Evidence map›Paper›PMID 41651985›Full record

ArticleScientific reports2026

Algorithmic analysis of the structure of mixed odontogenic tumors.

Vanesa Pereira-Prado, Estefanía Sicco, Felipe Martins Silveira, Lauren Frenzel Schuch, Keith Hunter, Sven Eric Niklander, Wanninayake Mudiyanselage Tilakaratne, Ricardo Santiago Gomez, Gabriel Landini, Ronell Bologna-Molina

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Article in Scientific reports, 2026. 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

10 authors.

Vanesa Pereira-PradoMolecular Pathology Area, Department of Diagnostics in Pathology and Oral Medicine, School of Dentistry, Universidad de la República, Las Heras 1925, CP 11600, Montevideo, Uruguay.ORCID http://orcid.org/0000-0001-7747-6718
Estefanía SiccoMolecular Pathology Area, Department of Diagnostics in Pathology and Oral Medicine, School of Dentistry, Universidad de la República, Las Heras 1925, CP 11600, Montevideo, Uruguay.ORCID http://orcid.org/0000-0003-1137-6866
Felipe Martins SilveiraMolecular Pathology Area, Department of Diagnostics in Pathology and Oral Medicine, School of Dentistry, Universidad de la República, Las Heras 1925, CP 11600, Montevideo, Uruguay.ORCID http://orcid.org/0000-0001-9834-5194
Lauren Frenzel SchuchMolecular Pathology Area, Department of Diagnostics in Pathology and Oral Medicine, School of Dentistry, Universidad de la República, Las Heras 1925, CP 11600, Montevideo, Uruguay.ORCID http://orcid.org/0000-0002-0993-936X
Keith HunterLiverpool Head and Neck Centre, Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool, UK.ORCID http://orcid.org/0000-0002-7873-0877
Sven Eric NiklanderUnidad de Patología y Medicina Oral, Facultad de Odontología, Universidad Andres Bello, Viña del Mar, Chile.ORCID http://orcid.org/0000-0003-1858-3091
Wanninayake Mudiyanselage TilakaratneDepartment of Oral and Maxillofacial Clinical Sciences, Faculty of Dentistry, Universiti Malaya, Kuala Lumpur, Malaysia.ORCID http://orcid.org/0000-0002-7061-7378
Ricardo Santiago GomezDepartment of Oral Surgery and Pathology, School of Dentistry, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.ORCID http://orcid.org/0000-0001-8770-8009
Gabriel LandiniMolecular Pathology Area, Department of Diagnostics in Pathology and Oral Medicine, School of Dentistry, Universidad de la República, Las Heras 1925, CP 11600, Montevideo, Uruguay.ORCID http://orcid.org/0000-0002-9689-0989
Ronell Bologna-MolinaMolecular Pathology Area, Department of Diagnostics in Pathology and Oral Medicine, School of Dentistry, Universidad de la República, Las Heras 1925, CP 11600, Montevideo, Uruguay. ronellbologna@hotmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aims to characterize the histomorphology of mixed odontogenic tumors, using mathematical morphology algorithms applied to digital images. Five cases of primordial odontogenic tumor (POT), 5 cases of ameloblastic fibroma, 5 cases of developing odontoma (DO), and 5 cases of tooth germs (TG) were analyzed. Histological sections stained with Haematoxylin & Eosin were digitized and the epithelial compartments were segmented into ‘virtual cells’ to further characterize the tissue compartment architecture. A comparison of the mean area of virtual epithelial cells in the entities investigated showed that, despite data distribution between the entities being similar, statistically significant differences (p < 0.001) were found, being larger for DO and smaller for AF. Additionally, DO exhibits a broader data distribution of the area compared to the other entities. Significant differences were not found between TG and POT without subepithelial condensation. Quantitative tissue analysis showed that, in focal areas, POT more closely resembles TG than other mixed odontogenic tumors. These findings suggest that virtual cell–based morphometric analysis may provide complementary quantitative information in diagnostically challenging cases, although validation in larger datasets is required.

Indexed as

AlgorithmsOdontogenic TumorsOdontomaHumansImage Processing, Computer-AssistedTooth GermAlgorithmic analysisAmeloblastic fibromaMixed odontogenic tumorsPrimordial odontogenic tumorTooth germ

Identifiers

PMID41651985
PMCPMC12932855

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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.