Evidence map›Paper›PMID 31131290›Full record

ArticleJournal of medical imaging (Bellingham, Wash.)2019

Preclinical evaluation of an integrated robotic system for magnetic resonance imaging guided shoulder arthrography.

Niravkumar Patel, Jiawen Yan, Reza Monfaredi, Karun Sharma, Kevin Cleary, Iulian Iordachita

Open access · greenAbstract read
In one paragraph

Article in Journal of medical imaging (Bellingham, Wash.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.9field-weighted citation impact, top 28% 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

7 citing papers in PubMed, 14 citations in OpenAlex.

  1. Current State of Robotics in Interventional Radiology.Cardiovascular and interventional radiology · 2023
    Review
  2. Open Source MR-Safe Pneumatic Radial Inflow Motor and Encoder (PRIME): Design and Manufacturing Guidelines.... International Symposium on Medical Robotics. International Symposium on Medical Robotics · 2023
    Article
  3. Simple methods to test the accuracy of MRgFUS robotic systems.The international journal of medical robotics + computer assisted surgery : MRCAS · 2021
    Article
  4. Article
  5. Body-Mounted Robotics for Interventional MRI Procedures.IEEE transactions on medical robotics and bionics · 2020
    Article
  6. Body-mounted robotic assistant for MRI-guided low back pain injection.International journal of computer assisted radiology and surgery · 2020
    Article
  7. A Fully Actuated Body-Mounted Robotic Assistant for MRI-Guided Low Back Pain Injection.IEEE International Conference on Robotics and Automation : ICRA : [proceedings]. IEEE International Conference on Robotics and Automation
    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

6 authors at 2 institutions in 1 country.

Niravkumar PatelJohns Hopkins University, Laboratory for Computational Sensing and Robotics, Baltimore, Maryland, United States.ORCID https://orcid.org/0000-0002-8113-6078
Jiawen YanJohns Hopkins University, Laboratory for Computational Sensing and Robotics, Baltimore, Maryland, United States.
Reza MonfarediChildren's National Medical Center, Washington, DC, United States.
Karun SharmaChildren's National Medical Center, Washington, DC, United States.
Kevin ClearyChildren's National Medical Center, Washington, DC, United States.
Iulian IordachitaJohns Hopkins University, Laboratory for Computational Sensing and Robotics, Baltimore, Maryland, United States.
Children's National · USJohns Hopkins University · US

Funding

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 EB020003
6 · The paper itself

Abstract

Shoulder arthrography is a diagnostic procedure which involves injecting a contrast agent into the joint space for enhanced visualization of anatomical structures. Typically, a contrast agent is injected under fluoroscopy or computed tomography (CT) guidance, resulting in exposure to ionizing radiation, which should be avoided especially in pediatric patients. The patient then waits for the next available magnetic resonance imaging (MRI) slot for obtaining high-resolution anatomical images for diagnosis, which can result in long procedure times. Performing the contrast agent injection under MRI guidance could overcome both these issues. However, it comes with the challenges of the MRI environment including high magnetic field strength, limited ergonomic patient access, and lack of real-time needle guidance. We present the development of an integrated robotic system to perform shoulder arthrography procedures under intraoperative MRI guidance, eliminating fluoroscopy/CT guidance and patient transportation from the fluoroscopy/CT room to the MRI suite. The average accuracy of the robotic manipulator in benchtop experiments is 0.90 mm and 1.04 deg, whereas the average accuracy of the integrated system in MRI phantom experiments is 1.92 mm and 1.28 deg at the needle tip. Based on the American Society for Testing and Materials (ASTM) tests performed, the system is classified as MR conditional.

Indexed as

image-guidedmagnetic resonance imagingrobotshoulder arthrography

Identifiers

PMID31131290
PMCPMC6519665
OpenAlexW2945375044

What OpenQuestion holds

Textmetadata
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.