Evidence map›Paper›PMID 41366410›Full record

ArticleBMC medical education2025

Fabrication and evaluation of a novel patient-specific 3D-printed simulation model for oral surgical training.

Leila Gholami, Edward Putnins, HsingChi von Bergmann, Arvin Bagheri, Rana Tarzemany

Abstract read
In one paragraph

Article in BMC medical education, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

5 authors.

Leila GholamiDepartment of Oral Biological and Medical Sciences, Faculty of Dentistry, The University of British Columbia, Vancouver, BC, Canada.
Edward PutninsDepartment of Oral Biological and Medical Sciences, Faculty of Dentistry, The University of British Columbia, Vancouver, BC, Canada.
HsingChi von BergmannDepartment of Oral Health Sciences, Faculty of Dentistry, The University of British Columbia, Vancouver, BC, Canada.
Arvin BagheriNobel BioCare Oral Health Centre, Faculty of Dentistry, The University of British Columbia, Vancouver, BC, Canada.
Rana TarzemanyDepartment of Oral Biological and Medical Sciences, Faculty of Dentistry, The University of British Columbia, Vancouver, BC, Canada. Rana.tarzemany@ubc.ca.ORCID http://orcid.org/0009-0000-4259-2583

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUse of patient-specific models as a surgical planning and training tool can support novice practitioners' surgical skill development. This study aimed to introduce a novel workflow for fabricating 3D-printed, patient-specific simulation models and evaluate their accuracy and transferability for use in periodontal and oral surgery training.

methodsPatient-specific anatomical models of the maxilla were fabricated using the CBCT and intraoral scan data. The proposed workflow outlines a novel process for creating a patient-specific model that accurately replicates both the hard and soft tissues of the patient. The accuracy of the printed models was evaluated by scanning five models and comparing them to the patient's intraoral scan using cloud-to-cloud distance analysis. Then, in an exploratory study design, a simulated gingival flap surgery exercise was completed by 18 periodontists and 50 students. The face and content validity of the model were assessed using an 8-item online questionnaire with a VAS of 0-100 and a free comment question. The data were analyzed using descriptive statistics, Mann-Whitney U tests and independent t-test.

resultsThe printed model demonstrated high dimensional accuracy. The overall VAS score of the model was significantly higher for students than for periodontists (83.7 ± 9.7 vs. 72.1 ± 15.8, p < 0.006). The face and content validity scores reported by students were also higher (P < 0.01), with mean differences of 8.86% and 12.62%, respectively. Periodontists rated the models lower for soft-tissue tactile feedback, particularly during incision.

conclusionsThe proposed 3D-printed simulation workflow produced an accurate and educationally valuable model with the potential to enhance surgical training. Experienced surgeons suggested that refining the soft-tissue realism could further improve its overall educational value.

Indexed as

Models, AnatomicOral Surgical ProceduresPeriodonticsPrinting, Three-DimensionalSimulation TrainingSurgery, OralClinical CompetenceCone-Beam Computed TomographyFemaleHumansMaleMaxilla3D printingDental educationFlap reflectionModel fabricationOral surgerySimulation

Identifiers

PMID41366410
PMCPMC12801927

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Registered trials

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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.