Artificial Intelligence and 3D Reconstruction in Complex Hepato-Pancreato-Biliary (HPB) Surgery: A Comprehensive Review of the Literature

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Background: The management of complex hepato-pancreato-biliary (HPB) pathologies demands exceptional surgical precision. Traditional two-dimensional imaging has limitations in depicting intricate anatomical relationships, potentially complicating preoperative planning. This review explores the synergistic application of three-dimensional (3D) reconstruction and artificial intelligence (AI) to enhance surgical management in complex HPB cases. Methods: This narrative review comprehensively synthesized the existing literature on the applications, benefits, and limitations of 3D reconstruction and AI technologies in the context of HPB surgery. Results: The literature demonstrates that 3D reconstruction provides patient-specific, interactive models that significantly improve surgeons' understanding of tumor resectability and vascular anatomy, contributing to reduced operative time and blood loss. Building upon this, AI algorithms automate image segmentation for 3D modeling, enhance diagnostic accuracy, and offer predictive analytics for postoperative complications, such as liver failure. By analyzing large datasets, AI can identify subtle risk factors to guide clinical decision-making. Conclusion: The convergence of 3D visualization and AI-driven analytics is creating a paradigm shift in HPB surgery. This powerful combination is fostering a move toward a more personalized, precise, and data-informed surgical approach, with the potential to optimize outcomes for the most challenging patient cohorts.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.