Soft Tissue Facial Changes Research Articles

Soft Tissue Facial Changes Following Massive Weight Loss Secondary to Medical and Surgical Bariatric Interventions: A Systematic Review.

Soft Tissue Facial Changes Following Massive Weight Loss Secondary to Medical and Surgical Bariatric Interventions: A Systematic Review.

Soft tissue facial changes among adult females during alignment stage of orthodontic treatment: a 3D geometric morphometric study

BackgroundTo investigate changes in facial morphology during the first six months of orthodontic treatment among adult females receiving orthodontic treatment.Methods43 adult females receiving orthodontic treatment were randomly recruited. 3D facial images were taken at baseline (T0), three months (T1), and six months (T2) after treatment initiation. Spatially dense facial landmarks were digitized to allow for sufficient details in characterization of facial features. 3D geometric morphometrics and multivariate statistics were used to investigate changes in mean and variance of facial shape and facial form associated with treatment.ResultsWe observed statistically significant changes in facial shape across the three treatment stages (p = 0.0022). Pairwise comparisons suggested significant changes from T0 to T1 (p = 0.0045) and from T0 to T2 (p = 0.0072). Heatmap visualization indicated that the buccal and temporal region were invaginated while the labial region became protruded with treatment. The magnitude of shape change was 0.009, 0.004, and 0.010 from T0 to T1, T1 to T2, and T0 to T2, respectively, in unit of Procrustes distance. The average magnitude of change per-landmark was 1.32 mm, 0.21 mm, and 1.34 mm, respectively. Changes in mean facial form were not statistically significant (p = 0.1143). No changes in variance of facial shape were observed across treatment stages (p > 0.05).ConclusionRate of facial changes was twice as fast during the first three months as that during fourth to sixth month. Buccal and temporal region became invaginated while labial region became protruded with treatment.

Three-dimensional soft tissue analysis of the face following micro-implant-supported maxillary skeletal expansion

BackgroundSkeletal maxillary expander (MSE) is one of the more recent expander designs being utilized for skeletal expansion by splitting the midpalatal sutures applying forces through palatal micro-implants. Its effects on the soft tissue remain a question asked by both patients and clinicians. The aim of this study was to analyze and quantify soft tissue facial changes induced by MSE.Methods3D facial images (3dMD) were used to capture face scans of 25 patients generating 3D soft tissue meshes before expansion (T0), right after expansion (T1), and 1 year in retention (T2). MATLAB was then used, utilizing non-rigid iterative closest point algorithm, to align all samples in vertex correspondence and generate averages. Surface mapping of each average, along with its variance, allows for quantification of changes between the three pools of samples in 3D space.ResultsThe generated 3D p-maps between T0 and T1 demonstrate that statistically significant changes (p < 0.05 and p < 0.01) are localized in the circummaxillary area (paranasal, lips, and both cheeks). Vector map shows a mean displacement of 1.5 mm in the paranasal area. The right cheek showing a mean displacement magnitude of 2.5 mm while the left cheek has a mean of 2.9 mm. Direction of vectors are latero-anterior with more dominant anterior direction.ConclusionsThere are significant changes in paranasal, upper lip, and at both cheeks following expansion using MSE with greater magnitude at the cheeks area. Those changes do not relapse after 1 year (p < 0.05).

Soft Tissue Changes Measured With Three-Dimensional Software Provides New Insights for Surgical Predictions

Although computer-aided craniofacial reconstructions allow for simulation of hard tissue changes, the prediction of the final soft tissue facial changes remains a challenge. The purpose of the present study was to evaluate the 3-dimensional (3D) soft tissue changes in patients undergoing 2-jaw orthognathic surgery. For the present retrospective cohort study, 40 consecutive patients (11 men and 29 women; mean age 23.5±4.9years) who had undergone 2-jaw orthognathic surgery were selected. We obtained the medical and dental records from 3weeks before surgery and 6months after surgery. We used image processing software to segment, superimpose, and quantify the hard and soft tissue displacements in 3 dimensions before and after surgery at 15 paired locations. The soft tissue and hard tissue changes were determined through quantification of homologous landmark displacements between the preoperative and postoperative computed tomography data. We measured the 3D soft and hard tissue changes and the anteroposterior, inferosuperior, and transverse components of the changes. We quantified the ratios between the soft and hard tissue changes, tested Pearson's correlation between these changes, and developed a predictive regression equation for the observations at each location. We found that soft tissue movement followed the hard tissue movement, with a correlation nearly equal to 0.9 (range 0.85 to 0.98), suggesting that in general the soft tissues of the maxillary and mandibular landmarks are affected similarly by the skeletal movements. The anteroposterior component of the soft tissue 3D displacements followed the hard tissue movement with a ratio greater than 0.9 and with high correlation (r>0.9) in the mandible. The results of the present study provide surgeons with a ratio of hard to soft tissue change and the strength of the correlations, which will allow for more accurate 3D predictions for both midline and lateral structures in bimaxillary orthognathic surgical cases. In addition, predictive equations for various landmarks were developed and can be used in computer-based prediction programs to aid in treatment planning of soft tissue changes.

Facial soft-tissue changes after rapid maxillary expansion analyzed with 3-dimensional stereophotogrammetry: A randomized, controlled clinical trial.

To evaluate three-dimensional (3-D) soft tissue facial changes following rapid maxillary expansion (RME) and to compare these changes with an untreated control group. Patients who need RME as a part of their orthodontic treatment were randomly divided into two groups of 17 patients each. Eligibility criteria included having maxillary transverse deficiency with crossbite, and to be in the normal range according to body mass index. In the first group (mean age = 13.4 ± 1.2 years), expansion was performed. The second group received no treatment initially and served as untreated control (mean age = 12.8 ± 1.3 years). Skeletal and soft tissue changes were evaluated using posteroanterior cephalograms and 3-D facial images. The primary outcome of this study was to assess the soft tissue changes. The secondary outcomes were evaluation hard tissue and soft tissue relations. Randomization was done with preprepared random number tables. Blinding was applicable for outcome assessment only. MANOVA, t-test, and correlation analyses were used (P = .05). In both groups, there was a general trend of increase for the transverse skeletal measurements, but these increases were more limited in the control group. Alar base width was greater in the treatment group (P = .002). Pogonion soft tissue point (P = .022) was located more posteriorly in the expansion group compared with the control group. Soft tissue changes between groups were similar, except for the alar base, which became wider in the treatment group. Weak correlations were found between the skeletal and soft tissue changes.

Longitudinal Photogrammetric Analysis of Soft Tissue Facial Changes: A Systematic Review of the Literature and a Summary of Recommendations.

Human faces are under a constant state of change throughout the entirety of one's lifetime. Photogrammetry has been advocated for use in large epidemiological studies investigating facial characteristics. This study aimed to review existing longitudinal photogrammetric studies in terms of the measurements selected and the observed facial changes overtime. A comprehensive literature search was performed in 4 databases, PubMed, ISI Web of Science, EMBASE, and Scopus, which was supplemented by hand search. No limitations were set as to the language, dates, or status of publication. The records were assessed for the eligibility and rated for the risk of bias by 2 independent reviewers. Data regarding study characteristics, measurements selected and the outcomes reported, were extracted for analysis. An initial search identified 5127 studies. After 2 rounds of study screening, 6 eligible studies informed this review. The risk of bias of the studies ranged from 41.7% to 80.8%. Only 1 study performed sample size calculation, and only 17% of the studies had a sample size of over 30 subjects. Confidence interval was reported by none of the studies. The facial features assessed varied among the studies, and some studies focused on only specific regions of the face. Photogrammetry has been used by a limited number of studies in the analysis of longitudinal soft tissue facial changes. Moreover, these studies are heterogeneous with respect to their levels of risk of bias and the facial features assessed. Recommendations are provided to improve the qualities of future photogrammetric studies.

Comparison of three methods of profile change prediction in the adult orthodontic patient

Potential changes in the contour of the facial profile that accompany tooth movement can be important considerations in developing an orthodontic treatment plan. The objective of this study was to compare the accuracy of three different methods of predicting horizontal soft-tissue changes. Eighty-three nongrowing, orthodontically treated patients comprised the sample. Pretreatment and posttreatment lateral cephalometric hard- and soft-tissue landmark points were digitized. A coordinate system was defined, landmark coordinates were corrected for magnification, and then hard- and soft-tissue, angular, and linear measures were calculated by computer programs developed on a DEC PDP 11/44. The accuracy of prediction of soft-tissue landmark changes was compared for three prediction methods: (1) use of ratios of means of soft-tissue changes to corresponding hard-tissue changes, (2) use of a bivariate regression equation on corresponding hard-tissue landmark changes, and (3) use of stepwise multiple regression with hard-tissue changes and initial hard- and soft-tissue facial characteristics as predictor variables. For predicting changes of four soft-tissue points, multiple regression equations were slightly more accurate than ratio of means predictions. The standard errors of the estimate ranged from 0.7 to 1.1 mm for the multiple regression predictions; these were from 0.2 to 1.4 mm lower than those obtained for ratio of means predictions. The accuracy of the bivariate regression prediction technique fell between that of the other two methods. Examination of the residuals showed that the multiple regression equations consistently underpredicted the most extreme soft-tissue facial changes.

Prediction of normal soft tissue facial changes.

Abstract No Abstract Available. Portions of this research were funded by the Pacific Coast Society of Orthodontists and presented in part at the 51st General Meeting, International Association for Dental Research, Washington, D.C.