Evidence map›Paper›PMID 22933973›Full record

ArticleRadiology and oncology2012

Human tooth pulp anatomy visualization by 3D magnetic resonance microscopy.

Dusan Sustercic, Igor Sersa

Open access · goldAbstract read
In one paragraph

Article in Radiology and oncology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.5field-weighted citation impact, top 17% 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

6 citing papers in PubMed, 20 citations in OpenAlex.

  1. Magnetic Resonance Imaging for Dental Pulp Assessment: A Comprehensive Review.Journal of magnetic resonance imaging : JMRI · 2025
    Review
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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 2 institutions in 1 country.

Dusan SustercicDepartment of Prosthodontics, Medical Faculty, University of Ljubljana, Ljubljana, Slovenia.
Igor Sersa
EN-FIST Centre of Excellence (Slovenia) · SIUniversity of Ljubljana · SI

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPrecise assessment of dental pulp anatomy is of an extreme importance for a successful endodontic treatment. As standard radiographs of teeth provide very limited information on dental pulp anatomy, more capable methods are highly appreciated. One of these is 3D magnetic resonance (MR) microscopy of which diagnostic capabilities in terms of a better dental pulp anatomy assessment were evaluated in the study. MATERIALS AND

methodsTwenty extracted human teeth were scanned on a 2.35 T MRI system for MR microscopy using the 3D spin-echo method that enabled image acquisition with isotropic resolution of 100 μm. The 3D images were then post processed by ImageJ program (NIH) to obtain advanced volume rendered views of dental pulps.

resultsMR microscopy at 2.35 T provided accurate data on dental pulp anatomy in vitro. The data were presented as a sequence of thin 2D slices through the pulp in various orientations or as volume rendered 3D images reconstructed form arbitrary view-points. Sequential 2D images enabled only an approximate assessment of the pulp, while volume rendered 3D images were more precise in visualization of pulp anatomy and clearly showed pulp diverticles, number of pulp canals and root canal anastomosis.

conclusionsThis in vitro study demonstrated that MR microscopy could provide very accurate 3D visualization of dental pulp anatomy. A possible future application of the method in vivo may be of a great importance for the endodontic treatment.

Indexed as

3D visualizationdental pulp anatomyendodontic treatmentMR microscopy

Identifiers

PMID22933973
PMCPMC3423768
OpenAlexW2141433718

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.