Accuracy of Three-Dimensional Soft Tissue Prediction in Orthognathic Cases Using Dolphin Three-Dimensional Software

The Accuracy of Three-Dimensional Soft Tissue Simulation in Orthognathic Surgery-A Systematic Review

Three-dimensional soft tissue simulation has become a popular tool in the process of virtual orthognathic surgery planning and patient-surgeon communication. To apply 3D soft tissue simulation software in routine clinical practice, both qualitative and quantitative validation of its accuracy are required. The objective of this study was to systematically review the literature on the accuracy of 3D soft tissue simulation in orthognathic surgery. The Web of Science, PubMed, Cochrane, and Embase databases were consulted for the literature search. The systematic review (SR) was conducted according to the PRISMA statement, and 40 articles fulfilled the inclusion and exclusion criteria. The Quadas-2 tool was used for the risk of bias assessment for selected studies. A mean error varying from 0.27 mm to 2.9 mm for 3D soft tissue simulations for the whole face was reported. In the studies evaluating 3D soft tissue simulation accuracy after a Le Fort I osteotomy only, the upper lip and paranasal regions were reported to have the largest error, while after an isolated bilateral sagittal split osteotomy, the largest error was reported for the lower lip and chin regions. In the studies evaluating simulation after bimaxillary osteotomy with or without genioplasty, the highest inaccuracy was reported at the level of the lips, predominantly the lower lip, chin, and, sometimes, the paranasal regions. Due to the variability in the study designs and analysis methods, a direct comparison was not possible. Therefore, based on the results of this SR, guidelines to systematize the workflow for evaluating the accuracy of 3D soft tissue simulations in orthognathic surgery in future studies are proposed.

Accuracy of hard and soft tissue prediction using three-dimensional simulation software in bimaxillary osteotomies: A systematic review

INTRODUCTION

Orthognathic surgery is considered nowadays as a revolutionary treatment option for treating skeletal discrepancies and severe malocclusions in the sagittal, vertical and transverse dimensions. This surgery allows both the restoration of facial harmony and the achievement of satisfactory dental occlusion. The technology of computer-assisted surgeries including virtual surgical simulation programs and planning software greatly contributes to providing a three-dimensional simulation and precise mobilization of the maxilla and/or mandible, thus allowing the prediction of the final outcome in soft tissues. This study aims to systematically review the available scientific literature about the accuracy of the hard and soft tissue predictions delivered by the many promoted three-dimensional simulation software.

MATERIAL AND METHODS

An electronic search was conducted on various databases: Medline via PubMed, The Cochrane Library, EBSCO-host, and Web of Science. The search was established on a well-defined research question following PICO principle: population, intervention, comparator and outcome. Search evaluation and the assessment of risk of bias were undertaken in each study following its type and design.

RESULTS

Fifteen studies were included for qualitative analysis. Seven studies evaluated the accuracy of soft tissue prediction, seven focused more on the accuracy of hard tissue and one study assessed both hard and soft tissue prediction accuracy delivered by the simulation software. Moreover, three studies were judged to be low risk and four were classified as high risk. Included studies revealed that hard tissue prediction is highly accurate and reliable, leading to clinically acceptable results. Yet, soft tissue prediction is unclear due to various factors that bias its results. Caution should therefore be taken when providing information about the soft tissue planning to patients.

CONCLUSIONS

Computer assisted 3D simulation protocols allow for more precise repositioning of the maxilla and/or mandible compared to conventional 2D methods. However, 3D soft tissue prediction using simulation software remains less accurate, especially in the labial region.

Correlation Analysis of Nasal Septum Deviation and Results of AI-Driven Automated 3D Cephalometric Analysis

The nasal septum is believed to play a crucial role in the development of the craniofacial skeleton. Nasal septum deviation (NSD) is a common condition, affecting 18-65% of individuals. This study aimed to assess the prevalence of NSD and its potential association with abnormalities detected through cephalometric analysis using artificial intelligence (AI) algorithms. The study included CT scans of 120 consecutive, post-traumatic patients aged 18-30. Cephalometric analysis was performed using an AI web-based software, CephX. The automatic analysis comprised all the available cephalometric analyses. NSD was assessed using two methods: maximum deviation from an ideal non-deviated septum and septal deviation angle (SDA). The concordance of repeated manual measurements and automatic analyses was assessed. Of the 120 cases, 90 met the inclusion criteria. The AI-based cephalometric analysis provided comprehensive reports with over 100 measurements. Only the hinge axis angle (HAA) and SDA showed significant (p = 0.039) negative correlations. The rest of the cephalometric analyses showed no correlation with the NSD indicators. The analysis of the agreement between repeated manual measurements and automatic analyses showed good-to-excellent concordance, except in the case of two angular measurements: LI-N-B and Pr-N-A. The CephX AI platform showed high repeatability in automatic cephalometric analyses, demonstrating the reliability of the AI model for most cephalometric analyses.

The impact of orthodontic-surgical treatment on facial expressions-a four-dimensional clinical trial

OBJECTIVE

The objective of this clinical trial was to compare facial expressions (magnitude, shape change, time, and symmetry) before (T0) and after (T1) orthognathic surgery by implementing a novel method of four-dimensional (4D) motion capture analysis, known as videostereophotogrammetry, in orthodontics.

METHODS

This prospective, single-centre, single-arm trial included a total of 26 adult patients (mean age 28.4 years; skeletal class II: n = 13, skeletal class III: n = 13) with indication for orthodontic-surgical treatment. Two reproducible facial expressions (maximum smile, lip purse) were captured at T0 and T1 by videostereophotogrammetry as 4D face scan. The magnitude, shape change, symmetry, and time of the facial movements were analysed. The motion changes were analysed in dependence of skeletal class and surgical movements.

RESULTS

4D motion capture analysis was feasible in all cases. The magnitude of the expression maximum smile increased from 15.24 to 17.27 mm (p = 0.002), while that of the expression lip purse decreased from 9.34 to 8.31 mm (p = 0.01). Shape change, symmetry, and time of the facial movements did not differ significantly pre- and postsurgical. The changes in facial movements following orthodontic-surgical treatment were observed independently of skeletal class and surgical movements.

CONCLUSIONS

Orthodontic-surgical treatment not only affects static soft tissue but also soft tissue dynamics while smiling or lip pursing.

CLINICAL RELEVANCE

To achieve comprehensive orthodontic treatment plans, the integration of facial dynamics via videostereophotogrammetry provides a promising approach in diagnostics.

TRIAL REGISTRATION NUMBER

DRKS00017206.

What is the current state of artificial intelligence applications in dentistry and orthodontics?

BACKGROUND

The use of Artificial Intelligence (AI) in the medical field has the potential to bring about significant improvements in patient care and outcomes. AI is being used in dentistry and more specifically in orthodontics through the development of diagnostic imaging tools, the development of treatment planning tools, and the development of robotic surgery. The aim of this study is to present the latest emerging AI softwares and applications in dental field to benefit from.

TYPES OF STUDIES REVIEWED

Search strategies were conducted in three electronic databases, with no date limits in the following databases up to April 30, 2023: MEDLINE, PUBMED, and GOOGLE® SCHOLAR for articles related to AI in dentistry & orthodontics. No inclusion and exclusion criteria were used for the selection of the articles. Most of the articles included (n = 79) are reviews of the literature, retro/prospective studies, systematic reviews and meta-analyses, and observational studies.

RESULTS

The use of AI in dentistry and orthodontics is a rapidly growing area of research and development, with the potential to revolutionize the field and bring about significant improvements in patient care and outcomes; this can save clinicians' chair-time and push for more individualized treatment plans. Results from the various studies reported in this review are suggestive that the accuracy of AI-based systems is quite promising and reliable.

PRACTICAL IMPLICATIONS

AI application in the healthcare field has proven to be efficient and helpful for the dentist to be more precise in diagnosis and clinical decision-making. These systems can simplify the tasks and provide results in quick time which can save dentists time and help them perform their duties more efficiently. These systems can be of greater aid and can be used as auxiliary support for dentists with lesser experience.

Accuracy in predicting soft tissue changes of orthodontic class III cases using Dolphin® software

OBJECTIVES

The prediction of posttreatment outcomes is conducive to the final determination of ideal therapeutic options. However, the prediction accuracy in orthodontic class III cases is unclear. Therefore, this study conducted exploration on prediction accuracy in orthodontic class III patients using the Dolphin® software.

MATERIALS AND METHODS

In this retrospective study, lateral cephalometric radiographs of pre- and posttreatment were collected from 28 angle class III adults who received completed non-orthognathic orthodontic therapy (8 males, 20 females; mean age = 20.89 ± 4.26 years). The values of 7 posttreatment parameters were recorded and inserted into the Dolphin® Imaging software to generate a predicted outcome, and then the prediction radiograph and actual posttreatment radiograph were superimposed and compared in terms of soft tissue parameters and landmarks.

RESULTS

The prediction showed significant differences with the actual outcomes in nasal prominence (the difference between the prediction and the actual value was - 0.78 ± 1.82 mm), the distance from the lower lip to the H line (0.55 ± 1.11 mm), and the distance from the lower lip to the E line (0.77 ± 1.62 mm) (p < 0.05). Point subnasale (Sn) (an accuracy of 92.86% in the horizontal direction and 100% in the vertical direction in 2 mm) and point soft tissue A (ST A) (an accuracy of 92.86% in the horizontal direction and 85.71% in the vertical direction in 2 mm) were proven to be the most accurate landmarks, while the predictions in the chin region were relatively inaccurate. Furthermore, the predictions in the vertical direction were of higher accuracy compared to the horizontal direction except for the points around the chin.

CONCLUSIONS

The Dolphin® software demonstrated acceptable prediction accuracy in midfacial changes in class III patients. However, there were still limitations for changes in the chin and lower lip prominence.

CLINICAL RELEVANCE

Clarifying the accuracy of Dolphin® software in predicting soft tissue changes of orthodontic class III cases will facilitate physician-patient communication and clinical treatment.

The accuracy of soft tissue movement using virtual planning for non-syndromic facial asymmetry cases-a systematic review

The 3D prediction of post-operative changes is an inevitable tool for the surgical correction of facial asymmetry. The objective is to execute an evidence-based review answering the following question. Does the 3D virtual prediction planning draw reliable and accurate results in the surgical outcome related to the soft tissues of the face in facial asymmetry? This systematic review of the literature is based on the 3D soft tissue prediction planning of facial asymmetry correction to draw conclusions on the reliability and accuracy of these methods in the surgical outcome related to the soft tissues of the face. PubMed, Web of Science, Cochrane, and Ovid databases were adopted for the literature search. Studies published between years 2000 and 2020, aimed at the assessment of soft tissue predictions using software prediction packages for facial asymmetry, were selected. The Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) was applied. Quadas-2 tool was used for the qualitative evaluation of selected studies. Initial search yielded 248 articles. Twenty articles fulfilled the inclusion and exclusion criteria and selected for qualitative analysis. Finally, 12 articles were selected for quantitative analysis. The results indicate 3D imaging prediction methods provided more accurate information with less distortion for soft tissue prediction regardless of various softwares currently available. The prediction of soft tissue accuracy in facial asymmetry was less accurate in lower face regardless of the type of surgery for facial asymmetry. The mean prediction error was less than 2 mm.

A Quantitative and Qualitative Clinical Validation of Soft Tissue Simulation for Orthognathic Surgery Planning

The purpose of this study was to perform a quantitative and qualitative validation of a soft tissue simulation pipeline for orthognathic surgery planning, necessary for clinical use. Simulation results were retrospectively obtained in 10 patients who underwent orthognathic surgery. Quantitatively, error was measured at 9 anatomical landmarks for each patient and different types of comparative analysis were performed considering two mesh resolutions, clinically accepted error, simulation time and error measured by means of percentage of the whole surface. Qualitatively, evaluation and binary questions were asked to two surgeons, both before and after seeing the actual surgical outcome, and their answers were compared. Finally, the quantitative and qualitative results were compared to check if these two types of validation are correlated. The quantitative results were accurate, with greater errors corresponding to gonions and lower lip. Qualitatively, surgeons answered similarly mostly and their evaluations improved when seeing the actual outcome of the surgery. The quantitative validation was not correlated to the qualitative validation. In this study, quantitative and qualitative validations were performed and compared, and the need to carry out both types of analysis in validation studies of soft tissue simulation software for orthognathic surgery planning was proved.

Interdisciplinary 3D digital treatment simulation before complex esthetic rehabilitation of orthodontic, orthognathic and prosthetic treatment: workflow establishment and primary evaluation

Background

An interdisciplinary treatment simulation and smile design before a complex esthetic rehabilitation is important for clinicians’ decision-making and patient motivation. Meanwhile, intervention and interaction are necessary for dental specialists in these complex rehabilitations. However, it is difficult to visualize an interdisciplinary treatment plan by using the conventional method, especially when orthognathic surgery is involved, thus hindering communication between dental specialists. This research aims to establish a 3D digital workflow of interdisciplinary treatment simulation to solve this problem.

Methods

An interdisciplinary 3D digital workflow of simulated treatment plan for complex esthetic rehabilitation was established. Eleven patients were enrolled and illustrated with their treatment plans using 3D treatment simulation, as well as 2D digital smile design (DSD) plus wax-up. Visual analogue scales (VAS) were used to rate the intuitiveness, understanding, and satisfaction or help between the two methods by patients and dental specialists.

Results

According to the ratings from the patients, 3D treatment simulation showed obvious advantages in the aspects of intuitiveness (9.7 ± 0.5 vs 6.4 ± 1.4) and treatment understanding (9.1 ± 0.8 vs 6.6 ± 1.5), and the satisfaction rates were also higher (9.0 ± 0.6 vs 7.1 ± 1.8). Dental specialists regarded the 3D digital plans as more intuitive (8.9 ± 0.8 vs 5.9 ± 1.0) and useful to understand the plans from the other specialists (8.9 ± 0.7 vs 6.1 ± 1.0) and helpful to their own treatment plans (8.7 ± 0.9 vs 5.9 ± 1.4).

Conclusions

The interdisciplinary 3D digital treatment simulation helps both patients and dental specialists to improve treatment understanding, and facilitates dental specialists for decision-making before complex esthetic rehabilitation.

Trial registration

This study was registered in the National Clinical Trials Registry under the identification number MR-11-20-002862. This is an observational study in which we did not assign the intervention.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12903-022-02070-z.

Prediction accuracy of Dolphin software for soft-tissue profile in Class I patients undergoing fixed orthodontic treatment

BACKGROUND

Simulation and prediction can facilitate the decision between an extraction versus nonextraction treatment plan. This study aimed to assess the accuracy of Dolphin Imaging software in predicting profile changes in class I borderline cases.

METHODS

In this retrospective study, class I borderline patients (i.e., both extraction and nonextraction treatment plans were possible for them) aged 15-35 years were enrolled. All of the cephalometric analyses were done by Dolphin Imaging software, version 11.8 Premium. The initial cephalograms were superimposed on initial photographs. The final values for the 7 angular and linear landmarks of the upper and lower incisors were extracted from post-treatment cephalograms and inserted in the "Goals" tab of the Dolphin Imaging software. Post-treatment images of patients were simulated. Final post-treatment photographs were superimposed on the simulated pictures. The differences between the real and simulated pictures were calculated in relation to the reference lines. The P value was set at 0.05.

RESULTS

A total of 70 patients (36 with tooth extraction, and 34 without tooth extraction) were included. In the extraction group, the horizontal position of both lips was predicted to be significantly more protruded than it actually was, whereas in the nonextraction group, the only difference between the simulated and actual results was that the vertical position of the lower lip, which was simulated as being more inferior than it actually was.

CONCLUSIONS

Despite the statistically significant differences between the real and simulated pictures, the differences were small and clinically insignificant. Prediction via Dolphin Imaging software can be an appropriate guide in extraction-nonextraction borderline cases.

Development of novel artificial intelligence systems to predict facial morphology after orthognathic surgery and orthodontic treatment in Japanese patients

From a socio-psychological standpoint, improving the morphology of the facial soft-tissues is regarded as an important therapeutic goal in modern orthodontic treatment. Currently, many of the algorithms used in commercially available software programs that are said to provide the function of performing profile prediction are based on the false assumption that the amount of movement of hard-tissue and soft-tissue has a proportional relationship. The specification of the proportionality constant value depends on the operator, and there is little evidence to support the validity of the prediction result. Thus, the present study attempted to develop artificial intelligence (AI) systems that predict the three-dimensional (3-D) facial morphology after orthognathic surgery and orthodontic treatment based on the results of previous treatment. This was a retrospective study in a secondary adult care setting. A total of 137 patients who underwent orthognathic surgery (n = 72) and orthodontic treatment with four premolar extraction (n = 65) were enrolled. Lateral cephalograms and 3-D facial images were obtained before and after treatment. We have developed two AI systems to predict facial morphology after orthognathic surgery (System S) and orthodontic treatment (System E) using landmark-based geometric morphometric methods together with deep learning methods; where cephalometric changes during treatment and the coordinate values of the faces before treatment were employed as predictive variables. Eleven-fold cross-validation showed that the average system errors were 0.94 mm and 0.69 mm for systems S and E, respectively. The total success rates, when success was defined by a system error of < 1 mm, were 54% and 98% for systems S and E, respectively. The total success rates when success was defined by a system error of < 2 mm were both 100%. AI systems to predict facial morphology after treatment were therefore confirmed to be clinically acceptable.

Voxel-based superimposition of serial craniofacial cone-beam computed tomographies for facial soft tissue assessment: Reproducibility and segmentation effects

INTRODUCTION

The aim of this investigation was to evaluate the reproducibility of a voxel-based 3-dimensional superimposition method and the effect of segmentation error on determining soft tissue surface changes.

METHODS

A total of 15 pairs of serial cone-beam computed tomography images (interval: 1.69 ± 0.37 years) from growing subjects (initial age: 11.75 ± 0.59 years) were selected from an existing digital database. Each pair was superimposed on the anterior cranial base, in 3 dimensions with Dolphin 3D software (version 2.1.6079.17633; Dolphin Imaging & Management Solutions, Chatsworth, Calif). The reproducibility of superimposition outcomes and surface segmentation were tested with intra- and interoperator comparisons.

RESULTS

Median differences in inter- and intrarater measurements at various areas presented a range of 0.08-0.21 mm. In few instances, the differences were larger than 0.5 mm. In areas where T0-T1 changes were increased, the error did not appear to increase. However, the method error increased the farther the measurement area was from the superimposition reference structure. For individual images, the median soft tissue segmentation error ranged from 0.05 to 0.06 at various areas and in no subject exceeded 0.13 mm.

CONCLUSIONS

The presented voxel-based superimposition method was efficient and well reproducible. The segmentation process was a minimal source of error; however, there were a few cases in which the total error was more than 0.5 mm and could be considered clinically significant. Therefore, this method can be used clinically to assess 3-dimensional soft tissue changes during orthodontic treatment in growing patients.

Analysis of facial features and prediction of lip position in skeletal class III malocclusion adult patients undergoing surgical-orthodontic treatment

OBJECTIVES

This study presents a retrospective study aimed to analyze the facial features at each stage of surgical-orthodontic treatment for skeletal class III malocclusion, and predict the changes in the lips after treatment.

MATERIALS AND METHODS

There were 49 skeletal class III malocclusion patients treated with bimaxillary surgery and orthodontic treatment enrolled in this study. Lateral cephalograms were obtained before treatment (T0), 1 month before surgery (T1), 1 month after surgery (T2), and after debonding (T3) for cephalometric measurements. After the measurement of the required variables, paired t-test, Pearson's correlation analysis, and multiple linear regression were performed using SPSS 19.0.

RESULTS

The main factors associated with changes in the upper lip included ΔUIE-V, ΔA-V, ΔU1A-V, and ΔL1A-V, and those associated with changes in the lower lip included ΔLIE-V, ΔL1A-V, ΔB-V, ΔPog-V, and Δfacial angle. The predicted regression equation for the horizontal change in the upper lip was represented as ΔUL-vertical reference line (VRL) = 9.430 + 0.779 (ΔUIE-VRL) - 0.542(VULT) (P < 0.05) with a mean error of 1.04 mm; the corresponding equation for the lower lip was ΔLL-VRL = -1.670 + 0.530 (ΔB-VRL) + 0.360 (Ls-E) + 0.393 (ΔLIE-VRL) (P < 0.05), with a mean error of 1.51 mm.

CONCLUSIONS

This study explored the relationship between orthognathic surgery and changes in the lips and obtained the predictive equations of lip position after treatment by using multiple linear regression, which likely offers a reference for prediction of soft tissue changes before surgical-orthodontic treatment in patients with skeletal class III malocclusion.

CLINICAL RELEVANCE

The findings can help dentists to rapidly predict the lip changes after surgical-orthodontic treatment in patients with skeletal class III malocclusion. The study has been registered with the Chinese Clinical Trial Registration (No: ChiCTR1800017694).

Accuracy of Three-Dimensional Upper Airway Prediction in Orthognathic Patients Using Dolphin Three-Dimensional Software

BACKGROUND

Orthodontists and surgeons have been looking for more accurate methods to predict surgical outcomes in patients with skeletal discrepancies.

METHODS

The sample consisted of 20 patients from the surgical clinic of a graduate orthodontic program who had been treated with Le Fort I maxillary movement, bilateral sagittal split osteotomy, with or without genioplasty. All patients had to have preoperative (T0) and at least 6 months postoperative (T1) cone-beam computed tomographies that were imported to Dolphin 3-dimensional (3D) software. The 3D voxel-based superimposition on the cranial base was performed for T0 and T1 to accurately measure the skeletal surgical movements. A virtual orthognathic surgery was performed on T0 to mimic the actual skeletal osteotomies using the treatment simulation tool in Dolphin 3D. A prediction 3D soft-tissue image (Tp) was generated based on the Dolphin virtual skeletal planning. The upper airway was segmented and exported as stereolithography surface files in both T1 and Tp. The measurements of the 3D volume of the airway were calculated and compared among T1 and Tp by using surface superimposition technique. Mean and standard deviations of upper airway volume were compared and correlated using paired t-test.

RESULTS

There was no statistically significant difference between the upper airway volume of T1 and Tp.

CONCLUSION

Dolphin 3D delivers accurate airway prediction which is an important step in 3D virtual planning.

Modeling and Clinical Application of Incision Space in Facial Contour Surgery

Virtual simulation surgical system is a good way to develop surgical instruments, make surgical plan, and train surgeons. At present, due to the deformation of intraoperative soft tissue after retraction and the lack of effective data collection, the surgical simulation of facial contour surgery can only be conducted according to the preoperative computed tomography data. Due to the difficulty of obtaining real operative spatial data, it is difficult for the virtual surgery trajectory planning process to yield a good effect on surgeon training. In this study, an optical tracking device was used to record the actual posture of surgical instruments, patient position, and incision space in the surgical environment, so as to construct a more accurate actual surgical space. The clinical data obtained in this study can be used for virtual simulation of surgical instrument movement and osteotomy, as well as selection, planning, and teaching purposes of surgical programs.

3-Dimensional prediction of pre-surgical decompensation after atypical extractions and soft tissue simulation for ortho-surgical management of skeletal Class III malocclusion: A case report

Three dimensional imaging systems whether in the form of digital models, facial scanning or dolphin software play an important role in proper diagnosis and treatment planning of the orthosurgical cases. This case report highlights importance of three-dimensional treatment planning in the ortho-surgical management of the patient with skeletal Class III malocclusion involving atypical extraction. On clinical examination, patient had concave profile, prominent chin, deficient midface, flat cheekbone contour and prominent nasal projection. He had Class III molar and canine relation bilaterally with missing 12 (previously extracted), negative overbite and overjet with discordant maxillomandibular midlines. After 3-dimensional digital model set-up for occlusion planning and dolphin simulation for soft tissue prediction, extraction of left maxillary lateral incisor was planned followed by maxillary advancement and mandibular setback surgery and finish the occlusion in Class II molar relationship. After the orthodontic and orthognathic surgical treatment, the skeletal and dental imbalance was corrected, and most of the treatment objectives were achieved and patient was extremely satisfied with his facial profile. The treatment results were stable at the 3 years follow-up.

Virtual Surgical Planning Assisted Management for Cleft-Related Maxillary Hypoplasia

Maxillary hypoplasia is a common developmental deformity affecting patients with cleft lip and palate. Various surgical techniques including conventional orthognathic surgery, total maxillary distraction osteogenesis, and anterior maxillary segmental distraction have been applied to address the deformity. With the evolution of 3D computed tomography imaging, the visualization of skeletal complexities in different perspectives is greatly enhanced and comprehensive surgical planning is achieved. Intraoperative efficiency is also improved with the fabrication of 3D-printed templates. The study aims to present different surgical techniques with virtual surgical planning (VSP) and 3D-printed surgical templates and the solution of representative cases. From January 2014 to January 2019, VSP was transferred to actual surgery or distraction precisely in 80 adult patients with cleft-related maxillary hypoplasia. The accuracy was analyzed and the relapse was also estimated and observed in 18 patients after 1-year follow-up. Based on our experience, VSP provides a more reliable and effective option to conventional model surgery. It facilitates the preoperative planning and accurately transfers the virtual plan to correct the cleft-related maxillary hypoplasia.