ArticleBMC oral health2025
Three-dimensional partitioning and quantification of orthodontic root resorption via automatic root extraction from cone-beam computed tomography.
Article in BMC oral health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Comparison of external apical root resorption in maxillary anterior teeth following en-masse versus two-step retraction: a 3D volumetric CBCT-based randomized controlled trial.Clinical oral investigations · 2026Trial
- Comprehensive three-dimensional analysis of alveolar bone adaptation and root resorption following premolar extraction in Class II malocclusion: a cohort study.Progress in orthodontics · 2026Article
- Automated deep learning detection of orthodontically induced external apical root resorption in maxillary incisors on panoramic radiographs.Progress in orthodontics · 2026Article
- Artificial Intelligence Models for the Detection and Quantification of Orthodontically Induced Root Resorption Using Cone-Beam Computed Tomography: A Systematic Review and Meta-Analysis.Dentistry journal · 2026Review
- AI for diagnosing malocclusions from 3D dental models.Bioinformation · 2025Article
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Authors and funding
5 authors.
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Abstract
backgroundExternal root resorption (ERR) during orthodontic treatment is a common concern, and accurate quantification is crucial for assessing outcomes and minimizing long-term complications. This study aims to quantify ERR using automated root extraction from cone beam computed tomography (CBCT), combined with a novel root partitioning method and enhanced through the integration of intraoral scans for improved accuracy.
methodsThirty-six patients with malocclusion were included and divided into two groups. Root extraction was performed on CBCT images using artificial intelligence (AI), Simultaneously, crown data from intraoral scans were integrated to create composite dental models in Geomagic software. Pre- and post-treatment models were aligned based on crowns. A novel partitioning method was then used to analyze root volume changes in three dimensions. Finally, these changes were analyzed according to age, tooth region, and extraction treatment using SPSS software.
resultsA statistically significant reduction in root volume was observed post-treatment in both groups (P < 0.001). Anterior teeth exhibited greater ERR, especially in the upper anterior teeth of Group II (extraction treatment, P < 0.05). Posterior maxillary teeth in Group I showed less ERR (P < 0.05). ERR was more pronounced in the apical third of the root (P < 0.001). Group II experienced greater overall ERR, particularly in the apical third, whereas Group I showed more ERR at the cervical third (P < 0.05).
conclusionThis 3D quantification method provides a novel assessment of ERR, with distribution influenced by age, tooth position, extraction treatment, and root region.
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