Fine needle insertion method for minimising deflection in lower abdomen: In vivo evaluation

Ryosuke Tsumura*, Iulian Iordachita, Hiroyasu Iwata

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


Background: Fine needle insertion in the lower abdomen is difficult because of complex deflections and few image feedbacks. We aim to develop an approach for generating a straight insertion path by minimizing the needle deflection robustly based on a preoperative computer tomography (CT) image. Method: This study presents two approaches: an insertion control strategy that performs both vibration and rotation-assisted needle insertions and a preoperative insertion path planning for determining an optimal insertion path based on insertion angles at each tissue boundary. Those proposed approaches were evaluated through an in vivo experiment with a Landrace mini-pig. We compered the following: (1) the deflection with and without the insertion control strategy in different 10 insertion paths and (2) the score calculated by the path planning and the actual deflection in the 10 insertion paths. Results: The result shows that the deflection can be reduced significantly by applying the insertion control strategy in the optimal insertion path calculated by the path planning. Conclusion: The proposed method can decrease fine needle deflections in the lower abdomen, which has the potential for accurate and safety procedures without real-time CT imaging.

Original languageEnglish
Pages (from-to)1-12
Number of pages12
JournalInternational Journal of Medical Robotics and Computer Assisted Surgery
Issue number6
Publication statusPublished - 2020 Dec


  • CT-guided needle insertion
  • fine needle insertion
  • in vivo
  • lower abdomen
  • robotic needle insertion

ASJC Scopus subject areas

  • Surgery
  • Biophysics
  • Computer Science Applications


Dive into the research topics of 'Fine needle insertion method for minimising deflection in lower abdomen: In vivo evaluation'. Together they form a unique fingerprint.

Cite this