[Exploration and clinical application of the "digital and intelligent surgery" diagnosis and treatment workflow for oral and maxillofacial tumors].

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Abstract

Tumors in the oral and maxillofacial region present significant clinical challenges due to anatomical complexity and high individual variability, with the traditional experience-dependent model often lacking three-dimensional visualization, precise intraoperative navigation, and quantitative postoperative assessment. This article comprehensively reviews over a decade of research and clinical advances in "digital and intelligent surgery" developed by our team at Peking University School and Hospital of Stomatology, systematically documenting its transformative impact on tumor management. In digital surgery, we have established multimodal image fusion techniques integrating CT, MRI, and PET/CT to achieve detailed three-dimensional preoperative visualization, enabling accurate delineation of tumor boundaries and relationships with critical anatomical structures, such as nerves and vessels. We further developed personalized surgical planning methods including virtual design for jaw reconstruction using vascularized fibula or iliac crest flaps, computer-aided pre-forming of orbital titanium mesh, 3D-printed patient- specific plates manufactured via electron beam melting, soft-tissue flap simulation and volumetric planning for the anterolateral thigh flap, and implant-guided rehabilitation for complex maxillary defects. For surgical execution, navigation systems and mixed reality technologies have been implemented to enable accurate tumor resection, osteotomy guidance, and precise positioning of reconstructed bone segments, thereby enhancing surgical accuracy and safety while reducing operative time. In parallel, artificial intelligence has been integrated to enhance diagnostic and planning efficiency through deep learning-based tumor segmentation and classification from enhanced CT and MRI, automated reconstruction planning based on shape completion and morphometric descriptors, postoperative facial contour prediction using surface mesh deformation models, and machine learning-driven prognostic modeling for salivary gland malignancies based on clinicopathological data. The synergistic integration of these digital and intelligent technologies, collectively termed "digital and intelligent surgery", has shifted clinical practice from an experience-driven to a data-driven paradigm, significantly improving precision, safety, and efficiency while enabling truly personalized treatment pathways. This review also identifies current limitations such as the need for further automation in soft-tissue simulation and broader clinical validation of AI tools, and outlines future directions including the development of integrated surgical platforms and real-time adaptive planning systems, emphasizing the role of intelligent surgical systems in shaping the next generation of oral and maxillofacial oncology care toward more predictive, preventive, and patient-centered outcomes.

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