Publications
2024
Moon, Stacey H.; Yue, Olivia; Vaughan, Mark; Suh, Heeyeon; Oh, Heesoo
Establishing Occlusion for Cleft Lip and Palate Patient Journal Article
In: Journal of the Korean Cleft Lip and Palate Society, vol. 27, no. 1, pp. 6-17, 2024.
Abstract | Links | BibTeX | Tags: Class III, cleft lip, Dental Crowding, malocclusion, Rapid Palatal Expander (RPE)
@article{Moon2024,
title = {Establishing Occlusion for Cleft Lip and Palate Patient},
author = {Stacey H. Moon and Olivia Yue and Mark Vaughan and Heeyeon Suh and Heesoo Oh},
url = {https://scholar.kyobobook.co.kr/article/detail/4050069418395},
year = {2024},
date = {2024-06-03},
journal = {Journal of the Korean Cleft Lip and Palate Society},
volume = {27},
number = {1},
pages = {6-17},
abstract = {Craniofacial cleft patients commonly present with under-developed maxilla, which may have a profound effect not only on their soft tissue facial appearance but also skeletal discrepancy and dental malocclusion. This case report presents the treatment of a 14-year-old girl with a Class III skeletal and dental malocclusion. Her occlusion is complicated by a maxillary anterior right osseous cleft, retrognathic narrow maxilla with associated anterior and posterior crossbite, dental crowding, retained primary teeth, and several missing permanent teeth including maxillary premolars, both permanent maxillary lateral incisors, and all third molars. Our treatment plan consisted of extractions of the remaining primary teeth, maxillary expansion, protraction of maxilla and substitution of the maxillary left premolar for a lateral incisor tooth. The need for orthognathic surgery was also explained to the patient prior to the start of the treatment. The treatment was successfully completed with fixed appliances, rapid palatal expander (RPE), facemask (FM), maxillary segmental advancement with the fistula closure, and alveolar bone graft and elastics. Septorhinoplasty was completed towards the end of the treatment. Orthodontic treatment was completed in 48 months. The maxillary anterior teeth were aesthetically restored after the orthodontic treatment was completed. The retention consisted of maxillary and mandibular Hawley retainers.},
keywords = {Class III, cleft lip, Dental Crowding, malocclusion, Rapid Palatal Expander (RPE)},
pubstate = {published},
tppubtype = {article}
}
Craniofacial cleft patients commonly present with under-developed maxilla, which may have a profound effect not only on their soft tissue facial appearance but also skeletal discrepancy and dental malocclusion. This case report presents the treatment of a 14-year-old girl with a Class III skeletal and dental malocclusion. Her occlusion is complicated by a maxillary anterior right osseous cleft, retrognathic narrow maxilla with associated anterior and posterior crossbite, dental crowding, retained primary teeth, and several missing permanent teeth including maxillary premolars, both permanent maxillary lateral incisors, and all third molars. Our treatment plan consisted of extractions of the remaining primary teeth, maxillary expansion, protraction of maxilla and substitution of the maxillary left premolar for a lateral incisor tooth. The need for orthognathic surgery was also explained to the patient prior to the start of the treatment. The treatment was successfully completed with fixed appliances, rapid palatal expander (RPE), facemask (FM), maxillary segmental advancement with the fistula closure, and alveolar bone graft and elastics. Septorhinoplasty was completed towards the end of the treatment. Orthodontic treatment was completed in 48 months. The maxillary anterior teeth were aesthetically restored after the orthodontic treatment was completed. The retention consisted of maxillary and mandibular Hawley retainers.
2023
F, Miranda; V, Choudhari; S, Barone; L, Anchling; N, Hutin; M, Gurgel; et al,
Interpretable artificial intelligence for classification of alveolar bone defect in patients with cleft lip and palate. Journal Article
In: Scientific Reports, vol. 15861, 2023.
Abstract | Links | BibTeX | Tags: 3D landmark identification, alveolar bone defect, artificial intelligence, cleft lip, cleft lip and palate
@article{Bianchi2023j,
title = {Interpretable artificial intelligence for classification of alveolar bone defect in patients with cleft lip and palate. },
author = {Miranda F and Choudhari V and Barone S and Anchling L and Hutin N and Gurgel M and et al},
url = {https://doi.org/10.1038/s41598-023-43125-7},
doi = {10.1038/s41598-023-43125-7},
year = {2023},
date = {2023-09-22},
journal = {Scientific Reports},
volume = {15861},
abstract = {Cleft lip and/or palate (CLP) is the most common congenital craniofacial anomaly and requires bone grafting of the alveolar cleft. This study aimed to develop a novel classification algorithm to assess the severity of alveolar bone defects in patients with CLP using three-dimensional (3D) surface models and to demonstrate through an interpretable artificial intelligence (AI)-based algorithm the decisions provided by the classifier. Cone-beam computed tomography scans of 194 patients with CLP were used to train and test the performance of an automatic classification of the severity of alveolar bone defect. The shape, height, and width of the alveolar bone defect were assessed in automatically segmented maxillary 3D surface models to determine the ground truth classification index of its severity. The novel classifier algorithm renders the 3D surface models from different viewpoints and captures 2D image snapshots fed into a 2D Convolutional Neural Network. An interpretable AI algorithm was developed that uses features from each view and aggregated via Attention Layers to explain the classification. The precision, recall and F-1 score were 0.823, 0.816, and 0.817, respectively, with agreement ranging from 97.4 to 100% on the severity index within 1 group difference. The new classifier and interpretable AI algorithm presented satisfactory accuracy to classify the severity of alveolar bone defect morphology using 3D surface models of patients with CLP and graphically displaying the features that were considered during the deep learning model's classification decision.},
keywords = {3D landmark identification, alveolar bone defect, artificial intelligence, cleft lip, cleft lip and palate},
pubstate = {published},
tppubtype = {article}
}
Cleft lip and/or palate (CLP) is the most common congenital craniofacial anomaly and requires bone grafting of the alveolar cleft. This study aimed to develop a novel classification algorithm to assess the severity of alveolar bone defects in patients with CLP using three-dimensional (3D) surface models and to demonstrate through an interpretable artificial intelligence (AI)-based algorithm the decisions provided by the classifier. Cone-beam computed tomography scans of 194 patients with CLP were used to train and test the performance of an automatic classification of the severity of alveolar bone defect. The shape, height, and width of the alveolar bone defect were assessed in automatically segmented maxillary 3D surface models to determine the ground truth classification index of its severity. The novel classifier algorithm renders the 3D surface models from different viewpoints and captures 2D image snapshots fed into a 2D Convolutional Neural Network. An interpretable AI algorithm was developed that uses features from each view and aggregated via Attention Layers to explain the classification. The precision, recall and F-1 score were 0.823, 0.816, and 0.817, respectively, with agreement ranging from 97.4 to 100% on the severity index within 1 group difference. The new classifier and interpretable AI algorithm presented satisfactory accuracy to classify the severity of alveolar bone defect morphology using 3D surface models of patients with CLP and graphically displaying the features that were considered during the deep learning model's classification decision.
Moon, Stacey H.; Yue, Olivia; Vaughan, Mark; Suh, Heeyeon; Oh, Heesoo
Establishing Occlusion for Cleft Lip and Palate Patient Journal Article
In: Journal of the Korean Cleft Lip and Palate Society, vol. 27, no. 1, pp. 6-17, 2024.
@article{Moon2024,
title = {Establishing Occlusion for Cleft Lip and Palate Patient},
author = {Stacey H. Moon and Olivia Yue and Mark Vaughan and Heeyeon Suh and Heesoo Oh},
url = {https://scholar.kyobobook.co.kr/article/detail/4050069418395},
year = {2024},
date = {2024-06-03},
journal = {Journal of the Korean Cleft Lip and Palate Society},
volume = {27},
number = {1},
pages = {6-17},
abstract = {Craniofacial cleft patients commonly present with under-developed maxilla, which may have a profound effect not only on their soft tissue facial appearance but also skeletal discrepancy and dental malocclusion. This case report presents the treatment of a 14-year-old girl with a Class III skeletal and dental malocclusion. Her occlusion is complicated by a maxillary anterior right osseous cleft, retrognathic narrow maxilla with associated anterior and posterior crossbite, dental crowding, retained primary teeth, and several missing permanent teeth including maxillary premolars, both permanent maxillary lateral incisors, and all third molars. Our treatment plan consisted of extractions of the remaining primary teeth, maxillary expansion, protraction of maxilla and substitution of the maxillary left premolar for a lateral incisor tooth. The need for orthognathic surgery was also explained to the patient prior to the start of the treatment. The treatment was successfully completed with fixed appliances, rapid palatal expander (RPE), facemask (FM), maxillary segmental advancement with the fistula closure, and alveolar bone graft and elastics. Septorhinoplasty was completed towards the end of the treatment. Orthodontic treatment was completed in 48 months. The maxillary anterior teeth were aesthetically restored after the orthodontic treatment was completed. The retention consisted of maxillary and mandibular Hawley retainers.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Craniofacial cleft patients commonly present with under-developed maxilla, which may have a profound effect not only on their soft tissue facial appearance but also skeletal discrepancy and dental malocclusion. This case report presents the treatment of a 14-year-old girl with a Class III skeletal and dental malocclusion. Her occlusion is complicated by a maxillary anterior right osseous cleft, retrognathic narrow maxilla with associated anterior and posterior crossbite, dental crowding, retained primary teeth, and several missing permanent teeth including maxillary premolars, both permanent maxillary lateral incisors, and all third molars. Our treatment plan consisted of extractions of the remaining primary teeth, maxillary expansion, protraction of maxilla and substitution of the maxillary left premolar for a lateral incisor tooth. The need for orthognathic surgery was also explained to the patient prior to the start of the treatment. The treatment was successfully completed with fixed appliances, rapid palatal expander (RPE), facemask (FM), maxillary segmental advancement with the fistula closure, and alveolar bone graft and elastics. Septorhinoplasty was completed towards the end of the treatment. Orthodontic treatment was completed in 48 months. The maxillary anterior teeth were aesthetically restored after the orthodontic treatment was completed. The retention consisted of maxillary and mandibular Hawley retainers.
F, Miranda; V, Choudhari; S, Barone; L, Anchling; N, Hutin; M, Gurgel; et al,
Interpretable artificial intelligence for classification of alveolar bone defect in patients with cleft lip and palate. Journal Article
In: Scientific Reports, vol. 15861, 2023.
@article{Bianchi2023j,
title = {Interpretable artificial intelligence for classification of alveolar bone defect in patients with cleft lip and palate. },
author = {Miranda F and Choudhari V and Barone S and Anchling L and Hutin N and Gurgel M and et al},
url = {https://doi.org/10.1038/s41598-023-43125-7},
doi = {10.1038/s41598-023-43125-7},
year = {2023},
date = {2023-09-22},
journal = {Scientific Reports},
volume = {15861},
abstract = {Cleft lip and/or palate (CLP) is the most common congenital craniofacial anomaly and requires bone grafting of the alveolar cleft. This study aimed to develop a novel classification algorithm to assess the severity of alveolar bone defects in patients with CLP using three-dimensional (3D) surface models and to demonstrate through an interpretable artificial intelligence (AI)-based algorithm the decisions provided by the classifier. Cone-beam computed tomography scans of 194 patients with CLP were used to train and test the performance of an automatic classification of the severity of alveolar bone defect. The shape, height, and width of the alveolar bone defect were assessed in automatically segmented maxillary 3D surface models to determine the ground truth classification index of its severity. The novel classifier algorithm renders the 3D surface models from different viewpoints and captures 2D image snapshots fed into a 2D Convolutional Neural Network. An interpretable AI algorithm was developed that uses features from each view and aggregated via Attention Layers to explain the classification. The precision, recall and F-1 score were 0.823, 0.816, and 0.817, respectively, with agreement ranging from 97.4 to 100% on the severity index within 1 group difference. The new classifier and interpretable AI algorithm presented satisfactory accuracy to classify the severity of alveolar bone defect morphology using 3D surface models of patients with CLP and graphically displaying the features that were considered during the deep learning model's classification decision.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Cleft lip and/or palate (CLP) is the most common congenital craniofacial anomaly and requires bone grafting of the alveolar cleft. This study aimed to develop a novel classification algorithm to assess the severity of alveolar bone defects in patients with CLP using three-dimensional (3D) surface models and to demonstrate through an interpretable artificial intelligence (AI)-based algorithm the decisions provided by the classifier. Cone-beam computed tomography scans of 194 patients with CLP were used to train and test the performance of an automatic classification of the severity of alveolar bone defect. The shape, height, and width of the alveolar bone defect were assessed in automatically segmented maxillary 3D surface models to determine the ground truth classification index of its severity. The novel classifier algorithm renders the 3D surface models from different viewpoints and captures 2D image snapshots fed into a 2D Convolutional Neural Network. An interpretable AI algorithm was developed that uses features from each view and aggregated via Attention Layers to explain the classification. The precision, recall and F-1 score were 0.823, 0.816, and 0.817, respectively, with agreement ranging from 97.4 to 100% on the severity index within 1 group difference. The new classifier and interpretable AI algorithm presented satisfactory accuracy to classify the severity of alveolar bone defect morphology using 3D surface models of patients with CLP and graphically displaying the features that were considered during the deep learning model's classification decision.
2024 |
Moon, Stacey H.; Yue, Olivia; Vaughan, Mark; Suh, Heeyeon; Oh, Heesoo: Establishing Occlusion for Cleft Lip and Palate Patient. In: Journal of the Korean Cleft Lip and Palate Society, vol. 27, no. 1, pp. 6-17, 2024. (Type: Journal Article | Abstract | Links | BibTeX | Tags: Class III, cleft lip, Dental Crowding, malocclusion, Rapid Palatal Expander (RPE))@article{Moon2024,Craniofacial cleft patients commonly present with under-developed maxilla, which may have a profound effect not only on their soft tissue facial appearance but also skeletal discrepancy and dental malocclusion. This case report presents the treatment of a 14-year-old girl with a Class III skeletal and dental malocclusion. Her occlusion is complicated by a maxillary anterior right osseous cleft, retrognathic narrow maxilla with associated anterior and posterior crossbite, dental crowding, retained primary teeth, and several missing permanent teeth including maxillary premolars, both permanent maxillary lateral incisors, and all third molars. Our treatment plan consisted of extractions of the remaining primary teeth, maxillary expansion, protraction of maxilla and substitution of the maxillary left premolar for a lateral incisor tooth. The need for orthognathic surgery was also explained to the patient prior to the start of the treatment. The treatment was successfully completed with fixed appliances, rapid palatal expander (RPE), facemask (FM), maxillary segmental advancement with the fistula closure, and alveolar bone graft and elastics. Septorhinoplasty was completed towards the end of the treatment. Orthodontic treatment was completed in 48 months. The maxillary anterior teeth were aesthetically restored after the orthodontic treatment was completed. The retention consisted of maxillary and mandibular Hawley retainers. |
2023 |
F, Miranda; V, Choudhari; S, Barone; L, Anchling; N, Hutin; M, Gurgel; et al,: Interpretable artificial intelligence for classification of alveolar bone defect in patients with cleft lip and palate. . In: Scientific Reports, vol. 15861, 2023. (Type: Journal Article | Abstract | Links | BibTeX | Tags: 3D landmark identification, alveolar bone defect, artificial intelligence, cleft lip, cleft lip and palate)@article{Bianchi2023j,Cleft lip and/or palate (CLP) is the most common congenital craniofacial anomaly and requires bone grafting of the alveolar cleft. This study aimed to develop a novel classification algorithm to assess the severity of alveolar bone defects in patients with CLP using three-dimensional (3D) surface models and to demonstrate through an interpretable artificial intelligence (AI)-based algorithm the decisions provided by the classifier. Cone-beam computed tomography scans of 194 patients with CLP were used to train and test the performance of an automatic classification of the severity of alveolar bone defect. The shape, height, and width of the alveolar bone defect were assessed in automatically segmented maxillary 3D surface models to determine the ground truth classification index of its severity. The novel classifier algorithm renders the 3D surface models from different viewpoints and captures 2D image snapshots fed into a 2D Convolutional Neural Network. An interpretable AI algorithm was developed that uses features from each view and aggregated via Attention Layers to explain the classification. The precision, recall and F-1 score were 0.823, 0.816, and 0.817, respectively, with agreement ranging from 97.4 to 100% on the severity index within 1 group difference. The new classifier and interpretable AI algorithm presented satisfactory accuracy to classify the severity of alveolar bone defect morphology using 3D surface models of patients with CLP and graphically displaying the features that were considered during the deep learning model's classification decision. |