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 Table of Contents  
ORIGINAL ARTICLE
Year : 2019  |  Volume : 31  |  Issue : 3  |  Page : 194-202

Facial soft tissue thickness in South Indian adults with varied occlusions – A cone beam computed tomography study


Department of Oral Medicine and Radiology, Dayananda Sagar College of Dental Sciences, Bengaluru, Karnataka, India

Date of Submission12-Apr-2019
Date of Acceptance13-Jun-2019
Date of Web Publication30-Sep-2019

Correspondence Address:
Dr. Manasa A Meundi
#695, 15th Cross, II Phase, JP Nagar, Bengaluru - 560 078, Karnataka
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jiaomr.jiaomr_83_19

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   Abstract 


Background: Facial soft tissue (FST) thickness is crucial to reconstruct a recognizable face from an unknown skull. Straight, convex, and concave profiles of the human face in class I, class II, and class III occlusal patterns, respectively, suggest the possibility of skeletal class to have a significant influence on FST thickness of an individual. The aim of this study was to collect and compare FST thickness in South Indian adults based on gender and varied occlusions. Materials and Methods: Cone beam computed tomography scans of 90 South Indian subjects (45 of each gender) age 18–35 years were categorized according to their dentoskeletal relationships as class I (ANB = 2–40), class II (ANB >40), and class III (ANB <20) with 30 subjects in each class and FST thickness at 34 landmarks (12 midline and 11 bilateral) were measured. Results: Significant differences were present at nasion, mid-nasal, rhinion, subnasal, labrale superius, and mid-supraorbital and infra canine in men and at mentolabial sulcus and gonion in women demonstrating variation in soft tissue thickness among different occlusions. In addition, gender-based differences were observed among the skeletal classes with men having thicker tissues at a majority of the measured landmarks. Sexual dimorphism was distinct in skeletal classes I and III occlusal patterns. Conclusion: Dentoskeletal morphology-related variations in FST thickness observed in this study highlight the need for anthropological analysis of the skull focusing on occlusal pattern along with age and sex during facial reconstruction to achieve better results.

Keywords: Cone beam computed tomography, facial profile, facial soft tissue thickness, forensic anthropology, orthodontics, skeletal classes


How to cite this article:
Meundi MA, David CM. Facial soft tissue thickness in South Indian adults with varied occlusions – A cone beam computed tomography study. J Indian Acad Oral Med Radiol 2019;31:194-202

How to cite this URL:
Meundi MA, David CM. Facial soft tissue thickness in South Indian adults with varied occlusions – A cone beam computed tomography study. J Indian Acad Oral Med Radiol [serial online] 2019 [cited 2019 Nov 14];31:194-202. Available from: http://www.jiaomr.in/text.asp?2019/31/3/194/268281




   Introduction Top


Face is the key for recognition and is the primary means to establish the identity of an individual. Forensic investigators therefore recourse to facial reconstruction especially when conventional method of matching postmortem data to the antemortem records turns unsuccessful in identifying human remains.[1]

Facial soft tissue (FST) thickness is a crucial component in forensic facial reconstruction as it beacons the anthropologists to reproduce a face that is detailed enough to be recognizable by the deceased family. Tissue depth markers attached on the skull at specific landmarks during reconstruction process denote the mean FST thickness.[2] Welcker, a German anatomist, was the first to measure soft tissue thickness by inserting a small surgical blade into the cadaveric face.

Over the years, two-dimensional (2D) lateral cephalograms [3],[4],[5] and certain three-dimensional (3D) methods such as ultrasonography,[6] magnetic resonance imaging (MRI),[7] and computed tomography (CT)[8] have enabled FST measurements in the living. Recently developed cone beam computed tomography (CBCT), designed exclusively for maxillofacial imaging, has also been used [9] for measurements as it records the relationship of FSTs and the skull in a 3D plane.[10]

From the embryological initiation around fourth week of intrauterine life until the growth completion, researchers have observed a strong association between the developing soft tissues and the growing facial skeleton.[11],[12],[13] The anatomic relationship of the upper and lower jaws and the arrangement of teeth casts an impact on the thickness, length, and even the tonicity of the FSTs.[13] Significant differences in the facial contour and profile of the individuals with varying skeletal relationship of the maxilla to the mandible have been observed. Angle's categorization of anteroposterior relationship of the jaws into class I, class II, and class III malocclusions have shown straight, convex, and concave facial profiles, respectively.[14]

Earlier studies that have demonstrated the influence of sagittal malocclusions on FST have quantified it using lateral cephalograms [4],[15],[16],[17],[18],[19] which will yield values only along the midline of the face. But 3D reconstruction of the face necessitates measurements of the soft tissue thickness of the entire face which is possible only by 3D imaging methods such as CBCT.

With previous studies revealing ethnic and gender differences in the FST in subjects with different occlusions,[20],[21],[22] it is imperative to establish population- and sex-specific measurements of FST in different occlusal patterns so that the generated data will be helpful in both forensic facial reconstructions and orthognathic surgeries for correction of malocclusion.

The aim of this study was to understand the possibilities of variations in FST thickness among three different skeletal classes in adult South Indian subjects. This study hence recorded FST for adult South Indian subjects having three varied skeletal classes and subsequently compared the relationship between FST thickness and skeletal classes to understand their relationship.


   Materials and Methods Top


This cross-sectional, comparative, and descriptive study was conducted in the Faculty of Dentistry, Rajiv Gandhi University of Health Sciences, Karnataka, India. The study was conducted using CBCT scans that were done for purposes other than that for the study. None of the subjects was exposed to radiation for the purpose of this study. Ethical clearance from the Institutional Research committee was obtained stating the same.

CBCT scans of 90 South Indian subjects were used for the study. The subjects were grouped into three based on their skeletal pattern as skeletal class I, skeletal class II, and skeletal class III. Thirty subjects were chosen under each skeletal pattern. This was based on a conventional statistical assumption that a sample size of 30 or more constitutes a large sample. Equal numbers of males and females were included to avoid bias. Randomly selected CBCT scans of South Indian subjects in the age group of 18–35 years were included in the study. This age group was included as the subjects in this age group would have completed their facial growth spurt phase and would not be undergoing physiological facial changes of aging. Scans done for swellings, trauma, or facial deformities and scans of those subjects undergoing orthodontic treatment were excluded.

Scans were done with subjects in upright posture, teeth in maximum intercuspation, lips relaxed, and Frankfort horizontal (FH) plane parallel to the floor. CBCT scanner (Planmeca ProMa × 3D Mid; Planmeca Oy, Helsinki, Finland) with a voxel size of 0.3–0.4 mm and a field of view of 20 × 17 cm was used. After the procedure, the DICOM (Digital Imaging and Communications in Medicine) formatted sectional images of each subject were imported to On Demand 3D software (Cybermed, Seoul, Korea) in a personal computer and 3D ceph tool of the software was used for all the analyses. 3D ceph tool of the software was used for measuring FSTs since the values of the linear distances are automatically computed by the software.

Once the 3D hard and soft tissue reconstructions along with the 2D images in three orthogonal planes (sagittal, coronal, and axial) were rendered, FH plane (plane intersecting Po and Or) was determined by plotting nasion (midline point on the frontonasal suture), right and left orbitale (Or: most inferior point on the infraorbital rim), and porion (Po: most superior point of the external auditory meatus), and the skull orientation was standardized in all the three (X, Y, Z) axes as shown in [Figure 1]. Subsequently, Steiner ANB angle which indicates the sagittal relationship between the maxilla and mandible and measures the extent of their positional discrepancy was calculated using the angle tool. ANB angle was determined by point A (deepest point on the line between the anterior nasal spine and the prosthion), point N (midline point on the frontonasal suture), and point B (deepest point from the line between infradentale and the pogonion). Based on the ANB angle [Figure 2], subjects were categorized into three skeletal classes: class I (ANB = 2°–4°), class II (ANB >4°), and class III (ANB <2°) with gender equated 30 scans in each group.
Figure 1: Frontal (a) and Profile (b) view of the skull showing the three axes (X, Y and Z) and head position standardized to Frankfurt Horizontal Plane. N: Nasion; Po: Porion; R: Right; L: Left

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Figure 2: Lateral View of the skull showing Skeletal Class I (a); Skeletal Class II (b) and Skeletal Class III (c) occlusions. N: Nasion; A: Point A; B: Point B. Numbers are indicating the ANB angle

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Following this, FST was measured at 34 craniometric landmarks (12 along the midline and 11 each on right and left sides) adopted from Stephan and Simpson.[23] Using the pre-set hard and soft tissue display tool, points on skull surface and their homologous points on the soft tissue outline were marked as defined by Stephan and Simpson.[23] The points at first were located on the reconstructed 3D skull/soft tissue image and then enhanced using two of the three orthogonal sections (coronal–axial or sagittal–axial) depending on their relative position on the skull/skin surface. Once the landmarks were plotted, the linear distance between the two corresponding points was automatically measured by the 3D ceph tool and enlisted [Figure 3]. These are the hard tissue and their corresponding soft tissue landmarks used in this study [Figure 4]: midline landmarks are glabella (g–g′), nasion (n–n′), mid-nasal (mn–mn′), rhinion (rhi–rhi′), subnasal (sn–sn′), mid-philtrum (mp–mp′), labrale superius (ls–ls′), labrale inferius (li–li′), mentolabial sulcus (mls–mls′), pogonion (pg–pg′), gnathion (gn–gn′), and menton (m–m′). Bilateral (R for right and L for left) landmarks are as follows: mid-supraorbital (mso–mso′), mid-infraorbital (mio–mio′), alar curvature point (acp–acp′), gonion (go–go′), zygion (zy–zy′), supra canine (sC–sC′), infra canine (iC–iC′), supra molar 2 (sM 2–sM 2′), infra molar 2 (iM2–iM′2), mid-ramus (mr–mr′), and mid-mandibular border (mmb–mmb′).
Figure 3: Homologous midline landmarks plotted for automatic measurement by 3D ceph tool of the software

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Figure 4: Three-dimensional reconstructions of the skull and the face. a) Hard tissue Landmarks depicted on the skull surface - Midline: glabella (g); nasion (n); midnasal (mn); rhinion (rhi); subnasal (sn); midphiltrum (mp); labrale superius (ls); labrale inferius (li); mentolabial sulcus (mls); pogonion (pg); gnathion (gn); menton (m). Lateral: mid supraorbital (mso); mid infraorbital (mio); alare curvature point (acp); gonion (go); zygion (zy); supra canine (sC); infra canine (iC); supra molar 2 (sM2); infra molar 2 (iM2); mid ramus (mr) and mid mandibular border (mid-mandibular border). b) corresponding Soft Tissue Landmarks depicted on the soft tissue surface having same abbreviations but with 'dash' superscripted

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Data were analyzed using SPSS version 18.3.2.2 and general descriptive statistics were calculated for all the measured FSTs among the three skeletal classes and independently for both the sexes. Measurements were repeated in 30 randomly chosen CBCT scans by a single observer at 4-week interval and the values of both the sets were compared using Cronbach's alpha to assess intra observer reliability. Facial asymmetry was assessed by comparing the soft tissue thickness values of the right and left sides using two-tailed dependent Student's t-test. Since the results yielded no significant differences in most of the landmarks, measurements of only the right side were considered for further analysis. Analysis of variance followed by post hoc Tukey's test was done for comparing the soft tissue thickness among the skeletal classes in each sex. Gender differences in FSST for each skeletal class were calculated using two-tailed independent Student's t-test. The power of the study was set at 80% with 0.05 as level of significance.


   Results Top


[Figure 5] shows that 67% of the study subjects were in the age group of 20–30 years. Chi-square test (P = 0.682) showed that the samples were age-matched among the three skeletal classes. [Table 1] describes the result of reliability test, Cronbach's alpha which is an indicator of internal consistency. A value of 0.8 and above for all the three skeletal classes indicates good consistency and reliability.
Figure 5: Ages of subjects among the three skeletal classes

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Table 1: Test for intraobserver variability using Cronbach's alpha

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[Table 2] summarizes the means of right and left-side measurements and their comparison in each skeletal class. The majority of the bilateral landmarks displayed no significant difference in the soft tissue thickness and none at all in skeletal class II. Differences were significant at the points mid-supraorbital, infra-M2, mid-ramus, and mid-mandibular border in skeletal class I and at mid-supraorbital and alar curvature point in class III. Only at those points, the absolute difference in mm (which is the arithmetic difference between right and left mean soft tissue thickness values) and relative difference (percentage of the absolute difference by mean average of the right and left value) was manually calculated. The absolute mean was as low as 0.35 mm (at alar curvature point in class I) and the relative mean difference did not exceed 6.6%. The maximum absolute mean difference was recorded for mid-ramus (0.7 mm) in skeletal class I; the relative mean difference was 3.7%.
Table 2: Comparison of bilateral facial soft tissue thickness measurements in each skeletal class

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[Table 3] shows descriptive statistics of soft tissue thickness at all the points (12 midline and 11 right side) for each skeletal class among men. The least values were found at rhinion and mid-infraorbital (class II); the greatest thickness was at labrale inferius (class II) and supra M 2 (class I). Values showed significant differences among classes in the nose and upper lip regions with most significant difference at labrale superius (P = 0.003) all of which had greatest thickness in skeletal class. At points glabella, subnasale, mid-philtrum, and menton, highest values were found in skeletal class III with significant difference only at subnasale. In class II, soft tissues were the thickest areas corresponding to the lower lip and chin regions. At bilateral measurement points, greatest values were found in class I at all the points except at infra canine and zygion which were highest in class II and class III, respectively. The thinnest tissues were found in skeletal class II. However, the thickness was significantly different only at mid-supraorbital and infra canine. Considering the overall FST, the values were greatest in skeletal class I and lowest in class II at most of the points with class III values ranging between them.
Table 3: Comparison of facial soft tissue thickness for males among three skeletal classes

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[Table 4] shows descriptive statistics of FST in women for each skeletal class. Similar to men, the greatest thickness was seen at labrale inferius and supra M2 (in class II) and least values were found at rhinion and mid-infraorbital in class II and class I, respectively. Along the midline, soft tissues were thickest in class II at lower lip, chin, and upper third regions of the face (glabella, nasion, and mid-nasal), whereas they were thinnest in class III at glabella, mid-nasal, mid-philtrum, labrale superius, and labrale inferius. At chin region, the tissues were thinnest in class I. However, significant difference was noted only at mentolabial sulcus between classes II and III. On comparison of bilateral soft tissue thickness, greatest values were found in class II at all the points except at supra canine and zygion which were highest in class I and class III, respectively. This pattern was similar to that observed in men. Soft tissues were thinnest in skeletal class I at all the points (except gonion, supra canine, and supra M2) in contrast to what was observed in men where it was found thinnest in class II. However, the differences in the thickness were significant only at gonion where soft tissue was thicker at class II when compared with class III. On considering the overall FST, the values were greatest in skeletal class II and lowest in class I with class III values ranging between them at most of the points, a pattern opposite to what was found among men.
Table 4: Comparison of facial soft tissue thickness for females among three skeletal classes

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[Table 5] describes the male and female characteristics of FST in each skeletal class. Soft tissues were thicker in men at all the measured points in class I except at zygion with similar trend in class III except at points rhinion, mid-infraorbital, and zygion where soft tissue was thicker in women. In fact at zygion, soft tissue was thickest in women of all skeletal classes. However, in skeletal class II malocclusion, there was a reversal in pattern with women having thicker soft tissues than men at most of the points (mid-nasal, menton, mid-infraorbital, gonion, zygion, supra M 2, infra M2, mid-ramus, and mid-mandibular border). The most significant difference between men and women was noted at points subnasale, mid-philtrum, labrale superius, and labrale inferius among all the three skeletal classes (except at labrale superius in class II) with largest values in men. Significant sex-based differences in skeletal classes I and III were noted at glabella, nasion, and mid-nasal, whereas in class I, men differed from women only at rhinion and gnathion and in class III, they differed at mentolabial sulcus and pogonion. Along the sides of the face, sexual dimorphism was significant in all the skeletal classes only at the point supra canine. At the points mid-supra orbital and alar curvature point, the differences in sex were observed only in class I and class III. Significant sexual dimorphism in class I and class II alone was seen at infra canine and zygion, respectively.
Table 5: Sex differences in facial soft tissue thickness for each skeletal class

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   Discussion Top


FSTs play a significant role in forensic science, anthropology, plastic surgery, and in dentistry as they provide basis for quantification and repeatability.[23] The majority of the soft tissue thickness data have originated from lateral cephalograms as observed by Stephan and Simpson in their analytical review.[23]

Variations in FST among different skeletal occlusal patterns are commonly assessed using lateral cephalometric radiographs [17],[20],[21] as it reveals soft tissue profile along with the skull surface thus facilitating soft tissue thickness measurements. Since it is also a standard diagnostic radiograph in orthodontic therapy, large data will be available at dental schools for making comparisons. However, lateral cephalograms provide only midline soft tissue thickness measurements, whereas thicknesses across the face are necessary for reconstructing a face to a recognizable degree, at least at 11 bilateral landmarks as proposed by Stephan and Simpson.[23]

CBCT facilitates measuring the soft tissues of the entire face. With volumetric reconstructions, it allows to understand the craniofacial relationships objectively in all the three dimensions. It is less expensive than CT and MRI, reliable, and accurate. The generated images are devoid of magnification errors and superimpositions of structures unlike lateral cephalograms. This study is perhaps the foremost to use CBCT as a method of measurement for the evaluation of soft tissue thickness in varied occlusions.

Age and sex have a proven impact on FST. Progressive increase in thickness occurs in children until growth ceases around 18 years after which it plateaus upto 40 years.[6],[24] Subjects in this study were therefore in the age range of 18–35 years to eliminate their influence on the results. Similarly, the effect of sex was removed by choosing equal number of men and women in each group.

Researchers in previous studies have either averaged the FST values of bilateral landmarks or have measured on only one side.[6],[25] In this study, measurements of both right and left sides of the face were done. Although significant differences were found at some landmarks, their absolute differences were as low as 0.5–1.2 mm. Presuming that such negligible differences may not make noticeable variations in the reconstructed face, only right-side measurements among the two were considered for the analyses.

In men, the soft tissue thickness values of skeletal class I ranged between class II and class III at subnasale, mid-philtrum, and labrale inferius. Same tendency was noted in women also. This observation was similar to the findings in Japanese population. In both sexes, soft tissue thickness from labrale superius to pogonion was greater in class II than in class III indicating an inverse relationship of skeletal occlusion to soft tissues,[26] that is, overgrown maxilla in class II that results in a convex profile possesses thicker tissues over the mandible, whereas tissue thickness decreases as mandible grows ahead of maxilla as in class III situations. Greater thickness was found to be present on the side opposite of the region of overgrowth. The trend was similar in the canine region represented by the points supra canine and infra canine; upper part of the face (at mid-supraorbital, mid-infraorbital, and alar curvature point) and mandibular regions represented by the points infra-M2, gonion, mid-ramus, and mid-mandibular border. But this pattern was noted only in men. Since this study is perhaps the first to compare bilateral soft tissue thickness among varied occlusions, the results could not be related with studies done on other population.

Significant differences noted between classes I and II at subnasale and labrale superius of men are in agreement with studies on Turkish,[21] Central Anatolians,[17] and Sudanese population.[19] Significant difference noted at labrale superius of class III is in agreement with findings of Kamak and Celikoglu [15] who implied that the labially tipped mandibular central incisor in class III would force protrude the upper lip thus affecting its thickness along with position. Utsuno et al.[20] opined that soft tissues that adhere snugly to the underlying bone do not differ between skeletal classes. Contrary to this, the current study showed significant differences at points nasion, mid-nasal, and rhinion.[21] Dumont observed that soft tissue thickness at gnathion decreases with increasing mandibular protrusion resulting in thinner tissue in class III than class II.[26] Although not significant, gnathion values in men indicated the same in the current study. The differences noted in women of this study match with Japanese [20] and Sudanese [19] women; however, they had significant differences at subnasale, labrale superius, stomion, and pogonion as well.

Sex-based differences at points subnasale, mid-philtrum, labrale superius, labrale inferius, and supra canine noted in this study in all skeletal classes are in agreement with most of the studies.[15],[17],[19],[20],[21],[26] Both classes I and III showed sex differences at glabella, nasion, mid-nasal, mid-supraorbital, and alar curvature point similar to a study by Kurkcuoglu et al.[21] In this study, sex-related differences were found in forehead (glabella and mid-supra orbital), nose (nasion, mid-nasal, rhinion, and alar curvature point), upper lip (subnasale, mid-philtrum, and labrale superius), lower lip (labrale inferius), chin (gnathion), and canine (supra canine and infra canine) regions of skeletal class I. Utsuno et al.,[20] however, noted sex-related differences only in the upper lip region. In this study, sex-related differences were not observed at menton, mid-infraorbital, supra M2, and all the points of the mandibular region in the three skeletal classes.

In classes I and III, men had thicker tissues than women except at zygion, rhinion and mid-infraorbital where women had negligibly thicker soft tissues. In skeletal class II however, women had greater thickness over men at most of the points on the sides of the face (mid-infraorbital, zygion, supra M2, infra-M2, go, mid-ramus, and mid-mandibular border) as well as at mid-nasal and menton along the midline. In general, men have thicker FSTs than women, but this imbalance is well-expressed only in a balanced class I profile. However, such differences fade in skeletal class II and class III in an attempt of soft tissue adaptation to the developing malocclusion.[21]

The present study data have been simplified for its application in facial reconstruction of South Indian males and females while respecting their skeletal occlusion patterns. Sex-specific soft tissue thickness values of three skeletal classes have been averaged at points, no statistically significant differences were observed, and the values for individual class have been retained at the points having significant differences [Table 6].
Table 6: Recommended mean facial soft tissue thickness for South Indian adults with skeletal classes

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Certain limitations foreshadowed this study. FST differences noted at bilateral landmarks could not be compared with the literature as there are none available yet. Similarly, this study data could not be statistically compared with other population studies since the examination methods differed. Although body mass index of an individual may affect the FST,[3] its influence as a confounding factor could not be controlled due to limited subject availability. Finally, this study has not recorded FST in vertical growth patterns even though variations along different vertical facial forms does exist.[27],[28] Future focus of the authors therefore would be to evaluate FST involving a combination of these variables using CBCT.


   Conclusion Top


This study which provides FST at both midline and bilateral points has shown variations among different occlusal patterns at all the facial regions. Men with class I and women with class II had thicker FSTs. The FST differences predominated in lower face of both genders (at subnasale, labrale, superius and infra canine in men and at mentolabial sulcus and gonion in women) in addition to upper face noted exclusively in men (at nasion, mid-nasal, rhinion, and mid-supraorbital points). Sex-related differences were predominant in the upper and lower lip regions (at subnasale, mid-philtrum, labrale superius, and labrale inferius) in each skeletal class apart from other facial regions except over the mandible (at infra-M2, gonion, mid-ramus, and mid-mandibular border). Sexual dimorphism that was evident in skeletal class I malocclusion diminished with class II and class III and lost its significance. However, the differences in FST among the skeletal classes were subtle in contrast to the marked sex-based differences noted.

The results of this study emphasize that there is a definite need for determining the occlusion type of the skull along with identification of the gender of the skull before the start of facial remodeling so that a more reliable face is reconstructed. This will further help hasten the identification of the unidentified skull after the forensic facial reconstruction. Apart from this, the soft tissue differences among skeletal types will also be helpful during the diagnosis and treatment planning of living subjects who will be undergoing orthognathic and plastic surgeries.

Acknowledgement

The authors are grateful to Cybermed Inc. (Seoul, Korea) for extending their continual support by providing access to OnDemand3D software for this research work.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
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    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]



 

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