Autonomous bone reposition around anatomical landmark for robot-assisted orthognathic surgery

Clinical application of robots in dentistry: A scoping review

PURPOSE

The surge in digitalization and artificial intelligence has led to the wide application of robots in various fields, but their application in dentistry started relatively late. This scoping review aimed to comprehensively explore and map the current status of the clinical application of robots in dentistry.

STUDY SELECTION

An iterative approach was used to gather as much evidence as possible from four online databases, including PubMed, the China National Knowledge Infrastructure, the Japan Science and Technology Information Aggregator, Electronic, and the Institute of Electrical and Electronics Engineers, from January 1980 to December 2022.

RESULTS

A total of 113 eligible articles were selected from the search results, and it was found that most of the robots were developed and applied in the United States (n = 56; 50%). Robots were clinically applied in oral and maxillofacial surgery, oral implantology, prosthodontics, orthodontics, endodontics, and oral medicine. The development of robots in oral and maxillofacial surgery and oral implantology is relatively fast and comprehensive. About 51% (n = 58) of the systems had reached clinical application, while 49% (n = 55) were at the pre-clinical stage. Most of these are hard robots (90%; n = 103), and their invention and development were mainly focused on university research groups with long research periods and diverse components.

CONCLUSIONS

There are still limitations and gaps between research and application in dental robots. While robotics is threatening to replace clinical decision-making, combining it with dentistry to gain maximum benefit remains a challenge for the future.

Ultraviolet disinfection (UV-D) robots: bridging the gaps in dentistry

Maintaining a microbe-free environment in healthcare facilities has become increasingly crucial for minimizing virus transmission, especially in the wake of recent epidemics like COVID-19. To meet the urgent need for ongoing sterilization, autonomous ultraviolet disinfection (UV-D) robots have emerged as vital tools. These robots are gaining popularity due to their automated nature, cost advantages, and ability to instantly disinfect rooms and workspaces without relying on human labor. Integrating disinfection robots into medical facilities reduces infection risk, lowers conventional cleaning costs, and instills greater confidence in patient safety. However, UV-D robots should complement rather than replace routine manual cleaning. To optimize the functionality of UV-D robots in medical settings, additional hospital and device design modifications are necessary to address visibility challenges. Achieving seamless integration requires more technical advancements and clinical investigations across various institutions. This mini-review presents an overview of advanced applications that demand disinfection, highlighting their limitations and challenges. Despite their potential, little comprehensive research has been conducted on the sterilizing impact of disinfection robots in the dental industry. By serving as a starting point for future research, this review aims to bridge the gaps in knowledge and identify unresolved issues. Our objective is to provide an extensive guide to UV-D robots, encompassing design requirements, technological breakthroughs, and in-depth use in healthcare and dentistry facilities. Understanding the capabilities and limitations of UV-D robots will aid in harnessing their potential to revolutionize infection control practices in the medical and dental fields.

Revolutionizing Dental Care: A Comprehensive Review of Artificial Intelligence Applications Among Various Dental Specialties

Since the beginning of recorded history, the human brain has been one of the most intriguing structures for scientists and engineers. Over the centuries, newer technologies have been developed based on principles that seek to mimic their functioning, but the creation of a machine that can think and behave like a human remains an unattainable fantasy. This idea is now known as "artificial intelligence". Dentistry has begun to experience the effects of artificial intelligence (AI). These include image enhancement for radiology, which improves the visibility of dental structures and facilitates disease diagnosis. AI has also been utilized for the identification of periapical lesions and root anatomy in endodontics, as well as for the diagnosis of periodontitis. This review is intended to provide a comprehensive overview of the use of AI in modern dentistry's numerous specialties. The relevant publications published between March 1987 and July 2023 were identified through an exhaustive search. Studies published in English were selected and included data regarding AI applications among various dental specialties. Dental practice involves more than just disease diagnosis, including correlation with clinical findings and administering treatment to patients. AI cannot replace dentists. However, a comprehensive understanding of AI concepts and techniques will be advantageous in the future. AI models for dental applications are currently being developed.

Robotic calvarial bone sampling

The aim of this study was to assess the feasibility of complex unicortical calvarial harvesting by using the Cold Ablation Robot-Guided Laser Osteotome (CARLO® primo+). A cadaveric study was performed with a progressive complexity of the bone harvesting. This preliminary study on the cadaveric cranial vault area examined the tracking precision, the strategies, settings and durations of harvesting, the accuracy of the unicortical bone cutting, and the risk of dura exposition. All sampling was realised with no more difficulty than that experienced during the standard procedure. No bicortical cutting occurred during CARLO® primo + robot-guided laser cutting. During the second sampling, dura was partially exposed due to improper angulation of the curved osteotome during harvesting. Complex unicortical calvarial harvesting using robot-guided laser appears to be feasible and safe. In the future, robotic approaches will probably replace current surgical techniques using cutting guides and help reduce intraoperative inaccuracies due to the human factor.

Advances in Robot-Assisted Surgery for Facial Bone Contouring Surgery

Since our team reported the application of robot-assisted surgery in facial contouring surgery in 2020, further clinical trials with large samples have been conducted. This paper will report the interim results of a single-center, large-sample randomized controlled trial of the first robot developed by our team for facial contouring surgery. Meanwhile, this research field will be systematically reviewed and prospected.

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.

Assessment of Robot-Assisted Mandibular Contouring Surgery in Comparison With Traditional Surgery: A Prospective, Single-Center, Randomized Controlled Trial

BACKGROUND

Few clinical studies on robot-assisted surgery (RAS) for mandibular contouring have been reported.

OBJECTIVES

The aim of this study was to follow the long-term effectiveness and safety of RAS for craniofacial bone surgery.

METHODS

This small-sample, early-phase, prospective, randomized controlled study included patients diagnosed with mandibular deformity requiring mandibular contouring surgery. Patients of both genders aged 18 to 30 years without complicated craniofacial repair defects were enrolled and randomly assigned in a 1:1 ratio by a permuted-block randomized assignments list generated by the study statistician. The primary outcomes were the positioning accuracy and accuracy of the osteotomy plane angle 1 week after surgery. Surgical auxiliary measurement index, patient satisfaction scale, surgical pain scale, perioperative period, and complications at 1 week, 1 month, and 6 months after surgery were also analyzed.

RESULTS

One patient was lost to follow-up, resulting in a total of 14 patients in the traditional surgery group and 15 in the robot-assisted group (mean [standard deviation] age, 22.65 [3.60] years). Among the primary outcomes, there was a significant difference in the positioning accuracy (2.91 mm vs 1.65 mm; P < 0.01) and angle accuracy (13.26º vs 4.85º; P < 0.01) between the 2 groups. Secondary outcomes did not significantly differ.

CONCLUSIONS

Compared to traditional surgery, robot-assisted mandibular contouring surgery showed improved precision in bone shaving, as well as higher safety.

LEVEL OF EVIDENCE: 2

Artificial intelligence in dentomaxillofacial radiology

Artificial intelligence (AI) has the potential to revolutionize healthcare and dentistry. Recently, there has been much interest in the development of AI applications. Dentomaxillofacial radiology (DMFR) is within the scope of these applications due to its compatibility with image processing methods. Classification and segmentation of teeth, automatic marking of anatomical structures and cephalometric analysis, determination of early dental diseases, gingival, periodontal diseases and evaluation of risk groups, diagnosis of certain diseases, such as; osteoporosis that can be detected in jaw radiographs are among studies conducted by using radiological images. Further research in the field of AI will make great contributions to DMFR. We aim to discuss most recent AI-based studies in the field of DMFR.

Robotic Applications in Orthodontics: Changing the Face of Contemporary Clinical Care

The last decade (2010-2021) has witnessed the evolution of robotic applications in orthodontics. This review scopes and analyzes published orthodontic literature in eight different domains: (1) robotic dental assistants; (2) robotics in diagnosis and simulation of orthodontic problems; (3) robotics in orthodontic patient education, teaching, and training; (4) wire bending and customized appliance robotics; (5) nanorobots/microrobots for acceleration of tooth movement and for remote monitoring; (6) robotics in maxillofacial surgeries and implant placement; (7) automated aligner production robotics; and (8) TMD rehabilitative robotics. A total of 1,150 records were searched, of which 124 potentially relevant articles were retrieved in full. 87 studies met the selection criteria following screening and were included in the scoping review. The review found that studies pertaining to arch wire bending and customized appliance robots, simulative robots for diagnosis, and surgical robots have been important areas of research in the last decade (32%, 22%, and 16%). Rehabilitative robots and nanorobots are quite promising and have been considerably reported in the orthodontic literature (13%, 9%). On the other hand, assistive robots, automated aligner production robots, and patient robots need more scientific data to be gathered in the future (1%, 1%, and 6%). Technological readiness of different robotic applications in orthodontics was further assessed. The presented eight domains of robotic technologies were assigned to an estimated technological readiness level according to the information given in the publications. Wire bending robots, TMD robots, nanorobots, and aligner production robots have reached the highest levels of technological readiness: 9; diagnostic robots and patient robots reached level 7, whereas surgical robots and assistive robots reached lower levels of readiness: 4 and 3, respectively.

Dental Robotics: A Disruptive Technology

Robotics is a disruptive technology that will change diagnostics and treatment protocols in dental medicine. Robots can perform repeated workflows for an indefinite length of time while enhancing the overall quality and quantity of patient care. Early robots required a human operator, but robotic systems have advanced significantly over the past decade, and the latest medical robots can perform patient intervention or remote monitoring autonomously. However, little research data on the therapeutic reliability and precision of autonomous robots are available. The present paper reviews the promise and practice of robots in dentistry by evaluating published work on commercial robot systems in dental implantology, oral and maxillofacial surgery, prosthetic and restorative dentistry, endodontics, orthodontics, oral radiology as well as dental education. In conclusion, this review critically addresses the current limitations of dental robotics and anticipates the potential future impact on oral healthcare and the dental profession.

Error Analysis of Robot-Assisted Orthognathic Surgery

OBJECTIVE

Orthognathic surgery is an effective method to correct the dentomaxillofacial deformities. The aim of the study is to introduce the robot-assisted orthognathic surgery and demonstrate the accuracy and feasibility of robot-assisted osteotomy in transferring the preoperative virtual surgical planning (VSP) into the intraoperative phase.

METHODS

The CMF robot system, a craniomaxillofacial surgical robot system was developed, consisted of a robotic arm with 6 degrees of freedom, a self-developed end-effector, and an optical localizer. The individualized end-effector was installed with reciprocating saw so that it could perform osteotomy. The study included control and experimental groups. In control group, under the guidance of navigation system, surgeon performed the osteotomies on 3 skull models. In experimental group, according to the preoperative VSP, the robot completed the osteotomies on 3 skull models automatically with assistance of navigation. Statistical analysis was carried out to evaluate the accuracy and feasibility of robot-assisted orthognathic surgery and compare the errors between robot-assisted automatic osteotomy and navigation-assisted manual osteotomy.

RESULTS

All the osteotomies were successfully completed. The overall osteotomy error was 1.07 ± 0.19 mm in the control group, and 1.12 ± 0.20 mm in the experimental group. No significant difference in osteotomy errors was found in the robot-assisted osteotomy groups (P = 0.353). There was consistence of errors between robot-assisted automatic osteotomy and navigation-assisted manual osteotomy.

CONCLUSION

In robot-assisted orthognathic surgery, the robot can complete an osteotomy according to the preoperative VSP and transfer a preoperative VSP into the actual surgical operation with good accuracy and feasibility.

Preliminary clinical experience of robot-assisted surgery in treatment with genioplasty

Genioplasty is the main way to treat diseases such as chin asymmetry, dysplasia and overdevelopment, which involve the three-dimensional direction abnormalities of the chin. Since this kind of surgery mainly uses intraoral incisions, the narrow surgical field of intraoral incisions and the surrounding important neurovascular tissues make it easy for complications, to occur during the osteotomy process, which results in greater surgical risks. The first craniofacial-plastic surgical robot (CPSR-I) system is developed to complete the precise positioning and improve the surgeon's force perception ability. The Kalman filtering method is adopted to reduce the interference of sensor signal noise. An adaptive fuzzy control system, which has strong robustness and adaptability to the environment, is designed to improve the stability of robot-assisted surgical operations. To solve the problem of the depth perception, we propose an automatic bone drilling control strategy that combines position and force conditions to ensure that the robot can automatically stop when the bone is penetrated. On the basis of model surgery and animal experiments, preliminary experiments were carried out clinically. Based on the early results of 6 patients, the robot-assisted approach appears to be a safe and effective strategy for genioplasty.

Dentronics: Towards robotics and artificial intelligence in dentistry

OBJECTIVES

This paper provides an overview of existing applications and concepts of robotic systems and artificial intelligence in dentistry. This review aims to provide the community with novel inputs and argues for an increased utilization of these recent technological developments, referred to as Dentronics, in order to advance dentistry.

METHODS

First, background on developments in robotics, artificial intelligence (AI) and machine learning (ML) are reviewed that may enable novel assistive applications in dentistry (Sec A). Second, a systematic technology review that evaluates existing state-of-the-art applications in AI, ML and robotics in the context of dentistry is presented (Sec B).

RESULTS

A systematic literature research in pubmed yielded in a total of 558 results. 41 studies related to ML, 53 studies related to AI and 49 original research papers on robotics application in dentistry were included. ML and AI have been applied in dental research to analyze large amounts of data to eventually support dental decision making, diagnosis, prognosis and treatment planning with the help of data-driven analysis algorithms based on machine learning. So far, only few robotic applications have made it to reality, mostly restricted to pilot use cases.

SIGNIFICANCE

The authors believe that dentistry can greatly benefit from the current rise of digital human-centered automation and be transformed towards a new robotic, ML and AI-enabled era. In the future, Dentronics will enhance reliability, reproducibility, accuracy and efficiency in dentistry through the democratized use of modern dental technologies, such as medical robot systems and specialized artificial intelligence. Dentronics will increase our understanding of disease pathogenesis, improve risk-assessment-strategies, diagnosis, disease prediction and finally lead to better treatment outcomes.

[Recent progress of robots in stomatology]

With the development of industrial robot technology, robotics has entered the medical field, and the research and development of new robots for many medical applications have become a significant research direction in global robotics. Robots are widely used in various aspects of dentistry, such as prosthodontics, orthodontics, implants, endodontics, and oral surgery. This article mainly introduces the application of robots in stomatology from the above five aspects.