Sci‐PM Thurs ‐ 07: Registration of geometric cardiac models to magnetic resonance images

Minimally invasive cardiac surgery (MICS) has already been shown to reduce hospital stays, but the full potential is not yet realized, largely due to limitations in pre‐ and intra‐operative visualization inside the closed chest. To address these issues, we are developing the Virtual Cardiac Surgery Platform (VCSP) — a 4D (3D + time), virtual reality model of the patient specific thorax, derived from pre‐procedural images. In this abstract, we discuss the accuracy of our image registration‐based method for deforming geometrical template models of the heart sub‐anatomy (myocardium, right atrium + ventricle, left atrium + aorta, epicardium) to 10 different volunteers (“patients”). The template models are built by manually segmenting a high quality magnetic resonance (MR) image (this template image is an average of 20 acquisitions of the same volunteer, 1.53 mm3 voxels). The template image is mapped to a much lower quality patient image (1.5×1.5×6.0 mm3 voxels) obtained in a clinically feasible manner, by maximizing the normalized mutual information (NMI) between the two images. The resulting global (affine) and local (free form deformation) transformation is applied to one of the four template models to transform it into patient space. The registration accuracy is assessed by comparing the mapped template to the manual segmentation of the patient. On average, the customization process is accurate to within 2.4 ± 0.2 mm, whereas, the difference between two manual segmentations (gold standards) was 1.3 ± 0.2 mm. We believe our method adequately prepares templates for use within VCSP, prior to and during MICS.