Changes in buccal facial depth of female patients after extraction and nonextraction orthodontic treatments: A preliminary study

Using a structured light scanner to evaluate 3-dimensional soft-tissue changes after extracting 4 premolars in young adult female patients

INTRODUCTION

Facial esthetics have always received much attention in orthodontic treatment, especially in young adult female patients. Three-dimensional (3D) soft-tissue changes after orthodontic extraction have not been fully explained. This study evaluated the 3D morphologic changes after orthodontic extraction in young female patients using a structured light scanner.

METHODS

Forty-five adult female patients aged 20-25 years were enrolled in our study. The treatment group consisted of patients who received orthodontic treatment with 4 premolar extractions, and the control group was composed of young female volunteers who had not undergone any orthodontic treatment. To monitor the soft-tissue changes, 9 morphologic regions and 12 landmarks were identified for the 3D deviation analyses. The spatial deviations of landmarks and regions in the x, y, and z directions were constructed for quantitative analysis. Color map images were constructed to visualize soft-tissue displacement as a qualitative evaluation. The paired sample test was used to compare differences at the beginning of the experiment (T0) and after 24 months (T1) in both groups. An independent t test with Bonferroni correction was performed to compare differences between the treatment and control groups. A linear regression test was performed between incisor retraction and changes in the perioral tissues.

RESULTS

Subtracting the effect of aging from the lip changes in the control group, the treatment group showed a statistically significant difference in the displacement of labrale superius (-1.37 mm), labrale inferius (-1.89 mm), the upper lip region (-0.98 mm), and the lower lip region (-1.36 mm) along the z-axis. No significant differences were found between the treatment and control groups in the temporal, parotideomasseteric, and buccal regions. Pearson correlation tests indicated a positive correlation between incisor tip retraction and changes in soft tissues (two-dimensional cephalometric analysis, 3D landmark measurements, and 3D regional measurements). The correlation coefficient ranged between 0.45 and 0.55.

CONCLUSIONS

Three-dimensional soft-tissue changes were mainly concentrated in the upper and lower lip regions in adult female patients after the 4 premolars were extracted. For female patients aged 20-25 years with 4 extracted premolars, soft-tissue changes in the temporal, parotideomasseteric, and buccal regions were not clinically significant.

Automatic Masseter Muscle Accurate Segmentation from CBCT Using Deep Learning-Based Model

Segmentation of the masseter muscle (MM) on cone-beam computed tomography (CBCT) is challenging due to the lack of sufficient soft-tissue contrast. Moreover, manual segmentation is laborious and time-consuming. The purpose of this study was to propose a deep learning-based automatic approach to accurately segment the MM from CBCT under the refinement of high-quality paired computed tomography (CT). Fifty independent CBCT and 42 clinically hard-to-obtain paired CBCT and CT were manually annotated by two observers. A 3D U-shape network was carefully designed to segment the MM effectively. Manual annotations on CT were set as the ground truth. Additionally, an extra five CT and five CBCT auto-segmentation results were revised by one oral and maxillofacial anatomy expert to evaluate their clinical suitability. CBCT auto-segmentation results were comparable to the CT counterparts and significantly improved the similarity with the ground truth compared with manual annotations on CBCT. The automatic approach was more than 332 times shorter than that of a human operation. Only 0.52% of the manual revision fraction was required. This automatic model could simultaneously and accurately segment the MM structures on CBCT and CT, which can improve clinical efficiency and efficacy, and provide critical information for personalized treatment and long-term follow-up.

Validity and reliability of masseter muscles segmentation from the transverse sections of Cone-Beam CT scans compared with MRI scans

BACKGROUND

To evaluate the validity and reliability of cone-beam computed tomography (CBCT) masseter muscle segmentation by comparing with the magnetic resonance imaging (MRI) masseter muscle segmentation of the same patients.

METHODS

Seventeen volunteers were included in this study. CBCT and MRI scans of the volunteers were taken, respectively, within one month. The masseter muscles in the CBCT scans were segmented by a generative adversarial network (GAN)-based framework combined with manual check. The masseter muscles in the MRI scans were segmented manually. The segmentations were repeated by the first examiner and a second examiner. For cross-sectional area (CSA), paired t-test, intraclass correlation coefficient (ICC) and standard error of measurement (SEM) were calculated to evaluate the validity and reliability of the segmentations. The validity and reliability were also calculated by Dice similarity coefficient (DSC) and average Hausdorff distance (aHD) between different segmentations. Seventeen volunteers were included in this study. CBCT and MRI scans of the volunteers were taken, respectively, within one month. The masseter muscles in the CBCT scans were segmented by a generative adversarial network (GAN)-based framework combined with manual check. The masseter muscles in the MRI scans were segmented manually. The segmentations were repeated by the first examiner and a second examiner. For cross-sectional area (CSA), paired t-test, intraclass correlation coefficient (ICC) and standard error of measurement (SEM) were calculated to evaluate the validity and reliability of the segmentations. The validity and reliability were also calculated by Dice similarity coefficient (DSC) and average Hausdorff distance (aHD) between different segmentations.

RESULTS

Paired t-test showed that there was no significant difference in CSA between CBCT and MRI masseter segmentations. The ICCs were all larger than 0.95 and the SEM was less than 4.85 mm² for CSA. The DSC was all larger than 0.95 showing over 95% of similarity between CBCT and MRI masseter segmentations. The aHD was all smaller than 0.09 mm showing great consistency of the contour of CBCT and MRI segmentations.

CONCLUSION

Masseter muscle segmentation from CBCT scans was not significantly different from the segmentation from MRI scans. CBCT muscle segmentation showed great validity compared with MRI scans, and great reliability in retests.

Thickness change of masseter muscles and the surrounding soft tissues in female patients during orthodontic treatment: a retrospective study

BACKGROUND

Facial esthetics is a major concern of orthodontic patients. This study aims to evaluate orthodontic treatment-related thickness changes of the masseter muscles and surrounding soft tissues and the potential factors that would influence these changes during orthodontic treatment in female adults.

METHODS

Forty-two female adult patients were included in this retrospective study and were divided into extraction (n = 22) and nonextraction (n = 20) groups. Pretreatment and posttreatment cone-beam computed tomography (CBCT) images were superimposed and reconstructed. The thickness changes of the masseter area of facial soft tissue (MAS), masseter muscles (MM) and surrounding fat tissue (FT) were measured. Pretreatment age, treatment duration, sagittal relationship (ANB), and vertical relationship (Frankfort-mandibular plane angle, FMA)-related MAS, MM and FT changes were compared between extraction and nonextraction groups. Spearman's correlation coefficient was calculated between the above variables. Regression analysis was conducted to confirm the causal relations of the variables.

RESULTS

The thickness of MAS and MM significantly decreased in both groups, with larger decreases (> 1 mm) in the extraction group. There were strong correlations (r > 0.7) between the thickness decrease in MAS and MM in both groups and moderate correlations (r > 0.4) between MAS and FT in the nonextraction group. A significantly greater decrease of MAS and MM were found to be moderately correlated with a smaller FMA (r > 0.4) in the extraction group. Scatter plots and regression analysis confirmed these correlations.

CONCLUSIONS

Masseter muscles and the surrounding soft tissue exhibited a significant decrease in thickness during orthodontic treatment in female adults. Low-angle patients experienced a greater decrease in soft tissue thickness in the masseter area in the extraction case. But the thickness changes were clinically very small in most patients.

Orthodontic incisor retraction caused changes in the soft tissue chin area: a retrospective study

BACKGROUND

To investigate the area and morphological changes around the soft tissue chin after orthodontic incisor retraction.

METHODS

Fifty-nine female adults with bimaxillary protrusion requiring extraction of four premolars were included in the study. Cephalograms were taken before (T0) and after (T1) orthodontic treatment. The soft tissue changes, including the area, thickness and morphology were measured. Paired-t tests were performed for statistical comparisons. Pearson correlation analyses and backward multivariate regression analyses were used to identify the relationship between the soft tissue changes and incisor retraction.

RESULTS

Following the incisor retractions (5.35 ± 1.79 mm and 4.42 ± 1.62 mm for the upper and lower, respectively), there was a significant increase in the soft tissue thickness of L1c-LL (0.64 ± 1.67 mm, P = 0.025) and Pog-Pog' (0.44 ± 1.10 mm, P = 0.022), and a significant decrease in the soft tissue thickness of B-B' (1.21 ± 1.34 mm, P <  0.01). Changes in the area of soft tissue chin and lower lip were not statistically significant (P > 0.05). Pearson coefficient between the thickness changes of B-B' and the retraction of lower incisors was - 0.376. The multiple correlations between the soft tissue thickness changes and incisor retractions were Y = 1.02-0.42a + 0.42b for L1c-LL, and Y = 0.17-0.31b for B-B'.

CONCLUSIONS

The orthodontic incisor retraction could cause soft tissue thickness changes (i.e. an increase in L1c-LL and Pog-Pog' and a decrease in B-B') without area changes.

Short-term impact of microimplant-assisted rapid palatal expansion on the nasal soft tissues in adults: A three-dimensional stereophotogrammetry study

Objective

The aim of this study was to evaluate changes in the nasal soft tissues, including movements of landmarks, changes in linear distances, and volumetric changes, using three-dimensional (3D) stereophotogrammetry after microimplant-assisted rapid palatal expansion (MARPE) in adult patients.

Methods

Facial data were scanned using a white light scanner before and after MARPE in 30 patients. In total, 7 mm of expansion was achieved over a 4-week expansion period. We determined 10 soft tissue landmarks using reverse engineering software and measured 3D vector changes at those points. In addition, we calculated the distances between points to determine changes in the width of the nasal soft tissues. The volumetric change in the nose was also measured.

Results

All landmarks except pronasale and subnasale showed statistically significant movement on the x-axis. Pronasale, subnasale, alar right, and alar left showed significant movement on the y-axis, while all landmarks except subnasale showed significant movement on the z-axis. The alar base width, alar width, and alar curvature width increased by 1.214, 0.932, and 0.987 mm, respectively. The average volumetric change was 993.33 mm³, and the amount of increase relative to the average initial volume was 2.96%.

Conclusions

The majority of soft tissue landmarks around the nasal region show significant positional changes after MARPE in adults. The nose tends to widen and move forward and downward. The post-treatment nasal volume may also exhibit a significant increase relative to the initial volume. Clinicians should thoroughly explain the anticipated changes to patients before MARPE initiation.