Facial Conformation Meshes for Orthognathic Surgery (FEU)

Segmented 3D Facial Conformation Meshes and Regional Esthetic Subunits: Advancing Soft Tissue Prediction Planning for Orthognathic Surgery: a Retrospective Study

This study is a retrospective analysis that evaluates the accuracy of 3D soft tissue simulation in bimaxillary orthognathic surgery for Class III dentofacial deformities. The study integrates segmented 3D facial conformation meshes and regional aesthetic subunits to enhance soft tissue prediction accuracy.

Key Aspects of the Study:

Study Design: Retrospective analysis based on existing CBCT scans of patients who have undergone maxillary advancement and mandibular setback surgery.

Objective: To assess the accuracy of soft tissue predictions using Dolphin software in different facial regions, particularly in midline vs. lateral regions.

Methodology:

.CBCT superimposition using voxel-based registration. .Soft tissue surface analysis via generic mesh conformation and dense correspondence analysis.

.Error assessment in X, Y, Z dimensions rather than Euclidean distance. .Color-coded maps for visualizing prediction accuracy.

Clinical Relevance:

The study aims to refine 3D prediction models for orthognathic surgery planning, making them more precise and reliable.

Key innovation: Modifying the aesthetic unit segmentation approach for a clinically and statistically relevant assessment of soft tissue changes.

Findings will contribute to improving surgical outcome predictability and optimizing treatment planning in maxillofacial surgery.

Ethical Considerations:

No patient recruitment; the study relies solely on existing anonymized CBCT scans.

Ethical approval and waiver of informed consent will be sought from the Institutional Review Board (IRB).

This research aligns with modern advancements in 3D facial prediction technology, aiming to enhance precision and clinical applicability in orthognathic surgery.

Study Overview

• Status: Recruiting
• Conditions: Orthognathic Surgical Procedures

Detailed Description

Orthognathic surgery for Class III dentofacial deformities has significantly evolved, particularly with advancements in soft tissue prediction technologies. Early methods, such as manual photo manipulation, progressed to two-dimensional (2D) computer-assisted predictions. However, the introduction of three-dimensional (3D) imaging revolutionized the field, enhancing prediction accuracy and enabling comprehensive analysis of facial morphology.

Imaging techniques like Multi-Slice Computed Tomography (MSCT) and Cone Beam Computed Tomography (CBCT) are critical for reconstructing the facial skeleton. MSCT provides high resolution but involves higher radiation exposure, whereas CBCT offers a balance of resolution and lower radiation dose, making it preferable for routine clinical applications. CBCT's ability to capture upright facial soft tissues in a natural head position further enhances its utility in orthognathic planning. Advanced technologies such as stereophotogrammetry and structured light imaging allow detailed capture of facial surfaces. Stereophotogrammetry excels in dynamic facial analysis, while structured light imaging offers rapid acquisition of high-resolution facial data. These techniques facilitate the creation of detailed 3D models essential for accurate surgical planning and prediction.

Soft tissue prediction models rely on mathematical algorithms to simulate responses to skeletal movements. The finite element model (FEM) and mass tensor model (MTM) are widely recognized for their predictive accuracy. MTM balances computational efficiency and precision, making it suitable for clinical applications. Recent innovations, such as probabilistic FEM and machine learning algorithms, further enhance prediction accuracy by integrating patient-specific data.

Generic facial meshes, consisting of indexed vertices, allow for precise superimposition and analysis of 3D facial images. Dense correspondence analysis uses these meshes to provide a comprehensive evaluation of facial surfaces, surpassing the limitations of landmark-based methods. This approach ensures precise prediction of soft tissue changes, contributing to better surgical outcomes.

Modern 3D simulation techniques achieve clinically acceptable prediction accuracies (<2 mm) across various facial regions. These tools not only assist in clinical decision-making but also improve communication with patients by providing photorealistic visualizations of potential surgical outcomes. Recent advancements in 3D simulation and analysis have transformed soft tissue prediction in orthognathic surgery. By integrating dense correspondence methods and patient-specific data, these technologies offer enhanced accuracy and reliability, paving the way for more precise and effective treatment planning for Class III dentofacial deformities. This study aims to evaluate the accuracy of combining a generic mesh-based 3D simulation model and facial esthetic units in predicting soft tissue responses to bimaxillary orthognathic surgery for Class III dentofacial deformities.

4- Aim & objectives of the Study This study aims to evaluate the accuracy of soft tissue simulation to bimaxillary orthognathic surgery for Class III dentofacial deformities using combination of a conformation mesh-based analysis model and facial esthetic units.

5- Social & scientific values The clinical relevance of this study lies in the potential to enhance the precision and predictability of treatment outcomes for patients undergoing bimaxillary orthognathic surgery for Class III dentofacial deformities by integrating conformation mesh with facial esthetic units' analysis.

6- Subjects of research:

• Recruitment: No patient recruitment will be conducted, as this study is retrospective and relies solely on existing patient CBCT scans.

• Age N/A

  8- Methodology This retrospective study aims to evaluate the accuracy of 3D software in predicting postoperative soft tissue changes following bimaxillary orthognathic surgery for the correction of Class III jaw deformities. The study will utilize pre-existing CBCT images routinely obtained from orthognathic surgery patients at Ain Shams Dental School. The analysis will compare the predicted preoperative soft tissue changes to the actual results observed in six months postoperatively.

Sample Size Calculation:

Based upon the assumption that the 90% is the required prediction accuracy, in light of the results of Resnick CM et al (2016), the computed effect size for the accuracy of linear measurements was found to be (1.05), using alpha (α) level of (5%) and Beta (β) level of (20%) i.e. power = 80%; the study will include 10 subjects. To compensate for 15% for the use of non-parametric tests the final minimum estimated sample size will be 12 subjects. Sample size calculation was performed using G*Power Version 3.1.9.2.

CBCT scans of Class III patients who underwent maxillary advancement with minimal or no impaction and mandibular setbacks will be identified. To quantify the actual surgical movements, voxel-based superimposition of the pre- and postoperative CBCT images will be conducted using ONDEMAND 3D software. Surgical movements will then be calculated through direct slice landmarking. These movements will inform the soft tissue prediction planning, which will subsequently be compared with the actual postoperative changes.

Soft tissue surface models for both the simulation and actual postoperative outcomes will be generated and exported as STL files. Superimposition of the predicted and postoperative STL models will be performed, and generic meshes will be conformed. Using VR Mesh software, the facial meshes will be segmented into predefined anatomical regions. Distances between corresponding vertices on the predicted and postoperative models will be displayed as a color scale in millimeters. Analyses will be conducted separately for the mediolateral (x), vertical (y), and anteroposterior (z) dimensions using custom-developed in-house software. Color-coded distance maps will be generated to illustrate the magnitude of prediction inaccuracies in each anatomical region. Each dimension will be analyzed to calculate the minimum, maximum, mean, standard deviation (SD), absolute maximum, and mean SD for 90% of the points in each region.

Dimensional inaccuracies will be represented visually, with corresponding points showing rightward, upward, or anterior changes displayed in red, while leftward, downward, or posterior changes will appear in blue. This approach will enable a detailed assessment of prediction accuracy across the three spatial dimensions.

9- Risks to study participants No Risks as no participants will be involved, the study is retrospective utilizing existing data. No direct patient involvement will be required, and all data was fully anonymized before analysis.

10- Benefits to study participants/ community This study benefits lies in the potential to enhance the precision and predictability of treatment outcomes for patients undergoing bimaxillary orthognathic surgery for Class III dentofacial deformities by integrating conformation mesh with facial esthetic units' analysis.

11- Privacy, Record keeping & confidentiality In this retrospective study Patient data will be anonymized using DICOM anonymizer software and assigned unique patient identification numbers. The anonymized data will be securely stored in an Excel sheet for easy retrieval of individual patient information. All data will be maintained on a limited-access, password-protected computer with the principal investigator. If analysis requires transferring images to another computer, a hardware-encrypted removable storage device will be used, and the data will be deleted from the device immediately after transfer. Access to the research data will be restricted to members of the research team only.

12- Consent form: A waiver for individual informed consent from the Institutional Review Board is considered, as the study is retrospective based on existing patient data.

• Study Type: Observational
• Enrollment (Estimated): 13

Contacts and Locations

• Study Contact: Name: Nehal I Shobair, PhD; Phone Number: +201063666985; Email: nehal.shobair@miuegypt.edu.eg
• Study Contact Backup: Name: Yassin S Alian, PhD; Phone Number: +201008161547; Email: Yassinalian@dent.asu.edu.eg

Study Locations

• Egypt
  • Abbassia
    • Cairo, Abbassia, Egypt, 11566
      • Recruiting
      • Ain Shams University
      • Contact: Yassin S Alian, PhD; Phone Number: +201008161547; Email: Yassinalian@dent.asu.edu.eg
      • Contact: Nehal Shobair, Lecturer; Phone Number: +201063666985; Email: nehal.shobair@miuegypt.edu.eg
      • Contact: Mohammed Diaa Zain El Abedeen, Professor
  • Cairo
    • Abbassia, Cairo, Egypt, 11566
      • Recruiting
      • Ain Shams University
      • Contact: Nehal I Shobair, Lecturer; Phone Number: +201063666985; Email: nehal.shobair@miuegypt.edu.eg
      • Contact: Mohamed Diaa Zain El Abedeen, Professor; Phone Number: 01006030255; Email: diaa67@yahoo.com
      • Contact: Amr Ghanem, Professor

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

Patients who suffered from class III facial deformity and had bimaxillary orthognathic surgical correction who undergone maxillary advancement and mandibular setbacks.

Description

Inclusion Criteria:

• Preoperative and at least 6 months postoperative CBCTs of Patients who suffered from class III facial deformity and had bimaxillary orthognathic surgical correction who undergone maxillary advancement and mandibular setbacks.

Exclusion Criteria:

• CBCTs of patients with:

  • Craniofacial anomalies including cleft lip/palate,
  • who had had previous maxillofacial operations or facial scars,
  • Surgical Corrections that required multi-segment Le Fort I osteotomies,
  • Simultaneous Genioplasty as part of the carried-out corrections.
  • Significant facial Asymmetry.
  • Missing Data

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort
Class III Patients treated with bimaxillary surgery; Preoperative and at least 6 months postoperative CBCTs of Patients who suffered from class III facial deformity and had bimaxillary orthognathic surgical correction who undergone maxillary advancement and mandibular setbacks.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Prediction accuracy	the accuracy of the software soft tissue simulation in response to bimaxillary surgery including maxillary advancement and mandibular setback will be measured comparing the stl if the actual patient soft tissue recorded at least 6 months postoperative versus the software prediction to the same surgical movement. the accuracy will be measured using facial conformation mesh for each esthetic unit. the outcome will be the mean of the linear discripance between the two stls for each facial esthetic region im millimeters.(mean discripancy for each esthetic unit in millimiters)	1 month

Collaborators and Investigators

• Sponsor: Ain Shams University
• Collaborators: Cairo University; Misr International University; University of Glasgow
• Investigators: Study Chair: Ashraf F Ayoub, Professor, Department of Oral and Maxillofacial Surgery, School of Medicine, Dentistry & Nursing, Glasgow Dental Hospital & School, Glasgow, United Kingdom.; Study Director: Mohammed Diaa Zain El Abedeen, Professor, Department of Oral and Maxillofacial Surgery, Faculty of Dentistry, Ain Shams University, Cairo, Egypt; Principal Investigator: Nehal I Shobair, Lecturer, Department of Oral and Maxillofacial Surgery, Faculty of Dentistry, Misr International University, Cairo, Egypt; Study Director: Xiangyang Ju, Head of Image Processing, Medical Devices Unit, NHS Greater Glasgow and Clyde, Glasgow, United Kingdom; Study Director: Amr A Ghanem, Professor, Department of Oral and Maxillofacial Surgery, Faculty of Dentistry, Ain Shams University, Cairo, Egypt; Study Director: Amr M Ekram, Consultant, Department of Oral and Maxillofacial Surgery, Faculty of Oral and Dental Medicine, Cairo University; Study Director: Ahmed Barakat, Professor, Department of Oral and Maxillofacial Surgery, Faculty of Oral and Dental Medicine, Cairo University

Study record dates

Study Major Dates

• Study Start (Actual): March 12, 2025
• Primary Completion (Estimated): April 15, 2025
• Study Completion (Estimated): May 1, 2025

Study Registration Dates

• First Submitted: March 18, 2025
• First Submitted That Met QC Criteria: March 23, 2025
• First Posted (Actual): March 25, 2025

Study Record Updates

• Last Update Posted (Actual): March 25, 2025
• Last Update Submitted That Met QC Criteria: March 23, 2025
• Last Verified: March 1, 2025

More Information

Terms related to this study

• Keywords: Cone-Beam Computed Tomography; Treatment Outcome; Orthognathic Surgery; Computer Simulation; Prognathism; Three-Dimensional Imaging.; Soft Tissue.
• Other Study ID Numbers: Nehal Esthetic units

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: Individual Participant Data (IPD) from this study will not be shared due to privacy and confidentiality concerns, as even de-identified data may pose a risk of re-identification. Additionally, ethical and regulatory restrictions may limit data sharing if participant consent was not explicitly obtained. Institutional policies and Intellectual Property (IP) considerations may also prevent public access to the data. Furthermore, logistical challenges related to data management, storage, and governance make widespread sharing unfeasible.

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No