There is an increasing need for indirect digitisation of dental arches for simulation and treatment purposes. One method of indirect digitisation is scanning the cast model with a CBCT device to create triangular meshes which can then be used for the fabrication of certain dental prostheses. It was the main purpose of this study to estimate how accurately a CBCT scanner can replicate the details of the gypsum model, thus providing support to our theory coming from personal experience that CBCT scanners are capable of the task.
For the estimation of the repeatability of the reference scanner, the standard deviation of the differences between identical meshes was employed, a method also used by other studies [13, 14]. Our mean standard deviation between the 90 pairs of meshes was 4.1 μm, and the repeatability could be considered excellent. The mean value of 16 μm for the differences between the meshes is the average deviation from the truth (0 mm); it can be considered a measure of accuracy, and it is similar to the value provided by the manufacturer of the laser scanner (15 μm).
Instead of a commercial alternative, CloudCompare (Version 2.9 Omnia, http://www.cloudcompare.org/), an independent open source project and free software under the GNU General Public License, was chosen as our mesh handling and comparison software. The accuracy and the repeatability of the software as expressed by the standard deviation and the mean values of differences between identical meshes can be considered adequate for the needs of the present study (Table 1).
Concerning Blue Sky Plan (Blue Sky Bio, USA), the software used to calculate and export the triangular meshes from DICOM data, it is a commercial software used for the design and fabrication of 3D surgical implant guides. The segmentation is accomplished with the use of a Hounsfield calibrated scale, and the software allowed the easy export of multiple meshes of the same stone model in different and discrete threshold values. The range of threshold values was decided based on our experience of using the value of 1750 HU for the production of meshes in our practices.
As the main statistic for our analysis, the Dissimilarity Index was used. This index can be considered as an unstandardized measure of effect and was devised when it became necessary to combine the measure of central tendency with the measure of the dispersion of the errors. Since the differences between the CBCT meshes and the gold standard were always skewed and away from normality, the median and the interquartile range were the appropriate statistics. It was invariably noted that the IQR values follow the tendency of the median (Fig. 3). However, when the median was approaching its lowest value, similar median values for different neighbour segmentations were computed. The product of the median and the IQR gives a greater resolution on the threshold value which best describes the pair of meshes with the lowest errors, taking into account not only the median value of the error but also the dispersion of the errors, too. The value of the DI can be easily traced back to its constituents (median and interquartile range), when necessary.
The average mean (SD) difference of the median errors for all the CBCT modalities was 0.052 mm (0.011) resulting in a 95% CI for the errors of 0.048 to 0.056 mm. To our knowledge, only one study evaluated the accuracy of stone model meshes originating from CBCT data . The authors examined 8 different CBCT devices and found a mean difference of 0.064 ± 0.005 mm against 5 different extraoral digitisers used as a gold standard. However, in that study, the threshold value used for the DICOM to mesh conversion was at the discretion of the investigator. In our study, we found a significant interaction between the error and the threshold value for the different imaging modalities indicating that an appropriate threshold value must be computed for each device in order to minimise errors.
An average value of 0.052 mm for the median error must be evaluated taking into account the overall expected errors of other modalities that are used in order to digitise the tooth reality. The recommended in vitro benchmark of ± 20 μm for the replication of the tooth morphology establishes the upper limit of accuracy for the manufacturing of any successful prosthesis in the area of prosthodontics . The in vitro accuracy of conventional impression and stone model pouring method has been found to be 20.4 ± 2.2 μm, and this error can be considered as the limit for the ability of the classical method to replicate reality . The standard procedure for the indirect digitisation is the use of a lab desktop laser or white light scanner for the facilitation of CAD/CAM prostheses. The accuracy of these commercial lab scanners has been proven by a number of studies and ranges from 6 to 33 μm with the majority of the scanners in the under 20 μm category [18, 19]. A final and newer method for the direct replication of tooth anatomy is with the use of intraoral scanners that can entirely bypass the impression and stone model pouring technique. A number of studies show that the full-arch accuracy of these devices ranges in vitro from 11.5 to 332.9 μm. [17, 20,21,22].
The value below which the errors are situated when 95% of the points for each pair of meshes (CBCT and gold standard) is considered was also calculated. Even though values of central tendency and dispersion are useful, this 95% value gives an idea for the majority of the absolute errors that are expected in the totality of the stone model, without any averaging. This value being in any situation below 210 μm is conservative and, as it can be seen from inspection of the deviation maps, usually reflects the error from the soft tissue or is the result of calculations in a very small number of points. We removed the extreme 5% of the errors between points since it is expected that outliers can inflate our range of differences. It should be noted that in studies where differences between meshes are computed, 60–80% of the pairs of points are used . In our study, the upper limit of the 95% of the values was in every case less than 210 μm and in the case of the Newtom VG device less than 150 μm.
Considering the different imaging modalities, the Newtom VG device was significantly more accurate than the Planmeca Mid for both sets of exposure parameters. Even though the stone models were scanned with the Newtom device 2 weeks after the stone pouring and suffered from handling due to transportation in another facility, the average error for the Newtom was 40 μm, ranging from a minimum value of 32 to a maximum value of 49 μm. The Newtom VG device operates in higher kilovoltage peak than the Planmeca, uses a rotating anode with a very small focal spot, and has a high total filtration value, which differences possibly partially explain its better performance. For the Planmeca Mid device, the difference between the two sets of exposure parameters was not significant, possibly implying that it is not the exposure parameters per se, but other software and hardware issues that increased the error compared to the Newtom VG. (Fig. 3).
A range of values was used in the Blue Sky Plan software in order to find the threshold that would produce the triangular mesh with the minimum error. The right threshold value is of importance especially for the Planmeca device since the error could be large for low threshold values. It was seen that with the low threshold value of 1425 HU, the error was maximum and the error reached a minimum at the area of 1825 to 2225 HU value after which it started increasing again, albeit very slowly. The mean best threshold value was almost the same for both Planmeca settings (2155 vs 2145 HU) as it was the range of the values for the smaller error (1925–2425 vs 1825–2425 HU) indicating that for the Planmeca device in general, any threshold value in the range of 1925–2425 HU can be used with relative safety. For the Newtom VG device, the errors in every threshold value were significantly less than the Planmeca and they reached their minimum at the values of 1825 to 2225 HU with a mean value of 1975 HU, indicating again that for Newtom VG device, any value in the range 1825–2225 HU can be used with relative safety. Combining the results of both CBCT models and of every exposure parameter, we find a mean (SD) value of 2092 (184) HU and a 95% CI for the mean of 2023–2161 HU. This range includes part of the best values of every device and every exposure setting and can be considered safe for the thresholding of stone models in all the CBCT devices of our study.
The use of CBCT for the scanning of stone models introduces artefacts to the final image. The divergent nature of the x-ray beam means that only the object lying in the midplane will be accurately reproduced . Depending on the cone beam angle of the midplane, inaccuracy is to be expected due to data inconsistency. In the present study, the stone models were placed in the centre of the field of view and with the arch of the teeth parallel to the midplane minimising the image degradation. Beam hardening artefacts resulting from the polychromatic nature of the x-ray beam showing as streaks and shadows in the reconstructed images should also be expected, especially when the kilovoltage peak value is low . In our cases, no such image degradation was optically noted for any given combination of exposure parameters, even when the 80 KVp tube voltage was used. Other possible limitations of the CBCT scanning method include the size of the focal spot and penumbra effects, the limited spatial resolution of the flat panel, the electronic and statistical x-ray noise, and the partial volume averaging effects . In addition to the errors due to the physical process of x-ray exposure and the inherent limitations of the CBCT devices, there is always a possibility of having defects such as inaccuracy due to errors in the STL file, following the DICOM to STL conversion process .
With an average error of 0.052 mm, a number of applications seem feasible. In orthodontic applications, an error in the models of 200 μm seems acceptable , whilst in the cases of surgical guides, the knowledge of this error could be incorporated in the design, if necessary. For model storage, this value is more than adequate.
The main limitation of our study was the use of a commercial desktop dental scanner as our gold standard. The use of an industrial scanner could offer greater accuracy and repeatability. However, the repeatability of our scanner could be considered excellent, whilst the estimation of its accuracy was in the range defined by the manufacturer. In addition, the main purpose of our study was to estimate the performance of the x-ray scanners in comparison with a commonly used and universally available method.
In conclusion, the results of this study provide support to our theory that CBCT scanners can be used for the clinically relevant accurate digitization of stone models.
However, there are significant differences between the two CBCT models used; therefore, hypothesis ‘a’ was rejected. Different exposure parameters of the same CBCT model do not seem to offer a significant advantage, and, therefore hypothesis ‘b’ could not be rejected. Finally, the interaction between the threshold value and the exposure modality as far as the errors are concerned mandates the careful selection of the right threshold value for the triangular mesh creation. Tested hypothesis ‘c’ was therefore also rejected.