A technique for respiratory motion correction in image guided cardiac catheterisation procedures

This paper presents a technique for compensating for respiratory motion and deformation in an augmented reality system for cardiac catheterisation procedures. The technique uses a subject-specific affine model of cardiac motion which is quickly constructed from a pre-procedure magnetic resonance imaging (MRI) scan. Respiratory phase information is acquired during the procedure by tracking the motion of the diaphragm in real-time X-ray images. This information is used as input to the model which uses it to predict the position of structures of interest during respiration. 3-D validation is performed on 4 volunteers and 4 patients using a leave-one-out test on manually identified anatomical landmarks in the MRI scan, and 2-D validation is performed by using the model to predict the respiratory motion of structures of the heart which contain catheters that are visible in X-ray images. The technique is shown to reduce 3-D registration errors due to respiratory motion from up to 15mm down to less than 5mm, which is within clinical requirements for many procedures. 2-D validation showed that accuracy improved from 14mm to 2mm. In addition, we use the model to analyse the effects of different types of breathing on the motion and deformation of the heart, specifically increasing the breathing rate and depth of breathing. Our findings suggest that the accuracy of the model is reduced if the subject breathes in a different way during model construction and application. However, models formed during deep breathing may be accurate enough to be applied to other types of breathing.