Variations of midline facial soft tissue thicknesses among three skeletal classes in Central Anatolian adults

Güngör, Kıvanç; Bulut, Özgür; Hizliol, Ismail; Hekįmoğlu, Baki; Gürcan, Safa

doi:10.1016/j.legalmed.2015.09.001

Cited by 22 publications

(35 citation statements)

References 32 publications

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“…Indeed, the results are difficult to discuss, as literature concerning the children is very limited; nevertheless, provide some food for thoughts. First, general rules concerning adults seem not to be entirely followed in case of children, as Class II shows lower thicknesses in labrale superius; from this point of view, the present data are concordant with several articles on adult population, where this specific difference has already been reported [13,15,17].…”

Section: Discussionsupporting

confidence: 90%

“…On the other side, in a similar Turkish population Kamak and Celikoglu [15] found a statistically significant increase of soft tissue thickness at labrale superius and stomion in Class III, at labrale inferius in Class II. Gungor et al, [17] in a Central Anatolian group found differences in soft tissue thicknesses at rhinion, labrale superius (higher in Class III) and labrale inferius (higher in Class II) in males, and at nasion and labrale inferius in females (higher in Class II).…”

Section: Discussionmentioning

confidence: 94%

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Modifications of Midfacial Soft-Tissue Thickness Among Different Skeletal Classes in Italian Children

Gibelli¹,

Zago²,

Cappella³

et al. 2018

TOMIJ

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Background:The anatomical assessment of the arrangement of facial soft tissues has important applications in different fields from orthodontics to plastic surgery. One of the issues concerns the relationship between facial soft tissue thickness and skeletal class. Literature mainly deals with adult populations, whereas very few studies have been focused on children. Objective:This study aims at investigating the relationship between midline facial soft tissue thickness and skeletal classes in Italian pretreatment orthodontic child patients. Methods:Lateral cephalometric X-ray films were obtained from 220 healthy Caucasoid children (91 males and 129 females), aged between 6 and 18 years (Class I: 41 males and 70 females; Class II: 18 males and 25 females; Class III: 32 males and 34 females). All the films were digitized and 14 soft tissue thicknesses were measured on the midface; in addition, the skeletal class was assessed according to the corrected ANB angle (ANBc). Differences in facial soft tissue thickness according to sex and skeletal class were assessed through two-way ANOVA test (p<0.01). Results:Statistically significant differences according to sex were found for labrale superius, stomion and labrale inferius, with thicker soft tissues in males than in females (p<0.01). Only measurements at labrale superius and gnathion showed statistically significant differences according to skeletal class, with thicker soft tissues in Class III children and thinner ones in Class II children (p<0.01). Conclusion:The limited number of investigations, as well as the differences in protocols, renders the comparison of results from different studies difficult, suggesting further investigations to enlighten this complex and debated anatomical issue.

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Section: Discussionsupporting

confidence: 90%

Section: Discussionmentioning

confidence: 94%

Modifications of Midfacial Soft-Tissue Thickness Among Different Skeletal Classes in Italian Children

Gibelli¹,

Zago²,

Cappella³

et al. 2018

TOMIJ

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“…The influence of skeletal class on ASTD has been explored from lateral cephalograms in numerous ways, including manual acetate sheet tracing [35][36][37][38][39]41,44,45,47], digital measurement using iTEM Analyses imaging program [42], DentaPacs 8.1 [43], Sidexis Xg [40], NemoCeph NS [46], and Adobe Photoshop CS5.1 (this study). Nevertheless, the ASTD among three skeletal classes of the Indonesian adult population was found comparable with the previous studies from other ancestral groups (Table 4).…”

Section: Discussionmentioning

confidence: 99%

“…There are numerous studies providing ASTD data based on sex, age, ancestral origin and body mass index (BMI) which are derived from various sample sources for instance cadavers [6][7][8][9][10], ultrasound [11][12][13][14][15][16][17], magnetic resonance imaging scans [18][19][20][21], computed tomography scans [22][23][24][25][26][27][28][29][30][31], cone beam computed tomography [32][33][34], and lateral cephalograms [35][36][37][38][39][40][41][42][43][44][45][46][47]. Interestingly, some papers have found that skeletal classes influences the ASTD pattern in the oral area, both in subadult [35][36][37][39][40]…”

Section: Introductionmentioning

confidence: 99%

Facial average soft tissue depth variation based on skeletal classes in Indonesian adult population: A retrospective lateral cephalometric study

et al. 2020

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Highlights • Database of 10 midline facial landmarks average soft tissue thickness grouped into 3 skeletal classes in Indonesian adult population is presented in this study. • Significant difference among skeletal classes occurred in male lower lip. • Significant differences among skeletal classes occurred in female subnasale, upper lip, stomion, lower lip and labiomentale. • A generic pattern of deeper upper lip than lower lip in class III compared to class II and conversely, deeper lower lip than upper lip in class II compared to class III, was visible in both male and female groups.

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“…Literature related to facial soft tissue thickness are often analyzed with the separation of sexes [42][43][44][45][46][47][48][49][50], specifically to nose prediction, Rynn et al [13] and Sarilita et al [35] both suggested significant sexual dimorphism.…”

Section: Rynn Et Al Suggested Nasal Height and Nasal Depth For Europmentioning

confidence: 99%

Prediction of nasal morphology in facial reconstruction: Validation and recalibration of the Rynn method

et al. 2019

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Background: Prediction of the nose from the skull remains an important issue in forensic facial approximation. In 2010, Rynn et al. published a method of predicting nose projection from the skull. With this method, three craniometric measurements (x, y, z) are taken, and these are then used in regression formulae to estimate the nasal dimensions. Aim: The purpose of this study was to examine and test the accuracy of the Rynn et al. method and if necessary to adapt the formulae for this population. Subjects and methods: A sample of 90 CT scans of Turkish adults was used in the study. The actual and predicted dimensions were compared using t-test. The age of the individuals ranged from 20 to 40 years by sex. Results: The descriptive statistics and correlations were calculated, and the actual and predicted measurements were compared. The differences between the actual and predicted values were statistically significant (p<0.01), with −1 mm for males and −1.5 mm for females. Validation accuracies ranged from 76-92% in females and 72-82% in males. Recalibration equation accuracies ranged from 88-100% in females and 90-100% in males. Conclusion: The results showed that the recalibration of the Rynn et al. method and its formulae gave satisfactory results with less error and can be employed in facial approximation cases.

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Variations of midline facial soft tissue thicknesses among three skeletal classes in Central Anatolian adults

Cited by 22 publications

References 32 publications

Modifications of Midfacial Soft-Tissue Thickness Among Different Skeletal Classes in Italian Children

Modifications of Midfacial Soft-Tissue Thickness Among Different Skeletal Classes in Italian Children

Facial average soft tissue depth variation based on skeletal classes in Indonesian adult population: A retrospective lateral cephalometric study

Prediction of nasal morphology in facial reconstruction: Validation and recalibration of the Rynn method

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