Comparative Evaluation of Temporomandibular Condylar Changes Using Texture Analysis of CT and MRI Images
This study aims to compare computed tomography (CT) with magnetic resonance imaging (MRI) of the temporomandibular joint (TMJ) by using texture analysis (TA) to detect condylar bone marrow changes associated with the flattening and erosion of cortical bone. A total of 47 patients from the Dentomaxillofacial Radiology Division at São Paulo State University were evaluated. Images from 250 CT and 250 MRI images were assessed by experienced radiologists employing OnDemand3D software. Texture parameters were extracted with MaZda software (version 4.6), and we focused on regions of interest within the condyles. Statistical analysis revealed significant differences in texture parameters between the affected and control groups. CT images showed higher correlation values in cases of flattening, whereas MRI images demonstrated substantial changes in texture parameters for both flattening and erosion. These findings suggest that the texture analysis of CT and MRI images can effectively detect early and advanced degenerative changes in the TMJ, thus providing valuable insights into the underlying pathophysiology and aiding in early intervention and treatment planning.
Authors
- Kaan Orhan (ORCID: https://orcid.org/0000-0001-6768-0176)
- André Luiz Ferreira Costa (ORCID: https://orcid.org/0000-0003-4856-5417)
- Diana Lorena Garcia Lopes (ORCID: https://orcid.org/0000-0002-5646-0992)
- Sérgio Lúcio Pereira de Castro Lopes (ORCID: https://orcid.org/0000-0002-0882-5862)
- Adriana Ortega (ORCID: https://orcid.org/0000-0001-7295-803X)
- Celso Massahiro Ogawa (ORCID: https://orcid.org/0000-0002-5010-5674)
- Everton Flaiban (ORCID: https://orcid.org/0000-0002-0040-7834)
- Ana Lúcia Franco Ricardo (ORCID: https://orcid.org/0000-0001-5475-1596)
- Bruna Maciel de Almeida
- Lays Assolini Pinheiro de Oliveira (ORCID: https://orcid.org/0000-0002-0649-0069)
Institutions
- Ankara University (TR)
- Centro Universitário Católico do Sudoeste do Paraná (BR)
- Universidade Cruzeiro do Sul (BR)
- Universidade Estadual Paulista (Unesp) (BR)
Publication Details
- Journal
- Applied Sciences
- Published
- 2024-08-10
- DOI
- https://doi.org/10.3390/app14167020
- Citations
- 3
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.21