State-of-the-art three-dimensional analysis of soft tissue changes following Le Fort I maxillary advancement

Almukhtar, Anas; Ayoub, Ashraf; Khambay, Balvinder; McDonald, James; Ju, Xiangyang

doi:10.1016/j.bjoms.2016.05.023

Cited by 28 publications

(14 citation statements)

References 30 publications

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“…This study only measured fluctuating asymmetry at specific landmarks. It will be important, in the future, to analyze the fluctuating asymmetry using a surface-based approach (generic facial mesh) 29–31 .…”

Section: Discussionmentioning

confidence: 99%

Fluctuating asymmetry of the normal facial skeleton

Gateño

Jones

Shen

et al. 2018

International Journal of Oral and Maxillofacial Surgery

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The purpose of this study was to produce reliable estimations of fluctuating facial asymmetry in a normal population. Fifty-four computed tomography (CT) facial models of average-looking and symmetrical Chinese subjects with a class I occlusion were used in this study. Eleven midline landmarks and 12 pairs of bilateral landmarks were digitized. The repeatability of the landmark digitization was first evaluated. A Procrustes analysis was then used to measure the fluctuating asymmetry of each CT model, after all of the models had been scaled to the average face size of the study sample. A principal component analysis was finally used to establish the direction of the fluctuating asymmetries. The results showed that there was excellent absolute agreement among the three repeated measurements. The mean fluctuating asymmetry of the average-size face varied at each anthropometric landmark site, ranging from 1.0mm to 2.8mm. At the 95% upper limit, the asymmetries ranged from 2.2mm to 5.7mm. Most of the asymmetry of the midline structures was mediolateral, while the asymmetry of the bilateral landmarks was more equally distributed. These values are for the average face. People with larger faces will have higher values, while subjects with smaller faces will have lower values.

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Section: Discussionmentioning

confidence: 99%

Fluctuating asymmetry of the normal facial skeleton

Gateño

Jones

Shen

et al. 2018

International Journal of Oral and Maxillofacial Surgery

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“…This mesh was conformed (wrapped) on each 3-D facial image, and a conformation mesh was achieved to accurately represent each of the captured faces. The first step of the conformation process was the identification of a set of anatomical landmarks on both the 3-D surface image and the generic mesh to guide the rigid superimposition between the 2 surfaces followed by elastic deformation of the mesh to wrap on the 3-D facial morphology (Almukhtar et al, 2016). During the conformation process, to standardize the site of the cleft for the analysis, the images of the right-sided cleft were reflected, so for all the 3-D facial models and their conformation meshes, the cleft was on the left side.…”

Section: Methodsmentioning

confidence: 99%

Longitudinal 3D Assessment of Facial Asymmetry in Unilateral Cleft Lip and Palate

Al-Rudainy

Mehendale

et al. 2018

The Cleft Palate-Craniofacial Journal

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“…The method is also well suited for analysis of data obtained by 3D stereophotogrammetry, which does not subject the patient to iodizing radiation. Several similar methods for quantification of FA have been described in the recent literature (Almukhtar et al, 2016; Cho et al, 2016; Cho et al, 2018; Gabrick et al, 2020; Visse et al, 2020), which would also be well-suited methods for this patient group.…”

Section: Discussionmentioning

confidence: 99%

Facial Asymmetry in Nonsyndromic and Muenke Syndrome–Associated Unicoronal Synostosis: A 3-Dimensional Study Based on Facial Surfaces Extracted From CT Scans

Öwall

Darvann

Hove

et al. 2020

The Cleft Palate-Craniofacial Journal

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Objective: To quantify soft tissue facial asymmetry (FA) in children with nonsyndromic and Muenke syndrome–associated unicoronal synostosis (NS-UCS and MS-UCS), hypothesizing that MS-UCS presents with significantly larger FA than NS-UCS. Design: Retrospective cohort study. Patients and Methods: Twenty-one children (mean age: 0.6 years; range: 0.1-1.4 years) were included in the study (NS-UCS = 14; MS-UCS = 7). From presurgical computed tomography scans, facial surfaces were constructed for analysis. A landmark guided atlas was deformed to match each patient’s surface, obtaining spatially detailed left-right point correspondence. Facial asymmetry was calculated in each surface point across the face, as the length (mm) of an asymmetry vector, with its Cartesian components providing 3 directions. Mean FA was calculated for the full face, and the forehead, eye, nose, cheek, mouth, and chin regions. Results: For the full face, a significant difference of 2.4 mm ( P = .001) was calculated between the 2 groups, predominately in the transverse direction (1.5 mm; P < .001). The forehead and chin regions presented with the largest significant difference, 3.5 mm ( P = .002) and 3.2 mm ( P < .001), respectively; followed by the eye (2.4 mm; P = .004), cheek (2.2 mm; P = .004), nose (1.7 mm; P = .001), and mouth (1.4 mm; P = .009) regions. The transverse direction presented with the largest significant difference in the forehead, chin, mouth, and nose regions, the sagittal direction in the cheek region, and the vertical direction in the eye region. Conclusions: Muenke syndrome–associated unicoronal synostosis presented with significantly larger FA in all regions compared to NS-UCS. The largest significant differences were found in the forehead and chin regions, predominantly in the transverse direction.

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State-of-the-art three-dimensional analysis of soft tissue changes following Le Fort I maxillary advancement

Cited by 28 publications

References 30 publications

Fluctuating asymmetry of the normal facial skeleton

Fluctuating asymmetry of the normal facial skeleton

Longitudinal 3D Assessment of Facial Asymmetry in Unilateral Cleft Lip and Palate

Facial Asymmetry in Nonsyndromic and Muenke Syndrome–Associated Unicoronal Synostosis: A 3-Dimensional Study Based on Facial Surfaces Extracted From CT Scans

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