Mapping Template Heart Models to Patient Data Using Image Registration

Currently, minimally invasive cardiac surgery (MICS) faces several limitations, including inadequate training methods using non-realistic models, insufficient surgery planning using 2D images, and the lack of global, 3D guidance during the procedure. To address these issues we are developing the Virtual Cardiac Surgery Platform (VCSP) – a virtual reality model of the patient specific thorax, derived from pre-procedural images. Here we present an image registration-based method for customizing a geometrical template model of the heart to any given patient, and validate it using manual segmentation as the gold standard. On average, the process is accurate to within 3.3 ± 0.3 mm in MR images, and 2.4 ± 0.3 mm in CT images. These results include inaccuracies in the gold standard, which are on average 1.6 ± 0.2 and 0.9 ± 0.2 mm for MR and CT images respectively. We believe this method adequately prepares templates for use within VCSP, prior to and during MICS.