Geometric morphometric analysis of the palatal morphology in children with impacted incisors: A three-dimensional evaluation

Pavoni, Chiara; Paoloni, Valeria; Ghislanzoni, Luis Huanca; Laganà, Giuseppina; Cozza, Paola

doi:10.2319/071716-557.1

Cited by 17 publications

(18 citation statements)

References 19 publications

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“…Like the skeletal measurement, analysing the palatal shape through 3D laser scanning has aided in high‐speed measurement with high accuracy . The morphological variations are visualized and analysed by geometric morphometric analysis …”

Section: Introductionmentioning

confidence: 99%

“…9 The morphological variations are visualized and analysed by geometric morphometric analysis. 10,11 Structural equation modelling (SEM) can be used to analyse the relationship between various factors from the skeletal pattern and palatal morphology. This statistical technique simplify the relationship of multiple factors and make it possible to express the results in a schematic manner to help achieve an overall understanding.…”

Section: Introductionmentioning

confidence: 99%

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Analysis of the relationship between the morphology of the palate and facial skeletal patterns in Class III malocclusion using structural equation modelling

Ahn

Shin

Choi

et al. 2019

Orthod Craniofacial Res

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Structured Abstract Introduction The present study investigated the relationship between facial skeletal patterns and morphology of the palate in adult patients with Class III malocclusion using structural equation modelling (SEM). Setting and sample population One hundred cone beam computed tomography images of Class III adults were evaluated for skeletal measurements. Materials and methods The skeletal measurements were classified into the vertical, anteroposterior and transverse group based on factor analysis. 3D scanning model of the maxilla was analysed by Generalized procrustes analysis (GPA) and principal component analysis (PCA). Structural equation modelling was used to analyse relationship among the skeletal and morphometric factors. Results According to the factor analysis, latent variables were extracted by each skeletal variable. First principal component (PC1) and PC2 of palatal morphology were used to analyse relationship with skeletal variables. As results of the structural equation model, the transverse latent variable had the most influence on PC1, followed by vertical and anteroposterior variables. This result means that as the facial width increases, the palate becomes narrower, deeper and longer. Conclusions The relationship between the skeletal pattern with Class III malocclusion and palatal morphology was analysed through SEM. The transverse facial skeletal pattern showed the highest correlation with PC1 of palatal morphology.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Analysis of the relationship between the morphology of the palate and facial skeletal patterns in Class III malocclusion using structural equation modelling

Ahn

Shin

Choi

et al. 2019

Orthod Craniofacial Res

View full text Add to dashboard Cite

show abstract

“…All differences in location, size, and orientation were removed, expressing pure shape differences between groups. 23 Procrustes Analysis has been used in growth and maturation studies, 24,25 facial profile analysis, 26,27 skel-etal shape evaluation, 28 and even in facial attractiveness. 29 The main limitation of the method was the need for 12 homologous points to be placed on digital models for running the Procrustes superimposition.…”

Section: Discussionmentioning

confidence: 99%

Dental arch size and shape after maxillary expansion in bilateral complete cleft palate:A comparison of three expander designs

Pugliese

Palomo

Calil

et al. 2019

The Angle Orthodontist

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Objective: The objective of this study was to compare the effects on upper dental arch size and shape after maxillary expansion with Hyrax, Quad-helix, and a differential opening expander in bilateral cleft lip and palate (BCLP) patients. Materials and Methods: Seventy-five BCLP patients were divided into three groups: Hyrax (H), Quad-helix (QH), and Expander with differential opening (EDO). Digital models were obtained before (T1) and after 6 months (T2) of maxillary expansion. Twelve landmarks were placed by one investigator on T1 and T2 dental models of each group, and x,y coordinates for each landmark were collected. For dental arch size analysis, centroid size of each dental arch at T1 and T2 was calculated from raw coordinates and was used as the measure of size. Procrustes Analysis was performed for dental arch shape analysis. Analysis of variance was used to compare the groups for size and shape differences (P < .05). Results: There were no significant dental arch size differences among the expanders at T1 or T2. Differences in arch shape were found between all groups at T2. Intragroup arch shape showed a significant variation for the QH and EDO groups. while it remained stable in the H group. Conclusions: Both the QH and the EDO create dental arch shape changes with greater intercanine than intermolar increase. The H does not change the dental arch shape.

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“…When a data set has a large number of variables, principal component analysis (PCA) is a popular method of summarizing the information. [1][2][3][4][5][6][7][8] PCA compresses original variables into several sets of linear combinations of variables. In theory, the reduced set of variables, known as the principal components (also called latent variables), enable focusing the information in a data set with a large number of variables into only a few underlying factors.…”

Section: Introductionmentioning

confidence: 99%

A sparse principal component analysis of Class III malocclusions

Kang

Eo²,

Cho

et al. 2019

The Angle Orthodontist

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Objectives: To identify the most characteristic variables out of a large number of anatomic landmark variables on three-dimensional computed tomography (CT) images. A modified principal component analysis (PCA) was used to identify which anatomic structures would demonstrate the major variabilities that would most characterize the patient. Materials and Methods: Data were collected from 217 patients with severe skeletal Class III malocclusions who had undergone orthognathic surgery. The input variables were composed of a total of 740 variables consisting of three-dimensional Cartesian coordinates and their Euclidean distances of 104 soft tissue and 81 hard tissue landmarks identified on the CT images. A statistical method, a modified PCA based on the penalized matrix decomposition, was performed to extract the principal components. Results: The first 10 (8 soft tissue, 2 hard tissue) principal components from the 740 input variables explained 63% of the total variance. The most conspicuous principal components indicated that groups of soft tissue variables on the nose, lips, and eyes explained more variability than skeletal variables did. In other words, these soft tissue components were most representative of the differences among the Class III patients. Conclusions: On three-dimensional images, soft tissues had more variability than the skeletal anatomic structures. In the assessment of three-dimensional facial variability, a limited number of anatomic landmarks being used today did not seem sufficient. Nevertheless, this modified PCA may be used to analyze orthodontic three-dimensional images in the future, but it may not fully express the variability of the patients.

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Geometric morphometric analysis of the palatal morphology in children with impacted incisors: A three-dimensional evaluation

Abstract: The absence of maxillary central incisors over the physiological age of eruption influenced the development of the palatal morphology compared with subjects without eruption anomalies.

Cited by 17 publications

References 19 publications

Analysis of the relationship between the morphology of the palate and facial skeletal patterns in Class III malocclusion using structural equation modelling

Analysis of the relationship between the morphology of the palate and facial skeletal patterns in Class III malocclusion using structural equation modelling

Dental arch size and shape after maxillary expansion in bilateral complete cleft palate:A comparison of three expander designs

A sparse principal component analysis of Class III malocclusions

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