Robotic assistance for quick and accurate image-guided needle placement

Abigail J. Fong, Camille L. Stewart, Kelly Lafaro, Christopher J. LaRocca, Yuman Fong, Joseph D. Femino, Brooke Crawford

Research output: Contribution to journalArticlepeer-review

Abstract

Computed tomography (CT) image-guided procedures including biopsy, drug delivery, and ablation are gaining increasing application in medicine. Robotic technology holds the promise for allowing surgeons, and other proceduralists, access to such CT-guided procedures by potentially shortening training, improving accuracy, decreasing needle passes, and reducing radiation exposure. We evaluated surgeon learning and proficiency for image-guided needle placement with an FDA-cleared robotic arm. Five out of six surgeons had no prior CT-guided procedural experience, while one had prior experience with freehand CT-guided needle placement. All surgeons underwent a 60-min training with the MAXIO robot (Perfint Healthcare, Redmond, WA). The robot was used to place needles into three different pre-specified targets on a spine model. Performance time, procedural errors, and needle placement accuracy were recorded. All participants successfully placed needles into the targets using the robotic arm. The average time for needle placement was 3:44 ± 1:43 min. Time for needle placement decreased with subsequent attempts, with average third placement taking 2:29 ± 1:51 min less than the first attempt. The average vector distance from the target was 2.3 ± 1.2 mm. One error resulted in the need for reimaging by CT scan. No errant needle placement occurred. Surgeons (attending fellows and residents) without previous experience and minimal training could successfully place percutaneous needles under CT guidance quickly, accurately, and reproducibly using a robotic arm. This suggests that robotic technology may be used to facilitate surgeon adoption of CT image-guided needle-based procedures in the future.

Original languageEnglish (US)
Pages (from-to)1197-1201
Number of pages5
JournalUpdates in Surgery
Volume73
Issue number3
DOIs
StatePublished - Jun 2021
Externally publishedYes

Bibliographical note

Funding Information:
Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under award number P30CA033572.

Publisher Copyright:
© 2021, Italian Society of Surgery (SIC).

Keywords

  • Image guidance
  • MAXIO
  • Robotics
  • Surgical technology

PubMed: MeSH publication types

  • Journal Article

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