Abstract
OBJECTIVE: We present a new algorithm to automatically convert 3-dimensional left atrium surface meshes into a standard 2-dimensional space: a Left Atrial Positioning System (LAPS). METHODS: Forty-five contrast-enhanced 4-dimensional computed tomography datasets were collected from 30 subjects. The left atrium volume was segmented using a trained neural network and converted into a surface mesh. LAPS coordinates were calculated on each mesh by computing lines of longitude and latitude on the surface of the mesh with reference to the center of the posterior wall and the mitral valve. LAPS accuracy was evaluated with one-way transfer of coordinates from a template mesh to a synthetic ground truth, which was created by registering the template mesh and pre-calculated LAPS coordinates to a target mesh. The Euclidian distance error was measured between each test node and its ground truth location. RESULTS: The median point transfer error was 2.13 mm between follow-up scans of the same subject (n = 15) and 3.99 mm between different subjects (n = 30). The left atrium was divided into 24 anatomic regions and represented on a 2D square diagram. CONCLUSION: The Left Atrial Positioning System is fully automatic, accurate, robust to anatomic variation, and has flexible visualization for mapping data in the left atrium. SIGNIFICANCE: This provides a framework for comparing regional LA surface data values in both follow-up and cohort studies.