Cardiovascular disease in general and coronary artery disease (CAD) in particular, are the leading cause of death worldwide. They are principally diagnosed using either invasive percutaneous transluminal coronary angiograms or non-invasive computed tomography angiograms (CTA). Minimally invasive therapies for CAD such as angioplasty and stenting are rendered under fluoroscopic guidance. Both invasive and non-invasive imaging modalities employ ionizing radiation and there is concern for deterministic and stochastic effects of radiation. Accurate simulation to optimize image quality with minimal radiation dose requires detailed, gender-specific anthropomorphic phantoms with anatomically correct heart and associated vasculature. Such phantoms are currently unavailable. This paper describes an open source heart phantom development platform based on a graphical user interface. Using this platform, we have developed seven high-resolution cardiac/coronary artery phantoms for imaging and dosimetry from seven high-quality CTA datasets. To extract a phantom from a coronary CTA, the relationship between the intensity distribution of the myocardium, the ventricles and the coronary arteries is identified via histogram analysis of the CTA images. By further refining the segmentation using anatomy-specific criteria such as vesselness, connectivity criteria required by the coronary tree and image operations such as active contours, we are able to capture excellent detail within our phantoms. For example, in one of the female heart phantoms, as many as 100 coronary artery branches could be identified. Triangular meshes are fitted to segmented high-resolution CTA data. We have also developed a visualization tool for adding stenotic lesions to the coronaries. The male and female heart phantoms generated so far have been cross-registered and entered in the mesh-based Virtual Family of phantoms with matched age/gender information. Any phantom in this family, along with user-defined stenoses, can be used to obtain clinically realistic projection images with the Monte Carlo code penMesh for optimizing imaging and dosimetry.

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http://dx.doi.org/10.1088/0031-9155/56/18/005DOI Listing

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