Consistency‐based respiratory motion estimation in rotational angiography

Purpose Rotational coronary angiography enables 3D reconstruction but suffers from intra‐scan cardiac and respiratory motion. While gating handles cardiac motion, respiratory motion requires compensation. State‐of‐the‐art algorithms rely on 3D‐2D registration that depends on initial reconstructions of sufficient quality. We propose a compensation method that is applied directly in projection domain. It overcomes the need for reconstruction and thus complements the state‐of‐the‐art. Methods Virtual single‐frame background subtraction based on vessel segmentation and spectral deconvolution yields non‐truncated images of the contrasted lumen. This allows motion compensation based on data consistency conditions. We compensate craniocaudal shifts by optimizing epipolar consistency to (a) devise an image‐based surrogate for cardiac motion and (b) compensate for respiratory motion. We validate our approach in two numerical phantom studies and three clinical cases. Results Correlation of the image‐based surrogate for cardiac motion with the ECG‐based ground truth was excellent yielding a Pearson correlation of 0.93 ± 0.04. Considering motion compensation, the target error measure decreased by 98% and 69%, respectively, for the phantom experiments while for the clinical cases the same figure of merit improved by 46 ± 21%. Conclusions The proposed method is entirely image‐based and accurately estimates craniocaudal shifts due to respiration and cardiac contraction. Future work will investigate experimental trajectories and possibilities for simplification of the single‐frame subtraction pipeline.