Evaluating deformation patterns of the thoracic aorta in gated CTA sequences

Authors:
Ernst Schwartz;Roman Gottardi;Johannes Holfeld;Christian Loewe;Martin Czerny;Georg Langs
Affiliations:
Computational Image Analysis and Radiology Lab, Medical University of Vienna and Vienna University of Technology;Dept. of Surgery, Medical University of Vienna;Dept. of Surgery, Medical University of Vienna;Dept. of Radiology, Medical University of Vienna;Dept. of Surgery, Medical University of Vienna;Computational Image Analysis and Radiology Lab, Medical University of Vienna and Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology
Venue:
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
Year:
2010

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Abstract

Cardiovascular interventions in the region of the aortic isthmus such as stent-grafting and vessel transposition introduce substantial changes in the deformation properties of the affected vessels. The changes playa fundamental role in the long-term prognosis for any such treatment, but are only poorly understood to date. We explore a fully automated method to quantify the deformation patterns of the thoracic aorta in gated computed tomography sequences. The aorta is segmented by a level set approach that accurately identifies the vessel lumen in each frame of the sequence. Consequently, landmarks on the vessel wall in each frame are registered using a probabilistic method. This allows for the measurement of global and local deformation properties. We evaluate our method on synthetic datasets and report first results of its application on real world data.