Preliminary study of the accuracy and safety of robot-assisted mandibular distraction osteogenesis with electromagnetic navigation in hemifacial microsomia using rabbit models

Artificial Intelligence Applications in Pediatric Craniofacial Surgery

Artificial intelligence is rapidly transforming pediatric craniofacial surgery by enhancing diagnostic accuracy, improving surgical precision, and optimizing postoperative care. Machine learning and deep learning models are increasingly used to analyze complex craniofacial imaging, enabling early detection of congenital anomalies such as craniosynostosis, and cleft lip and palate. AI-driven algorithms assist in preoperative planning by identifying anatomical abnormalities, predicting surgical outcomes, and guiding personalized treatment strategies. In cleft lip and palate care, AI enhances prenatal detection, severity classification, and the design of custom therapeutic devices, while also refining speech evaluation. For craniosynostosis, AI supports automated morphology classification, severity scoring, and the assessment of surgical indications, thereby promoting diagnostic consistency and predictive outcome modeling. In orthognathic surgery, AI-driven analyses, including skeletal maturity evaluation and cephalometric assessment, inform optimal timing and diagnosis. Furthermore, in cases of craniofacial microsomia and microtia, AI improves phenotypic classification and surgical planning through precise intraoperative navigation. These advancements underscore AI's transformative role in diagnostic accuracy, and clinical decision-making, highlighting its potential to significantly enhance evidence-based pediatric craniofacial care.

New Productive Force: The Preliminary Report of First Craniofacial Surgical Robot IST Multicenter Clinical Trial in China

BACKGROUND

This paper presents the authors' team's research on a craniofacial surgical robot developed in China. Initiated in 2011 with government funding, the craniofacial surgical robot project was officially launched in Shanghai, developed jointly by the Ninth People's Hospital affiliated with Shanghai Jiao Tong University School of Medicine and the Shanghai Jiao Tong University medical-engineering team. Currently, based on multiple rounds of model surgeries, animal experiments, and clinical trials, our team is applying for approval as a Class III medical device from the National Medical Products Administration (NMPA). As an innovative tool in the field of craniofacial surgery, it fills a technological gap within the country.

METHODS

This study is a multicenter cohort study based on patient data from Shanghai Ninth People's Hospital from 2019 to 2024. Inclusion criteria included patients who underwent craniofacial surgery with complete follow-up data, with the primary variable being the use of robotic assistance in craniofacial surgery. Data analysis involved descriptive statistics, t tests, and multivariable regression, with a significance level set at P<0.05.

RESULTS

The craniofacial surgical robot has been widely explored in the fields of congenital deformities, tumor reconstruction, and esthetic surgery. In the clinical trials discussed in this article, which included experiments on both craniofacial deformity correction surgeries and esthetic surgeries, a total of 39 patients were enrolled. In mandibular osteotomy surgery, robotic-assisted procedures can reduce osteotomy length error by an average of 2.2 mm and mandibular angle error by 9.09 degrees, while also decreasing the average surgery time by 10.43 minutes. In hemifacial microsomia distraction osteogenesis surgery, robotic-assisted surgery can reduce osteotomy length error by an average of 4.6 mm and shorten the average surgery time by 60 minutes. The robotic-assisted group also showed better perioperative outcomes for patients. The surgical precision was improved and there was a significant reduction in postoperative complications.

CONCLUSION

The authors' research team has completed the first multicenter study on craniofacial surgical robots in China, demonstrating that this robot significantly enhances surgical precision, reduces operation time, and improves perioperative patient indicators. These findings indicate that the robot is highly effective in assisting surgeons with complex procedures. The study suggests that, in the future, this robot is likely to be widely adopted in craniofacial surgery, significantly advancing surgical efficiency and precision, and bringing transformative progress to clinical practice.

Computerized Surgical Planning for Mandibular Distraction Osteogenesis

Mandibular distraction osteogenesis is a technically challenging procedure due to complex mandibular anatomy, especially in the treatment of Pierre-Robin Sequence due to variable bone thickness in the infant mandible and the presence of tooth buds. Computerized surgical planning (CSP) simplifies the procedure by preoperatively visualizing critical structures, producing cutting guides, and planning distractor placement. This paper describes the process of using CSP to plan mandibular distraction osteogenesis, including discussion of recent advances in the use of custom distractors.

Intelligent electromagnetic navigation system for robot-assisted intraoral osteotomy in mandibular tumor resection: a model experiment

Background

Mandibular tumor surgery necessitates precise osteotomies based on tumor boundaries; however, conventional osteotomies often lack accuracy in predicting osteotomy positions and planes, potentially leading to excessive resection of normal bone tissues or residual tumors, thus compromising postoperative quality of life and clinical outcomes. Robotic-assisted surgery (RAS) augmented with artificial intelligence (AI) offers precise localization capabilities, aiding surgeons in achieving accurate osteotomy positioning. This study aimed to evaluate the feasibility and accuracy of a robotic magnetic navigation system for positioning and osteotomy in an intraoral surgical trial of a mandibular tumor model.

Methods

Patient computed tomography (CT) imaging data of mandibular chin and body tumors were utilized to create 3D printed models, serving as study subjects for mandibular tumor resection. Ten pairs of models were printed for the experimental and control groups. The experimental group (EG) underwent osteotomy using a robot-assisted surgical navigation system, performing osteotomy under robotic navigation following alignment based on preoperative design. The control group (CG) underwent traditional surgery, estimating osteotomy position empirically according to preoperative design. Postoperative CT scans were conducted on both models, and actual postoperative results were compared to preoperative design. Osteotomy accuracy was evaluated by positional and angular errors between preoperatively designed and actual osteotomy planes.

Results

For ten randomly selected spots on the left and right sides, respectively, the EG group had mean distance errors of 0.338 mm and 0.941 mm. These values were obtained from the EG group. In the EG group, on the left side, the mean angular errors were 14.741 degrees, while on the right side, they were 13.021 degrees. For the 10 randomly selected spots on the left and right sides, respectively, the CG had mean distance errors of 1.776 mm and 2.320 mm. This is in contrast to the results obtained by the EG. It was determined that the left side had a mean angle error of 16.841 degrees, while the right side had an error of 18.416 degrees in the CG group. The above results indicated significantly lower point errors of bilateral osteotomy planes in the experimental group compared to the control group.

Conclusion

This study demonstrates the feasibility of electromagnetic navigation robot-assisted intraoral osteotomy for mandibular tumors and suggests that this approach can enhance the precision of clinical surgery.

Efficacy of navigation system-assisted distraction osteogenesis for hemifacial microsomia based on artificial intelligence for 3 to 18 years old: study protocol for a randomized controlled single-blind trial

BACKGROUND

Mandibular distraction osteogenesis (MDO) is a major part of the treatment for hemifacial microsomia patients. Due to the narrow surgical field of the intraoral approach, osteotomy accuracy is highly dependent on the surgeons' experience. Electromagnetic (EM) tracking systems can achieve satisfying accuracy to provide helpful real-time surgical navigation. Our research team developed an EM navigation system based on artificial intelligence, which has been justified in improving the accuracy of osteotomy in the MDO in animal experiments. This study aims to clarify the effect of the EM navigation system in improving the MDO accuracy for hemifacial microsomia patients.

METHODS

This study is designed as a single-centered and randomized controlled trial. Altogether, 22 hemifacial microsomia patients are randomly assigned to the experiment and control groups. All patients receive three-dimensional CT scans and preoperative surgical plans. The EM navigation system will be set up for those in the experiment group, and the control group will undergo traditional surgery. The primary outcome is the surgical precision by comparing the osteotomy position of pre- and postoperative CT scan images through the Geomagic Control software. The secondary outcomes include mandibular symmetry (occlusal plane deviation angle, mandibular ramus height, and body length), pain scale, and complications. Other indications, such as the adverse events of the system and the satisfactory score from patients and their families, will be recorded.

DISCUSSION

This small sample randomized controlled trial intends to explore the application of an EM navigation system in MDO for patients, which has been adopted in other surgeries such as orthognathic procedures. Because of the delicate structures of children and the narrow surgical view, accurate osteotomy and protection of nearby tissue from injury are essential for successful treatment. The EM navigation system based on artificial intelligence adopted in this trial is hypothesized to provide precise real-time navigation for surgeons and optimally improve patient outcomes, including function and aesthetic results. The results of this trial will extend the application of new navigation technology in pediatric plastic surgery.

TRIAL REGISTRATION

Chinese Clinical Trial Registry ChiCTR2200061565. Registered on 29 June 2022.

Accuracy and safety of robotic navigation-assisted distraction osteogenesis for hemifacial microsomia

Introduction

This study aimed to verify the accuracy and safety of distraction osteogenesis for hemifacial microsomia assisted by a robotic navigation system based on artificial intelligence.

Methods

The small sample early-phase single-arm clinical study, available at http://www.chictr.org.cn/index.aspx, included children aged three years and older diagnosed with unilateral hemifacial microsomia (Pruzansky-Kaban type II). A preoperative design was performed, and an intelligent robotic navigation system assisted in the intraoperative osteotomy. The primary outcome was the accuracy of distraction osteogenesis, including the positional and angular errors of the osteotomy plane and the distractor, by comparing the preoperative design plan with the actual images one week postoperatively. Perioperative indicators, pain scales, satisfaction scales, and complications at one week were also analyzed.

Results

Four cases (mean 6.5 years, 3 type IIa and 1 type IIb deformity) were included. According to the craniofacial images one week after surgery, the osteotomy plane positional error was 1.77 ± 0.12 mm, and the angular error was 8.94 ± 4.13°. The positional error of the distractor was 3.67 ± 0.23 mm, and the angular error was 8.13 ± 2.73°. Postoperative patient satisfaction was high, and no adverse events occurred.

Discussion

The robotic navigation-assisted distraction osteogenesis in hemifacial microsomia is safe, and the operational precision meets clinical requirements. Its clinical application potential is to be further explored and validated.