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24 January 2025

Reproducibility and Accuracy of Two Facial Scanners: A 3D In Vivo Study

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,
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and
1
Department of Orthodontics, University of Ferrara, 44121 Ferrara, Italy
2
School of Dentistry, University of Ferrara, 44121 Ferrara, Italy
*
Author to whom correspondence should be addressed.
Appl. Sci.2025, 15(3), 1191;https://doi.org/10.3390/app15031191
This article belongs to the Special Issue Advances in Orthodontic Diagnosis and Treatment: Methods and Applications
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Abstract

Aim: This study aimed to compare the accuracy and reproducibility of the EinScan H2 (SHINING 3D, Hangzhou, China) with the Vectra M3 3D Imaging System (Canfield Scientific, Parsippany, NJ, USA) and with direct anthropometric measurements. Methods: Twenty subjects were scanned with two different facial scanning systems. Linear measurements were compared with direct anthropometric measurements taken on the patient’s face, while area analysis (forehead, tip of the nose, chin, right and left cheek) was performed by overlaying scans after best-fit alignment using the Geomagic Control X v2020.1.1 program. Statistical analysis was conducted using IBM SPSS v28 software, except for the power analysis, which was conducted using R v4.2.1. Results: The intraclass correlation coefficient (ICC) showed high repeatability for both the linear and point measurements, with all values exceeding 0.90. The paired-sample Wilcoxon test revealed no significant differences (p > 0.05) between the linear measurements, indicating consistency across the three measurement methods. Point analysis using the single-sample Wilcoxon test also showed no significant differences (p > 0.05) in the median values. The differences between the two scanning instruments for cephalometric points ranged from 0.5 mm to −0.5 mm, except for the subnasal point (0.73 mm). Over 70% of the surface areas analyzed showed overlapping within the highly reproducible range (0.5 mm to −0.5 mm). Conclusion: Both scanning systems investigated in this study proved to be accurate and reliable for capturing 3D images of the patient’s face.

1. Introduction

In the medical field, including in orthodontics and maxillofacial surgery, the application of three-dimensional (3D) imaging techniques has significantly expanded in recent years [1].
Several technologies now enable the creation of three-dimensional (3D) facial models, using methods like computed tomography or cone beam computed tomography data, stereophotogrammetry, and laser or structured light scanning, replacing traditional 2D analysis and allowing for detailed measurement and comparison of surface areas, volumes, and angles [2,3,4].
The literature shows that 3D facial scanners are highly precise and accurate, making them ideal for dentistry [5,6,7], by improving the evaluation and planning of orthodontic treatments and enhancing communication between orthodontists and surgeons [8,9,10].
Particularly, 3D photogrammetry shows promise in orthodontic fields by allowing the analysis of frontal views with the ability to rotate, translate, and zoom, thereby facilitating realistic analyses and treatment outcome predictions [11].
Moreover, the development of these new acquisition technologies has made it possible to capture high-quality images useful for landmark detection, replacing cone beam computed tomography (CBCT). In this way, sequential frames can be obtained while limiting radiation exposure for the patient [12].
In a previous study, Pellitteri et al. compared the accuracy of three face scanners with different acquisition systems and showed that all proved to be effective in capturing 3D images of the face. Area overlaps analysis between the scanners confirmed the accuracy of all the systems, with more than 90% of each area analyzed falling within the reproducible band (from 1.5 to −1.5 mm) [13].
However, the analysis of superimpositions conducted in the literature revealed the presence of areas that were more reproducible than others, with higher accuracy in the middle and lower regions of the face [14]. Indeed, the forehead is the least reproducible, with an average overlap percentage varying from 11% to 50% in the highly reproducible band (0.5 mm to 0 mm and 0 mm to −0.5 mm). The right and left cheeks, instead, had the highest average value (almost 60%) of the surface in the highly reproducible category, followed by the tip of the nose and the chin (around 55%) [9,13].
Three-dimensional (3D) photogrammetry is widely available through various imaging systems. Leveraging the safety of LED white light, numerous devices have emerged, varying in cost, capture methods, hardware, and software. These systems provide an efficient way to acquire high-resolution surface data quickly, making them particularly advantageous for young or developmentally impaired subjects [14].
There are two types of devices that utilize LED white light based on the method of data capture: stereophotogrammetry and structured light systems. Digital stereophotogrammetry stands out as one of the most frequently employed technologies for three-dimensional (3D) facial surface imaging. However, the structured light system method also provides high-resolution 3D geometry measurements together with a relatively high measurement speed and accuracy [15].
In the last few years, the use of smartphones in conjunction with artificial intelligence has become commonplace in orthodontics, allowing the clinician to benefit from their accessibility, affordability, and practicality. Consequently, 3D imaging systems for smartphones are now widely used in medical and health fields due to improved camera capabilities. However, what has emerged is that the average accuracy of smartphones is lower (from 0.460 to 1.400 mm) compared to that of stationary stereophotogrammetry devices (from 0.087 to 0.860 mm) and portable scanners (from 0.150 to 0.849 mm) [16].
Thus, given the importance of 3D cephalometric areas and points analysis in orthodontics, this study aimed to compare the accuracy and reproducibility of two 3D imaging devices and direct anthropometric measurements.
The first system, the EinScan H2 (SHINING 3D, Hangzhou, China), is a hybrid LED and infrared light source 3D scanner with a 5MP resolution texture camera, accuracy up to 0.05 mm, ultra-wide FOV and adjustable working distance, and three infrared VCSEL projectors for more photorealistic textures and better-quality data.
The second one is the previously validated Vectra M3 3D Imaging System (Canfield Scientific, Parsippany, NJ, USA) [17]. It is a static stereophotogrammetric device that captures three shots simultaneously via three cameras. The system has a 3.5 ms acquisition time, and the stereophotogrammetry is guided by integrated intelligent and adaptable flash units and can deliver a 1.2 mm geometrical resolution.

2. Materials and Methods

2.1. Scanning Phase

After the approval from the Institutional Review Board of the Postgraduate School of Orthodontics of the University of Ferrara and acquiring informed consent, 20 volunteers—11 men and 9 women, mean age 26 years old—were selected for the study.
The inclusion criteria were subjects who had completed growth. Exclusion criteria included men with beards, previous trauma to the facial area, facial esthetic surgery, or skin blemishes.
Each participant was measured manually and scanned using the two devices—the EinScan H2 scanner (EIN) and the Vectra scanner (VEC)—on the same day.
A skilled operator performed all the scans and the other two operators verified the correct processing of the 3D image.
On the day of the scans, each participant was instructed to take off glasses they might have been wearing and to pull back their hair through a band to ensure proper visibility of the face and of the ears. Pellitteri et al.’s [13] methodology was employed, and six reference markers were placed on each subject’s face at six cephalometric points (Figure 1, Table 1), using a special cross-shaped mold.
Figure 1. Frontal photograph and facial scan of the subject with reference points in order from top to bottom: Tr (midline of hairline), Na′ (point on soft tissue over nasion), Prn (soft tissue point on tip of nose), L–R Zyg (lateral point of zygomatic arches), Pog′ (soft tissue over pogonion).
Table 1. Definition of the six cephalometric points.
To maintain a natural head position and prevent movement during the scan, participants were seated with backrests and instructed to keep their mouths closed, lips relaxed, and eyes closed, while a thorough quality control assessment ensured consistency in head position and facial expression [13,18].
The first scan was conducted with the Einscan H2. The operator positioned the patient correctly in front of the camera, monitored the alignment on the computer screen, and moved the scanner around the subject’s face while using color-coded lights to maintain the proper distance and ensure complete coverage.
The second scan was performed with the Vectra M3, capturing three images—two at 45° angles and one frontal—20–30 cm below the subject’s face. The device was connected to a laptop to ensure 3D reconstruction accuracy throughout the session.
Given the importance of the light source and its temperature for accurate scanning and good image quality [19,20,21], all patients were scanned under a good direct light source, ensuring that the face was sufficiently and evenly illuminated.

2.2. Anthropometric and Digital Measurements

The anthropometric distances between the Tr (trichion)–Na′ (soft tissue nasion), Na′–Prn (pronasion), Prn–Pog′ (soft tissue pogonion), and left–right Zyg (zygomatic) points were manually measured as a reference using a digital caliper directly on the subject’s face. One hour later, measurements were repeated by the same operator to verify the repeatability of the measurements.
Geomagic X Control software (v2020.1.1, 3D Systems Inc., Rock Hill, SC, USA) was used to calculate the distances between the cephalometric reference points on each of the scans. The sets of measurements were compared with each other and the anthropometric data. After two days, the digital linear measurements on the face scans were repeated to verify the repeatability of the measurements. The same software was used to perform the 3D analysis.
Firstly, the scans were carefully trimmed to include the entire forehead, passing in front of the tragus, and at the submandibular level. Subsequently, the software provided the automatic best-fit alignment between the two scans of the same patient.
For point analysis, the operator manually inserted the cephalometric reference points on each of the scans, as described in Table 2 and Figure 2. Two days later, the points were placed again on the face scans to verify repeatability.
Table 2. Definition of 13 cephalometric landmarks for analysis of points.
Figure 2. Thirteen cephalometric points analyzed on the facial scan.
The 3D analysis of the points was performed by dividing the measurement results into the following tolerance ranges: 0.5 mm to 0 mm and 0 mm to −0.5 mm, considered highly reproducible; 1 mm to 0.5 mm and −0.5 mm to −1 mm, considered moderately reproducible; 1.5 mm to 1 mm and −1 mm to −1.5 mm, considered poorly reproducible; and, finally, >1.5 mm and <1.5 mm, considered not reproducible [13].
Secondly, five different areas were delimited for analysis: forehead, tip of the nose, left cheek, right cheek, and chin (Figure 3). For each area, the percentage of overlapping area contained within a measurement tolerance range was assessed. The five tolerance bands were defined for point analysis (Figure 4) [9,13].
Figure 3. The five areas analyzed in frontal and lateral views. Each area is automatically distinguished by the software with a different color.
Figure 4. Analysis of the areas within the tolerance ranges: 0.5 mm to 0 mm and 0 mm to −0.5 mm, considered highly reproducible (A); 1 mm to 0.5 mm and −0.5 mm to −1 mm, considered moderately reproducible (B); 1.5 mm to 1 mm and −1 mm to −1.5 mm, considered poorly reproducible (C).

2.3. Statistical Analysis

Descriptive statistics were calculated for all variables: means, standard deviations, minimums, maximums, and quartiles were computed for linear measurements, point measurements, and areas. In relation to points and linear measurements, ICCs were calculated to assess repeatability.
The Shapiro–Wilk test was used to assess the normality of the distribution. Non-parametric Wilcoxon tests were performed for variables related to linear measurements to determine if there were differences in measurements among different instruments (ANT vs. VEC, ANT vs. EIN). Regarding variables related to point measurements, the non-parametric Wilcoxon test was used to verify whether the value is statistically different from zero. Lastly, a post-hoc power analysis was conducted to ensure the sample size was adequate. The sample size was confirmed to be adequate, as the retrospective power calculation for the smallest ICC (0.909) with a sample of 20 and α = 0.05 yields a power of 98.9%, exceeding the minimum threshold of 80%. For all tests, a significance level of p < 0.05 was considered. The analyses were performed using IBM SPSS v28, except for the power analysis, which was conducted using R v4.2.1.

3. Results

3.1. Linear Measurements

Descriptive analysis of the linear anthropometric measurements is reported in Table 3.
Table 3. Descriptive analysis of linear measurements.
The intraclass correlation coefficient (ICC) ranges from 0 (no repeatability) to 1 (perfect repeatability). In this case, all ICC values are above 0.90 and significantly different from 0 (p < 0.05), which indicated that the first and the second measurement showed good repeatability for all measurements (Table 4).
Table 4. Intraclass correlation coefficient (ICC) of linear measurements.
For these reasons, only the first measurements were considered. The paired-sample Wilcoxon test was conducted to verify any differences between the different linear measurements. The null hypothesis was that the medians of the two variables were equal. It is observed that there are no significant differences (p > 0.05); therefore, it can be stated that the measurements among the three instruments are similar (Table 5).
Table 5. Non-parametric Wilcoxon tests for linear measurements ANT-VEC and ANT-EIN.

3.2. Points Measurements

Table 6 reports the descriptive analysis of the points measurements, showing that all the cephalometric points, except for the subnasal point, have shown a difference between Eiscan and Vectra within the range from 0.5 mm to −0.5 mm, considered highly reproducible. The ICC values are all above 0.90 and significantly different from 0 (p < 0.05), indicating excellent repeatability (Table 7).
Table 6. Descriptive analysis of points measurements.
Table 7. Intraclass correlation coefficient (ICC) of points measurements.
A single-sample Wilcoxon test was conducted in order to verify whether the value is statistically different from zero. It was observed that there were no significant differences, so the median does not deviate from zero (p > 0.05) (Table 8).
Table 8. Single-sample Wilcoxon test for point measurements.

3.3. Analysis of the Areas

Table 9 reports the descriptive analysis of the areas. It must be considered that more than 70% of the averages of overlapping surfaces between the two scans fell within the highly reproducible band (0.5 mm to −0.5 mm).
Table 9. Average percentages of overlapping surfaces of the forehead, left cheek, right cheek, tip of nose, and chin areas in the five tolerance ranges when comparing VEC-EIN.
Considering the tolerance range between 1.5 mm and −1.5 mm, what emerged is that the left and right cheeks showed the lowest values out of tolerance (0.91% and 1.15%, respectively), while it emerged that the forehead, nose, and chin reached the highest values out of tolerance (17.49%, 4.27%, and 2.23%, respectively).
The post-hoc power analysis was performed relative to the ICC measurements, aiming for at least 0.80 (80%). Considering the smallest ICC obtained (0.909 for the left zygomatic point measurements), with a sample size of 20 and a Type I error rate (α) of 0.05, the power obtained is 0.989, or 98.9%; thus, the sample size is adequate.

4. Discussion

Currently, 3D facial scans are promising for assessing facial soft tissue morphology, offering high-resolution surface textures and quickly capturing detailed 3D images, which benefit pediatric facial development evaluation, analysis of pathological facial morphology, cosmetic and reconstructive procedures, orthognathic surgery, and orthodontic procedures [22,23,24]. Furthermore, the advancement of these new acquisition technologies has enabled the capture of high-quality images suitable for landmark detection, serving as an alternative to CBCT. This approach allows for the acquisition of sequential frames while minimizing the patient’s exposure to radiation, which is a very important goal in the medical and orthodontic fields [12].
Despite the existing literature on the accuracy of individual 3D imaging systems, numerous options are available on the market, and inter-device repeatability still needs to be verified by analyzing scans from different devices and comparing their relative performances [25,26].
This study aimed to compare the accuracy and reproducibility of the EinScan H2 with respect to the Vectra M3 3D Imaging System and to anthropometric measurements. Specifically, the goal was to compare the accuracy of the portable EinScan H2 with the previously validated static Vectra M3. The use of portable devices can facilitate their application in clinical practice, as they are more accessible than static devices [16].
Moreover, no existing research evaluates the accuracy of this scanner in relation to 3D cephalometric areas and points. These data, thoroughly analyzed in this study, represent a crucial aspect in the field of orthodontics and, for this reason, have been investigated in this manuscript.
The analysis of linear measurements has been extensively investigated in the literature. The importance of these measurements lies in their ability to obtain a comparison between the two scanners, and particularly a direct comparison of them with real anthropometric measurements [27,28]. In this regard, comparison of linear measurements on 3D facial scans with direct anthropometry measurements has proved they are reliable and repeatable, showing no significant differences (p > 0.05). These findings are supported by the literature, confirming that the differences observed in linear measurements are not clinically relevant [13,29,30].
Considering point measurements, it was observed that all the points taken into consideration showed a difference between Vectra and Einscan within the range from 0.5 mm to −0.5 mm. The only point that showed a greater millimetric difference was the subnasal point (0.73 mm). However, the literature confirms that the vertical orientation of the head can affect the scanning accuracy in certain areas, making it difficult to correctly scan certain cephalometric landmarks, thus justifying the greater millimetric deviation [31]. To maintain a natural head position, various modalities such as chin rest, head positioning devices, or digital orientation sensors, should be used to obtain a more stable head position and to prevent unwanted movements [32].
The analysis of superimpositions revealed that more than 70% of the averages of overlapping surfaces of the forehead, left cheek, right cheek, tip of nose, and chin areas fell within the highly reproducible band (0.5 mm to −0.5 mm) when comparing the Vectra–Einscan scanners. The nose and the right and left cheeks had the highest average value (almost 80%) of the surface in the highly reproducible category. The chin and the forehead, instead, obtained the lowest values in the bands considered highly reproducible (respectively, 70.46% and 71.72% in the 0.5–>0 and 0–>−0.5 mm range). The poor reproducibility of the forehead can be explained by the fact that facial scanners encounter greater difficulties in capturing images with large curvatures compared to areas with defined angles [33]. Additionally, it is important to consider how the scanning accuracy depended on the location of the scanned surface area, being more accurate on the middle of the face. In comparing surface areas, Revilla-León et al. confirmed that the forehead area had the lowest mean precision [34]. These findings are supported by the literature, which has demonstrated that the forehead showed an average overlap percentage of 54.46% within the highly reproducible band (0.5 mm to 0 mm and 0 mm to −0.5 mm), with previous studies confirming an even lower overlap percentage of 11.08% [9,13].
The same difficulty in capturing images is also observed for the chin, as demonstrated by Kau et al. The mandible, in fact, represents the only moving bone of the face, making the lower third less reproducible [35].
However, it is also important to emphasize that Vectra and Einscan are two different three-dimensional acquisition systems. The Canfield VECTRA M3 3D Imaging System is a static device that captures precise 3D models of the human face by combining synchronized 2D images with photogrammetric algorithms [36]. As demonstrated by a previous study, synchronized two-dimensional images of the subjects are captured within 0.75 milliseconds with Vectra 3D [37], making the system immune to subject movement and less susceptible to operator-dependent scanning errors. Moreover, it includes lighting specifically designed for clinical photography, which produces shadow-free images with colors that adjust to the patient’s skin tones [38].
The EinScan H2 integrates structured light and infrared technology, offering versatility across various scanning applications and capturing the fine details of complex surfaces and dark materials with remarkable precision [39]. However, it has a scanning speed of 1,200,000 points/s and, as a portable device, it often requires an extensive learning curve to perform the scanning protocols optimally. These factors can lead to errors during the image acquisition process, resulting in lower accuracy and reproducibility in certain areas of the face [16,39].
Despite the areas showing different percentages within the highly reproducible range (0.5 mm to 0 mm and 0 mm to −0.5 mm), it is very important to consider the 3D analysis of point measurements. Considering both the forehead and the chin, the trichion (Tr), nasion (Na′), and pogonion (Pog′) points did not show statistically significant differences in median values (p > 0.05) between the two instruments, indicating a similarity between Vectra and Eiscan. These data allow us to highlight how, within the same area, some zones are more easily influenceable than others during the 3D scan.
However, except for the forehead (82.52%), more than 90% of the averages of overlapping surfaces between the two scans fell within the tolerance band (1.5 mm to −1.5 mm). These data agree with the study by Pellitteri et al. [13], although in their study, the forehead also fell within this band. Notably, the mean percentages of areas within the highly reproducible band obtained in their study appear to be lower than those in ours.
The limitations of this study include the high costs of the scanners, the need for a larger sample size to strengthen the obtained results, the challenge of obtaining a neutral facial expression while avoiding potential face movements to prevent image distortions, and the requirement for proper illumination during scanning. Moreover, it is necessary to consider that many factors influence the accuracy of the 3D scanner, such as the ability to record details, accuracy, scanning principles, span of scanning, size of the scanning area, arch length, surface irregularities, temperature, relative humidity, and illumination [19,20,21]. Additionally, it should be noted that only subjects without facial alterations or skin imperfections were selected. Furthermore, the sample lacks diversity in age and ethnicity, limiting the applicability of the results to a broader population. It would be advisable to consider the various conditions present in the population for a better assessment of the scanning capabilities.
Despite these limitations, both scanning systems investigated in the current study can be considered an accurate acquisition system proved to be effective in capturing 3D images of the face. This is an important goal since accuracy verification is essential, particularly in orthodontics, as even small millimetric variations can have a significant impact [40]. Moreover, since soft tissues are continuously changing [41], assessing the accuracy of facial scanners becomes even more critical.
The combination of teeth, facial soft tissues, and hard tissues plays a crucial role in orthodontic treatment planning [42]. Three-dimensional imaging in orthodontics is valuable for assessing dento-skeletal and craniofacial relationships, before and after treatment, and it also aids in reviewing treatment outcomes, guiding investigative decisions, and supporting therapeutic planning with 3D projections [43].
In the future of digital scanning, further studies should be conducted to investigate the performance of scans under varying light conditions, as this factor may influence the final outcome. Moreover, scientific research should increase the sample size by focusing on analyzing different facial types and conditions, age, and ethnicity, to better understand how these factors may affect the success of facial scanning and to generalize the obtained results to a broader population.

5. Conclusions

The conclusions of the study are as follows:
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The Vectra 3D and the Eiscan facial scanners generate 3D models with similar, consistent, and replicable measurements, suggesting no systematic advantage of one measurement tool over the other in terms of accuracy compared to anthropometric measurements.
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The analysis of linear measurements on 3D facial scans has proved they are reliable and repeatable, showing no significant differences with respect to each other and with respect to anthropometric measurements. Similarly, all the cephalometric points analyzed turned out to be within the range from 0.5 mm to −0.5 mm, indicating a similarity between the Vectra 3D and the Einscan.
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The comparison of the overlays in the areas of the scans shows that more than 70% of the averages of overlapping surfaces of the forehead, left cheek, right cheek, tip of nose, and chin areas fell within the highly reproducible band (0.5 mm to −0.5 mm). The nose and the right and left cheeks are the area with the highest average percentage of surface in the highly reproducible band (about 80%). Except for the forehead (82.52%), more than 90% of each area analyzed fell within the reproducible band (1.5 mm to −1.5 mm).
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Three-dimensional facial scanners represent a promising tool in the field of dentistry and orthognathic surgery, allowing for a three-dimensional analysis of patients’ faces, treatment predictions, and soft tissue analysis without the use of radiation.
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Future studies should aim to analyze different facial types as well as various environmental conditions to be considered for successful scanning.

Author Contributions

Conceptualization, L.L. and F.P.; methodology, L.L. and F.P.; software, M.C. and G.B.; validation, L.L. and F.P.; formal analysis, F.P. and M.C.; investigation, M.C. and M.D.M.; resources, L.L. data curation, F.P.; writing—original draft preparation, F.P.; writing—review and editing, F.P. and M.C.; visualization, L.L. and F.P.; supervision, L.L. and F.P.; project administration, L.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

This study was conducted in accordance with the Declaration of Helsinki, and it was approved by the Institutional Review Board (or Ethics Committee) of the University of Ferrara (protocol code 08/2024, 3 March 2024).

Data Availability Statement

All authors ensured that all the data and materials, as well as software application or custom code, support their published claims and comply with field standards. The raw data supporting the conclusions of this article will be made available by the corresponding author on request.

Conflicts of Interest

The authors declare no conflicts of interest.

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