Alkhimova S. Adaptive CT-image processing and analysis of scull base Juvenile Angiofibromas

The dissertation is devoted to obtaining complex data of scull base Juvenile Angiofibromas blood filling estimation questions. It is based on adaptive CT-image processing and analysis and provides probabilities increasing of huge bleeding risks prediction during Juvenile Angiofibromas surgery for each specific patient. Analytical survey of diagnostic methods for blood filling visualization and its quantitative estimation showed the absence of universal, reliable, and available method for estimation of bleeding volume during the surgeries. Widespread methods of perfusion examination such as Perfusion CT can't be used for such purposes because of reliable analytic software absence for obtained data processing that has approved statistics. New procedure of complex data obtaining for tissues blood filling estimation was proposed. It is based on common clinical analysis and on image processing and analysis data of widespread examination for patients with scull base Juvenile Angiofibromas (computed tomographic scanning). The procedure can be used for complex visual and quantitative analysis of blood filling. Therefore it resolves composite dependency of intraoperative bleeding from such several factors as operative technique, local, and general characteristics of patient's body. In addition it increases the examination area on whole tumor volume in comparison of Perfusion CT examination results. Further developments of region growing segmentation method were proposed based on usage of CT-images with contrast enhancement. This improved the accuracy of Juvenile Angiofibromas segments obtaining on tomographic slices through decreasing in the number of wrong area presents. Therefore it improved the accuracy of more exact visual and quantitative data obtaining for tissues blood filling estimation. It was obtained formalized description of tumor segments vascularization through vessel's masks for tumor tissues area. Vessel's masks are based on information from computed tomographic slices with contrast enhancement that provides additional information of tumor density. Usage of vessel's masks made it possible to obtain visual and quantitative information of tumor's vascular structures based on anatomical data for each specific patient. 3D visualization method based on optical model was improved with usage of vessel's masks for tumor slices. This made it possible to maintain the visualization of tumor's vascularization regions in 3D space and extended 3D visualization capabilities for blood filling investigation of Juvenile Angiofibromas tissues and for visual comprehension of tumors internal structure in 3D space. Therefore it gave the possibilities to see operative techniques by physicians in proper perspective of specific execution techniques. For the first time 3D anatomical voxel models statistical analysis was proposed for tumor's tissues blood filling quantitative estimation based on data from CT-images. It was experimentally approved statistical characteristic's values dependence on relative blood portion of tumor volume. It was showed statistically significant relationships between intraoperative bleeding and values of statistical characteristics. This proved the objectivity of statistical characteristics usage for quantitative estimation of Juvenile Angiofibromas blood filling based on results of CT-images processing and analysis. Segmentation method with using of contrast enhancement slices, 3D visualization method with using of vessel's masks for tumor slices, 3D anatomical voxel models statistical analysis, and their algorithm's realizations and implementations can be used for maintain decision making functionality in medical expert systems and for presurgical treatment planning and specific surgery modeling in surgery planning systems. Obtained results have important role for tissues blood filling diagnostic based on computed tomographic scanning examinations with contrast enhancement. They can be adopted for obtaining diagnostic data that help to predict huge bleeding risks for each specific patient during any surgeries. Dissertation results were adopted to the practice of Otolaryngology Institute A.Kolomyichenko and to the education of National Technical University of Ukraine "KPI".