Orthognathic surgery plays a vital role in correcting various skeletal discrepancies of the maxillofacial region. Achieving optimal occlusion is a fundamental aspect of orthognathic surgery planning, as it directly influences postoperative outcomes and patient satisfaction. Traditional methods for setting final occlusion involve the use of dental casts which are time-consuming, prone to errors and cannot be easily shared among collaborating specialties. In recent years, advancements in digital technology have introduced innovative approaches, such as virtual occlusion, which may offer enhanced accuracy and efficiency in orthognathic surgery planning. Furthermore, the emergence of mixed reality devices and their 3D visualization capabilities have brought about novel benefits in the medical field, particularly in computer-assisted planning. This paper presents for the first time a prototype tool for setting virtual occlusion during orthognathic surgery planning using mixed reality technology. A complete walkthrough of the workflow is presented including an explanation of the implicit advantages of this novel tool. The new approach to defining virtual occlusion is set into context with other published methods of virtual occlusion setting, discussing advantages and limitations as well as concepts of surgical occlusion for orthognathic surgery.

Background/Objectives: Surgical navigation has advanced maxillofacial surgery since the 1990s, bringing benefits for various indications. Traditional registration methods use fiducial markers that are either invasively bone-anchored or attached to a dental vacuum splint and offer high accuracy but necessitate additional imaging with increased radiation exposure. We propose a novel, non-invasive registration protocol using a CAD/CAM dental splint based on high-resolution intraoral scans. Methods: The effectiveness of this method was experimentally evaluated with an ex vivo 3D-printed skull measuring the target registration error (TRE). Surgical application is demonstrated in two clinical cases. Results: In the ex vivo model, the new CAD/CAM-splint-based method achieved a mean TRE across the whole facial skull of 0.97 ± 0.29 mm, which was comparable to traditional techniques like using bone-anchored screws (1.02 ± 0.23 mm) and dental vacuum splints (1.01 ± 0.33 mm), while dental anatomical landmarks showed a lower accuracy with a mean TRE of 1.84 ± 0.44 mm. Multifactorial ANOVA confirmed significant differences in TRE based on the registration method and the navigated level of the facial skull (p < 0.001). In clinical applications, the presented method demonstrated high accuracy for both midfacial and mandibular surgeries. Conclusions: Our results suggest that this non-invasive CAD/CAM-splint-based method is a viable alternative to traditional fiducial marker techniques, with the potential for broad application in maxillofacial surgery. This approach retains high accuracy while eliminating the need for supplementary imaging and reduces patient radiation exposure. Further clinical trials are necessary to confirm these findings and optimize splint design for enhanced navigational accuracy.

This technical note describes the usage of object matching to virtually compare different modes of reconstruction in orbital trauma and display the results to the surgeon and the patient pre-operatively via mixed reality devices for enhanced surgical decision making and immersive patient education. A case of an orbital floor fracture is presented for which surface and volume matching were implemented to compare orbital reconstruction utilizing pre-fabricated titanium meshes versus patient-specific implants. The results could be visualized by mixed reality devices to further enhance surgical decision-making. The data sets were demonstrated to the patient in mixed reality for immersive patient education and enhanced shared decision making. The advantages of the new technologies are discussed in view of the new possibilities of improved patient education and informed consent processes, as well as new ways of teaching medical trainees.

Oral Health-Related Quality of Life (OHRQoL) is an important aspect of quality of life. Acute illnesses, as well as chronic diseases, can have a strong, persisting impact on an individual’s quality of life. This study evaluates OHRQoL of patients with odontogenic fascial space abscesses, the underlying conditions, and its consequences for clinical routines. The research group consisted of patients presenting themselves to the emergency room or elective clinic of the Department for Cranio-Maxillofacial and Plastic Surgery (n = 94). The validated German version of the Oral Health Impact Profile (OHIP-G) and additional questions (including habits and routines in oral hygiene) with an anamnestic recall period of 1 month was used to evaluate OHRQoL shortly after emergency treatment (baseline) and again after 3–6 months’ follow-up. Ninety-four patients completed the questionnaire at baseline, 54 completed both questionnaires. Additionally, OHIP-G scores were compared to those of the non-impacted general German population. Results showed a significant difference in OHIP-G scores from baseline to follow-up (p = 0.001). Overall a mean of 55.24 (±37.02) points was scored at baseline and a mean of 37.02 (±35.79) points was scored at follow-up. Patients scored higher than participants of a representative study of the general German population. Overall results suggest an increase in OHRQoL 3–6 months after acute treatment. Nevertheless, OHRQoL of patients suffering from odontogenic fascial space abscesses seems to remain generally lower than the OHRQoL of the general German population. Trial registration: Central Study Register of the University Hospital Duesseldorf, Registration-ID: 2016085405 . Registered 24 August 2016.

Background/Objectives: Large language models (LLMs) show promise for clinical decision support, yet their accuracy in interpreting specialized medical guidelines remains uncertain. Retrieval-augmented generation (RAG) may enhance performance by grounding responses in authoritative knowledge bases. This study aimed to compare the accuracy, comprehensiveness, and safety of RAG-enhanced versus standard LLMs for answering clinical questions derived from the German S3 guideline for oral cavity carcinoma. Methods: We conducted a prospective, single-blind benchmark study evaluating six LLMs: one RAG-enhanced model (Custom GPT with guideline access), one consensus-based model (ConsensusGPT), and four standard models (DeepSeek-V3.2, Mistral Small 3.2, Qwen3-Next-80B, GPT-OSS-120B). Fifty clinical questions covering 17 guideline domains were presented to each model three times, yielding 900 evaluations. Three expert reviewers assessed responses using 5-point Likert scales for accuracy, comprehensiveness, and clarity, under a single-blind procedure, the effectiveness of which was tested by a pre-specified manipulation check. We then ran a paired within-model experiment in which each base model was queried with and without guideline access through a transparent, openly released retrieval pipeline, and scored every response with a condition-blind automated judge alongside deterministic retrieval metrics computed from the logs. Secondary outcomes included hallucination rates and guideline citation behavior. Inter-rater reliability was assessed using intraclass correlation coefficients (ICCs). Results: In a paired within-model design that held each base model fixed, adding transparent guideline retrieval improved accuracy—significantly in the three weaker open-weight models (Mistral, Qwen3, and GPT-OSS) and directionally in the already-strong DeepSeek and GPT-5 bases. Because a pre-specified blinding check found that experts could still identify retrieval-augmented answers with 98.5% accuracy, we anchored causal interpretation on measures that do not depend on the human raters, ranked by their independence: deterministic, log-derived retrieval metrics first, and then an automated, condition-blind LLM judge, whose agreement with the experts (Spearman ρ = 0.81, 95.7% within-one agreement) establishes shared calibration rather than independence from their bias. Deterministically from the retrieval logs, citation groundedness rose from 0% to 51–89% and retrieval recall@5 was 92%. On the judge, content-level hallucination fell from 42% to 4% and accuracy rose by a pooled +0.64 points (95% CI 0.47–0.80); the accuracy gain persisted after adjustment for response length (+0.48, 95% CI 0.22–0.73), which retrieval shortened rather than lengthened. The accuracy gain was large for weaker base models and small or non-significant for already-strong ones, whereas the hallucination and auditability gains were consistent across all models. The human ratings reproduced the judge’s accuracy effect (+0.61, 95% CI 0.49–0.74), and GPT-5 run through the transparent pipeline showed no significant difference from the proprietary Custom GPT (judge accuracy 4.48 vs. 4.58). Conclusions: Guideline retrieval yields a reproducible, largely base-independent improvement in the safety and auditability of LLM answers to clinical guideline questions, with accuracy gains concentrated in weaker base models. Because retrieval-augmented answers are recognizable to experts, rigorous evaluation should rely on rater-independent measures, and residual hallucination continues to require human oversight.

Objective: To quantify the gap between oral cancer disease burden and public awareness in Germany, and to characterize research dissemination patterns across social media platforms. Methods: We conducted a multi-dimensional analysis integrating: (1) Robert Koch Institut cancer registry data for oral and maxillofacial malignancies (ICD-10: C00–C06) from 2015 to 2023; (2) Google Trends search interest for cancer-related German terms; (3) Altmetric data for 2581 PubMed-indexed oral cancer publications; and (4) sentiment analysis of 10,308 social media posts. Age-standardized incidence rates were calculated using the European Standard Population. Results: Over the study period, 65,757 oral cavity cancer cases were registered. Google Trends analysis revealed a 64% attention deficit for “Mundkrebs” (oral cancer; mean: 17) compared to “Brustkrebs” (breast cancer; mean: 47). Case numbers declined from 7577 (2019) to 6870 (2023; −9.3%), while age-standardized rates decreased by 15.5% (11.6 to 9.8 per 100,000), with males disproportionately affected (−17.7%). Research dissemination was dominated by X/Twitter (86.2%), with minimal policy document (0.3%) or clinical guideline (0.3%) citations. Sentiment analysis revealed 77% positive public reception. Regional analysis identified an East–West divide, with Eastern German states showing 22% higher search interest. Conclusions: A substantial public awareness deficit exists for oral cancer in Germany, paradoxically widening during a period of declining diagnoses potentially associated with COVID-19-related diagnostic delays. The positive public sentiment toward oral cancer research suggests a favorable environment for targeted awareness campaigns, particularly in Western German states where search interest is lowest. These findings have practical implications for designing regionally tailored awareness campaigns prioritizing anatomically specific terminology. Future research should evaluate the effectiveness of such targeted interventions and assess whether post-pandemic diagnoses present at more advanced stages.