Novel C-arm based planning spine surgery robot proved in a porcine model and quantitative accuracy assessment methodology

Hyung Cheol Kim, Hyeongseok Jeon, Seong Bae An, Hongho Kim, Sungteac Hwang, Yongyeob Cha, Seohyun Moon, Dong Ah Shin, Yoon Ha, Keung Nyun Kim, Do Heum Yoon, Seong Yi

Research output: Contribution to journalArticlepeer-review

Abstract

Background: We assessed pedicle screw accuracy utilizing a novel navigation-based spine surgery robotic system by comparing planned pathways with placed pathways in a porcine model. Methods: We placed three mini screws per vertebra for accuracy evaluation and used a reference frame for registration in four pigs (46 screws in 23 vertebrae). We planned screw paths and performed screw insertion under robot guidance. Using C-arm and CT images, we evaluated accuracy by comparing the 3D distance of the placed screw head/tip from the planned screw head/tip and 3D angular offset. Results: Mean registration deviation between the preoperative 3D space (C-arm) and postoperative CT scans was 0.475 ± 0.119 mm. The average offset from preoperative plan to final placement was 4.8 ± 2.0 mm from the head (tail), 5.3 ± 2.3 mm from the tip and 3.9 ± 2.4 degrees of angulation. Conclusions: Our spine surgery robot showed good accuracy in executing an intended planned trajectory and screw path. This faster and more accurate robotic system will be applied in future studies, first in cadavers and subsequently in the clinical field.

Original languageEnglish
JournalInternational Journal of Medical Robotics and Computer Assisted Surgery
DOIs
Publication statusAccepted/In press - 2020

Bibliographical note

Funding Information:
This study was supported by The Technology Innovation Program funded by the Ministry of Trade, Industry & Energy, Korea (10062712, Development of spinal fusion implant and its manufacturing system; the functionality optimized, patient‐customized in terms of bioactive materials to meet the clinical needs) and the Technological Innovation R&D Program (S2519401) funded by the Small and Medium Business Administration (SMBA, Korea) and The Development spine surgery robot and animal study funded by Curexo Inc. (2017‐31‐1035, 2019‐31‐0831) and funded by the Korea Institute for Robot Industry Advancement.

All Science Journal Classification (ASJC) codes

  • Surgery
  • Biophysics
  • Computer Science Applications

Fingerprint Dive into the research topics of 'Novel C-arm based planning spine surgery robot proved in a porcine model and quantitative accuracy assessment methodology'. Together they form a unique fingerprint.

Cite this