Strategy for accurate liver intervention by an optical tracking system.

Qinyong Lin, Rongqian Yang, Ken Cai, Peifeng Guan, Weihu Xiao, Xiaoming Wu
Author Information
  1. Qinyong Lin: Department of Biomedical Engineering, South China University of Technology, Guangzhou, Guangdong, China.
  2. Rongqian Yang: Department of Biomedical Engineering, South China University of Technology, Guangzhou, Guangdong, China.
  3. Ken Cai: School of Information Science and Technology, Zhongkai University of Agriculture and Engineering, Guangzhou, Guangdong, China.
  4. Peifeng Guan: Department of Biomedical Engineering, South China University of Technology, Guangzhou, Guangdong, China.
  5. Weihu Xiao: Department of Biomedical Engineering, South China University of Technology, Guangzhou, Guangdong, China.
  6. Xiaoming Wu: Department of Biomedical Engineering, South China University of Technology, Guangzhou, Guangdong, China.

Abstract

Image-guided navigation for radiofrequency ablation of liver tumors requires the accurate guidance of needle insertion into a tumor target. The main challenge of image-guided navigation for radiofrequency ablation of liver tumors is the occurrence of liver deformations caused by respiratory motion. This study reports a strategy of real-time automatic registration to track custom fiducial markers glued onto the surface of a patient's abdomen to find the respiratory phase, in which the static preoperative CT is performed. Custom fiducial markers are designed. Real-time automatic registration method consists of the automatic localization of custom fiducial markers in the patient and image spaces. The fiducial registration error is calculated in real time and indicates if the current respiratory phase corresponds to the phase of the static preoperative CT. To demonstrate the feasibility of the proposed strategy, a liver simulator is constructed and two volunteers are involved in the preliminary experiments. An ex-vivo porcine liver model is employed to further verify the strategy for liver intervention. Experimental results demonstrate that real-time automatic registration method is rapid, accurate, and feasible for capturing the respiratory phase from which the static preoperative CT anatomical model is generated by tracking the movement of the skin-adhered custom fiducial markers.

Keywords

References

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