Bone defects within the cranio-orbital complex present unique challenges in terms of surgical planning and reconstruction. This article presents a novel approach using PEEK material and advanced surgical technologies to address these challenges. A retrospective analysis of 15 patients who underwent craniofacial reconstruction using patient-specific polyetheretherketone (PEEK) implants between 2016 and 2021 was carried out. Comprehensive preoperative planning was performed, utilizing advanced imaging techniques and specialized software for virtual surgical planning. Patient-specific PEEK PSIs were designed and manufactured based on the preoperative plan. Intraoperative navigation was used to guide the surgical procedure, enabling precise osteotomy and optimal implant placement. This article describes the step-by-step process and the tools utilized in each phase. The etiologies were as follows: meningioma in seven cases, benign lesions in five cases, malignant tumors in two cases, and trauma sequelae in one case. In all cases, 3D-printed PEEK implants were utilized to achieve precise reconstruction. No major complications were described. In one case, an implant replacement was needed with successful outcomes. Our study demonstrates the feasibility and effectiveness of using PEEK patient-specific implants for personalized craniofacial reconstruction. The combination of advanced imaging, virtual planning, and CAD-CAM technology contributes to improved surgical outcomes in terms of oncologic margin control, functional restoration, and aesthetic results.

Introduction: Oral squamous cell carcinoma (OSCC) is a frequent head and neck malignancy with high morbidity and mortality. Locoregional recurrence is the main determinant of long-term prognosis, yet reliable predictive models remain limited. This study aimed to identify clinicopathological predictors of recurrence and to develop a nomogram-based recurrence risk score (RRS) for patient stratification. Materials and Methods: A retrospective study was conducted including 332 patients with histologically confirmed OSCC treated surgically between 2012 and 2022. Clinical and pathological variables were analyzed. Statistical analyses included Chi-squared tests, Cox regression, Kaplan–Meier survival analysis, and multivariate modeling to construct a predictive nomogram and derive the RRS. Results: Close or involved surgical margins were observed in 33.4% of patients, and 66.9% presented moderately or poorly differentiated tumors. Locoregional recurrence occurred in 34.6% of cases, mainly within 24 months. Close margins and poor differentiation were independent predictors of recurrence (p < 0.005). The RRS effectively stratified patients into low-, intermediate-, and high-risk groups, with recurrence rates of 21.6%, 50.6%, and 82.1%, respectively (p < 0.001). Conclusions: The RRS is a practical tool for predicting OSCC recurrence and may support personalized follow-up and adjuvant treatment strategies. Prospective validation is warranted.