Establishment of antibody panels and histochemical techniques in routine tumor diagnosis in Veterinary Pathology

In Portugal, Veterinary Pathology is developing rapidly, and in recent years we assist to the emergence of private laboratories and the restructuring of universities,polytechnics and public laboratories.The Portuguese Society of Animal Pathology,through its actions and its associates has been keeping the discussion among its peers in order to standardizethe criteria of description,classification and evaluation of cases which are the subject of our daily work.One of the last challenges is associated with the use of routine histochemical techniques and immunohistochemistry, in an effort to establish standardized panels for tumour diagnosis, which could eventually reduce each analysis cost.For this purpose a simple survey was built, in which all collaborators answered questions about the markers used for carcinoma, sarcoma and round cell tumour diagnosis, as well as general questions related with the subject. We obtained twenty-one answered to the questions, from public and private laboratories.In general, in most cases immunohistochemical and histochemical methods are used for diagnosis.The wide spectrum cytokeratins are universally used to confirm carcinoma, and vimentin for sarcoma. The CD3 marker is used by all laboratories to identify T lymphocytes. For the diagnosis of B-cell lymphoma, the marker used is not consensual. In each laboratory there are different markers for more specific situations and only two labs perform PCR techniques for diagnosis. These data will be presented to promote extended discussion,namely to reach a consensus when different markers are used.

Analysis of Pancreas Histological Images for Glucose Intolerance Identification using Wavelet Decomposition

Subtle structural differencescan be observed in the islets of Langer-hans region of microscopic image of pancreas cell of the rats having normal glucose tolerance and the rats having pre-diabetic(glucose intolerant)situa-tions. This paper proposes a way to automatically segment the islets of Langer-hans region fromthe histological image of rat's pancreas cell and on the basis of some morphological feature extracted from the segmented region the images are classified as normal and pre-diabetic.The experiment is done on a set of 134 images of which 56 are of normal type and the rests 78 are of pre-diabetictype. The work has two stages: primarily,segmentationof theregion of interest (roi)i.e. islets of Langerhansfrom the pancreatic cell and secondly, the extrac-tion of the morphological featuresfrom the region of interest for classification. Wavelet analysis and connected component analysis method have been used for automatic segmentationof the images. A few classifiers like OneRule, Naïve Bayes, MLP, J48 Tree, SVM etc.are used for evaluation among which MLP performed the best.