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"Face-Surgery"
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Utilization of facial fat grafting augmented reality guidance system in facial soft tissue defect reconstruction
Background
Successfully restoring facial contours continues to pose a significant challenge for surgeons. This study aims to utilize head-mounted display-based augmented reality (AR) navigation technology for facial soft tissue defect reconstruction and to evaluate its accuracy and effectiveness, exploring its feasibility in craniofacial surgery.
Methods
Hololens 2 was utilized to construct the AR guidance system for facial fat grafting. Twenty artificial cases with facial soft tissue defects were randomly assigned to Group A and Group B, undergoing filling surgeries with the AR guidance system and conventional methods, respectively. All postoperative three-dimensional models were superimposed onto virtual plans to evaluate the accuracy of the system versus conventional filling methods. Additionally, procedure completion time was recorded to assess system efficiency relative to conventional methods.
Results
The error in facial soft tissue defect reconstruction assisted by the system in Group A was 2.09 ± 0.56 mm, significantly lower than the 3.23 ± 1.15 mm observed with conventional methods in Group B (
p
< 0.05). Additionally, the time required for facial defect filling reconstruction using the system in Group A was 25.45 ± 2.58 min, markedly shorter than the 37.05 ± 3.34 min needed with conventional methods in Group B (
p
< 0.05).
Conclusion
The visual navigation offered by the fat grafting AR guidance system presents obvious advantages in facial soft tissue defect reconstruction, facilitating enhanced precision and efficiency in these filling procedures.
Journal Article
Volume Retention After Facial Fat Grafting and Relevant Factors: A Systematic Review and Meta-analysis
BackgroundAutologous fat grafting is common in facial reconstructive and cosmetic surgeries; the most important drawbacks are the high absorption rate and unpredictable volume retention rate. Surgeons usually make clinical judgements based on their own experience. Therefore, this study aimed to systematically and quantitatively review the volume retention rate of facial autologous fat grafting and analyse the relevant influencing factors.MethodsA systematic literature review was performed using the Medline, EMBASE, Cochrane Library, and Web of Science databases in October 2019 for articles that reported objectively measured volume retention rates of facial fat grafting. Patient characteristics, fat graft volumetric data, and complications were collected. A meta-analysis using a random-effects model was conducted to pool the estimated fat retention rate. Relevant factors were analysed and reviewed on the basis of subgroups.ResultsWe included 27 studies involving 1011 patients with facial fat grafting. The volume retention rate varied from 26 to 83%, with a mean follow-up of 3–24 months. The overall pooled retention rate was 47% (95% CI 41–53%). The volume measurement method significantly influenced the reported retention rate. A trend towards better retention was found for secondary fat grafting procedures and patients with congenital deformities. Only 2.8% of all patients had complications.ConclusionThe exact percentage of facial fat grafts retained is currently unpredictable; the reported rate varies with different estimation methods. This review analysed studies that provided objectively measured volume retention rates, the pooled average percentage of facial fat graft retention (47%, 95% CI 41–53%), and relevant factors.Level of Evidence IIIThis journal requires that authors assign a level of evidence to each article. For a full description of these evidence-based medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266.
Journal Article
Advances in Bioprinting Technologies for Craniofacial Reconstruction
Recent developments in craniofacial reconstruction have shown important advances in both the materials and methods used. While autogenous tissue is still considered to be the gold standard for these reconstructions, the harvesting procedure remains tedious and in many cases causes significant donor site morbidity. These limitations have subsequently led to the development of less invasive techniques such as 3D bioprinting that could offer possibilities to manufacture patient-tailored bioactive tissue constructs for craniofacial reconstruction. Here, we discuss the current technological and (pre)clinical advances of 3D bioprinting for use in craniofacial reconstruction and highlight the challenges that need to be addressed in the coming years.
Conventional craniofacial reconstruction methods still fail to mimic the complex 3D anatomy and biology of native tissues.
Bioprinting can aid in the production of cell-incorporated and patient-tailored bioactive scaffolds that can be used for craniofacial reconstruction.
Currently, there are three different bioprinting technologies (laser-assisted, inkjet, and extrusion-based) used to print craniofacial tissues.
Bioprinting technologies will soon be used to enhance the self-repair capabilities of tissues in the craniofacial area.
Journal Article
Comparison of the Accuracy of Voxel Based Registration and Surface Based Registration for 3D Assessment of Surgical Change following Orthognathic Surgery
Superimposition of two dimensional preoperative and postoperative facial images, including radiographs and photographs, are used to evaluate the surgical changes after orthognathic surgery. Recently, three dimensional (3D) imaging has been introduced allowing more accurate analysis of surgical changes. Surface based registration and voxel based registration are commonly used methods for 3D superimposition. The aim of this study was to evaluate and compare the accuracy of the two methods.
Pre-operative and 6 months post-operative cone beam CT scan (CBCT) images of 31 patients were randomly selected from the orthognathic patient database at the Dental Hospital and School, University of Glasgow, UK. Voxel based registration was performed on the DICOM images (Digital Imaging Communication in Medicine) using Maxilim software (Medicim-Medical Image Computing, Belgium). Surface based registration was performed on the soft and hard tissue 3D models using VRMesh (VirtualGrid, Bellevue City, WA). The accuracy of the superimposition was evaluated by measuring the mean value of the absolute distance between the two 3D image surfaces. The results were statistically analysed using a paired Student t-test, ANOVA with post-hoc Duncan test, a one sample t-test and Pearson correlation coefficient test.
The results showed no significant statistical difference between the two superimposition methods (p<0.05). However surface based registration showed a high variability in the mean distances between the corresponding surfaces compared to voxel based registration, especially for soft tissue. Within each method there was a significant difference between superimposition of the soft and hard tissue models.
There were no significant statistical differences between the two registration methods and it was unlikely to have any clinical significance. Voxel based registration was associated with less variability. Registering on the soft tissue in isolation from the hard tissue may not be a true reflection of the surgical change.
Journal Article