Comparison of the accuracy of the image registration methods for the impressions of edentulous jaws
- Open Access
- 01.04.2025
- Research
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Abstract
Introduction
The physiological structure of teeth and edentulous patients varies greatly. In terms of chewing function, patients with teeth can effectively chew food through tooth cutting, tearing, grinding and other actions, which is conducive to the subsequent digestion process. Dentulous patients have missing teeth, resulting in a large reduction in chewing efficiency, and food often can not be fully chewed, increasing the digestive burden of the gastrointestinal tract. In terms of oral structure, the existence of teeth maintains the normal shape and space of the oral cavity, which can support the lips and cheeks, and maintain the fullness of the face. The alveolar bone in edentulous patients will gradually be absorbed after the tooth is missing, and the height of the alveolar ridge decreases and the width becomes narrowed. This change changes the anatomy of the oral cavity. In terms of the oral microbial environment, in the mouth with teeth, there is a complex microbial community on the tooth surface, which is normally in a relatively balanced state. The habitat environment of microorganisms in the mouth of edentulous patients has changed greatly, and the species and proportion of microorganisms have also changed, which may be more likely to breed some opportunistic pathogens, increasing the risk of oral infection. Studying the oral physiological characteristics of teeth in the presence of teeth can provide reference for simulating the chewing function of natural teeth. In terms of diagnosis, the diagnosis of oral diseases in patients with teeth is relatively complex, so the types of dental lesions need to be considered comprehensively, and the symptoms and signs of different dental lesions are very different.
In past, the manual model measurement was mostly used to study the morphological differences of edentulous jaw impressions or models, that offered the advantage of being intuitive but had the drawback of being capable only of measuring linear distances or curve shapes. Moreover, these methods are limited by the location of the sampling points, resulting in the loss of important information and making it impossible to conduct comprehensive quantitative 3-dimensional deviation comparison studies [1]. In recent years, many conveniences have been provided for the quantitative evaluation of dental model quality through the development of computer-aided 3D model reconstruction and measurement techniques [2]. In 2019, Jung [3] et al. compared the effectiveness of traditional impression method, simplified closed-mouth impression method and intraoral scanning impression method in edentulous patients, and evaluated them by three-dimensional analysis software. Si-Han C et al. [4]also studied the accuracy of intraoral scanning of complete dentition in reverse engineering software. This method is also commonly used for registration, point cloud stitching and alignment of scanning data of multiple models with overlapping regions.However, at present, there are few studies on registration methods for edentulous jaw models with insignificant curvature changes.The most important prerequisite for quantitative deviation research between two 3D models was accurate registration that was consistent with clinical data. The registration tools for dental models mostly involved reverse engineering software such as Geomagic, Imageware, and specialized dental software such as 3Shape. Geomagic software was the most commonly used software according to the literature. It provides two registration methods: best fit alignment and manual multi-point registration followed by global registration. However, there are few studies on how to choose a registration method. This study applied two registration methods to align open and closed-mouth edentulous impression models of the same patient and compared the 3D deviation data to explore the exact registration methods suitable for edentulous patients.
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Materials and methods
Main experimental equipment and software
Shape D900 model scanner (3 shape company, Denmark).
Geomagic Control 2014 Reverse Engineering Software (Raindrop Company, USA).
Obtaining edentulous jaw impressions and models
This study was reviewed and approved by the Biomedical Ethics Committee of Dalian Stomatological Hospital (DLKQLL2018011) and strictly complied with the World Medical Association Declaration of Helsinki (version 2013). Using a convenient sampling method, all cases that met the inclusion and exclusion criteria from July 2022 to December 2022 were included in the study. Participants ranged in age from 60 to 90 years. Patients without tempo-mandibular joint disorders, mucosal diseases, or occlusal abnormalities were included, a total of 14 people including 12 patients with complete dentition loss and 2 patients with only maxillary single dentition loss. All participants signed an informed consent before clinical operation. Two impression techniques, open-mouth impressions (Fig. 1) and closed-mouth impressions (Fig. 2), were applied to take impressions on each patient. 14 pairs of maxillary models and 12 pairs of mandibular models were subsequently obtained.These samples are highly representative cases after rigorous screening. It shows a high degree of consistency and specificity in a specific research category, and the information contained is extremely high enough to accurately reflect key characteristics and trends, which is not simply comparable. And, through the advanced statistical model and fine analysis method, can deep dig the inherent law, effectively make up for the relative shortage of sample size, which still can conclude with highly scientific and reliable, enough to provide valuable reference in related clinical field and guide these samples are strictly screening of typical cases. It shows a high degree of consistency and specificity in a specific disease or research category, and the information contained is extremely high enough to accurately reflect key characteristics and trends, which is not simply comparable. In addition, through advanced statistical models and fine analysis methods, the internal laws can be deeply explored and effectively make up for the relative shortage of sample size, so that highly scientific and reliable conclusions can still be drawn, which is enough to provide valuable reference and guidance in relevant clinical fields.
Fig. 1
Open-mouth impression. Left: maxilla, right: mandible
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Fig. 2
Closed-mouth impression
Methods for obtaining open-mouth and closed-mouth impressions
First, an appropriately sized edentulous aluminum stock tray was selected. After that, initial impressions were made using the impression compound followed by alginate. The superhard gypsum was poured, and the initial models were duplicated. The margin line was shortened by 3 mm at the lowest point of the flange zone on the initial model, the maxillary distal part covered the pterygomaxillary notch, and 2 mm extended past the foveolar palatina; the mandibular distal part covered the entire posterior molar pad. The undercut areas on the initial models were subsequently filled with wax. Individual resin trays and temporary bases were made separately using light-cured base resin (Supertec, DMG, Germany) according to the marginal line in the initial models. The wax rim (Base wax tablet, Shanghai Pharma, China) was fixed on the temporary base, after which the vertical dimension of occlusion and centric relation position (CRP) in the mouth were recorded. Individual trays were used for open-mouth impressions, and temporary bases were used for closed-mouth impressions. A tray adhesive (Tray Adhesive, DMG, Germany) was used before the impressions were taken. Both open and closed mouth impressions were taken in two steps. First, the border was modified with medium-body MONO polyvinyl siloxane, and then the fine impression of the tissue surface was taken with light-body polyvinyl siloxane (DMG, Germany). The impressions were sterilized in 2% glutaraldehyde for 30 min. Die-stone gypsum (Heraeus Kulzer, Germany) was mixed in a vacuum gypsum mixer according to the water-to-power ratio recommended by the manufacturer and poured into the impressions.
Model digitization, data clipping, and preprocessing
The super hard gypsum models, including the upper jaw (14 pairs) and lower jaw (12 pairs), were scanned in a 3Shape D900 model scanner (accuracy 15 μm) and saved in STL format.
Model data were imported into Geomagic Control 2014 reverse engineering software in STL format, and the “plane clipping” and “curve clipping” commands were applied to trim off the excess data outside the working area. The model boundary line was set at a 3 mm width from the lowest point of the buccal and lingual flange area, pterygomaxillary notch and 5 mm from the foveola palatina, the entire molar posterior pads of the mandibular distal zone. The defects that occurred from the model scanning or 3D reconstruction process were corrected by reducing noise, removing spikes and filling holes. See Fig. 3.
Fig. 3
After trimming, the open-mouth impressions of the digitized models were blue, and the closed-mouth impressions were yellow. Left: Maxilla, right: Mandible
Register models and comparison of 3D deviation
The open-mouth and closed-mouth impression models of the same patient were independently registered using two registration methods, as follows: best fit alignment and manual multi-point combined with global registration. The 3D deviation between the reference and test models of the two registration methods was also recorded.
Two model registration methods
Method 1: Best fit alignment. Refer to Fig. 4.
Fig. 4
Best fit alignment
The closed-mouth impressions were used as the reference model (Reference), and the open-mouth impressions were used as the test model (Test). The “best fit alignment” command was selected, which was performed in two phases. First, the initial gross alignment phase is performed with a default of 300 sample points on the surface of the reference and test models; subsequently, the fine alignment phase is performed using a value of 1500 sample points. The closed-mouth reference model is the fixed object, while the open-mouth test model is moved to minimize the distance between the two models. High-precision fitting alignment is achieved through software iteration calculations and automatic deviation elimination.
For more accurate alignment between models, the models should have similar border ranges. After the alignment was completed, provided that a large deviation was found in the cropped edge range between the reference and test models, the excess edge data were further trimmed with the curve trimming tool and reregistered, and the final registration result was recorded.
Method 2: Manual N-point registration followed by global registration (Manual + Global Registration). Refer to Figs. 5 and 6.
Fig. 5
Manual n-point registration: Multi-recognizable anatomical marks on the two models were manually clicked in interactive mode
Fig. 6
Global registration
Manual n-point registration
The closed-mouth impression model was pinned up to keep it stationary as a fixed model (fixed model), the open-mouth impression model was set as the movable model (floating model), and the open- and closed-mouth models were aligned. The “n-Point Registration” option of the manual registration command was selected to complete the preliminary alignment between the floated and fixed models. The registration point selected by each patient will be different. Maxilla usually chooses incisor papilla, palatal fold, pterygomaxillary notch, labial and buccal frenulum apex. Mandibular usually chooses the anterior edge of molar posterior cushion, labial, buccal and lingual frenulum apex, or other identifiable alveolar crest bone protrusion or depression point. There were 6–9 registration points, which were evenly distributed on both sides of the dental arch as far as possible. Because different patients have different tooth loss time, order and alveolar ridge absorption degree, the easily identifiable anatomical markers will be different, so the registration points selected by different patients will be different.
Global registration
The global registration command was applied with the software default parameters set as follows: tolerance, 0.0 mm; maximum number of iterations, 100; sample size, 2000; and subsequent application.
Comparison of 3D deviation
With Geomagic Control 2014 software, the closed-mouth model was set as the reference model, and the open-mouth model was set as the test model. Using the “3D Compare” command, the deviation between the test and the reference models was calculated, and the deviation distribution is displayed in a colour gradient map. The nominal value zone in the colour gradient is displayed in green. A smaller nominal value deviation and a larger nominal value area represent better registration quality. A positive deviation, which is shown in the red gradient, indicates that the test model is above the reference model, while a negative deviation, which is shown in the blue gradient, indicates that the test model is below the reference model. A 3D deviation comparison report was exported. The four parameters investigated, namely, the RMS error, average positive deviation, average negative deviation, and nominal value, were recorded.
(1)
RMS, Root mean square of the deviation. The calculation formula is:
$$RMS\, = \,{{\sqrt {\sum\nolimits_{i = 1}^n {{{\left( {{x_{1,i}} - {x_{2,i}}} \right)}^2}} } } \over {\sqrt n }}$$
where x1,i - x2,i is the closest Euclidean distance between the corresponding points on the reference model and the test model and n is the total number of measured point pairs. The greater the distance between the corresponding points on the reference model and the test model is the greater the difference between the two models at that point. A smaller RMS value reflects better alignment quality between models.
(2)
The average deviation (Avg. deviation). The results reflect the alignment quality between the models, with a smaller average error indicating better quality. The average positive deviation and average negative deviation were separately investigated in this study.
(3)
Nominal value. The nominal value is shown in green in the color gradient and was calculated automatically by software to represent the segment of positive and negative deviations closest to 0. A smaller absolute nominal value indicates smaller inter-model deviations. The threshold of nominal values may be different between two registration methods for the same pair of open and closed mouth impression models. For comparison, the three-dimensional colour scale of the Manual + Global Registration method was modified according to the best fit alignment method. The colour-coded deviation spectra of the two registration methods were also modified to be the same, as the area of the nominal value (green area) was comparable. A larger area proportion of the nominal value threshold indicates higher registration quality of the model pair. The distribution of the green area can also indicate the distribution of consistent areas between the models.
Statistical analysis
The registration quality of the two methods was compared. The statistical software SPSS26.0 was used. The four parameters of 3D deviation were the RMS error, the Avg. positive deviation, Ave. negative deviation and the normal value area. The measurement data were tested by the Kolmogorov‒Smirnov test for normality. The normal data are expressed as the mean ± standard deviation, and the non normal data are expressed as the median and quartile. A paired t test was conducted to compare the registration quality of the two registration methods, with a significance level set at two-tailed α = 0.05.
Results
An intuitive visual comparison of the 3D deviation results of the two registration methods
The deviation color scale maps of typical cases using the two registration methods can be seen in Figs. 7 and 8. Visually, the deviation between the reference and test models using the best fit alignment method was greater than that using manual n-point + global registration in the primary stress-bearing area and secondary stress-bearing area. The deviation distribution using the best fit alignment method was asymmetrical, and the area proportion of the nominal value threshold was smaller. The Manual n-point + Global Registration method can achieve a more extensive green region distribution than can the best fit alignment method, and the green distribution was symmetrical in the primary stress-bearing area and secondary stress-bearing area, which were not affected by muscle activity around the mouth.
Fig. 7
The 3D deviation of two registration methods used for maxillary open- and closed-mouth impression digital models of the same patient was compared. The nominal value was ± 0.1760 mm, the nominal value threshold (green) area proportion: the best fit alignment was 21.04%, and the manual n-point + global registration was 66.74%
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Fig. 8
The 3D deviations of two registration methods used for mandibular open- and closed-mouth impression digital models of the same patient were compared. The nominal values were ± 0.2240 mm, the nominal value threshold (green) area proportion: the best fit alignment was 15.30%, and the manual n-point + global registration was 52.73%
The 3D deviations of the two registration methods were compared using paired t tests
The data in each group were normally distributed. The mean nominal value thresholds were as follows: maxillary:±(0.150 ± 0.022) mm; mandibular:±(0.183 ± 0.012) mm. The area of the nominal value threshold for the best fit alignment group (maxilla, 48.58%; mandible, 44.16%) was less than that for the manual n-point + global registration group (maxilla, 70.55%; mandible, 66.27%), and the difference was statistically significant at P < 0.05. The RMS(0.530vs0.376,p = 0.006), mean average positive deviation(0.281vs0.191,P = 0.020) and mean average negative deviation(-0.238vs-0.160,p = 0.007)in the best fit alignment group were greater than those in the manual n-point + global registration group. Statistically significant differences were found in the maxilla at P < 0.05, while no statistically significant differences were found in the mandible at P > 0.05 (Tables 1 and 2).
Table 1
Paired sample t test of best fit alignment and manual n-point + global registration in the maxilla (n = 14)
mean (M ± SD) | Paired difference (M ± SD) | |||||
|---|---|---|---|---|---|---|
Best fit alignment | Manual + Global Registration | t | df | Sig.(two-side) | ||
RMS(mm) | 0.530 ± 0.117 | 0.376 ± 0.067 | 0.154 ± 0.83 | 4.571 | 13 | 0.006* |
Avg. positive Deviation. (mm) | 0.281 ± 0.090 | 0.191 ± 0.058 | 0.089 ± 0.065 | 3.370 | 13 | 0.020* |
Avg. negative Deviation. (mm) | -0.238 ± 0.079 | -0.160 ± 0.052 | -0.078 ± 0.044 | -4.350 | 13 | 0.007* |
Nominal value (mm) | ±(0.150 ± 0.022) | |||||
Nominal value proportion (%) | 48.58 ± 8.78 | 70.55 ± 7.45 | -21.98 ± 4.16 | -12.939 | 13 | 0.000* |
Table 2
Paired sample t test of best fit alignment and manual n-point + global registration in the mandible (n = 12)
mean (M ± SD) | Paired difference (M ± SD) | |||||
|---|---|---|---|---|---|---|
Best fit alignment | Manual + Global Registration | t | df | Sig.(two-side) | ||
RMS(mm) | 0.727 ± 0.253 | 0.549 ± 0.147 | 0.178 ± 0.337 | 1.179 | 11 | 0.304 |
Avg. positive deviation(mm) | 0.384 ± 0.102 | 0.356 ± 0.115 | 0.028 ± 0.112 | 0.566 | 11 | 0.602 |
Avg. negative deviation(mm) | -0.189 ± 0.042 | -0.164 ± 0.260 | 0.025 ± 0.295 | 0.190 | 11 | 0.859 |
Nominal value (mm) | ±(0.183 ± 0.012) | |||||
Nominal value proportion (%) | 44.16 ± 13.07 | 66.27 ± 5.81 | -22.11 ± 11.93 | -4.144 | 11 | 0.014* |
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Discussion
The development of modern computer graphics and 3D detection and analysis technology has facilitated the comparative study of dental models in stomatology. With the advancement of digital technology, the digitalization of dental models through intraoral scanning (IOS) or model scanning has been widely clinically confirmed in the field of fixed partial dentures and implant-supported dentures [5, 6]. In recent years, many scholars have performed extensive work on three-dimensional comparisons of edentulous jaw models generated via various impression methods, including intraoral scanning [7, 8]. A prerequisite for a 3D comparative study was the reliable registration method of 3D models (also named alignment, registration, superimposed, or overlapped) [9‐13]. Registration is also an indispensable tool for digital clinical dentistry of edentulous jaws [14, 15], such as transferring jaw relations in digital complete dentures, aligning jaw relation records with impressions, and aligning radiographic templates with CBCT in preoperative implant design [14, 16‐18]. There are three main recorded model registration methods in the literature: ①Scanner’s own software, such as 3Shape, which performs alignment by manually selecting three points and calculating internally [11]; ②Reverse engineering software, in which the most widely used registration method is the best fit alignment tool [2, 3, 19, 20], which is also recommended for model alignment in reverse engineering software for product quality analysis; and ③When Si-Han C [4] et al. studied the accuracy of intraoral scanning of complete dentition, they used the manual registration command first and then the global registration command for model alignment in reverse engineering software. This method is also commonly used for the registration of multiple model scanning data with overlapping areas, point cloud stitching and alignment. The field of complete dentures and removable partial dentures, the digitalization of dental models has been a hot topic in recent years. Due to the deformability and viscoelasticity of the oral mucosa and the influence of the movable mucosa at the margins, the IOS still cannot fully meet clinical requirements [21, 22]. At the same time, there are few comparative studies on which method is used to register the edentulous jaw model with no obvious curvature change. Traditional impressions taken followed by model scanning are still widely recognized by experts as digitalization methods for edentulous models [4, 5, 11, 20]. Therefore, this study used the reverse engineering software Geomagic Control 2014 to compare the registration results of the best fit alignment method and the manual registration + global registration method, and provided a reference for the three-dimensional registration method of clinical edentulous jaw impressions.Two traditional edentulous jaw impressions, open and closed-mouth impressions, were scanned in a laboratory model scanner to digitize the edentulous jaw impressions.
To facilitate the comparison of the two registration methods in this study, the 3D deviation colour order scale of manual + global registration was corrected with reference to the best fit alignment. In some scenarios requiring very high registration accuracy, the optimal quota registration method can achieve higher registration accuracy through more fine adjustment. There are large anatomical differences between different individuals, and the morphology, size and relative position may vary even at the same site. The best fit alignment method can flexibly adjust the registration strategy according to the specific characteristics of each individual, and better adapt to this individual difference. For some objects that change dynamically with time, such as bone or organ growth, the best fit alignment method can dynamically adjust the registration quota according to the characteristics and trends of different stages to achieve continuous and accurate monitoring.
The mean nominal value threshold ranged from 0.150 to 0.196 mm. The nominal value threshold proportion of the Manual + Global registration method (nearly 70%) was significantly greater than that of the Best fit alignmentMethod (less than 50%), with P < 0.05. Manual + Global registration achieved better registration quality than did the Best fit alignment. Additionally, the green area of the nominal value threshold in the Manual + Global registration method was mostly distributed in the main stress support area and the secondary stress support area where there was less mucosal deformation. In contrast, the best fit alignmentmethod showed an asymmetric deviation distribution in the main stress support area and the secondary stress support area, resulting in model misalignment. The Manual + Global registration method obtained significantly smaller average positive deviation, average negative deviation, and root mean square (RMS) values than did the Best fit alignment method for the maxilla but not significantly difference for the mandible. The Manual + Global registration is better than the Best fit alignment in terms of a smaller deviation between models, especially in the maxilla. In oral and maxillofacial surgery, such as dental implant surgery or orognathic surgery, doctors can through the preoperative imaging data (such as CT scan) on multiple key anatomical points, such as the alveolar bone vertex, neurovascular walking position, etc., and in the intraoperative navigation system to match these points with the actual anatomical structure of the patient. This method can provide a more accurate three-dimensional spatial positioning for the operation, ensure that the implantation position and angle of the implant meet the ideal biomechanical requirements, and improve the stability and success rate of the implant. In orthognathic surgery, it can help doctors to adjust the position of the jaw bone more precisely and achieve better reconstruction of the occlusal relationship.
We also attempted to use N-point alignment combined with the best fit alignment command. First, the N-Point Alignment command allows you to align objects by selecting at least three (but as many as nine) corresponding points on reference and test models. After N-point alignment, when using the best fit alignment command, only the “fine adjustments only” and “automatic deviator elimination” options were selected, and the “high-precision fitting” option was not selected. The software defaults to 1500 sampling points, which can achieve alignment results similar to Manual N-point Alignment combined with Global registration. However, if the “High-Precision Fitting” option is selected, there will be a significant shift between the models.The idea that maxilla registration plays a greater role is justified. As a relatively stable and obvious anatomical landmark structure, the hard palate can provide a relatively reliable reference point in the registration process, which helps to improve the accuracy and reproducibility of the maxillary registration.
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The reasons for the difference in the results of the two registration methods used for edentulous impressions may be as follows: ① The anatomical structure of the edentulous jaw models was affected. The edentulous jaw alveolar ridge is entirely covered by oral mucosa and is deformable and viscoelastic. In addition to the influence of muscle activity around the working area, different impression techniques can cause mucosal deformation. This deviation is much larger than that between models of teeth. ② The best fit alignment method relies solely on software calculations and may focus on minimizing overall deviation, but it may ignore clear correspondence relationships, such as anatomical marker features on the primary stress-bearing area and secondary stress-bearing area, where less mucosal mobility occurs. In a 2020 study by Professor Lucio Lo Russo et al. comparing differences between intraoral scanning and traditional impression model scanning of edentulous jaws [9], the best fit alignment method was used. One group had complete models without trimming the mobile mucosal border area, and the other group had partially trimmed models without the mobile mucosal border area. The alignment results showed significant differences; that is, the average distance between the aligned models decreased from 0.19 mm before trimming to 0.02 mm after trimming. The deviation of the models significantly decreased after trimming. The best fit alignment method may result in alignment offset when edentulous jaw models include the mobile mucosal border area. Manual multipoint alignment of edentulous jaw models is beneficial for obtaining artificial constraints on the correspondence between models. The combination of manual multi-point alignment and global alignment can achieve better alignment results for edentulous jaw models, including larger deviated marginal areas. The two registration methods have different application situations. Manual + global registration, also known as scan alignment, is the process of placing two or more objects (point or polygon) that constitute a single object in the proper position with respect to each other. The common areas between models are selected for iterative calculation of the minimum deviation without considering non overlapping areas. In this way, the main stress-bearing areas, secondary stress-bearing areas, and other areas with less mucosal mobility can be taken into account for alignment while reducing the influence of the border mobile mucosal area.
During surgery, accurate positioning helps to avoid damage to important neurovascular structures and reduce the risk of surgical complications. For example, in dental implant surgery, precise navigation and coordination can avoid damaging the lower alveolar nerve during implant implantation and reduce the occurrence of complications such as numbness of the lower lip. In orthognathic surgery, accurate jaw reduction can reduce the occurrence of postoperative complications such as poor occlusal relationship and facial asymmetry.In the postoperative follow-up, this method can be used again to compare the postoperative imaging data with the preoperative registration, and to accurately evaluate the surgical effect by measuring the position changes of the relevant anatomy of the surgical site and the displacement of the implant. For example, after dental implant surgery, the healing of bone tissue around the implant can be observed through registration and comparison, and possible complications, such as peri-implantitis and bone resorption, can be found and handled in time, so as to guarantee the long-term prognosis of patients.In daily practice, doctors can perform a detailed 3 D reconstruction and analysis of the patient’s oral cavity through this method. CT and other imaging techniques are used to mark the key anatomical points of the alveolar bone, such as the top of the alveolar crest, the bottom of the maxillary sinus, and the inferior alveolar nerve canal, etc., to accurately match the actual anatomy of the patient, so as to determine the optimal location, Angle and depth of the implant implantation. This can effectively avoid damage to the important anatomical structure, improve the initial stability and long-term success rate of the implant, and achieve more ideal function and aesthetic effect for patients.There have been some studies on the short-term effect of artificial multipoint combination global coordination methods in dental practice, but the evaluation of their long-term effect is relatively insufficient. Long-term follow-up studies are needed to observe the long-term survival rate of implants, the recurrence rate after orthodontic treatment, and the service life of restorations, so as to comprehensively evaluate the clinical value and safety of this method and provide more powerful evidence for clinical application.
However, this study still has limitations: 1. Sample size: The number of samples used in the study is relatively small, which may not fully represent the entire population, and the universality and reliability of the results may be affected. 2. Selection of subjects: In the aspect of edentulous jaw, only specific types of patients were involved, such as patients with non tempo-mandibular joint disease, mucosal disease or abnormal occlusion, which may limit the generalization of the research results. 3. Research methods: Although the comparative study of the two registration methods is adopted, there may still be other effective registration methods that have not been considered or compared, which affects the comprehensiveness of the conclusion. 4. Instruments and software: The model scanners and reverse engineering software used in the study may have limitations, and different equipment and software may have an impact on the results.
In summary, although the combination of manual multi-point alignment and global alignment can improve the alignment effect of the edentulous jaw model, especially in the deviation processing of the edge region, the manual multi-point combined global registration method is more accurate than the best fit alignment used in the edentulous jaw impression registration, and is more effective for the maxilla.The above restrictive factors need to be considered and solved more comprehensively in further research and practice to ensure the accuracy and effectiveness of the research conclusions.
Conclusion
In summary, for dental model 3D deviation research involving no significant curvature change characteristics or symmetry, such as edentulous jaw models with large deviations in the margin area, manual multi-point registration combined with the global registration method will yield more accurate and reliable registration results than the best fit alignment method, which relies absolutely on automatic calculations by software. However, due to the small sample size in this study, additional clinical research is needed for validation. In the study of edentulous model deviation and digital clinical practice, when a significant deviation in the registration results was found, it was worth trying to increase the recognizable corresponding relationship between models as a constraint to improve the quality of the registration results.
Acknowledgements
The authors appreciatively acknowledge Tian-Yu Zhang and Jian-Min Wang for help with the model scanning.
Declarations
Ethics approval and consent to participate
The study was conducted in accordance with the Declaration of Helsinki and approved by the Biomedical Ethics Committee of Dalian Stomatological Hospital (DLKQLL2018011). Written informed consent was obtained from all participants.
Informed consent
Informed consent was obtained from all the subjects involved in the study.
Competing interests
The authors declare no competing interests.
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