Evidence map›Paper›PMID 33778433›Full record

ArticleIEEE transactions on medical robotics and bionics2020

Body-Mounted Robotics for Interventional MRI Procedures.

Gang Li, Niravkumar A Patel, Karun Sharma, Reza Monfaredi, Charles Dumoulin, Jan Fritz, Iulian Iordachita, Kevin Cleary

Open access · greenAbstract read
In one paragraph

Article in IEEE transactions on medical robotics and bionics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.5field-weighted citation impact, top 38% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 8 citations in OpenAlex.

  1. A Pneumatically Actuated Robotic Assistant for MRI-Guided Stereotactic Neurosurgery.IEEE transactions on medical robotics and bionics · 2026
    Article
  2. A magnetic resonance conditional robot for lumbar spinal injection: Development and preliminary validation.The international journal of medical robotics + computer assisted surgery : MRCAS · 2024
    Article
  3. Review
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 1 country.

Gang LiLaboratory for Computational Sensing and Robotics (LCSR), Johns Hopkins University, Baltimore, MD, USA.
Niravkumar A PatelLaboratory for Computational Sensing and Robotics (LCSR), Johns Hopkins University, Baltimore, MD, USA.
Karun SharmaSheikh Zayed Institute for Pediatric Surgical Innovation, Childrens National Hospital, Washington, DC, USA.
Reza MonfarediSheikh Zayed Institute for Pediatric Surgical Innovation, Childrens National Hospital, Washington, DC, USA.
Charles DumoulinCincinnati Childrens Hospital Medical Center, Cincinnati, OH, USA.
Jan FritzNew York University, New York, NY, USA.
Iulian IordachitaLaboratory for Computational Sensing and Robotics (LCSR), Johns Hopkins University, Baltimore, MD, USA.
Kevin ClearySheikh Zayed Institute for Pediatric Surgical Innovation, Childrens National Hospital, Washington, DC, USA.
Johns Hopkins University · USCincinnati Children's Hospital Medical Center · USNew York University · US

Funding

MRI Compatible Robot for Improved Pain Injections in Adults and ChildrenR01EB025179 · NIBIB · CHILDREN'S RESEARCH INSTITUTE · PI CLEARY, KEVIN R. · 2018 to 2021
$2.8M
MRI Compatible Body-Mounted Robot to Streamline Pediatric Shoulder ArthrographyR01EB020003 · NIBIB · CHILDREN'S RESEARCH INSTITUTE · PI CLEARY, KEVIN R. · 2016 to 2019
$2.0M
NIBIB NIH HHS R01 EB020003NIBIB NIH HHS R01 EB025179
6 · The paper itself

Abstract

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.

Indexed as

arthrographybody-mounted robotchronic pain managementMRI-guided interventionmusculoskeletal procedure

Identifiers

PMID33778433
PMCPMC7996400
OpenAlexW3109663244

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.