1. Introduction
Dentofacial deformity (DFD) is a multifactorial condition affecting the position and/or the size of the jaw, suffered by around 15% of the general population [1]. Patients with DFD may appear to have an upper or lower jaw or chin that is too large or too small, which can manifest within the dentition as a malocclusion (e.g., Class I, II, or III) [2]. Patients with DFD often exhibit facial asymmetry, and previous studies have shown that approximately 21–67% of patients with prognathism or retrognathism exhibit facial asymmetry, with chin deviation being the most notable manifestation [3,4].
Patients with DFD exhibit a range of symptoms, including impaired chewing, swallowing, breathing, speech articulation, and facial aesthetics [1,5,6,7]. These symptoms can result in decreased well-being and, consequently, a lower quality of life (QOL) [8]. Furthermore, several studies have shown that this disease is closely related to obstructive sleep apnea syndrome (OSA, particularly in Class II patients) [4,9,10]. OSA is a sleep disorder characterized by repeated obstruction of the airway during sleep, resulting in a decrease in oxygen saturation and arousal from sleep, and consequently fragmented, nonrestorative sleep [11].
There are several therapies that have been proven to be effective for all these disorders, with orthognathic surgery (OS) for maxillo-mandibular advancement being the required option for patients who do not tolerate long-term non-invasive treatment [5,6,12].
Orthognathic surgery involves repositioning of the maxillary and mandibular bones to improve function and aesthetic release of the upper airway and maintain correct dental occlusion [13]. The precision required for the development of this technique places special value on the use of new technical advances in virtual surgical planning (VSP) and computer-aided design/computer-aided manufacturing (CAD/CAM) three-dimensional models of the patient [14,15,16]. This methodology for virtual surgical planning is based on three-dimensional reconstructions from specialized radiological tests, such as computed tomography (CT) and intraoral scanning (IS), taken as a starting point [17,18]. The necessary bone movements for normal positioning, airway release, and preservation of an optimal dental occlusion are simulated on them. Once both jaws have been virtually repositioned using CAD, occlusal splints are obtained using 3D printing (CAM). These splints provide the necessary information for correct positioning of the bones while maintaining optimal occlusion [15,16,17,19].
VSP has been shown to be highly accurate and reproducible for orthognathic treatment planning. Studies have demonstrated that VSP can achieve a mean difference of less than 2 mm between the planned and actual surgical outcomes, which is considered clinically acceptable [20,21]. For example, one study reported an overall mean of root mean square deviation (RMSD) of 1.37 mm, with the greatest deviation, 1.76 mm, occurring in the sagittal direction, which is still below the 2 mm threshold [22]. Another study found that the mean 3D error met the clinical success standards, at less than 2 mm [23]. Furthermore, combining cone-beam computed tomography (CBCT) and intraoral scans for imaging has been shown to enhance the accuracy of VSP even further [21]. Studies consistently demonstrate that VSP achieves high accuracy in orthognathic surgery, with deviations typically remaining within the clinically acceptable range of 2 mm.
For a good outcome with VSP, one of the most important factors to consider is soft tissue predictability and simulation on CAD software v12. Accurate soft tissue simulation contributes to greater reliability in the VSP system’s proposed repositioning. However, modelling soft tissue behavior is complex and VSP systems have shown varying degrees of accuracy in predicting soft tissue outcomes, with the precision of these predictions varying between different facial regions [24]. Despite advancements, challenges remain in achieving perfect soft tissue predictability. The accuracy of these predictions can be influenced by the complexity of the algorithms, as well as the need for continuous improvement. Furthermore, predictability varies considerably between different algorithms. Studies show a wide range of accuracy performance in soft tissue prediction, from 69% to 91%, suggesting that improvements in mesh deformation methods must be considered [21]. Consequently, surgeon criteria and experience could be considered to play a key role in achieving highly satisfied patients and good surgical outcomes, in addition to VSP. While many studies compare different VSP software v12, such as Dolphin, in terms of soft tissue fitting [25,26], none has considered the functional performance of surgeries or studied the effect of dentofacial deformity class on software prediction performance.
Therefore, we decided to evaluate surgical performance using the OQOL questionnaire combined with deviations from VSP produced during surgery. We hypothesized that the surgeon’s judgement takes precedence over the VSP’s definition of repositioning and that VSP is used merely as a guidance and powerful assessment tool. If so, patients with high deviations from the VSP due to the surgeon’s decision should have similar satisfaction levels to those who have undergone repositioning close to the VSP. To test this hypothesis, we conducted an open retrospective study for patients who had undergone orthognathic surgery at the Oral and Maxillofacial Department (OMD) of the Hospital San Pedro de La Rioja.
2. Materials and Methods
A single-center, national, retrospective, and open study was proposed to evaluate the relationship between VSP deviations and OS outcomes in patients diagnosed with DFD. All patients were considered a unique group for the study; therefore, they all received the same treatment following identical therapeutic protocols. Patients were then classified as either having low deviation (accumulated deviation from VSP positioning of less than 2 mm) or significant deviation.
This study recruited sixteen patients requiring orthognathic surgery at the OMD between January 2021 and May 2023. The inclusion criteria for the study were as follows: (1) patients over 18 years of age presenting with some type of dentofacial deformity and candidates for orthognathic surgery treatment; (2) patients with fully developed maxillofacial complexes; (3) patients willing to understand the study procedures and willing to provide signed informed consent; (4) patients willing to undergo postoperative controls for at least one year after surgery; and (5) patients in good general health, as confirmed by preoperative studies and evaluation by anesthesiologists. The exclusion criteria for the study were the following: (1) patients with a high anesthetic risk who are unsuitable for surgery; (2) patients with uncontrolled periodontal disease or unrehabilitated partial or complete edentulism; (3) patients with injuries or disabilities affecting the performance of daily activities and interfering with quality-of-life scales; and (4) patients with uncontrolled psychiatric conditions.
All participants followed the same clinical protocol for orthognathic surgery with partially guided VSP using occlusion splint guides. Once the patient had completed the preoperative orthodontic treatment, they were enrolled for orthognathic surgery in the OMD within a year to a year and a half. The surgical team conducted the necessary tests and data collection for VSP, including radiological and medical examinations, as well as anatomical photography. All the necessary data were submitted to the virtual planning laboratory after the patient had given their consent. The team then reviewed the virtual surgery report and performed the surgery as described above. The follow-up stage was performed between six and twelve months after surgery, involving medical examinations and the acquisition of anatomical photographs. Additionally, radiological tests were performed to take final morphological measurements, and OQOL surveys were carried out.
Informed consent was obtained from all participants and approved by the La Rioja Medical Research Ethics Committee (CEImLAR) (clinical research protocol PI713).
2.1. Radiological Exploration
Pre- and postoperative radiological examinations comprised a high-resolution craniofacial CT scan with a centric wax for condylar positioning. In addition, dental radiography and an intraoral scan were performed for the preoperative stage only, due to the requirements of virtual planning. The radiological examinations were followed by a protocol involving intra- and extraoral photographs, as well as maxillary and mandibular intraoral scans.
2.2. Surgical Planning and Surgery
This study was carried out using computer-aided (partially guided) planning. The Germán Vincent Maxillofacial Prosthesis Laboratory was therefore contacted once the patient’s complete preoperative study was available. In collaboration with the laboratory, a VSP was carried out using Dolphin Imaging and Management System software (version 11.8; Dolphin Imaging and Management, Chatsworth, CA, USA). Maxillofacial measurements were recorded for each surgery, including superior incisive anteroposterior and vertical displacement, pogonion anteroposterior and vertical displacement, and glabella–pogonion and glabella–superior incisive anteroposterior displacement. Once the desired advancements and movements had been planned, the Germán Vincent laboratory provided us with biocompatible resin surgical guide occlusion splints with which to perform the surgical intervention. These splints were modelled according to digital occlusion simulation and were the only surgical guides used in the procedure. No guide was used for mandibular and maxillary repositioning.
Orthognathic surgery was carried out according to the VSP, with surgical occlusion splints used and the soft tissue fitting evaluated by the surgeon during the procedure. The soft tissue fit was evaluated by the surgeon during surgery by visual inspection while the repositioning was being performed. If a poor functional or aesthetic soft tissue fit was detected, the surgeon modified the position of the hard tissue to achieve a good soft tissue fit, without compromising guided occlusion, according to his own criteria. Otherwise, the VSP position was fully respected.
The occlusal splints were manufactured using a Formlabs Form 2 3D printer with Formlabs Surgical Guide Resin, following the manufacturer’s printing parameters (Formlabs Inc., Somerville, MA, USA). The post-processing protocol was followed according to the proposed Formlabs workflow for surgical guide resin, with the addition of an ultrasonic cleaning process in an IPA bath. UV curing was performed for 30 min at room temperature in a desiccant environment. Once finished, the splints were sterilized by the HSP Sterilisation Facility and were ready for use by the surgeon. The manufacturing tolerances declared with this work protocol are less than 0.2 mm.
2.3. Final Measurements and Variance Evaluation
Measurements of surgical outcomes were performed based on postoperative radiological explorations. Postoperative CT scans were compared with preoperative CT scans, and the distances and movements of many facial landmarks were recorded. The postoperative CT was registered with the preoperative CT based on cranial anatomical landmarks. Once registered, both CTs were superimposed, and the positions of the pogonion, glabella, and superior incisor were marked on both CTs. In conclusion, the distance between each marker was measured in both radiological images and decomposed into vertical and anteroposterior distances. Based on CT image resolution, the measurement reliability was ± 0.556 mm for anteroposterior observations and ±0.896 mm for vertical ones.
The parameters considered in the study were the anteroposterior and vertical displacements of the superior incisive (SI), pogonion (Pg), and glabella–Pg and glabella–SI. These measurements were summarized in combination with the parameters recorded from the surgical plan, and the two sets of measurements were then compared.
Deviations from the surgical plan and the results were calculated using the surgical plan data and the preoperative and postoperative CT measures. Deviation summaries were also calculated considering deviation in the vertical and anteroposterior axes. Finally, deviation ratios were calculated for performance revision according to surgeon feedback records from surgery.
2.4. Statistical Analysis
All statistical analyses were performed using the R suite v 4.2.2 [27]. Descriptive statistics were performed based on population data for each variable measured and study outcome. The correlation between variables was measured using the Pearson correlation coefficient. Group comparisons were tested using a non-parametric Wilcoxon test when normality could not be assumed and a parametric t-test when the data fitted a normal distribution. The Shapiro–Wilk test was also performed to test for normality when this was required. For all statistical tests, a p-value of 0.05 was set to accept the alternative hypothesis.
2.5. Patient Quality of Life Assessment
The quality of life of the patients after the surgical intervention was assessed using the OQOL questionnaire [28]. The study leader explained the questionnaire to the patients and provided contact details for further information and questions. The test was evaluated according to the published guidelines, and all subdomains were calculated and recorded. The acquisition process for all questionnaires was performed and anonymized according to the relevant data protection regulations referred to in the clinical research protocol.
3. Results
A total of 16 patients between the ages of 20 and 50 were recruited for the study after surgery during the follow-up period. Five patients did not comply with the study protocol and questionnaire and were therefore excluded. The reasons for noncompliance were not clear due to great difficulty in communicating with these patients, so they were considered as miscommunication and lack of interest in participation. Therefore, the final study included 11 successfully treated patients, divided into 6 patients with Class II malocclusion and 5 patients with Class III malocclusion. All patients showed functional and aesthetic disorders for orthognathic surgery. Consequently, the motivation for surgery was considered functional and aesthetic for all patients. Data from the cohort are described in Table 1.
Postoperative measurements showed that in five patients the surgeon followed the VSP exactly, demonstrating good precision and limiting deviations. On the other hand, six patients were considered modified from VSP and showed that SI and Pg advancement were always more conservative than planned according to the surgeon’s criteria. Pg position showed more variability between cases than SI. All Class II patients also required less advancement than originally planned for both pogonion and superior incisive displacements, and only one of them was strictly adapted to VSP. Table 2 shows the final displacements and total surgical deviation. In addition, Figure 1 shows deviation maps for each surgery for SI and Pg displacements.
In addition, Figure 2A illustrates the deviation of all considered procedures combined with Pg and SI deviation maps, which are categorized by dentofacial deformity class. The accuracy of Pg anteroposterior positioning showed significant differences between Class II and III deformities (p-value = 0.017), suggesting that VSP performed better in predicting Class III patients. This is also consistent with the higher number of Class II patients for whom intraoperative planning modifications were considered. It was also reproducible for SI in Class II anteroposterior (p-value = 0.0117) and vertical (p-value = 0.0252) positioning operations. On the other hand, Pg vertical deviations were similar (p-value = 0.654).
Figure 2A,B show the deviations for Class II and Class III patients, respectively. The data were grouped according to patients for whom the VSP was strictly followed and patients whose VSP was modified intraoperatively. Clear deviation was found in anteroposterior repositioning of Pg and SI for Class II patients, reaching an average deviation of almost 5 mm for Pg and 2.5 mm for SI. However, statistical significance was not achieved due to the small number of patients in the VSP-treated group: p-value = 0.915 for Pg and p-value = 0.8477 for SI. Only one patient in the Class II group followed the VSP, which led to a lack of statistical power. Therefore, almost all Class II procedures (five out of six—83%) requiring surgeon intervention due to the VSP sought a higher advancement than the one finally considered by the surgeon. More limited deviations were observed in Class III patients, where only two out of five (40%) deviated from the VSP. Furthermore, even in patients for whom the VSP protocol was not fully adhered to, minor deviations were exhibited.
Table 3 shows the overall and subdomain results of the OQOL questionnaire grouped by dentofacial deformity class. Most patients had positive outcomes through all test subdomains, indicating satisfaction with orthognathic surgery. However, one patient was an outlier, showing an overall score of 58, which is associated with low satisfaction and issues related to the results of the surgery. However, we were aware that this patient had difficulty understanding the questionnaire, since the results do not match the patient’s subjective evaluation of satisfaction. Therefore, we suggest not considering this patient as representative in further data interpretation.
On the other hand, all subdomains showed high satisfaction scores. Oral functionality was the highest among fully satisfied patients, especially among Class III patients. Social implications also showed a good result with an overall score of 5.36. Awareness impact showed a similar result. Despite also achieving a good satisfaction score, higher patient concern was found in the aesthetic impact category.
Figure 3 analyzes the impact of VSP modifications on satisfaction outcomes for all patients studied. Figure 3A shows the overall satisfaction levels of the cohort. Figure 3B shows the overall cohort data grouped by VSP following. No difference was observed between VSP followers and modified planning patients in any OQOL domain. Similarly, the same characteristic was observed for Class II (Figure 3C) and Class III (Figure 3D) patients, who also showed no differences between VSP-followed and -modified patients. Overall, all patients showed similar satisfaction levels regarding surgical performance, regardless of whether the procedure adhered to the initially proposed VSP.
4. Discussion
Nowadays, it is clear that digital tools are useful for surgical planning and development. In fact, the ability to 3D-print personalized occlusion splints designed using CAD techniques has significantly reduced errors relating to inter-jaw positioning [29]. This translates into higher satisfaction rates and better functional outcomes from procedures. Meanwhile, complete virtual planning is becoming more common in procedure planning. However, the scientific community is still divided on its validation as a step forward for orthognathic surgery [30]. Our results align with previous reports and reviews indicating that VSP does not accurately predict surgery and that deviations from the plan are necessary [31].
While many studies agree that VSP accurately predicts hard tissue, soft tissue planning still requires workarounds and presents problems in the lower face, upper lip, and nasal base [24,32]. This is all related to the Class II phenomena observed when predicting mandibular soft tissue fitting, which could be connected to the OS soft tissue prediction evaluations where Dolphin software was included. While Dolphin works well with cephalometric radiographs, its modelling of 3D tissues is limited. Studies have shown that Dolphin exhibits greater variability in performance (1.8 ± 0.8 mm) than ProPlan and PFEM (~1.3 ± 0.4 mm), indicating slightly lower performance in 3D predictions. Other software, such as IPS CaseDesigner, exhibits variability similar to that of Dolphin, emphasizing variability in predicting the lower lip. In addition, PFEM offers a more complex, parametrizable simulation, but its technical complexity increases significantly. However, issues regarding sample size should be addressed, as these are common problems in these studies [24,26].PFEM is aligned with newer approaches involving more complex finite element modelling (FEM) and must be considered for extension to other VSP software. In some studies, complex FEM modelling based on a combination of CT and MR data has shown deviations of 0.55 mm in the midface area between simulation and postoperative CBCT. However, high variability (2.9 mm) has also been demonstrated. Once again, sample size limitations are a key issue for these studies [25]. Novel sliding FEM models have been proposed for retrospective data, showing promising results, especially for predicting the lips and mucosa, but these have not yet been applied to real surgical VSP procedures. [33]. The studies summarized in Table 4 had a similar sample size to those using real surgical application data and shared the overall deviation observed for Dolphin’s VSP surgeries. However, none of them studied differences between dentofacial deformity classes or surgical functional outcomes using OQOL or other methods.
The fact that cranial areas can be simulated more accurately than lower facial areas may explain the differences observed in our study between Class II and Class III patients with respect to VSP compliance [24]. Class II dentofacial deformity (DFD) correction typically requires more mandibular advancement than Class III, resulting in poorer soft tissue simulation due to greater hard tissue displacement carrying soft tissue movement. While this explains our findings, there is no literature on performance observations by dentofacial deformity classes.
OQOL scores for surgeries performed were consistent in terms of patient satisfaction and DFD correction. They indicate that all patients were highly satisfied with the outcome of the surgery. Since lower scores indicate greater satisfaction, a mean score of 24.82 is consistent with expected scores following successful surgery [36]. The study aligns with the mean score of 20.53 reported by many studies, leading us to affirm the result [1]. Analysis of grouped OQOL domains by VSP adherence showed that surgeries where the surgeon’s criteria drove the final positioning had the same good outcome as those that strictly followed VSP. No difference was observed in either Class II or Class III patients. However, there is concern about an outlier patient who had difficulty understanding the questionnaire. Specifically, oral functionality and social concerns were the best-scoring subdomains, reaching higher satisfaction levels than the average results reported in the literature [36,37]. This confirms the findings of many studies that social awareness improves the most in DFD patients after OS [4,38,39,40].
Additionally, we must consider the limitations of this study, which were caused by the small sample size. A lack of adherence by many patients, as well as different external factors, resulted in a study of only 11 cases, which is not optimal for statistical analysis. This had a direct impact on statistical power, which was compromised. It is difficult to establish statistical correlations between factors that could affect VSP reliability and precision. Nevertheless, the previously mentioned studies had even fewer participants than our study, with 8–10 patient cohorts, sharing our statistical limitations and issues. In addition, few studies have been found that measure VSP prediction performance in real surgical cases like ours. Others have used theoretical retrospective approaches to test novel methodologies that are not yet ready for clinical application. However, a lack of effectiveness in soft tissue prediction has been demonstrated, especially in Class II patients. Having a large patient cohort would help to reach stronger statistical conclusions, but this is acknowledged as a limitation due to patient enrolment in the service. Furthermore, future research could consider more VSP software incorporating different algorithms for soft tissue prediction.
5. Conclusions
In conclusion, the study confirmed that, in many cases, surgeon intervention is required to modify VSP positioning due to poor soft tissue fitting. Furthermore, we found that surgical outcomes were equally favorable in cases with voluntary deviations from the VSP compared to those where the plan was strictly followed. This demonstrates that soft tissue predictions sometimes fail and that surgeon judgment should prevail over strict adherence to the virtual plan.
The study highlights variability and reliability issues in patients with Class II dentofacial deformities, who showed significantly lower adherence to VSP (17%) compared to Class III patients (60%). On average, final mandibular advancement was 8.6 mm less in Class II patients, where Pg deviations were greater than SI deviations. These findings suggest that the virtual plan often recommends excessive advancement for Class II deformities. This raises concerns about the effectiveness of VSP in these cases, beyond its utility for occlusal splint fabrication. In practice, surgeons tend to adopt more conservative repositioning strategies that still achieve proper correction of the deformity while minimizing surgical impact. In contrast, deviations in Class III patients were comparable to those in cases where the VSP was fully followed, suggesting that VSP provides more accurate soft tissue prediction in Class III cases than in Class II cases.
Overall, all surgeries were considered successful, and patients were generally satisfied with the results. The study confirms that VSP plays a key role in guiding occlusion and ensuring accurate correction of dentofacial deformities. However, surgeons must be aware that soft tissue adaptation may differ from predicted outcomes, potentially requiring intraoperative adjustments. We recommend using VSP for the design and manufacturing of occlusal splints in all cases of dentofacial deformity. Nevertheless, the positioning proposed by VSP for Class II patients should be regarded as a reference rather than a strict plan, whereas for Class III patients, VSP positioning can be considered reliable and followed more confidently.
Conceptualization, P.M.F.-M. and Á.P.-S.; methodology, P.M.F.-M. and I.C.A.; software, J.M.G.; validation, J.L.D.C.P.d.V., J.L.C.C. and C.N.C.; formal analysis, Á.V.; investigation, I.M.L.; resources, R.F.-V.G.; data curation, A.L.L.; writing—original draft preparation, I.N.C.; writing—review and editing, M.B.; visualization, G.A.; supervision, Á.P.-S.; project administration, M.B.; funding acquisition, R.P. All authors have read and agreed to the published version of the manuscript.
The study was conducted in accordance with the Declaration of Helsinki and approved by the Medical Research Ethics Committee of La Rioja (CEImlAR) (protocol code PI713 of 30 October 2023).
Informed consent was obtained from all subjects involved in the study.
The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.
The authors declare no conflicts of interest.
| CAD | Computer-Aided Design |
| CAM | Computer-Aided Manufacturing |
| CEImLaR | Medical Research Ethics Committee of La Rioja |
| CT | Computed Tomography |
| DFD | Dentofacial Deformity |
| FEM | Finite Element Modeling |
| QOL | Finite Element Modeling |
| OMD | Oral and Maxillofacial Department |
| OQOL | Orthognathic Quality of Life |
| OS | Orthognathic Surgery |
| OSA | Obstructive Sleep Apnea |
| Pg | Pogonion |
| SD | Standard Deviation |
| SI | Superior Incisive |
| VSP | Virtual Surgery Planning |
Footnotes
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Figure 1 Anteroposterior (X-Axe) and vertical (Y-Axe) deviation for each evaluated surgery case. Each point represents a single patient. (A) Deviations produced in surgery of SI anatomical markers from VSP proposed positioning. (B) Deviations of Pg anatomical markers from VSP proposed positioning.
Figure 2 (A) Mean deviations and SDs for anteroposterior (Ap) and vertical (V) displacements of surgery results compared with VSP proposal for each anatomical marker (Pg and SI) and grouped by dentofacial deformity class. (B) Mean deviations and SDs for Ap and V displacements of final surgery result compared with VSP proposals for Class II patients for Pg and SI grouped by VSP following groups. “On VSP” represents those patients for whom VSP was followed; “Mod. VSP” represents those patients for whom the surgeon decided to modify the positioning from VSP. (C) Mean deviations and SDs for Ap and V displacements of final surgery results compared with VSP proposals for Class III patients for Pg and SI grouped by VSP following groups. *: p < 0.05.
Figure 3 Mean OQOL scores and SDs for each questionary domain and total scores summarized. Dots represent individual score values. (A) Representation of OQOL results for all study patients. (B) Representation of OQOL results for all study patients grouped by VSP following. (C) Representation of OQOL results for Class II patients grouped by VSP following. (D) Representation of OQOL results for Class III patients grouped by VSP following. “On VSP” represents those patients for whom VSP was followed; “Mod. VSP” represents those patients for whom the surgeon decided to modify the positioning from VSP.
Patient cohort description. Description of phenotypic data of enrolled patients categorized and summarized by dentofacial deformity class. Return to work refers to the number of weeks to return to work. Planned displacements are the corresponding Ap displacements for PG and SI defined by the VSP.
| Patient Characteristics | Fulfilled Program Patients | Class II Patients | Class III Patients |
|---|---|---|---|
| Number of patients | 11 | 6 | 5 |
| Age—years (SD) | 34.64 (9.23) | 38 (11.54) | 30.6 (3.04) |
| Gender—N (%) | |||
| Male | 3 (27.3) | 1 (16.67) | 2 (40) |
| Female | 8 (72.7) | 5 (83.33) | 3 (60) |
| Laboral return—mean weeks (SD) | 4.9 (2.49) | 4.5 (1.96) | 5.4 (3.36) |
| Sport practice return—mean weeks (SD) | 7.82 (3) | 8.3 (3.3) | 7.2 (3) |
| Planed SI Ap displacement—mean mm (SD) | 4.36 (2.70) | 4.33 (2.7) | 4.4 (3.2) |
| Planed Pg Ap displacement—mean mm (SD) | 7.21 (7.23) | 12.53 (6.75) | 0.84 (3.21) |
Final displacements and overall surgical deviation. Empirically measured displacements for all procedures performed based on postoperative CT imagery. Overall SI and Pg deviations from VSP-defined displacement and final empirical measures.
| Patient Characteristics | Class II | Class III | Overall |
|---|---|---|---|
| Final SI Ap displacement—mean mm (SD) | 2.04 (2.37) | 5.03 (2.23) | 3.34 (2.37) |
| Final Pg Ap displacement—mean mm (SD) | 8.16 (5.67) | 1.86 (5.87) | 5.30 (5.67) |
| Final SI V displacement—mean mm (SD) | 0.75 (2.09) | 0.92 (1.82) | 0.83 (2.09) |
| Final Pg V Displacement—mean mm (SD) | −1.18 (2.76) | 0.50 (2.29) | −0.42 (2.75) |
| Overall SI deviation—mean mm (SD) | −2.30 (2.25) | 0.63 (2.27) | −0.96 (2.4) |
| Overall Pg deviation—mean mm (SD) | −4.37 (3.05) | 1.02 (3.05) | −1.92 (3.05) |
Overall score and subdomains results. OQOL scores for each questionnaire subdomain and final score summary for all patients grouped by dentofacial deformity class and overall.
| OQOL Domain | Class II | Class III | Overall |
|---|---|---|---|
| Aesthetic | 8.90 (3.63) | 7.89 (0.78) | 8.81 (3.46) |
| Oral | 4.7 (6.07) | 2.33 (2.65) | 4.36 (5.87) |
| Awareness | 6.30 (4.64) | 5.22 (3.35) | 6.27 (4.41) |
| Social | 5.90 (5.97) | 5.89 (6.50) | 5.36 (5.94) |
| Final Score | 25.80 (14.58) | 21.33 (10.03) | 24.82 (14.21) |
Comparative table of studies measuring VSP performance involving soft tissue simulation.
| Study | Sample Size | VSP Performance Test | Software | Deviation |
|---|---|---|---|---|
| Knoops et al. (2019) [ | 8 | Real surgical application | PFEM | 1.3 ± 0.4 mm |
| Dolphin | 1.8 ± 0.8 mm | |||
| ProPlan | 1.2 ± 0.4 mm | |||
| Kim et al. (2021) [ | 35 | Theoretical VSP simulation for previous surgeries | Lip sliding FEM | 0.6 ± 0.2 mm |
| Kim et al. (2017) [ | 40 | Theoretical VSP simulation for previous surgeries | 3-step FEM with sliding | 1.1 ± 0.7 mm |
| Gutiérrez Venturini et al. (2022) [ | 10 | Real surgical application | Adapted FEM | ~3 mm |
| Awad et al. (2022) [ | 20 | Real surgical application | IPS CaseDesigner® | ~2 mm |
| Ruggiero et al. (2023) [ | 8 | Theoretical VSP simulation for previous surgeries | Detailed anatomical FEM (CBCT + RM) | 0.55 ± 2.9 mm |
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; Montes Fernández-Micheltorena Pablo 2 ; Bobadilla Miriam 3
; Fernández-Valadés, Gámez Ricardo 2 ; Martínez, Goñi Javier 4 ; Villanueva Ángela 3 ; Archanco Iñigo Calvo 2 ; Del Castillo Pardo de Vera José Luis 5
; Cebrián Carretero José Luis 5
; Cuéllar Carlos Navarro 6
; Cuellar, Ignacio Navarro 6 ; Arenas Gema 6 ; López López Ana 6 ; Larrayoz, Ignacio M 3 ; Peláez, Rafael 1
1 Bioengineering and 3D Printing Lab, Biomarkers and Molecular Signaling, Centre for Biomedical Research of La Rioja, C/Piqueras 98, 26006 Logroño, Spain; [email protected] (Á.P.-S.); [email protected] (R.P.)
2 Oral and Maxillofacial Surgery Department, University Hospital San Pedro, C/Piqueras 98, 26006 Logroño, Spain; [email protected] (P.M.F.-M.); [email protected] (R.F.-V.G.); [email protected] (I.C.A.)
3 Biomarkers, Artificial Intelligence and Signaling (BIAS), Department of Nursing, University of La Rioja, Duquesa de la Victoria 88, 26006 Logroño, Spain; [email protected] (Á.V.); [email protected] (I.M.L.)
4 Bioengineering Department, Geruza 3D Digital Solutions in Medicine, Plaza Juana García Orcoyen, 5, 31012 Pamplona, Spain; [email protected]
5 Oral and Maxillofacial Surgery Department, University Hospital La Paz, Paseo de la Castellana, 261, 28046 Madrid, Spain; [email protected] (J.L.D.C.P.d.V.); [email protected] (J.L.C.C.)
6 Oral and Maxillofacial Surgery Department, University Hospital Gregorio Marañón, C/Dr. Esquerdo 46, 28007 Madrid, Spain; [email protected] (C.N.C.); [email protected] (I.N.C.); [email protected] (G.A.); [email protected] (A.L.L.)