Detection of substances in the left atrial appendage by spatiotemporal motion analysis based on 4D-CT

Abstract

The detection of substances in the left atrial appendage (LAA) is essential in evaluating disease development and treatment planning in patients with atrial fibrillation. The advent of 4D-CT bringing high spatiotemporal resolution, we present a new approach for the detection of substances in the LAA by spatiotemporal motion analysis and make a detailed judgment and analysis of spatial distribution and classification of most objects in the LAA. The noise interference is also eliminated properly. This approach requires the extraction of the optical flow field for all adjacent phases in a cardiac cycle of 20 phases. According to the optical flow information of 19 optical flow fields, we adopt the nearest neighbor interpolation method to establish the motion trajectory of the key voxels in a whole cardiac cycle. Then we create a hierarchical clustering tree by calculating the similarity between the tracks based on hierarchical clustering and find the corresponding classification for every track. Different classifications of tracks represent the divisions of substances in the LAA. Finally, we perform the stress and strain detection of the critical lump using time-frequency analysis of their trajectories. Tests and validations of our approach were performed on 32 data sets (artificial diagnosis of echocardiography and 4-D CT). The frequency responded range to stress and strain of different substances was obtained, which included normal circulation blood, mild, moderate and severe SEC blood, initial jelling thrombi, old or calcified thrombi, organic thrombi and pectinate muscles. Our results are consistent with the two artificial diagnoses. Furthermore, they can refine the identification of substances such as their texture and tiny sizes.