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Fully Actuated Body-Mounted Robotic System for MRI-Guided Lower Back Pain Injections: Initial Phantom and Cadaver Studies.
Li, Gang; Patel, Niravkumar A; Wang, Yanzhou; Dumoulin, Charles; Loew, Wolfgang; Loparo, Olivia; Schneider, Katherine; Sharma, Karun; Cleary, Kevin; Fritz, Jan; Iordachita, Iulian.
Afiliación
  • Li G; Gang Li, Niravkumar A. Patel, Yanzhou Wang, and Iulian Iordachita are with Laboratory for Computational Sensing and Robotics (LCSR), Johns Hopkins University, Baltimore, MD, USA.
  • Patel NA; Gang Li, Niravkumar A. Patel, Yanzhou Wang, and Iulian Iordachita are with Laboratory for Computational Sensing and Robotics (LCSR), Johns Hopkins University, Baltimore, MD, USA.
  • Wang Y; Gang Li, Niravkumar A. Patel, Yanzhou Wang, and Iulian Iordachita are with Laboratory for Computational Sensing and Robotics (LCSR), Johns Hopkins University, Baltimore, MD, USA.
  • Dumoulin C; Charles Dumoulin, Wolfgang Loew, Olivia Loparo, and Katherine Schneider are with Cincinnati Childrens Hospital Medical Center, Cincinnati, OH, USA.
  • Loew W; Charles Dumoulin, Wolfgang Loew, Olivia Loparo, and Katherine Schneider are with Cincinnati Childrens Hospital Medical Center, Cincinnati, OH, USA.
  • Loparo O; Charles Dumoulin, Wolfgang Loew, Olivia Loparo, and Katherine Schneider are with Cincinnati Childrens Hospital Medical Center, Cincinnati, OH, USA.
  • Schneider K; Charles Dumoulin, Wolfgang Loew, Olivia Loparo, and Katherine Schneider are with Cincinnati Childrens Hospital Medical Center, Cincinnati, OH, USA.
  • Sharma K; Karun Sharma and Kevin Cleary are with the Sheikh Zayed Institute for Pediatric Surgical Innovation, Childrens National Hospital, Washington, DC, USA.
  • Cleary K; Karun Sharma and Kevin Cleary are with the Sheikh Zayed Institute for Pediatric Surgical Innovation, Childrens National Hospital, Washington, DC, USA.
  • Fritz J; Jan Fritz is with Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
  • Iordachita I; Gang Li, Niravkumar A. Patel, Yanzhou Wang, and Iulian Iordachita are with Laboratory for Computational Sensing and Robotics (LCSR), Johns Hopkins University, Baltimore, MD, USA.
IEEE Robot Autom Lett ; 5(4): 5245-5251, 2020 Oct.
Article en En | MEDLINE | ID: mdl-33748414
This paper reports the improved design, system integration, and initial experimental evaluation of a fully actuated body-mounted robotic system for real-time MRI-guided lower back pain injections. The 6-DOF robot is composed of a 4-DOF needle alignment module and a 2-DOF remotely actuated needle driver module, which together provide a fully actuated manipulator that can operate inside the scanner bore during imaging. The system minimizes the need to move the patient in and out of the scanner during a procedure, and thus may shorten the procedure time and streamline the clinical workflow. The robot is devised with a compact and lightweight structure that can be attached directly to the patient's lower back via straps. This approach minimizes the effect of patient motion by allowing the robot to move with the patient. The robot is integrated with an image-based surgical planning module. A dedicated clinical workflow is proposed for robot-assisted lower back pain injections under real-time MRI guidance. Targeting accuracy of the system was evaluated with a real-time MRI-guided phantom study, demonstrating the mean absolute errors (MAE) of the tip position to be 1.50±0.68mm and of the needle angle to be 1.56±0.93°. An initial cadaver study was performed to validate the feasibility of the clinical workflow, indicating the maximum error of the position to be less than 1.90mm and of the angle to be less than 3.14°.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Guideline Idioma: En Revista: IEEE Robot Autom Lett Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Guideline Idioma: En Revista: IEEE Robot Autom Lett Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos