ArticleOral radiology2023
Magnetic resonance imaging texture analysis for quantitative evaluation of the mandibular condyle in juvenile idiopathic arthritis.
Article in Oral radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Radiomics-Based Diagnosis in Dentomaxillofacial Radiology: A Systematic Review.Journal of imaging informatics in medicine · 2025Pooled it
- Radiographic texture analysis of the hard tissue changes following socket preservation with allograft and xenograft materials for dental implantation: a randomized clinical trial.Oral and maxillofacial surgery · 2024Trial
- Quantitative Imaging of the Mandibular Condyle: Radiomics and Microarchitectural Biomarkers.Medical principles and practice : international journal of the Kuwait University, Health Science Centre · 2026Review
- Integrating deep learning and machine learning for improved CKD-related cortical bone assessment in HRpQCT images: A pilot study.Bone reports · 2025Article
- Differentiation of Early Sacroiliitis Using Machine-Learning- Supported Texture Analysis.Diagnostics (Basel, Switzerland) · 2025Article
- Differential diagnosis of cemento-osseous dysplasia and periapical cyst using texture analysis of CBCT.BMC oral health · 2024Article
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesJuvenile idiopathic arthritis (JIA) is a chronic inflammatory disease that affects the joints and other organs, including the development of the former in a growing child. This study aimed to evaluate the feasibility of texture analysis (TA) based on magnetic resonance imaging (MRI) to provide biomarkers that serve to identify patients likely to progress to temporomandibular joint damage by associating JIA with age, gender and disease onset age.
methodsThe radiological database was retrospectively reviewed. A total of 45 patients were first divided into control group (23) and JIA group (22). TA was performed using grey-level co-occurrence matrix (GLCM) parameters, in which 11 textural parameters were calculated using MaZda software. These 11 parameters were ranked based on the p value obtained with ANOVA and then correlated with age, gender and disease onset age.
resultsSignificant differences in texture parameters of condyle were demonstrated between JIA group and control group (p < 0.05). There was a progressive loss of uniformity in the grayscale pixels of MRI with an increasing age in JIA group.
conclusionsMRI TA of the condyle can make it possible to detect the alterations in bone marrow of patients with JIA and promising tool which may help the image analysis.
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Registered trials
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