An image-guided hybrid robot system for dental implant surgery

Robot-assisted surgery for dental implant placement: A narrative review

OBJECTIVE

To determine the current status and accuracy of robotic computer-assisted implant surgery (CAIS) applications by examining the associated clinical and experimental outcomes.

DATA AND SOURCES

PubMed, Medline, and Cochrane Library databases were searched for relevant studies published between January 2000 and November 2023, and focusing on robotic CAIS in dental implant surgery. All search results were then manually reviewed to identify only the pertinent articles. Only in vitro and clinical studies were included in this narrative review, with implant placement accuracy considered the main outcome.

RESULT

Based on our inclusion and exclusion criteria, we included 21 studies (with 1085 implant sites); of them, 8 were clinical studies, 12 were in vitro studies, and 1 included both an in vitro study and a case series. The ranges of the mean implant shoulder, apical, and angular deviations were respectively 0.43-1.04 mm, 0.53-1.06 mm, and 0.77°-3.77° in the clinical studies and 0.23-1.04 mm, 0.24-2.13 mm, and 0.43°-3.78° in the in vitro studies, respectively.

CONCLUSION

The accuracy of robotic CAIS in dental implant procedures appears to be within the clinically acceptable ranges. However, further relevant clinical trials validating the existing evidence are needed.

CLINICAL SIGNIFICANCE

Robotic CAIS can achieve clinically acceptable implant placement accuracy. This innovative technology may improve the precision and success rates of dental implant procedures, with benefit for surgeons and patients.

Accuracy analysis of robotic-assisted immediate implant placement: A retrospective case series

OBJECTIVES

This study aimed to investigate the accuracy of a robotic computer-assisted implant surgery (r-CAIS) for immediate implant placement.

METHODS

Patients requiring immediate implant placement in the maxillary anterior region were enrolled for r-CAIS. Before surgery, the patients underwent a cone beam computed tomography (CBCT) scan with a positioning marker. Virtual implant placement position and drilling sequences were planned. Following spatial registration and calibration, the implants were placed with the robotic system under supervision. A postoperative CBCT was taken to control the actual implant positions. The DICOM data of the virtually planned and the actually placed implant were superimposed and registered through the accuracy verification software of the robotic system. The accuracy was calculated automatically. The deviation at the mesial-distal, labial-palatal, and apico-coronal directions were recorded.

RESULTS

Fifteen patients with 20 implants were included. No adverse surgical events or postoperative complications were reported. The global platform, apex, and angular deviation were 0.75 ± 0.20 mm (95 % CI: 0.65 to 0.84 mm), 0.70 ± 0.27 mm (95 % CI: 0.57 to 0.82 mm), and 1.17 ± 0.73° (95 % CI: 0.83 to 1.51°), respectively. Moreover, the vertical platform and apex deviation were 0.50 ± 0.31 mm, (95 % CI: 0.35 to 0.64 mm) and 0.48 ± 0.32 mm, (95 % CI: 0.33 to 0.63 mm), respectively. All the placed implant positions were further labial and apical than the planned ones, respectively.

CONCLUSIONS

High accuracy of immediate implant placement was achieved with the robotic system.

CLINICAL SIGNIFICANCE

Our study provided evidence to support the potential of the robotic system in implant placement, even in challenging scenarios.

Accuracy of an autonomous dental implant robotic system in partial edentulism: A pilot clinical study

OBJECTIVES

Robots are increasingly being used for surgical procedures in various specialties. However, information about the accuracy of robot-assisted dental implant surgery is lacking. This pilot clinical study aimed to investigate the accuracy of an autonomous dental implant robotic (ADIR) system in partially edentulous cases.

MATERIAL AND METHODS

The ADIR system was used to place a total of 20 implants in 13 participants. Implant deviation from the planned positions was assessed to determine accuracy. The entry, apex, and angular deviations were described as means ± standard deviation. A two-sample t test was used to compare implant deviation between the flap and flapless groups and between maxillary and mandibular implants (α = .05).

RESULTS

The entry, apex, and angular deviations were 0.65 ± 0.32 mm, 0.66 ± 0.34 mm, and 1.52 ± 1.01°, respectively, with no statistically significant difference between the flap and flapless approaches (P > .05). No adverse events were encountered in any of the participants.

CONCLUSIONS

DIR accuracy in this clinical series was comparable to that reported for static and dynamic computer-assisted implant surgery. Robotic computer-assisted implant surgery may be useful for dental implant placement, potentially improving the quality and safety of the procedure.

CLINICAL RELEVANCE

The findings of this study showed that the ADIR system could be useful for dental implant surgery.

A hybrid robotic system for zygomatic implant placement based on mixed reality navigation

BACKGROUNDS

Zygomatic implant (ZI) placement surgery is a viable surgical option for patients with severe maxillary atrophy and insufficient residual maxillary bone. Still, it is difficult and risky due to the long path of ZI placement and the narrow field of vision. Dynamic navigation is a superior solution, but it presents challenges such as requiring operators to have advanced skills and experience. Moreover, the precision and stability of manual implantation remain inadequate. These issues are anticipated to be addressed by implementing robot-assisted surgery and achieved by introducing a mixed reality (MR) navigation-guided hybrid robotic system for ZI placement surgery.

METHODS

This study utilized a hybrid robotic system to perform the ZI placement surgery. Our first step was to reconstruct a virtual 3D model from preoperative cone-beam CT (CBCT) images. We proposed a series of algorithms based on coordinate transformation, which includes image-phantom registration, HoloLens-tracker registration, drill-phantom calibration, and robot-implant calibration, to unify all objects within the same coordinate system. These algorithms enable real-time tracking of the surgical drill's position and orientation relative to the patient phantom. Subsequently, the surgical drill is directed to the entry position, and the planned implantation paths are superimposed on the patient phantom using HoloLens 2 for visualization. Finally, the hybrid robot system performs the processed of drilling, expansion, and placement of ZIs under the guidance of the MR navigation system.

RESULTS

Phantom experiments of ZI placement were conducted using 10 patient phantoms, with a total of 40 ZIs inserted. Out of these, 20 were manually implanted, and the remaining 20 were robotically implanted. Comparisons between the actual implanted ZI paths and the preoperatively planned ZI paths showed that our MR navigation-guided hybrid robotic system achieved a coronal deviation of 0.887 ± 0.213 mm, an apical deviation of 1.201 ± 0.318 mm, and an angular deviation of 3.468 ± 0.339° This demonstrates significantly better accuracy and stability than manual implantation.

CONCLUSION

Our proposed hybrid robotic system enables automated ZI placement surgery guided by MR navigation, achieving greater accuracy and stability compared to manual operations in phantom experiments. Furthermore, this system is expected to apply to animal and cadaveric experiments, to get a good ready for clinical studies.

Automatic planning of maxillary anterior dental implant based on prosthetically guided and pose evaluation indicator

PURPOSE

Preoperative planning of maxillary anterior dental implant is a prerequisite to ensuring that the implant achieves the proper three-dimensional (3D) pose, which is essential for its long-term stability. However, the current planning process is labor-intensive and subjective, relying heavily on the surgeon's experience. Consequently, this paper proposes an automatic method for computing the optimal pose of the dental implant.

METHODS

The method adopts the principle of prosthetically guided dental implant placement. Initially, the prosthesis coordinate system is established to determine the implant candidate orientations. Subsequently, virtual slices of the maxilla in the buccal-palatal direction are generated according to the prosthesis position. By extracting feature points from the virtual slices, the implant candidate starting points are acquired. Then, a candidate pose set is obtained by combining these candidate starting points and orientations. Finally, a pose evaluation indicator is introduced to determine the optimal implant pose from this set.

RESULTS

Twenty-two cases were utilized to validate the method. The results show that the method could determine an ideal pose for the dental implant, with the average minimum distance between the implant and the left tooth root, the right tooth root, the palatal side, and the buccal side being 2.57 ± 0.53 mm, 2.59 ± 0.65 mm, 0.74 ± 0.19 mm, 1.83 ± 0.16 mm, respectively. The planning time was less than 9 s.

CONCLUSION

Unlike manual planning, the proposed method can efficiently and accurately complete maxillary anterior dental implant planning, providing a theoretical analysis of the success rate of the implant. Thus, it has great potential for future clinical application.

The evolution of robotics: research and application progress of dental implant robotic systems

The use of robots to augment human capabilities and assist in work has long been an aspiration. Robotics has been developing since the 1960s when the first industrial robot was introduced. As technology has advanced, robotic-assisted surgery has shown numerous advantages, including more precision, efficiency, minimal invasiveness, and safety than is possible with conventional techniques, which are research hotspots and cutting-edge trends. This article reviewed the history of medical robot development and seminal research papers about current research progress. Taking the autonomous dental implant robotic system as an example, the advantages and prospects of medical robotic systems would be discussed which would provide a reference for future research.

Comparison of the positional accuracy of robotic guided dental implant placement with static guided and dynamic navigation systems: A systematic review and meta-analysis

STATEMENT OF PROBLEM

The development of robotic computer assisted implant surgery (r-CAIS) offers advantages, but how the positional accuracy of r-CAIS compares with other forms of guided implant surgery remains unclear.

PURPOSE

The purpose of this systematic review and meta-analysis was to evaluate the positional accuracy of r-CAIS and to compare the positional accuracy of r-CAIS with s-CAIS and d-CAIS.

MATERIAL AND METHODS

Five databases were systematically searched by 2 independent reviewers for articles published before May 2023. A manual search was also performed. Articles evaluating the positional accuracy of r-CAIS were included. The Cochrane risk of bias tool was used for the clinical studies, whereas the QUIN tool was used for the in vitro studies. A meta-analysis was performed to compare the positional accuracy of r-CAIS with d-CAIS.

RESULTS

Thirteen studies were included, with 9 in vitro studies, 4 clinical studies, and a total of 920 dental implants. A high risk of bias was noted in 6 studies and low to moderate in 7 studies. R-CAIS showed greater accuracy for the coronal, apical, and angular deviations compared with d-CAIS. (-0.17 [-0.24, 0.09], (P<.001); -0.21 [-0.36, -0.06] (P=.006), and -1.41 [-1.56, -1.26] (P<.001)) CONCLUSIONS: R-CAIS can provide improved positional accuracy compared with d-CAIS when considering coronal, apical, and angular deviations. However, evidence to compare the positional accuracy of r-CAIS with s-CAIS was insufficient. These results should be interpreted with caution because of the limited data and the bias noted in several studies.

Accuracy assessment of robot-assisted implant surgery in dentistry: A systematic review and meta-analysis

STATEMENT OF PROBLEM

The systematic assessment of accuracy of robot-assisted implant surgery is lacking.

PURPOSE

The purpose of this systematic review and meta-analysis was to evaluate the accuracy of robot-assisted implant surgery and compare it with computer-aided implant surgery in partially and completely edentulous patients and human phantoms.

MATERIAL AND METHODS

The studies were selected from ScienceDirect, Web of science, Cochrane Library, PubMed, and CNKI databases. The risk of bias of the included studies was evaluated with the risk of bias in nonrandomized studies of interventions tool. The mean and standard deviation of global coronal, apical, and angular deviations of implants were the primary outcome. Meta-analysis was conducted to evaluate the accuracy of the robot-assisted implant surgery and compare it with computer-aided implant surgery in dental implantation (α=.05).

RESULTS

Eleven in vitro studies with 809 implants and 10 clinical studies with 257 implants were included. For the in vitro studies, the mean global coronal, apical, and angular deviations of robot-assisted implant surgery were 0.7 mm (95% CI: 0.6 to 0.8), 0.8 mm (95% CI: 0.6 to 1.0), and 1.8 degrees (95%CI: 1.2 to 2.5), respectively. For the clinical studies, the average global coronal, apical, and angular deviations of robot-assisted implant surgery were 0.6 mm (95% CI: 0.5 to 0.8), 0.7 mm (95% CI: 0.6 to 0.8), and 1.6 degrees (95%CI: 1.1 to 2.0), respectively. For the in vitro studies, the robot-assisted implant surgery group showed significantly more decrease in global coronal deviation than the computer-assisted implant surgery group (P=.012). The robot-assisted implant surgery group offered smaller global apical deviation (P=.001) and angular deviation (P<.001) than the computer-assisted implant surgery group.

CONCLUSIONS

Robot navigation is a clinically reliable method of implant placement. Significantly lower global coronal, apical, and angular deviations were observed for robot-assisted implant surgery compared with computer-assisted implant surgery in human phantoms.

Accuracy Comparison between Robot-Assisted Dental Implant Placement and Static/Dynamic Computer-Assisted Implant Surgery: A Systematic Review and Meta-Analysis of In Vitro Studies

Background and Objectives: The present systematic review and meta-analysis undertake a comparison of studies that examine the accuracy of robot-assisted dental implant placement in relation to static computer-assisted implant surgery (SCAIS), dynamic computer-assisted implant surgery (DCAIS), and freehand procedures. This study aims to provide a comprehensive understanding of the precision of robot-assisted dental implant placement and its comparative efficacy in relation to other placement techniques. Methods: The guidelines recommended by Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) were used to organize and compose this review. Four electronic databases (PubMed, Web of Science, Scopus, and Cochrane) were systematically searched for pertinent articles. Articles were selected following the inclusion and exclusion criteria. Qualitative and quantitative analyses of the selected articles were performed. Results: The initial electronic search resulted in 1087 hits. Based on the inclusion and exclusion criteria, five articles were selected for qualitative analysis, out of which three were considered for quantitative analysis. Three parameters were considered for accuracy evaluation (angular, coronal, and apical deviation). The mean angular deviation was -1.22 degrees (95% CI, -1.06--1.39), the mean coronal deviation was -0.15 mm (95% CI, -0.24--0.07), and the mean apical deviation was -0.19 mm (95% CI, -0.27--0.10). Conclusions: The robotic implant system was found to have significantly lower angular deviations and insignificantly lower coronal and apical deviations compared to DCAIS. Within the limitations of this review, it can be concluded that robot-assisted implant placement in resin models permits higher accuracy compared to DCAIS and SCAIS systems. However, due to the limited number of comparative studies with high heterogeneity, the findings of this review should be interpreted with caution. Further research is necessary to confirm the clinical application of robotics in implant surgery.

Modern Image-Guided Surgery: A Narrative Review of Medical Image Processing and Visualization

Medical image analysis forms the basis of image-guided surgery (IGS) and many of its fundamental tasks. Driven by the growing number of medical imaging modalities, the research community of medical imaging has developed methods and achieved functionality breakthroughs. However, with the overwhelming pool of information in the literature, it has become increasingly challenging for researchers to extract context-relevant information for specific applications, especially when many widely used methods exist in a variety of versions optimized for their respective application domains. By being further equipped with sophisticated three-dimensional (3D) medical image visualization and digital reality technology, medical experts could enhance their performance capabilities in IGS by multiple folds. The goal of this narrative review is to organize the key components of IGS in the aspects of medical image processing and visualization with a new perspective and insights. The literature search was conducted using mainstream academic search engines with a combination of keywords relevant to the field up until mid-2022. This survey systemically summarizes the basic, mainstream, and state-of-the-art medical image processing methods as well as how visualization technology like augmented/mixed/virtual reality (AR/MR/VR) are enhancing performance in IGS. Further, we hope that this survey will shed some light on the future of IGS in the face of challenges and opportunities for the research directions of medical image processing and visualization.

Advancing accuracy in guided implant placement: A comprehensive meta-analysis: Meta-Analysis evaluation of the accuracy of available implant placement Methods

OBJECTIVES

This meta-analysis aimed to determine the accuracy of currently available computer-assisted implant surgery (CAIS) modalities under in vitro conditions and investigate whether these novel techniques can achieve clinically acceptable accuracy.

DATA

In vitro studies comparing the postoperative implant position with the preoperative plan were included. Risk of bias was assessed using the Quality Assessment Tool For In Vitro Studies (QUIN Tool) and a sensitivity analysis was conducted using funnel plots.

SOURCES

A systematic search was performed on April 18, 2023, using the following three databases: MEDLINE (via PubMed), EMBASE, and Cochrane Central Register of Controlled Trials. No filters or restrictions were applied during the search.

RESULTS

A total of 5,894 studies were included following study selection. Robotic- and static CAIS (sCAIS) had the most accurate and clinically acceptable outcomes. sCAIS was further divided according to the guidance level. Among the sCAIS groups, fully guided implant placement had the greatest accuracy. Augmented reality-based CAIS (AR-based CAIS) had clinically acceptable results for all the outcomes except for apical global deviation. Dynamic CAIS (dCAIS) demonstrated clinically safe results, except for horizontal apical deviation. Freehand implant placement was associated with the greatest number of errors.

CONCLUSIONS

Fully guided sCAIS demonstrated the most predictable outcomes, whereas freehand sCAIS demonstrated the lowest accuracy. AR-based and robotic CAIS may be promising alternatives.

CLINICAL SIGNIFICANCE

To our knowledge, this is the first meta-analysis to evaluate the accuracy of robotic CAIS and investigate the accuracy of various CAIS modalities.

Accuracy and efficiency of robotic dental implant surgery with different human-robot interactions: An in vitro study

OBJECTIVES

This study aims to compare the surgical efficiency (preparation and operation time) and accuracy of implant placement between robots with different human-robot interactions.

METHODS

The implant robots were divided into three groups: semi-active robot (SR), active robot (AR) and passive robot (PR). Each robot placed two implants (#31 and #36) on a phantom, practising 10 times. The surgical efficiency and accuracy of implant placement were then evaluated.

RESULTS

Sixty implants were placed in 30 phantoms. The mean preparation times for the AR, PR and SR groups were 3.85 ± 0.17 min, 2.14 ± 0.06 mins and 1.65 ± 0.19 mins, respectively. The mean operation time of the PR group (3.76 ± 0.59 min) was shorter that of than the AR (4.89 ± 0.70 mins) and SR (4.59 ± 0.56 min) groups (all P < 0.001). The operation time of the AR group in the anterior region (4.47 ± 0.31 min) was longer than that of the SR group (4.07 ± 0.10 min) (P = 0.007). The mean coronal, apical and axial deviations of the PR group (0.40 ± 0.12 mm, 0.49 ± 0.13 mm, 0.96 ± 0.22°) were higher than those of the AR (0.23 ± 0.11 mm, 0.24 ± 0.11 mm, 0.54 ± 0.20 °) (all P < 0.001) and SR (0.31 ± 0.10 mm, 0.36 ± 0.12 mm, 0.43 ± 0.14 °) groups (P = 0.044, P = 0.002, and P < 0.001, respectively).

CONCLUSIONS

Human-robot interactions affect the efficiency of implant surgery. Active and semi-active robots show comparable implant accuracy. However, the implants placed by the passive robot show higher deviations.

CLINICAL SIGNIFICANCE

This in vitro study preliminarily demonstrates that implant placement is accurate when using implant robots with different human-robot interactions. However, different human-robot interactions have variable surgical efficiencies.

Autonomous aspirating robot for removing saliva blood mixed liquid in oral surgery

Saliva blood mixed liquid (SBML) appears in oral surgery, such as scaling and root planning, and it affects surgical vision and causes discomfort to the patient. However, removing SBML, i.e. frequent aspiration of the mixed liquid, is a routine task involving heavy workload and interruption of oral surgery. Therefore, it is valuable to alternate the manual mode by autonomous robotic technique. The robotic system is designed consisting of an RGB-D camera, a manipulator, a disposable oral aspirator. An algorithm is developed for detection of SBML. Path planning method is also addressed for the distal end of the aspirator. A workflow for removing SBML is presented. 95% of the area of the SBML in the oral cavity was removed after liquid aspiration among a group of ten SBML aspiration experiments. This study provides the first result of the autonomous aspirating robot (AAR) for removing SBML in oral surgery, demonstrating that SBML can be removed by the autonomous robot, freeing stomatology surgeon from tedious work.

Accuracy of implant site preparation in robotic navigated dental implant surgery

BACKGROUND

Modern technological advancements have led to increase in the development of surgical robots in dentistry, resulting in excellent clinical treatment outcomes.

PURPOSE

This study aimed to determine the accuracy of automatic robotic implant site preparation for different implant sizes by correlating planned and posttreatment positions, and to compare the performance of robotic and human freehand drilling.

METHOD

Seventy-six drilling sites on partially edentulous models were used, with three different implant sizes (Ø = 3.5 × 10 mm, 4.0 × 10 mm, 5.0 × 10 mm). The robotic procedure was performed using software for calibration and step-by-step drilling processes. After robotic drilling, deviations in the implant position from the planned position were determined. The angulation, depth, and coronal and apical diameters on the sagittal plane of sockets created by human and robotic drilling were measured.

RESULTS

The deviation of the robotic system was 3.78° ± 1.97° (angulation), 0.58 ± 0.36 mm (entry point), and 0.99 ± 0.56 mm (apical point). Comparison of implant groups showed the largest deviation from the planned position for 5 mm implants. On the sagittal plane, there were no significant differences between robotic and human surgery except for the 5-mm implant angulation, indicating similar quality between human and robotic drilling. Based on standard implant measurements, robotic drilling exhibited comparable performance to freehand human drilling.

CONCLUSIONS

A robotic surgical system can provide the greatest accuracy and reliability regarding the preoperative plan for small implant diameters. In addition, the accuracy of robotic drilling for anterior implant surgery can also be comparable to that of human drilling.

Preoperative Planning Framework for Robot-Assisted Dental Implant Surgery: Finite-Parameter Surrogate Model and Optimization of Instrument Placement

For robot-assisted dental implant surgery, it is necessary to feed the instrument into a specified position to perform surgery. To improve safety and efficiency, a preoperative planning framework, including a finite-parameter surrogate model (FPSM) and an automatic instrument-placement method, is proposed in this paper. This framework is implemented via two-stage optimization. In the first stage, a group of closed curves in polar coordinates is used to represent the oral cavity. By optimizing a finite number of parameters for these curves, the oral structure is simplified to form the FPSM. In the second stage, the FPSM serves as a fast safety estimator with which the target position/orientation of the instrument for the feeding motion is automatically determined through particle swarm optimization (PSO). The optimized feeding target can be used to generate a virtual fixture (VF) to avoid undesired operations and to lower the risk of collision. This proposed framework has the advantages of being safe, fast, and accurate, overcoming the computational burden and insufficient real-time performance of complex 3D models. The framework has been developed and tested, preliminarily verifying its feasibility, efficiency, and effectiveness.

Comparison the accuracy of a novel implant robot surgery and dynamic navigation system in dental implant surgery: an in vitro pilot study

BACKGROUND

To compare the accuracy of dental implant placement using a novel dental implant robotic system (THETA) and a dynamic navigation system (Yizhimei) by a vitro model experiment.

METHODS

10 partially edentulous jaws models were included in this study, and 20 sites were randomly assigned into two groups: the dental implant robotic system (THETA) group and a dynamic navigation system (Yizhimei) group. 20 implants were placed in the defects according to each manufacturer's protocol respectively. The implant platform, apex and angle deviations were measured by fusion of the preoperative design and the actual postoperative cone-beam computed tomography (CBCT) using 3D Slicer software. Data were analyzed by t - test and Mann-Whitney U test, p < 0.05 was considered statistically significant.

RESULTS

A total of 20 implants were placed in 10 phantoms. The comparison deviation of implant platform, apex and angulation in THETA group were 0.58 ± 0.31 mm, 0.69 ± 0.28 mm, and 1.08 ± 0.66° respectively, while in Yizhimei group, the comparison deviation of implant platform, apex and angulation were 0.73 ± 0.20 mm, 0.86 ± 0.33 mm, and 2.32 ± 0.71° respectively. The angulation deviation in THETA group was significantly smaller than the Yizhimei group, and there was no significant difference in the deviation of the platform and apex of the implants placed using THETA and Yizhimei, respectively.

CONCLUSION

The implant positioning accuracy of the robotic system, especially the angular deviation was superior to that of the dynamic navigation system, suggesting that the THETA robotic system could be a promising tool in dental implant surgery in the future. Further clinical studies are needed to evaluate the current results.

The effect of implant surgery experience on the learning curve of a dynamic navigation system: an in vitro study

BACKGROUND

Dynamic navigation systems have a broad application prospect in digital implanting field. This study aimed to explore and compare the dynamic navigation system learning curve of dentists with different implant surgery experience through dental models.

METHODS

The nine participants from the same hospital were divided equally into three groups. Group 1 (G1) and Group 2 (G2) were dentists who had more than 5 years of implant surgery experience. G1 also had more than 3 years of experience with dynamic navigation, while G2 had no experience with dynamic navigation. Group 3 (G3) consisted of dentists with no implant surgery experience and no experience with dynamic navigation. Each participant sequentially placed two implants (31 and 36) on dental models according to four practice courses (1-3, 4-6, 7-9, 10-12 exercises). Each dentist completed 1-3, 4-6 exercises in one day, and then 7-9 and 10-12 exercises 7 ± 1 days later. The preparation time, surgery time and related implant accuracy were analyzed.

RESULTS

Three groups placed 216 implants in four practice courses. The regressions for preparation time (F = 10.294, R² = 0.284), coronal deviation (F = 4.117, R² = 0.071), apical deviation (F = 13.016, R² = 0.194) and axial deviation (F = 30.736, R² = 0.363) were statistically significant in G2. The regressions for preparation time (F = 9.544, R² = 0.269), surgery time (F = 45.032, R² = 0.455), apical deviation (F = 4.295, R² = 0.074) and axial deviation (F = 21.656, R² = 0.286) were statistically significant in G3. Regarding preparation and surgery time, differences were found between G1 and G3, G2 and G3. Regarding implant accuracy, differences were found in the first two practice courses between G1 and G3.

CONCLUSIONS

The operation process of dynamic navigation system is relatively simple and easy to use. The linear regression analysis showed there is a dynamic navigation learning curve for dentists with or without implant experience and the learning curve of surgery time for dentists with implant experience fluctuates. However, dentists with implant experience learn more efficiently and have a shorter learning curve.

The Feasibility of Robot-Assisted Chin Osteotomy on Skull Models: Comparison with Surgical Guides Technique

Surgical robotic technology is characterized by its high accuracy, good stability, and repeatability. The accuracy of mandibular osteotomy is important in tumor resection, function reconstruction, and abnormality correction. This study is designed to compare the operative accuracy between robot-assisted osteotomy and surgical guide technique in the skull model trials which simulated the genioplasty. In an experimental group, robot-assisted chin osteotomy was automatically performed in 12 models of 12 patients according to the preoperative virtual surgical planning (VSP). In a control group, with the assistance of a surgical guide, a surgeon performed the chin osteotomy in another 12 models of the same patients. All the mandibular osteotomies were successfully completed, and then the distance error and direction error of the osteotomy plane were measured and analyzed. The overall distance errors of the osteotomy plane were 1.57 ± 0.26 mm in the experimental group and 1.55 ± 0.23 mm in the control group, and the direction errors were 7.99 ± 1.10° in the experimental group and 8.61 ± 1.05° in the control group. The Bland-Altman analysis results revealed that the distance error of 91.7% (11/12) and the direction error of 100% (12/12) of the osteotomy plane were within the 95% limits of agreement, suggesting the consistency of differences in the osteotomy planes between the two groups. Robot-assisted chin osteotomy is a feasible auxiliary technology and achieves the accuracy level of surgical guide-assisted manual operation.

Dental Implant Navigation System Based on Trinocular Stereo Vision

Traditional dental implant navigation systems (DINS) based on binocular stereo vision (BSV) have limitations, for example, weak anti-occlusion abilities, as well as problems with feature point mismatching. These shortcomings limit the operators’ operation scope, and the instruments may even cause damage to the adjacent important blood vessels, nerves, and other anatomical structures. Trinocular stereo vision (TSV) is introduced to DINS to improve the accuracy and safety of dental implants in this study. High positioning accuracy is provided by adding cameras. When one of the cameras is blocked, spatial positioning can still be achieved, and doctors can adjust to system tips; thus, the continuity and safety of the surgery is significantly improved. Some key technologies of DINS have also been updated. A bipolar line constraint algorithm based on TSV is proposed to eliminate the feature point mismatching problem. A reference template with active optical markers attached to the jaw measures head movement. A T-type template with active optical markers is used to obtain the position and direction of surgery instruments. The calibration algorithms of endpoint, axis, and drill are proposed for 3D display of the surgical instrument in real time. With the preoperative path planning of implant navigation software, implant surgery can be carried out. Phantom experiments are carried out based on the system to assess the feasibility and accuracy. The results show that the mean entry deviation, exit deviation, and angle deviation are 0.55 mm, 0.88 mm, and 2.23 degrees, respectively.

Evaluation of a custom-designed human-robot collaboration control system for dental implant robot

BACKGROUND

The purpose of this study is to develop a methodology to better control a human-robot collaboration for robotic dental implant placement. We have designed a human-robot collaborative implant system (HRCDIS) which is based on a zero-force hand-guiding concept and a operational task management workflow that can achieve highly accurate and stable osteotomy drilling based on a surgeon's decision and robotic arm movements during implant surgery.

METHOD

The HRCDIS brings forth the robot arm positions, exact drilling location, direction and performs automatic drilling. The HRCDIS can also avoid complex programing in the robot. The purpose of the study is to evaluate the accuracy of drilling resulting from our developed operational task management method (OTMM). The OTMM can enable the robot to switch, pause, and resume drilling tasks. The force required for hand-guiding in a zero-force control mode of the robot was detected by a 6D force sensor. We compared our force data to those provided by the manufacturer's manual. The study was conducted on a phantom head with a 3D-printed jaw bone to verify the validity of our HRCDIS. We appraised the discrepancies between free-hand drillings and the HRCDIS controlled drillings at apical centre and head centre of the implant and implant angulation to the baseline data from a virtual surgical planning model.

RESULTS

The average required force used by hand-guiding to operate the robot with HRCDIS was near 7 Newton which is much less than the manufacturer's specification (30 Newton). The results from our study showed that the average error at implant head was 1.04 ± 0.37 mm, 1.56 ± 0.52 mm at the implant apex, and deviation of implant angle was 3.74 ± 0.67°.

CONCLUSIONS

The results from this study validate the merit of the human-robot collaboration control by the HRCDIS. Based on the improved navigation system using HRCDIS, a robotic implant placement can provide seamless drilling with ease, efficiency and accuracy.