Evidence map›Paper›PMID 28652857›Full record

ArticleIEEE sensors journal2017

Fiber Optic Force Sensors for MRI-Guided Interventions and Rehabilitation: A Review.

Hao Su, Iulian I Iordachita, Junichi Tokuda, Nobuhiko Hata, Xuan Liu, Reza Seifabadi, Sheng Xu, Bradford Wood, Gregory S Fischer

Open access · greenAbstract read
In one paragraph

Article in IEEE sensors journal, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
2.9field-weighted citation impact, top 9% 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

21 citing papers in PubMed, 1 synthesis or guideline pooled it, 84 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Portable and Versatile Catheter Robot for Image-Guided Cardiovascular Interventions.IEEE/ASME transactions on mechatronics : a joint publication of the IEEE Industrial Electronics Society and the ASME Dynamic Systems and Control Division · 2025
    Article
  9. Article
  10. Review
  11. A Review of Recent Advancements in Sensor-Integrated Medical Tools.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Review
  12. Article
  13. Article
  14. State of the Art and Future Opportunities in MRI-Guided Robot-Assisted Surgery and Interventions.Proceedings of the IEEE. Institute of Electrical and Electronics Engineers · 2022
    Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Article
  20. 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

9 authors at 6 institutions in 1 country.

Hao SuWyss Institute for Biologically Inspired Engineering and the John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA.
Iulian I IordachitaJohns Hopkins University, Baltimore MD, 21218, USA.
Junichi TokudaNational Center for Image Guided Therapy (NCIGT), Brigham and Women's Hospital, Department of Radiology, Harvard Medical School, Boston, MA, 02115 USA.
Nobuhiko HataNational Center for Image Guided Therapy (NCIGT), Brigham and Women's Hospital, Department of Radiology, Harvard Medical School, Boston, MA, 02115 USA.
Xuan LiuNew Jersey Institute of Technology, Newark, NJ 07103, USA.
Reza SeifabadiCenter for Interventional Oncology, Radiology and Imaging Sciences, National Institutes of Health, Bethesda, MD, 20892, USA.
Sheng XuCenter for Interventional Oncology, Radiology and Imaging Sciences, National Institutes of Health, Bethesda, MD, 20892, USA.
Bradford WoodCenter for Interventional Oncology, Radiology and Imaging Sciences, National Institutes of Health, Bethesda, MD, 20892, USA.
Gregory S FischerAutomation and Interventional Medicine (AIM) Robotics Laboratory, Department of Mechanical Engineering, Worcester Polytechnic Institute, 100 Institute Road, Worcester, MA 01609, USA.
National Institutes of Health Clinical Center · USBrigham and Women's Hospital · USHarvard University · USJohns Hopkins University · USNew Jersey Institute of Technology · USWorcester Polytechnic Institute · US

Funding

Center for Interventional OncologyZIDBC011242 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI WOOD, BRADFORD J · 2009 to 2025
$18.7M
Enabling Technologies for MRI-Guided Prostate InterventionsR01CA111288 · NCI · BRIGHAM AND WOMEN'S HOSPITAL · PI TEMPANY, CLARE M · 2006 to 2015
$7.8M
MR-Guided Precision Conformal Ablation Therapy for Brain TumorsR01CA166379 · NCI · WORCESTER POLYTECHNIC INSTITUTE · PI FISCHER, GREGORY S, PILITSIS, JULIE GEORGIA · 2013 to 2022
$6.5M
Navigation Tools for Image Guided Minimally invasive TherapiesZIACL040011 · CLC · CLINICAL CENTER · PI WOOD, BRADFORD · 2009 to 2025
$0k
Interventional OncologyZIACL040015 · CLC · CLINICAL CENTER · PI WOOD, BRADFORD · 2009 to 2025
$0k
NCI NIH HHS R01 CA111288NCI NIH HHS R01 CA166379
6 · The paper itself

Abstract

Magnetic Resonance Imaging (MRI) provides both anatomical imaging with excellent soft tissue contrast and functional MRI imaging (fMRI) of physiological parameters. The last two decades have witnessed the manifestation of increased interest in MRI-guided minimally invasive intervention procedures and fMRI for rehabilitation and neuroscience research. Accompanying the aspiration to utilize MRI to provide imaging feedback during interventions and brain activity for neuroscience study, there is an accumulated effort to utilize force sensors compatible with the MRI environment to meet the growing demand of these procedures, with the goal of enhanced interventional safety and accuracy, improved efficacy and rehabilitation outcome. This paper summarizes the fundamental principles, the state of the art development and challenges of fiber optic force sensors for MRI-guided interventions and rehabilitation. It provides an overview of MRI-compatible fiber optic force sensors based on different sensing principles, including light intensity modulation, wavelength modulation, and phase modulation. Extensive design prototypes are reviewed to illustrate the detailed implementation of these principles. Advantages and disadvantages of the sensor designs are compared and analyzed. A perspective on the future development of fiber optic sensors is also presented which may have additional broad clinical applications. Future surgical interventions or rehabilitation will rely on intelligent force sensors to provide situational awareness to augment or complement human perception in these procedures.

Indexed as

Fabry-Perot interferometer (FPI)fiber Bragg grating (FBG)Fiber optic sensorhapticsimage-guided interventionsMRI compatible robotneurosciencepercutaneous interventionsrehabilitation

Identifiers

PMID28652857
PMCPMC5482288
OpenAlexW2577566293

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.