1. Plast Reconstr Surg. 2026 Jul 1;158(1):56-65. doi: 10.1097/PRS.0000000000012683. Epub 2025 Dec 4. 3-Dimensional Simulation for Breast Augmentation: Does the Software Actually Work? Lorange E(1), Bouhadana G(1), Oiknine N(1), Luc M(2), Borsuk DE(1). Author information: (1)From the Division of Plastic and Reconstructive Surgery, University of Montreal. (2)Division of Plastic and Reconstructive Surgery, McGill University. BACKGROUND: Recent advances in 3-dimensional (3D) imaging, such as the Vectra XT 3D imaging system (Vectra; Canfield Imaging Systems), have enabled simulations for breast augmentation. These simulations are popular and valuable in preoperative consultations, but no studies have evaluated the system's predictive volume accuracy with a large sample size or explored the patient-specific and surgical factors influencing these simulations. METHODS: A prospective cohort study was conducted on patients undergoing breast augmentation simulations with Vectra between January of 2021 and December of 2022. Predictive volumetric accuracy was analyzed with a ±10% precision threshold and Bland-Altman visualization. Linear breast measurements were compared using mean and median absolute error analysis, and a generalized linear model with generalized estimating equations was used to identify factors affecting volume prediction accuracy. RESULTS: The study included 78 patients (154 breasts). Accurate predictions (±10% error) were achieved in 73% of cases, with an average margin of error of 7.52%. The most accurate measurement was sternal-nipple ( P = 0.64) and the least accurate measurement was nipple-inframammary fold ( P = 0.001). Factors influencing prediction accuracy included pregnancy history, preoperative breast volume, and implant volume. CONCLUSIONS: Vectra accurately predicts postoperative breast volumes within a 10% margin of error, although precision decreases with larger breasts (greater than 650 cc). Patient-specific factors, such as pregnancy history and preoperative breast characteristics, should guide preoperative consultations. The system enhances patient education, shared decision-making, and participation in care, reinforcing its value in preoperative planning for breast augmentation. Copyright © 2025 by the American Society of Plastic Surgeons. DOI: 10.1097/PRS.0000000000012683 PMID: 41344311 [Indexed for MEDLINE] 2. Comput Biol Med. 2025 Aug;194:110529. doi: 10.1016/j.compbiomed.2025.110529. Epub 2025 Jun 11. Soft-tissue prediction based on 3D photographs for virtual surgery planning of orthognathic surgery. Berends B(1), Bielevelt F(2), Baan F(3), Schreurs R(4), Maal T(5), Xi T(6), de Jong G(7). Author information: (1)Radboudumc 3D Lab, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, the Netherlands. Electronic address: Bo.Berends@radboudumc.nl. (2)Radboudumc 3D Lab, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, the Netherlands. Electronic address: Freek.Bielevelt@radboudumc.nl. (3)Radboudumc 3D Lab, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, the Netherlands. Electronic address: Frank.Baan@radboudumc.nl. (4)Radboudumc 3D Lab, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, the Netherlands; Department of Oral and Maxillofacial Surgery, Amsterdam University Medical Center (UMC), AMC, Academic Center for Dentistry Amsterdam (ACTA), Meibergdreef 9, 1105 AZ, Amsterdam, the Netherlands. Electronic address: Ruud.Schreurs@radboudumc.nl. (5)Radboudumc 3D Lab, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, the Netherlands. Electronic address: Thomas.Maal@radboudumc.nl. (6)Department of Oral and Maxillofacial Surgery, Radboud University Medical Center Nijmegen, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, the Netherlands. Electronic address: Tong.Xi@radboudumc.nl. (7)Radboudumc 3D Lab, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, the Netherlands. Electronic address: Guido.deJong@radboudumc.nl. OBJECTIVES: In orthognathic surgery, preoperative three-dimensional soft-tissue simulations are frequently used to determine the desired jaw displacements to enhance the facial soft tissue. This study aimed to develop and validate a deep learning-based method to predict postoperative facial soft tissue outcomes in real time for various orthognathic procedures. METHODS: The study included 458 patients who underwent various orthognathic procedures. A deep learning-based method was developed based on 3D photographs for the real-time prediction of soft-tissue changes following orthognathic surgery. The developed method combined a morphable model, principal component analysis, and a feedforward neural network for predicting the effects of maxilla, mandible, and chin displacements on facial soft tissue. Prediction accuracy was evaluated by comparing the surface distance between predicted and actual postoperative soft tissues across facial regions. RESULTS: The trained network generated postoperative facial predictions within 0.02 s, achieving a mean accuracy of 1.17 ± 0.49 mm across all surgery types. Regional accuracy ranged from 0.55 ± 0.23 mm (nose) to 1.60 ± 0.96 mm (chin). CONCLUSION: This study demonstrated the potential of a deep learning-based approach for real-time prediction of facial soft-tissue changes following various orthognathic procedures, achieving clinically relevant accuracy comparable to existing deep learning-based methods. Copyright © 2025 The Authors. Published by Elsevier Ltd.. All rights reserved. DOI: 10.1016/j.compbiomed.2025.110529 PMID: 40505289 [Indexed for MEDLINE] Conflict of interest statement: Declaration of competing interest The authors declare no competing interests. 3. Plast Reconstr Surg Glob Open. 2026 Aug 5;14(8):e7999. doi: 10.1097/GOX.0000000000007999. eCollection 2026 Aug. Preoperative 3-dimensional Simulation in Aesthetic Surgery. Atiyeh BS(1), Issa OB(1), Daoud FJ(1), Baajour JA(1). Author information: (1)From the Faculty of Medicine, Division of Plastic and Reconstructive Surgery, American University of Beirut Medical Center, Beirut, Lebanon. BACKGROUND: Many patients cannot visualize the expected outcome of aesthetic interventions. Better than verbal descriptions and confusing diagrams, preoperative simulation of outcome displays complex ideas simply and improves surgeon-patient communication. Unfortunately, objective assessment of the factors that affect simulation accuracy is still lacking. Moreover, there is no real discussion about the ethical and legal implications of an eventual mismatch between preoperative simulation and the actual surgical outcome. This review aimed to summarize the current status of 3D simulation applications in aesthetic surgery. METHODS: A systematic literature search was conducted to identify clinical studies related to aesthetic surgery, measuring and reporting the accuracy of preoperative simulation compared with the achieved outcome. RESULTS: Seventeen studies (12 on breast augmentation and 5 on rhinoplasty) were identified and included for review. No studies about other aesthetic procedures were identified. Simulation accuracy varied for rhinoplasty. Although high accuracy has been reported in various 3D breast augmentation simulation software programs, dissatisfaction with the accuracy of preoperative simulation information is not negligible. Relying solely on simulation may lead to inaccuracies. CONCLUSIONS: Undoubtedly, 3D simulation has been a significant step forward in aesthetic surgery. Originally introduced to enhance patient consultations, it is now becoming a strategic tool in planning and refining surgical interventions. The possible mismatch between simulation and outcome must be well recognized. Despite its numerous advantages, if misused, the technology can be counterproductive for both patient and surgeon. Making patients aware that simulations may not represent the final surgical outcome is essential. Copyright © 2026 The Authors. Published by Wolters Kluwer Health, LLC. on behalf of The American Society of Plastic Surgeons. DOI: 10.1097/GOX.0000000000007999 PMCID: PMC13441132 PMID: 42559587 Conflict of interest statement: The authors have no financial interest to declare in relation to the content of this article. 4. J Craniofac Surg. 2026 Jul 29. doi: 10.1097/SCS.0000000000013213. Online ahead of print. Three-Dimensional Digital Planning and Long-Term Outcome Analysis in Aesthetic Rhinoplasty. Horoz U(1), Sariguney Y(2). Author information: (1)Departments of Reconstructive and Aesthetic Surgery Clinic, Private Plastic, 34421, Istanbul. (2)Plastic, Reconstructive, and Aesthetic Surgery, Sanko University, Gaziantep, Turkey. BACKGROUND: Preoperative digital imaging and simulation technologies have become increasingly important in aesthetic rhinoplasty for improving surgical planning, surgeon-patient communication, and patient expectation management. However, data evaluating the relationship between preoperative simulation and long-term postoperative outcomes remain limited. METHODS: This retrospective study included 198 patients who underwent aesthetic rhinoplasty. The study population consisted of 138 female and 60 male patients with a mean age of 28 years. All patients underwent preoperative 2-dimensional (2D) photographic analysis and 3-dimensional (3D) digital simulation before surgery. Long-term postoperative outcomes, revision rates, postoperative discrepancies between preoperative planning and actual outcomes, and patient satisfaction were evaluated over a 3-year follow-up period. The study was conducted in accordance with ethical standards, and written informed consent was obtained from all participants. RESULTS: The overall revision rate was 12.6% (25/198 patients). Revision rhinoplasty was performed in 11 patients (44%) for inadequate dorsal contour depth, in 8 patients (32%) for tip ptosis, and in 6 patients (24%) for intermittent functional breathing problems associated with septal deviation. Most postoperative dorsal contour discrepancies remained within clinically acceptable limits. Eleven patients demonstrated a ∼1 mm discrepancy, 10 patients a ∼1.5 mm discrepancy, 5 patients a ∼2m m discrepancy, and 3 patients a ∼3 mm discrepancy between preoperative simulation and postoperative outcomes without requiring revision surgery. Preoperative 3D simulation improved visualization of surgical goals and facilitated patient understanding of postoperative expectations. CONCLUSIONS: Preoperative 2D and 3D digital imaging and simulation techniques represent valuable adjuncts in modern rhinoplasty practice. These technologies improve patient communication, facilitate expectation management, and may contribute to greater long-term postoperative satisfaction by improving consistency between preoperative planning and actual surgical outcomes. Copyright © 2026 by Mutaz B. Habal, MD. DOI: 10.1097/SCS.0000000000013213 PMID: 42522961 Conflict of interest statement: The authors report no conflicts of interest. 5. Comput Assist Surg (Abingdon). 2026 Dec;31(1):2614532. doi: 10.1080/24699322.2026.2614532. Epub 2026 Jan 10. The impact of three-dimensional simulation and virtual reality technologies on surgical decision-making and postoperative satisfaction in aesthetic surgery: a preliminary study. Ersan M(1), Demirbaşoğlu H(2), Kolcu B(3), Yıldız HA(1). Author information: (1)Department of Plastic, Reconstructive and Aesthetic Surgery, Yeditepe University Faculty of Medicine, Istanbul, Türkiye. (2)Department of Plastic, Reconstructive and Aesthetic Surgery, Van Training and Research Hospital, University of Health Sciences, Van, Türkiye. (3)Department of Plastic, Reconstructive and Aesthetic Surgery, Şanlıurfa Mehmet Akif İnan Training and Research Hospital, University of Health Sciences, Şanlıurfa, Türkiye. BACKGROUND: Three-dimensional (3D) simulation and virtual reality (VR) technologies are increasingly used in aesthetic surgery consultations to enhance decision-making and expectation management. However, their impact on surgical decision-making and postoperative satisfaction across different procedures remains unclear. OBJECTIVES: This study aimed to evaluate the influence of 3D simulation and VR technology in patients undergoing rhinoplasty, breast augmentation, mastopexy, augmentation-mastopexy and breast reduction. METHODS: A retrospective study was conducted with 75 female patients who underwent primary aesthetic surgery. Preoperative 3D simulations and VR visualizations were generated using the Crisalix Virtual Esthetics system (Crisalix S.A., Switzerland). Patients were assessed postoperatively at one year using structured surveys to evaluate the influence of 3D simulation and VR technology on their decision-making and satisfaction. Statistical analyses included the Kruskal-Wallis H test, the Chi-Square test, and Spearman's correlation. RESULTS: 3D simulation had the greatest influence on breast augmentation (8.4/10), rhinoplasty (7.6/10), and augmentation-mastopexy (7.1/10) patients but was less impactful for mastopexy (6.6/10) and breast reduction (3.8/10) patients (p < 0.001). The most decisive factors were previous patient photos (30.7%) and communication with the surgeon (29.3%), with simulation ranking third (18.7%). Postoperative similarity ratings were highest in breast augmentation (7.9/10) and rhinoplasty (7.5/10) patients. While 70.7% of patients would recommend 3D simulation, VR headset use did not influence decisions (p < 0.001). CONCLUSIONS: 3D simulation enhances patient engagement and expectation management across various aesthetic procedures. While its influence is more significant in surgeries primarily focused on aesthetic outcomes, it serves as a complementary tool rather than a definitive factor in decision-making. DOI: 10.1080/24699322.2026.2614532 PMID: 41518093 [Indexed for MEDLINE]