Automatic Displacement and Strain measuring in the Aorta from dynamic electrocardiographically-gated Computed Tomographic Angiography

• Introduction Image modalities like Duplex Ultrasound, Transesophageal Echocardiography, Intravascular Ultrasound, Computed Tomography and Magnetic Resonance provide vascular interventionists and surgeons with useful diagnostic information for treatment planning. Recent developments in cross-sectional imaging, including multi-modality image fusion and new contrast agents have resulted in improved spatial resolution. Specifically, dynamic Electrocardiographically-Gated Computed Tomographic Angiography (ECG-gated CTA) provides valuable information regarding motion and deformation of the normal and diseased aorta during the cardiac cycle. Extracting and presenting (visualization) of accurate quantitative information from the recorded image data, however remains a challenging task of image post processing. Method The algorithm proposed within this paper processes ECG-gated CTA data (here goes the scanner model and manufacturer) in DICOM (digital imaging and communication in medicine) format, within which the user manually defines an Eulerian Region of Interest (ROI). 2D deformable (active) contour models are used to pre-segment the luminal surfaces of the selected vessels at an arbitrary time point during the cardiac cycle. A tessellation algorithm is used to define the initial configuration of a 3D deformable (active) contour model, which in turn is used for the final segmentation of the luminal surfaces continuously during the cardiac cycle. Specifically, Finite Element (FE) formulations [1] for frames and shells, as known from structural mechanics, are used to define the deformable contour modes. This allows a direct mechanical interpretation of the applied set of reconstruction parameters and leads to an efficient FE implementation of the models [2]; parallel processor architecture is used to solve the global set of non-linear FE equations. Finally displacement and strain measures are derived from the dynamic segmentations and color coded plots are used to visualize them. Results and Conclusions The clinical relevance of dynamic imaging has not been fully exploited and accurate and fast image processing tools are critical to extract valuable information from ECG-gated CTA data. Such information is not only of direct clinical relevance but also critical to process our current understanding regarding normal and pathological aortic motions and deformations. The image processing concept proposed in this paper leads to efficient and clinically applicable software that facilitates an analysis of the entire aorta on a standard Personal Computer within a few minutes. Deformable (active) contour models are known to be more accurate compared to threshold based segmentation concepts [3] and the accuracy of the present approach is in the range of the in-plane image resolution. Apart from direct diagnostic information the extracted geometrical data could also be used (once enriched by accurate pressure measurements) for none invasive (minimal invasive) estimation of biomechanical aortic tissue properties. References [1] O. C. Zienkiewicz and R. L. Taylor, vol.1,2, 5th ed. Oxford: Butterworth Heinemann, 2000. [2] M. Auer and T. C. Gasser, IEEE T. Med. Imaging, 2010 (in press). [3] M. Sonka and J. M. Fitzpatrick, editors., Bellingham: Spie press, 2000

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TEKNIK OCH TEKNOLOGIER  -- Medicinteknik (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Medical Engineering (hsv//eng)

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