# Ultrasound Navigation for Transcatheter Aortic Stent Deployment Using Global and Local Information
## 2 Materials and Methods
### A Global 3D Navigation Map Based on 2D US-3D MR Image Registration
#### 2.2.1 Multi-Feature Particle Filter Tracking Method for the 3D Trajectory of the Catheter
By adding the local high-resolution navigation information to global navigation, the targeting error reduces to 1.7214 mm. Thus, combining the large view of global navigation with the high accuracy of local navigation can provide surgeons with an intuitive 3D map and adequate lesion location for precise catheter intervention in stent deployment. We have validated the applicability of our proposed system in a laboratory setting, but several problems exist and need to be solved before delivering our system to clinical in vivo interventions. Firstly, compared with the static phantom experiment in water tank, the beating of heart needs to be taken into account in the in vivo experiment. We will add phase synchronization of US, MR and IVUS images through electrocardiograph (ECG) signals to solve this problem; Secondly, in the in-vivo experiment, the collected IVUS images are more complex than the IVUS images of aortic phantom. We are conducting more evaluations of images segmentation for more patients with different degrees of severity. We acknowledge that 2D US imaging of the human body is more challenging than a phantom in water bath. This is because propagation in homogeneous tissue will cause acoustic noise and the lung and ribs will reduce the acoustic window. Our future works will focus on the research about human body experiments and applications. Furthermore, besides phantom experiments in water tanks, we are developing the evaluation experiment of a beating high-reality heart phantom through different intervention routes and operators. We believe that the proposed US navigation system has great potential to provide surgeons with more abundant information for precise transcatheter aortic stent deployment. ## 5 Conclusions

The proposed US navigation system combines the global information of intuitive 3D images with the local information of aortic morphological characteristics to provide surgeons with abundant guidance information. This system facilitates transcatheter aortic stent placement and reduces X-ray radiation and doses of contrast. The following are available online at www.mdpi.com/2076-3417/6/12/391/s1, Table S1: The detailed information and lesion characters of the patients. This study was supported in part by National Natural Science Foundation of China (Grant No. 81427803, 61361160417, 81271735), Grant-in-Aid of Project 985, and Beijing Municipal Science and Technology Commission (Z151100003915079). The Authors would like to thank [PERSON] and [PERSON] from Department of Cardiology, Navy PLA General Hospital for assistance in acquiring and analyzing the IVUS data for this study. [PERSON] and [PERSON] proposed the method, and designed the experiment. [PERSON] performed the experiment, and wrote the manuscript; [PERSON] conceived experiments and analyzed the data; [PERSON] initiated the study and supervised the project overall. All authors discussed the results. The authors declare no conflict of interest. ## Appendix A

Multi-feature fusion for particles' weights decision \(\mathbf{\lambda}\left\{,\right\}\). To compare the differences between template region \(\mathrm{R}_{t}\) and region of particles \(\mathrm{\ }^{s}\mathrm{R}_{t,m}\), multiple features of template region and particle region need to be calculated. The first feature is normalized histogram of intensity (HOI), which is defined as

\[\mathbf{g}=\mathbf{g}/\left\|\mathbf{g}\right\|=\left[g_{1}\right/\sqrt{\sum \limits_{k=1}^{K_{1}}{{{g_{k}}^{2}}}},\ \cdots,g_{K_{1}}\Big{/}\sqrt{\sum\limits_{k=1}^{K_{1}}{{{g_{k}}^{2}}}} \tag{1}\]

where \(g_{k}\) is the gray histogram counts of \(k^{\mathrm{th}}\) bin, \(K_{1}\) specifies the number of bins used in histogram. The second feature is histogram of oriented gradient (HOG) which represents contour information.