Multilevel principal components analysis of three-dimensional facial growth in adolescents

Farnell, Damian J. J.; Richmond, Stephen; Galloway, Jennifer; Zhurov, Alexei I.; Pirttiniemi, Pertti; Heikkinen, Tuomo; Harila, Virpi; Matthews, Harold; Claes, Peter

doi:10.1016/j.cmpb.2019.105272

Cited by 9 publications

(27 citation statements)

References 66 publications

(82 reference statements)

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“…Fig. 2: Colour map of the projection representing differences in shapes normal to the surface at each point (broadly: blue indicates inward changes in mm and yellow indicates outward changes in mm) going from ages 12 to 17 using mPCA [57] (upper figure) and mPLSR (lower figure). Excellent correspondence is seen between the two approaches, although changes via mPLSR appear to be slightly more distinct.…”

Section: Resultsmentioning

confidence: 99%

“…Results of single-level PCA and mPCA (using the model shown in Fig. 1) for this dataset were presented previously in [57] and so we give a brief recap here only. For mPCA eigenvalues at level 1 (ethnicity/sex), level 2 (between-subjects) and level 3 (age) accounted for 7.9%, 71.5%, and 20.6% of shape variation in our dataset, respectively.…”

Section: Resultsmentioning

confidence: 99%

“…Multilevel principal components analysis (mPCA) [50][51][52][53][54][55][56][57] provides another multivariate method to fit multilevel models to shape coordinate data. mPCA has been used to investigate facial shape changes by ethnicity and sex [51,52], the act of smiling [53,54], maternal smoking and alcohol intake [55], and facial shape changes during adolescence [56,57]. Group centroids were found in [56,57] at (integer) ages 12 to 17 (i.e., 6 groups) in order to explore component scores at an appropriate level of the model.…”

Section: Introductionmentioning

confidence: 99%

“…mPCA has been used to investigate facial shape changes by ethnicity and sex [51,52], the act of smiling [53,54], maternal smoking and alcohol intake [55], and facial shape changes during adolescence [56,57]. Group centroids were found in [56,57] at (integer) ages 12 to 17 (i.e., 6 groups) in order to explore component scores at an appropriate level of the model. A limitation of this approach was that age was treated indirectly as a discrete rather continuous quantity.…”

Section: Introductionmentioning

confidence: 99%

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An exploration of adolescent facial shape changes with age via multilevel partial least squares regression

Farnell

Richmond

Galloway

et al. 2021

Computer Methods and Programs in Biomedicine

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Background and Objectives: Multilevel statistical models represent the existence of hierarchies or clustering within populations of subjects (or shapes in this work). This is a distinct advantage over single-level methods that do not. Multilevel partial-least squares regression (mPLSR) is used here to study facial shape changes with age during adolescence in Welsh and Finnish samples comprising males and females.Methods: 3D facial images were obtained for Welsh and Finnish male and female subjects at multiple ages from 12 to 17 years old. 1000 3D points were defined regularly for each shape by using "meshmonk" software. A three-level model was used here, including level 1 (sex/ethnicity); level 2, all "subject" variations excluding sex, ethnicity, and age; and level 3, age. The mathematical formalism of mPLSR is given in an Appendix.Results: Differences in facial shape between the ages of 12 and 17 predicted by mPLSR agree well with previous results of multilevel principal components analysis (mPCA); buccal fat is reduced with increasing age and features such as the nose, brow, and chin become larger and more distinct. Differences due to ethnicity and sex are also observed. Plausible simulated faces are predicted from the model for different ages, sexes and ethnicities. Our models provide good representations of the shape data by consideration of appropriate measures of model fit (RMSE and R 2 ).Conclusions: Repeat measures in our dataset for the same subject at different ages can only be modelled indirectly at the lowest level of the model at discrete ages via mPCA. By contrast, mPLSR models age explicitly as a continuous covariate, which is a strong advantage of mPLSR over mPCA. These investigations demonstrate that multivariate multilevel methods such as mPLSR can be used to describe such age-related changes for dense 3D point data. mPLSR 3 might be of much use in future for the prediction of facial shapes for missing persons at specific ages or for simulating shapes for syndromes that affect facial shape in new subject populations.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An exploration of adolescent facial shape changes with age via multilevel partial least squares regression

Farnell

Richmond

Galloway

et al. 2021

Computer Methods and Programs in Biomedicine

Self Cite

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show abstract

“…It allows one to account for groupings or clustering when analysing multivariate data such as shapes or image texture. It has been applied previously to investigate (in humans): facial shape changes by ethnicity and sex [18,19]; the act of smiling [20,21]; and facial shape changes in adolescents due to age [22,23]; maternal smoking and alcohol intake on the facial shape of children [24].…”

Section: Introductionmentioning

confidence: 99%

Initial Investigations of the Cranial Size and Shape of Adult Eurasian Otters (<em>Lutra lutra</em>) in Great Britain

Farnell¹,

Khor²,

Doyle³

et al. 2020

Preprint

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3D surface scans were carried out to determine the shapes of the upper sections of (skeletal) crania of adult Eurasian otters (Lutra lutra) from Great Britain. Landmark points were placed on these shapes by using a graphical user interface (GUI) and distance measurements (i.e., the length, height, and width of the crania) could be found by using the landmark points. These “GUI-based” distances were shown to be accurate and reliable in comparison to physical measurements taken on the crania directly by using a digital calliper. The crania of males were 6.85mm, 5.44mm, 1.66mm larger in terms of length, width and height, respectively, than females in our sample (P < 0.001), i.e., male otters had significantly larger skulls than females. Significant differences in size occurred also by geographical area in Great Britain (P < 0.05). Multilevel Principal Components Analysis (mPCA) indicated that sex and geographical area explained 31.1% and 9.6% of shape variation in “unscaled” shape data and that they explained 17.2% and 9.7% of variation in “scaled” data. The first mode of variation at level 1 (sex) correctly reflected size changes between males and females for “unscaled” shape data. Modes at level 2 (geographical area) also showed possible changes in size and shape. Clustering by sex and geographical area was observed in standardised component scores. Such clustering in cranial shape by geographical area might reflect genetic differences that are known to occur in otter populations in Great Britain, although other potentially confounding factors (e.g. population age-structure, diet, etc.) might also drive regional differences. Furthermore, sample sizes per group were small for geographical comparisons. However, this work provides a successful first test of the effectiveness of 3D surface scans and multivariate methods such as mPCA to study the cranial morphology of otters.

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A quantitative analysis of facial changes after orthodontic treatment with vertical control in patients with idiopathic condylar resorption

Mao¹,

Tian²,

Li³

et al. 2022

Orthod Craniofacial Res

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Objective This study aimed to investigate temporomandibular joint (TMJ) stability and three‐dimensional (3D) facial changes in class II hyperdivergent patients with stable idiopathic condylar resorption (ICR) after orthodontic camouflage treatment with vertical control by using temporary anchorage devises (TADs). Methods Nineteen skeletal class II hyperdivergent patients who were diagnosed with stable ICR underwent bicuspid extraction orthodontic treatment with vertical control via TADs were enrolled. TMJ was evaluated with the cone beam computerized tomography (CBCT) and clinical records before and after treatment. Changes in dental and skeletal parameters were evaluated with cephalometric and dental cast measurements. The 3D morphable model (3DMM) method was performed with the MeshMonk toolbox for the 3D facial analysis. After the reposition and landmark setting process, 3D facial heatmaps were used to illustrate facial changes, and the 3D deviations of landmarks were calculated. Results Both the imaging evaluation and clinical examination proved that TMJs remained stable after treatment. The retrusion of the upper and lower incisors reached 6.63 ± 0.79 mm and 3.78 ± 1.49 mm. The intrusion of the upper first molar reached 2.65 ± 0.75 mm, with a 2.27 ± 0.82° counterclockwise rotation of the mandibular plane. An upward shift of the soft tissue pogonion (2.34 ± 2.03 mm) and protrusion of Po‐NB (0.82 ± 0.70 mm) was gained. Larger intrusion was found in the lower lip (3.29 ± 0.80 mm) than in the upper lip (2.20 ± 0.69 mm). Conclusion Camouflage orthodontic treatment with TAD for vertical control is acceptable for skeletal class II hyperdivergent patients with ICR, which can improve the facial profile.

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Multilevel principal components analysis of three-dimensional facial growth in adolescents

Cited by 9 publications

References 66 publications

An exploration of adolescent facial shape changes with age via multilevel partial least squares regression

An exploration of adolescent facial shape changes with age via multilevel partial least squares regression

Initial Investigations of the Cranial Size and Shape of Adult Eurasian Otters (<em>Lutra lutra</em>) in Great Britain

A quantitative analysis of facial changes after orthodontic treatment with vertical control in patients with idiopathic condylar resorption

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