nuclei were correctly delineated. CONCLUSION: The proposed algorithm could be of value in computer-based systems for automated interpretation of microscopic images. Anal Quant Cytol Histol

All malignant cells appear to have increased needs for glucose in vitro as well as in vivo. The enhanced glucose uptake is mediated through transporters (Gluts), whose action and expression are regulated by oncogenes and growth factors. Cyclin D1 is a nuclear protein that plays an important role in regulating the cell cycle by promoting entry of cells from the G1 to S phase. Increased expression of Glut1 glucose transporter and cyclin D1 have been reported in several neoplasms. In the present study we examined the expression of Glut1 and cyclin D1 in breast carcinomas with negative lymph nodes. We studied 78 infiltrating ductal carcinomas (25 grade 1, 36 grade 2, and 17 grade 3) with negative lymph nodes. Glut1 was expressed in 28% of grade 1, 63.8% of grade 2 and 58.7% of grade 3 carcinomas. Nuclear expression of cyclin D1 was detected in 32% of grade 1, 44.4% of grade 2, and 41.2% of grade 3 carcinomas. From our study it appears that in breast carcinomas with negative lymph nodes Glut1 expression is better correlated to the grade of the neoplasm than cyclin D1. Eur J Gynaecol Oncol

OBJECTIVE: To develop an image analysis system for automated nuclear segmentation and classification of histologic bladder sections employing quantitative nuclear features. STUDY DESIGN: Ninety-two cases were classified into three classes by experienced pathologists according to the WHO grading system: 18 cases as grade 1, 45 as grade 2, and 29 as grade 3. Nuclear segmentation was performed by means of an artificial neural network (ANN)-based pixel classification algorithm, and each case was represented by 36 nuclei features. Automated grading of bladder tumor histologic sections was performed by an ANN classifier implemented in a two-stage hierarchic tree. RESULTS: On average, 95% of the nuclei were correctly detected. At the first stage of the hierarchic tree, classifier performance in discriminating between cases of grade 1 and 2 and cases of grade 3 was 89%. At the second stage, 79% of grade 1 cases were correctly distinguished from grade 2 cases. CONCLUSION: The proposed image analysis system provides the means to reduce subjectivity in grading bladder tumors and may contribute to more accurate diagnosis and prognosis since it relies on nuclear features, the value of which has been confirmed. Anal Quant Cytol Histol