Search Results (7)

Facial reconstruction presents complex challenges due to the intricate nature of craniofacial anatomy and the necessity for individualized treatment. Conventional reconstructive methods—such as autologous bone grafts and prefabricated alloplastic implants—pose limitations, including donor site morbidity, implant rejection, and suboptimal aesthetic results. The emergence of 3D printing technology has introduced patient-specific implants (PSIs) that enhance anatomical fit, functional restoration, and biocompatibility. This review outlines the evolution of 3D-printed implants, key materials, computer-assisted design (CAD), and their applications across trauma, oncology, congenital conditions, and aesthetics. It also addresses current challenges and explores future directions, such as bioprinting, smart implants, and drug-eluting coatings. Full article

Preoperative facial markings are critical to surgical precision and aesthetic outcomes in plastic surgery, yet remain operator-dependent and variably documented. Generative artificial intelligence (AI), particularly large multimodal models, offers potential for the automated illustration of surgical plans. This study compares the performances of ChatGPT-4o and Gemini Advanced in generating standardised preoperative markings for aesthetic facial procedures. Methods: Six text prompts describing common facial aesthetic surgeries were developed using established marking protocols. Each prompt was submitted once to ChatGPT-4o and Gemini Advanced, yielding twelve illustrations. Three board-certified plastic surgeons independently evaluated the images using a five-domain Likert scale assessing incision clarity, anatomical accuracy, template conformity, clinical usefulness, and overall graphic quality. A composite score out of 25 was calculated. Data were analysed using paired t-tests, and interrater reliability was assessed with intraclass correlation coefficients. Results: ChatGPT-4o significantly outperformed Gemini Advanced in composite scores (mean 18.0 ± 1.4 vs. 13.9 ± 1.6, p = 0.001, Cohen’s d = 1.69). Superior performance was noted across all domains, particularly in clarity (mean difference 0.83, p = 0.002) and graphic quality (mean difference 0.90, p = 0.001). Interrater reliability was good (ICC = 0.82). Discussion: ChatGPT-4o demonstrated higher fidelity in translating surgical prompts into anatomically appropriate, clinically useful illustrations. However, neither system achieved the precision required for clinical implementation without revision. These models may serve as adjuncts in education and preliminary planning. Future work should explore model fine-tuning, surgeon-guided generation, and performance in reconstructive procedures. Full article

Background: Three-dimensional facial scan technologies, such as stereophotogrammetry, are frequently used in oral and maxillofacial surgery, dentistry, and plastic surgery to assess patient outcomes and plan surgical procedures. Most facial scanners rely on stationary clinical systems, which provide high accuracy and reliability in generating 3D representations of the human face; however, they are cost-intensive and immobile. Recently, smartphone-based facial scan applications that use stereophotogrammetry have been developed. These applications are cost-effective and more accessible than existing stationary systems. Methods: In this study, we compared the accuracy of three different smartphone applications—EM3D, Polycam, and ScandyPro—on an iPhone 14 Pro, which utilizes Apple’s LiDAR (Light Detection and Ranging) technology, to a stationary system by 3DMD, which is considered a gold standard in many studies. Results: The applications included in the study have demonstrated the capability to perform accurately in clinical settings, with mean surface distances of 1.46 mm for EM3D, 1.66 mm for Polycam, and 1.61 mm for ScandyPro. Conclusions: These results suggest that smartphone-based facial scan systems could be a viable alternative, particularly in resource-limited settings. However, further research and collaboration between academia and industry are necessary to fully integrate these technologies into clinical practice. Full article

Background: Orthognathic surgery is a multidisciplinary surgery in which the aesthetic results have become increasingly important, and consequently, also the predictability of the surgical outcomes. In this paper, we analyzed the volumetric distribution of the lower two-thirds of the face, in patients operated by orthognathic surgery and selected for their attractiveness. Our goal was to analyze the aesthetic volumetric distribution for gender and to propose our operating philosophy, that a normative distribution of facial volumes could be used like a new 3D aesthetic guide in orthognathic planning. Methods: A group of 46 orthognathic patients (26 females, 20 males) with the best postoperative aesthetic score was selected by a jury of plastic surgeons, orthodontists, and journalists. The mean soft tissue volumes of the malar, maxillary, mandibular, and chin regions were analyzed. Results: Overall, we measured a mean female facial volume distribution of 38.7%, 29%, 27.6%, and 4.7%, respectively, in the malar, maxillary, mandibular, and chin regions, while in males, it was 37%, 26%, 30%, and 6%, respectively. Conclusions: In this paper, the expansion of facial volumes in orthognathic surgery is proposed as a key point for facial harmonization. Beauty could be scientifically interpreted as a balanced distribution of facial volumes, and the virtual study of this distribution can become an important part of the preoperative analysis, such as a “volumetric” 3D cephalometry, where the surgeon could use average values of aesthetic volumetric distribution as preoperative surgical references. Full article

The 3D quantitative analysis of facial morphology is of importance in plastic surgery (PS), which could help surgeons design appropriate procedures before conducting the surgery. We propose a system to simulate and guide the shaping effect analysis, which could produce a similar but more harmonious face simulation. To this end, first, the depth camera based on structured light coding is employed for facial 3D data acquisition, from which the point cloud data of multiple facial perspectives could be obtained. Next, the cascade regression tree algorithm is used to extract the esthetic key points of the face model and to calculate the facial features composed of the key points, such as the nose, chin, and eyes. Quantitative facial esthetic indexes are offered to doctors to simulate PS. Afterward, we exploit a face mesh metamorphosis based on finite elements. We design several morphing operators, including augmentation, cutting, and lacerating. Finally, the regional deformation is detected, and the operation effect is quantitatively evaluated by registering the 3D scanning model before and after the operation. The test of our proposed system and the simulation of PS operations find that the measurement error of facial geometric features is 0.458 mm, and the area is 0.65 mm². The ratings of the simulation outcomes provided by panels of PS prove that the system is effective. The manipulated 3D faces are deemed more beautiful compared to the original faces respecting the beauty canons such as facial symmetry and the golden ratio. The proposed algorithm could generate realistic visual effects of PS simulation. It could thus assist the preoperative planning of facial PS. Full article

Plastic surgery is a broad field, including maxillofacial surgery, skin flaps and grafts, liposuction and body contouring, breast surgery, and facial cosmetic procedures. Due to the requirements of plastic surgery for the biological safety of materials, biomaterials are widely used because of its superior biocompatibility and biodegradability. Currently, there are many kinds of biomaterials clinically used in plastic surgery and their applications are diverse. Moreover, with the rise of three-dimensional printing technology in recent years, the macroscopically more precise and personalized bio-scaffolding materials with microporous structure have made good progress, which is thought to bring new development to biomaterials. Therefore, in this paper, we reviewed the plastic surgery biomaterials and current progress in their 3D manufacturing technology. Full article

The psychological and social impact of the lipodystrophy syndrome on HIV-infected individuals may be quite considerable and adversely affect their quality of life. Currently no validated assessment tool for facial lipoatrophy is available. The main objective of this paper is to evaluate the reliability of interactive anthropometric landmark localization based on digitized 3D facial images. By comparing both computed tomography (CT) and structured light scanning we try to demonstrate that surface scanning shows a higher sensitivity in measuring facial reference points. Besides, we evaluate the reproducibility of facial 3D white-light scans. Three HIVpositive men attending our plastic surgery outpatient clinic for treatment of facial lipodystrophy were enrolled in the study. Localization of anthropometric landmarks measurements was performed on the patients. All patients underwent a facial CT and a facial white-light scanning on the same day. The inter-landmark distances measured on facial models developed from CT aided with VirSSPA 3D software and structured light scanning were compared to the real human models. We found that facial distances measured in the CT 3D reconstruction showed a mean error margin of 0.357 cm from the real distances measured on patients. On the contrary, mean error margin with the white-light scanning was of 0.096 cm. In both cases, measurements were found to be statistically significant (p < 0.05). When compared to CT reconstructions, white-light surface scanning offers a more accurate landmark localization as well as reliable reconstructions of up to less than the tenth of a millimetre as average when compared to real measurements on facial human models. Full article