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Preparing the anatomical model for ablation of unresectable liver tumor

INTRODUCTION: Nowadays the best treatment of the primary and secondary hepatic tumor is surgical resection, but only 5–15% of all patient with hepatocellular carcinoma and 20–25% of all patients with liver metastases are indicated for resection. In these cases some kind of ablation and other techniq...

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Detalles Bibliográficos
Autor principal: Spinczyk, Dominik
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Termedia Publishing House 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4105683/
https://www.ncbi.nlm.nih.gov/pubmed/25097694
http://dx.doi.org/10.5114/wiitm.2014.43022
Descripción
Sumario:INTRODUCTION: Nowadays the best treatment of the primary and secondary hepatic tumor is surgical resection, but only 5–15% of all patient with hepatocellular carcinoma and 20–25% of all patients with liver metastases are indicated for resection. In these cases some kind of ablation and other technique could be used. AIM: To present the methodology of preparing the anatomical model for ablation of unresectable liver tumor. MATERIAL AND METHODS: The presented method is based on abdomen computed tomography (CT) dynamic examination. Three methods of segmentation are used: rolling vector for liver volume, modified Frangi filter for liver vessels, and fuzzy expert system with initial region-of-interest anisotropic filtration for liver metastases. Segmentation results are the input data for creating 3D anatomical models in the form of B-spline curves and surfaces performing the surface global interpolation algorithm. A graphical user interface for presentation and evaluation of models, presented in color against DICOM images in grayscale, is designed and implemented. RESULTS: The proposed approach was tested on 20 abdominal CT obtained from the Department of Clinical Radiology of Silesian Medical University. The lack of a “gold standard” provides for the correction of the results. CONCLUSIONS: Preparation of the anatomical model is one of the important early stages of the use of image-based navigation systems. This process could not take place in a fully automatic manner and verification of the results obtained is performed by the radiologist. Using the above anatomical model in surgical workflow is presented.