Publications
2024
Barone, Selene; Cevidanes, Lucia; Bianchi, Jonas; Goncalves, Joao Roberto; Giudice, Amerigo
In: Orthodontics & Craniofacial Research, iss. 28, pp. 441-448, 2024.
Abstract | Links | BibTeX | Tags: 3D analysis, condylar morphology, condylar remodeling, Orthognathic Surgery, skeletal class III
@article{nokey,
title = {Deep Learning-Based Three-Dimensional Analysis Reveals Distinct Patterns of Condylar Remodelling After Orthognathic Surgery in Skeletal Class III Patients},
author = {Selene Barone and Lucia Cevidanes and Jonas Bianchi and Joao Roberto Goncalves and Amerigo Giudice},
url = {https://www.scopus.com/pages/publications/85214127594?origin=resultslist&source=sd-apx},
doi = {10.1111/ocr.12895},
year = {2024},
date = {2024-12-24},
journal = {Orthodontics & Craniofacial Research},
issue = {28},
pages = {441-448},
abstract = {Objective: This retrospective study aimed to evaluate morphometric changes in mandibular condyles of patients with skeletal Class III malocclusion following two-jaw orthognathic surgery planned using virtual surgical planning (VSP) and analyzed with automated three-dimensional (3D) image analysis based on deep-learning techniques. Materials and Methods: Pre-operative (T1) and 12–18 months post-operative (T2) Cone-Beam Computed Tomography (CBCT) scans of 17 patients (mean age: 24.8 ± 3.5 years) were analyzed using 3DSlicer software. Deep-learning algorithms automated CBCT orientation, registration, bone segmentation, and landmark identification. By utilizing voxel-based superimposition of pre- and post-operative CBCT scans and shape correspondence, the overall changes in condylar morphology were assessed, with a focus on bone resorption and apposition at specific regions (superior, lateral and medial poles). The correlation between these modifications and the extent of actual condylar movements post-surgery was investigated. Statistical analysis was conducted with a significance level of α = 0.05. Results: Overall condylar remodeling was minimal, with mean changes of < 1 mm. Small but statistically significant bone resorption occurred at the condylar superior articular surface, while bone apposition was primarily observed at the lateral pole. The bone apposition at the lateral pole and resorption at the superior articular surface were significantly correlated with medial condylar displacement (p < 0.05). Conclusion: The automated 3D analysis revealed distinct patterns of condylar remodeling following orthognathic surgery in skeletal Class III patients, with minimal overall changes but significant regional variations. The correlation between condylar displacements and remodeling patterns highlights the need for precise pre-operative planning to optimize condylar positioning, potentially minimizing harmful remodeling and enhancing stability.},
keywords = {3D analysis, condylar morphology, condylar remodeling, Orthognathic Surgery, skeletal class III},
pubstate = {published},
tppubtype = {article}
}
Objective: This retrospective study aimed to evaluate morphometric changes in mandibular condyles of patients with skeletal Class III malocclusion following two-jaw orthognathic surgery planned using virtual surgical planning (VSP) and analyzed with automated three-dimensional (3D) image analysis based on deep-learning techniques. Materials and Methods: Pre-operative (T1) and 12–18 months post-operative (T2) Cone-Beam Computed Tomography (CBCT) scans of 17 patients (mean age: 24.8 ± 3.5 years) were analyzed using 3DSlicer software. Deep-learning algorithms automated CBCT orientation, registration, bone segmentation, and landmark identification. By utilizing voxel-based superimposition of pre- and post-operative CBCT scans and shape correspondence, the overall changes in condylar morphology were assessed, with a focus on bone resorption and apposition at specific regions (superior, lateral and medial poles). The correlation between these modifications and the extent of actual condylar movements post-surgery was investigated. Statistical analysis was conducted with a significance level of α = 0.05. Results: Overall condylar remodeling was minimal, with mean changes of < 1 mm. Small but statistically significant bone resorption occurred at the condylar superior articular surface, while bone apposition was primarily observed at the lateral pole. The bone apposition at the lateral pole and resorption at the superior articular surface were significantly correlated with medial condylar displacement (p < 0.05). Conclusion: The automated 3D analysis revealed distinct patterns of condylar remodeling following orthognathic surgery in skeletal Class III patients, with minimal overall changes but significant regional variations. The correlation between condylar displacements and remodeling patterns highlights the need for precise pre-operative planning to optimize condylar positioning, potentially minimizing harmful remodeling and enhancing stability.
Barone, Selene; Cevidanes, Lucia; Bianchi, Jonas; Goncalves, Joao Roberto; Giudice, Amerigo
Deep Learning-Based Three-Dimensional Analysis Reveals Distinct Patterns of Condylar Remodelling After Orthognathic Surgery in Skeletal Class III Patients Journal Article
In: Orthodontics & Craniofacial Research, iss. 28, pp. 441-448, 2024.
@article{nokey,
title = {Deep Learning-Based Three-Dimensional Analysis Reveals Distinct Patterns of Condylar Remodelling After Orthognathic Surgery in Skeletal Class III Patients},
author = {Selene Barone and Lucia Cevidanes and Jonas Bianchi and Joao Roberto Goncalves and Amerigo Giudice},
url = {https://www.scopus.com/pages/publications/85214127594?origin=resultslist&source=sd-apx},
doi = {10.1111/ocr.12895},
year = {2024},
date = {2024-12-24},
journal = {Orthodontics & Craniofacial Research},
issue = {28},
pages = {441-448},
abstract = {Objective: This retrospective study aimed to evaluate morphometric changes in mandibular condyles of patients with skeletal Class III malocclusion following two-jaw orthognathic surgery planned using virtual surgical planning (VSP) and analyzed with automated three-dimensional (3D) image analysis based on deep-learning techniques. Materials and Methods: Pre-operative (T1) and 12–18 months post-operative (T2) Cone-Beam Computed Tomography (CBCT) scans of 17 patients (mean age: 24.8 ± 3.5 years) were analyzed using 3DSlicer software. Deep-learning algorithms automated CBCT orientation, registration, bone segmentation, and landmark identification. By utilizing voxel-based superimposition of pre- and post-operative CBCT scans and shape correspondence, the overall changes in condylar morphology were assessed, with a focus on bone resorption and apposition at specific regions (superior, lateral and medial poles). The correlation between these modifications and the extent of actual condylar movements post-surgery was investigated. Statistical analysis was conducted with a significance level of α = 0.05. Results: Overall condylar remodeling was minimal, with mean changes of < 1 mm. Small but statistically significant bone resorption occurred at the condylar superior articular surface, while bone apposition was primarily observed at the lateral pole. The bone apposition at the lateral pole and resorption at the superior articular surface were significantly correlated with medial condylar displacement (p < 0.05). Conclusion: The automated 3D analysis revealed distinct patterns of condylar remodeling following orthognathic surgery in skeletal Class III patients, with minimal overall changes but significant regional variations. The correlation between condylar displacements and remodeling patterns highlights the need for precise pre-operative planning to optimize condylar positioning, potentially minimizing harmful remodeling and enhancing stability.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Objective: This retrospective study aimed to evaluate morphometric changes in mandibular condyles of patients with skeletal Class III malocclusion following two-jaw orthognathic surgery planned using virtual surgical planning (VSP) and analyzed with automated three-dimensional (3D) image analysis based on deep-learning techniques. Materials and Methods: Pre-operative (T1) and 12–18 months post-operative (T2) Cone-Beam Computed Tomography (CBCT) scans of 17 patients (mean age: 24.8 ± 3.5 years) were analyzed using 3DSlicer software. Deep-learning algorithms automated CBCT orientation, registration, bone segmentation, and landmark identification. By utilizing voxel-based superimposition of pre- and post-operative CBCT scans and shape correspondence, the overall changes in condylar morphology were assessed, with a focus on bone resorption and apposition at specific regions (superior, lateral and medial poles). The correlation between these modifications and the extent of actual condylar movements post-surgery was investigated. Statistical analysis was conducted with a significance level of α = 0.05. Results: Overall condylar remodeling was minimal, with mean changes of < 1 mm. Small but statistically significant bone resorption occurred at the condylar superior articular surface, while bone apposition was primarily observed at the lateral pole. The bone apposition at the lateral pole and resorption at the superior articular surface were significantly correlated with medial condylar displacement (p < 0.05). Conclusion: The automated 3D analysis revealed distinct patterns of condylar remodeling following orthognathic surgery in skeletal Class III patients, with minimal overall changes but significant regional variations. The correlation between condylar displacements and remodeling patterns highlights the need for precise pre-operative planning to optimize condylar positioning, potentially minimizing harmful remodeling and enhancing stability.
2024 |
Barone, Selene; Cevidanes, Lucia; Bianchi, Jonas; Goncalves, Joao Roberto; Giudice, Amerigo: Deep Learning-Based Three-Dimensional Analysis Reveals Distinct Patterns of Condylar Remodelling After Orthognathic Surgery in Skeletal Class III Patients. In: Orthodontics & Craniofacial Research, iss. 28, pp. 441-448, 2024. (Type: Journal Article | Abstract | Links | BibTeX | Tags: 3D analysis, condylar morphology, condylar remodeling, Orthognathic Surgery, skeletal class III)@article{nokey,Objective: This retrospective study aimed to evaluate morphometric changes in mandibular condyles of patients with skeletal Class III malocclusion following two-jaw orthognathic surgery planned using virtual surgical planning (VSP) and analyzed with automated three-dimensional (3D) image analysis based on deep-learning techniques. Materials and Methods: Pre-operative (T1) and 12–18 months post-operative (T2) Cone-Beam Computed Tomography (CBCT) scans of 17 patients (mean age: 24.8 ± 3.5 years) were analyzed using 3DSlicer software. Deep-learning algorithms automated CBCT orientation, registration, bone segmentation, and landmark identification. By utilizing voxel-based superimposition of pre- and post-operative CBCT scans and shape correspondence, the overall changes in condylar morphology were assessed, with a focus on bone resorption and apposition at specific regions (superior, lateral and medial poles). The correlation between these modifications and the extent of actual condylar movements post-surgery was investigated. Statistical analysis was conducted with a significance level of α = 0.05. Results: Overall condylar remodeling was minimal, with mean changes of < 1 mm. Small but statistically significant bone resorption occurred at the condylar superior articular surface, while bone apposition was primarily observed at the lateral pole. The bone apposition at the lateral pole and resorption at the superior articular surface were significantly correlated with medial condylar displacement (p < 0.05). Conclusion: The automated 3D analysis revealed distinct patterns of condylar remodeling following orthognathic surgery in skeletal Class III patients, with minimal overall changes but significant regional variations. The correlation between condylar displacements and remodeling patterns highlights the need for precise pre-operative planning to optimize condylar positioning, potentially minimizing harmful remodeling and enhancing stability. |