The use of a face scanner to obtain 3D facial images has become increasingly popular during the last decades especially in the field of maxillofacial and aesthetic surgery. There are several fields of utilization of face scan images, such as in evaluation of volumetric changes after surgical interventions, preoperative and /or postoperative evaluation of surgeries. However, several different models exist, with a wide range of quality of the data set and the consecutive reconstructed 3D face.
Camison et al. calculated the distances between several marked points in the face and it resulted in 136 distances in total. The deviation was on average 0.84 mm [2]. Other authors used heatmaps to determine a mean absolute difference, resulting in an accuracy from 0.32 to 0.71 mm. The same technique was also used for an accessory iPad hardware sensor, resulting in an accuracy of 1.33 mm [3, 6]. In our study cohort, we achieved an average deviation of 1.34 mm with photometry and 3.01 mm with a smart device respectively. Since the distance between anthropometric points were measured, the results are comparable to Camison et al., however they are technically not comparable to the measurement of a heatmap. Using lego bricks Modabber et al. determined a mean deviation from the 90° angles of 0.42° to 35.41° in a professional face-scanner [4]. Surprisingly, the results from both techniques in our study achieved better results in the measurement of the angles than professional face scanner. The reason might not be related the capturing device of the 3D data, but rather the software of the processors, because they tend to smoothen edges. This effect was also seen in our cohort of patients measured with the smart device. The angles were larger than in reality, which is probably attributed to the smoothening effect.
In our study cohort, manual photogrammetry with a regular photo-camera was more detailed and more accurate than the smart device. However, the major disadvantage in manual photogrammetry is the data acquisition. There were on average 151.18 ± 30.26 photos needed and at they need to be fused. Thus, it does not appear to be a likeable solution for daily routine. Nonetheless, in distinct cases, for example in a research setting, it might be a usable solution.
In contrast, the scan with the smart device is more user friendly and intuitive but leads to a less accurate reconstruction of the face. On a long term, smart devices are likely to further improve in terms of camera technique but also in terms of processing software. It appears to be likeable that in near future these devices can deliver 3D data sets comparable to professional cameras. Thus, a regular control with every new generation of smart device-cameras should be performed.
In daily clinical practice, one purpose of 3D face-scan is the production of individual protective masks for athletes. Cazon et al. compared two scanners and found a deviation of the mask from the scanned surface between − 2.0 and 2.7 mm and an average of 0.18 and 0.15 mm for two scanning devices [9]. In a case series report by Steiner et al., the face mask was produced conventional by plaster impression and it showed an average deviation of 1.57 mm with a maximum of 5.62 mm. It was then compared with a production based on a 3D scan. Latter mentioned showed an average deviation of 0.99 mm and a maximum deviation of 6.18 mm. 10 They conclude that differences of a few millimeters do not seem to reduce comfort or protective effect of these masks [10]. In our study, the average deviation of the anthropometric measurements ranged from 1.34 mm to 3.01 mm. Thus, it could be clinical usable the production of protective masks as well.
Amornvit et al. also described the use of an iPhone for face-scanning. They used Bellus3D as an App for data acquisition[11]. Further potential software programmes are Trnio, Capture and Scandy Pro. However, in evaluation phase prior to the conduction of the study, all of the obtained images obtained with Bellus3D APP were either not precise enough, or showed problems with data export. So, the authors chose Heges App as the most suitable for an iOS device. Android driven or other devices were not considered in the study, but certainly provide also reliable alternatives.
Finally, it is important to mention, that pictures from photogrammetry do not appear as smooth as 3D pictures from the smart device as we previously described. Nonetheless, it is important to note for daily practice. If the scan is needed for patient education, a smoothened surface is desirable and minor discrepancies in length or angles might not be a relevant problem. In contrast, for research issues, the more detailed the face-scan is and the less deviation is seen, the better it is. Thus, photogrammetry seems a favorable option in those cases.