4.5 Article

Database-driven patient-specific registration error compensation method for image-guided laparoscopic surgery

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s11548-022-02804-y

Keywords

Surgical navigation; Registration; Laparoscopy; Computer-aided surgery

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A surgical navigation system is important for surgeons to understand anatomical structures during surgery. In this study, a compensation method using a database was proposed to reduce registration error in laparoscopic surgery navigation. The method involved analyzing positional information and averaging difference matrices computed from fiducial markers. The results demonstrated that the proposed method significantly decreased target registration error and improved the accuracy of laparoscopic surgery navigation.
Purpose A surgical navigation system helps surgeons understand anatomical structures in the operative field during surgery. Patient-to-image registration, which aligns coordinate systems between the CT volume and a positional tracker, is vital for accurate surgical navigation. Although a point-based rigid registration method using fiducials on the body surface is often utilized for laparoscopic surgery navigation, precise registration is difficult due to such factors as soft tissue deformation. We propose a method that compensates a transformation matrix computed using fiducials on the body surface based on the analysis of positional information in the database. Methods We built our database by measuring the positional information of the fiducials and the guidance targets in both the CT volume and positional tracker coordinate systems through previous surgeries. We computed two transformation matrices: using only the fiducials and using only the guidance targets in all the data in the database. We calculated the differences between the two transformation matrices in each piece of data. The compensation transformation matrix was computed by averaging these difference matrices. In this step, we selected the data from the database based on the similarity of the fiducials and the configuration of the guidance targets. Results We evaluated our proposed method using 20 pieces of data acquired during laparoscopic gastrectomy for gastric cancer. The locations of blood vessels were used as guidance targets for computing target registration error. The mean target registration errors significantly decreased from 33.0 to 17.1 mm before and after the compensation. Conclusion This paper described a registration error compensation method using a database for image-guided laparoscopic surgery. Since our proposed method reduced registration error without additional intraoperative measurements during surgery, it increases the accuracy of surgical navigation for laparoscopic surgery.

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