Fully automated tracking of cardiac structures using radiopaque markers and high-frequency videofluoroscopy in an in vivo ovine model: from three-dimensional marker coordinates to quantitative analyses

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Abstract
Recently, algorithms were developed to track radiopaque markers in the heart fully automated. However, the methodology did not allow to assign the exact anatomical location to each marker. In this case study we describe the steps from the generation of three-dimensional marker coordinates to quantitative data analyses in an in vivo ovine model. In one adult sheep, twenty silver balls were sutured to the right side of the heart: 10 to the tricuspid annulus, one to the anterior tricuspid leaflet and nine to the epicardial surface of the right ventricle. In addition, 13 cylindrical tantalum markers were implanted into the left ventricle. Data were acquired with a biplanar X-ray acquisition system (Neurostar R, Siemens AG, 500 Hz). Radiopaque marker coordinates were determined fully automated using novel tracking algorithms. The anatomical marker locations were identified using a 3-dimensional model of a single frame containing all tracked markers. First, cylindrical markers were manually separated from spherical markers, thus allowing to distinguish right from left heart markers. The fast moving leaflet marker was identified by using video loops constructed of all recorded frames. Rotation of the 3-dimensional model allowed the identification of the precise anatomical position for each marker. Data sets were then analyzed quantitatively using customized software. The method presented in this case study allowed quantitative data analyses of radiopaque cardiac markers that were tracked fully automated with high temporal resolution. However, marker identification still requires substantial manual work. Future improvements including the implication of marker identification algorithms and data analysis software could allow almost real-time quantitative analyses of distinct cardiac structures with high temporal and spatial resolution.
Funding Information
  • Interdisziplinäres Zentrum für Klinische Forschung (IZKF), Friedrich Schiller University, Jena, Germany (J 26)

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