Evidence map›Paper›PMID 40212788›Full record

ReviewThe Japanese dental science review2025

Nanoidentification in endodontics: Bibliometric analysis and comprehensive review on the basis of characterisation research by Nano-computed tomography imaging.

Olcay Özdemir, Sena Kaşıkçı, Turkan Kopac

Abstract readReview
In one paragraph

Review in The Japanese dental science review, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Review
  2. 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

3 authors.

Olcay ÖzdemirDepartment of Endodontics, Faculty of Dentistry, Karabük University, Karabük, Türkiye.
Sena KaşıkçıDepartment of Endodontics, Faculty of Dentistry, Kocaeli University, Kocaeli, Türkiye.
Turkan KopacDepartment of Chemistry, Zonguldak Bülent Ecevit University, Zonguldak, Türkiye.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nanoimaging, crucial in endodontics, has advanced, leading to more effective and less invasive treatments. Nano-computed tomography (nano-CT) is an advanced imaging technique to evaluate bone structures or gaps in filling materials, providing submicrometer spatial resolution due to smaller focal points and voxels, higher signal-to-noise ratios, and higher tube voltages and powers compared to conventional devices, improving dental imaging precision and safety by producing detailed images with minimal radiation exposure. This study conducted a bibliometric analysis on nano-CT imaging as a nano identification tool in endodontics. Using various tools and methods, it evaluated progress and trends in nano-CT, aiming to enhance understanding of bibliometric data and complement existing endodontic knowledge. Nano-CT imaging has gained prominence in endodontics research, offering potential applications and insights into various aspects of the field. A review of relevant studies highlighted the technique's ability to visualize dentin tubules, root canal anatomy, filling quality, root resorption, cracks, microcracks, soft dental tissues, cellular layers, volumetric changes post-instrumentation, hard tissue debris, root surface deposits, and bioceramic pore structures. Nano-CT has the potential to become the gold standard for imaging in endodontics, presenting opportunities and challenges for future research. These findings provide researchers and practitioners with the latest advancements in nanoimaging.

Indexed as

Advanced imagingBibliometricsEndodonticsNano-computed tomographyNano-CT

Identifiers

PMID40212788
PMCPMC11984532

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.