Evidence map›Paper›PMID 30341371›Full record

ArticleScientific reports2018

Photoacoustic-based visual servoing of a needle tip.

Muyinatu A Lediju Bell, Joshua Shubert

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
3.9field-weighted citation impact, top 6% 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

30 citing papers in PubMed, 70 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Shortcut learning leads to sex bias in deep learning models for photoacoustic tomography.International journal of computer assisted radiology and surgery · 2025
    Article
  7. Deep Learning to Localize Photoacoustic Sources in Three Dimensions: Theory and Implementation.IEEE transactions on ultrasonics, ferroelectrics, and frequency control · 2025
    Article
  8. MixTURE: L1-Norm-Based Mixed Second-Order Continuity in Strain Tensor Ultrasound Elastography.IEEE transactions on ultrasonics, ferroelectrics, and frequency control · 2024
    Article
  9. Deep learningJournal of biomedical optics · 2024
    Article
  10. Article
  11. Optical absorption spectra and correspondingJournal of biomedical optics · 2023
    Article
  12. Article
  13. Review
  14. Article
  15. Review
  16. Article
  17. Article
  18. Recent advances in aggregation-induced emission luminogens in photoacoustic imaging.European journal of nuclear medicine and molecular imaging · 2022
    Review
  19. CuInSAdvanced materials interfaces · 2021
    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

2 authors at 1 institution in 1 country.

Muyinatu A Lediju BellJohns Hopkins University, Department of Electrical and Computer Engineering, Baltimore, MD, 21218, USA. mledijubell@jhu.edu.ORCID http://orcid.org/0000-0002-8394-4482
Joshua ShubertJohns Hopkins University, Department of Electrical and Computer Engineering, Baltimore, MD, 21218, USA.
Johns Hopkins University · US

Funding

Coherence-Based Photoacoustic Image Guidance of Transsphenoidal SurgeriesR00EB018994 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI BELL, MUYINATU A. LEDIJU · 2017 to 2019
$726k
National Science Foundation ECCS 1751522NIBIB NIH HHS R00 EB018994
6 · The paper itself

Abstract

In intraoperative settings, the presence of acoustic clutter and reflection artifacts from metallic surgical tools often reduces the effectiveness of ultrasound imaging and complicates the localization of surgical tool tips. We propose an alternative approach for tool tracking and navigation in these challenging acoustic environments by augmenting ultrasound systems with a light source (to perform photoacoustic imaging) and a robot (to autonomously and robustly follow a surgical tool regardless of the tissue medium). The robotically controlled ultrasound probe continuously visualizes the location of the tool tip by segmenting and tracking photoacoustic signals generated from an optical fiber inside the tool. System validation in the presence of fat, muscle, brain, skull, and liver tissue with and without the presence of an additional clutter layer resulted in mean signal tracking errors <2 mm, mean probe centering errors <1 mm, and successful recovery from ultrasound perturbations, representing either patient motion or switching from photoacoustic images to ultrasound images to search for a target of interest. A detailed analysis of channel SNR in controlled experiments with and without significant acoustic clutter revealed that the detection of a needle tip is possible with photoacoustic imaging, particularly in cases where ultrasound imaging traditionally fails. Results show promise for guiding surgeries and procedures in acoustically challenging environments with this novel robotic and photoacoustic system combination.

Indexed as

LightAdipose TissueAlgorithmsAnimalsCattleChickensImage Processing, Computer-AssistedMusclesNeedlesOptical FibersPhotoacoustic TechniquesRoboticsSpectrum AnalysisSurgery, Computer-AssistedUltrasonography, Interventional

Identifiers

PMID30341371
PMCPMC6195562
OpenAlexW2897110362

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.