Superimposition of serial 3-dimensional facial photographs to assess changes over time: A systematic review

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.

Facial asymmetry and midsagittal plane definition in 3D: A bias-free, automated method

Symmetry is a fundamental biological concept in all living organisms. It is related to a variety of physical and social traits ranging from genetic background integrity and developmental stability to the perception of physical appearance. Within this context, the study of human facial asymmetry carries a unique significance. Here, we validated an efficient method to assess 3D facial surface symmetry by best-fit approximating the original surface to its mirrored one. Following this step, the midsagittal plane of the face was automatically defined at the midpoints of the contralateral corresponding vertices of the superimposed models and colour coded distance maps were constructed. The method was tested by two operators using facial models of different surface size. The results show that the midsagittal plane definition was highly reproducible (maximum error < 0.1 mm or°) and remained robust for different extents of the facial surface model. The symmetry assessments were valid (differences between corresponding bilateral measurement areas < 0.1 mm), highly reproducible (error < 0.01 mm), and were modified by the extent of the initial surface model. The present landmark-free, automated method to assess facial asymmetry and define the midsagittal plane of the face is accurate, objective, easily applicable, comprehensible and cost effective.

Validation of three-dimensional facial imaging captured with smartphone-based photogrammetry application in comparison to stereophotogrammetry system

Statement of problem

The development of facial scanners has improved capabilities to create three-dimensional (3D) virtual patients for accurate facial and smile analysis. However, most of these scanners are expensive, stationary and involve a significant clinical footprint. The use of the Apple iPhone and its integrated "TrueDepth" near-infrared (NIR) scanner combined with an image processing application (app) offers the potential to capture and analyze the unique 3D nature of the face; the accuracy and reliability of which are yet to be established for use in clinical dentistry.

Purpose

This study was designed to validate both the trueness and precision of the iPhone 11 Pro smartphone TrueDepth NIR scanner in conjunction with the Bellus3D Face app in capturing 3D facial images in a sample of adult participants in comparison to the conventional 3dMDface stereophotogrammetry system.

Material and methods

Twenty-nine adult participants were prospectively recruited. Eighteen soft tissue landmarks were marked on each participant's face before imaging. 3D facial images were captured using a 3dMDface system and the Apple iPhone TrueDepth NIR scanner combined with the Bellus3D Face app respectively. The best fit of each experimental model to the 3dMD scan was analyzed using Geomagic Control X software. The root mean square (RMS) was used to measure the "trueness" as the absolute deviation of each TrueDepth scan from the reference 3dMD image. Individual facial landmark deviations were also assessed to evaluate the reliability in different craniofacial regions. The "precision" of the smartphone was tested by taking 10 consecutive scans of the same subject and comparing those to the reference scan. Intra-observer and inter-observer reliabilities were assessed using the intra-class correlation coefficient (ICC).

Results

Relative to the 3dMDface system, the mean RMS difference of the iPhone/Bellus3D app was 0.86 ± 0.31 mm. 97% of all the landmarks were within 2 mm of error compared with the reference data. The ICC for intra-observer reproducibility or precision of the iPhone/Bellus3D app was 0.96, which was classified as excellent. The ICC for inter-observer reliability was 0.84, which was classified as good.

Conclusions

These results suggest that 3D facial images acquired with this system, the iPhone TrueDepth NIR camera in conjunction with the Bellus3D Face app, are clinically accurate and reliable. Judicious use is advised in clinical situations that require high degrees of detail due to a lack of image resolution and a longer acquisition time. Generally, this system possesses the potential to serve as a practical alternative to conventional stereophotogrammetry systems for use in a clinical setting due to its accessibility and relative ease of use and further research is planned to appraise its updated clinical use.

Three-dimensional morphometric analysis of facial units in virtual smiling facial images with different smile expressions

PURPOSE

Accuracy of image matching between resting and smiling facial models is affected by the stability of the reference surfaces. This study aimed to investigate the morphometric variations in subdivided facial units during resting, posed and spontaneous smiling.

MATERIALS AND METHODS

The posed and spontaneous smiling faces of 33 adults were digitized and registered to the resting faces. The morphological changes of subdivided facial units at the forehead (upper and lower central, upper and lower lateral, and temple), nasal (dorsum, tip, lateral wall, and alar lobules), and chin (central and lateral) regions were assessed by measuring the 3D mesh deviations between the smiling and resting facial models. The one-way analysis of variance, Duncan post hoc tests, and Student's t-test were used to determine the differences among the groups (α = .05).

RESULTS

The smallest morphometric changes were observed at the upper and central forehead and nasal dorsum; meanwhile, the largest deviation was found at the nasal alar lobules in both the posed and spontaneous smiles (P < .001). The spontaneous smile generally resulted in larger facial unit changes than the posed smile, and significant difference was observed at the alar lobules, central chin, and lateral chin units (P < .001).

CONCLUSION

The upper and central forehead and nasal dorsum are reliable areas for image matching between resting and smiling 3D facial images. The central chin area can be considered an additional reference area for posed smiles; however, special cautions should be taken when selecting this area as references for spontaneous smiles.

Reproducibility of Three-Dimensional Volumetric Measurement of Periocular Tumor Models

INTRODUCTION

In this study, we measured the volume of customized tumor models in the periocular area using three-dimensional (3D) stereophotogrammetry and evaluated the reproducibility of these measurements.

METHODS

Five tumor models of different colors and sizes were placed in different periocular positions, and 3D facial images were obtained from 68 healthy adult volunteers. Subsequently, the volumes of the tumor models were measured, and the intra- and interrater reproducibility was assessed.

RESULTS

The gray 6 mm model revealed the highest reliable measurements in both Caucasians (intra- and interrater intraclass correlation coefficients of 0.981 and 0.899, mean absolute difference of 1.446 and 3.327 mm³, relative error measurement of 3.497% and 8.120%, technical error of measurement of 1.450 and 3.105 mm³, and relative technical error of measurement of 3.506% and 7.580%) and Asians (0.968 and 0.844, 1.974 and 4.067 mm³, 4.772% and 9.526%, 2.100 and 4.302 mm³, and 5.076% and 10.076%, respectively). The highest reliability of measurements in the lateral upper eyelid (0.88 and 0.95, 4.042 and 3.626 mm³, 9.730% and 9.020%, 5.714 and 3.358 mm³, and 9.730% and 8.350%, respectively) and medial upper eyelid (0.81 and 0.89, 4.313 and 4.226 mm³, 9.730% and 9.020%, 6.098 and 4.069 mm³, and 9.730% and 8.350%, respectively) with eyes closed was evident in Caucasians, while the same trend (0.841 and 0.815, 2.828 and 3.757 mm³, 9.860% and 9.840%, 4.052 and 4.308 mm³, and 9.860% and 9.740%, respectively) was observed in Asians in the medial canthus with eyes closed.

CONCLUSIONS

This study confirms, for the first time, the high reliability of periocular tumor volume measurements using 3D stereophotogrammetry, suggesting its feasibility for eyelid tumor measurement. Further trials are required to investigate its clinical use for documentation and follow-up of different eyelid tumors.