3D Facial Scanning for Evaluating Autologous Fat Grafting in Craniofacial Deformities
Application of Three-dimensional Facial Scanning Images in Evaluating the Therapeutic Efficacy of Autologous Fat Grafting in the Treatment of Craniofacial Deformities
Peking University
100 participants
Apr 27, 2024
INTERVENTIONAL
Conditions
Summary
Treatment of craniofacial deformities is a significant topic in oral and maxillofacial surgery, and autologous fat grafting has become one of the main methods for treating facial concave deformities. However, the instability of its treatment effect has always been a bottleneck in this field, mainly due to the uncertain absorption rate of transplanted fat. This project aims to use advanced the 3dMD face system (3dMD) (3dMD Inc, Atlanta, Ga) technology to precisely measure the facial volume changes before and after autologous fat grafting to address this issue. By performing autologous fat grafting surgery on 100 patients with craniofacial deformities that meet the research criteria, 3dMD technology will be used for facial three-dimensional scanning preoperatively, immediately postoperatively, and at six months postoperatively to obtain facial volume data. Then, through precise data analysis, we will calculate the fat absorption rate and study the effects of individual factors on treatment outcomes through correlation regression analysis.
Eligibility
Inclusion Criteria4
- Facial soft tissue volume deficiency deformity caused by congenital/acquired factors, meeting the indications for autologous fat grafting surgery.
- Good physical health, without severe systemic diseases or infectious diseases.
- Not pregnant and without plans for pregnancy.
- Signed informed consent form.
Exclusion Criteria3
- Contraindications to general anesthesia.
- Patient refusal to participate in this study.
- Significant contour changes in non-filled facial areas during follow-up period leading to inability to register data.
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Interventions
By taking photos using 3dMD, we obtained preoperative, immediate postoperative, and long-term postoperative three-dimensional data of patients. The software automatically fused the data to obtain the volume difference of facial volume at different time points, and then divided it to obtain the objective data of facial volume improvement rate. To improve the reliability of the measurements, two researchers measured independently and took the average value.
Locations(1)
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NCT06306326