engleski

Mastocytoma in dogs - Persistant challenge in veterinary oncology

Among dog's skin tumors mast-cell tumors are the most frequent and represent major problem in oncology of these animals. All literature data state that the frequency of these tumors is between 12 and 20% of all skin tumors, there is no sex predisposition, location is in the majority of cases limbs, thorax and abdomen, and the breed risk is significant for boxers, retrievers and beagles. Although the clinical diagnose may be challeging, histopathological examination in most cases is not so demanding. Namely, in the majority of cases mast-cell are characteristic enough to allow positive diagnosis. However, the problem emerges in uniform use of grading system. Although, all mast-cell tumors should been considered as malignant, there are important differences in its clinical behaviour. Classically there are three grades of this tumor, low grade (grade I.), intermediate grade (grade II.) and high grade (grade III.) among which the high grade is most malignant. PHD grading systems try to collerate biological behaviour of the tumor and it histopathological features. This procedure is unfortunately very subjective and there is significant differences in the grades ratio in the literature. Because of that, the contiunuous investigation concerning the tumor biological behaviour and its histological caharacteristics is necessar. Recently in our Department we conduct the comprehensive investigations of this tumors in which we tried to collerate and statisticaly evaluate all PHD features and some immunohistochemical tumor markers (CD117, VEGF, CD45, Ki67 and survivin). Besides that, we evaluated the usefullness of NuMap 7.06 software for implementation of neural network for performing nonlinear regression and aproximation. This software is developed on Image Processing and Neural Networks Lab University of Texas at Arlington (www-ee.uta.edu/eeweb/IP/). Basically, these self-learning softwares are used for computer-based calculation of the very different entering data which at the end provide objective finding. Network constants are calculated on the test data, which in this case means various PHD features expressed numerically and final grade for each case. All new cases of mast-cell tumors were evaluated using that software and routine procedure and the results were statisticaly the same. These findings allows very significant improvement of the objectivity of the grading system and give us possibility of the uniform diagnostic procedure which is not depending on the pathologist's experience. Also, statistical analysis of the various PHD characteristics showed marked differences in its importance for the determination of the different tumor grades, which will allow us to reduce and more simplify entering data and whole process.

Dog; Mastocytoma

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