Evidence map›Paper›PMID 29466904›Full record

ArticleInterventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences2018

Effect of metal artifact reduction software on image quality of C-arm cone-beam computed tomography during intracranial aneurysm treatment.

Yukiko Enomoto, Keita Yamauchi, Takahiko Asano, Katharina Otani, Toru Iwama

Abstract read
In one paragraph

Article in Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-weighted citation impact, top 34% 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

5 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. BioMed research international · 2022
    Article
  3. Article
  4. Comparison of quantitative measurements of four manufacturer's metal artifact reduction techniques for CT imaging with a self-made acrylic phantom.Technology and health care : official journal of the European Society for Engineering and Medicine · 2020
    Article
  5. 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

5 authors at 1 institution in 1 country.

Yukiko Enomoto1 Department of Neurosurgery, Graduate School of Medicine, Gifu University, Gifu, Japan.
Keita Yamauchi1 Department of Neurosurgery, Graduate School of Medicine, Gifu University, Gifu, Japan.
Takahiko Asano2 Department of Radiology, Graduate School of Medicine, Gifu University, Gifu, Japan.
Katharina Otani3 AT Innovation Department, Siemens Healthcare K.K., Tokyo, Japan.
Toru Iwama1 Department of Neurosurgery, Graduate School of Medicine, Gifu University, Gifu, Japan.
Gifu University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and purpose C-arm cone-beam computed tomography (CBCT) has the drawback that image quality is degraded by artifacts caused by implanted metal objects. We evaluated whether metal artifact reduction (MAR) prototype software can improve the subjective image quality of CBCT images of patients with intracranial aneurysms treated with coils or clips. Materials and methods Forty-four patients with intracranial aneurysms implanted with coils (40 patients) or clips (four patients) underwent one CBCT scan from which uncorrected and MAR-corrected CBCT image datasets were reconstructed. Three blinded readers evaluated the image quality of the image sets using a four-point scale (1: Excellent, 2: Good, 3: Poor, 4: Bad). The median scores of the three readers of uncorrected and MAR-corrected images were compared with the paired Wilcoxon signed-rank and inter-reader agreement of change scores was assessed by weighted kappa statistics. The readers also recorded new clinical findings, such as intracranial hemorrhage, air, or surrounding anatomical structures on MAR-corrected images. Results The image quality of MAR-corrected CBCT images was significantly improved compared with the uncorrected CBCT image ( p < 0.001). Additional clinical findings were seen on CBCT images of 70.4% of patients after MAR correction. Conclusion MAR software improved image quality of CBCT images degraded by metal artifacts.

Indexed as

ArtifactsProstheses and ImplantsSoftwareAgedAlgorithmsCone-Beam Computed TomographyEmbolization, TherapeuticFemaleHumansIntracranial AneurysmMaleMetalsRadiographic Image Interpretation, Computer-AssistedMetalscerebral aneurysmCone-beam computed tomographyendovascular treatment

Identifiers

PMID29466904
PMCPMC5967185
OpenAlexW2788845388

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.