Evidence map›Paper›PMID 39057007›Full record

ArticleDentistry journal2024

Assessing the Volume of the Head of the Mandibular Condyle Using 3T-MRI-A Preliminary Trial.

Alessandro Mosca Balma, Davide Cavagnetto, Lorenzo Pavone, Federico Mussano

Abstract read
In one paragraph

Article in Dentistry journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Alessandro Mosca BalmaBone and Dental Bioengineering Laboratory, CIR Dental School, Department of Surgical Sciences, University of Turin, Via Nizza 230, 10126 Turin, Italy.ORCID 0000-0002-8095-2524
Davide CavagnettoBone and Dental Bioengineering Laboratory, CIR Dental School, Department of Surgical Sciences, University of Turin, Via Nizza 230, 10126 Turin, Italy.ORCID 0000-0001-8573-8327
Lorenzo PavoneBone and Dental Bioengineering Laboratory, CIR Dental School, Department of Surgical Sciences, University of Turin, Via Nizza 230, 10126 Turin, Italy.ORCID 0009-0009-3885-7142
Federico MussanoBone and Dental Bioengineering Laboratory, CIR Dental School, Department of Surgical Sciences, University of Turin, Via Nizza 230, 10126 Turin, Italy.ORCID 0000-0001-5800-0749

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Due to potentially harmful exposure to X-rays, condylar growth in response to orthodontic treatment is poorly studied. To overcome this limitation, here, the authors have proposed high-resolution MRI as a viable alternative to CBCT for clinical 3D assessment of TMJ. A male subject underwent both MRI and CBCT scans. The obtained three-dimensional reconstructions of the TMJ were segmented and superimposed by a semiautomatic algorithm developed in MATLAB R2022a. The condylar geometries were reconstructed using dedicated software for image segmentation. Two geometrical parameters, i.e., the total volume and surface of the single condyle model, were selected to quantify the intraclass and interclass variability from the mean of each DICOM series (CBCT and MRI). The final comparison between the reference standard model of CBCT and 3T MRI showed that the former was more robust in terms of reproducibility, while the latter reached a higher standard deviation compared to CBCT, but these values were similar between the operators and clinically not significant. Within the inherent limitation of image reconstruction on MRI scans due to the current lower resolution of this technique, the method proposed here could be considered as a nucleus for developing future completely automatic AI algorithms, owing to its great potential and satisfactory consistency among different times and operators.

Indexed as

cone beam computed tomographydigital dentistrymagnetic resonance imagingorthodonticssemiautomatic volumetric segmentationthree-dimensional imaging

Identifiers

PMID39057007
PMCPMC11276145

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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.