Body-Mounted Robotics for Interventional MRI Procedures.

MRI-guided intervention arthrography body-mounted robot chronic pain management musculoskeletal procedure

Journal

IEEE transactions on medical robotics and bionics
ISSN: 2576-3202
Titre abrégé: IEEE Trans Med Robot Bionics
Pays: United States
ID NLM: 101749706

Informations de publication

Date de publication:
Nov 2020
Historique:
entrez: 29 3 2021
pubmed: 30 3 2021
medline: 30 3 2021
Statut: ppublish

Résumé

This paper reports the development and initial cadaveric evaluation of a robotic framework for MRI-guided interventions using a body-mounted approach. The framework is developed based on modular design principles. The framework consists of a body-mounted needle placement manipulator, robot control software, robot controller, interventional planning workstation, and MRI scanner. The framework is modular in the sense that all components are connected independently, making it readily extensible and reconfigurable for supporting the clinical workflow of various interventional MRI procedures. Based on this framework we developed two body-mounted robots for musculoskeletal procedures. The first robot is a four-degree of freedom system called ArthroBot for shoulder arthrography in pediatric patients. The second robot is a six-degree of freedom system called PainBot for perineural injections used to treat pain in adult and pediatric patients. Body-mounted robots are designed with compact and lightweight structure so that they can be attached directly to the patient, which minimizes the effect of patient motion by allowing the robot to move with the patient. A dedicated clinical workflow is proposed for the MRI-guided musculoskeletal procedures using body-mounted robots. Initial cadaveric evaluations of both systems were performed to verify the feasibility of the systems and validate the clinical workflow.

Identifiants

pubmed: 33778433
doi: 10.1109/tmrb.2020.3030532
pmc: PMC7996400
mid: NIHMS1649199
doi:

Types de publication

Journal Article

Langues

eng

Pagination

557-560

Subventions

Organisme : NIBIB NIH HHS
ID : R01 EB020003
Pays : United States
Organisme : NIBIB NIH HHS
ID : R01 EB025179
Pays : United States

Références

IEEE Trans Robot. 2017 Dec;33(6):1386-1397
pubmed: 29225557
J Med Imaging (Bellingham). 2019 Apr;6(2):025006
pubmed: 31131290
J Med Robot Res. 2019 Jun;4(2):
pubmed: 31485544
IEEE ASME Trans Mechatron. 2017 Feb;22(1):115-126
pubmed: 28867930
IEEE Robot Autom Lett. 2020 Oct;5(4):5245-5251
pubmed: 33748414
IEEE Trans Biomed Eng. 2015 Apr;62(4):1077-88
pubmed: 25376035
Phys Med Biol. 2018 Apr 13;63(8):085010
pubmed: 29546845
Cardiovasc Intervent Radiol. 2018 Sep;41(9):1428-1435
pubmed: 29876597
Int J Med Robot. 2009 Dec;5(4):423-34
pubmed: 19621334

Auteurs

Gang Li (G)

Laboratory for Computational Sensing and Robotics (LCSR), Johns Hopkins University, Baltimore, MD, USA.

Niravkumar A Patel (NA)

Laboratory for Computational Sensing and Robotics (LCSR), Johns Hopkins University, Baltimore, MD, USA.

Karun Sharma (K)

Sheikh Zayed Institute for Pediatric Surgical Innovation, Childrens National Hospital, Washington, DC, USA.

Reza Monfaredi (R)

Sheikh Zayed Institute for Pediatric Surgical Innovation, Childrens National Hospital, Washington, DC, USA.

Charles Dumoulin (C)

Cincinnati Childrens Hospital Medical Center, Cincinnati, OH, USA.

Jan Fritz (J)

New York University, New York, NY, USA.

Iulian Iordachita (I)

Laboratory for Computational Sensing and Robotics (LCSR), Johns Hopkins University, Baltimore, MD, USA.

Kevin Cleary (K)

Sheikh Zayed Institute for Pediatric Surgical Innovation, Childrens National Hospital, Washington, DC, USA.

Classifications MeSH