Left atrium surface mesh reconstruction from cardiac MRI

FUNDING ACKNOWLEDGEMENTS: Type of funding sources: None. BACKGROUND: The strive towards personalised medicine is universal across all aspects of healthcare. In the management of atrial fibrillation (AF), this can take the form of shape analysis tools to predict an individual’s outcome from catheter ablation (1–3), or electrophysiological simulations to plan an ablation strategy (4–6). Fundamental to their application is our ability to derive accurate three-dimensional (3D) anatomical models of a patient’s left atrial geometry from cross-sectional imaging. MRI is widely utilised in this regard due to its excellent tissue characterisation. However, constructing surface meshes can be challenging given its relatively sparse two-dimensional (2D) image planes. A particular challenge exists in producing a mesh that balances concordance with left atrium segmentation and smoothing terms to eliminate sharp edges and artifact from the contouring process. OBJECTIVE: Here, we describe a novel method for left atrium surface mesh reconstruction from MRI contours. METHODS: Cardiac MRI was performed on ten patients with paroxysmal or persistent AF, on a 3T clinical MR scanner using phased-array receiver coils. Image sequences included respiratory and ECG-gated 15-minute post contrast late gadolinium enhancement, with a 1.3mm slice thickness and in-plane resolution of 0.66×0.66mm2. Seven individuals were in sinus rhythm, and three in AF at the time of MRI. A single, custom, graphical interface tool implemented in Matlab R2014a enabled 3D mesh reconstruction from 2D MRI slices (7,8). Endocardial surfaces of the left atrium were manually segmented by an experienced clinician, with the pulmonary veins and left atrial appendage excluded at their ostia (Figure 1A). Our tool produced an initial sparse representation with vertices equally spaced along the contours (Figure 1B). Attractor points were defined along the contours, with subdivision and Laplacian smoothing applied to the mesh. This was balanced with a deformation step, which iteratively pulled the mesh towards the attractor points (Figure 1C), resulting in its final shape (Figure 1D). RESULTS: Reconstruction performance was evaluated by measuring the distance between heart contours and the reconstructed 3D surface for each case, producing the value for average misalignment 0.71 ± 0.58mm, which compares favourably to the in-plane resolution. CONCLUSIONS: Our approach offers a highly accurate method for producing 3D anatomical models of the left atrium from MRI, which is fully automated following segmentation through an interactive graphical interface. The iterative optimisation between attractor-based deformation towards the original contours and the Laplacian smoothing enables us to create smooth geometries which remain true to their segmentations. Furthermore, our approach does not require the use of a template mesh, which can result in final geometries being biased towards the template. [Figure: see text]