Data-driven detection of adverse events in robotic needle steering

Meenakshi Narayan, Ann Majewicz Fey, Michael A. Choti

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In robotic needle steering, adverse events such as needle buckling, undesired curvature changes, and tissue displacement can occur during needle insertions into tissue, preventing accurate needle placement. This paper focuses on detecting tissue displacement and needle curvature changes using data-driven detection algorithms, informed solely by needle and tissue position measurements. The algorithms were evaluated for different needle insertion velocities and duty-cycles, and analyzed using a Kruskal-Wallis statistical test. Results show that with increased insertion velocity, tissues displace sooner (p <0.01), while duty-cycles have no effect. Furthermore, with increased insertion velocity and lower duty-cycles, the needle curvature radius decreases (p <0.01). Additionally, the algorithms were evaluated for needle insertions into ex vivo liver tissue, under live fluoroscopic imaging. The goal of this study was to evaluate the effects of constrained or unconstrained boundary conditions on adverse events. As expected, unconstrained tissue experienced more displacement events. Fluoroscopic videos confirmed accurate and timely prediction of the adverse events. Finally, these algorithms were designed to detect multiple adverse events, simultaneously, and can be implemented in real time.

Original languageEnglish (US)
Title of host publication2018 International Symposium on Medical Robotics, ISMR 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
Volume2018-January
ISBN (Electronic)9781538625125
DOIs
StatePublished - Apr 6 2018
Event2018 International Symposium on Medical Robotics, ISMR 2018 - Atlanta, United States
Duration: Mar 1 2018Mar 3 2018

Other

Other2018 International Symposium on Medical Robotics, ISMR 2018
CountryUnited States
CityAtlanta
Period3/1/183/3/18

Fingerprint

Needles
Robotics
Tissue
Position measurement
Statistical tests
Liver
Buckling
Boundary conditions
Imaging techniques

Keywords

  • adverse events
  • Data-driven detection
  • robotic needle steering
  • tissue displacement

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Biomedical Engineering
  • Artificial Intelligence

Cite this

Narayan, M., Fey, A. M., & Choti, M. A. (2018). Data-driven detection of adverse events in robotic needle steering. In 2018 International Symposium on Medical Robotics, ISMR 2018 (Vol. 2018-January, pp. 1-6). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISMR.2018.8333297

Data-driven detection of adverse events in robotic needle steering. / Narayan, Meenakshi; Fey, Ann Majewicz; Choti, Michael A.

2018 International Symposium on Medical Robotics, ISMR 2018. Vol. 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. p. 1-6.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Narayan, M, Fey, AM & Choti, MA 2018, Data-driven detection of adverse events in robotic needle steering. in 2018 International Symposium on Medical Robotics, ISMR 2018. vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 1-6, 2018 International Symposium on Medical Robotics, ISMR 2018, Atlanta, United States, 3/1/18. https://doi.org/10.1109/ISMR.2018.8333297
Narayan M, Fey AM, Choti MA. Data-driven detection of adverse events in robotic needle steering. In 2018 International Symposium on Medical Robotics, ISMR 2018. Vol. 2018-January. Institute of Electrical and Electronics Engineers Inc. 2018. p. 1-6 https://doi.org/10.1109/ISMR.2018.8333297
Narayan, Meenakshi ; Fey, Ann Majewicz ; Choti, Michael A. / Data-driven detection of adverse events in robotic needle steering. 2018 International Symposium on Medical Robotics, ISMR 2018. Vol. 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. pp. 1-6
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